I: pbuilder: network access will be disabled during build I: Current time: Tue May 6 10:14:33 +14 2025 I: pbuilder-time-stamp: 1746476073 I: Building the build Environment I: extracting base tarball [/var/cache/pbuilder/trixie-reproducible-base.tgz] I: copying local configuration W: --override-config is not set; not updating apt.conf Read the manpage for details. I: mounting /proc filesystem I: mounting /sys filesystem I: creating /{dev,run}/shm I: mounting /dev/pts filesystem I: redirecting /dev/ptmx to /dev/pts/ptmx I: policy-rc.d already exists I: using eatmydata during job I: Copying source file I: copying [octave-statistics_1.6.5-3.dsc] I: copying [./octave-statistics_1.6.5.orig.tar.gz] I: copying [./octave-statistics_1.6.5-3.debian.tar.xz] I: Extracting source gpgv: Signature made Fri Mar 22 11:43:10 2024 gpgv: using RSA key 3F464391498FE874BDB5D98F2124AA1983785C90 gpgv: issuer "rafael@debian.org" gpgv: Can't check signature: No public key dpkg-source: warning: cannot verify inline signature for ./octave-statistics_1.6.5-3.dsc: no acceptable signature found dpkg-source: info: extracting octave-statistics in octave-statistics-1.6.5 dpkg-source: info: unpacking octave-statistics_1.6.5.orig.tar.gz dpkg-source: info: unpacking octave-statistics_1.6.5-3.debian.tar.xz dpkg-source: info: using patch list from debian/patches/series dpkg-source: info: applying glmfit-reproducible-bist.patch dpkg-source: info: applying binomial-dist-median.patch dpkg-source: info: applying fpdf-reproducile-bist.patch I: Not using root during the build. I: Installing the build-deps I: user script /srv/workspace/pbuilder/29027/tmp/hooks/D01_modify_environment starting debug: Running on ionos16-i386. I: Changing host+domainname to test build reproducibility I: Adding a custom variable just for the fun of it... I: Changing /bin/sh to bash '/bin/sh' -> '/bin/bash' lrwxrwxrwx 1 root root 9 May 5 20:14 /bin/sh -> /bin/bash I: Setting pbuilder2's login shell to /bin/bash I: Setting pbuilder2's GECOS to second user,second room,second work-phone,second home-phone,second other I: user script /srv/workspace/pbuilder/29027/tmp/hooks/D01_modify_environment finished I: user script /srv/workspace/pbuilder/29027/tmp/hooks/D02_print_environment starting I: set BASH=/bin/sh BASHOPTS=checkwinsize:cmdhist:complete_fullquote:extquote:force_fignore:globasciiranges:globskipdots:hostcomplete:interactive_comments:patsub_replacement:progcomp:promptvars:sourcepath BASH_ALIASES=() BASH_ARGC=() BASH_ARGV=() BASH_CMDS=() BASH_LINENO=([0]="12" [1]="0") BASH_LOADABLES_PATH=/usr/local/lib/bash:/usr/lib/bash:/opt/local/lib/bash:/usr/pkg/lib/bash:/opt/pkg/lib/bash:. BASH_SOURCE=([0]="/tmp/hooks/D02_print_environment" [1]="/tmp/hooks/D02_print_environment") BASH_VERSINFO=([0]="5" [1]="2" [2]="21" [3]="1" [4]="release" [5]="i686-pc-linux-gnu") BASH_VERSION='5.2.21(1)-release' BUILDDIR=/build/reproducible-path BUILDUSERGECOS='second user,second room,second work-phone,second home-phone,second other' BUILDUSERNAME=pbuilder2 BUILD_ARCH=i386 DEBIAN_FRONTEND=noninteractive DEB_BUILD_OPTIONS='buildinfo=+all reproducible=+all parallel=21 ' DIRSTACK=() DISTRIBUTION=trixie EUID=0 FUNCNAME=([0]="Echo" [1]="main") GROUPS=() HOME=/root HOSTNAME=i-capture-the-hostname HOSTTYPE=i686 HOST_ARCH=i386 IFS=' ' INVOCATION_ID=546cc2fe1750417dab2eec67615914de LANG=C LANGUAGE=de_CH:de LC_ALL=C LD_LIBRARY_PATH=/usr/lib/libeatmydata LD_PRELOAD=libeatmydata.so MACHTYPE=i686-pc-linux-gnu MAIL=/var/mail/root OPTERR=1 OPTIND=1 OSTYPE=linux-gnu PATH=/usr/sbin:/usr/bin:/sbin:/bin:/usr/games:/i/capture/the/path PBCURRENTCOMMANDLINEOPERATION=build PBUILDER_OPERATION=build PBUILDER_PKGDATADIR=/usr/share/pbuilder PBUILDER_PKGLIBDIR=/usr/lib/pbuilder PBUILDER_SYSCONFDIR=/etc PIPESTATUS=([0]="0") POSIXLY_CORRECT=y PPID=29027 PS4='+ ' PWD=/ SHELL=/bin/bash SHELLOPTS=braceexpand:errexit:hashall:interactive-comments:posix SHLVL=3 SUDO_COMMAND='/usr/bin/timeout -k 24.1h 24h /usr/bin/ionice -c 3 /usr/bin/nice -n 11 /usr/bin/unshare --uts -- /usr/sbin/pbuilder --build --configfile /srv/reproducible-results/rbuild-debian/r-b-build.IMSRmJcH/pbuilderrc_hBL6 --distribution trixie --hookdir /etc/pbuilder/rebuild-hooks --debbuildopts -b --basetgz /var/cache/pbuilder/trixie-reproducible-base.tgz --buildresult /srv/reproducible-results/rbuild-debian/r-b-build.IMSRmJcH/b2 --logfile b2/build.log octave-statistics_1.6.5-3.dsc' SUDO_GID=112 SUDO_UID=107 SUDO_USER=jenkins TERM=unknown TZ=/usr/share/zoneinfo/Etc/GMT-14 UID=0 USER=root _='I: set' http_proxy=http://85.184.249.68:3128 I: uname -a Linux i-capture-the-hostname 6.1.0-18-amd64 #1 SMP PREEMPT_DYNAMIC Debian 6.1.76-1 (2024-02-01) x86_64 GNU/Linux I: ls -l /bin lrwxrwxrwx 1 root root 7 Apr 29 17:46 /bin -> usr/bin I: user script /srv/workspace/pbuilder/29027/tmp/hooks/D02_print_environment finished -> Attempting to satisfy build-dependencies -> Creating pbuilder-satisfydepends-dummy package Package: pbuilder-satisfydepends-dummy Version: 0.invalid.0 Architecture: i386 Maintainer: Debian Pbuilder Team Description: Dummy package to satisfy dependencies with aptitude - created by pbuilder This package was created automatically by pbuilder to satisfy the build-dependencies of the package being currently built. Depends: debhelper-compat (= 13), dh-octave (>= 1.2.3), dh-sequence-octave, octave, octave-io, python3 Conflicts: octave-nan dpkg-deb: building package 'pbuilder-satisfydepends-dummy' in '/tmp/satisfydepends-aptitude/pbuilder-satisfydepends-dummy.deb'. Selecting previously unselected package pbuilder-satisfydepends-dummy. (Reading database ... 19876 files and directories currently installed.) Preparing to unpack .../pbuilder-satisfydepends-dummy.deb ... Unpacking pbuilder-satisfydepends-dummy (0.invalid.0) ... dpkg: pbuilder-satisfydepends-dummy: dependency problems, but configuring anyway as you requested: pbuilder-satisfydepends-dummy depends on debhelper-compat (= 13); however: Package debhelper-compat is not installed. pbuilder-satisfydepends-dummy depends on dh-octave (>= 1.2.3); however: Package dh-octave is not installed. pbuilder-satisfydepends-dummy depends on dh-sequence-octave; however: Package dh-sequence-octave is not installed. pbuilder-satisfydepends-dummy depends on octave; however: Package octave is not installed. pbuilder-satisfydepends-dummy depends on octave-io; however: Package octave-io is not installed. pbuilder-satisfydepends-dummy depends on python3; however: Package python3 is not installed. Setting up pbuilder-satisfydepends-dummy (0.invalid.0) ... Reading package lists... Building dependency tree... Reading state information... Initializing package states... Writing extended state information... Building tag database... pbuilder-satisfydepends-dummy is already installed at the requested version (0.invalid.0) pbuilder-satisfydepends-dummy is already installed at the requested version (0.invalid.0) The following NEW packages will be installed: aglfn{a} autoconf{a} automake{a} autopoint{a} autotools-dev{a} bsdextrautils{a} ca-certificates{a} cme{a} debhelper{a} dh-autoreconf{a} dh-octave{a} dh-octave-autopkgtest{a} dh-strip-nondeterminism{a} diffstat{a} dwz{a} file{a} fontconfig{a} fontconfig-config{a} fonts-dejavu-core{a} fonts-dejavu-mono{a} fonts-freefont-otf{a} gettext{a} gettext-base{a} gfortran{a} gfortran-13{a} gfortran-13-i686-linux-gnu{a} gfortran-i686-linux-gnu{a} gnuplot-data{a} gnuplot-nox{a} gpg{a} gpgconf{a} groff-base{a} hdf5-helpers{a} intltool-debian{a} iso-codes{a} libabsl20220623{a} libaec-dev{a} libaec0{a} libalgorithm-c3-perl{a} libaliased-perl{a} libamd3{a} libaom3{a} libapp-cmd-perl{a} libapt-pkg-perl{a} libarchive-zip-perl{a} libarpack2{a} libarray-intspan-perl{a} libasound2{a} libasound2-data{a} libassuan0{a} libavahi-client3{a} libavahi-common-data{a} libavahi-common3{a} libavif16{a} libb-hooks-endofscope-perl{a} libb-hooks-op-check-perl{a} libberkeleydb-perl{a} libblas-dev{a} libblas3{a} libboolean-perl{a} libbrotli1{a} libbsd0{a} libbtf2{a} libcairo2{a} libcamd3{a} libcapture-tiny-perl{a} libcarp-assert-more-perl{a} libcbor0.10{a} libccolamd3{a} libcgi-pm-perl{a} libcholmod5{a} libclass-c3-perl{a} libclass-data-inheritable-perl{a} libclass-load-perl{a} libclass-method-modifiers-perl{a} libclass-xsaccessor-perl{a} libclone-choose-perl{a} libclone-perl{a} libcolamd3{a} libcombblas2.0.0{a} libconfig-model-backend-yaml-perl{a} libconfig-model-dpkg-perl{a} libconfig-model-perl{a} libconfig-tiny-perl{a} libconst-fast-perl{a} libconvert-binhex-perl{a} libcpanel-json-xs-perl{a} libcups2{a} libcurl3-gnutls{a} libcurl4{a} libcurl4-openssl-dev{a} libcxsparse4{a} libdata-dpath-perl{a} libdata-messagepack-perl{a} libdata-optlist-perl{a} libdata-section-perl{a} libdata-validate-domain-perl{a} libdata-validate-ip-perl{a} libdata-validate-uri-perl{a} libdatrie1{a} libdav1d7{a} libdbus-1-3{a} libde265-0{a} libdebhelper-perl{a} libdeflate0{a} libdevel-callchecker-perl{a} libdevel-size-perl{a} libdevel-stacktrace-perl{a} libdouble-conversion3{a} libdrm-amdgpu1{a} libdrm-common{a} libdrm-intel1{a} libdrm-nouveau2{a} libdrm-radeon1{a} libdrm2{a} libdynaloader-functions-perl{a} libedit2{a} libegl-mesa0{a} libegl1{a} libelf1{a} libemail-address-xs-perl{a} libencode-locale-perl{a} liberror-perl{a} libevdev2{a} libevent-core-2.1-7{a} libevent-pthreads-2.1-7{a} libexception-class-perl{a} libexpat1{a} libexporter-lite-perl{a} libexporter-tiny-perl{a} libfabric1{a} libfeature-compat-class-perl{a} libfeature-compat-try-perl{a} libfftw3-bin{a} libfftw3-dev{a} libfftw3-double3{a} libfftw3-long3{a} libfftw3-mpi3{a} libfftw3-quad3{a} libfftw3-single3{a} libfido2-1{a} libfile-basedir-perl{a} libfile-find-rule-perl{a} libfile-homedir-perl{a} libfile-listing-perl{a} libfile-stripnondeterminism-perl{a} libfile-which-perl{a} libflac12{a} libfltk-gl1.3{a} libfltk1.3{a} libfont-ttf-perl{a} libfontconfig1{a} libfreetype6{a} libfribidi0{a} libgav1-1{a} libgbm1{a} libgd3{a} libgetopt-long-descriptive-perl{a} libgfortran-13-dev{a} libgfortran5{a} libgl-dev{a} libgl1{a} libgl1-mesa-dri{a} libgl2ps1.4{a} libglapi-mesa{a} libglib2.0-0{a} libglpk40{a} libglu1-mesa{a} libglvnd0{a} libglx-dev{a} libglx-mesa0{a} libglx0{a} libgraphicsmagick++-q16-12{a} libgraphicsmagick-q16-3{a} libgraphite2-3{a} libgudev-1.0-0{a} libharfbuzz0b{a} libhash-merge-perl{a} libhdf5-103-1{a} libhdf5-cpp-103-1{a} libhdf5-dev{a} libhdf5-fortran-102{a} libhdf5-hl-100{a} libhdf5-hl-cpp-100{a} libhdf5-hl-fortran-100{a} libhdf5-openmpi-103-1{a} libheif-plugin-dav1d{a} libheif-plugin-libde265{a} libheif1{a} libhtml-form-perl{a} libhtml-html5-entities-perl{a} libhtml-parser-perl{a} libhtml-tagset-perl{a} libhtml-tokeparser-simple-perl{a} libhtml-tree-perl{a} libhttp-cookies-perl{a} libhttp-date-perl{a} libhttp-message-perl{a} libhttp-negotiate-perl{a} libhwloc-plugins{a} libhwloc15{a} libhwy1{a} libhypre-2.28.0{a} libibverbs1{a} libice6{a} libicu72{a} libimport-into-perl{a} libindirect-perl{a} libinput-bin{a} libinput10{a} libio-html-perl{a} libio-interactive-perl{a} libio-socket-ssl-perl{a} libio-string-perl{a} libio-stringy-perl{a} libio-tiecombine-perl{a} libipc-run3-perl{a} libipc-system-simple-perl{a} libiterator-perl{a} libiterator-util-perl{a} libjack-jackd2-0{a} libjbig0{a} libjpeg-dev{a} libjpeg62-turbo{a} libjpeg62-turbo-dev{a} libjson-maybexs-perl{a} libjson-perl{a} libjxl0.7{a} libklu2{a} liblapack-dev{a} liblapack3{a} liblcms2-2{a} libldap-2.5-0{a} liblerc4{a} liblist-compare-perl{a} liblist-moreutils-perl{a} liblist-moreutils-xs-perl{a} liblist-someutils-perl{a} liblist-utilsby-perl{a} libllvm17{a} liblog-any-adapter-screen-perl{a} liblog-any-perl{a} liblog-log4perl-perl{a} libltdl7{a} liblua5.4-0{a} liblwp-mediatypes-perl{a} liblwp-protocol-https-perl{a} liblz1{a} liblzo2-2{a} libmagic-mgc{a} libmagic1{a} libmailtools-perl{a} libmarkdown2{a} libmd4c0{a} libmetis5{a} libmime-tools-perl{a} libmldbm-perl{a} libmodule-implementation-perl{a} libmodule-pluggable-perl{a} libmodule-runtime-perl{a} libmoo-perl{a} libmoox-aliases-perl{a} libmouse-perl{a} libmousex-nativetraits-perl{a} libmousex-strictconstructor-perl{a} libmp3lame0{a} libmpg123-0{a} libmro-compat-perl{a} libmtdev1{a} libmumps-5.6{a} libmunge2{a} libnamespace-clean-perl{a} libncurses-dev{a} libncurses6{a} libnet-domain-tld-perl{a} libnet-http-perl{a} libnet-ipv6addr-perl{a} libnet-netmask-perl{a} libnet-smtp-ssl-perl{a} libnet-ssleay-perl{a} libnetaddr-ip-perl{a} libnghttp2-14{a} libnl-3-200{a} libnl-route-3-200{a} libnumber-compare-perl{a} libobject-pad-perl{a} libogg0{a} libopengl0{a} libopenmpi3{a} libopus0{a} libpackage-stash-perl{a} libpango-1.0-0{a} libpangocairo-1.0-0{a} libpangoft2-1.0-0{a} libparams-classify-perl{a} libparams-util-perl{a} libparams-validate-perl{a} libparse-debcontrol-perl{a} libparse-recdescent-perl{a} libpath-iterator-rule-perl{a} libpath-tiny-perl{a} libpciaccess0{a} libpcre2-16-0{a} libperlio-gzip-perl{a} libperlio-utf8-strict-perl{a} libpetsc-real3.19{a} libpipeline1{a} libpixman-1-0{a} libpmix2{a} libpng16-16{a} libpod-constants-perl{a} libpod-parser-perl{a} libpod-pom-perl{a} libportaudio2{a} libproc-processtable-perl{a} libpsl5{a} libpsm-infinipath1{a} libpthread-stubs0-dev{a} libptscotch-7.0{a} libpython3-stdlib{a} libpython3.11-minimal{a} libpython3.11-stdlib{a} libqhull-r8.0{a} libqrupdate1{a} libqscintilla2-qt5-15{a} libqscintilla2-qt5-l10n{a} libqt5core5a{a} libqt5dbus5{a} libqt5gui5{a} libqt5help5{a} libqt5network5{a} libqt5printsupport5{a} libqt5sql5{a} libqt5widgets5{a} libqt5xml5{a} librav1e0{a} librdmacm1{a} libreadline-dev{a} libreadline8{a} libregexp-common-perl{a} libregexp-pattern-license-perl{a} libregexp-pattern-perl{a} libregexp-wildcards-perl{a} librole-tiny-perl{a} librtmp1{a} libsamplerate0{a} libsasl2-2{a} libsasl2-modules-db{a} libscalapack-openmpi2.2{a} libsensors-config{a} libsensors5{a} libsereal-decoder-perl{a} libsereal-encoder-perl{a} libset-intspan-perl{a} libsharpyuv0{a} libsm6{a} libsndfile1{a} libsoftware-copyright-perl{a} libsoftware-license-perl{a} libsoftware-licensemoreutils-perl{a} libsort-versions-perl{a} libspqr4{a} libssh2-1{a} libssl-dev{a} libstrictures-perl{a} libstring-copyright-perl{a} libstring-escape-perl{a} libstring-license-perl{a} libstring-rewriteprefix-perl{a} libsub-exporter-perl{a} libsub-exporter-progressive-perl{a} libsub-identify-perl{a} libsub-install-perl{a} libsub-name-perl{a} libsub-override-perl{a} libsub-quote-perl{a} libsub-uplevel-perl{a} libsuitesparseconfig7{a} libsundials-ida6{a} libsundials-nvecparallel-petsc6{a} libsundials-sunlinsol3{a} libsundials-sunmatrix4{a} libsuperlu-dist8{a} libsuperlu6{a} libsyntax-keyword-try-perl{a} libsz2{a} libterm-readkey-perl{a} libtest-exception-perl{a} libtext-autoformat-perl{a} libtext-glob-perl{a} libtext-levenshtein-damerau-perl{a} libtext-levenshteinxs-perl{a} libtext-markdown-discount-perl{a} libtext-reform-perl{a} libtext-template-perl{a} libtext-unidecode-perl{a} libtext-xslate-perl{a} libthai-data{a} libthai0{a} libtiff6{a} libtime-duration-perl{a} libtime-moment-perl{a} libtimedate-perl{a} libtoml-tiny-perl{a} libtool{a} libtry-tiny-perl{a} libuchardet0{a} libumfpack6{a} libunicode-utf8-perl{a} liburi-perl{a} libvariable-magic-perl{a} libvorbis0a{a} libvorbisenc2{a} libvulkan1{a} libwacom-common{a} libwacom9{a} libwayland-client0{a} libwayland-server0{a} libwebp7{a} libwebpmux3{a} libwmflite-0.2-7{a} libwww-mechanize-perl{a} libwww-perl{a} libwww-robotrules-perl{a} libx11-6{a} libx11-data{a} libx11-dev{a} libx11-xcb1{a} libxau-dev{a} libxau6{a} libxcb-dri2-0{a} libxcb-dri3-0{a} libxcb-glx0{a} libxcb-icccm4{a} libxcb-image0{a} libxcb-keysyms1{a} libxcb-present0{a} libxcb-randr0{a} libxcb-render-util0{a} libxcb-render0{a} libxcb-shape0{a} libxcb-shm0{a} libxcb-sync1{a} libxcb-util1{a} libxcb-xfixes0{a} libxcb-xinerama0{a} libxcb-xinput0{a} libxcb-xkb1{a} libxcb1{a} libxcb1-dev{a} libxcursor1{a} libxdmcp-dev{a} libxdmcp6{a} libxext6{a} libxfixes3{a} libxft2{a} libxinerama1{a} libxkbcommon-x11-0{a} libxkbcommon0{a} libxml-libxml-perl{a} libxml-namespacesupport-perl{a} libxml-sax-base-perl{a} libxml-sax-perl{a} libxml2{a} libxnvctrl0{a} libxpm4{a} libxrender1{a} libxs-parse-keyword-perl{a} libxs-parse-sublike-perl{a} libxshmfence1{a} libxxf86vm1{a} libyaml-0-2{a} libyaml-libyaml-perl{a} libyaml-pp-perl{a} libyaml-tiny-perl{a} libyuv0{a} libz3-4{a} licensecheck{a} lintian{a} lzop{a} m4{a} man-db{a} media-types{a} mpi-default-bin{a} netbase{a} ocl-icd-libopencl1{a} octave{a} octave-common{a} octave-dev{a} octave-io{a} openmpi-bin{a} openmpi-common{a} openssh-client{a} openssl{a} patchutils{a} perl-openssl-defaults{a} plzip{a} po-debconf{a} python3{a} python3-minimal{a} python3.11{a} python3.11-minimal{a} readline-common{a} sensible-utils{a} shared-mime-info{a} t1utils{a} tex-common{a} texinfo{a} texinfo-lib{a} tzdata{a} ucf{a} unzip{a} x11-common{a} x11proto-dev{a} xkb-data{a} xorg-sgml-doctools{a} xtrans-dev{a} zlib1g-dev{a} The following packages are RECOMMENDED but will NOT be installed: alsa-topology-conf alsa-ucm-conf bash-completion curl dbus default-jre-headless epstool fonts-liberation fonts-urw-base35 ghostscript groff ibverbs-providers libapache-poi-java libarchive-cpio-perl libauthen-sasl-perl libblis4 libcgi-fast-perl libclass-c3-xs-perl libconfig-model-approx-perl libconfig-model-lcdproc-perl libconfig-model-openssh-perl libconfig-model-systemd-perl libconfig-model-tkui-perl libdata-dump-perl libfreezethaw-perl libfuse-perl libglib2.0-data libgpm2 libheif-plugin-aomenc libheif-plugin-x265 libhtml-format-perl libhttp-daemon-perl libio-compress-brotli-perl libipc-shareable-perl libjexcelapi-java libjopendocument-java libjson-xs-perl libldap-common liblist-someutils-xs-perl liblog-dispatch-perl libltdl-dev libmail-sendmail-perl libmath-base85-perl libopenblas0 libpackage-stash-xs-perl libqt5sql5-ibase libqt5sql5-mysql libqt5sql5-odbc libqt5sql5-psql libqt5sql5-sqlite libqt5sql5-tds libqt5svg5 libre-engine-re2-perl libreoffice-core libreoffice-java-common libsasl2-modules libsocket6-perl libtie-ixhash-perl libtypes-serialiser-perl libxerces2-java libxml-sax-expat-perl libxstring-perl lynx mesa-vulkan-drivers octave-doc pstoedit publicsuffix qt5-gtk-platformtheme qttranslations5-l10n qtwayland5 wget xauth xdg-user-dirs 0 packages upgraded, 518 newly installed, 0 to remove and 0 not upgraded. Need to get 218 MB of archives. After unpacking 852 MB will be used. Writing extended state information... Get: 1 http://deb.debian.org/debian trixie/main i386 libpython3.11-minimal i386 3.11.8-1 [817 kB] Get: 2 http://deb.debian.org/debian trixie/main i386 libexpat1 i386 2.5.0-2+b2 [104 kB] Get: 3 http://deb.debian.org/debian trixie/main i386 python3.11-minimal i386 3.11.8-1 [2087 kB] Get: 4 http://deb.debian.org/debian trixie/main i386 python3-minimal i386 3.11.6-1 [26.2 kB] Get: 5 http://deb.debian.org/debian trixie/main i386 media-types all 10.1.0 [26.9 kB] Get: 6 http://deb.debian.org/debian trixie/main i386 netbase all 6.4 [12.8 kB] Get: 7 http://deb.debian.org/debian trixie/main i386 tzdata all 2024a-1 [255 kB] Get: 8 http://deb.debian.org/debian trixie/main i386 readline-common all 8.2-3 [69.1 kB] Get: 9 http://deb.debian.org/debian trixie/main i386 libreadline8 i386 8.2-3+b1 [171 kB] Get: 10 http://deb.debian.org/debian trixie/main i386 libpython3.11-stdlib i386 3.11.8-1 [1821 kB] Get: 11 http://deb.debian.org/debian trixie/main i386 python3.11 i386 3.11.8-1 [597 kB] Get: 12 http://deb.debian.org/debian trixie/main i386 libpython3-stdlib i386 3.11.6-1 [9224 B] Get: 13 http://deb.debian.org/debian trixie/main i386 python3 i386 3.11.6-1 [26.2 kB] Get: 14 http://deb.debian.org/debian trixie/main i386 sensible-utils all 0.0.22 [22.4 kB] Get: 15 http://deb.debian.org/debian trixie/main i386 openssl i386 3.1.5-1 [1246 kB] Get: 16 http://deb.debian.org/debian trixie/main i386 ca-certificates all 20240203 [158 kB] Get: 17 http://deb.debian.org/debian trixie/main i386 libmagic-mgc i386 1:5.45-2+b1 [314 kB] Get: 18 http://deb.debian.org/debian trixie/main i386 libmagic1 i386 1:5.45-2+b1 [114 kB] Get: 19 http://deb.debian.org/debian trixie/main i386 file i386 1:5.45-2+b1 [43.0 kB] Get: 20 http://deb.debian.org/debian trixie/main i386 gettext-base i386 0.21-14+b1 [162 kB] Get: 21 http://deb.debian.org/debian trixie/main i386 libuchardet0 i386 0.0.8-1+b1 [69.1 kB] Get: 22 http://deb.debian.org/debian trixie/main i386 groff-base i386 1.23.0-3 [1195 kB] Get: 23 http://deb.debian.org/debian trixie/main i386 bsdextrautils i386 2.39.3-6 [93.3 kB] Get: 24 http://deb.debian.org/debian trixie/main i386 libpipeline1 i386 1.5.7-1+b2 [39.6 kB] Get: 25 http://deb.debian.org/debian trixie/main i386 man-db i386 2.12.0-3 [1413 kB] Get: 26 http://deb.debian.org/debian trixie/main i386 libbsd0 i386 0.12.2-1 [134 kB] Get: 27 http://deb.debian.org/debian trixie/main i386 libedit2 i386 3.1-20230828-1 [97.5 kB] Get: 28 http://deb.debian.org/debian trixie/main i386 libcbor0.10 i386 0.10.2-1.1 [30.7 kB] Get: 29 http://deb.debian.org/debian trixie/main i386 libfido2-1 i386 1.14.0-1 [87.1 kB] Get: 30 http://deb.debian.org/debian trixie/main i386 openssh-client i386 1:9.6p1-4 [1001 kB] Get: 31 http://deb.debian.org/debian trixie/main i386 ucf all 3.0043+nmu1 [55.2 kB] Get: 32 http://deb.debian.org/debian trixie/main i386 aglfn all 1.7+git20191031.4036a9c-2 [30.5 kB] Get: 33 http://deb.debian.org/debian trixie/main i386 m4 i386 1.4.19-4 [293 kB] Get: 34 http://deb.debian.org/debian trixie/main i386 autoconf all 2.71-3 [332 kB] Get: 35 http://deb.debian.org/debian trixie/main i386 autotools-dev all 20220109.1 [51.6 kB] Get: 36 http://deb.debian.org/debian trixie/main i386 automake all 1:1.16.5-1.3 [823 kB] Get: 37 http://deb.debian.org/debian trixie/main i386 autopoint all 0.21-14 [496 kB] Get: 38 http://deb.debian.org/debian trixie/main i386 libcapture-tiny-perl all 0.48-2 [24.6 kB] Get: 39 http://deb.debian.org/debian trixie/main i386 libparams-util-perl i386 1.102-2+b2 [24.7 kB] Get: 40 http://deb.debian.org/debian trixie/main i386 libsub-install-perl all 0.929-1 [10.5 kB] Get: 41 http://deb.debian.org/debian trixie/main i386 libdata-optlist-perl all 0.114-1 [10.6 kB] Get: 42 http://deb.debian.org/debian trixie/main i386 libb-hooks-op-check-perl i386 0.22-2+b2 [10.7 kB] Get: 43 http://deb.debian.org/debian trixie/main i386 libdynaloader-functions-perl all 0.003-3 [12.7 kB] Get: 44 http://deb.debian.org/debian trixie/main i386 libdevel-callchecker-perl i386 0.008-2+b1 [15.1 kB] Get: 45 http://deb.debian.org/debian trixie/main i386 libparams-classify-perl i386 0.015-2+b2 [23.1 kB] Get: 46 http://deb.debian.org/debian trixie/main i386 libmodule-runtime-perl all 0.016-2 [19.6 kB] Get: 47 http://deb.debian.org/debian trixie/main i386 libtry-tiny-perl all 0.31-2 [22.6 kB] Get: 48 http://deb.debian.org/debian trixie/main i386 libmodule-implementation-perl all 0.09-2 [12.6 kB] Get: 49 http://deb.debian.org/debian trixie/main i386 libpackage-stash-perl all 0.40-1 [22.0 kB] Get: 50 http://deb.debian.org/debian trixie/main i386 libclass-load-perl all 0.25-2 [15.3 kB] Get: 51 http://deb.debian.org/debian trixie/main i386 libio-stringy-perl all 2.111-3 [56.5 kB] Get: 52 http://deb.debian.org/debian trixie/main i386 libparams-validate-perl i386 1.31-2+b1 [64.9 kB] Get: 53 http://deb.debian.org/debian trixie/main i386 libsub-exporter-perl all 0.990-1 [50.6 kB] Get: 54 http://deb.debian.org/debian trixie/main i386 libgetopt-long-descriptive-perl all 0.111-1 [27.8 kB] Get: 55 http://deb.debian.org/debian trixie/main i386 libio-tiecombine-perl all 1.005-3 [10.8 kB] Get: 56 http://deb.debian.org/debian trixie/main i386 libmodule-pluggable-perl all 5.2-5 [23.0 kB] Get: 57 http://deb.debian.org/debian trixie/main i386 libstring-rewriteprefix-perl all 0.009-1 [7140 B] Get: 58 http://deb.debian.org/debian trixie/main i386 libapp-cmd-perl all 0.336-1 [65.8 kB] Get: 59 http://deb.debian.org/debian trixie/main i386 libboolean-perl all 0.46-3 [9924 B] Get: 60 http://deb.debian.org/debian trixie/main i386 libsub-uplevel-perl all 0.2800-3 [14.0 kB] Get: 61 http://deb.debian.org/debian trixie/main i386 libtest-exception-perl all 0.43-3 [16.9 kB] Get: 62 http://deb.debian.org/debian trixie/main i386 libcarp-assert-more-perl all 2.4.0-1 [20.2 kB] Get: 63 http://deb.debian.org/debian trixie/main i386 libfile-which-perl all 1.27-2 [15.1 kB] Get: 64 http://deb.debian.org/debian trixie/main i386 libfile-homedir-perl all 1.006-2 [42.4 kB] Get: 65 http://deb.debian.org/debian trixie/main i386 libclone-choose-perl all 0.010-2 [8676 B] Get: 66 http://deb.debian.org/debian trixie/main i386 libhash-merge-perl all 0.302-1 [14.7 kB] Get: 67 http://deb.debian.org/debian trixie/main i386 libjson-perl all 4.10000-1 [87.5 kB] Get: 68 http://deb.debian.org/debian trixie/main i386 libexporter-tiny-perl all 1.006002-1 [38.7 kB] Get: 69 http://deb.debian.org/debian trixie/main i386 liblist-moreutils-xs-perl i386 0.430-3+b2 [45.2 kB] Get: 70 http://deb.debian.org/debian trixie/main i386 liblist-moreutils-perl all 0.430-2 [46.9 kB] Get: 71 http://deb.debian.org/debian trixie/main i386 liblog-log4perl-perl all 1.57-1 [367 kB] Get: 72 http://deb.debian.org/debian trixie/main i386 libmouse-perl i386 2.5.10-1+b4 [146 kB] Get: 73 http://deb.debian.org/debian trixie/main i386 libmousex-nativetraits-perl all 1.09-3 [53.5 kB] Get: 74 http://deb.debian.org/debian trixie/main i386 libmousex-strictconstructor-perl all 0.02-3 [5304 B] Get: 75 http://deb.debian.org/debian trixie/main i386 libparse-recdescent-perl all 1.967015+dfsg-4 [147 kB] Get: 76 http://deb.debian.org/debian trixie/main i386 libpath-tiny-perl all 0.144-1 [56.4 kB] Get: 77 http://deb.debian.org/debian trixie/main i386 libpod-pom-perl all 2.01-4 [65.0 kB] Get: 78 http://deb.debian.org/debian trixie/main i386 libregexp-common-perl all 2017060201-3 [175 kB] Get: 79 http://deb.debian.org/debian trixie/main i386 libyaml-tiny-perl all 1.74-1 [30.7 kB] Get: 80 http://deb.debian.org/debian trixie/main i386 libconfig-model-perl all 2.153-3 [448 kB] Get: 81 http://deb.debian.org/debian trixie/main i386 libyaml-pp-perl all 0.38.0-1 [109 kB] Get: 82 http://deb.debian.org/debian trixie/main i386 cme all 1.040-1 [68.8 kB] Get: 83 http://deb.debian.org/debian trixie/main i386 libdebhelper-perl all 13.15.3 [88.0 kB] Get: 84 http://deb.debian.org/debian trixie/main i386 libtool all 2.4.7-7 [517 kB] Get: 85 http://deb.debian.org/debian trixie/main i386 dh-autoreconf all 20 [17.1 kB] Get: 86 http://deb.debian.org/debian trixie/main i386 libarchive-zip-perl all 1.68-1 [104 kB] Get: 87 http://deb.debian.org/debian trixie/main i386 libsub-override-perl all 0.10-1 [10.6 kB] Get: 88 http://deb.debian.org/debian trixie/main i386 libfile-stripnondeterminism-perl all 1.13.1-1 [19.4 kB] Get: 89 http://deb.debian.org/debian trixie/main i386 dh-strip-nondeterminism all 1.13.1-1 [8620 B] Get: 90 http://deb.debian.org/debian trixie/main i386 libelf1 i386 0.190-1+b1 [182 kB] Get: 91 http://deb.debian.org/debian trixie/main i386 dwz i386 0.15-1 [118 kB] Get: 92 http://deb.debian.org/debian trixie/main i386 libicu72 i386 72.1-4+b1 [9549 kB] Get: 93 http://deb.debian.org/debian trixie/main i386 libxml2 i386 2.9.14+dfsg-1.3+b2 [727 kB] Get: 94 http://deb.debian.org/debian trixie/main i386 gettext i386 0.21-14+b1 [1311 kB] Get: 95 http://deb.debian.org/debian trixie/main i386 intltool-debian all 0.35.0+20060710.6 [22.9 kB] Get: 96 http://deb.debian.org/debian trixie/main i386 po-debconf all 1.0.21+nmu1 [248 kB] Get: 97 http://deb.debian.org/debian trixie/main i386 debhelper all 13.15.3 [901 kB] Get: 98 http://deb.debian.org/debian trixie/main i386 gnuplot-data all 6.0.0+dfsg1-1 [72.1 kB] Get: 99 http://deb.debian.org/debian trixie/main i386 libbrotli1 i386 1.1.0-2+b3 [314 kB] Get: 100 http://deb.debian.org/debian trixie/main i386 libpng16-16 i386 1.6.43-1 [285 kB] Get: 101 http://deb.debian.org/debian trixie/main i386 libfreetype6 i386 2.13.2+dfsg-1+b1 [449 kB] Get: 102 http://deb.debian.org/debian trixie/main i386 fonts-dejavu-mono all 2.37-8 [489 kB] Get: 103 http://deb.debian.org/debian trixie/main i386 fonts-dejavu-core all 2.37-8 [840 kB] Get: 104 http://deb.debian.org/debian trixie/main i386 fonts-freefont-otf all 20211204+svn4273-2 [4328 kB] Get: 105 http://deb.debian.org/debian trixie/main i386 fontconfig-config i386 2.15.0-1.1 [317 kB] Get: 106 http://deb.debian.org/debian trixie/main i386 libfontconfig1 i386 2.15.0-1.1 [401 kB] Get: 107 http://deb.debian.org/debian trixie/main i386 libpixman-1-0 i386 0.42.2-1+b1 [555 kB] Get: 108 http://deb.debian.org/debian trixie/main i386 libxau6 i386 1:1.0.9-1 [20.0 kB] Get: 109 http://deb.debian.org/debian trixie/main i386 libxdmcp6 i386 1:1.1.2-3 [26.7 kB] Get: 110 http://deb.debian.org/debian trixie/main i386 libxcb1 i386 1.15-1 [148 kB] Get: 111 http://deb.debian.org/debian trixie/main i386 libx11-data all 2:1.8.7-1 [328 kB] Get: 112 http://deb.debian.org/debian trixie/main i386 libx11-6 i386 2:1.8.7-1 [822 kB] Get: 113 http://deb.debian.org/debian trixie/main i386 libxcb-render0 i386 1.15-1 [116 kB] Get: 114 http://deb.debian.org/debian trixie/main i386 libxcb-shm0 i386 1.15-1 [106 kB] Get: 115 http://deb.debian.org/debian trixie/main i386 libxext6 i386 2:1.3.4-1+b1 [55.3 kB] Get: 116 http://deb.debian.org/debian trixie/main i386 libxrender1 i386 1:0.9.10-1.1 [34.1 kB] Get: 117 http://deb.debian.org/debian trixie/main i386 libcairo2 i386 1.18.0-1+b1 [587 kB] Get: 118 http://deb.debian.org/debian trixie/main i386 libaom3 i386 3.8.2-2 [1910 kB] Get: 119 http://deb.debian.org/debian trixie/main i386 libdav1d7 i386 1.4.1-1 [330 kB] Get: 120 http://deb.debian.org/debian trixie/main i386 libabsl20220623 i386 20220623.1-3 [447 kB] Get: 121 http://deb.debian.org/debian trixie/main i386 libgav1-1 i386 0.18.0-1+b1 [307 kB] Get: 122 http://deb.debian.org/debian trixie/main i386 librav1e0 i386 0.7.1-2 [650 kB] Get: 123 http://deb.debian.org/debian trixie/main i386 libsharpyuv0 i386 1.3.2-0.4 [107 kB] Get: 124 http://deb.debian.org/debian trixie/main i386 libjpeg62-turbo i386 1:2.1.5-2+b2 [169 kB] Get: 125 http://deb.debian.org/debian trixie/main i386 libyuv0 i386 0.0~git202401110.af6ac82-1 [108 kB] Get: 126 http://deb.debian.org/debian trixie/main i386 libavif16 i386 1.0.4-1 [112 kB] Get: 127 http://deb.debian.org/debian trixie/main i386 libheif-plugin-dav1d i386 1.17.6-1 [9936 B] Get: 128 http://deb.debian.org/debian trixie/main i386 libde265-0 i386 1.0.15-1 [195 kB] Get: 129 http://deb.debian.org/debian trixie/main i386 libheif-plugin-libde265 i386 1.17.6-1 [13.4 kB] Get: 130 http://deb.debian.org/debian trixie/main i386 libheif1 i386 1.17.6-1 [299 kB] Get: 131 http://deb.debian.org/debian trixie/main i386 libdeflate0 i386 1.20-1 [46.9 kB] Get: 132 http://deb.debian.org/debian trixie/main i386 libjbig0 i386 2.1-6.1+b1 [31.8 kB] Get: 133 http://deb.debian.org/debian trixie/main i386 liblerc4 i386 4.0.0+ds-4+b1 [180 kB] Get: 134 http://deb.debian.org/debian trixie/main i386 libwebp7 i386 1.3.2-0.4 [314 kB] Get: 135 http://deb.debian.org/debian trixie/main i386 libtiff6 i386 4.5.1+git230720-4 [338 kB] Get: 136 http://deb.debian.org/debian trixie/main i386 libxpm4 i386 1:3.5.17-1 [57.5 kB] Get: 137 http://deb.debian.org/debian trixie/main i386 libgd3 i386 2.3.3-9+b1 [129 kB] Get: 138 http://deb.debian.org/debian trixie/main i386 libglib2.0-0 i386 2.78.4-1 [1520 kB] Get: 139 http://deb.debian.org/debian trixie/main i386 liblua5.4-0 i386 5.4.6-3 [168 kB] Get: 140 http://deb.debian.org/debian trixie/main i386 fontconfig i386 2.15.0-1.1 [462 kB] Get: 141 http://deb.debian.org/debian trixie/main i386 libfribidi0 i386 1.0.13-3+b1 [71.8 kB] Get: 142 http://deb.debian.org/debian trixie/main i386 libgraphite2-3 i386 1.3.14-2 [77.7 kB] Get: 143 http://deb.debian.org/debian trixie/main i386 libharfbuzz0b i386 8.3.0-2 [2234 kB] Get: 144 http://deb.debian.org/debian trixie/main i386 libthai-data all 0.1.29-2 [168 kB] Get: 145 http://deb.debian.org/debian trixie/main i386 libdatrie1 i386 0.2.13-3 [39.5 kB] Get: 146 http://deb.debian.org/debian trixie/main i386 libthai0 i386 0.1.29-2 [50.1 kB] Get: 147 http://deb.debian.org/debian trixie/main i386 libpango-1.0-0 i386 1.52.0+ds-1 [224 kB] Get: 148 http://deb.debian.org/debian trixie/main i386 libpangoft2-1.0-0 i386 1.52.0+ds-1 [51.0 kB] Get: 149 http://deb.debian.org/debian trixie/main i386 libpangocairo-1.0-0 i386 1.52.0+ds-1 [35.9 kB] Get: 150 http://deb.debian.org/debian trixie/main i386 libwebpmux3 i386 1.3.2-0.4 [121 kB] Get: 151 http://deb.debian.org/debian trixie/main i386 gnuplot-nox i386 6.0.0+dfsg1-1 [926 kB] Get: 152 http://deb.debian.org/debian trixie/main i386 dh-octave-autopkgtest all 1.8.0 [10.0 kB] Get: 153 http://deb.debian.org/debian trixie/main i386 libapt-pkg-perl i386 0.1.40+b3 [68.9 kB] Get: 154 http://deb.debian.org/debian trixie/main i386 libarray-intspan-perl all 2.004-2 [25.7 kB] Get: 155 http://deb.debian.org/debian trixie/main i386 libyaml-0-2 i386 0.2.5-1 [55.9 kB] Get: 156 http://deb.debian.org/debian trixie/main i386 libyaml-libyaml-perl i386 0.89+ds-1 [35.7 kB] Get: 157 http://deb.debian.org/debian trixie/main i386 libconfig-model-backend-yaml-perl all 2.134-2 [10.8 kB] Get: 158 http://deb.debian.org/debian trixie/main i386 libexporter-lite-perl all 0.09-2 [10.7 kB] Get: 159 http://deb.debian.org/debian trixie/main i386 libencode-locale-perl all 1.05-3 [12.9 kB] Get: 160 http://deb.debian.org/debian trixie/main i386 libtimedate-perl all 2.3300-2 [39.3 kB] Get: 161 http://deb.debian.org/debian trixie/main i386 libhttp-date-perl all 6.06-1 [10.7 kB] Get: 162 http://deb.debian.org/debian trixie/main i386 libfile-listing-perl all 6.16-1 [12.4 kB] Get: 163 http://deb.debian.org/debian trixie/main i386 libhtml-tagset-perl all 3.24-1 [14.7 kB] Get: 164 http://deb.debian.org/debian trixie/main i386 liburi-perl all 5.27-1 [98.4 kB] Get: 165 http://deb.debian.org/debian trixie/main i386 libhtml-parser-perl i386 3.81-1+b1 [100 kB] Get: 166 http://deb.debian.org/debian trixie/main i386 libhtml-tree-perl all 5.07-3 [211 kB] Get: 167 http://deb.debian.org/debian trixie/main i386 libclone-perl i386 0.46-1+b1 [13.9 kB] Get: 168 http://deb.debian.org/debian trixie/main i386 libio-html-perl all 1.004-3 [16.2 kB] Get: 169 http://deb.debian.org/debian trixie/main i386 liblwp-mediatypes-perl all 6.04-2 [20.2 kB] Get: 170 http://deb.debian.org/debian trixie/main i386 libhttp-message-perl all 6.45-1 [82.0 kB] Get: 171 http://deb.debian.org/debian trixie/main i386 libhttp-cookies-perl all 6.11-1 [19.1 kB] Get: 172 http://deb.debian.org/debian trixie/main i386 libhttp-negotiate-perl all 6.01-2 [13.1 kB] Get: 173 http://deb.debian.org/debian trixie/main i386 perl-openssl-defaults i386 7+b1 [7920 B] Get: 174 http://deb.debian.org/debian trixie/main i386 libnet-ssleay-perl i386 1.94-1 [339 kB] Get: 175 http://deb.debian.org/debian trixie/main i386 libio-socket-ssl-perl all 2.085-1 [218 kB] Get: 176 http://deb.debian.org/debian trixie/main i386 libnet-http-perl all 6.23-1 [23.9 kB] Get: 177 http://deb.debian.org/debian trixie/main i386 liblwp-protocol-https-perl all 6.14-1 [10.8 kB] Get: 178 http://deb.debian.org/debian trixie/main i386 libwww-robotrules-perl all 6.02-1 [12.9 kB] Get: 179 http://deb.debian.org/debian trixie/main i386 libwww-perl all 6.77-1 [183 kB] Get: 180 http://deb.debian.org/debian trixie/main i386 liberror-perl all 0.17029-2 [29.0 kB] Get: 181 http://deb.debian.org/debian trixie/main i386 libparse-debcontrol-perl all 2.005-6 [21.6 kB] Get: 182 http://deb.debian.org/debian trixie/main i386 libsoftware-copyright-perl all 0.012-2 [18.0 kB] Get: 183 http://deb.debian.org/debian trixie/main i386 libalgorithm-c3-perl all 0.11-2 [10.8 kB] Get: 184 http://deb.debian.org/debian trixie/main i386 libclass-c3-perl all 0.35-2 [21.0 kB] Get: 185 http://deb.debian.org/debian trixie/main i386 libmro-compat-perl all 0.15-2 [11.8 kB] Get: 186 http://deb.debian.org/debian trixie/main i386 libdata-section-perl all 0.200008-1 [13.1 kB] Get: 187 http://deb.debian.org/debian trixie/main i386 libtext-template-perl all 1.61-1 [54.4 kB] Get: 188 http://deb.debian.org/debian trixie/main i386 libsoftware-license-perl all 0.104006-1 [116 kB] Get: 189 http://deb.debian.org/debian trixie/main i386 libsoftware-licensemoreutils-perl all 1.009-1 [22.0 kB] Get: 190 http://deb.debian.org/debian trixie/main i386 libsort-versions-perl all 1.62-3 [8928 B] Get: 191 http://deb.debian.org/debian trixie/main i386 libtext-reform-perl all 1.20-5 [36.0 kB] Get: 192 http://deb.debian.org/debian trixie/main i386 libtext-autoformat-perl all 1.750000-2 [35.2 kB] Get: 193 http://deb.debian.org/debian trixie/main i386 libtext-levenshtein-damerau-perl all 0.41-3 [12.3 kB] Get: 194 http://deb.debian.org/debian trixie/main i386 libtoml-tiny-perl all 0.16-1 [23.4 kB] Get: 195 http://deb.debian.org/debian trixie/main i386 libindirect-perl i386 0.39-2+b2 [28.0 kB] Get: 196 http://deb.debian.org/debian trixie/main i386 libxs-parse-keyword-perl i386 0.39-1+b1 [59.3 kB] Get: 197 http://deb.debian.org/debian trixie/main i386 libxs-parse-sublike-perl i386 0.21-2+b1 [41.7 kB] Get: 198 http://deb.debian.org/debian trixie/main i386 libobject-pad-perl i386 0.808-1+b1 [124 kB] Get: 199 http://deb.debian.org/debian trixie/main i386 libfeature-compat-class-perl all 0.06-1 [10.7 kB] Get: 200 http://deb.debian.org/debian trixie/main i386 libsyntax-keyword-try-perl i386 0.29-1+b1 [27.4 kB] Get: 201 http://deb.debian.org/debian trixie/main i386 libfeature-compat-try-perl all 0.05-1 [10.4 kB] Get: 202 http://deb.debian.org/debian trixie/main i386 libio-interactive-perl all 1.025-1 [11.4 kB] Get: 203 http://deb.debian.org/debian trixie/main i386 liblog-any-perl all 1.717-1 [78.9 kB] Get: 204 http://deb.debian.org/debian trixie/main i386 liblog-any-adapter-screen-perl all 0.140-2 [13.3 kB] Get: 205 http://deb.debian.org/debian trixie/main i386 libsub-exporter-progressive-perl all 0.001013-3 [7496 B] Get: 206 http://deb.debian.org/debian trixie/main i386 libvariable-magic-perl i386 0.63-1+b2 [44.5 kB] Get: 207 http://deb.debian.org/debian trixie/main i386 libb-hooks-endofscope-perl all 0.28-1 [17.5 kB] Get: 208 http://deb.debian.org/debian trixie/main i386 libsub-identify-perl i386 0.14-3+b1 [11.2 kB] Get: 209 http://deb.debian.org/debian trixie/main i386 libsub-name-perl i386 0.27-1+b1 [12.6 kB] Get: 210 http://deb.debian.org/debian trixie/main i386 libnamespace-clean-perl all 0.27-2 [17.8 kB] Get: 211 http://deb.debian.org/debian trixie/main i386 libnumber-compare-perl all 0.03-3 [6332 B] Get: 212 http://deb.debian.org/debian trixie/main i386 libtext-glob-perl all 0.11-3 [7676 B] Get: 213 http://deb.debian.org/debian trixie/main i386 libpath-iterator-rule-perl all 1.015-2 [41.7 kB] Get: 214 http://deb.debian.org/debian trixie/main i386 libpod-parser-perl all 1.67-1 [94.1 kB] Get: 215 http://deb.debian.org/debian trixie/main i386 libpod-constants-perl all 0.19-2 [17.3 kB] Get: 216 http://deb.debian.org/debian trixie/main i386 libset-intspan-perl all 1.19-3 [25.3 kB] Get: 217 http://deb.debian.org/debian trixie/main i386 libstring-copyright-perl all 0.003014-1 [23.4 kB] Get: 218 http://deb.debian.org/debian trixie/main i386 libstring-escape-perl all 2010.002-3 [18.7 kB] Get: 219 http://deb.debian.org/debian trixie/main i386 libregexp-pattern-license-perl all 3.11.0-1 [94.8 kB] Get: 220 http://deb.debian.org/debian trixie/main i386 libregexp-pattern-perl all 0.2.14-2 [18.7 kB] Get: 221 http://deb.debian.org/debian trixie/main i386 libstring-license-perl all 0.0.9-2 [35.5 kB] Get: 222 http://deb.debian.org/debian trixie/main i386 licensecheck all 3.3.9-1 [50.1 kB] Get: 223 http://deb.debian.org/debian trixie/main i386 diffstat i386 1.66-1 [34.7 kB] Get: 224 http://deb.debian.org/debian trixie/main i386 libassuan0 i386 2.5.6-1 [51.9 kB] Get: 225 http://deb.debian.org/debian trixie/main i386 gpgconf i386 2.2.40-1.1+b1 [572 kB] Get: 226 http://deb.debian.org/debian trixie/main i386 gpg i386 2.2.40-1.1+b1 [991 kB] Get: 227 http://deb.debian.org/debian trixie/main i386 iso-codes all 4.16.0-1 [2936 kB] Get: 228 http://deb.debian.org/debian trixie/main i386 libberkeleydb-perl i386 0.64-2+b2 [126 kB] Get: 229 http://deb.debian.org/debian trixie/main i386 libclass-xsaccessor-perl i386 1.19-4+b2 [37.7 kB] Get: 230 http://deb.debian.org/debian trixie/main i386 libconfig-tiny-perl all 2.30-1 [18.9 kB] Get: 231 http://deb.debian.org/debian trixie/main i386 libconst-fast-perl all 0.014-2 [8792 B] Get: 232 http://deb.debian.org/debian trixie/main i386 libcpanel-json-xs-perl i386 4.37-1+b1 [133 kB] Get: 233 http://deb.debian.org/debian trixie/main i386 libaliased-perl all 0.34-3 [13.5 kB] Get: 234 http://deb.debian.org/debian trixie/main i386 libclass-data-inheritable-perl all 0.08-3 [8588 B] Get: 235 http://deb.debian.org/debian trixie/main i386 libdevel-stacktrace-perl all 2.0500-1 [26.4 kB] Get: 236 http://deb.debian.org/debian trixie/main i386 libexception-class-perl all 1.45-1 [34.6 kB] Get: 237 http://deb.debian.org/debian trixie/main i386 libiterator-perl all 0.03+ds1-2 [18.8 kB] Get: 238 http://deb.debian.org/debian trixie/main i386 libiterator-util-perl all 0.02+ds1-2 [14.0 kB] Get: 239 http://deb.debian.org/debian trixie/main i386 libdata-dpath-perl all 0.59-1 [43.6 kB] Get: 240 http://deb.debian.org/debian trixie/main i386 libnet-domain-tld-perl all 1.75-3 [31.9 kB] Get: 241 http://deb.debian.org/debian trixie/main i386 libdata-validate-domain-perl all 0.10-1.1 [11.1 kB] Get: 242 http://deb.debian.org/debian trixie/main i386 libnet-ipv6addr-perl all 1.02-1 [21.7 kB] Get: 243 http://deb.debian.org/debian trixie/main i386 libnet-netmask-perl all 2.0002-2 [28.6 kB] Get: 244 http://deb.debian.org/debian trixie/main i386 libnetaddr-ip-perl i386 4.079+dfsg-2+b2 [98.8 kB] Get: 245 http://deb.debian.org/debian trixie/main i386 libdata-validate-ip-perl all 0.31-1 [20.6 kB] Get: 246 http://deb.debian.org/debian trixie/main i386 libdata-validate-uri-perl all 0.07-3 [11.0 kB] Get: 247 http://deb.debian.org/debian trixie/main i386 libdevel-size-perl i386 0.83-2+b2 [24.7 kB] Get: 248 http://deb.debian.org/debian trixie/main i386 libemail-address-xs-perl i386 1.05-1+b2 [30.2 kB] Get: 249 http://deb.debian.org/debian trixie/main i386 libipc-system-simple-perl all 1.30-2 [26.8 kB] Get: 250 http://deb.debian.org/debian trixie/main i386 libfile-basedir-perl all 0.09-2 [15.1 kB] Get: 251 http://deb.debian.org/debian trixie/main i386 libfile-find-rule-perl all 0.34-3 [26.6 kB] Get: 252 http://deb.debian.org/debian trixie/main i386 libio-string-perl all 1.08-4 [12.1 kB] Get: 253 http://deb.debian.org/debian trixie/main i386 libfont-ttf-perl all 1.06-2 [318 kB] Get: 254 http://deb.debian.org/debian trixie/main i386 libhtml-html5-entities-perl all 0.004-3 [21.0 kB] Get: 255 http://deb.debian.org/debian trixie/main i386 libhtml-tokeparser-simple-perl all 3.16-4 [39.1 kB] Get: 256 http://deb.debian.org/debian trixie/main i386 libipc-run3-perl all 0.049-1 [31.5 kB] Get: 257 http://deb.debian.org/debian trixie/main i386 libjson-maybexs-perl all 1.004005-1 [12.9 kB] Get: 258 http://deb.debian.org/debian trixie/main i386 liblist-compare-perl all 0.55-2 [65.7 kB] Get: 259 http://deb.debian.org/debian trixie/main i386 liblist-someutils-perl all 0.59-1 [37.1 kB] Get: 260 http://deb.debian.org/debian trixie/main i386 liblist-utilsby-perl all 0.12-2 [15.5 kB] Get: 261 http://deb.debian.org/debian trixie/main i386 libmldbm-perl all 2.05-4 [16.8 kB] Get: 262 http://deb.debian.org/debian trixie/main i386 libclass-method-modifiers-perl all 2.15-1 [18.0 kB] Get: 263 http://deb.debian.org/debian trixie/main i386 libimport-into-perl all 1.002005-2 [11.3 kB] Get: 264 http://deb.debian.org/debian trixie/main i386 librole-tiny-perl all 2.002004-1 [21.4 kB] Get: 265 http://deb.debian.org/debian trixie/main i386 libsub-quote-perl all 2.006008-1 [21.8 kB] Get: 266 http://deb.debian.org/debian trixie/main i386 libmoo-perl all 2.005005-1 [58.0 kB] Get: 267 http://deb.debian.org/debian trixie/main i386 libstrictures-perl all 2.000006-1 [18.6 kB] Get: 268 http://deb.debian.org/debian trixie/main i386 libmoox-aliases-perl all 0.001006-2 [7156 B] Get: 269 http://deb.debian.org/debian trixie/main i386 libperlio-gzip-perl i386 0.20-1+b2 [17.8 kB] Get: 270 http://deb.debian.org/debian trixie/main i386 libperlio-utf8-strict-perl i386 0.010-1+b1 [11.6 kB] Get: 271 http://deb.debian.org/debian trixie/main i386 libproc-processtable-perl i386 0.636-1+b1 [42.4 kB] Get: 272 http://deb.debian.org/debian trixie/main i386 libregexp-wildcards-perl all 1.05-3 [14.1 kB] Get: 273 http://deb.debian.org/debian trixie/main i386 libsereal-decoder-perl i386 5.004+ds-1+b1 [106 kB] Get: 274 http://deb.debian.org/debian trixie/main i386 libsereal-encoder-perl i386 5.004+ds-1+b1 [110 kB] Get: 275 http://deb.debian.org/debian trixie/main i386 libterm-readkey-perl i386 2.38-2+b2 [25.4 kB] Get: 276 http://deb.debian.org/debian trixie/main i386 libtext-levenshteinxs-perl i386 0.03-5+b2 [8612 B] Get: 277 http://deb.debian.org/debian trixie/main i386 libmarkdown2 i386 2.2.7-2+b1 [37.5 kB] Get: 278 http://deb.debian.org/debian trixie/main i386 libtext-markdown-discount-perl i386 0.16-1+b1 [13.2 kB] Get: 279 http://deb.debian.org/debian trixie/main i386 libdata-messagepack-perl i386 1.02-1+b2 [33.0 kB] Get: 280 http://deb.debian.org/debian trixie/main i386 libtext-xslate-perl i386 3.5.9-1+b3 [177 kB] Get: 281 http://deb.debian.org/debian trixie/main i386 libtime-duration-perl all 1.21-2 [13.1 kB] Get: 282 http://deb.debian.org/debian trixie/main i386 libtime-moment-perl i386 0.44-2+b2 [79.7 kB] Get: 283 http://deb.debian.org/debian trixie/main i386 libunicode-utf8-perl i386 0.62-2+b1 [20.9 kB] Get: 284 http://deb.debian.org/debian trixie/main i386 libcgi-pm-perl all 4.64-1 [217 kB] Get: 285 http://deb.debian.org/debian trixie/main i386 libhtml-form-perl all 6.11-1 [33.1 kB] Get: 286 http://deb.debian.org/debian trixie/main i386 libwww-mechanize-perl all 2.18-1 [114 kB] Get: 287 http://deb.debian.org/debian trixie/main i386 libxml-namespacesupport-perl all 1.12-2 [15.1 kB] Get: 288 http://deb.debian.org/debian trixie/main i386 libxml-sax-base-perl all 1.09-3 [20.6 kB] Get: 289 http://deb.debian.org/debian trixie/main i386 libxml-sax-perl all 1.02+dfsg-3 [59.4 kB] Get: 290 http://deb.debian.org/debian trixie/main i386 libxml-libxml-perl i386 2.0207+dfsg+really+2.0134-1+b2 [323 kB] Get: 291 http://deb.debian.org/debian trixie/main i386 liblz1 i386 1.14-1 [39.4 kB] Get: 292 http://deb.debian.org/debian trixie/main i386 plzip i386 1.11-1 [67.5 kB] Get: 293 http://deb.debian.org/debian trixie/main i386 liblzo2-2 i386 2.10-2+b1 [58.0 kB] Get: 294 http://deb.debian.org/debian trixie/main i386 lzop i386 1.04-2 [87.8 kB] Get: 295 http://deb.debian.org/debian trixie/main i386 patchutils i386 0.4.2-1 [79.6 kB] Get: 296 http://deb.debian.org/debian trixie/main i386 t1utils i386 1.41-4 [62.3 kB] Get: 297 http://deb.debian.org/debian trixie/main i386 unzip i386 6.0-28 [166 kB] Get: 298 http://deb.debian.org/debian trixie/main i386 lintian all 2.117.0 [1052 kB] Get: 299 http://deb.debian.org/debian trixie/main i386 libconfig-model-dpkg-perl all 3.004 [173 kB] Get: 300 http://deb.debian.org/debian trixie/main i386 libconvert-binhex-perl all 1.125-3 [27.4 kB] Get: 301 http://deb.debian.org/debian trixie/main i386 libnet-smtp-ssl-perl all 1.04-2 [6548 B] Get: 302 http://deb.debian.org/debian trixie/main i386 libmailtools-perl all 2.21-3 [88.6 kB] Get: 303 http://deb.debian.org/debian trixie/main i386 libmime-tools-perl all 5.514-1 [203 kB] Get: 304 http://deb.debian.org/debian trixie/main i386 libsuitesparseconfig7 i386 1:7.6.1+dfsg-1 [22.5 kB] Get: 305 http://deb.debian.org/debian trixie/main i386 libamd3 i386 1:7.6.1+dfsg-1 [41.4 kB] Get: 306 http://deb.debian.org/debian trixie/main i386 libblas3 i386 3.12.0-3 [140 kB] Get: 307 http://deb.debian.org/debian trixie/main i386 libgfortran5 i386 14-20240201-3 [733 kB] Get: 308 http://deb.debian.org/debian trixie/main i386 liblapack3 i386 3.12.0-3 [2167 kB] Get: 309 http://deb.debian.org/debian trixie/main i386 libarpack2 i386 3.9.1-1+b1 [100 kB] Get: 310 http://deb.debian.org/debian trixie/main i386 libccolamd3 i386 1:7.6.1+dfsg-1 [41.8 kB] Get: 311 http://deb.debian.org/debian trixie/main i386 libcamd3 i386 1:7.6.1+dfsg-1 [39.3 kB] Get: 312 http://deb.debian.org/debian trixie/main i386 libcolamd3 i386 1:7.6.1+dfsg-1 [33.9 kB] Get: 313 http://deb.debian.org/debian trixie/main i386 libcholmod5 i386 1:7.6.1+dfsg-1 [714 kB] Get: 314 http://deb.debian.org/debian trixie/main i386 libsasl2-modules-db i386 2.1.28+dfsg1-4+b1 [20.7 kB] Get: 315 http://deb.debian.org/debian trixie/main i386 libsasl2-2 i386 2.1.28+dfsg1-4+b1 [60.7 kB] Get: 316 http://deb.debian.org/debian trixie/main i386 libldap-2.5-0 i386 2.5.13+dfsg-5+b3 [196 kB] Get: 317 http://deb.debian.org/debian trixie/main i386 libnghttp2-14 i386 1.59.0-1 [82.5 kB] Get: 318 http://deb.debian.org/debian trixie/main i386 libpsl5 i386 0.21.2-1+b1 [59.7 kB] Get: 319 http://deb.debian.org/debian trixie/main i386 librtmp1 i386 2.4+20151223.gitfa8646d.1-2+b2 [64.3 kB] Get: 320 http://deb.debian.org/debian trixie/main i386 libssh2-1 i386 1.11.0-4 [224 kB] Get: 321 http://deb.debian.org/debian trixie/main i386 libcurl3-gnutls i386 8.5.0-2 [454 kB] Get: 322 http://deb.debian.org/debian trixie/main i386 libcxsparse4 i386 1:7.6.1+dfsg-1 [99.2 kB] Get: 323 http://deb.debian.org/debian trixie/main i386 libfftw3-double3 i386 3.3.10-1+b1 [635 kB] Get: 324 http://deb.debian.org/debian trixie/main i386 libfftw3-single3 i386 3.3.10-1+b1 [644 kB] Get: 325 http://deb.debian.org/debian trixie/main i386 libxfixes3 i386 1:6.0.0-2 [23.0 kB] Get: 326 http://deb.debian.org/debian trixie/main i386 libxcursor1 i386 1:1.2.1-1 [42.4 kB] Get: 327 http://deb.debian.org/debian trixie/main i386 libxft2 i386 2.3.6-1+b1 [55.3 kB] Get: 328 http://deb.debian.org/debian trixie/main i386 libxinerama1 i386 2:1.1.4-3 [18.1 kB] Get: 329 http://deb.debian.org/debian trixie/main i386 libfltk1.3 i386 1.3.8-6+b1 [580 kB] Get: 330 http://deb.debian.org/debian trixie/main i386 libglvnd0 i386 1.7.0-1 [43.7 kB] Get: 331 http://deb.debian.org/debian trixie/main i386 libdrm-common all 2.4.120-2 [7688 B] Get: 332 http://deb.debian.org/debian trixie/main i386 libdrm2 i386 2.4.120-2 [41.4 kB] Get: 333 http://deb.debian.org/debian trixie/main i386 libglapi-mesa i386 23.3.5-1 [35.4 kB] Get: 334 http://deb.debian.org/debian trixie/main i386 libx11-xcb1 i386 2:1.8.7-1 [232 kB] Get: 335 http://deb.debian.org/debian trixie/main i386 libxcb-dri2-0 i386 1.15-1 [107 kB] Get: 336 http://deb.debian.org/debian trixie/main i386 libxcb-dri3-0 i386 1.15-1 [107 kB] Get: 337 http://deb.debian.org/debian trixie/main i386 libxcb-glx0 i386 1.15-1 [124 kB] Get: 338 http://deb.debian.org/debian trixie/main i386 libxcb-present0 i386 1.15-1 [106 kB] Get: 339 http://deb.debian.org/debian trixie/main i386 libxcb-randr0 i386 1.15-1 [118 kB] Get: 340 http://deb.debian.org/debian trixie/main i386 libxcb-sync1 i386 1.15-1 [109 kB] Get: 341 http://deb.debian.org/debian trixie/main i386 libxcb-xfixes0 i386 1.15-1 [110 kB] Get: 342 http://deb.debian.org/debian trixie/main i386 libxshmfence1 i386 1.3-1 [8976 B] Get: 343 http://deb.debian.org/debian trixie/main i386 libxxf86vm1 i386 1:1.1.4-1+b2 [21.7 kB] Get: 344 http://deb.debian.org/debian trixie/main i386 libvulkan1 i386 1.3.275.0-1 [141 kB] Get: 345 http://deb.debian.org/debian trixie/main i386 libdrm-amdgpu1 i386 2.4.120-2 [24.4 kB] Get: 346 http://deb.debian.org/debian trixie/main i386 libpciaccess0 i386 0.17-3 [53.6 kB] Get: 347 http://deb.debian.org/debian trixie/main i386 libdrm-intel1 i386 2.4.120-2 [66.5 kB] Get: 348 http://deb.debian.org/debian trixie/main i386 libdrm-nouveau2 i386 2.4.120-2 [20.8 kB] Get: 349 http://deb.debian.org/debian trixie/main i386 libdrm-radeon1 i386 2.4.120-2 [23.0 kB] Get: 350 http://deb.debian.org/debian trixie/main i386 libz3-4 i386 4.8.12-3.1+b2 [7989 kB] Get: 351 http://deb.debian.org/debian trixie/main i386 libllvm17 i386 1:17.0.6-5 [27.7 MB] Get: 352 http://deb.debian.org/debian trixie/main i386 libsensors-config all 1:3.6.0-9 [14.6 kB] Get: 353 http://deb.debian.org/debian trixie/main i386 libsensors5 i386 1:3.6.0-9 [35.4 kB] Get: 354 http://deb.debian.org/debian trixie/main i386 libgl1-mesa-dri i386 23.3.5-1 [8327 kB] Get: 355 http://deb.debian.org/debian trixie/main i386 libglx-mesa0 i386 23.3.5-1 [157 kB] Get: 356 http://deb.debian.org/debian trixie/main i386 libglx0 i386 1.7.0-1 [37.8 kB] Get: 357 http://deb.debian.org/debian trixie/main i386 libgl1 i386 1.7.0-1 [82.0 kB] Get: 358 http://deb.debian.org/debian trixie/main i386 libfltk-gl1.3 i386 1.3.8-6+b1 [62.9 kB] Get: 359 http://deb.debian.org/debian trixie/main i386 libgl2ps1.4 i386 1.4.2+dfsg1-2 [42.0 kB] Get: 360 http://deb.debian.org/debian trixie/main i386 libltdl7 i386 2.4.7-7 [395 kB] Get: 361 http://deb.debian.org/debian trixie/main i386 libglpk40 i386 5.0-1+b1 [420 kB] Get: 362 http://deb.debian.org/debian trixie/main i386 libopengl0 i386 1.7.0-1 [29.3 kB] Get: 363 http://deb.debian.org/debian trixie/main i386 libglu1-mesa i386 9.0.2-1.1 [186 kB] Get: 364 http://deb.debian.org/debian trixie/main i386 libhwy1 i386 1.0.7-8+b1 [580 kB] Get: 365 http://deb.debian.org/debian trixie/main i386 liblcms2-2 i386 2.14-2+b1 [165 kB] Get: 366 http://deb.debian.org/debian trixie/main i386 libjxl0.7 i386 0.7.0-10.2+b1 [896 kB] Get: 367 http://deb.debian.org/debian trixie/main i386 libwmflite-0.2-7 i386 0.2.13-1.1 [78.5 kB] Get: 368 http://deb.debian.org/debian trixie/main i386 libgraphicsmagick-q16-3 i386 1.4+really1.3.42-1+b1 [1258 kB] Get: 369 http://deb.debian.org/debian trixie/main i386 libgraphicsmagick++-q16-12 i386 1.4+really1.3.42-1+b1 [138 kB] Get: 370 http://deb.debian.org/debian trixie/main i386 libcurl4 i386 8.5.0-2 [463 kB] Get: 371 http://deb.debian.org/debian trixie/main i386 libaec0 i386 1.1.3-1 [24.5 kB] Get: 372 http://deb.debian.org/debian trixie/main i386 libsz2 i386 1.1.3-1 [7824 B] Get: 373 http://deb.debian.org/debian trixie/main i386 libhdf5-103-1 i386 1.10.10+repack-3+b1 [1177 kB] Get: 374 http://deb.debian.org/debian trixie/main i386 libasound2-data all 1.2.10-3 [20.7 kB] Get: 375 http://deb.debian.org/debian trixie/main i386 libasound2 i386 1.2.10-3 [394 kB] Get: 376 http://deb.debian.org/debian trixie/main i386 libopus0 i386 1.4-1+b1 [197 kB] Get: 377 http://deb.debian.org/debian trixie/main i386 libsamplerate0 i386 0.2.2-4 [951 kB] Get: 378 http://deb.debian.org/debian trixie/main i386 libjack-jackd2-0 i386 1.9.21~dfsg-3+b1 [315 kB] Get: 379 http://deb.debian.org/debian trixie/main i386 libportaudio2 i386 19.6.0-1.2+b1 [67.3 kB] Get: 380 http://deb.debian.org/debian trixie/main i386 libqhull-r8.0 i386 2020.2-6+b1 [256 kB] Get: 381 http://deb.debian.org/debian trixie/main i386 libqrupdate1 i386 1.1.2-4+b1 [38.1 kB] Get: 382 http://deb.debian.org/debian trixie/main i386 libqscintilla2-qt5-l10n all 2.14.1+dfsg-1 [105 kB] Get: 383 http://deb.debian.org/debian trixie/main i386 shared-mime-info i386 2.4-1 [752 kB] Get: 384 http://deb.debian.org/debian trixie/main i386 libdouble-conversion3 i386 3.3.0-1+b1 [44.9 kB] Get: 385 http://deb.debian.org/debian trixie/main i386 libpcre2-16-0 i386 10.42-4+b1 [244 kB] Get: 386 http://deb.debian.org/debian trixie/main i386 libqt5core5a i386 5.15.10+dfsg-7 [2696 kB] Get: 387 http://deb.debian.org/debian trixie/main i386 libwayland-server0 i386 1.22.0-2.1+b1 [34.8 kB] Get: 388 http://deb.debian.org/debian trixie/main i386 libgbm1 i386 23.3.5-1 [41.4 kB] Get: 389 http://deb.debian.org/debian trixie/main i386 libwayland-client0 i386 1.22.0-2.1+b1 [26.4 kB] Get: 390 http://deb.debian.org/debian trixie/main i386 libegl-mesa0 i386 23.3.5-1 [128 kB] Get: 391 http://deb.debian.org/debian trixie/main i386 libegl1 i386 1.7.0-1 [35.9 kB] Get: 392 http://deb.debian.org/debian trixie/main i386 x11-common all 1:7.7+23 [252 kB] Get: 393 http://deb.debian.org/debian trixie/main i386 libice6 i386 2:1.0.10-1 [60.8 kB] Get: 394 http://deb.debian.org/debian trixie/main i386 libevdev2 i386 1.13.1+dfsg-1 [30.3 kB] Get: 395 http://deb.debian.org/debian trixie/main i386 libmtdev1 i386 1.1.6-1+b1 [22.6 kB] Get: 396 http://deb.debian.org/debian trixie/main i386 libgudev-1.0-0 i386 238-3 [14.8 kB] Get: 397 http://deb.debian.org/debian trixie/main i386 libwacom-common all 2.10.0-1 [62.4 kB] Get: 398 http://deb.debian.org/debian trixie/main i386 libwacom9 i386 2.10.0-1 [23.8 kB] Get: 399 http://deb.debian.org/debian trixie/main i386 libinput-bin i386 1.25.0-1 [24.9 kB] Get: 400 http://deb.debian.org/debian trixie/main i386 libinput10 i386 1.25.0-1 [143 kB] Get: 401 http://deb.debian.org/debian trixie/main i386 libmd4c0 i386 0.4.8-1+b1 [45.2 kB] Get: 402 http://deb.debian.org/debian trixie/main i386 libdbus-1-3 i386 1.14.10-4 [216 kB] Get: 403 http://deb.debian.org/debian trixie/main i386 libqt5dbus5 i386 5.15.10+dfsg-7 [237 kB] Get: 404 http://deb.debian.org/debian trixie/main i386 libqt5network5 i386 5.15.10+dfsg-7 [766 kB] Get: 405 http://deb.debian.org/debian trixie/main i386 libsm6 i386 2:1.2.3-1 [35.7 kB] Get: 406 http://deb.debian.org/debian trixie/main i386 libxcb-icccm4 i386 0.4.1-1.1+b1 [27.5 kB] Get: 407 http://deb.debian.org/debian trixie/main i386 libxcb-util1 i386 0.4.0-1+b1 [23.6 kB] Get: 408 http://deb.debian.org/debian trixie/main i386 libxcb-image0 i386 0.4.0-2+b1 [22.8 kB] Get: 409 http://deb.debian.org/debian trixie/main i386 libxcb-keysyms1 i386 0.4.0-1+b2 [16.7 kB] Get: 410 http://deb.debian.org/debian trixie/main i386 libxcb-render-util0 i386 0.3.9-1+b1 [18.7 kB] Get: 411 http://deb.debian.org/debian trixie/main i386 libxcb-shape0 i386 1.15-1 [106 kB] Get: 412 http://deb.debian.org/debian trixie/main i386 libxcb-xinerama0 i386 1.15-1 [105 kB] Get: 413 http://deb.debian.org/debian trixie/main i386 libxcb-xinput0 i386 1.15-1 [134 kB] Get: 414 http://deb.debian.org/debian trixie/main i386 libxcb-xkb1 i386 1.15-1 [131 kB] Get: 415 http://deb.debian.org/debian trixie/main i386 xkb-data all 2.41-2 [795 kB] Get: 416 http://deb.debian.org/debian trixie/main i386 libxkbcommon0 i386 1.6.0-1 [114 kB] Get: 417 http://deb.debian.org/debian trixie/main i386 libxkbcommon-x11-0 i386 1.6.0-1 [16.8 kB] Get: 418 http://deb.debian.org/debian trixie/main i386 libqt5gui5 i386 5.15.10+dfsg-7 [5972 kB] Get: 419 http://deb.debian.org/debian trixie/main i386 libavahi-common-data i386 0.8-13+b1 [111 kB] Get: 420 http://deb.debian.org/debian trixie/main i386 libavahi-common3 i386 0.8-13+b1 [45.3 kB] Get: 421 http://deb.debian.org/debian trixie/main i386 libavahi-client3 i386 0.8-13+b1 [49.2 kB] Get: 422 http://deb.debian.org/debian trixie/main i386 libcups2 i386 2.4.7-1+b1 [263 kB] Get: 423 http://deb.debian.org/debian trixie/main i386 libqt5widgets5 i386 5.15.10+dfsg-7 [2665 kB] Get: 424 http://deb.debian.org/debian trixie/main i386 libqt5printsupport5 i386 5.15.10+dfsg-7 [220 kB] Get: 425 http://deb.debian.org/debian trixie/main i386 libqscintilla2-qt5-15 i386 2.14.1+dfsg-1+b1 [1196 kB] Get: 426 http://deb.debian.org/debian trixie/main i386 libqt5sql5 i386 5.15.10+dfsg-7 [135 kB] Get: 427 http://deb.debian.org/debian trixie/main i386 libqt5help5 i386 5.15.10-6 [170 kB] Get: 428 http://deb.debian.org/debian trixie/main i386 libqt5xml5 i386 5.15.10+dfsg-7 [135 kB] Get: 429 http://deb.debian.org/debian trixie/main i386 libogg0 i386 1.3.5-3 [24.1 kB] Get: 430 http://deb.debian.org/debian trixie/main i386 libflac12 i386 1.4.3+ds-2+b1 [206 kB] Get: 431 http://deb.debian.org/debian trixie/main i386 libmp3lame0 i386 3.100-6+b2 [362 kB] Get: 432 http://deb.debian.org/debian trixie/main i386 libmpg123-0 i386 1.32.5-1 [150 kB] Get: 433 http://deb.debian.org/debian trixie/main i386 libvorbis0a i386 1.3.7-2 [88.3 kB] Get: 434 http://deb.debian.org/debian trixie/main i386 libvorbisenc2 i386 1.3.7-2 [69.5 kB] Get: 435 http://deb.debian.org/debian trixie/main i386 libsndfile1 i386 1.2.2-1 [222 kB] Get: 436 http://deb.debian.org/debian trixie/main i386 libspqr4 i386 1:7.6.1+dfsg-1 [159 kB] Get: 437 http://deb.debian.org/debian trixie/main i386 libsundials-ida6 i386 6.4.1+dfsg1-3+b3 [153 kB] Get: 438 http://deb.debian.org/debian trixie/main i386 libbtf2 i386 1:7.6.1+dfsg-1 [24.2 kB] Get: 439 http://deb.debian.org/debian trixie/main i386 libklu2 i386 1:7.6.1+dfsg-1 [91.2 kB] Get: 440 http://deb.debian.org/debian trixie/main i386 libfftw3-long3 i386 3.3.10-1+b1 [340 kB] Get: 441 http://deb.debian.org/debian trixie/main i386 libevent-core-2.1-7 i386 2.1.12-stable-8 [139 kB] Get: 442 http://deb.debian.org/debian trixie/main i386 libevent-pthreads-2.1-7 i386 2.1.12-stable-8 [53.7 kB] Get: 443 http://deb.debian.org/debian trixie/main i386 libnl-3-200 i386 3.7.0-0.3 [61.8 kB] Get: 444 http://deb.debian.org/debian trixie/main i386 libnl-route-3-200 i386 3.7.0-0.3 [193 kB] Get: 445 http://deb.debian.org/debian trixie/main i386 libibverbs1 i386 48.0-1.1 [66.2 kB] Get: 446 http://deb.debian.org/debian trixie/main i386 libpsm-infinipath1 i386 3.3+20.604758e7-6.3 [177 kB] Get: 447 http://deb.debian.org/debian trixie/main i386 librdmacm1 i386 48.0-1.1 [75.4 kB] Get: 448 http://deb.debian.org/debian trixie/main i386 libfabric1 i386 1.17.0-3 [538 kB] Get: 449 http://deb.debian.org/debian trixie/main i386 libhwloc15 i386 2.10.0-1+b1 [175 kB] Get: 450 http://deb.debian.org/debian trixie/main i386 libmunge2 i386 0.5.15-4 [20.5 kB] Get: 451 http://deb.debian.org/debian trixie/main i386 libxnvctrl0 i386 535.171.04-1 [13.7 kB] Get: 452 http://deb.debian.org/debian trixie/main i386 ocl-icd-libopencl1 i386 2.3.2-1 [42.5 kB] Get: 453 http://deb.debian.org/debian trixie/main i386 libhwloc-plugins i386 2.10.0-1+b1 [18.4 kB] Get: 454 http://deb.debian.org/debian trixie/main i386 libpmix2 i386 5.0.1-4+b1 [650 kB] Get: 455 http://deb.debian.org/debian trixie/main i386 libopenmpi3 i386 4.1.6-5 [2186 kB] Get: 456 http://deb.debian.org/debian trixie/main i386 libfftw3-mpi3 i386 3.3.10-1+b1 [67.5 kB] Get: 457 http://deb.debian.org/debian trixie/main i386 libhdf5-openmpi-103-1 i386 1.10.10+repack-3+b1 [1230 kB] Get: 458 http://deb.debian.org/debian trixie/main i386 libcombblas2.0.0 i386 2.0.0-3+b1 [283 kB] Get: 459 http://deb.debian.org/debian trixie/main i386 libmetis5 i386 5.1.0.dfsg-7+b1 [175 kB] Get: 460 http://deb.debian.org/debian trixie/main i386 libptscotch-7.0 i386 7.0.4-1+b1 [847 kB] Get: 461 http://deb.debian.org/debian trixie/main i386 libsuperlu-dist8 i386 8.2.1+dfsg1-1 [574 kB] Get: 462 http://deb.debian.org/debian trixie/main i386 libhypre-2.28.0 i386 2.28.0-8 [1465 kB] Get: 463 http://deb.debian.org/debian trixie/main i386 openmpi-common all 4.1.6-5 [168 kB] Get: 464 http://deb.debian.org/debian trixie/main i386 openmpi-bin i386 4.1.6-5 [197 kB] Get: 465 http://deb.debian.org/debian trixie/main i386 mpi-default-bin i386 1.15 [2408 B] Get: 466 http://deb.debian.org/debian trixie/main i386 libscalapack-openmpi2.2 i386 2.2.1-3+b1 [1437 kB] Get: 467 http://deb.debian.org/debian trixie/main i386 libmumps-5.6 i386 5.6.2-2+b1 [1867 kB] Get: 468 http://deb.debian.org/debian trixie/main i386 libsuperlu6 i386 6.0.1+dfsg1-1+b1 [172 kB] Get: 469 http://deb.debian.org/debian trixie/main i386 libumfpack6 i386 1:7.6.1+dfsg-1 [308 kB] Get: 470 http://deb.debian.org/debian trixie/main i386 libpetsc-real3.19 i386 3.19.6+dfsg1-2 [5674 kB] Get: 471 http://deb.debian.org/debian trixie/main i386 libsundials-nvecparallel-petsc6 i386 6.4.1+dfsg1-3+b3 [60.4 kB] Get: 472 http://deb.debian.org/debian trixie/main i386 libsundials-sunmatrix4 i386 6.4.1+dfsg1-3+b3 [112 kB] Get: 473 http://deb.debian.org/debian trixie/main i386 libsundials-sunlinsol3 i386 6.4.1+dfsg1-3+b3 [214 kB] Get: 474 http://deb.debian.org/debian trixie/main i386 libtext-unidecode-perl all 1.30-3 [101 kB] Get: 475 http://deb.debian.org/debian trixie/main i386 texinfo-lib i386 7.1-3 [231 kB] Get: 476 http://deb.debian.org/debian trixie/main i386 tex-common all 6.18 [32.5 kB] Get: 477 http://deb.debian.org/debian trixie/main i386 texinfo all 7.1-3 [1748 kB] Get: 478 http://deb.debian.org/debian trixie/main i386 octave-common all 8.4.0-1 [6368 kB] Get: 479 http://deb.debian.org/debian trixie/main i386 octave i386 8.4.0-1+b1 [10.1 MB] Get: 480 http://deb.debian.org/debian trixie/main i386 libncurses6 i386 6.4+20240113-1 [111 kB] Get: 481 http://deb.debian.org/debian trixie/main i386 libncurses-dev i386 6.4+20240113-1 [380 kB] Get: 482 http://deb.debian.org/debian trixie/main i386 libreadline-dev i386 8.2-3+b1 [164 kB] Get: 483 http://deb.debian.org/debian trixie/main i386 libhdf5-fortran-102 i386 1.10.10+repack-3+b1 [97.9 kB] Get: 484 http://deb.debian.org/debian trixie/main i386 libhdf5-hl-100 i386 1.10.10+repack-3+b1 [74.3 kB] Get: 485 http://deb.debian.org/debian trixie/main i386 libhdf5-hl-fortran-100 i386 1.10.10+repack-3+b1 [41.8 kB] Get: 486 http://deb.debian.org/debian trixie/main i386 libhdf5-cpp-103-1 i386 1.10.10+repack-3+b1 [138 kB] Get: 487 http://deb.debian.org/debian trixie/main i386 libhdf5-hl-cpp-100 i386 1.10.10+repack-3+b1 [21.7 kB] Get: 488 http://deb.debian.org/debian trixie/main i386 zlib1g-dev i386 1:1.3.dfsg-3+b1 [915 kB] Get: 489 http://deb.debian.org/debian trixie/main i386 libjpeg62-turbo-dev i386 1:2.1.5-2+b2 [303 kB] Get: 490 http://deb.debian.org/debian trixie/main i386 libjpeg-dev i386 1:2.1.5-2+b2 [72.1 kB] Get: 491 http://deb.debian.org/debian trixie/main i386 libaec-dev i386 1.1.3-1 [22.4 kB] Get: 492 http://deb.debian.org/debian trixie/main i386 libcurl4-openssl-dev i386 8.5.0-2 [582 kB] Get: 493 http://deb.debian.org/debian trixie/main i386 libssl-dev i386 3.1.5-1 [2502 kB] Get: 494 http://deb.debian.org/debian trixie/main i386 hdf5-helpers i386 1.10.10+repack-3+b1 [23.5 kB] Get: 495 http://deb.debian.org/debian trixie/main i386 libhdf5-dev i386 1.10.10+repack-3+b1 [2773 kB] Get: 496 http://deb.debian.org/debian trixie/main i386 xorg-sgml-doctools all 1:1.11-1.1 [22.1 kB] Get: 497 http://deb.debian.org/debian trixie/main i386 x11proto-dev all 2023.2-1 [598 kB] Get: 498 http://deb.debian.org/debian trixie/main i386 libxau-dev i386 1:1.0.9-1 [23.3 kB] Get: 499 http://deb.debian.org/debian trixie/main i386 libxdmcp-dev i386 1:1.1.2-3 [42.7 kB] Get: 500 http://deb.debian.org/debian trixie/main i386 xtrans-dev all 1.4.0-1 [98.7 kB] Get: 501 http://deb.debian.org/debian trixie/main i386 libpthread-stubs0-dev i386 0.4-1 [5340 B] Get: 502 http://deb.debian.org/debian trixie/main i386 libxcb1-dev i386 1.15-1 [185 kB] Get: 503 http://deb.debian.org/debian trixie/main i386 libx11-dev i386 2:1.8.7-1 [901 kB] Get: 504 http://deb.debian.org/debian trixie/main i386 libglx-dev i386 1.7.0-1 [15.5 kB] Get: 505 http://deb.debian.org/debian trixie/main i386 libgl-dev i386 1.7.0-1 [100 kB] Get: 506 http://deb.debian.org/debian trixie/main i386 libblas-dev i386 3.12.0-3 [152 kB] Get: 507 http://deb.debian.org/debian trixie/main i386 liblapack-dev i386 3.12.0-3 [4400 kB] Get: 508 http://deb.debian.org/debian trixie/main i386 libfftw3-quad3 i386 3.3.10-1+b1 [1798 kB] Get: 509 http://deb.debian.org/debian trixie/main i386 libfftw3-bin i386 3.3.10-1+b1 [49.8 kB] Get: 510 http://deb.debian.org/debian trixie/main i386 libfftw3-dev i386 3.3.10-1+b1 [3200 kB] Get: 511 http://deb.debian.org/debian trixie/main i386 libgfortran-13-dev i386 13.2.0-13 [783 kB] Get: 512 http://deb.debian.org/debian trixie/main i386 gfortran-13-i686-linux-gnu i386 13.2.0-13 [11.1 MB] Get: 513 http://deb.debian.org/debian trixie/main i386 gfortran-13 i386 13.2.0-13 [10.5 kB] Get: 514 http://deb.debian.org/debian trixie/main i386 gfortran-i686-linux-gnu i386 4:13.2.0-7 [1280 B] Get: 515 http://deb.debian.org/debian trixie/main i386 gfortran i386 4:13.2.0-7 [1432 B] Get: 516 http://deb.debian.org/debian trixie/main i386 octave-dev i386 8.4.0-1+b1 [960 kB] Get: 517 http://deb.debian.org/debian trixie/main i386 dh-octave all 1.8.0 [22.7 kB] Get: 518 http://deb.debian.org/debian trixie/main i386 octave-io i386 2.6.4-3+b1 [204 kB] Fetched 218 MB in 7s (32.5 MB/s) debconf: delaying package configuration, since apt-utils is not installed Selecting previously unselected package libpython3.11-minimal:i386. (Reading database ... (Reading database ... 5% (Reading database ... 10% (Reading database ... 15% (Reading database ... 20% (Reading database ... 25% (Reading database ... 30% (Reading database ... 35% (Reading database ... 40% (Reading database ... 45% (Reading database ... 50% (Reading database ... 55% (Reading database ... 60% (Reading database ... 65% (Reading database ... 70% (Reading database ... 75% (Reading database ... 80% (Reading database ... 85% (Reading database ... 90% (Reading database ... 95% (Reading database ... 100% (Reading database ... 19876 files and directories currently installed.) Preparing to unpack .../libpython3.11-minimal_3.11.8-1_i386.deb ... Unpacking libpython3.11-minimal:i386 (3.11.8-1) ... Selecting previously unselected package libexpat1:i386. Preparing to unpack .../libexpat1_2.5.0-2+b2_i386.deb ... Unpacking libexpat1:i386 (2.5.0-2+b2) ... Selecting previously unselected package python3.11-minimal. Preparing to unpack .../python3.11-minimal_3.11.8-1_i386.deb ... Unpacking python3.11-minimal (3.11.8-1) ... Setting up libpython3.11-minimal:i386 (3.11.8-1) ... Setting up libexpat1:i386 (2.5.0-2+b2) ... Setting up python3.11-minimal (3.11.8-1) ... Selecting previously unselected package python3-minimal. (Reading database ... (Reading database ... 5% (Reading database ... 10% (Reading database ... 15% (Reading database ... 20% (Reading database ... 25% (Reading database ... 30% (Reading database ... 35% (Reading database ... 40% (Reading database ... 45% (Reading database ... 50% (Reading database ... 55% (Reading database ... 60% (Reading database ... 65% (Reading database ... 70% (Reading database ... 75% (Reading database ... 80% (Reading database ... 85% (Reading database ... 90% (Reading database ... 95% (Reading database ... 100% (Reading database ... 20193 files and directories currently installed.) Preparing to unpack .../0-python3-minimal_3.11.6-1_i386.deb ... Unpacking python3-minimal (3.11.6-1) ... Selecting previously unselected package media-types. Preparing to unpack .../1-media-types_10.1.0_all.deb ... Unpacking media-types (10.1.0) ... Selecting previously unselected package netbase. Preparing to unpack .../2-netbase_6.4_all.deb ... Unpacking netbase (6.4) ... Selecting previously unselected package tzdata. Preparing to unpack .../3-tzdata_2024a-1_all.deb ... Unpacking tzdata (2024a-1) ... Selecting previously unselected package readline-common. Preparing to unpack .../4-readline-common_8.2-3_all.deb ... Unpacking readline-common (8.2-3) ... Selecting previously unselected package libreadline8:i386. Preparing to unpack .../5-libreadline8_8.2-3+b1_i386.deb ... Unpacking libreadline8:i386 (8.2-3+b1) ... Selecting previously unselected package libpython3.11-stdlib:i386. Preparing to unpack .../6-libpython3.11-stdlib_3.11.8-1_i386.deb ... Unpacking libpython3.11-stdlib:i386 (3.11.8-1) ... Selecting previously unselected package python3.11. Preparing to unpack .../7-python3.11_3.11.8-1_i386.deb ... Unpacking python3.11 (3.11.8-1) ... Selecting previously unselected package libpython3-stdlib:i386. Preparing to unpack .../8-libpython3-stdlib_3.11.6-1_i386.deb ... Unpacking libpython3-stdlib:i386 (3.11.6-1) ... Setting up python3-minimal (3.11.6-1) ... Selecting previously unselected package python3. (Reading database ... (Reading database ... 5% (Reading database ... 10% (Reading database ... 15% (Reading database ... 20% (Reading database ... 25% (Reading database ... 30% (Reading database ... 35% (Reading database ... 40% (Reading database ... 45% (Reading database ... 50% (Reading database ... 55% (Reading database ... 60% (Reading database ... 65% (Reading database ... 70% (Reading database ... 75% (Reading database ... 80% (Reading database ... 85% (Reading database ... 90% (Reading database ... 95% (Reading database ... 100% (Reading database ... 21181 files and directories currently installed.) Preparing to unpack .../000-python3_3.11.6-1_i386.deb ... Unpacking python3 (3.11.6-1) ... Selecting previously unselected package sensible-utils. Preparing to unpack .../001-sensible-utils_0.0.22_all.deb ... Unpacking sensible-utils (0.0.22) ... Selecting previously unselected package openssl. Preparing to unpack .../002-openssl_3.1.5-1_i386.deb ... Unpacking openssl (3.1.5-1) ... Selecting previously unselected package ca-certificates. Preparing to unpack .../003-ca-certificates_20240203_all.deb ... Unpacking ca-certificates (20240203) ... Selecting previously unselected package libmagic-mgc. Preparing to unpack .../004-libmagic-mgc_1%3a5.45-2+b1_i386.deb ... Unpacking libmagic-mgc (1:5.45-2+b1) ... Selecting previously unselected package libmagic1:i386. Preparing to unpack .../005-libmagic1_1%3a5.45-2+b1_i386.deb ... Unpacking libmagic1:i386 (1:5.45-2+b1) ... Selecting previously unselected package file. Preparing to unpack .../006-file_1%3a5.45-2+b1_i386.deb ... Unpacking file (1:5.45-2+b1) ... Selecting previously unselected package gettext-base. Preparing to unpack .../007-gettext-base_0.21-14+b1_i386.deb ... Unpacking gettext-base (0.21-14+b1) ... Selecting previously unselected package libuchardet0:i386. Preparing to unpack .../008-libuchardet0_0.0.8-1+b1_i386.deb ... Unpacking libuchardet0:i386 (0.0.8-1+b1) ... Selecting previously unselected package groff-base. Preparing to unpack .../009-groff-base_1.23.0-3_i386.deb ... Unpacking groff-base (1.23.0-3) ... Selecting previously unselected package bsdextrautils. Preparing to unpack .../010-bsdextrautils_2.39.3-6_i386.deb ... Unpacking bsdextrautils (2.39.3-6) ... Selecting previously unselected package libpipeline1:i386. Preparing to unpack .../011-libpipeline1_1.5.7-1+b2_i386.deb ... Unpacking libpipeline1:i386 (1.5.7-1+b2) ... Selecting previously unselected package man-db. Preparing to unpack .../012-man-db_2.12.0-3_i386.deb ... Unpacking man-db (2.12.0-3) ... Selecting previously unselected package libbsd0:i386. Preparing to unpack .../013-libbsd0_0.12.2-1_i386.deb ... Unpacking libbsd0:i386 (0.12.2-1) ... Selecting previously unselected package libedit2:i386. Preparing to unpack .../014-libedit2_3.1-20230828-1_i386.deb ... Unpacking libedit2:i386 (3.1-20230828-1) ... Selecting previously unselected package libcbor0.10:i386. Preparing to unpack .../015-libcbor0.10_0.10.2-1.1_i386.deb ... Unpacking libcbor0.10:i386 (0.10.2-1.1) ... Selecting previously unselected package libfido2-1:i386. Preparing to unpack .../016-libfido2-1_1.14.0-1_i386.deb ... Unpacking libfido2-1:i386 (1.14.0-1) ... Selecting previously unselected package openssh-client. Preparing to unpack .../017-openssh-client_1%3a9.6p1-4_i386.deb ... Unpacking openssh-client (1:9.6p1-4) ... Selecting previously unselected package ucf. Preparing to unpack .../018-ucf_3.0043+nmu1_all.deb ... Moving old data out of the way Unpacking ucf (3.0043+nmu1) ... Selecting previously unselected package aglfn. Preparing to unpack .../019-aglfn_1.7+git20191031.4036a9c-2_all.deb ... Unpacking aglfn (1.7+git20191031.4036a9c-2) ... Selecting previously unselected package m4. Preparing to unpack .../020-m4_1.4.19-4_i386.deb ... Unpacking m4 (1.4.19-4) ... Selecting previously unselected package autoconf. Preparing to unpack .../021-autoconf_2.71-3_all.deb ... Unpacking autoconf (2.71-3) ... Selecting previously unselected package autotools-dev. Preparing to unpack .../022-autotools-dev_20220109.1_all.deb ... Unpacking autotools-dev (20220109.1) ... Selecting previously unselected package automake. Preparing to unpack .../023-automake_1%3a1.16.5-1.3_all.deb ... Unpacking automake (1:1.16.5-1.3) ... Selecting previously unselected package autopoint. Preparing to unpack .../024-autopoint_0.21-14_all.deb ... Unpacking autopoint (0.21-14) ... Selecting previously unselected package libcapture-tiny-perl. Preparing to unpack .../025-libcapture-tiny-perl_0.48-2_all.deb ... Unpacking libcapture-tiny-perl (0.48-2) ... Selecting previously unselected package libparams-util-perl. Preparing to unpack .../026-libparams-util-perl_1.102-2+b2_i386.deb ... Unpacking libparams-util-perl (1.102-2+b2) ... Selecting previously unselected package libsub-install-perl. Preparing to unpack .../027-libsub-install-perl_0.929-1_all.deb ... Unpacking libsub-install-perl (0.929-1) ... Selecting previously unselected package libdata-optlist-perl. Preparing to unpack .../028-libdata-optlist-perl_0.114-1_all.deb ... Unpacking libdata-optlist-perl (0.114-1) ... Selecting previously unselected package libb-hooks-op-check-perl:i386. Preparing to unpack .../029-libb-hooks-op-check-perl_0.22-2+b2_i386.deb ... Unpacking libb-hooks-op-check-perl:i386 (0.22-2+b2) ... Selecting previously unselected package libdynaloader-functions-perl. Preparing to unpack .../030-libdynaloader-functions-perl_0.003-3_all.deb ... Unpacking libdynaloader-functions-perl (0.003-3) ... Selecting previously unselected package libdevel-callchecker-perl:i386. Preparing to unpack .../031-libdevel-callchecker-perl_0.008-2+b1_i386.deb ... Unpacking libdevel-callchecker-perl:i386 (0.008-2+b1) ... Selecting previously unselected package libparams-classify-perl:i386. Preparing to unpack .../032-libparams-classify-perl_0.015-2+b2_i386.deb ... Unpacking libparams-classify-perl:i386 (0.015-2+b2) ... Selecting previously unselected package libmodule-runtime-perl. Preparing to unpack .../033-libmodule-runtime-perl_0.016-2_all.deb ... Unpacking libmodule-runtime-perl (0.016-2) ... Selecting previously unselected package libtry-tiny-perl. Preparing to unpack .../034-libtry-tiny-perl_0.31-2_all.deb ... Unpacking libtry-tiny-perl (0.31-2) ... Selecting previously unselected package libmodule-implementation-perl. Preparing to unpack .../035-libmodule-implementation-perl_0.09-2_all.deb ... Unpacking libmodule-implementation-perl (0.09-2) ... Selecting previously unselected package libpackage-stash-perl. Preparing to unpack .../036-libpackage-stash-perl_0.40-1_all.deb ... Unpacking libpackage-stash-perl (0.40-1) ... Selecting previously unselected package libclass-load-perl. Preparing to unpack .../037-libclass-load-perl_0.25-2_all.deb ... Unpacking libclass-load-perl (0.25-2) ... Selecting previously unselected package libio-stringy-perl. Preparing to unpack .../038-libio-stringy-perl_2.111-3_all.deb ... Unpacking libio-stringy-perl (2.111-3) ... Selecting previously unselected package libparams-validate-perl:i386. Preparing to unpack .../039-libparams-validate-perl_1.31-2+b1_i386.deb ... Unpacking libparams-validate-perl:i386 (1.31-2+b1) ... Selecting previously unselected package libsub-exporter-perl. Preparing to unpack .../040-libsub-exporter-perl_0.990-1_all.deb ... Unpacking libsub-exporter-perl (0.990-1) ... Selecting previously unselected package libgetopt-long-descriptive-perl. Preparing to unpack .../041-libgetopt-long-descriptive-perl_0.111-1_all.deb ... Unpacking libgetopt-long-descriptive-perl (0.111-1) ... Selecting previously unselected package libio-tiecombine-perl. Preparing to unpack .../042-libio-tiecombine-perl_1.005-3_all.deb ... Unpacking libio-tiecombine-perl (1.005-3) ... Selecting previously unselected package libmodule-pluggable-perl. Preparing to unpack .../043-libmodule-pluggable-perl_5.2-5_all.deb ... Unpacking libmodule-pluggable-perl (5.2-5) ... Selecting previously unselected package libstring-rewriteprefix-perl. Preparing to unpack .../044-libstring-rewriteprefix-perl_0.009-1_all.deb ... Unpacking libstring-rewriteprefix-perl (0.009-1) ... Selecting previously unselected package libapp-cmd-perl. Preparing to unpack .../045-libapp-cmd-perl_0.336-1_all.deb ... Unpacking libapp-cmd-perl (0.336-1) ... Selecting previously unselected package libboolean-perl. Preparing to unpack .../046-libboolean-perl_0.46-3_all.deb ... Unpacking libboolean-perl (0.46-3) ... Selecting previously unselected package libsub-uplevel-perl. Preparing to unpack .../047-libsub-uplevel-perl_0.2800-3_all.deb ... Unpacking libsub-uplevel-perl (0.2800-3) ... Selecting previously unselected package libtest-exception-perl. Preparing to unpack .../048-libtest-exception-perl_0.43-3_all.deb ... Unpacking libtest-exception-perl (0.43-3) ... Selecting previously unselected package libcarp-assert-more-perl. Preparing to unpack .../049-libcarp-assert-more-perl_2.4.0-1_all.deb ... Unpacking libcarp-assert-more-perl (2.4.0-1) ... Selecting previously unselected package libfile-which-perl. Preparing to unpack .../050-libfile-which-perl_1.27-2_all.deb ... Unpacking libfile-which-perl (1.27-2) ... Selecting previously unselected package libfile-homedir-perl. Preparing to unpack .../051-libfile-homedir-perl_1.006-2_all.deb ... Unpacking libfile-homedir-perl (1.006-2) ... Selecting previously unselected package libclone-choose-perl. Preparing to unpack .../052-libclone-choose-perl_0.010-2_all.deb ... Unpacking libclone-choose-perl (0.010-2) ... Selecting previously unselected package libhash-merge-perl. Preparing to unpack .../053-libhash-merge-perl_0.302-1_all.deb ... Unpacking libhash-merge-perl (0.302-1) ... Selecting previously unselected package libjson-perl. Preparing to unpack .../054-libjson-perl_4.10000-1_all.deb ... Unpacking libjson-perl (4.10000-1) ... Selecting previously unselected package libexporter-tiny-perl. Preparing to unpack .../055-libexporter-tiny-perl_1.006002-1_all.deb ... Unpacking libexporter-tiny-perl (1.006002-1) ... Selecting previously unselected package liblist-moreutils-xs-perl. Preparing to unpack .../056-liblist-moreutils-xs-perl_0.430-3+b2_i386.deb ... Unpacking liblist-moreutils-xs-perl (0.430-3+b2) ... Selecting previously unselected package liblist-moreutils-perl. Preparing to unpack .../057-liblist-moreutils-perl_0.430-2_all.deb ... Unpacking liblist-moreutils-perl (0.430-2) ... Selecting previously unselected package liblog-log4perl-perl. Preparing to unpack .../058-liblog-log4perl-perl_1.57-1_all.deb ... Unpacking liblog-log4perl-perl (1.57-1) ... Selecting previously unselected package libmouse-perl. Preparing to unpack .../059-libmouse-perl_2.5.10-1+b4_i386.deb ... Unpacking libmouse-perl (2.5.10-1+b4) ... Selecting previously unselected package libmousex-nativetraits-perl. Preparing to unpack .../060-libmousex-nativetraits-perl_1.09-3_all.deb ... Unpacking libmousex-nativetraits-perl (1.09-3) ... Selecting previously unselected package libmousex-strictconstructor-perl. Preparing to unpack .../061-libmousex-strictconstructor-perl_0.02-3_all.deb ... Unpacking libmousex-strictconstructor-perl (0.02-3) ... Selecting previously unselected package libparse-recdescent-perl. Preparing to unpack .../062-libparse-recdescent-perl_1.967015+dfsg-4_all.deb ... Unpacking libparse-recdescent-perl (1.967015+dfsg-4) ... Selecting previously unselected package libpath-tiny-perl. Preparing to unpack .../063-libpath-tiny-perl_0.144-1_all.deb ... Unpacking libpath-tiny-perl (0.144-1) ... Selecting previously unselected package libpod-pom-perl. Preparing to unpack .../064-libpod-pom-perl_2.01-4_all.deb ... Unpacking libpod-pom-perl (2.01-4) ... Selecting previously unselected package libregexp-common-perl. Preparing to unpack .../065-libregexp-common-perl_2017060201-3_all.deb ... Unpacking libregexp-common-perl (2017060201-3) ... Selecting previously unselected package libyaml-tiny-perl. Preparing to unpack .../066-libyaml-tiny-perl_1.74-1_all.deb ... Unpacking libyaml-tiny-perl (1.74-1) ... Selecting previously unselected package libconfig-model-perl. Preparing to unpack .../067-libconfig-model-perl_2.153-3_all.deb ... Unpacking libconfig-model-perl (2.153-3) ... Selecting previously unselected package libyaml-pp-perl. Preparing to unpack .../068-libyaml-pp-perl_0.38.0-1_all.deb ... Unpacking libyaml-pp-perl (0.38.0-1) ... Selecting previously unselected package cme. Preparing to unpack .../069-cme_1.040-1_all.deb ... Unpacking cme (1.040-1) ... Selecting previously unselected package libdebhelper-perl. Preparing to unpack .../070-libdebhelper-perl_13.15.3_all.deb ... Unpacking libdebhelper-perl (13.15.3) ... Selecting previously unselected package libtool. Preparing to unpack .../071-libtool_2.4.7-7_all.deb ... Unpacking libtool (2.4.7-7) ... Selecting previously unselected package dh-autoreconf. Preparing to unpack .../072-dh-autoreconf_20_all.deb ... Unpacking dh-autoreconf (20) ... Selecting previously unselected package libarchive-zip-perl. Preparing to unpack .../073-libarchive-zip-perl_1.68-1_all.deb ... Unpacking libarchive-zip-perl (1.68-1) ... Selecting previously unselected package libsub-override-perl. Preparing to unpack .../074-libsub-override-perl_0.10-1_all.deb ... Unpacking libsub-override-perl (0.10-1) ... Selecting previously unselected package libfile-stripnondeterminism-perl. Preparing to unpack .../075-libfile-stripnondeterminism-perl_1.13.1-1_all.deb ... Unpacking libfile-stripnondeterminism-perl (1.13.1-1) ... Selecting previously unselected package dh-strip-nondeterminism. Preparing to unpack .../076-dh-strip-nondeterminism_1.13.1-1_all.deb ... Unpacking dh-strip-nondeterminism (1.13.1-1) ... Selecting previously unselected package libelf1:i386. Preparing to unpack .../077-libelf1_0.190-1+b1_i386.deb ... Unpacking libelf1:i386 (0.190-1+b1) ... Selecting previously unselected package dwz. Preparing to unpack .../078-dwz_0.15-1_i386.deb ... Unpacking dwz (0.15-1) ... Selecting previously unselected package libicu72:i386. Preparing to unpack .../079-libicu72_72.1-4+b1_i386.deb ... Unpacking libicu72:i386 (72.1-4+b1) ... Selecting previously unselected package libxml2:i386. Preparing to unpack .../080-libxml2_2.9.14+dfsg-1.3+b2_i386.deb ... Unpacking libxml2:i386 (2.9.14+dfsg-1.3+b2) ... Selecting previously unselected package gettext. Preparing to unpack .../081-gettext_0.21-14+b1_i386.deb ... Unpacking gettext (0.21-14+b1) ... Selecting previously unselected package intltool-debian. Preparing to unpack .../082-intltool-debian_0.35.0+20060710.6_all.deb ... Unpacking intltool-debian (0.35.0+20060710.6) ... Selecting previously unselected package po-debconf. Preparing to unpack .../083-po-debconf_1.0.21+nmu1_all.deb ... Unpacking po-debconf (1.0.21+nmu1) ... Selecting previously unselected package debhelper. Preparing to unpack .../084-debhelper_13.15.3_all.deb ... Unpacking debhelper (13.15.3) ... Selecting previously unselected package gnuplot-data. Preparing to unpack .../085-gnuplot-data_6.0.0+dfsg1-1_all.deb ... Unpacking gnuplot-data (6.0.0+dfsg1-1) ... Selecting previously unselected package libbrotli1:i386. Preparing to unpack .../086-libbrotli1_1.1.0-2+b3_i386.deb ... Unpacking libbrotli1:i386 (1.1.0-2+b3) ... Selecting previously unselected package libpng16-16:i386. Preparing to unpack .../087-libpng16-16_1.6.43-1_i386.deb ... Unpacking libpng16-16:i386 (1.6.43-1) ... Selecting previously unselected package libfreetype6:i386. Preparing to unpack .../088-libfreetype6_2.13.2+dfsg-1+b1_i386.deb ... Unpacking libfreetype6:i386 (2.13.2+dfsg-1+b1) ... Selecting previously unselected package fonts-dejavu-mono. Preparing to unpack .../089-fonts-dejavu-mono_2.37-8_all.deb ... Unpacking fonts-dejavu-mono (2.37-8) ... Selecting previously unselected package fonts-dejavu-core. Preparing to unpack .../090-fonts-dejavu-core_2.37-8_all.deb ... Unpacking fonts-dejavu-core (2.37-8) ... Selecting previously unselected package fonts-freefont-otf. Preparing to unpack .../091-fonts-freefont-otf_20211204+svn4273-2_all.deb ... Unpacking fonts-freefont-otf (20211204+svn4273-2) ... Selecting previously unselected package fontconfig-config. Preparing to unpack .../092-fontconfig-config_2.15.0-1.1_i386.deb ... Unpacking fontconfig-config (2.15.0-1.1) ... Selecting previously unselected package libfontconfig1:i386. Preparing to unpack .../093-libfontconfig1_2.15.0-1.1_i386.deb ... Unpacking libfontconfig1:i386 (2.15.0-1.1) ... Selecting previously unselected package libpixman-1-0:i386. Preparing to unpack .../094-libpixman-1-0_0.42.2-1+b1_i386.deb ... Unpacking libpixman-1-0:i386 (0.42.2-1+b1) ... Selecting previously unselected package libxau6:i386. Preparing to unpack .../095-libxau6_1%3a1.0.9-1_i386.deb ... Unpacking libxau6:i386 (1:1.0.9-1) ... Selecting previously unselected package libxdmcp6:i386. Preparing to unpack .../096-libxdmcp6_1%3a1.1.2-3_i386.deb ... Unpacking libxdmcp6:i386 (1:1.1.2-3) ... Selecting previously unselected package libxcb1:i386. Preparing to unpack .../097-libxcb1_1.15-1_i386.deb ... Unpacking libxcb1:i386 (1.15-1) ... Selecting previously unselected package libx11-data. Preparing to unpack .../098-libx11-data_2%3a1.8.7-1_all.deb ... Unpacking libx11-data (2:1.8.7-1) ... Selecting previously unselected package libx11-6:i386. Preparing to unpack .../099-libx11-6_2%3a1.8.7-1_i386.deb ... Unpacking libx11-6:i386 (2:1.8.7-1) ... Selecting previously unselected package libxcb-render0:i386. Preparing to unpack .../100-libxcb-render0_1.15-1_i386.deb ... Unpacking libxcb-render0:i386 (1.15-1) ... Selecting previously unselected package libxcb-shm0:i386. Preparing to unpack .../101-libxcb-shm0_1.15-1_i386.deb ... Unpacking libxcb-shm0:i386 (1.15-1) ... Selecting previously unselected package libxext6:i386. Preparing to unpack .../102-libxext6_2%3a1.3.4-1+b1_i386.deb ... Unpacking libxext6:i386 (2:1.3.4-1+b1) ... Selecting previously unselected package libxrender1:i386. Preparing to unpack .../103-libxrender1_1%3a0.9.10-1.1_i386.deb ... Unpacking libxrender1:i386 (1:0.9.10-1.1) ... Selecting previously unselected package libcairo2:i386. Preparing to unpack .../104-libcairo2_1.18.0-1+b1_i386.deb ... Unpacking libcairo2:i386 (1.18.0-1+b1) ... Selecting previously unselected package libaom3:i386. Preparing to unpack .../105-libaom3_3.8.2-2_i386.deb ... Unpacking libaom3:i386 (3.8.2-2) ... Selecting previously unselected package libdav1d7:i386. Preparing to unpack .../106-libdav1d7_1.4.1-1_i386.deb ... Unpacking libdav1d7:i386 (1.4.1-1) ... Selecting previously unselected package libabsl20220623:i386. Preparing to unpack .../107-libabsl20220623_20220623.1-3_i386.deb ... Unpacking libabsl20220623:i386 (20220623.1-3) ... Selecting previously unselected package libgav1-1:i386. Preparing to unpack .../108-libgav1-1_0.18.0-1+b1_i386.deb ... Unpacking libgav1-1:i386 (0.18.0-1+b1) ... Selecting previously unselected package librav1e0:i386. Preparing to unpack .../109-librav1e0_0.7.1-2_i386.deb ... Unpacking librav1e0:i386 (0.7.1-2) ... Selecting previously unselected package libsharpyuv0:i386. Preparing to unpack .../110-libsharpyuv0_1.3.2-0.4_i386.deb ... Unpacking libsharpyuv0:i386 (1.3.2-0.4) ... Selecting previously unselected package libjpeg62-turbo:i386. Preparing to unpack .../111-libjpeg62-turbo_1%3a2.1.5-2+b2_i386.deb ... Unpacking libjpeg62-turbo:i386 (1:2.1.5-2+b2) ... Selecting previously unselected package libyuv0:i386. Preparing to unpack .../112-libyuv0_0.0~git202401110.af6ac82-1_i386.deb ... Unpacking libyuv0:i386 (0.0~git202401110.af6ac82-1) ... Selecting previously unselected package libavif16:i386. Preparing to unpack .../113-libavif16_1.0.4-1_i386.deb ... Unpacking libavif16:i386 (1.0.4-1) ... Selecting previously unselected package libheif-plugin-dav1d:i386. Preparing to unpack .../114-libheif-plugin-dav1d_1.17.6-1_i386.deb ... Unpacking libheif-plugin-dav1d:i386 (1.17.6-1) ... Selecting previously unselected package libde265-0:i386. Preparing to unpack .../115-libde265-0_1.0.15-1_i386.deb ... Unpacking libde265-0:i386 (1.0.15-1) ... Selecting previously unselected package libheif-plugin-libde265:i386. Preparing to unpack .../116-libheif-plugin-libde265_1.17.6-1_i386.deb ... Unpacking libheif-plugin-libde265:i386 (1.17.6-1) ... Selecting previously unselected package libheif1:i386. Preparing to unpack .../117-libheif1_1.17.6-1_i386.deb ... Unpacking libheif1:i386 (1.17.6-1) ... Selecting previously unselected package libdeflate0:i386. Preparing to unpack .../118-libdeflate0_1.20-1_i386.deb ... Unpacking libdeflate0:i386 (1.20-1) ... Selecting previously unselected package libjbig0:i386. Preparing to unpack .../119-libjbig0_2.1-6.1+b1_i386.deb ... Unpacking libjbig0:i386 (2.1-6.1+b1) ... Selecting previously unselected package liblerc4:i386. Preparing to unpack .../120-liblerc4_4.0.0+ds-4+b1_i386.deb ... Unpacking liblerc4:i386 (4.0.0+ds-4+b1) ... Selecting previously unselected package libwebp7:i386. Preparing to unpack .../121-libwebp7_1.3.2-0.4_i386.deb ... Unpacking libwebp7:i386 (1.3.2-0.4) ... Selecting previously unselected package libtiff6:i386. Preparing to unpack .../122-libtiff6_4.5.1+git230720-4_i386.deb ... Unpacking libtiff6:i386 (4.5.1+git230720-4) ... Selecting previously unselected package libxpm4:i386. Preparing to unpack .../123-libxpm4_1%3a3.5.17-1_i386.deb ... Unpacking libxpm4:i386 (1:3.5.17-1) ... Selecting previously unselected package libgd3:i386. Preparing to unpack .../124-libgd3_2.3.3-9+b1_i386.deb ... Unpacking libgd3:i386 (2.3.3-9+b1) ... Selecting previously unselected package libglib2.0-0:i386. Preparing to unpack .../125-libglib2.0-0_2.78.4-1_i386.deb ... Unpacking libglib2.0-0:i386 (2.78.4-1) ... Selecting previously unselected package liblua5.4-0:i386. Preparing to unpack .../126-liblua5.4-0_5.4.6-3_i386.deb ... Unpacking liblua5.4-0:i386 (5.4.6-3) ... Selecting previously unselected package fontconfig. Preparing to unpack .../127-fontconfig_2.15.0-1.1_i386.deb ... Unpacking fontconfig (2.15.0-1.1) ... Selecting previously unselected package libfribidi0:i386. Preparing to unpack .../128-libfribidi0_1.0.13-3+b1_i386.deb ... Unpacking libfribidi0:i386 (1.0.13-3+b1) ... Selecting previously unselected package libgraphite2-3:i386. Preparing to unpack .../129-libgraphite2-3_1.3.14-2_i386.deb ... Unpacking libgraphite2-3:i386 (1.3.14-2) ... Selecting previously unselected package libharfbuzz0b:i386. Preparing to unpack .../130-libharfbuzz0b_8.3.0-2_i386.deb ... Unpacking libharfbuzz0b:i386 (8.3.0-2) ... Selecting previously unselected package libthai-data. Preparing to unpack .../131-libthai-data_0.1.29-2_all.deb ... Unpacking libthai-data (0.1.29-2) ... Selecting previously unselected package libdatrie1:i386. Preparing to unpack .../132-libdatrie1_0.2.13-3_i386.deb ... Unpacking libdatrie1:i386 (0.2.13-3) ... Selecting previously unselected package libthai0:i386. Preparing to unpack .../133-libthai0_0.1.29-2_i386.deb ... Unpacking libthai0:i386 (0.1.29-2) ... Selecting previously unselected package libpango-1.0-0:i386. Preparing to unpack .../134-libpango-1.0-0_1.52.0+ds-1_i386.deb ... Unpacking libpango-1.0-0:i386 (1.52.0+ds-1) ... Selecting previously unselected package libpangoft2-1.0-0:i386. Preparing to unpack .../135-libpangoft2-1.0-0_1.52.0+ds-1_i386.deb ... Unpacking libpangoft2-1.0-0:i386 (1.52.0+ds-1) ... Selecting previously unselected package libpangocairo-1.0-0:i386. Preparing to unpack .../136-libpangocairo-1.0-0_1.52.0+ds-1_i386.deb ... Unpacking libpangocairo-1.0-0:i386 (1.52.0+ds-1) ... Selecting previously unselected package libwebpmux3:i386. Preparing to unpack .../137-libwebpmux3_1.3.2-0.4_i386.deb ... Unpacking libwebpmux3:i386 (1.3.2-0.4) ... Selecting previously unselected package gnuplot-nox. Preparing to unpack .../138-gnuplot-nox_6.0.0+dfsg1-1_i386.deb ... Unpacking gnuplot-nox (6.0.0+dfsg1-1) ... Selecting previously unselected package dh-octave-autopkgtest. Preparing to unpack .../139-dh-octave-autopkgtest_1.8.0_all.deb ... Unpacking dh-octave-autopkgtest (1.8.0) ... Selecting previously unselected package libapt-pkg-perl. Preparing to unpack .../140-libapt-pkg-perl_0.1.40+b3_i386.deb ... Unpacking libapt-pkg-perl (0.1.40+b3) ... Selecting previously unselected package libarray-intspan-perl. Preparing to unpack .../141-libarray-intspan-perl_2.004-2_all.deb ... Unpacking libarray-intspan-perl (2.004-2) ... Selecting previously unselected package libyaml-0-2:i386. Preparing to unpack .../142-libyaml-0-2_0.2.5-1_i386.deb ... Unpacking libyaml-0-2:i386 (0.2.5-1) ... Selecting previously unselected package libyaml-libyaml-perl. Preparing to unpack .../143-libyaml-libyaml-perl_0.89+ds-1_i386.deb ... Unpacking libyaml-libyaml-perl (0.89+ds-1) ... Selecting previously unselected package libconfig-model-backend-yaml-perl. Preparing to unpack .../144-libconfig-model-backend-yaml-perl_2.134-2_all.deb ... Unpacking libconfig-model-backend-yaml-perl (2.134-2) ... Selecting previously unselected package libexporter-lite-perl. Preparing to unpack .../145-libexporter-lite-perl_0.09-2_all.deb ... Unpacking libexporter-lite-perl (0.09-2) ... Selecting previously unselected package libencode-locale-perl. Preparing to unpack .../146-libencode-locale-perl_1.05-3_all.deb ... Unpacking libencode-locale-perl (1.05-3) ... Selecting previously unselected package libtimedate-perl. Preparing to unpack .../147-libtimedate-perl_2.3300-2_all.deb ... Unpacking libtimedate-perl (2.3300-2) ... Selecting previously unselected package libhttp-date-perl. Preparing to unpack .../148-libhttp-date-perl_6.06-1_all.deb ... Unpacking libhttp-date-perl (6.06-1) ... Selecting previously unselected package libfile-listing-perl. Preparing to unpack .../149-libfile-listing-perl_6.16-1_all.deb ... Unpacking libfile-listing-perl (6.16-1) ... Selecting previously unselected package libhtml-tagset-perl. Preparing to unpack .../150-libhtml-tagset-perl_3.24-1_all.deb ... Unpacking libhtml-tagset-perl (3.24-1) ... Selecting previously unselected package liburi-perl. Preparing to unpack .../151-liburi-perl_5.27-1_all.deb ... Unpacking liburi-perl (5.27-1) ... Selecting previously unselected package libhtml-parser-perl:i386. Preparing to unpack .../152-libhtml-parser-perl_3.81-1+b1_i386.deb ... Unpacking libhtml-parser-perl:i386 (3.81-1+b1) ... Selecting previously unselected package libhtml-tree-perl. Preparing to unpack .../153-libhtml-tree-perl_5.07-3_all.deb ... Unpacking libhtml-tree-perl (5.07-3) ... Selecting previously unselected package libclone-perl:i386. Preparing to unpack .../154-libclone-perl_0.46-1+b1_i386.deb ... Unpacking libclone-perl:i386 (0.46-1+b1) ... Selecting previously unselected package libio-html-perl. Preparing to unpack .../155-libio-html-perl_1.004-3_all.deb ... Unpacking libio-html-perl (1.004-3) ... Selecting previously unselected package liblwp-mediatypes-perl. Preparing to unpack .../156-liblwp-mediatypes-perl_6.04-2_all.deb ... Unpacking liblwp-mediatypes-perl (6.04-2) ... Selecting previously unselected package libhttp-message-perl. Preparing to unpack .../157-libhttp-message-perl_6.45-1_all.deb ... Unpacking libhttp-message-perl (6.45-1) ... Selecting previously unselected package libhttp-cookies-perl. Preparing to unpack .../158-libhttp-cookies-perl_6.11-1_all.deb ... Unpacking libhttp-cookies-perl (6.11-1) ... Selecting previously unselected package libhttp-negotiate-perl. Preparing to unpack .../159-libhttp-negotiate-perl_6.01-2_all.deb ... Unpacking libhttp-negotiate-perl (6.01-2) ... Selecting previously unselected package perl-openssl-defaults:i386. Preparing to unpack .../160-perl-openssl-defaults_7+b1_i386.deb ... Unpacking perl-openssl-defaults:i386 (7+b1) ... Selecting previously unselected package libnet-ssleay-perl:i386. Preparing to unpack .../161-libnet-ssleay-perl_1.94-1_i386.deb ... Unpacking libnet-ssleay-perl:i386 (1.94-1) ... Selecting previously unselected package libio-socket-ssl-perl. Preparing to unpack .../162-libio-socket-ssl-perl_2.085-1_all.deb ... Unpacking libio-socket-ssl-perl (2.085-1) ... Selecting previously unselected package libnet-http-perl. Preparing to unpack .../163-libnet-http-perl_6.23-1_all.deb ... Unpacking libnet-http-perl (6.23-1) ... Selecting previously unselected package liblwp-protocol-https-perl. Preparing to unpack .../164-liblwp-protocol-https-perl_6.14-1_all.deb ... Unpacking liblwp-protocol-https-perl (6.14-1) ... Selecting previously unselected package libwww-robotrules-perl. Preparing to unpack .../165-libwww-robotrules-perl_6.02-1_all.deb ... Unpacking libwww-robotrules-perl (6.02-1) ... Selecting previously unselected package libwww-perl. Preparing to unpack .../166-libwww-perl_6.77-1_all.deb ... Unpacking libwww-perl (6.77-1) ... Selecting previously unselected package liberror-perl. Preparing to unpack .../167-liberror-perl_0.17029-2_all.deb ... Unpacking liberror-perl (0.17029-2) ... Selecting previously unselected package libparse-debcontrol-perl. Preparing to unpack .../168-libparse-debcontrol-perl_2.005-6_all.deb ... Unpacking libparse-debcontrol-perl (2.005-6) ... Selecting previously unselected package libsoftware-copyright-perl. Preparing to unpack .../169-libsoftware-copyright-perl_0.012-2_all.deb ... Unpacking libsoftware-copyright-perl (0.012-2) ... Selecting previously unselected package libalgorithm-c3-perl. Preparing to unpack .../170-libalgorithm-c3-perl_0.11-2_all.deb ... Unpacking libalgorithm-c3-perl (0.11-2) ... Selecting previously unselected package libclass-c3-perl. Preparing to unpack .../171-libclass-c3-perl_0.35-2_all.deb ... Unpacking libclass-c3-perl (0.35-2) ... Selecting previously unselected package libmro-compat-perl. Preparing to unpack .../172-libmro-compat-perl_0.15-2_all.deb ... Unpacking libmro-compat-perl (0.15-2) ... Selecting previously unselected package libdata-section-perl. Preparing to unpack .../173-libdata-section-perl_0.200008-1_all.deb ... Unpacking libdata-section-perl (0.200008-1) ... Selecting previously unselected package libtext-template-perl. Preparing to unpack .../174-libtext-template-perl_1.61-1_all.deb ... Unpacking libtext-template-perl (1.61-1) ... Selecting previously unselected package libsoftware-license-perl. Preparing to unpack .../175-libsoftware-license-perl_0.104006-1_all.deb ... Unpacking libsoftware-license-perl (0.104006-1) ... Selecting previously unselected package libsoftware-licensemoreutils-perl. Preparing to unpack .../176-libsoftware-licensemoreutils-perl_1.009-1_all.deb ... Unpacking libsoftware-licensemoreutils-perl (1.009-1) ... Selecting previously unselected package libsort-versions-perl. Preparing to unpack .../177-libsort-versions-perl_1.62-3_all.deb ... Unpacking libsort-versions-perl (1.62-3) ... Selecting previously unselected package libtext-reform-perl. Preparing to unpack .../178-libtext-reform-perl_1.20-5_all.deb ... Unpacking libtext-reform-perl (1.20-5) ... Selecting previously unselected package libtext-autoformat-perl. Preparing to unpack .../179-libtext-autoformat-perl_1.750000-2_all.deb ... Unpacking libtext-autoformat-perl (1.750000-2) ... Selecting previously unselected package libtext-levenshtein-damerau-perl. Preparing to unpack .../180-libtext-levenshtein-damerau-perl_0.41-3_all.deb ... Unpacking libtext-levenshtein-damerau-perl (0.41-3) ... Selecting previously unselected package libtoml-tiny-perl. Preparing to unpack .../181-libtoml-tiny-perl_0.16-1_all.deb ... Unpacking libtoml-tiny-perl (0.16-1) ... Selecting previously unselected package libindirect-perl. Preparing to unpack .../182-libindirect-perl_0.39-2+b2_i386.deb ... Unpacking libindirect-perl (0.39-2+b2) ... Selecting previously unselected package libxs-parse-keyword-perl. Preparing to unpack .../183-libxs-parse-keyword-perl_0.39-1+b1_i386.deb ... Unpacking libxs-parse-keyword-perl (0.39-1+b1) ... Selecting previously unselected package libxs-parse-sublike-perl:i386. Preparing to unpack .../184-libxs-parse-sublike-perl_0.21-2+b1_i386.deb ... Unpacking libxs-parse-sublike-perl:i386 (0.21-2+b1) ... Selecting previously unselected package libobject-pad-perl. Preparing to unpack .../185-libobject-pad-perl_0.808-1+b1_i386.deb ... Unpacking libobject-pad-perl (0.808-1+b1) ... Selecting previously unselected package libfeature-compat-class-perl. Preparing to unpack .../186-libfeature-compat-class-perl_0.06-1_all.deb ... Unpacking libfeature-compat-class-perl (0.06-1) ... Selecting previously unselected package libsyntax-keyword-try-perl. Preparing to unpack .../187-libsyntax-keyword-try-perl_0.29-1+b1_i386.deb ... Unpacking libsyntax-keyword-try-perl (0.29-1+b1) ... Selecting previously unselected package libfeature-compat-try-perl. Preparing to unpack .../188-libfeature-compat-try-perl_0.05-1_all.deb ... Unpacking libfeature-compat-try-perl (0.05-1) ... Selecting previously unselected package libio-interactive-perl. Preparing to unpack .../189-libio-interactive-perl_1.025-1_all.deb ... Unpacking libio-interactive-perl (1.025-1) ... Selecting previously unselected package liblog-any-perl. Preparing to unpack .../190-liblog-any-perl_1.717-1_all.deb ... Unpacking liblog-any-perl (1.717-1) ... Selecting previously unselected package liblog-any-adapter-screen-perl. Preparing to unpack .../191-liblog-any-adapter-screen-perl_0.140-2_all.deb ... Unpacking liblog-any-adapter-screen-perl (0.140-2) ... Selecting previously unselected package libsub-exporter-progressive-perl. Preparing to unpack .../192-libsub-exporter-progressive-perl_0.001013-3_all.deb ... Unpacking libsub-exporter-progressive-perl (0.001013-3) ... Selecting previously unselected package libvariable-magic-perl. Preparing to unpack .../193-libvariable-magic-perl_0.63-1+b2_i386.deb ... Unpacking libvariable-magic-perl (0.63-1+b2) ... Selecting previously unselected package libb-hooks-endofscope-perl. Preparing to unpack .../194-libb-hooks-endofscope-perl_0.28-1_all.deb ... Unpacking libb-hooks-endofscope-perl (0.28-1) ... Selecting previously unselected package libsub-identify-perl. Preparing to unpack .../195-libsub-identify-perl_0.14-3+b1_i386.deb ... Unpacking libsub-identify-perl (0.14-3+b1) ... Selecting previously unselected package libsub-name-perl:i386. Preparing to unpack .../196-libsub-name-perl_0.27-1+b1_i386.deb ... Unpacking libsub-name-perl:i386 (0.27-1+b1) ... Selecting previously unselected package libnamespace-clean-perl. Preparing to unpack .../197-libnamespace-clean-perl_0.27-2_all.deb ... Unpacking libnamespace-clean-perl (0.27-2) ... Selecting previously unselected package libnumber-compare-perl. Preparing to unpack .../198-libnumber-compare-perl_0.03-3_all.deb ... Unpacking libnumber-compare-perl (0.03-3) ... Selecting previously unselected package libtext-glob-perl. Preparing to unpack .../199-libtext-glob-perl_0.11-3_all.deb ... Unpacking libtext-glob-perl (0.11-3) ... Selecting previously unselected package libpath-iterator-rule-perl. Preparing to unpack .../200-libpath-iterator-rule-perl_1.015-2_all.deb ... Unpacking libpath-iterator-rule-perl (1.015-2) ... Selecting previously unselected package libpod-parser-perl. Preparing to unpack .../201-libpod-parser-perl_1.67-1_all.deb ... Adding 'diversion of /usr/bin/podselect to /usr/bin/podselect.bundled by libpod-parser-perl' Adding 'diversion of /usr/share/man/man1/podselect.1.gz to /usr/share/man/man1/podselect.bundled.1.gz by libpod-parser-perl' Unpacking libpod-parser-perl (1.67-1) ... Selecting previously unselected package libpod-constants-perl. Preparing to unpack .../202-libpod-constants-perl_0.19-2_all.deb ... Unpacking libpod-constants-perl (0.19-2) ... Selecting previously unselected package libset-intspan-perl. Preparing to unpack .../203-libset-intspan-perl_1.19-3_all.deb ... Unpacking libset-intspan-perl (1.19-3) ... Selecting previously unselected package libstring-copyright-perl. Preparing to unpack .../204-libstring-copyright-perl_0.003014-1_all.deb ... Unpacking libstring-copyright-perl (0.003014-1) ... Selecting previously unselected package libstring-escape-perl. Preparing to unpack .../205-libstring-escape-perl_2010.002-3_all.deb ... Unpacking libstring-escape-perl (2010.002-3) ... Selecting previously unselected package libregexp-pattern-license-perl. Preparing to unpack .../206-libregexp-pattern-license-perl_3.11.0-1_all.deb ... Unpacking libregexp-pattern-license-perl (3.11.0-1) ... Selecting previously unselected package libregexp-pattern-perl. Preparing to unpack .../207-libregexp-pattern-perl_0.2.14-2_all.deb ... Unpacking libregexp-pattern-perl (0.2.14-2) ... Selecting previously unselected package libstring-license-perl. Preparing to unpack .../208-libstring-license-perl_0.0.9-2_all.deb ... Unpacking libstring-license-perl (0.0.9-2) ... Selecting previously unselected package licensecheck. Preparing to unpack .../209-licensecheck_3.3.9-1_all.deb ... Unpacking licensecheck (3.3.9-1) ... Selecting previously unselected package diffstat. Preparing to unpack .../210-diffstat_1.66-1_i386.deb ... Unpacking diffstat (1.66-1) ... Selecting previously unselected package libassuan0:i386. Preparing to unpack .../211-libassuan0_2.5.6-1_i386.deb ... Unpacking libassuan0:i386 (2.5.6-1) ... Selecting previously unselected package gpgconf. Preparing to unpack .../212-gpgconf_2.2.40-1.1+b1_i386.deb ... Unpacking gpgconf (2.2.40-1.1+b1) ... Selecting previously unselected package gpg. Preparing to unpack .../213-gpg_2.2.40-1.1+b1_i386.deb ... Unpacking gpg (2.2.40-1.1+b1) ... Selecting previously unselected package iso-codes. Preparing to unpack .../214-iso-codes_4.16.0-1_all.deb ... Unpacking iso-codes (4.16.0-1) ... Selecting previously unselected package libberkeleydb-perl:i386. Preparing to unpack .../215-libberkeleydb-perl_0.64-2+b2_i386.deb ... Unpacking libberkeleydb-perl:i386 (0.64-2+b2) ... Selecting previously unselected package libclass-xsaccessor-perl. Preparing to unpack .../216-libclass-xsaccessor-perl_1.19-4+b2_i386.deb ... Unpacking libclass-xsaccessor-perl (1.19-4+b2) ... Selecting previously unselected package libconfig-tiny-perl. Preparing to unpack .../217-libconfig-tiny-perl_2.30-1_all.deb ... Unpacking libconfig-tiny-perl (2.30-1) ... Selecting previously unselected package libconst-fast-perl. Preparing to unpack .../218-libconst-fast-perl_0.014-2_all.deb ... Unpacking libconst-fast-perl (0.014-2) ... Selecting previously unselected package libcpanel-json-xs-perl:i386. Preparing to unpack .../219-libcpanel-json-xs-perl_4.37-1+b1_i386.deb ... Unpacking libcpanel-json-xs-perl:i386 (4.37-1+b1) ... Selecting previously unselected package libaliased-perl. Preparing to unpack .../220-libaliased-perl_0.34-3_all.deb ... Unpacking libaliased-perl (0.34-3) ... Selecting previously unselected package libclass-data-inheritable-perl. Preparing to unpack .../221-libclass-data-inheritable-perl_0.08-3_all.deb ... Unpacking libclass-data-inheritable-perl (0.08-3) ... Selecting previously unselected package libdevel-stacktrace-perl. Preparing to unpack .../222-libdevel-stacktrace-perl_2.0500-1_all.deb ... Unpacking libdevel-stacktrace-perl (2.0500-1) ... Selecting previously unselected package libexception-class-perl. Preparing to unpack .../223-libexception-class-perl_1.45-1_all.deb ... Unpacking libexception-class-perl (1.45-1) ... Selecting previously unselected package libiterator-perl. Preparing to unpack .../224-libiterator-perl_0.03+ds1-2_all.deb ... Unpacking libiterator-perl (0.03+ds1-2) ... Selecting previously unselected package libiterator-util-perl. Preparing to unpack .../225-libiterator-util-perl_0.02+ds1-2_all.deb ... Unpacking libiterator-util-perl (0.02+ds1-2) ... Selecting previously unselected package libdata-dpath-perl. Preparing to unpack .../226-libdata-dpath-perl_0.59-1_all.deb ... Unpacking libdata-dpath-perl (0.59-1) ... Selecting previously unselected package libnet-domain-tld-perl. Preparing to unpack .../227-libnet-domain-tld-perl_1.75-3_all.deb ... Unpacking libnet-domain-tld-perl (1.75-3) ... Selecting previously unselected package libdata-validate-domain-perl. Preparing to unpack .../228-libdata-validate-domain-perl_0.10-1.1_all.deb ... Unpacking libdata-validate-domain-perl (0.10-1.1) ... Selecting previously unselected package libnet-ipv6addr-perl. Preparing to unpack .../229-libnet-ipv6addr-perl_1.02-1_all.deb ... Unpacking libnet-ipv6addr-perl (1.02-1) ... Selecting previously unselected package libnet-netmask-perl. Preparing to unpack .../230-libnet-netmask-perl_2.0002-2_all.deb ... Unpacking libnet-netmask-perl (2.0002-2) ... Selecting previously unselected package libnetaddr-ip-perl. Preparing to unpack .../231-libnetaddr-ip-perl_4.079+dfsg-2+b2_i386.deb ... Unpacking libnetaddr-ip-perl (4.079+dfsg-2+b2) ... Selecting previously unselected package libdata-validate-ip-perl. Preparing to unpack .../232-libdata-validate-ip-perl_0.31-1_all.deb ... Unpacking libdata-validate-ip-perl (0.31-1) ... Selecting previously unselected package libdata-validate-uri-perl. Preparing to unpack .../233-libdata-validate-uri-perl_0.07-3_all.deb ... Unpacking libdata-validate-uri-perl (0.07-3) ... Selecting previously unselected package libdevel-size-perl. Preparing to unpack .../234-libdevel-size-perl_0.83-2+b2_i386.deb ... Unpacking libdevel-size-perl (0.83-2+b2) ... Selecting previously unselected package libemail-address-xs-perl. Preparing to unpack .../235-libemail-address-xs-perl_1.05-1+b2_i386.deb ... Unpacking libemail-address-xs-perl (1.05-1+b2) ... Selecting previously unselected package libipc-system-simple-perl. Preparing to unpack .../236-libipc-system-simple-perl_1.30-2_all.deb ... Unpacking libipc-system-simple-perl (1.30-2) ... Selecting previously unselected package libfile-basedir-perl. Preparing to unpack .../237-libfile-basedir-perl_0.09-2_all.deb ... Unpacking libfile-basedir-perl (0.09-2) ... Selecting previously unselected package libfile-find-rule-perl. Preparing to unpack .../238-libfile-find-rule-perl_0.34-3_all.deb ... Unpacking libfile-find-rule-perl (0.34-3) ... Selecting previously unselected package libio-string-perl. Preparing to unpack .../239-libio-string-perl_1.08-4_all.deb ... Unpacking libio-string-perl (1.08-4) ... Selecting previously unselected package libfont-ttf-perl. Preparing to unpack .../240-libfont-ttf-perl_1.06-2_all.deb ... Unpacking libfont-ttf-perl (1.06-2) ... Selecting previously unselected package libhtml-html5-entities-perl. Preparing to unpack .../241-libhtml-html5-entities-perl_0.004-3_all.deb ... Unpacking libhtml-html5-entities-perl (0.004-3) ... Selecting previously unselected package libhtml-tokeparser-simple-perl. Preparing to unpack .../242-libhtml-tokeparser-simple-perl_3.16-4_all.deb ... Unpacking libhtml-tokeparser-simple-perl (3.16-4) ... Selecting previously unselected package libipc-run3-perl. Preparing to unpack .../243-libipc-run3-perl_0.049-1_all.deb ... Unpacking libipc-run3-perl (0.049-1) ... Selecting previously unselected package libjson-maybexs-perl. Preparing to unpack .../244-libjson-maybexs-perl_1.004005-1_all.deb ... Unpacking libjson-maybexs-perl (1.004005-1) ... Selecting previously unselected package liblist-compare-perl. Preparing to unpack .../245-liblist-compare-perl_0.55-2_all.deb ... Unpacking liblist-compare-perl (0.55-2) ... Selecting previously unselected package liblist-someutils-perl. Preparing to unpack .../246-liblist-someutils-perl_0.59-1_all.deb ... Unpacking liblist-someutils-perl (0.59-1) ... Selecting previously unselected package liblist-utilsby-perl. Preparing to unpack .../247-liblist-utilsby-perl_0.12-2_all.deb ... Unpacking liblist-utilsby-perl (0.12-2) ... Selecting previously unselected package libmldbm-perl. Preparing to unpack .../248-libmldbm-perl_2.05-4_all.deb ... Unpacking libmldbm-perl (2.05-4) ... Selecting previously unselected package libclass-method-modifiers-perl. Preparing to unpack .../249-libclass-method-modifiers-perl_2.15-1_all.deb ... Unpacking libclass-method-modifiers-perl (2.15-1) ... Selecting previously unselected package libimport-into-perl. Preparing to unpack .../250-libimport-into-perl_1.002005-2_all.deb ... Unpacking libimport-into-perl (1.002005-2) ... Selecting previously unselected package librole-tiny-perl. Preparing to unpack .../251-librole-tiny-perl_2.002004-1_all.deb ... Unpacking librole-tiny-perl (2.002004-1) ... Selecting previously unselected package libsub-quote-perl. Preparing to unpack .../252-libsub-quote-perl_2.006008-1_all.deb ... Unpacking libsub-quote-perl (2.006008-1) ... Selecting previously unselected package libmoo-perl. Preparing to unpack .../253-libmoo-perl_2.005005-1_all.deb ... Unpacking libmoo-perl (2.005005-1) ... Selecting previously unselected package libstrictures-perl. Preparing to unpack .../254-libstrictures-perl_2.000006-1_all.deb ... Unpacking libstrictures-perl (2.000006-1) ... Selecting previously unselected package libmoox-aliases-perl. Preparing to unpack .../255-libmoox-aliases-perl_0.001006-2_all.deb ... Unpacking libmoox-aliases-perl (0.001006-2) ... Selecting previously unselected package libperlio-gzip-perl. Preparing to unpack .../256-libperlio-gzip-perl_0.20-1+b2_i386.deb ... Unpacking libperlio-gzip-perl (0.20-1+b2) ... Selecting previously unselected package libperlio-utf8-strict-perl. Preparing to unpack .../257-libperlio-utf8-strict-perl_0.010-1+b1_i386.deb ... Unpacking libperlio-utf8-strict-perl (0.010-1+b1) ... Selecting previously unselected package libproc-processtable-perl:i386. Preparing to unpack .../258-libproc-processtable-perl_0.636-1+b1_i386.deb ... Unpacking libproc-processtable-perl:i386 (0.636-1+b1) ... Selecting previously unselected package libregexp-wildcards-perl. Preparing to unpack .../259-libregexp-wildcards-perl_1.05-3_all.deb ... Unpacking libregexp-wildcards-perl (1.05-3) ... Selecting previously unselected package libsereal-decoder-perl. Preparing to unpack .../260-libsereal-decoder-perl_5.004+ds-1+b1_i386.deb ... Unpacking libsereal-decoder-perl (5.004+ds-1+b1) ... Selecting previously unselected package libsereal-encoder-perl. Preparing to unpack .../261-libsereal-encoder-perl_5.004+ds-1+b1_i386.deb ... Unpacking libsereal-encoder-perl (5.004+ds-1+b1) ... Selecting previously unselected package libterm-readkey-perl. Preparing to unpack .../262-libterm-readkey-perl_2.38-2+b2_i386.deb ... Unpacking libterm-readkey-perl (2.38-2+b2) ... Selecting previously unselected package libtext-levenshteinxs-perl. Preparing to unpack .../263-libtext-levenshteinxs-perl_0.03-5+b2_i386.deb ... Unpacking libtext-levenshteinxs-perl (0.03-5+b2) ... Selecting previously unselected package libmarkdown2:i386. Preparing to unpack .../264-libmarkdown2_2.2.7-2+b1_i386.deb ... Unpacking libmarkdown2:i386 (2.2.7-2+b1) ... Selecting previously unselected package libtext-markdown-discount-perl. Preparing to unpack .../265-libtext-markdown-discount-perl_0.16-1+b1_i386.deb ... Unpacking libtext-markdown-discount-perl (0.16-1+b1) ... Selecting previously unselected package libdata-messagepack-perl. Preparing to unpack .../266-libdata-messagepack-perl_1.02-1+b2_i386.deb ... Unpacking libdata-messagepack-perl (1.02-1+b2) ... Selecting previously unselected package libtext-xslate-perl:i386. Preparing to unpack .../267-libtext-xslate-perl_3.5.9-1+b3_i386.deb ... Unpacking libtext-xslate-perl:i386 (3.5.9-1+b3) ... Selecting previously unselected package libtime-duration-perl. Preparing to unpack .../268-libtime-duration-perl_1.21-2_all.deb ... Unpacking libtime-duration-perl (1.21-2) ... Selecting previously unselected package libtime-moment-perl. Preparing to unpack .../269-libtime-moment-perl_0.44-2+b2_i386.deb ... Unpacking libtime-moment-perl (0.44-2+b2) ... Selecting previously unselected package libunicode-utf8-perl. Preparing to unpack .../270-libunicode-utf8-perl_0.62-2+b1_i386.deb ... Unpacking libunicode-utf8-perl (0.62-2+b1) ... Selecting previously unselected package libcgi-pm-perl. Preparing to unpack .../271-libcgi-pm-perl_4.64-1_all.deb ... Unpacking libcgi-pm-perl (4.64-1) ... Selecting previously unselected package libhtml-form-perl. Preparing to unpack .../272-libhtml-form-perl_6.11-1_all.deb ... Unpacking libhtml-form-perl (6.11-1) ... Selecting previously unselected package libwww-mechanize-perl. Preparing to unpack .../273-libwww-mechanize-perl_2.18-1_all.deb ... Unpacking libwww-mechanize-perl (2.18-1) ... Selecting previously unselected package libxml-namespacesupport-perl. Preparing to unpack .../274-libxml-namespacesupport-perl_1.12-2_all.deb ... Unpacking libxml-namespacesupport-perl (1.12-2) ... Selecting previously unselected package libxml-sax-base-perl. Preparing to unpack .../275-libxml-sax-base-perl_1.09-3_all.deb ... Unpacking libxml-sax-base-perl (1.09-3) ... Selecting previously unselected package libxml-sax-perl. Preparing to unpack .../276-libxml-sax-perl_1.02+dfsg-3_all.deb ... Unpacking libxml-sax-perl (1.02+dfsg-3) ... Selecting previously unselected package libxml-libxml-perl. Preparing to unpack .../277-libxml-libxml-perl_2.0207+dfsg+really+2.0134-1+b2_i386.deb ... Unpacking libxml-libxml-perl (2.0207+dfsg+really+2.0134-1+b2) ... Selecting previously unselected package liblz1:i386. Preparing to unpack .../278-liblz1_1.14-1_i386.deb ... Unpacking liblz1:i386 (1.14-1) ... Selecting previously unselected package plzip. Preparing to unpack .../279-plzip_1.11-1_i386.deb ... Unpacking plzip (1.11-1) ... Selecting previously unselected package liblzo2-2:i386. Preparing to unpack .../280-liblzo2-2_2.10-2+b1_i386.deb ... Unpacking liblzo2-2:i386 (2.10-2+b1) ... Selecting previously unselected package lzop. Preparing to unpack .../281-lzop_1.04-2_i386.deb ... Unpacking lzop (1.04-2) ... Selecting previously unselected package patchutils. Preparing to unpack .../282-patchutils_0.4.2-1_i386.deb ... Unpacking patchutils (0.4.2-1) ... Selecting previously unselected package t1utils. Preparing to unpack .../283-t1utils_1.41-4_i386.deb ... Unpacking t1utils (1.41-4) ... Selecting previously unselected package unzip. Preparing to unpack .../284-unzip_6.0-28_i386.deb ... Unpacking unzip (6.0-28) ... Selecting previously unselected package lintian. Preparing to unpack .../285-lintian_2.117.0_all.deb ... Unpacking lintian (2.117.0) ... Selecting previously unselected package libconfig-model-dpkg-perl. Preparing to unpack .../286-libconfig-model-dpkg-perl_3.004_all.deb ... Unpacking libconfig-model-dpkg-perl (3.004) ... Selecting previously unselected package libconvert-binhex-perl. Preparing to unpack .../287-libconvert-binhex-perl_1.125-3_all.deb ... Unpacking libconvert-binhex-perl (1.125-3) ... Selecting previously unselected package libnet-smtp-ssl-perl. Preparing to unpack .../288-libnet-smtp-ssl-perl_1.04-2_all.deb ... Unpacking libnet-smtp-ssl-perl (1.04-2) ... Selecting previously unselected package libmailtools-perl. Preparing to unpack .../289-libmailtools-perl_2.21-3_all.deb ... Unpacking libmailtools-perl (2.21-3) ... Selecting previously unselected package libmime-tools-perl. Preparing to unpack .../290-libmime-tools-perl_5.514-1_all.deb ... Unpacking libmime-tools-perl (5.514-1) ... Selecting previously unselected package libsuitesparseconfig7:i386. Preparing to unpack .../291-libsuitesparseconfig7_1%3a7.6.1+dfsg-1_i386.deb ... Unpacking libsuitesparseconfig7:i386 (1:7.6.1+dfsg-1) ... Selecting previously unselected package libamd3:i386. Preparing to unpack .../292-libamd3_1%3a7.6.1+dfsg-1_i386.deb ... Unpacking libamd3:i386 (1:7.6.1+dfsg-1) ... Selecting previously unselected package libblas3:i386. Preparing to unpack .../293-libblas3_3.12.0-3_i386.deb ... Unpacking libblas3:i386 (3.12.0-3) ... Selecting previously unselected package libgfortran5:i386. Preparing to unpack .../294-libgfortran5_14-20240201-3_i386.deb ... Unpacking libgfortran5:i386 (14-20240201-3) ... Selecting previously unselected package liblapack3:i386. Preparing to unpack .../295-liblapack3_3.12.0-3_i386.deb ... Unpacking liblapack3:i386 (3.12.0-3) ... Selecting previously unselected package libarpack2:i386. Preparing to unpack .../296-libarpack2_3.9.1-1+b1_i386.deb ... Unpacking libarpack2:i386 (3.9.1-1+b1) ... Selecting previously unselected package libccolamd3:i386. Preparing to unpack .../297-libccolamd3_1%3a7.6.1+dfsg-1_i386.deb ... Unpacking libccolamd3:i386 (1:7.6.1+dfsg-1) ... Selecting previously unselected package libcamd3:i386. Preparing to unpack .../298-libcamd3_1%3a7.6.1+dfsg-1_i386.deb ... Unpacking libcamd3:i386 (1:7.6.1+dfsg-1) ... Selecting previously unselected package libcolamd3:i386. Preparing to unpack .../299-libcolamd3_1%3a7.6.1+dfsg-1_i386.deb ... Unpacking libcolamd3:i386 (1:7.6.1+dfsg-1) ... Selecting previously unselected package libcholmod5:i386. Preparing to unpack .../300-libcholmod5_1%3a7.6.1+dfsg-1_i386.deb ... Unpacking libcholmod5:i386 (1:7.6.1+dfsg-1) ... Selecting previously unselected package libsasl2-modules-db:i386. Preparing to unpack .../301-libsasl2-modules-db_2.1.28+dfsg1-4+b1_i386.deb ... Unpacking libsasl2-modules-db:i386 (2.1.28+dfsg1-4+b1) ... Selecting previously unselected package libsasl2-2:i386. Preparing to unpack .../302-libsasl2-2_2.1.28+dfsg1-4+b1_i386.deb ... Unpacking libsasl2-2:i386 (2.1.28+dfsg1-4+b1) ... Selecting previously unselected package libldap-2.5-0:i386. Preparing to unpack .../303-libldap-2.5-0_2.5.13+dfsg-5+b3_i386.deb ... Unpacking libldap-2.5-0:i386 (2.5.13+dfsg-5+b3) ... Selecting previously unselected package libnghttp2-14:i386. Preparing to unpack .../304-libnghttp2-14_1.59.0-1_i386.deb ... Unpacking libnghttp2-14:i386 (1.59.0-1) ... Selecting previously unselected package libpsl5:i386. Preparing to unpack .../305-libpsl5_0.21.2-1+b1_i386.deb ... Unpacking libpsl5:i386 (0.21.2-1+b1) ... Selecting previously unselected package librtmp1:i386. Preparing to unpack .../306-librtmp1_2.4+20151223.gitfa8646d.1-2+b2_i386.deb ... Unpacking librtmp1:i386 (2.4+20151223.gitfa8646d.1-2+b2) ... Selecting previously unselected package libssh2-1:i386. Preparing to unpack .../307-libssh2-1_1.11.0-4_i386.deb ... Unpacking libssh2-1:i386 (1.11.0-4) ... Selecting previously unselected package libcurl3-gnutls:i386. Preparing to unpack .../308-libcurl3-gnutls_8.5.0-2_i386.deb ... Unpacking libcurl3-gnutls:i386 (8.5.0-2) ... Selecting previously unselected package libcxsparse4:i386. Preparing to unpack .../309-libcxsparse4_1%3a7.6.1+dfsg-1_i386.deb ... Unpacking libcxsparse4:i386 (1:7.6.1+dfsg-1) ... Selecting previously unselected package libfftw3-double3:i386. Preparing to unpack .../310-libfftw3-double3_3.3.10-1+b1_i386.deb ... Unpacking libfftw3-double3:i386 (3.3.10-1+b1) ... Selecting previously unselected package libfftw3-single3:i386. Preparing to unpack .../311-libfftw3-single3_3.3.10-1+b1_i386.deb ... Unpacking libfftw3-single3:i386 (3.3.10-1+b1) ... Selecting previously unselected package libxfixes3:i386. Preparing to unpack .../312-libxfixes3_1%3a6.0.0-2_i386.deb ... Unpacking libxfixes3:i386 (1:6.0.0-2) ... Selecting previously unselected package libxcursor1:i386. Preparing to unpack .../313-libxcursor1_1%3a1.2.1-1_i386.deb ... Unpacking libxcursor1:i386 (1:1.2.1-1) ... Selecting previously unselected package libxft2:i386. Preparing to unpack .../314-libxft2_2.3.6-1+b1_i386.deb ... Unpacking libxft2:i386 (2.3.6-1+b1) ... Selecting previously unselected package libxinerama1:i386. Preparing to unpack .../315-libxinerama1_2%3a1.1.4-3_i386.deb ... Unpacking libxinerama1:i386 (2:1.1.4-3) ... Selecting previously unselected package libfltk1.3:i386. Preparing to unpack .../316-libfltk1.3_1.3.8-6+b1_i386.deb ... Unpacking libfltk1.3:i386 (1.3.8-6+b1) ... Selecting previously unselected package libglvnd0:i386. Preparing to unpack .../317-libglvnd0_1.7.0-1_i386.deb ... Unpacking libglvnd0:i386 (1.7.0-1) ... Selecting previously unselected package libdrm-common. Preparing to unpack .../318-libdrm-common_2.4.120-2_all.deb ... Unpacking libdrm-common (2.4.120-2) ... Selecting previously unselected package libdrm2:i386. Preparing to unpack .../319-libdrm2_2.4.120-2_i386.deb ... Unpacking libdrm2:i386 (2.4.120-2) ... Selecting previously unselected package libglapi-mesa:i386. Preparing to unpack .../320-libglapi-mesa_23.3.5-1_i386.deb ... Unpacking libglapi-mesa:i386 (23.3.5-1) ... Selecting previously unselected package libx11-xcb1:i386. Preparing to unpack .../321-libx11-xcb1_2%3a1.8.7-1_i386.deb ... Unpacking libx11-xcb1:i386 (2:1.8.7-1) ... Selecting previously unselected package libxcb-dri2-0:i386. Preparing to unpack .../322-libxcb-dri2-0_1.15-1_i386.deb ... Unpacking libxcb-dri2-0:i386 (1.15-1) ... Selecting previously unselected package libxcb-dri3-0:i386. Preparing to unpack .../323-libxcb-dri3-0_1.15-1_i386.deb ... Unpacking libxcb-dri3-0:i386 (1.15-1) ... Selecting previously unselected package libxcb-glx0:i386. Preparing to unpack .../324-libxcb-glx0_1.15-1_i386.deb ... Unpacking libxcb-glx0:i386 (1.15-1) ... Selecting previously unselected package libxcb-present0:i386. Preparing to unpack .../325-libxcb-present0_1.15-1_i386.deb ... Unpacking libxcb-present0:i386 (1.15-1) ... Selecting previously unselected package libxcb-randr0:i386. Preparing to unpack .../326-libxcb-randr0_1.15-1_i386.deb ... Unpacking libxcb-randr0:i386 (1.15-1) ... Selecting previously unselected package libxcb-sync1:i386. Preparing to unpack .../327-libxcb-sync1_1.15-1_i386.deb ... Unpacking libxcb-sync1:i386 (1.15-1) ... Selecting previously unselected package libxcb-xfixes0:i386. Preparing to unpack .../328-libxcb-xfixes0_1.15-1_i386.deb ... Unpacking libxcb-xfixes0:i386 (1.15-1) ... Selecting previously unselected package libxshmfence1:i386. Preparing to unpack .../329-libxshmfence1_1.3-1_i386.deb ... Unpacking libxshmfence1:i386 (1.3-1) ... Selecting previously unselected package libxxf86vm1:i386. Preparing to unpack .../330-libxxf86vm1_1%3a1.1.4-1+b2_i386.deb ... Unpacking libxxf86vm1:i386 (1:1.1.4-1+b2) ... Selecting previously unselected package libvulkan1:i386. Preparing to unpack .../331-libvulkan1_1.3.275.0-1_i386.deb ... Unpacking libvulkan1:i386 (1.3.275.0-1) ... Selecting previously unselected package libdrm-amdgpu1:i386. Preparing to unpack .../332-libdrm-amdgpu1_2.4.120-2_i386.deb ... Unpacking libdrm-amdgpu1:i386 (2.4.120-2) ... Selecting previously unselected package libpciaccess0:i386. Preparing to unpack .../333-libpciaccess0_0.17-3_i386.deb ... Unpacking libpciaccess0:i386 (0.17-3) ... Selecting previously unselected package libdrm-intel1:i386. Preparing to unpack .../334-libdrm-intel1_2.4.120-2_i386.deb ... Unpacking libdrm-intel1:i386 (2.4.120-2) ... Selecting previously unselected package libdrm-nouveau2:i386. Preparing to unpack .../335-libdrm-nouveau2_2.4.120-2_i386.deb ... Unpacking libdrm-nouveau2:i386 (2.4.120-2) ... Selecting previously unselected package libdrm-radeon1:i386. Preparing to unpack .../336-libdrm-radeon1_2.4.120-2_i386.deb ... Unpacking libdrm-radeon1:i386 (2.4.120-2) ... Selecting previously unselected package libz3-4:i386. Preparing to unpack .../337-libz3-4_4.8.12-3.1+b2_i386.deb ... Unpacking libz3-4:i386 (4.8.12-3.1+b2) ... Selecting previously unselected package libllvm17:i386. Preparing to unpack .../338-libllvm17_1%3a17.0.6-5_i386.deb ... Unpacking libllvm17:i386 (1:17.0.6-5) ... Selecting previously unselected package libsensors-config. Preparing to unpack .../339-libsensors-config_1%3a3.6.0-9_all.deb ... Unpacking libsensors-config (1:3.6.0-9) ... Selecting previously unselected package libsensors5:i386. Preparing to unpack .../340-libsensors5_1%3a3.6.0-9_i386.deb ... Unpacking libsensors5:i386 (1:3.6.0-9) ... Selecting previously unselected package libgl1-mesa-dri:i386. Preparing to unpack .../341-libgl1-mesa-dri_23.3.5-1_i386.deb ... Unpacking libgl1-mesa-dri:i386 (23.3.5-1) ... Selecting previously unselected package libglx-mesa0:i386. Preparing to unpack .../342-libglx-mesa0_23.3.5-1_i386.deb ... Unpacking libglx-mesa0:i386 (23.3.5-1) ... Selecting previously unselected package libglx0:i386. Preparing to unpack .../343-libglx0_1.7.0-1_i386.deb ... Unpacking libglx0:i386 (1.7.0-1) ... Selecting previously unselected package libgl1:i386. Preparing to unpack .../344-libgl1_1.7.0-1_i386.deb ... Unpacking libgl1:i386 (1.7.0-1) ... Selecting previously unselected package libfltk-gl1.3:i386. Preparing to unpack .../345-libfltk-gl1.3_1.3.8-6+b1_i386.deb ... Unpacking libfltk-gl1.3:i386 (1.3.8-6+b1) ... Selecting previously unselected package libgl2ps1.4. Preparing to unpack .../346-libgl2ps1.4_1.4.2+dfsg1-2_i386.deb ... Unpacking libgl2ps1.4 (1.4.2+dfsg1-2) ... Selecting previously unselected package libltdl7:i386. Preparing to unpack .../347-libltdl7_2.4.7-7_i386.deb ... Unpacking libltdl7:i386 (2.4.7-7) ... Selecting previously unselected package libglpk40:i386. Preparing to unpack .../348-libglpk40_5.0-1+b1_i386.deb ... Unpacking libglpk40:i386 (5.0-1+b1) ... Selecting previously unselected package libopengl0:i386. Preparing to unpack .../349-libopengl0_1.7.0-1_i386.deb ... Unpacking libopengl0:i386 (1.7.0-1) ... Selecting previously unselected package libglu1-mesa:i386. Preparing to unpack .../350-libglu1-mesa_9.0.2-1.1_i386.deb ... Unpacking libglu1-mesa:i386 (9.0.2-1.1) ... Selecting previously unselected package libhwy1:i386. Preparing to unpack .../351-libhwy1_1.0.7-8+b1_i386.deb ... Unpacking libhwy1:i386 (1.0.7-8+b1) ... Selecting previously unselected package liblcms2-2:i386. Preparing to unpack .../352-liblcms2-2_2.14-2+b1_i386.deb ... Unpacking liblcms2-2:i386 (2.14-2+b1) ... Selecting previously unselected package libjxl0.7:i386. Preparing to unpack .../353-libjxl0.7_0.7.0-10.2+b1_i386.deb ... Unpacking libjxl0.7:i386 (0.7.0-10.2+b1) ... Selecting previously unselected package libwmflite-0.2-7:i386. Preparing to unpack .../354-libwmflite-0.2-7_0.2.13-1.1_i386.deb ... Unpacking libwmflite-0.2-7:i386 (0.2.13-1.1) ... Selecting previously unselected package libgraphicsmagick-q16-3. Preparing to unpack .../355-libgraphicsmagick-q16-3_1.4+really1.3.42-1+b1_i386.deb ... Unpacking libgraphicsmagick-q16-3 (1.4+really1.3.42-1+b1) ... Selecting previously unselected package libgraphicsmagick++-q16-12. Preparing to unpack .../356-libgraphicsmagick++-q16-12_1.4+really1.3.42-1+b1_i386.deb ... Unpacking libgraphicsmagick++-q16-12 (1.4+really1.3.42-1+b1) ... Selecting previously unselected package libcurl4:i386. Preparing to unpack .../357-libcurl4_8.5.0-2_i386.deb ... Unpacking libcurl4:i386 (8.5.0-2) ... Selecting previously unselected package libaec0:i386. Preparing to unpack .../358-libaec0_1.1.3-1_i386.deb ... Unpacking libaec0:i386 (1.1.3-1) ... Selecting previously unselected package libsz2:i386. Preparing to unpack .../359-libsz2_1.1.3-1_i386.deb ... Unpacking libsz2:i386 (1.1.3-1) ... Selecting previously unselected package libhdf5-103-1:i386. Preparing to unpack .../360-libhdf5-103-1_1.10.10+repack-3+b1_i386.deb ... Unpacking libhdf5-103-1:i386 (1.10.10+repack-3+b1) ... Selecting previously unselected package libasound2-data. Preparing to unpack .../361-libasound2-data_1.2.10-3_all.deb ... Unpacking libasound2-data (1.2.10-3) ... Selecting previously unselected package libasound2:i386. Preparing to unpack .../362-libasound2_1.2.10-3_i386.deb ... Unpacking libasound2:i386 (1.2.10-3) ... Selecting previously unselected package libopus0:i386. Preparing to unpack .../363-libopus0_1.4-1+b1_i386.deb ... Unpacking libopus0:i386 (1.4-1+b1) ... Selecting previously unselected package libsamplerate0:i386. Preparing to unpack .../364-libsamplerate0_0.2.2-4_i386.deb ... Unpacking libsamplerate0:i386 (0.2.2-4) ... Selecting previously unselected package libjack-jackd2-0:i386. Preparing to unpack .../365-libjack-jackd2-0_1.9.21~dfsg-3+b1_i386.deb ... Unpacking libjack-jackd2-0:i386 (1.9.21~dfsg-3+b1) ... Selecting previously unselected package libportaudio2:i386. Preparing to unpack .../366-libportaudio2_19.6.0-1.2+b1_i386.deb ... Unpacking libportaudio2:i386 (19.6.0-1.2+b1) ... Selecting previously unselected package libqhull-r8.0:i386. Preparing to unpack .../367-libqhull-r8.0_2020.2-6+b1_i386.deb ... Unpacking libqhull-r8.0:i386 (2020.2-6+b1) ... Selecting previously unselected package libqrupdate1:i386. Preparing to unpack .../368-libqrupdate1_1.1.2-4+b1_i386.deb ... Unpacking libqrupdate1:i386 (1.1.2-4+b1) ... Selecting previously unselected package libqscintilla2-qt5-l10n. Preparing to unpack .../369-libqscintilla2-qt5-l10n_2.14.1+dfsg-1_all.deb ... Unpacking libqscintilla2-qt5-l10n (2.14.1+dfsg-1) ... Selecting previously unselected package shared-mime-info. Preparing to unpack .../370-shared-mime-info_2.4-1_i386.deb ... Unpacking shared-mime-info (2.4-1) ... Selecting previously unselected package libdouble-conversion3:i386. Preparing to unpack .../371-libdouble-conversion3_3.3.0-1+b1_i386.deb ... Unpacking libdouble-conversion3:i386 (3.3.0-1+b1) ... Selecting previously unselected package libpcre2-16-0:i386. Preparing to unpack .../372-libpcre2-16-0_10.42-4+b1_i386.deb ... Unpacking libpcre2-16-0:i386 (10.42-4+b1) ... Selecting previously unselected package libqt5core5a:i386. Preparing to unpack .../373-libqt5core5a_5.15.10+dfsg-7_i386.deb ... Unpacking libqt5core5a:i386 (5.15.10+dfsg-7) ... Selecting previously unselected package libwayland-server0:i386. Preparing to unpack .../374-libwayland-server0_1.22.0-2.1+b1_i386.deb ... Unpacking libwayland-server0:i386 (1.22.0-2.1+b1) ... Selecting previously unselected package libgbm1:i386. Preparing to unpack .../375-libgbm1_23.3.5-1_i386.deb ... Unpacking libgbm1:i386 (23.3.5-1) ... Selecting previously unselected package libwayland-client0:i386. Preparing to unpack .../376-libwayland-client0_1.22.0-2.1+b1_i386.deb ... Unpacking libwayland-client0:i386 (1.22.0-2.1+b1) ... Selecting previously unselected package libegl-mesa0:i386. Preparing to unpack .../377-libegl-mesa0_23.3.5-1_i386.deb ... Unpacking libegl-mesa0:i386 (23.3.5-1) ... Selecting previously unselected package libegl1:i386. Preparing to unpack .../378-libegl1_1.7.0-1_i386.deb ... Unpacking libegl1:i386 (1.7.0-1) ... Selecting previously unselected package x11-common. Preparing to unpack .../379-x11-common_1%3a7.7+23_all.deb ... Unpacking x11-common (1:7.7+23) ... Selecting previously unselected package libice6:i386. Preparing to unpack .../380-libice6_2%3a1.0.10-1_i386.deb ... Unpacking libice6:i386 (2:1.0.10-1) ... Selecting previously unselected package libevdev2:i386. Preparing to unpack .../381-libevdev2_1.13.1+dfsg-1_i386.deb ... Unpacking libevdev2:i386 (1.13.1+dfsg-1) ... Selecting previously unselected package libmtdev1:i386. Preparing to unpack .../382-libmtdev1_1.1.6-1+b1_i386.deb ... Unpacking libmtdev1:i386 (1.1.6-1+b1) ... Selecting previously unselected package libgudev-1.0-0:i386. Preparing to unpack .../383-libgudev-1.0-0_238-3_i386.deb ... Unpacking libgudev-1.0-0:i386 (238-3) ... Selecting previously unselected package libwacom-common. Preparing to unpack .../384-libwacom-common_2.10.0-1_all.deb ... Unpacking libwacom-common (2.10.0-1) ... Selecting previously unselected package libwacom9:i386. Preparing to unpack .../385-libwacom9_2.10.0-1_i386.deb ... Unpacking libwacom9:i386 (2.10.0-1) ... Selecting previously unselected package libinput-bin. Preparing to unpack .../386-libinput-bin_1.25.0-1_i386.deb ... Unpacking libinput-bin (1.25.0-1) ... Selecting previously unselected package libinput10:i386. Preparing to unpack .../387-libinput10_1.25.0-1_i386.deb ... Unpacking libinput10:i386 (1.25.0-1) ... Selecting previously unselected package libmd4c0:i386. Preparing to unpack .../388-libmd4c0_0.4.8-1+b1_i386.deb ... Unpacking libmd4c0:i386 (0.4.8-1+b1) ... Selecting previously unselected package libdbus-1-3:i386. Preparing to unpack .../389-libdbus-1-3_1.14.10-4_i386.deb ... Unpacking libdbus-1-3:i386 (1.14.10-4) ... Selecting previously unselected package libqt5dbus5:i386. Preparing to unpack .../390-libqt5dbus5_5.15.10+dfsg-7_i386.deb ... Unpacking libqt5dbus5:i386 (5.15.10+dfsg-7) ... Selecting previously unselected package libqt5network5:i386. Preparing to unpack .../391-libqt5network5_5.15.10+dfsg-7_i386.deb ... Unpacking libqt5network5:i386 (5.15.10+dfsg-7) ... Selecting previously unselected package libsm6:i386. Preparing to unpack .../392-libsm6_2%3a1.2.3-1_i386.deb ... Unpacking libsm6:i386 (2:1.2.3-1) ... Selecting previously unselected package libxcb-icccm4:i386. Preparing to unpack .../393-libxcb-icccm4_0.4.1-1.1+b1_i386.deb ... Unpacking libxcb-icccm4:i386 (0.4.1-1.1+b1) ... Selecting previously unselected package libxcb-util1:i386. Preparing to unpack .../394-libxcb-util1_0.4.0-1+b1_i386.deb ... Unpacking libxcb-util1:i386 (0.4.0-1+b1) ... Selecting previously unselected package libxcb-image0:i386. Preparing to unpack .../395-libxcb-image0_0.4.0-2+b1_i386.deb ... Unpacking libxcb-image0:i386 (0.4.0-2+b1) ... Selecting previously unselected package libxcb-keysyms1:i386. Preparing to unpack .../396-libxcb-keysyms1_0.4.0-1+b2_i386.deb ... Unpacking libxcb-keysyms1:i386 (0.4.0-1+b2) ... Selecting previously unselected package libxcb-render-util0:i386. Preparing to unpack .../397-libxcb-render-util0_0.3.9-1+b1_i386.deb ... Unpacking libxcb-render-util0:i386 (0.3.9-1+b1) ... Selecting previously unselected package libxcb-shape0:i386. Preparing to unpack .../398-libxcb-shape0_1.15-1_i386.deb ... Unpacking libxcb-shape0:i386 (1.15-1) ... Selecting previously unselected package libxcb-xinerama0:i386. Preparing to unpack .../399-libxcb-xinerama0_1.15-1_i386.deb ... Unpacking libxcb-xinerama0:i386 (1.15-1) ... Selecting previously unselected package libxcb-xinput0:i386. Preparing to unpack .../400-libxcb-xinput0_1.15-1_i386.deb ... Unpacking libxcb-xinput0:i386 (1.15-1) ... Selecting previously unselected package libxcb-xkb1:i386. Preparing to unpack .../401-libxcb-xkb1_1.15-1_i386.deb ... Unpacking libxcb-xkb1:i386 (1.15-1) ... Selecting previously unselected package xkb-data. Preparing to unpack .../402-xkb-data_2.41-2_all.deb ... Unpacking xkb-data (2.41-2) ... Selecting previously unselected package libxkbcommon0:i386. Preparing to unpack .../403-libxkbcommon0_1.6.0-1_i386.deb ... Unpacking libxkbcommon0:i386 (1.6.0-1) ... Selecting previously unselected package libxkbcommon-x11-0:i386. Preparing to unpack .../404-libxkbcommon-x11-0_1.6.0-1_i386.deb ... Unpacking libxkbcommon-x11-0:i386 (1.6.0-1) ... Selecting previously unselected package libqt5gui5:i386. Preparing to unpack .../405-libqt5gui5_5.15.10+dfsg-7_i386.deb ... Unpacking libqt5gui5:i386 (5.15.10+dfsg-7) ... Selecting previously unselected package libavahi-common-data:i386. Preparing to unpack .../406-libavahi-common-data_0.8-13+b1_i386.deb ... Unpacking libavahi-common-data:i386 (0.8-13+b1) ... Selecting previously unselected package libavahi-common3:i386. Preparing to unpack .../407-libavahi-common3_0.8-13+b1_i386.deb ... Unpacking libavahi-common3:i386 (0.8-13+b1) ... Selecting previously unselected package libavahi-client3:i386. Preparing to unpack .../408-libavahi-client3_0.8-13+b1_i386.deb ... Unpacking libavahi-client3:i386 (0.8-13+b1) ... Selecting previously unselected package libcups2:i386. Preparing to unpack .../409-libcups2_2.4.7-1+b1_i386.deb ... Unpacking libcups2:i386 (2.4.7-1+b1) ... Selecting previously unselected package libqt5widgets5:i386. Preparing to unpack .../410-libqt5widgets5_5.15.10+dfsg-7_i386.deb ... Unpacking libqt5widgets5:i386 (5.15.10+dfsg-7) ... Selecting previously unselected package libqt5printsupport5:i386. Preparing to unpack .../411-libqt5printsupport5_5.15.10+dfsg-7_i386.deb ... Unpacking libqt5printsupport5:i386 (5.15.10+dfsg-7) ... Selecting previously unselected package libqscintilla2-qt5-15:i386. Preparing to unpack .../412-libqscintilla2-qt5-15_2.14.1+dfsg-1+b1_i386.deb ... Unpacking libqscintilla2-qt5-15:i386 (2.14.1+dfsg-1+b1) ... Selecting previously unselected package libqt5sql5:i386. Preparing to unpack .../413-libqt5sql5_5.15.10+dfsg-7_i386.deb ... Unpacking libqt5sql5:i386 (5.15.10+dfsg-7) ... Selecting previously unselected package libqt5help5:i386. Preparing to unpack .../414-libqt5help5_5.15.10-6_i386.deb ... Unpacking libqt5help5:i386 (5.15.10-6) ... Selecting previously unselected package libqt5xml5:i386. Preparing to unpack .../415-libqt5xml5_5.15.10+dfsg-7_i386.deb ... Unpacking libqt5xml5:i386 (5.15.10+dfsg-7) ... Selecting previously unselected package libogg0:i386. Preparing to unpack .../416-libogg0_1.3.5-3_i386.deb ... Unpacking libogg0:i386 (1.3.5-3) ... Selecting previously unselected package libflac12:i386. Preparing to unpack .../417-libflac12_1.4.3+ds-2+b1_i386.deb ... Unpacking libflac12:i386 (1.4.3+ds-2+b1) ... Selecting previously unselected package libmp3lame0:i386. Preparing to unpack .../418-libmp3lame0_3.100-6+b2_i386.deb ... Unpacking libmp3lame0:i386 (3.100-6+b2) ... Selecting previously unselected package libmpg123-0:i386. Preparing to unpack .../419-libmpg123-0_1.32.5-1_i386.deb ... Unpacking libmpg123-0:i386 (1.32.5-1) ... Selecting previously unselected package libvorbis0a:i386. Preparing to unpack .../420-libvorbis0a_1.3.7-2_i386.deb ... Unpacking libvorbis0a:i386 (1.3.7-2) ... Selecting previously unselected package libvorbisenc2:i386. Preparing to unpack .../421-libvorbisenc2_1.3.7-2_i386.deb ... Unpacking libvorbisenc2:i386 (1.3.7-2) ... Selecting previously unselected package libsndfile1:i386. Preparing to unpack .../422-libsndfile1_1.2.2-1_i386.deb ... Unpacking libsndfile1:i386 (1.2.2-1) ... Selecting previously unselected package libspqr4:i386. Preparing to unpack .../423-libspqr4_1%3a7.6.1+dfsg-1_i386.deb ... Unpacking libspqr4:i386 (1:7.6.1+dfsg-1) ... Selecting previously unselected package libsundials-ida6:i386. Preparing to unpack .../424-libsundials-ida6_6.4.1+dfsg1-3+b3_i386.deb ... Unpacking libsundials-ida6:i386 (6.4.1+dfsg1-3+b3) ... Selecting previously unselected package libbtf2:i386. Preparing to unpack .../425-libbtf2_1%3a7.6.1+dfsg-1_i386.deb ... Unpacking libbtf2:i386 (1:7.6.1+dfsg-1) ... Selecting previously unselected package libklu2:i386. Preparing to unpack .../426-libklu2_1%3a7.6.1+dfsg-1_i386.deb ... Unpacking libklu2:i386 (1:7.6.1+dfsg-1) ... Selecting previously unselected package libfftw3-long3:i386. Preparing to unpack .../427-libfftw3-long3_3.3.10-1+b1_i386.deb ... Unpacking libfftw3-long3:i386 (3.3.10-1+b1) ... Selecting previously unselected package libevent-core-2.1-7:i386. Preparing to unpack .../428-libevent-core-2.1-7_2.1.12-stable-8_i386.deb ... Unpacking libevent-core-2.1-7:i386 (2.1.12-stable-8) ... Selecting previously unselected package libevent-pthreads-2.1-7:i386. Preparing to unpack .../429-libevent-pthreads-2.1-7_2.1.12-stable-8_i386.deb ... Unpacking libevent-pthreads-2.1-7:i386 (2.1.12-stable-8) ... Selecting previously unselected package libnl-3-200:i386. Preparing to unpack .../430-libnl-3-200_3.7.0-0.3_i386.deb ... Unpacking libnl-3-200:i386 (3.7.0-0.3) ... Selecting previously unselected package libnl-route-3-200:i386. Preparing to unpack .../431-libnl-route-3-200_3.7.0-0.3_i386.deb ... Unpacking libnl-route-3-200:i386 (3.7.0-0.3) ... Selecting previously unselected package libibverbs1:i386. Preparing to unpack .../432-libibverbs1_48.0-1.1_i386.deb ... Unpacking libibverbs1:i386 (48.0-1.1) ... Selecting previously unselected package libpsm-infinipath1. Preparing to unpack .../433-libpsm-infinipath1_3.3+20.604758e7-6.3_i386.deb ... Unpacking libpsm-infinipath1 (3.3+20.604758e7-6.3) ... Selecting previously unselected package librdmacm1:i386. Preparing to unpack .../434-librdmacm1_48.0-1.1_i386.deb ... Unpacking librdmacm1:i386 (48.0-1.1) ... Selecting previously unselected package libfabric1:i386. Preparing to unpack .../435-libfabric1_1.17.0-3_i386.deb ... Unpacking libfabric1:i386 (1.17.0-3) ... Selecting previously unselected package libhwloc15:i386. Preparing to unpack .../436-libhwloc15_2.10.0-1+b1_i386.deb ... Unpacking libhwloc15:i386 (2.10.0-1+b1) ... Selecting previously unselected package libmunge2:i386. Preparing to unpack .../437-libmunge2_0.5.15-4_i386.deb ... Unpacking libmunge2:i386 (0.5.15-4) ... Selecting previously unselected package libxnvctrl0:i386. Preparing to unpack .../438-libxnvctrl0_535.171.04-1_i386.deb ... Unpacking libxnvctrl0:i386 (535.171.04-1) ... Selecting previously unselected package ocl-icd-libopencl1:i386. Preparing to unpack .../439-ocl-icd-libopencl1_2.3.2-1_i386.deb ... Unpacking ocl-icd-libopencl1:i386 (2.3.2-1) ... Selecting previously unselected package libhwloc-plugins:i386. Preparing to unpack .../440-libhwloc-plugins_2.10.0-1+b1_i386.deb ... Unpacking libhwloc-plugins:i386 (2.10.0-1+b1) ... Selecting previously unselected package libpmix2:i386. Preparing to unpack .../441-libpmix2_5.0.1-4+b1_i386.deb ... Unpacking libpmix2:i386 (5.0.1-4+b1) ... Selecting previously unselected package libopenmpi3:i386. Preparing to unpack .../442-libopenmpi3_4.1.6-5_i386.deb ... Unpacking libopenmpi3:i386 (4.1.6-5) ... Selecting previously unselected package libfftw3-mpi3:i386. Preparing to unpack .../443-libfftw3-mpi3_3.3.10-1+b1_i386.deb ... Unpacking libfftw3-mpi3:i386 (3.3.10-1+b1) ... Selecting previously unselected package libhdf5-openmpi-103-1:i386. Preparing to unpack .../444-libhdf5-openmpi-103-1_1.10.10+repack-3+b1_i386.deb ... Unpacking libhdf5-openmpi-103-1:i386 (1.10.10+repack-3+b1) ... Selecting previously unselected package libcombblas2.0.0:i386. Preparing to unpack .../445-libcombblas2.0.0_2.0.0-3+b1_i386.deb ... Unpacking libcombblas2.0.0:i386 (2.0.0-3+b1) ... Selecting previously unselected package libmetis5:i386. Preparing to unpack .../446-libmetis5_5.1.0.dfsg-7+b1_i386.deb ... Unpacking libmetis5:i386 (5.1.0.dfsg-7+b1) ... Selecting previously unselected package libptscotch-7.0:i386. Preparing to unpack .../447-libptscotch-7.0_7.0.4-1+b1_i386.deb ... Unpacking libptscotch-7.0:i386 (7.0.4-1+b1) ... Selecting previously unselected package libsuperlu-dist8:i386. Preparing to unpack .../448-libsuperlu-dist8_8.2.1+dfsg1-1_i386.deb ... Unpacking libsuperlu-dist8:i386 (8.2.1+dfsg1-1) ... Selecting previously unselected package libhypre-2.28.0:i386. Preparing to unpack .../449-libhypre-2.28.0_2.28.0-8_i386.deb ... Unpacking libhypre-2.28.0:i386 (2.28.0-8) ... Selecting previously unselected package openmpi-common. Preparing to unpack .../450-openmpi-common_4.1.6-5_all.deb ... Unpacking openmpi-common (4.1.6-5) ... Selecting previously unselected package openmpi-bin. Preparing to unpack .../451-openmpi-bin_4.1.6-5_i386.deb ... Unpacking openmpi-bin (4.1.6-5) ... Selecting previously unselected package mpi-default-bin. Preparing to unpack .../452-mpi-default-bin_1.15_i386.deb ... Unpacking mpi-default-bin (1.15) ... Selecting previously unselected package libscalapack-openmpi2.2:i386. Preparing to unpack .../453-libscalapack-openmpi2.2_2.2.1-3+b1_i386.deb ... Unpacking libscalapack-openmpi2.2:i386 (2.2.1-3+b1) ... Selecting previously unselected package libmumps-5.6:i386. Preparing to unpack .../454-libmumps-5.6_5.6.2-2+b1_i386.deb ... Unpacking libmumps-5.6:i386 (5.6.2-2+b1) ... Selecting previously unselected package libsuperlu6:i386. Preparing to unpack .../455-libsuperlu6_6.0.1+dfsg1-1+b1_i386.deb ... Unpacking libsuperlu6:i386 (6.0.1+dfsg1-1+b1) ... Selecting previously unselected package libumfpack6:i386. Preparing to unpack .../456-libumfpack6_1%3a7.6.1+dfsg-1_i386.deb ... Unpacking libumfpack6:i386 (1:7.6.1+dfsg-1) ... Selecting previously unselected package libpetsc-real3.19:i386. Preparing to unpack .../457-libpetsc-real3.19_3.19.6+dfsg1-2_i386.deb ... Unpacking libpetsc-real3.19:i386 (3.19.6+dfsg1-2) ... Selecting previously unselected package libsundials-nvecparallel-petsc6:i386. Preparing to unpack .../458-libsundials-nvecparallel-petsc6_6.4.1+dfsg1-3+b3_i386.deb ... Unpacking libsundials-nvecparallel-petsc6:i386 (6.4.1+dfsg1-3+b3) ... Selecting previously unselected package libsundials-sunmatrix4:i386. Preparing to unpack .../459-libsundials-sunmatrix4_6.4.1+dfsg1-3+b3_i386.deb ... Unpacking libsundials-sunmatrix4:i386 (6.4.1+dfsg1-3+b3) ... Selecting previously unselected package libsundials-sunlinsol3:i386. Preparing to unpack .../460-libsundials-sunlinsol3_6.4.1+dfsg1-3+b3_i386.deb ... Unpacking libsundials-sunlinsol3:i386 (6.4.1+dfsg1-3+b3) ... Selecting previously unselected package libtext-unidecode-perl. Preparing to unpack .../461-libtext-unidecode-perl_1.30-3_all.deb ... Unpacking libtext-unidecode-perl (1.30-3) ... Selecting previously unselected package texinfo-lib. Preparing to unpack .../462-texinfo-lib_7.1-3_i386.deb ... Unpacking texinfo-lib (7.1-3) ... Selecting previously unselected package tex-common. Preparing to unpack .../463-tex-common_6.18_all.deb ... Unpacking tex-common (6.18) ... Selecting previously unselected package texinfo. Preparing to unpack .../464-texinfo_7.1-3_all.deb ... Unpacking texinfo (7.1-3) ... Selecting previously unselected package octave-common. Preparing to unpack .../465-octave-common_8.4.0-1_all.deb ... Unpacking octave-common (8.4.0-1) ... Selecting previously unselected package octave. Preparing to unpack .../466-octave_8.4.0-1+b1_i386.deb ... Unpacking octave (8.4.0-1+b1) ... Selecting previously unselected package libncurses6:i386. Preparing to unpack .../467-libncurses6_6.4+20240113-1_i386.deb ... Unpacking libncurses6:i386 (6.4+20240113-1) ... Selecting previously unselected package libncurses-dev:i386. Preparing to unpack .../468-libncurses-dev_6.4+20240113-1_i386.deb ... Unpacking libncurses-dev:i386 (6.4+20240113-1) ... Selecting previously unselected package libreadline-dev:i386. Preparing to unpack .../469-libreadline-dev_8.2-3+b1_i386.deb ... Unpacking libreadline-dev:i386 (8.2-3+b1) ... Selecting previously unselected package libhdf5-fortran-102:i386. Preparing to unpack .../470-libhdf5-fortran-102_1.10.10+repack-3+b1_i386.deb ... Unpacking libhdf5-fortran-102:i386 (1.10.10+repack-3+b1) ... Selecting previously unselected package libhdf5-hl-100:i386. Preparing to unpack .../471-libhdf5-hl-100_1.10.10+repack-3+b1_i386.deb ... Unpacking libhdf5-hl-100:i386 (1.10.10+repack-3+b1) ... Selecting previously unselected package libhdf5-hl-fortran-100:i386. Preparing to unpack .../472-libhdf5-hl-fortran-100_1.10.10+repack-3+b1_i386.deb ... Unpacking libhdf5-hl-fortran-100:i386 (1.10.10+repack-3+b1) ... Selecting previously unselected package libhdf5-cpp-103-1:i386. Preparing to unpack .../473-libhdf5-cpp-103-1_1.10.10+repack-3+b1_i386.deb ... Unpacking libhdf5-cpp-103-1:i386 (1.10.10+repack-3+b1) ... Selecting previously unselected package libhdf5-hl-cpp-100:i386. Preparing to unpack .../474-libhdf5-hl-cpp-100_1.10.10+repack-3+b1_i386.deb ... Unpacking libhdf5-hl-cpp-100:i386 (1.10.10+repack-3+b1) ... Selecting previously unselected package zlib1g-dev:i386. Preparing to unpack .../475-zlib1g-dev_1%3a1.3.dfsg-3+b1_i386.deb ... Unpacking zlib1g-dev:i386 (1:1.3.dfsg-3+b1) ... Selecting previously unselected package libjpeg62-turbo-dev:i386. Preparing to unpack .../476-libjpeg62-turbo-dev_1%3a2.1.5-2+b2_i386.deb ... Unpacking libjpeg62-turbo-dev:i386 (1:2.1.5-2+b2) ... Selecting previously unselected package libjpeg-dev:i386. Preparing to unpack .../477-libjpeg-dev_1%3a2.1.5-2+b2_i386.deb ... Unpacking libjpeg-dev:i386 (1:2.1.5-2+b2) ... Selecting previously unselected package libaec-dev:i386. Preparing to unpack .../478-libaec-dev_1.1.3-1_i386.deb ... Unpacking libaec-dev:i386 (1.1.3-1) ... Selecting previously unselected package libcurl4-openssl-dev:i386. Preparing to unpack .../479-libcurl4-openssl-dev_8.5.0-2_i386.deb ... Unpacking libcurl4-openssl-dev:i386 (8.5.0-2) ... Selecting previously unselected package libssl-dev:i386. Preparing to unpack .../480-libssl-dev_3.1.5-1_i386.deb ... Unpacking libssl-dev:i386 (3.1.5-1) ... Selecting previously unselected package hdf5-helpers. Preparing to unpack .../481-hdf5-helpers_1.10.10+repack-3+b1_i386.deb ... Unpacking hdf5-helpers (1.10.10+repack-3+b1) ... Selecting previously unselected package libhdf5-dev. Preparing to unpack .../482-libhdf5-dev_1.10.10+repack-3+b1_i386.deb ... Unpacking libhdf5-dev (1.10.10+repack-3+b1) ... Selecting previously unselected package xorg-sgml-doctools. Preparing to unpack .../483-xorg-sgml-doctools_1%3a1.11-1.1_all.deb ... Unpacking xorg-sgml-doctools (1:1.11-1.1) ... Selecting previously unselected package x11proto-dev. Preparing to unpack .../484-x11proto-dev_2023.2-1_all.deb ... Unpacking x11proto-dev (2023.2-1) ... Selecting previously unselected package libxau-dev:i386. Preparing to unpack .../485-libxau-dev_1%3a1.0.9-1_i386.deb ... Unpacking libxau-dev:i386 (1:1.0.9-1) ... Selecting previously unselected package libxdmcp-dev:i386. Preparing to unpack .../486-libxdmcp-dev_1%3a1.1.2-3_i386.deb ... Unpacking libxdmcp-dev:i386 (1:1.1.2-3) ... Selecting previously unselected package xtrans-dev. Preparing to unpack .../487-xtrans-dev_1.4.0-1_all.deb ... Unpacking xtrans-dev (1.4.0-1) ... Selecting previously unselected package libpthread-stubs0-dev:i386. Preparing to unpack .../488-libpthread-stubs0-dev_0.4-1_i386.deb ... Unpacking libpthread-stubs0-dev:i386 (0.4-1) ... Selecting previously unselected package libxcb1-dev:i386. Preparing to unpack .../489-libxcb1-dev_1.15-1_i386.deb ... Unpacking libxcb1-dev:i386 (1.15-1) ... Selecting previously unselected package libx11-dev:i386. Preparing to unpack .../490-libx11-dev_2%3a1.8.7-1_i386.deb ... Unpacking libx11-dev:i386 (2:1.8.7-1) ... Selecting previously unselected package libglx-dev:i386. Preparing to unpack .../491-libglx-dev_1.7.0-1_i386.deb ... Unpacking libglx-dev:i386 (1.7.0-1) ... Selecting previously unselected package libgl-dev:i386. Preparing to unpack .../492-libgl-dev_1.7.0-1_i386.deb ... Unpacking libgl-dev:i386 (1.7.0-1) ... Selecting previously unselected package libblas-dev:i386. Preparing to unpack .../493-libblas-dev_3.12.0-3_i386.deb ... Unpacking libblas-dev:i386 (3.12.0-3) ... Selecting previously unselected package liblapack-dev:i386. Preparing to unpack .../494-liblapack-dev_3.12.0-3_i386.deb ... Unpacking liblapack-dev:i386 (3.12.0-3) ... Selecting previously unselected package libfftw3-quad3:i386. Preparing to unpack .../495-libfftw3-quad3_3.3.10-1+b1_i386.deb ... Unpacking libfftw3-quad3:i386 (3.3.10-1+b1) ... Selecting previously unselected package libfftw3-bin. Preparing to unpack .../496-libfftw3-bin_3.3.10-1+b1_i386.deb ... Unpacking libfftw3-bin (3.3.10-1+b1) ... Selecting previously unselected package libfftw3-dev:i386. Preparing to unpack .../497-libfftw3-dev_3.3.10-1+b1_i386.deb ... Unpacking libfftw3-dev:i386 (3.3.10-1+b1) ... Selecting previously unselected package libgfortran-13-dev:i386. Preparing to unpack .../498-libgfortran-13-dev_13.2.0-13_i386.deb ... Unpacking libgfortran-13-dev:i386 (13.2.0-13) ... Selecting previously unselected package gfortran-13-i686-linux-gnu. Preparing to unpack .../499-gfortran-13-i686-linux-gnu_13.2.0-13_i386.deb ... Unpacking gfortran-13-i686-linux-gnu (13.2.0-13) ... Selecting previously unselected package gfortran-13. Preparing to unpack .../500-gfortran-13_13.2.0-13_i386.deb ... Unpacking gfortran-13 (13.2.0-13) ... Selecting previously unselected package gfortran-i686-linux-gnu. Preparing to unpack .../501-gfortran-i686-linux-gnu_4%3a13.2.0-7_i386.deb ... Unpacking gfortran-i686-linux-gnu (4:13.2.0-7) ... Selecting previously unselected package gfortran. Preparing to unpack .../502-gfortran_4%3a13.2.0-7_i386.deb ... Unpacking gfortran (4:13.2.0-7) ... Selecting previously unselected package octave-dev. Preparing to unpack .../503-octave-dev_8.4.0-1+b1_i386.deb ... Unpacking octave-dev (8.4.0-1+b1) ... Selecting previously unselected package dh-octave. Preparing to unpack .../504-dh-octave_1.8.0_all.deb ... Unpacking dh-octave (1.8.0) ... Selecting previously unselected package octave-io. Preparing to unpack .../505-octave-io_2.6.4-3+b1_i386.deb ... Unpacking octave-io (2.6.4-3+b1) ... Setting up libapt-pkg-perl (0.1.40+b3) ... Setting up liblz1:i386 (1.14-1) ... Setting up media-types (10.1.0) ... Setting up libmodule-pluggable-perl (5.2-5) ... Setting up libpipeline1:i386 (1.5.7-1+b2) ... Setting up libgraphite2-3:i386 (1.3.14-2) ... Setting up libstring-escape-perl (2010.002-3) ... Setting up liblcms2-2:i386 (2.14-2+b1) ... Setting up libberkeleydb-perl:i386 (0.64-2+b2) ... Setting up libpixman-1-0:i386 (0.42.2-1+b1) ... Setting up plzip (1.11-1) ... update-alternatives: using /usr/bin/lzip.plzip to provide /usr/bin/lzip (lzip) in auto mode update-alternatives: using /usr/bin/lzip.plzip to provide /usr/bin/lzip-compressor (lzip-compressor) in auto mode update-alternatives: using /usr/bin/lzip.plzip to provide /usr/bin/lzip-decompressor (lzip-decompressor) in auto mode Setting up libsharpyuv0:i386 (1.3.2-0.4) ... Setting up libwayland-server0:i386 (1.22.0-2.1+b1) ... Setting up libaom3:i386 (3.8.2-2) ... Setting up libpciaccess0:i386 (0.17-3) ... Setting up libfile-which-perl (1.27-2) ... Setting up libabsl20220623:i386 (20220623.1-3) ... Setting up libxau6:i386 (1:1.0.9-1) ... Setting up libdouble-conversion3:i386 (3.3.0-1+b1) ... Setting up libpsl5:i386 (0.21.2-1+b1) ... Setting up libunicode-utf8-perl (0.62-2+b1) ... Setting up libfftw3-single3:i386 (3.3.10-1+b1) ... Setting up libset-intspan-perl (1.19-3) ... Setting up libicu72:i386 (72.1-4+b1) ... Setting up libmpg123-0:i386 (1.32.5-1) ... Setting up libogg0:i386 (1.3.5-3) ... Setting up libmouse-perl (2.5.10-1+b4) ... Setting up liblerc4:i386 (4.0.0+ds-4+b1) ... Setting up libpod-pom-perl (2.01-4) ... Setting up bsdextrautils (2.39.3-6) ... Setting up hdf5-helpers (1.10.10+repack-3+b1) ... Setting up libwmflite-0.2-7:i386 (0.2.13-1.1) ... Setting up libregexp-pattern-perl (0.2.14-2) ... Setting up libdata-messagepack-perl (1.02-1+b2) ... Setting up libdynaloader-functions-perl (0.003-3) ... Setting up libdatrie1:i386 (0.2.13-3) ... Setting up libtext-glob-perl (0.11-3) ... Setting up libclass-method-modifiers-perl (2.15-1) ... Setting up liblist-compare-perl (0.55-2) ... Setting up libmagic-mgc (1:5.45-2+b1) ... Setting up libcbor0.10:i386 (0.10.2-1.1) ... Setting up libclone-perl:i386 (0.46-1+b1) ... Setting up libarchive-zip-perl (1.68-1) ... Setting up libyaml-0-2:i386 (0.2.5-1) ... Setting up libsub-identify-perl (0.14-3+b1) ... Setting up libglib2.0-0:i386 (2.78.4-1) ... No schema files found: doing nothing. Setting up libcpanel-json-xs-perl:i386 (4.37-1+b1) ... Setting up libglvnd0:i386 (1.7.0-1) ... Setting up libio-stringy-perl (2.111-3) ... Setting up libhtml-tagset-perl (3.24-1) ... Setting up liblog-any-perl (1.717-1) ... Setting up libqscintilla2-qt5-l10n (2.14.1+dfsg-1) ... Setting up libyaml-pp-perl (0.38.0-1) ... Setting up libdevel-size-perl (0.83-2+b2) ... Setting up unzip (6.0-28) ... Setting up libdebhelper-perl (13.15.3) ... Setting up libbrotli1:i386 (1.1.0-2+b3) ... Setting up libregexp-pattern-license-perl (3.11.0-1) ... Setting up libconvert-binhex-perl (1.125-3) ... Setting up liblwp-mediatypes-perl (6.04-2) ... Setting up libyaml-libyaml-perl (0.89+ds-1) ... Setting up fonts-freefont-otf (20211204+svn4273-2) ... Setting up libio-interactive-perl (1.025-1) ... Setting up x11-common (1:7.7+23) ... invoke-rc.d: could not determine current runlevel Setting up X socket directories... /tmp/.X11-unix /tmp/.ICE-unix. Setting up libtry-tiny-perl (0.31-2) ... Setting up libsensors-config (1:3.6.0-9) ... Setting up libcxsparse4:i386 (1:7.6.1+dfsg-1) ... Setting up libnghttp2-14:i386 (1.59.0-1) ... Setting up libmagic1:i386 (1:5.45-2+b1) ... Setting up libdeflate0:i386 (1.20-1) ... Setting up perl-openssl-defaults:i386 (7+b1) ... Setting up libmldbm-perl (2.05-4) ... Setting up libxml-namespacesupport-perl (1.12-2) ... Setting up libfftw3-long3:i386 (3.3.10-1+b1) ... Setting up gettext-base (0.21-14+b1) ... Setting up m4 (1.4.19-4) ... Setting up libclone-choose-perl (0.010-2) ... Setting up libqhull-r8.0:i386 (2020.2-6+b1) ... Setting up xkb-data (2.41-2) ... Setting up liblzo2-2:i386 (2.10-2+b1) ... Setting up libtime-moment-perl (0.44-2+b2) ... Setting up libencode-locale-perl (1.05-3) ... Setting up libhwy1:i386 (1.0.7-8+b1) ... Setting up libmetis5:i386 (5.1.0.dfsg-7+b1) ... Setting up file (1:5.45-2+b1) ... Setting up texinfo-lib (7.1-3) ... Setting up libassuan0:i386 (2.5.6-1) ... Setting up libconfig-tiny-perl (2.30-1) ... Setting up libsereal-encoder-perl (5.004+ds-1+b1) ... Setting up liblist-utilsby-perl (0.12-2) ... Setting up libyaml-tiny-perl (1.74-1) ... Setting up libpthread-stubs0-dev:i386 (0.4-1) ... Setting up libjbig0:i386 (2.1-6.1+b1) ... Setting up octave-common (8.4.0-1) ... Setting up libregexp-common-perl (2017060201-3) ... Setting up librav1e0:i386 (0.7.1-2) ... Setting up libpcre2-16-0:i386 (10.42-4+b1) ... Setting up libaec0:i386 (1.1.3-1) ... Setting up libnet-netmask-perl (2.0002-2) ... Setting up libopengl0:i386 (1.7.0-1) ... Setting up libsub-install-perl (0.929-1) ... Setting up libindirect-perl (0.39-2+b2) ... Setting up libxs-parse-sublike-perl:i386 (0.21-2+b1) ... Setting up libnumber-compare-perl (0.03-3) ... Setting up libsasl2-modules-db:i386 (2.1.28+dfsg1-4+b1) ... Setting up tzdata (2024a-1) ... Current default time zone: 'Etc/UTC' Local time is now: Mon May 5 20:15:24 UTC 2025. Universal Time is now: Mon May 5 20:15:24 UTC 2025. Run 'dpkg-reconfigure tzdata' if you wish to change it. Setting up liberror-perl (0.17029-2) ... Setting up libasound2-data (1.2.10-3) ... Setting up libbtf2:i386 (1:7.6.1+dfsg-1) ... Setting up libjson-maybexs-perl (1.004005-1) ... Setting up libxml-sax-base-perl (1.09-3) ... Setting up libio-string-perl (1.08-4) ... Setting up libboolean-perl (0.46-3) ... Setting up libnetaddr-ip-perl (4.079+dfsg-2+b2) ... Setting up xtrans-dev (1.4.0-1) ... Setting up autotools-dev (20220109.1) ... Setting up libz3-4:i386 (4.8.12-3.1+b2) ... Setting up libblas3:i386 (3.12.0-3) ... update-alternatives: using /usr/lib/i386-linux-gnu/blas/libblas.so.3 to provide /usr/lib/i386-linux-gnu/libblas.so.3 (libblas.so.3-i386-linux-gnu) in auto mode Setting up libclass-data-inheritable-perl (0.08-3) ... Setting up libxs-parse-keyword-perl (0.39-1+b1) ... Setting up libflac12:i386 (1.4.3+ds-2+b1) ... Setting up libalgorithm-c3-perl (0.11-2) ... Setting up libmunge2:i386 (0.5.15-4) ... Setting up liblog-log4perl-perl (1.57-1) ... Setting up libtext-reform-perl (1.20-5) ... Setting up libjpeg62-turbo:i386 (1:2.1.5-2+b2) ... Setting up libx11-data (2:1.8.7-1) ... Setting up libjpeg62-turbo-dev:i386 (1:2.1.5-2+b2) ... Setting up libfile-find-rule-perl (0.34-3) ... Setting up librtmp1:i386 (2.4+20151223.gitfa8646d.1-2+b2) ... Setting up libipc-system-simple-perl (1.30-2) ... Setting up libio-tiecombine-perl (1.005-3) ... Setting up libnet-domain-tld-perl (1.75-3) ... Setting up libperlio-utf8-strict-perl (0.010-1+b1) ... Setting up aglfn (1.7+git20191031.4036a9c-2) ... Setting up libavahi-common-data:i386 (0.8-13+b1) ... Setting up libncurses6:i386 (6.4+20240113-1) ... Setting up libdbus-1-3:i386 (1.14.10-4) ... Setting up libfftw3-quad3:i386 (3.3.10-1+b1) ... Setting up libfribidi0:i386 (1.0.13-3+b1) ... Setting up libopus0:i386 (1.4-1+b1) ... Setting up t1utils (1.41-4) ... Setting up diffstat (1.66-1) ... Setting up fonts-dejavu-mono (2.37-8) ... Setting up libssl-dev:i386 (3.1.5-1) ... Setting up libpng16-16:i386 (1.6.43-1) ... Setting up libhwloc15:i386 (2.10.0-1+b1) ... Setting up libevent-core-2.1-7:i386 (2.1.12-stable-8) ... Setting up libvorbis0a:i386 (1.3.7-2) ... Setting up libvariable-magic-perl (0.63-1+b2) ... Setting up libio-html-perl (1.004-3) ... Setting up libtext-template-perl (1.61-1) ... Setting up libpod-parser-perl (1.67-1) ... Setting up autopoint (0.21-14) ... Setting up libb-hooks-op-check-perl:i386 (0.22-2+b2) ... Setting up fonts-dejavu-core (2.37-8) ... Setting up libgav1-1:i386 (0.18.0-1+b1) ... Setting up liblist-moreutils-xs-perl (0.430-3+b2) ... Setting up libsensors5:i386 (1:3.6.0-9) ... Setting up libjxl0.7:i386 (0.7.0-10.2+b1) ... Setting up libltdl7:i386 (2.4.7-7) ... Setting up libfftw3-double3:i386 (3.3.10-1+b1) ... Setting up libglapi-mesa:i386 (23.3.5-1) ... Setting up libparams-util-perl (1.102-2+b2) ... Setting up libsasl2-2:i386 (2.1.28+dfsg1-4+b1) ... Setting up libgfortran5:i386 (14-20240201-3) ... Setting up libmtdev1:i386 (1.1.6-1+b1) ... Setting up libvulkan1:i386 (1.3.275.0-1) ... Setting up libtime-duration-perl (1.21-2) ... Setting up autoconf (2.71-3) ... Setting up libtext-xslate-perl:i386 (3.5.9-1+b3) ... Setting up libsub-exporter-progressive-perl (0.001013-3) ... Setting up libwebp7:i386 (1.3.2-0.4) ... Setting up libarray-intspan-perl (2.004-2) ... Setting up libcapture-tiny-perl (0.48-2) ... Setting up libtimedate-perl (2.3300-2) ... Setting up libexporter-lite-perl (0.09-2) ... Setting up libsub-name-perl:i386 (0.27-1+b1) ... Setting up zlib1g-dev:i386 (1:1.3.dfsg-3+b1) ... Setting up libsyntax-keyword-try-perl (0.29-1+b1) ... Setting up libdata-validate-domain-perl (0.10-1.1) ... Setting up libproc-processtable-perl:i386 (0.636-1+b1) ... Setting up libparse-recdescent-perl (1.967015+dfsg-4) ... Setting up libdav1d7:i386 (1.4.1-1) ... Setting up sensible-utils (0.0.22) ... Setting up ocl-icd-libopencl1:i386 (2.3.2-1) ... Setting up libxshmfence1:i386 (1.3-1) ... Setting up libtiff6:i386 (4.5.1+git230720-4) ... Setting up libpath-tiny-perl (0.144-1) ... Setting up libuchardet0:i386 (0.0.8-1+b1) ... Setting up lzop (1.04-2) ... Setting up libjson-perl (4.10000-1) ... Setting up libasound2:i386 (1.2.10-3) ... Setting up liblog-any-adapter-screen-perl (0.140-2) ... Setting up libnl-3-200:i386 (3.7.0-0.3) ... Setting up librole-tiny-perl (2.002004-1) ... Setting up openmpi-common (4.1.6-5) ... Setting up libipc-run3-perl (0.049-1) ... Setting up libmd4c0:i386 (0.4.8-1+b1) ... Setting up libregexp-wildcards-perl (1.05-3) ... Setting up libmousex-strictconstructor-perl (0.02-3) ... Setting up libsub-uplevel-perl (0.2800-3) ... Setting up libsuitesparseconfig7:i386 (1:7.6.1+dfsg-1) ... Setting up liblua5.4-0:i386 (5.4.6-3) ... Setting up libsub-override-perl (0.10-1) ... Setting up libaliased-perl (0.34-3) ... Setting up libthai-data (0.1.29-2) ... Setting up libssh2-1:i386 (1.11.0-4) ... Setting up xorg-sgml-doctools (1:1.11-1.1) ... Setting up netbase (6.4) ... Setting up libstrictures-perl (2.000006-1) ... Setting up libsub-quote-perl (2.006008-1) ... Setting up libdevel-stacktrace-perl (2.0500-1) ... Setting up libclass-xsaccessor-perl (1.19-4+b2) ... Setting up libtext-autoformat-perl (1.750000-2) ... Setting up libglu1-mesa:i386 (9.0.2-1.1) ... Setting up libtoml-tiny-perl (0.16-1) ... Setting up libpsm-infinipath1 (3.3+20.604758e7-6.3) ... update-alternatives: using /usr/lib/libpsm1/libpsm_infinipath.so.1.16 to provide /usr/lib/i386-linux-gnu/libpsm_infinipath.so.1 (libpsm_infinipath.so.1) in auto mode Setting up libsort-versions-perl (1.62-3) ... Setting up libexporter-tiny-perl (1.006002-1) ... Setting up libterm-readkey-perl (2.38-2+b2) ... Setting up libfido2-1:i386 (1.14.0-1) ... Setting up libtext-unidecode-perl (1.30-3) ... Setting up libde265-0:i386 (1.0.15-1) ... Setting up libfont-ttf-perl (1.06-2) ... Setting up libfile-homedir-perl (1.006-2) ... Setting up libgfortran-13-dev:i386 (13.2.0-13) ... Setting up libsamplerate0:i386 (0.2.2-4) ... Setting up openssl (3.1.5-1) ... Setting up libwebpmux3:i386 (1.3.2-0.4) ... Setting up libbsd0:i386 (0.12.2-1) ... Setting up libtext-levenshteinxs-perl (0.03-5+b2) ... Setting up libperlio-gzip-perl (0.20-1+b2) ... Setting up libdrm-common (2.4.120-2) ... Setting up libyuv0:i386 (0.0~git202401110.af6ac82-1) ... Setting up libelf1:i386 (0.190-1+b1) ... Setting up libevdev2:i386 (1.13.1+dfsg-1) ... Setting up readline-common (8.2-3) ... Setting up libxml2:i386 (2.9.14+dfsg-1.3+b2) ... Setting up libhtml-html5-entities-perl (0.004-3) ... Setting up libtext-levenshtein-damerau-perl (0.41-3) ... Setting up libsereal-decoder-perl (5.004+ds-1+b1) ... Setting up libmarkdown2:i386 (2.2.7-2+b1) ... Setting up liburi-perl (5.27-1) ... Setting up iso-codes (4.16.0-1) ... Setting up libnet-ipv6addr-perl (1.02-1) ... Setting up libgudev-1.0-0:i386 (238-3) ... Setting up libmp3lame0:i386 (3.100-6+b2) ... Setting up libblas-dev:i386 (3.12.0-3) ... update-alternatives: using /usr/lib/i386-linux-gnu/blas/libblas.so to provide /usr/lib/i386-linux-gnu/libblas.so (libblas.so-i386-linux-gnu) in auto mode Setting up libsz2:i386 (1.1.3-1) ... Setting up libvorbisenc2:i386 (1.3.7-2) ... Setting up libevent-pthreads-2.1-7:i386 (2.1.12-stable-8) ... Setting up libdata-validate-ip-perl (0.31-1) ... Setting up libwacom-common (2.10.0-1) ... Setting up libmousex-nativetraits-perl (1.09-3) ... Setting up libemail-address-xs-perl (1.05-1+b2) ... Setting up libxkbcommon0:i386 (1.6.0-1) ... Setting up libwayland-client0:i386 (1.22.0-2.1+b1) ... Setting up libnet-ssleay-perl:i386 (1.94-1) ... Setting up gfortran-13-i686-linux-gnu (13.2.0-13) ... Setting up automake (1:1.16.5-1.3) ... update-alternatives: using /usr/bin/automake-1.16 to provide /usr/bin/automake (automake) in auto mode Setting up x11proto-dev (2023.2-1) ... Setting up libfile-stripnondeterminism-perl (1.13.1-1) ... Setting up gnuplot-data (6.0.0+dfsg1-1) ... Setting up libice6:i386 (2:1.0.10-1) ... Setting up libhttp-date-perl (6.06-1) ... Setting up libavif16:i386 (1.0.4-1) ... Setting up libxdmcp6:i386 (1:1.1.2-3) ... Setting up liblapack3:i386 (3.12.0-3) ... update-alternatives: using /usr/lib/i386-linux-gnu/lapack/liblapack.so.3 to provide /usr/lib/i386-linux-gnu/liblapack.so.3 (liblapack.so.3-i386-linux-gnu) in auto mode Setting up libncurses-dev:i386 (6.4+20240113-1) ... Setting up libxcb1:i386 (1.15-1) ... Setting up libfile-basedir-perl (0.09-2) ... Setting up gettext (0.21-14+b1) ... Setting up libfeature-compat-try-perl (0.05-1) ... Setting up libxcb-xfixes0:i386 (1.15-1) ... Setting up libamd3:i386 (1:7.6.1+dfsg-1) ... Setting up libfile-listing-perl (6.16-1) ... Setting up libxau-dev:i386 (1:1.0.9-1) ... Setting up libxcb-xinput0:i386 (1.15-1) ... Setting up libtool (2.4.7-7) ... Setting up libcolamd3:i386 (1:7.6.1+dfsg-1) ... Setting up libxcb-render0:i386 (1.15-1) ... Setting up libfftw3-bin (3.3.10-1+b1) ... Setting up libwacom9:i386 (2.10.0-1) ... Setting up fontconfig-config (2.15.0-1.1) ... Setting up liblist-moreutils-perl (0.430-2) ... Setting up libxcb-glx0:i386 (1.15-1) ... Setting up libpod-constants-perl (0.19-2) ... Setting up libedit2:i386 (3.1-20230828-1) ... Setting up libreadline8:i386 (8.2-3+b1) ... Setting up libhash-merge-perl (0.302-1) ... Setting up libxcb-keysyms1:i386 (0.4.0-1+b2) ... Setting up libsoftware-copyright-perl (0.012-2) ... Setting up libaec-dev:i386 (1.1.3-1) ... Setting up libarpack2:i386 (3.9.1-1+b1) ... Setting up libxcb-shape0:i386 (1.15-1) ... Setting up libavahi-common3:i386 (0.8-13+b1) ... Setting up libjpeg-dev:i386 (1:2.1.5-2+b2) ... Setting up libnet-http-perl (6.23-1) ... Setting up libpath-iterator-rule-perl (1.015-2) ... Setting up libtext-markdown-discount-perl (0.16-1+b1) ... Setting up libxcb-render-util0:i386 (0.3.9-1+b1) ... Setting up libxcb-shm0:i386 (1.15-1) ... Setting up libexception-class-perl (1.45-1) ... Setting up libxcb-icccm4:i386 (0.4.1-1.1+b1) ... Setting up libsundials-sunmatrix4:i386 (6.4.1+dfsg1-3+b3) ... Setting up libclass-c3-perl (0.35-2) ... Setting up libsuperlu6:i386 (6.0.1+dfsg1-1+b1) ... Setting up libreadline-dev:i386 (8.2-3+b1) ... Setting up libqrupdate1:i386 (1.1.2-4+b1) ... Setting up libdevel-callchecker-perl:i386 (0.008-2+b1) ... Setting up libldap-2.5-0:i386 (2.5.13+dfsg-5+b3) ... Setting up libsundials-ida6:i386 (6.4.1+dfsg1-3+b3) ... Setting up libcamd3:i386 (1:7.6.1+dfsg-1) ... Setting up libxcb-util1:i386 (0.4.0-1+b1) ... Setting up libinput-bin (1.25.0-1) ... Setting up libxcb-xkb1:i386 (1.15-1) ... Setting up libxcb-image0:i386 (0.4.0-2+b1) ... Setting up intltool-debian (0.35.0+20060710.6) ... Setting up libnl-route-3-200:i386 (3.7.0-0.3) ... Setting up libobject-pad-perl (0.808-1+b1) ... Setting up libxcb-present0:i386 (1.15-1) ... Setting up dh-autoreconf (20) ... Setting up patchutils (0.4.2-1) ... Setting up libthai0:i386 (0.1.29-2) ... Setting up ca-certificates (20240203) ... Updating certificates in /etc/ssl/certs... 146 added, 0 removed; done. Setting up libxdmcp-dev:i386 (1:1.1.2-3) ... Setting up libdata-validate-uri-perl (0.07-3) ... Setting up libxcb-xinerama0:i386 (1.15-1) ... Setting up libtest-exception-perl (0.43-3) ... Setting up libfreetype6:i386 (2.13.2+dfsg-1+b1) ... Setting up gfortran-i686-linux-gnu (4:13.2.0-7) ... Setting up libglpk40:i386 (5.0-1+b1) ... Setting up libstring-copyright-perl (0.003014-1) ... Setting up libxcb-sync1:i386 (1.15-1) ... Setting up gfortran-13 (13.2.0-13) ... Setting up shared-mime-info (2.4-1) ... Setting up libxkbcommon-x11-0:i386 (1.6.0-1) ... Setting up liblapack-dev:i386 (3.12.0-3) ... update-alternatives: using /usr/lib/i386-linux-gnu/lapack/liblapack.so to provide /usr/lib/i386-linux-gnu/liblapack.so (liblapack.so-i386-linux-gnu) in auto mode Setting up libdata-optlist-perl (0.114-1) ... Setting up ucf (3.0043+nmu1) ... Setting up libqt5core5a:i386 (5.15.10+dfsg-7) ... Setting up libccolamd3:i386 (1:7.6.1+dfsg-1) ... Setting up libxcb-dri2-0:i386 (1.15-1) ... Setting up dh-strip-nondeterminism (1.13.1-1) ... Setting up libwww-robotrules-perl (6.02-1) ... Setting up libjack-jackd2-0:i386 (1.9.21~dfsg-3+b1) ... Setting up libdrm2:i386 (2.4.120-2) ... Setting up dwz (0.15-1) ... Setting up groff-base (1.23.0-3) ... Setting up libqt5dbus5:i386 (5.15.10+dfsg-7) ... Setting up libxcb-randr0:i386 (1.15-1) ... Setting up libhtml-parser-perl:i386 (3.81-1+b1) ... Setting up gpgconf (2.2.40-1.1+b1) ... Setting up libcurl4:i386 (8.5.0-2) ... Setting up libx11-6:i386 (2:1.8.7-1) ... Setting up libharfbuzz0b:i386 (8.3.0-2) ... Setting up libfontconfig1:i386 (2.15.0-1.1) ... Setting up libsndfile1:i386 (1.2.2-1) ... Setting up libmro-compat-perl (0.15-2) ... Setting up libllvm17:i386 (1:17.0.6-5) ... Setting up libsm6:i386 (2:1.2.3-1) ... Setting up libfftw3-dev:i386 (3.3.10-1+b1) ... Setting up libavahi-client3:i386 (0.8-13+b1) ... Setting up libio-socket-ssl-perl (2.085-1) ... Setting up gpg (2.2.40-1.1+b1) ... Setting up libsub-exporter-perl (0.990-1) ... Setting up libhttp-message-perl (6.45-1) ... Setting up libdrm-amdgpu1:i386 (2.4.120-2) ... Setting up libhtml-form-perl (6.11-1) ... Setting up libiterator-perl (0.03+ds1-2) ... Setting up libxcb-dri3-0:i386 (1.15-1) ... Setting up libinput10:i386 (1.25.0-1) ... Setting up libportaudio2:i386 (19.6.0-1.2+b1) ... Setting up libx11-xcb1:i386 (2:1.8.7-1) ... Setting up libhttp-negotiate-perl (6.01-2) ... Setting up libibverbs1:i386 (48.0-1.1) ... Setting up fontconfig (2.15.0-1.1) ... Regenerating fonts cache... done. Setting up libcarp-assert-more-perl (2.4.0-1) ... Setting up libcholmod5:i386 (1:7.6.1+dfsg-1) ... Setting up libdrm-nouveau2:i386 (2.4.120-2) ... Setting up libxcb1-dev:i386 (1.15-1) ... Setting up libxpm4:i386 (1:3.5.17-1) ... Setting up libiterator-util-perl (0.02+ds1-2) ... Setting up libxrender1:i386 (1:0.9.10-1.1) ... Setting up libgbm1:i386 (23.3.5-1) ... Setting up libhttp-cookies-perl (6.11-1) ... Setting up libspqr4:i386 (1:7.6.1+dfsg-1) ... Setting up libdrm-radeon1:i386 (2.4.120-2) ... Setting up openssh-client (1:9.6p1-4) ... Setting up po-debconf (1.0.21+nmu1) ... Setting up libhtml-tree-perl (5.07-3) ... Setting up libpython3.11-stdlib:i386 (3.11.8-1) ... Setting up libparams-classify-perl:i386 (0.015-2+b2) ... Setting up libpango-1.0-0:i386 (1.52.0+ds-1) ... Setting up libdrm-intel1:i386 (2.4.120-2) ... Setting up libcgi-pm-perl (4.64-1) ... Setting up libgl1-mesa-dri:i386 (23.3.5-1) ... Setting up libx11-dev:i386 (2:1.8.7-1) ... Setting up libxext6:i386 (2:1.3.4-1+b1) ... Setting up libcurl3-gnutls:i386 (8.5.0-2) ... Setting up man-db (2.12.0-3) ... Not building database; man-db/auto-update is not 'true'. Setting up libxml-sax-perl (1.02+dfsg-3) ... update-perl-sax-parsers: Registering Perl SAX parser XML::SAX::PurePerl with priority 10... update-perl-sax-parsers: Updating overall Perl SAX parser modules info file... Creating config file /etc/perl/XML/SAX/ParserDetails.ini with new version Setting up gfortran (4:13.2.0-7) ... update-alternatives: using /usr/bin/gfortran to provide /usr/bin/f95 (f95) in auto mode update-alternatives: using /usr/bin/gfortran to provide /usr/bin/f77 (f77) in auto mode Setting up libcairo2:i386 (1.18.0-1+b1) ... Setting up libqt5network5:i386 (5.15.10+dfsg-7) ... Setting up libxxf86vm1:i386 (1:1.1.4-1+b2) ... Setting up libxnvctrl0:i386 (535.171.04-1) ... Setting up libfeature-compat-class-perl (0.06-1) ... Setting up libqt5sql5:i386 (5.15.10+dfsg-7) ... Setting up tex-common (6.18) ... update-language: texlive-base not installed and configured, doing nothing! Setting up libqt5xml5:i386 (5.15.10+dfsg-7) ... Setting up libegl-mesa0:i386 (23.3.5-1) ... Setting up libnet-smtp-ssl-perl (1.04-2) ... Setting up libmodule-runtime-perl (0.016-2) ... Setting up libmailtools-perl (2.21-3) ... Setting up libxfixes3:i386 (1:6.0.0-2) ... Setting up libcurl4-openssl-dev:i386 (8.5.0-2) ... Setting up libklu2:i386 (1:7.6.1+dfsg-1) ... Setting up libconfig-model-perl (2.153-3) ... Setting up libxinerama1:i386 (2:1.1.4-3) ... Setting up libxml-libxml-perl (2.0207+dfsg+really+2.0134-1+b2) ... update-perl-sax-parsers: Registering Perl SAX parser XML::LibXML::SAX::Parser with priority 50... update-perl-sax-parsers: Registering Perl SAX parser XML::LibXML::SAX with priority 50... update-perl-sax-parsers: Updating overall Perl SAX parser modules info file... Replacing config file /etc/perl/XML/SAX/ParserDetails.ini with new version Setting up libcups2:i386 (2.4.7-1+b1) ... Setting up libumfpack6:i386 (1:7.6.1+dfsg-1) ... Setting up libconst-fast-perl (0.014-2) ... Setting up libhdf5-103-1:i386 (1.10.10+repack-3+b1) ... Setting up libdata-section-perl (0.200008-1) ... Setting up libhdf5-cpp-103-1:i386 (1.10.10+repack-3+b1) ... Setting up libegl1:i386 (1.7.0-1) ... Setting up libpangoft2-1.0-0:i386 (1.52.0+ds-1) ... Setting up libdata-dpath-perl (0.59-1) ... Setting up libstring-rewriteprefix-perl (0.009-1) ... Setting up libpangocairo-1.0-0:i386 (1.52.0+ds-1) ... Setting up libpython3-stdlib:i386 (3.11.6-1) ... Setting up libhdf5-hl-100:i386 (1.10.10+repack-3+b1) ... Setting up libconfig-model-backend-yaml-perl (2.134-2) ... Setting up librdmacm1:i386 (48.0-1.1) ... Setting up python3.11 (3.11.8-1) ... Setting up libxft2:i386 (2.3.6-1+b1) ... Setting up libglx-mesa0:i386 (23.3.5-1) ... Setting up libglx0:i386 (1.7.0-1) ... Setting up libmodule-implementation-perl (0.09-2) ... Setting up libpackage-stash-perl (0.40-1) ... Setting up libimport-into-perl (1.002005-2) ... Setting up libmoo-perl (2.005005-1) ... Setting up libxcursor1:i386 (1:1.2.1-1) ... Setting up liblist-someutils-perl (0.59-1) ... Setting up debhelper (13.15.3) ... Setting up python3 (3.11.6-1) ... Setting up libhwloc-plugins:i386 (2.10.0-1+b1) ... Setting up libmime-tools-perl (5.514-1) ... Setting up libsoftware-license-perl (0.104006-1) ... Setting up libclass-load-perl (0.25-2) ... Setting up libhdf5-hl-cpp-100:i386 (1.10.10+repack-3+b1) ... Setting up libgl1:i386 (1.7.0-1) ... Setting up libhdf5-fortran-102:i386 (1.10.10+repack-3+b1) ... Setting up texinfo (7.1-3) ... Setting up libhdf5-hl-fortran-100:i386 (1.10.10+repack-3+b1) ... Setting up libglx-dev:i386 (1.7.0-1) ... Setting up libmoox-aliases-perl (0.001006-2) ... Setting up libparams-validate-perl:i386 (1.31-2+b1) ... Setting up libb-hooks-endofscope-perl (0.28-1) ... Setting up libgl-dev:i386 (1.7.0-1) ... Setting up libfabric1:i386 (1.17.0-3) ... Setting up libpmix2:i386 (5.0.1-4+b1) ... Setting up libsoftware-licensemoreutils-perl (1.009-1) ... Setting up libopenmpi3:i386 (4.1.6-5) ... Setting up libfltk1.3:i386 (1.3.8-6+b1) ... Setting up libfltk-gl1.3:i386 (1.3.8-6+b1) ... Setting up libqt5gui5:i386 (5.15.10+dfsg-7) ... Setting up libqt5widgets5:i386 (5.15.10+dfsg-7) ... Setting up libfftw3-mpi3:i386 (3.3.10-1+b1) ... Setting up libqt5help5:i386 (5.15.10-6) ... Setting up libgl2ps1.4 (1.4.2+dfsg1-2) ... Setting up libqt5printsupport5:i386 (5.15.10+dfsg-7) ... Setting up libcombblas2.0.0:i386 (2.0.0-3+b1) ... Setting up libhdf5-dev (1.10.10+repack-3+b1) ... update-alternatives: using /usr/lib/i386-linux-gnu/pkgconfig/hdf5-serial.pc to provide /usr/lib/i386-linux-gnu/pkgconfig/hdf5.pc (hdf5.pc) in auto mode Setting up libnamespace-clean-perl (0.27-2) ... Setting up libstring-license-perl (0.0.9-2) ... Setting up libgetopt-long-descriptive-perl (0.111-1) ... Setting up openmpi-bin (4.1.6-5) ... update-alternatives: using /usr/bin/mpirun.openmpi to provide /usr/bin/mpirun (mpirun) in auto mode update-alternatives: using /usr/bin/mpicc.openmpi to provide /usr/bin/mpicc (mpi) in auto mode Setting up licensecheck (3.3.9-1) ... Setting up libhdf5-openmpi-103-1:i386 (1.10.10+repack-3+b1) ... Setting up libptscotch-7.0:i386 (7.0.4-1+b1) ... Setting up libsuperlu-dist8:i386 (8.2.1+dfsg1-1) ... Setting up libapp-cmd-perl (0.336-1) ... Setting up mpi-default-bin (1.15) ... Setting up libqscintilla2-qt5-15:i386 (2.14.1+dfsg-1+b1) ... Setting up libhypre-2.28.0:i386 (2.28.0-8) ... Setting up cme (1.040-1) ... Setting up libscalapack-openmpi2.2:i386 (2.2.1-3+b1) ... Setting up libmumps-5.6:i386 (5.6.2-2+b1) ... Setting up libpetsc-real3.19:i386 (3.19.6+dfsg1-2) ... update-alternatives: using /usr/lib/i386-linux-gnu/libpetsc_real.so.3.19.6 to provide /usr/lib/i386-linux-gnu/libpetsc.so.3.19 (libpetsc.so.3.19) in auto mode Setting up libsundials-nvecparallel-petsc6:i386 (6.4.1+dfsg1-3+b3) ... Setting up libsundials-sunlinsol3:i386 (6.4.1+dfsg1-3+b3) ... Setting up libheif-plugin-dav1d:i386 (1.17.6-1) ... Setting up liblwp-protocol-https-perl (6.14-1) ... Setting up libheif-plugin-libde265:i386 (1.17.6-1) ... Setting up libwww-perl (6.77-1) ... Setting up libheif1:i386 (1.17.6-1) ... Setting up libparse-debcontrol-perl (2.005-6) ... Setting up libhtml-tokeparser-simple-perl (3.16-4) ... Setting up libwww-mechanize-perl (2.18-1) ... Setting up libgd3:i386 (2.3.3-9+b1) ... Setting up libgraphicsmagick-q16-3 (1.4+really1.3.42-1+b1) ... Setting up libgraphicsmagick++-q16-12 (1.4+really1.3.42-1+b1) ... Setting up gnuplot-nox (6.0.0+dfsg1-1) ... update-alternatives: using /usr/bin/gnuplot-nox to provide /usr/bin/gnuplot (gnuplot) in auto mode Setting up lintian (2.117.0) ... Setting up libconfig-model-dpkg-perl (3.004) ... Setting up dh-octave-autopkgtest (1.8.0) ... Setting up octave (8.4.0-1+b1) ... Setting up octave-dev (8.4.0-1+b1) ... Setting up octave-io (2.6.4-3+b1) ... Setting up dh-octave (1.8.0) ... Processing triggers for libc-bin (2.37-15) ... Processing triggers for ca-certificates (20240203) ... Updating certificates in /etc/ssl/certs... 0 added, 0 removed; done. Running hooks in /etc/ca-certificates/update.d... done. Reading package lists... Building dependency tree... Reading state information... Reading extended state information... Initializing package states... Writing extended state information... Building tag database... -> Finished parsing the build-deps I: Building the package I: user script /srv/workspace/pbuilder/29027/tmp/hooks/A99_set_merged_usr starting Not re-configuring usrmerge for trixie I: user script /srv/workspace/pbuilder/29027/tmp/hooks/A99_set_merged_usr finished hostname: Name or service not known I: Running cd /build/reproducible-path/octave-statistics-1.6.5/ && env PATH="/usr/sbin:/usr/bin:/sbin:/bin:/usr/games:/i/capture/the/path" HOME="/nonexistent/second-build" dpkg-buildpackage -us -uc -b && env PATH="/usr/sbin:/usr/bin:/sbin:/bin:/usr/games:/i/capture/the/path" HOME="/nonexistent/second-build" dpkg-genchanges -S > ../octave-statistics_1.6.5-3_source.changes dpkg-buildpackage: info: source package octave-statistics dpkg-buildpackage: info: source version 1.6.5-3 dpkg-buildpackage: info: source distribution unstable dpkg-buildpackage: info: source changed by Rafael Laboissière dpkg-source --before-build . dpkg-buildpackage: info: host architecture i386 debian/rules clean dh clean --buildsystem=octave dh_auto_clean -O--buildsystem=octave dh_octave_clean make[1]: Entering directory '/build/reproducible-path/octave-statistics-1.6.5' make[1]: *** No rule to make target 'clean'. make[1]: *** No rule to make target 'distclean'. make[1]: Leaving directory '/build/reproducible-path/octave-statistics-1.6.5' make[1]: Entering directory '/build/reproducible-path/octave-statistics-1.6.5/src' make[1]: *** No rule to make target 'clean'. make[1]: *** No rule to make target 'distclean'. make[1]: Leaving directory '/build/reproducible-path/octave-statistics-1.6.5/src' dh_autoreconf_clean -O--buildsystem=octave dh_clean -O--buildsystem=octave debian/rules binary dh binary --buildsystem=octave dh_update_autotools_config -O--buildsystem=octave dh_autoreconf -O--buildsystem=octave dh_octave_version -O--buildsystem=octave Checking the Octave version... ok dh_auto_configure -O--buildsystem=octave dh_auto_build -O--buildsystem=octave dh_auto_test -O--buildsystem=octave create-stamp debian/debhelper-build-stamp dh_testroot -O--buildsystem=octave dh_prep -O--buildsystem=octave dh_auto_install -O--buildsystem=octave octave --no-gui --no-history --silent --no-init-file --no-window-system /usr/share/dh-octave/install-pkg.m /build/reproducible-path/octave-statistics-1.6.5/debian/tmp/usr/share/octave/packages /build/reproducible-path/octave-statistics-1.6.5/debian/tmp/usr/lib/i386-linux-gnu/octave/packages make[1]: Entering directory '/build/reproducible-path/octave-statistics-1.6.5/src' /usr/bin/mkoctfile --verbose libsvmread.cc g++ -c -Wdate-time -D_FORTIFY_SOURCE=2 -fPIC -I/usr/include/octave-8.4.0/octave/.. -I/usr/include/octave-8.4.0/octave -pthread -fopenmp -mieee-fp -g -O2 -ffile-prefix-map=/build/reproducible-path/octave-statistics-1.6.5=. -fstack-protector-strong -Wformat -Werror=format-security libsvmread.cc -o /tmp/oct-T1Zfnu.o g++ -I/usr/include/octave-8.4.0/octave/.. -I/usr/include/octave-8.4.0/octave -pthread -fopenmp -mieee-fp -g -O2 -ffile-prefix-map=/build/reproducible-path/octave-statistics-1.6.5=. -fstack-protector-strong -Wformat -Werror=format-security -o libsvmread.oct /tmp/oct-T1Zfnu.o -shared -Wl,-Bsymbolic -Wl,-z,relro -L/usr/lib/i386-linux-gnu -shared -Wl,-Bsymbolic -flto=auto -ffat-lto-objects -Wl,-z,relro /usr/bin/mkoctfile --verbose libsvmwrite.cc g++ -c -Wdate-time -D_FORTIFY_SOURCE=2 -fPIC -I/usr/include/octave-8.4.0/octave/.. -I/usr/include/octave-8.4.0/octave -pthread -fopenmp -mieee-fp -g -O2 -ffile-prefix-map=/build/reproducible-path/octave-statistics-1.6.5=. -fstack-protector-strong -Wformat -Werror=format-security libsvmwrite.cc -o /tmp/oct-j1gwmX.o libsvmwrite.cc: In function 'void write(std::string, ColumnVector, SparseMatrix)': libsvmwrite.cc:75:25: warning: format '%lu' expects argument of type 'long unsigned int', but argument 3 has type 'size_t' {aka 'unsigned int'} [-Wformat=] 75 | fprintf(fp ," %lu:%g", (size_t)ir[k]+1, samples[k]); | ~~^ ~~~~~~~~~~~~~~~ | | | | long unsigned int size_t {aka unsigned int} | %u g++ -I/usr/include/octave-8.4.0/octave/.. -I/usr/include/octave-8.4.0/octave -pthread -fopenmp -mieee-fp -g -O2 -ffile-prefix-map=/build/reproducible-path/octave-statistics-1.6.5=. -fstack-protector-strong -Wformat -Werror=format-security -o libsvmwrite.oct /tmp/oct-j1gwmX.o -shared -Wl,-Bsymbolic -Wl,-z,relro -L/usr/lib/i386-linux-gnu -shared -Wl,-Bsymbolic -flto=auto -ffat-lto-objects -Wl,-z,relro /usr/bin/mkoctfile --verbose svmpredict.cc svm.cpp svm_model_octave.cc g++ -c -Wdate-time -D_FORTIFY_SOURCE=2 -fPIC -I/usr/include/octave-8.4.0/octave/.. -I/usr/include/octave-8.4.0/octave -pthread -fopenmp -mieee-fp -g -O2 -ffile-prefix-map=/build/reproducible-path/octave-statistics-1.6.5=. -fstack-protector-strong -Wformat -Werror=format-security svmpredict.cc -o /tmp/oct-ecGPyW.o g++ -c -Wdate-time -D_FORTIFY_SOURCE=2 -fPIC -I/usr/include/octave-8.4.0/octave/.. -I/usr/include/octave-8.4.0/octave -pthread -fopenmp -mieee-fp -g -O2 -ffile-prefix-map=/build/reproducible-path/octave-statistics-1.6.5=. -fstack-protector-strong -Wformat -Werror=format-security svm.cpp -o /tmp/oct-0R9OWP.o g++ -c -Wdate-time -D_FORTIFY_SOURCE=2 -fPIC -I/usr/include/octave-8.4.0/octave/.. -I/usr/include/octave-8.4.0/octave -pthread -fopenmp -mieee-fp -g -O2 -ffile-prefix-map=/build/reproducible-path/octave-statistics-1.6.5=. -fstack-protector-strong -Wformat -Werror=format-security svm_model_octave.cc -o /tmp/oct-5bRRow.o g++ -I/usr/include/octave-8.4.0/octave/.. -I/usr/include/octave-8.4.0/octave -pthread -fopenmp -mieee-fp -g -O2 -ffile-prefix-map=/build/reproducible-path/octave-statistics-1.6.5=. -fstack-protector-strong -Wformat -Werror=format-security -o svmpredict.oct /tmp/oct-ecGPyW.o /tmp/oct-0R9OWP.o /tmp/oct-5bRRow.o -shared -Wl,-Bsymbolic -Wl,-z,relro -L/usr/lib/i386-linux-gnu -shared -Wl,-Bsymbolic -flto=auto -ffat-lto-objects -Wl,-z,relro /usr/bin/mkoctfile --verbose svmtrain.cc svm.cpp svm_model_octave.cc g++ -c -Wdate-time -D_FORTIFY_SOURCE=2 -fPIC -I/usr/include/octave-8.4.0/octave/.. -I/usr/include/octave-8.4.0/octave -pthread -fopenmp -mieee-fp -g -O2 -ffile-prefix-map=/build/reproducible-path/octave-statistics-1.6.5=. -fstack-protector-strong -Wformat -Werror=format-security svmtrain.cc -o /tmp/oct-32ikD7.o g++ -c -Wdate-time -D_FORTIFY_SOURCE=2 -fPIC -I/usr/include/octave-8.4.0/octave/.. -I/usr/include/octave-8.4.0/octave -pthread -fopenmp -mieee-fp -g -O2 -ffile-prefix-map=/build/reproducible-path/octave-statistics-1.6.5=. -fstack-protector-strong -Wformat -Werror=format-security svm.cpp -o /tmp/oct-TLaugx.o g++ -c -Wdate-time -D_FORTIFY_SOURCE=2 -fPIC -I/usr/include/octave-8.4.0/octave/.. -I/usr/include/octave-8.4.0/octave -pthread -fopenmp -mieee-fp -g -O2 -ffile-prefix-map=/build/reproducible-path/octave-statistics-1.6.5=. -fstack-protector-strong -Wformat -Werror=format-security svm_model_octave.cc -o /tmp/oct-49SEl9.o g++ -I/usr/include/octave-8.4.0/octave/.. -I/usr/include/octave-8.4.0/octave -pthread -fopenmp -mieee-fp -g -O2 -ffile-prefix-map=/build/reproducible-path/octave-statistics-1.6.5=. -fstack-protector-strong -Wformat -Werror=format-security -o svmtrain.oct /tmp/oct-32ikD7.o /tmp/oct-TLaugx.o /tmp/oct-49SEl9.o -shared -Wl,-Bsymbolic -Wl,-z,relro -L/usr/lib/i386-linux-gnu -shared -Wl,-Bsymbolic -flto=auto -ffat-lto-objects -Wl,-z,relro make[1]: Leaving directory '/build/reproducible-path/octave-statistics-1.6.5/src' copyfile /build/reproducible-path/octave-statistics-1.6.5/./src/libsvmread.oct /build/reproducible-path/octave-statistics-1.6.5/./src/libsvmwrite.oct /build/reproducible-path/octave-statistics-1.6.5/./src/svmpredict.oct /build/reproducible-path/octave-statistics-1.6.5/./src/svmtrain.oct /build/reproducible-path/octave-statistics-1.6.5/./src/libsvmread.cc-tst /build/reproducible-path/octave-statistics-1.6.5/./src/libsvmwrite.cc-tst /build/reproducible-path/octave-statistics-1.6.5/./src/svmpredict.cc-tst /build/reproducible-path/octave-statistics-1.6.5/./src/svmtrain.cc-tst /build/reproducible-path/octave-statistics-1.6.5/./inst/i686-pc-linux-gnu-api-v58 warning: function /build/reproducible-path/octave-statistics-1.6.5/debian/tmp/usr/share/octave/packages/statistics-1.6.5/shadow9/mean.m shadows a core library function warning: called from /build/reproducible-path/octave-statistics-1.6.5/debian/tmp/usr/share/octave/packages/statistics-1.6.5/PKG_ADD at line 15 column 3 doc_cache_create>gen_doc_cache_in_dir at line 146 column 5 doc_cache_create at line 62 column 12 install>generate_lookfor_cache at line 842 column 5 install at line 243 column 7 pkg at line 619 column 9 /usr/share/dh-octave/install-pkg.m at line 38 column 1 warning: function /build/reproducible-path/octave-statistics-1.6.5/debian/tmp/usr/share/octave/packages/statistics-1.6.5/shadow9/std.m shadows a core library function warning: called from /build/reproducible-path/octave-statistics-1.6.5/debian/tmp/usr/share/octave/packages/statistics-1.6.5/PKG_ADD at line 15 column 3 doc_cache_create>gen_doc_cache_in_dir at line 146 column 5 doc_cache_create at line 62 column 12 install>generate_lookfor_cache at line 842 column 5 install at line 243 column 7 pkg at line 619 column 9 /usr/share/dh-octave/install-pkg.m at line 38 column 1 warning: function /build/reproducible-path/octave-statistics-1.6.5/debian/tmp/usr/share/octave/packages/statistics-1.6.5/shadow9/median.m shadows a core library function warning: called from /build/reproducible-path/octave-statistics-1.6.5/debian/tmp/usr/share/octave/packages/statistics-1.6.5/PKG_ADD at line 15 column 3 doc_cache_create>gen_doc_cache_in_dir at line 146 column 5 doc_cache_create at line 62 column 12 install>generate_lookfor_cache at line 842 column 5 install at line 243 column 7 pkg at line 619 column 9 /usr/share/dh-octave/install-pkg.m at line 38 column 1 warning: function /build/reproducible-path/octave-statistics-1.6.5/debian/tmp/usr/share/octave/packages/statistics-1.6.5/shadow9/mad.m shadows a core library function warning: called from /build/reproducible-path/octave-statistics-1.6.5/debian/tmp/usr/share/octave/packages/statistics-1.6.5/PKG_ADD at line 15 column 3 doc_cache_create>gen_doc_cache_in_dir at line 146 column 5 doc_cache_create at line 62 column 12 install>generate_lookfor_cache at line 842 column 5 install at line 243 column 7 pkg at line 619 column 9 /usr/share/dh-octave/install-pkg.m at line 38 column 1 warning: function /build/reproducible-path/octave-statistics-1.6.5/debian/tmp/usr/share/octave/packages/statistics-1.6.5/shadow9/var.m shadows a core library function warning: called from /build/reproducible-path/octave-statistics-1.6.5/debian/tmp/usr/share/octave/packages/statistics-1.6.5/PKG_ADD at line 15 column 3 doc_cache_create>gen_doc_cache_in_dir at line 146 column 5 doc_cache_create at line 62 column 12 install>generate_lookfor_cache at line 842 column 5 install at line 243 column 7 pkg at line 619 column 9 /usr/share/dh-octave/install-pkg.m at line 38 column 1 warning: function /build/reproducible-path/octave-statistics-1.6.5/debian/tmp/usr/share/octave/packages/statistics-1.6.5/shadow9/mean.m shadows a core library function warning: called from doc_cache_create>gen_doc_cache_in_dir at line 146 column 5 doc_cache_create at line 62 column 12 install>generate_lookfor_cache at line 842 column 5 install at line 243 column 7 pkg at line 619 column 9 /usr/share/dh-octave/install-pkg.m at line 38 column 1 warning: function /build/reproducible-path/octave-statistics-1.6.5/debian/tmp/usr/share/octave/packages/statistics-1.6.5/shadow9/std.m shadows a core library function warning: called from doc_cache_create>gen_doc_cache_in_dir at line 146 column 5 doc_cache_create at line 62 column 12 install>generate_lookfor_cache at line 842 column 5 install at line 243 column 7 pkg at line 619 column 9 /usr/share/dh-octave/install-pkg.m at line 38 column 1 warning: function /build/reproducible-path/octave-statistics-1.6.5/debian/tmp/usr/share/octave/packages/statistics-1.6.5/shadow9/median.m shadows a core library function warning: called from doc_cache_create>gen_doc_cache_in_dir at line 146 column 5 doc_cache_create at line 62 column 12 install>generate_lookfor_cache at line 842 column 5 install at line 243 column 7 pkg at line 619 column 9 /usr/share/dh-octave/install-pkg.m at line 38 column 1 warning: function /build/reproducible-path/octave-statistics-1.6.5/debian/tmp/usr/share/octave/packages/statistics-1.6.5/shadow9/mad.m shadows a core library function warning: called from doc_cache_create>gen_doc_cache_in_dir at line 146 column 5 doc_cache_create at line 62 column 12 install>generate_lookfor_cache at line 842 column 5 install at line 243 column 7 pkg at line 619 column 9 /usr/share/dh-octave/install-pkg.m at line 38 column 1 warning: function /build/reproducible-path/octave-statistics-1.6.5/debian/tmp/usr/share/octave/packages/statistics-1.6.5/shadow9/var.m shadows a core library function warning: called from doc_cache_create>gen_doc_cache_in_dir at line 146 column 5 doc_cache_create at line 62 column 12 install>generate_lookfor_cache at line 842 column 5 install at line 243 column 7 pkg at line 619 column 9 /usr/share/dh-octave/install-pkg.m at line 38 column 1 For information about changes from previous versions of the statistics package, run 'news statistics'. rm: cannot remove '/build/reproducible-path/octave-statistics-1.6.5/debian/tmp/usr/share/octave/packages/statistics-1.6.5/doc': Is a directory dh_octave_check -O--buildsystem=octave Checking package... Run the unit tests... Checking m files ... warning: function /build/reproducible-path/octave-statistics-1.6.5/debian/tmp/usr/share/octave/packages/statistics-1.6.5/shadow9/mean.m shadows a core library function warning: called from /tmp/tmp.3GT7NzdGmN at line 12 column 1 warning: function /build/reproducible-path/octave-statistics-1.6.5/debian/tmp/usr/share/octave/packages/statistics-1.6.5/shadow9/std.m shadows a core library function warning: called from /tmp/tmp.3GT7NzdGmN at line 12 column 1 warning: function /build/reproducible-path/octave-statistics-1.6.5/debian/tmp/usr/share/octave/packages/statistics-1.6.5/shadow9/median.m shadows a core library function warning: called from /tmp/tmp.3GT7NzdGmN at line 12 column 1 warning: function /build/reproducible-path/octave-statistics-1.6.5/debian/tmp/usr/share/octave/packages/statistics-1.6.5/shadow9/mad.m shadows a core library function warning: called from /tmp/tmp.3GT7NzdGmN at line 12 column 1 warning: function /build/reproducible-path/octave-statistics-1.6.5/debian/tmp/usr/share/octave/packages/statistics-1.6.5/shadow9/var.m shadows a core library function warning: called from /tmp/tmp.3GT7NzdGmN at line 12 column 1 [inst/ff2n.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/ff2n.m ***** error ff2n (); ***** error ff2n (2, 5); ***** error ff2n (2.5); ***** error ff2n (0); ***** error ff2n (-3); ***** error ff2n (3+2i); ***** error ff2n (Inf); ***** error ff2n (NaN); ***** test A = ff2n (3); assert (A, fullfact (3)); ***** test A = ff2n (8); assert (A, fullfact (8)); 10 tests, 10 passed, 0 known failure, 0 skipped [inst/cholcov.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/cholcov.m ***** demo C1 = [2, 1, 1, 2; 1, 2, 1, 2; 1, 1, 2, 2; 2, 2, 2, 3] T = cholcov (C1) C2 = T'*T ***** test C1 = [2, 1, 1, 2; 1, 2, 1, 2; 1, 1, 2, 2; 2, 2, 2, 3]; T = cholcov (C1); assert (C1, T'*T, 1e-15 * ones (size (C1))); 1 test, 1 passed, 0 known failure, 0 skipped [inst/levene_test.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/levene_test.m ***** error levene_test () ***** error ... levene_test (1, 2, 3, 4, 5); ***** error levene_test (randn (50, 2), 0); ***** error ... levene_test (randn (50, 2), [1, 2, 3]); ***** error ... levene_test (randn (50, 1), ones (55, 1)); ***** error ... levene_test (randn (50, 1), ones (50, 2)); ***** error ... levene_test (randn (50, 2), [], 1.2); ***** error ... levene_test (randn (50, 2), "some_string"); ***** error ... levene_test (randn (50, 2), [], "alpha"); ***** error ... levene_test (randn (50, 1), [ones(25, 1); 2*ones(25, 1)], 1.2); ***** error ... levene_test (randn (50, 1), [ones(25, 1); 2*ones(25, 1)], "err"); ***** error ... levene_test (randn (50, 1), [ones(25, 1); 2*ones(25, 1)], 0.05, "type"); ***** warning ... levene_test (randn (50, 1), [ones(24, 1); 2*ones(25, 1); 3]); ***** test load examgrades [h, pval, W, df] = levene_test (grades); assert (h, 1); assert (pval, 9.523239714592791e-07, 1e-14); assert (W, 8.59529, 1e-5); assert (df, [4, 595]); ***** test load examgrades [h, pval, W, df] = levene_test (grades, [], "quadratic"); assert (h, 1); assert (pval, 9.523239714592791e-07, 1e-14); assert (W, 8.59529, 1e-5); assert (df, [4, 595]); ***** test load examgrades [h, pval, W, df] = levene_test (grades, [], "median"); assert (h, 1); assert (pval, 1.312093241723211e-06, 1e-14); assert (W, 8.415969, 1e-6); assert (df, [4, 595]); ***** test load examgrades [h, pval, W, df] = levene_test (grades(:,[1:3])); assert (h, 1); assert (pval, 0.004349390980463497, 1e-14); assert (W, 5.52139, 1e-5); assert (df, [2, 357]); ***** test load examgrades [h, pval, W, df] = levene_test (grades(:,[1:3]), "median"); assert (h, 1); assert (pval, 0.004355216763951453, 1e-14); assert (W, 5.52001, 1e-5); assert (df, [2, 357]); ***** test load examgrades [h, pval, W, df] = levene_test (grades(:,[3,4]), "quadratic"); assert (h, 0); assert (pval, 0.1807494957440653, 2e-14); assert (W, 1.80200, 1e-5); assert (df, [1, 238]); ***** test load examgrades [h, pval, W, df] = levene_test (grades(:,[3,4]), "median"); assert (h, 0); assert (pval, 0.1978225622063785, 2e-14); assert (W, 1.66768, 1e-5); assert (df, [1, 238]); 20 tests, 20 passed, 0 known failure, 0 skipped [inst/ismissing.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/ismissing.m ***** assert (ismissing ([1,NaN,3]), [false,true,false]) ***** assert (ismissing ('abcd f'), [false,false,false,false,true,false]) ***** assert (ismissing ({'xxx','','xyz'}), [false,true,false]) ***** assert (ismissing ({'x','','y'}), [false,true,false]) ***** assert (ismissing ({'x','','y';'z','a',''}), logical([0,1,0;0,0,1])) ***** assert (ismissing ([1,2;NaN,2]), [false,false;true,false]) ***** assert (ismissing ([1,2;NaN,2], 2), [false,true;false,true]) ***** assert (ismissing ([1,2;NaN,2], [1 2]), [true,true;false,true]) ***** assert (ismissing ([1,2;NaN,2], NaN), [false,false;true,false]) ***** assert (ismissing (cat(3,magic(2),magic(2))), logical (zeros (2,2,2))) ***** assert (ismissing (cat(3,magic(2),[1 2;3 NaN])), logical (cat(3,[0,0;0,0],[0,0;0,1]))) ***** assert (ismissing ([1 2; 3 4], [5 1; 2 0]), logical([1 1; 0 0])) ***** assert (ismissing (cat(3,'f oo','ba r')), logical(cat(3,[0 1 0 0],[0 0 1 0]))) ***** assert (ismissing (cat(3,{'foo'},{''},{'bar'})), logical(cat(3,0,1,0))) ***** assert (ismissing (double (NaN)), true) ***** assert (ismissing (single (NaN)), true) ***** assert (ismissing (' '), true) ***** assert (ismissing ({''}), true) ***** assert (ismissing ({' '}), false) ***** assert (ismissing (double (eye(3)), single (1)), logical(eye(3))) ***** assert (ismissing (double (eye(3)), true), logical(eye(3))) ***** assert (ismissing (double (eye(3)), int32 (1)), logical(eye(3))) ***** assert (ismissing (single (eye(3)), true), logical(eye(3))) ***** assert (ismissing (single (eye(3)), double (1)), logical(eye(3))) ***** assert (ismissing (single(eye(3)), int32 (1)), logical(eye(3))) ***** assert (ismissing ({'123', '', 123}), [false false false]) ***** assert (ismissing (logical ([1 0 1])), [false false false]) ***** assert (ismissing (int32 ([1 2 3])), [false false false]) ***** assert (ismissing (uint32 ([1 2 3])), [false false false]) ***** assert (ismissing ({1, 2, 3}), [false false false]) ***** assert (ismissing ([struct struct struct]), [false false false]) ***** assert (ismissing (logical (eye(3)), true), logical(eye(3))) ***** assert (ismissing (logical (eye(3)), double (1)), logical(eye(3))) ***** assert (ismissing (logical (eye(3)), single (1)), logical(eye(3))) ***** assert (ismissing (logical (eye(3)), int32 (1)), logical(eye(3))) ***** assert (ismissing (int32 (eye(3)), int32 (1)), logical(eye(3))) ***** assert (ismissing (int32 (eye(3)), true), logical(eye(3))) ***** assert (ismissing (int32 (eye(3)), double (1)), logical(eye(3))) ***** assert (ismissing (int32 (eye(3)), single (1)), logical(eye(3))) ***** assert (ismissing ([]), logical([])) ***** assert (ismissing (''), logical([])) ***** assert (ismissing (ones (0,1)), logical(ones(0,1))) ***** assert (ismissing (ones (1,0)), logical(ones(1,0))) ***** assert (ismissing (ones (1,2,0)), logical(ones(1,2,0))) ***** error ismissing () ***** error <'indicator' and 'A' must have the same> ismissing ([1 2; 3 4], "abc") ***** error <'indicator' and 'A' must have the same> ismissing ({"", "", ""}, 1) ***** error <'indicator' and 'A' must have the same> ismissing (1, struct) ***** error ismissing (struct, 1) 49 tests, 49 passed, 0 known failure, 0 skipped [inst/einstein.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/einstein.m ***** demo einstein (0.4, 0.6) ***** demo einstein (0.2, 0.5) ***** demo einstein (0.6, 0.1) ***** test hf = figure ("visible", "off"); unwind_protect tiles = einstein (0.4, 0.6); assert (isstruct (tiles), true); unwind_protect_cleanup close (hf); end_unwind_protect warning: using the gnuplot graphics toolkit is discouraged The gnuplot graphics toolkit is not actively maintained and has a number of limitations that are unlikely to be fixed. Communication with gnuplot uses a one-directional pipe and limited information is passed back to the Octave interpreter so most changes made interactively in the plot window will not be reflected in the graphics properties managed by Octave. For example, if the plot window is closed with a mouse click, Octave will not be notified and will not update its internal list of open figure windows. The qt toolkit is recommended instead. ***** error einstein ***** error einstein (0.5) ***** error einstein (0, 0.9) ***** error einstein (0.4, 1) ***** error einstein (-0.4, 1) 6 tests, 6 passed, 0 known failure, 0 skipped [inst/fitrgam.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/fitrgam.m ***** demo # Train a RegressionGAM Model for synthetic values f1 = @(x) cos (3 *x); f2 = @(x) x .^ 3; # generate x1 and x2 for f1 and f2 x1 = 2 * rand (50, 1) - 1; x2 = 2 * rand (50, 1) - 1; # calculate y y = f1(x1) + f2(x2); # add noise y = y + y .* 0.2 .* rand (50,1); X = [x1, x2]; # create an object a = fitrgam (X, y, "tol", 1e-3) ***** test x = [1, 2, 3; 4, 5, 6; 7, 8, 9; 3, 2, 1]; y = [1; 2; 3; 4]; a = fitrgam (x, y); assert ({a.X, a.Y}, {x, y}) assert ({a.BaseModel.Intercept}, {2.5000}) assert ({a.Knots, a.Order, a.DoF}, {[5, 5, 5], [3, 3, 3], [8, 8, 8]}) assert ({a.NumObservations, a.NumPredictors}, {4, 3}) assert ({a.ResponseName, a.PredictorNames}, {"Y", {"x1", "x2", "x3"}}) assert ({a.Formula}, {[]}) ***** test x = [1, 2, 3, 4; 4, 5, 6, 7; 7, 8, 9, 1; 3, 2, 1, 2]; y = [1; 2; 3; 4]; pnames = {"A", "B", "C", "D"}; formula = "Y ~ A + B + C + D + A:C"; intMat = logical ([1,0,0,0;0,1,0,0;0,0,1,0;0,0,0,1;1,0,1,0]); a = fitrgam (x, y, "predictors", pnames, "formula", formula); assert ({a.IntMatrix}, {intMat}) assert ({a.ResponseName, a.PredictorNames}, {"Y", pnames}) assert ({a.Formula}, {formula}) ***** error fitrgam () ***** error fitrgam (ones(10,2)) ***** error fitrgam (ones (4,2), ones (4, 1), "K") ***** error fitrgam (ones (4,2), ones (3, 1)) ***** error fitrgam (ones (4,2), ones (3, 1), "K", 2) 7 tests, 7 passed, 0 known failure, 0 skipped [inst/fitlm.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/fitlm.m ***** demo y = [ 8.706 10.362 11.552 6.941 10.983 10.092 6.421 14.943 15.931 ... 22.968 18.590 16.567 15.944 21.637 14.492 17.965 18.851 22.891 ... 22.028 16.884 17.252 18.325 25.435 19.141 21.238 22.196 18.038 ... 22.628 31.163 26.053 24.419 32.145 28.966 30.207 29.142 33.212 ... 25.694 ]'; X = [1 1 1 1 1 1 1 1 2 2 2 2 2 3 3 3 3 3 3 3 3 4 4 4 4 4 4 4 5 5 5 5 5 5 5 5 5]'; [TAB,STATS] = fitlm (X,y,"linear","CategoricalVars",1,"display","on"); ***** demo popcorn = [5.5, 4.5, 3.5; 5.5, 4.5, 4.0; 6.0, 4.0, 3.0; ... 6.5, 5.0, 4.0; 7.0, 5.5, 5.0; 7.0, 5.0, 4.5]; brands = {'Gourmet', 'National', 'Generic'; ... 'Gourmet', 'National', 'Generic'; ... 'Gourmet', 'National', 'Generic'; ... 'Gourmet', 'National', 'Generic'; ... 'Gourmet', 'National', 'Generic'; ... 'Gourmet', 'National', 'Generic'}; popper = {'oil', 'oil', 'oil'; 'oil', 'oil', 'oil'; 'oil', 'oil', 'oil'; ... 'air', 'air', 'air'; 'air', 'air', 'air'; 'air', 'air', 'air'}; [TAB, STATS] = fitlm ({brands(:),popper(:)},popcorn(:),"interactions",... "CategoricalVars",[1,2],"display","on"); ***** test y = [ 8.706 10.362 11.552 6.941 10.983 10.092 6.421 14.943 15.931 ... 22.968 18.590 16.567 15.944 21.637 14.492 17.965 18.851 22.891 ... 22.028 16.884 17.252 18.325 25.435 19.141 21.238 22.196 18.038 ... 22.628 31.163 26.053 24.419 32.145 28.966 30.207 29.142 33.212 ... 25.694 ]'; X = [1 1 1 1 1 1 1 1 2 2 2 2 2 3 3 3 3 3 3 3 3 4 4 4 4 4 4 4 5 5 5 5 5 5 5 5 5]'; [TAB,STATS] = fitlm (X,y,"continuous",[],"display","off"); [TAB,STATS] = fitlm (X,y,"CategoricalVars",1,"display","off"); [TAB,STATS] = fitlm (X,y,"constant","categorical",1,"display","off"); [TAB,STATS] = fitlm (X,y,"linear","categorical",1,"display","off"); [TAB,STATS] = fitlm (X,y,[0,0;1,0],"categorical",1,"display","off"); assert (TAB{2,2}, 10, 1e-04); assert (TAB{3,2}, 7.99999999999999, 1e-09); assert (TAB{4,2}, 8.99999999999999, 1e-09); assert (TAB{5,2}, 11.0001428571429, 1e-09); assert (TAB{6,2}, 19.0001111111111, 1e-09); assert (TAB{2,3}, 1.01775379540949, 1e-09); assert (TAB{3,3}, 1.64107868458008, 1e-09); assert (TAB{4,3}, 1.43932122062479, 1e-09); assert (TAB{5,3}, 1.48983900477565, 1e-09); assert (TAB{6,3}, 1.3987687997822, 1e-09); assert (TAB{2,6}, 9.82555903510687, 1e-09); assert (TAB{3,6}, 4.87484242844031, 1e-09); assert (TAB{4,6}, 6.25294748040552, 1e-09); assert (TAB{5,6}, 7.38344399756088, 1e-09); assert (TAB{6,6}, 13.5834536158296, 1e-09); assert (TAB{3,7}, 2.85812420217862e-05, 1e-12); assert (TAB{4,7}, 5.22936741204002e-07, 1e-06); assert (TAB{5,7}, 2.12794763209106e-08, 1e-07); assert (TAB{6,7}, 7.82091664406755e-15, 1e-08); ***** test popcorn = [5.5, 4.5, 3.5; 5.5, 4.5, 4.0; 6.0, 4.0, 3.0; ... 6.5, 5.0, 4.0; 7.0, 5.5, 5.0; 7.0, 5.0, 4.5]; brands = bsxfun (@times, ones(6,1), [1,2,3]); popper = bsxfun (@times, [1;1;1;2;2;2], ones(1,3)); [TAB, STATS] = fitlm ({brands(:),popper(:)},popcorn(:),"interactions",... "categoricalvars",[1,2],"display","off"); assert (TAB{2,2}, 5.66666666666667, 1e-09); assert (TAB{3,2}, -1.33333333333333, 1e-09); assert (TAB{4,2}, -2.16666666666667, 1e-09); assert (TAB{5,2}, 1.16666666666667, 1e-09); assert (TAB{6,2}, -0.333333333333334, 1e-09); assert (TAB{7,2}, -0.166666666666667, 1e-09); assert (TAB{2,3}, 0.215165741455965, 1e-09); assert (TAB{3,3}, 0.304290309725089, 1e-09); assert (TAB{4,3}, 0.304290309725089, 1e-09); assert (TAB{5,3}, 0.304290309725089, 1e-09); assert (TAB{6,3}, 0.43033148291193, 1e-09); assert (TAB{7,3}, 0.43033148291193, 1e-09); assert (TAB{2,6}, 26.3362867542108, 1e-09); assert (TAB{3,6}, -4.38178046004138, 1e-09); assert (TAB{4,6}, -7.12039324756724, 1e-09); assert (TAB{5,6}, 3.83405790253621, 1e-09); assert (TAB{6,6}, -0.774596669241495, 1e-09); assert (TAB{7,6}, -0.387298334620748, 1e-09); assert (TAB{2,7}, 5.49841502258254e-12, 1e-09); assert (TAB{3,7}, 0.000893505495903642, 1e-09); assert (TAB{4,7}, 1.21291454302428e-05, 1e-09); assert (TAB{5,7}, 0.00237798044119407, 1e-09); assert (TAB{6,7}, 0.453570536021938, 1e-09); assert (TAB{7,7}, 0.705316781644046, 1e-09); ## Test with string ids for categorical variables brands = {'Gourmet', 'National', 'Generic'; ... 'Gourmet', 'National', 'Generic'; ... 'Gourmet', 'National', 'Generic'; ... 'Gourmet', 'National', 'Generic'; ... 'Gourmet', 'National', 'Generic'; ... 'Gourmet', 'National', 'Generic'}; popper = {'oil', 'oil', 'oil'; 'oil', 'oil', 'oil'; 'oil', 'oil', 'oil'; ... 'air', 'air', 'air'; 'air', 'air', 'air'; 'air', 'air', 'air'}; [TAB, STATS] = fitlm ({brands(:),popper(:)},popcorn(:),"interactions",... "categoricalvars",[1,2],"display","off"); ***** test load carsmall X = [Weight,Horsepower,Acceleration]; [TAB, STATS] = fitlm (X, MPG,"constant","display","off"); [TAB, STATS] = fitlm (X, MPG,"linear","display","off"); assert (TAB{2,2}, 47.9767628118615, 1e-09); assert (TAB{3,2}, -0.00654155878851796, 1e-09); assert (TAB{4,2}, -0.0429433065881864, 1e-09); assert (TAB{5,2}, -0.0115826516894871, 1e-09); assert (TAB{2,3}, 3.87851641748551, 1e-09); assert (TAB{3,3}, 0.00112741016370336, 1e-09); assert (TAB{4,3}, 0.0243130608813806, 1e-09); assert (TAB{5,3}, 0.193325043113178, 1e-09); assert (TAB{2,6}, 12.369874881944, 1e-09); assert (TAB{3,6}, -5.80228828790225, 1e-09); assert (TAB{4,6}, -1.76626492228599, 1e-09); assert (TAB{5,6}, -0.0599128364487485, 1e-09); assert (TAB{2,7}, 4.89570341688996e-21, 1e-09); assert (TAB{3,7}, 9.87424814144e-08, 1e-09); assert (TAB{4,7}, 0.0807803098213114, 1e-09); assert (TAB{5,7}, 0.952359384151778, 1e-09); 3 tests, 3 passed, 0 known failure, 0 skipped [inst/combnk.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/combnk.m ***** demo c = combnk (1:5, 2); disp ("All pairs of integers between 1 and 5:"); disp (c); ***** test c = combnk (1:3, 2); assert (c, [1, 2; 1, 3; 2, 3]); ***** test c = combnk (1:3, 6); assert (isempty (c)); ***** test c = combnk ({1, 2, 3}, 2); assert (c, {1, 2; 1, 3; 2, 3}); ***** test c = combnk ("hello", 2); assert (c, ["lo"; "lo"; "ll"; "eo"; "el"; "el"; "ho"; "hl"; "hl"; "he"]); 4 tests, 4 passed, 0 known failure, 0 skipped [inst/tabulate.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/tabulate.m ***** demo ## Generate a frequency table for a vector of data in a cell array load patients ## Display the first seven entries of the Gender variable gender = Gender(1:7) ## Compute the equency table that shows the number and ## percentage of Male and Female patients tabulate (Gender) ***** demo ## Create a frequency table for a vector of positive integers load patients ## Display the first seven entries of the Gender variable height = Height(1:7) ## Create a frequency table that shows, in its second and third columns, ## the number and percentage of patients with a particular height. table = tabulate (Height); ## Display the first and last seven entries of the frequency table first = table(1:7,:) last = table(end-6:end,:) ***** demo ## Create a frequency table from a character array load carsmall ## Tabulate the data in the Origin variable, which shows the ## country of origin of each car in the data set tabulate (Origin) ***** demo ## Create a frequency table from a numeric vector with NaN values load carsmall ## The carsmall dataset contains measurements of 100 cars total_cars = length (MPG) ## For six cars, the MPG value is missing missingMPG = length (MPG(isnan (MPG))) ## Create a frequency table using MPG tabulate (MPG) table = tabulate (MPG); ## Only 94 cars were used valid_cars = sum (table(:,2)) ***** test load patients table = tabulate (Gender); assert (table{1,1}, "Male"); assert (table{2,1}, "Female"); assert (table{1,2}, 47); assert (table{2,2}, 53); ***** test load patients table = tabulate (Height); assert (table(end-4,:), [68, 15, 15]); assert (table(end-3,:), [69, 8, 8]); assert (table(end-2,:), [70, 11, 11]); assert (table(end-1,:), [71, 10, 10]); assert (table(end,:), [72, 4, 4]); ***** error tabulate (ones (3)) ***** error tabulate ({1, 2, 3, 4}) ***** error ... tabulate ({"a", "b"; "a", "c"}) 5 tests, 5 passed, 0 known failure, 0 skipped [inst/vartestn.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/vartestn.m ***** demo ## Test the null hypothesis that the variances are equal across the five ## columns of data in the students’ exam grades matrix, grades. load examgrades vartestn (grades) ***** demo ## Test the null hypothesis that the variances in miles per gallon (MPG) are ## equal across different model years. load carsmall vartestn (MPG, Model_Year) ***** demo ## Use Levene’s test to test the null hypothesis that the variances in miles ## per gallon (MPG) are equal across different model years. load carsmall p = vartestn (MPG, Model_Year, "TestType", "LeveneAbsolute") ***** demo ## Test the null hypothesis that the variances are equal across the five ## columns of data in the students’ exam grades matrix, grades, using the ## Brown-Forsythe test. Suppress the display of the summary table of ## statistics and the box plot. load examgrades [p, stats] = vartestn (grades, "TestType", "BrownForsythe", "Display", "off") ***** error vartestn (); ***** error vartestn (1); ***** error ... vartestn ([1, 2, 3, 4, 5, 6, 7]); ***** error ... vartestn ([1, 2, 3, 4, 5, 6, 7], []); ***** error ... vartestn ([1, 2, 3, 4, 5, 6, 7], "TestType", "LeveneAbsolute"); ***** error ... vartestn ([1, 2, 3, 4, 5, 6, 7], [], "TestType", "LeveneAbsolute"); ***** error ... vartestn ([1, 2, 3, 4, 5, 6, 7], [1, 1, 1, 2, 2, 2, 2], "Display", "some"); ***** error ... vartestn (ones (50,3), "Display", "some"); ***** error ... vartestn (ones (50,3), "Display", "off", "testtype", "some"); ***** error ... vartestn (ones (50,3), [], "som"); ***** error ... vartestn (ones (50,3), [], "some", "some"); ***** error ... vartestn (ones (50,3), [1, 2], "Display", "off"); ***** test load examgrades [p, stat] = vartestn (grades, "Display", "off"); assert (p, 7.908647337018238e-08, 1e-14); assert (stat.chisqstat, 38.7332, 1e-4); assert (stat.df, 4); ***** test load examgrades [p, stat] = vartestn (grades, "Display", "off", "TestType", "LeveneAbsolute"); assert (p, 9.523239714592791e-07, 1e-14); assert (stat.fstat, 8.5953, 1e-4); assert (stat.df, [4, 595]); ***** test load examgrades [p, stat] = vartestn (grades, "Display", "off", "TestType", "LeveneQuadratic"); assert (p, 7.219514351897161e-07, 1e-14); assert (stat.fstat, 8.7503, 1e-4); assert (stat.df, [4, 595]); ***** test load examgrades [p, stat] = vartestn (grades, "Display", "off", "TestType", "BrownForsythe"); assert (p, 1.312093241723211e-06, 1e-14); assert (stat.fstat, 8.4160, 1e-4); assert (stat.df, [4, 595]); ***** test load examgrades [p, stat] = vartestn (grades, "Display", "off", "TestType", "OBrien"); assert (p, 8.235660885480556e-07, 1e-14); assert (stat.fstat, 8.6766, 1e-4); assert (stat.df, [4, 595]); 17 tests, 17 passed, 0 known failure, 0 skipped [inst/chi2gof.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/chi2gof.m ***** demo x = normrnd (50, 5, 100, 1); [h, p, stats] = chi2gof (x) [h, p, stats] = chi2gof (x, "cdf", @(x)normcdf (x, mean(x), std(x))) [h, p, stats] = chi2gof (x, "cdf", {@normcdf, mean(x), std(x)}) ***** demo x = rand (100,1 ); n = length (x); binedges = linspace (0, 1, 11); expectedCounts = n * diff (binedges); [h, p, stats] = chi2gof (x, "binedges", binedges, "expected", expectedCounts) ***** demo bins = 0:5; obsCounts = [6 16 10 12 4 2]; n = sum(obsCounts); lambdaHat = sum(bins.*obsCounts) / n; expCounts = n * poisspdf(bins,lambdaHat); [h, p, stats] = chi2gof (bins, "binctrs", bins, "frequency", obsCounts, ... "expected", expCounts, "nparams",1) ***** error chi2gof () ***** error chi2gof ([2,3;3,4]) ***** error chi2gof ([1,2,3,4], "nbins", 3, "ctrs", [2,3,4]) ***** error chi2gof ([1,2,3,4], "frequency", [2,3,2]) ***** error chi2gof ([1,2,3,4], "frequency", [2,3,2,-2]) ***** error chi2gof ([1,2,3,4], "frequency", [2,3,2,2], "nparams", i) ***** error chi2gof ([1,2,3,4], "frequency", [2,3,2,2], "alpha", 1.3) ***** error chi2gof ([1,2,3,4], "expected", [-3,2,2]) ***** error chi2gof ([1,2,3,4], "expected", [3,2,2], "nbins", 5) ***** error chi2gof ([1,2,3,4], "cdf", @normcdff) ***** test x = [1 2 1 3 2 4 3 2 4 3 2 2]; [h, p, stats] = chi2gof (x); assert (h, 0); assert (p, NaN); assert (stats.chi2stat, 0.1205375022748029, 1e-14); assert (stats.df, 0); assert (stats.edges, [1, 2.5, 4], 1e-14); assert (stats.O, [7, 5], 1e-14); assert (stats.E, [6.399995519909668, 5.600004480090332], 1e-14); 11 tests, 11 passed, 0 known failure, 0 skipped [inst/mcnemar_test.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/mcnemar_test.m ***** test [h, pval, chisq] = mcnemar_test ([101,121;59,33]); assert (h, 1); assert (pval, 3.8151e-06, 1e-10); assert (chisq, 21.356, 1e-3); ***** test [h, pval, chisq] = mcnemar_test ([59,6;16,80]); assert (h, 1); assert (pval, 0.034690, 1e-6); assert (isempty (chisq), true); ***** test [h, pval, chisq] = mcnemar_test ([59,6;16,80], 0.01); assert (h, 0); assert (pval, 0.034690, 1e-6); assert (isempty (chisq), true); ***** test [h, pval, chisq] = mcnemar_test ([59,6;16,80], "mid-p"); assert (h, 1); assert (pval, 0.034690, 1e-6); assert (isempty (chisq), true); ***** test [h, pval, chisq] = mcnemar_test ([59,6;16,80], "asymptotic"); assert (h, 1); assert (pval, 0.033006, 1e-6); assert (chisq, 4.5455, 1e-4); ***** test [h, pval, chisq] = mcnemar_test ([59,6;16,80], "exact"); assert (h, 0); assert (pval, 0.052479, 1e-6); assert (isempty (chisq), true); ***** test [h, pval, chisq] = mcnemar_test ([59,6;16,80], "corrected"); assert (h, 0); assert (pval, 0.055009, 1e-6); assert (chisq, 3.6818, 1e-4); ***** test [h, pval, chisq] = mcnemar_test ([59,6;16,80], 0.1, "corrected"); assert (h, 1); assert (pval, 0.055009, 1e-6); assert (chisq, 3.6818, 1e-4); ***** error mcnemar_test (59, 6, 16, 80) ***** error mcnemar_test (ones (3, 3)) ***** error ... mcnemar_test ([59,6;16,-80]) ***** error ... mcnemar_test ([59,6;16,4.5]) ***** error ... mcnemar_test ([59,6;16,80], {""}) ***** error ... mcnemar_test ([59,6;16,80], -0.2) ***** error ... mcnemar_test ([59,6;16,80], [0.05, 0.1]) ***** error ... mcnemar_test ([59,6;16,80], 1) ***** error ... mcnemar_test ([59,6;16,80], "") 17 tests, 17 passed, 0 known failure, 0 skipped [inst/regress.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/regress.m ***** test % Longley data from the NIST Statistical Reference Dataset Z = [ 60323 83.0 234289 2356 1590 107608 1947 61122 88.5 259426 2325 1456 108632 1948 60171 88.2 258054 3682 1616 109773 1949 61187 89.5 284599 3351 1650 110929 1950 63221 96.2 328975 2099 3099 112075 1951 63639 98.1 346999 1932 3594 113270 1952 64989 99.0 365385 1870 3547 115094 1953 63761 100.0 363112 3578 3350 116219 1954 66019 101.2 397469 2904 3048 117388 1955 67857 104.6 419180 2822 2857 118734 1956 68169 108.4 442769 2936 2798 120445 1957 66513 110.8 444546 4681 2637 121950 1958 68655 112.6 482704 3813 2552 123366 1959 69564 114.2 502601 3931 2514 125368 1960 69331 115.7 518173 4806 2572 127852 1961 70551 116.9 554894 4007 2827 130081 1962 ]; % Results certified by NIST using 500 digit arithmetic % b and standard error in b V = [ -3482258.63459582 890420.383607373 15.0618722713733 84.9149257747669 -0.358191792925910E-01 0.334910077722432E-01 -2.02022980381683 0.488399681651699 -1.03322686717359 0.214274163161675 -0.511041056535807E-01 0.226073200069370 1829.15146461355 455.478499142212 ]; Rsq = 0.995479004577296; F = 330.285339234588; y = Z(:,1); X = [ones(rows(Z),1), Z(:,2:end)]; alpha = 0.05; [b, bint, r, rint, stats] = regress (y, X, alpha); assert(b,V(:,1),4e-6); assert(stats(1),Rsq,1e-12); assert(stats(2),F,3e-8); assert(((bint(:,1)-bint(:,2))/2)/tinv(alpha/2,9),V(:,2),-1.e-5); warning: matrix singular to machine precision, rcond = 3.50566e-20 warning: called from regress at line 131 column 7 __test__ at line 33 column 28 test at line 682 column 11 /tmp/tmp.3GT7NzdGmN at line 110 column 31 1 test, 1 passed, 0 known failure, 0 skipped [inst/geomean.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/geomean.m ***** test x = [0:10]; y = [x;x+5;x+10]; assert (geomean (x), 0); m = [0 9.462942809849169 14.65658770861967]; assert (geomean (y, 2), m', 4e-14); assert (geomean (y, "all"), 0); y(2,4) = NaN; m(2) = 9.623207231679554; assert (geomean (y, 2), [0 NaN m(3)]', 4e-14); assert (geomean (y', "omitnan"), m, 4e-14); z = y + 20; assert (geomean (z, "all"), NaN); assert (geomean (z, "all", "includenan"), NaN); assert (geomean (z, "all", "omitnan"), 29.59298474535024, 4e-14); m = [24.79790781765634 NaN 34.85638839503932]; assert (geomean (z'), m, 4e-14); assert (geomean (z', "includenan"), m, 4e-14); m(2) = 30.02181156156319; assert (geomean (z', "omitnan"), m, 4e-14); assert (geomean (z, 2, "omitnan"), m', 4e-14); ***** test x = repmat ([1:20;6:25], [5 2 6 3]); assert (size (geomean (x, [3 2])), [10 1 1 3]); assert (size (geomean (x, [1 2])), [1 1 6 3]); assert (size (geomean (x, [1 2 4])), [1 1 6]); assert (size (geomean (x, [1 4 3])), [1 40]); assert (size (geomean (x, [1 2 3 4])), [1 1]); ***** test x = repmat ([1:20;6:25], [5 2 6 3]); m = repmat ([8.304361203739333;14.3078118884256], [5 1 1 3]); assert (geomean (x, [3 2]), m, 4e-13); x(2,5,6,3) = NaN; m(2,3) = NaN; assert (geomean (x, [3 2]), m, 4e-13); m(2,3) = 14.3292729579901; assert (geomean (x, [3 2], "omitnan"), m, 4e-13); ***** error geomean ("char") ***** error geomean ([1 -1 3]) ***** error ... geomean (repmat ([1:20;6:25], [5 2 6 3 5]), -1) ***** error ... geomean (repmat ([1:20;6:25], [5 2 6 3 5]), 0) ***** error ... geomean (repmat ([1:20;6:25], [5 2 6 3 5]), [1 1]) 8 tests, 8 passed, 0 known failure, 0 skipped [inst/pdist2.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/pdist2.m ***** shared x, y, xx x = [1, 1, 1; 2, 2, 2; 3, 3, 3]; y = [0, 0, 0; 1, 2, 3; 0, 2, 4; 4, 7, 1]; xx = [1 2 3; 4 5 6; 7 8 9; 3 2 1]; ***** test d = sqrt([3, 5, 11, 45; 12, 2, 8, 30; 27, 5, 11, 21]); assert (pdist2 (x, y), d); ***** test d = [5.1962, 2.2361, 3.3166, 6.7082; ... 3.4641, 2.2361, 3.3166, 5.4772]; i = [3, 1, 1, 1; 2, 3, 3, 2]; [D, I] = pdist2 (x, y, "euclidean", "largest", 2); assert ({D, I}, {d, i}, 1e-4); ***** test d = [1.7321, 1.4142, 2.8284, 4.5826; ... 3.4641, 2.2361, 3.3166, 5.4772]; i = [1, 2, 2, 3;2, 1, 1, 2]; [D, I] = pdist2 (x, y, "euclidean", "smallest", 2); assert ({D, I}, {d, i}, 1e-4); ***** test yy = [1 2 3;5 6 7;9 5 1]; d = [0, 6.1644, 5.3852; 1.4142, 6.9282, 8.7750; ... 3.7417, 7.0711, 9.9499; 6.1644, 10.4881, 10.3441]; i = [2, 4, 4; 3, 2, 2; 1, 3, 3; 4, 1, 1]; [D, I] = pdist2 (y, yy, "euclidean", "smallest", 4); assert ({D, I}, {d, i}, 1e-4); ***** test yy = [1 2 3;5 6 7;9 5 1]; d = [0, 38, 29; 2, 48, 77; 14, 50, 99; 38, 110, 107]; i = [2, 4, 4; 3, 2, 2; 1, 3, 3; 4, 1, 1]; [D, I] = pdist2 (y, yy, "squaredeuclidean", "smallest", 4); assert ({D, I}, {d, i}, 1e-4); ***** test yy = [1 2 3;5 6 7;9 5 1]; d = [0, 3.3256, 2.7249; 0.7610, 3.3453, 4.4799; ... 1.8514, 3.3869, 5.0703; 2.5525, 5.0709, 5.1297]; i = [2, 2, 4; 3, 4, 2; 1, 3, 1; 4, 1, 3]; [D, I] = pdist2 (y, yy, "seuclidean", "smallest", 4); assert ({D, I}, {d, i}, 1e-4); ***** test d = [2.1213, 4.2426, 6.3640; 1.2247, 2.4495, 4.4159; ... 3.2404, 4.8990, 6.8191; 2.7386, 4.2426, 6.1237]; assert (pdist2 (y, x, "mahalanobis"), d, 1e-4); ***** test xx = [1, 3, 4; 3, 5, 4; 8, 7, 6]; d = [1.3053, 1.8257, 15.0499; 1.3053, 3.3665, 16.5680]; i = [2, 2, 2; 3, 4, 4]; [D, I] = pdist2 (y, xx, "mahalanobis", "smallest", 2); assert ({D, I}, {d, i}, 1e-4); ***** test d = [2.5240, 4.1633, 17.3638; 2.0905, 3.9158, 17.0147]; i = [1, 1, 3; 4, 3, 1]; [D, I] = pdist2 (y, xx, "mahalanobis", "largest", 2); assert ({D, I}, {d, i}, 1e-4); ***** test d = [3, 3, 5, 9; 6, 2, 4, 8; 9, 3, 5, 7]; assert (pdist2 (x, y, "cityblock"), d); ***** test d = [1, 2, 3, 6; 2, 1, 2, 5; 3, 2, 3, 4]; assert (pdist2 (x, y, "chebychev"), d); ***** test d = repmat ([NaN, 0.0742, 0.2254, 0.1472], [3, 1]); assert (pdist2 (x, y, "cosine"), d, 1e-4); ***** test yy = [1 2 3;5 6 7;9 5 1]; d = [0, 0, 0.5; 0, 0, 2; 1.5, 1.5, 2; NaN, NaN, NaN]; i = [2, 2, 4; 3, 3, 2; 4, 4, 3; 1, 1, 1]; [D, I] = pdist2 (y, yy, "correlation", "smallest", 4); assert ({D, I}, {d, i}, eps); [D, I] = pdist2 (y, yy, "spearman", "smallest", 4); assert ({D, I}, {d, i}, eps); ***** test d = [1, 2/3, 1, 1; 1, 2/3, 1, 1; 1, 2/3, 2/3, 2/3]; i = [1, 1, 1, 2; 2, 2, 3, 3; 3, 3, 2, 1]; [D, I] = pdist2 (x, y, "hamming", "largest", 4); assert ({D, I}, {d, i}, eps); [D, I] = pdist2 (x, y, "jaccard", "largest", 4); assert ({D, I}, {d, i}, eps); ***** test xx = [1, 2, 3, 4; 2, 3, 4, 5; 3, 4, 5, 6]; yy = [1, 2, 2, 3; 2, 3, 3, 4]; [D, I] = pdist2 (x, y, "euclidean", "Smallest", 4); eucldist = @(v,m) sqrt(sumsq(repmat(v,rows(m),1)-m,2)); [d, i] = pdist2 (x, y, eucldist, "Smallest", 4); assert ({D, I}, {d, i}); ***** warning ... pdist2 (xx, xx, "mahalanobis"); ***** error pdist2 (1) ***** error ... pdist2 (ones (4, 5), ones (4)) ***** error ... pdist2 (ones (4, 2, 3), ones (3, 2)) ***** error ... pdist2 (ones (3), ones (3), "euclidean", "Largest") ***** error ... pdist2 (ones (3), ones (3), "minkowski", 3, "Largest") ***** error ... pdist2 (ones (3), ones (3), "minkowski", 3, "large", 4) ***** error ... pdist2 (ones (3), ones (3), "minkowski", 3, "Largest", 4, "smallest", 5) ***** error ... [d, i] = pdist2(ones (3), ones (3), "minkowski", 3) ***** error ... pdist2 (ones (3), ones (3), "seuclidean", 3) ***** error ... pdist2 (ones (3), ones (3), "seuclidean", [1, -1, 3]) ***** error ... pdist2 (ones (3), eye (3), "mahalanobis", eye(2)) ***** error ... pdist2 (ones (3), eye (3), "mahalanobis", ones(3)) ***** error ... pdist2 (ones (3), eye (3), "minkowski", 0) ***** error ... pdist2 (ones (3), eye (3), "minkowski", -5) ***** error ... pdist2 (ones (3), eye (3), "minkowski", [1, 2]) ***** error ... pdist2 (ones (3), ones (3), @(v,m) sqrt(repmat(v,rows(m),1)-m,2)) ***** error ... pdist2 (ones (3), ones (3), @(v,m) sqrt(sum(sumsq(repmat(v,rows(m),1)-m,2)))) 33 tests, 33 passed, 0 known failure, 0 skipped [inst/ztest.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/ztest.m ***** error ztest (); ***** error ... ztest ([1, 2, 3, 4], 2, -0.5); ***** error ... ztest ([1, 2, 3, 4], 1, 2, "alpha", 0); ***** error ... ztest ([1, 2, 3, 4], 1, 2, "alpha", 1.2); ***** error ... ztest ([1, 2, 3, 4], 1, 2, "alpha", "val"); ***** error ... ztest ([1, 2, 3, 4], 1, 2, "tail", "val"); ***** error ... ztest ([1, 2, 3, 4], 1, 2, "alpha", 0.01, "tail", "val"); ***** error ... ztest ([1, 2, 3, 4], 1, 2, "dim", 3); ***** error ... ztest ([1, 2, 3, 4], 1, 2, "alpha", 0.01, "tail", "both", "dim", 3); ***** error ... ztest ([1, 2, 3, 4], 1, 2, "alpha", 0.01, "tail", "both", "badoption", 3); ***** test load carsmall [h, pval, ci] = ztest (MPG, mean (MPG, "omitnan"), std (MPG, "omitnan")); assert (h, 0); assert (pval, 1, 1e-14); assert (ci, [22.094; 25.343], 1e-3); ***** test load carsmall [h, pval, ci] = ztest (MPG, 26, 8); assert (h, 1); assert (pval, 0.00568359158544743, 1e-14); assert (ci, [22.101; 25.335], 1e-3); ***** test load carsmall [h, pval, ci] = ztest (MPG, 26, 4); assert (h, 1); assert (pval, 3.184168011941316e-08, 1e-14); assert (ci, [22.909; 24.527], 1e-3); 13 tests, 13 passed, 0 known failure, 0 skipped [inst/fitcknn.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/fitcknn.m ***** test x = [1, 2, 3; 4, 5, 6; 7, 8, 9; 3, 2, 1]; y = ["a"; "a"; "b"; "b"]; a = fitcknn (x, y); assert (class (a), "ClassificationKNN"); assert ({a.X, a.Y, a.NumNeighbors}, {x, y, 1}) assert ({a.NSMethod, a.Distance}, {"kdtree", "euclidean"}) assert ({a.BucketSize}, {50}) ***** test x = [1, 2, 3; 4, 5, 6; 7, 8, 9; 3, 2, 1]; y = ["a"; "a"; "b"; "b"]; a = fitcknn (x, y, "NSMethod", "exhaustive"); assert (class (a), "ClassificationKNN"); assert ({a.X, a.Y, a.NumNeighbors}, {x, y, 1}) assert ({a.NSMethod, a.Distance}, {"exhaustive", "euclidean"}) assert ({a.BucketSize}, {50}) ***** test x = [1, 2, 3; 4, 5, 6; 7, 8, 9; 3, 2, 1]; y = ["a"; "a"; "b"; "b"]; k = 10; a = fitcknn (x, y, "NumNeighbors" ,k); assert (class (a), "ClassificationKNN"); assert ({a.X, a.Y, a.NumNeighbors}, {x, y, 10}) assert ({a.NSMethod, a.Distance}, {"kdtree", "euclidean"}) assert ({a.BucketSize}, {50}) ***** test x = ones (4, 11); y = ["a"; "a"; "b"; "b"]; k = 10; a = fitcknn (x, y, "NumNeighbors" ,k); assert (class (a), "ClassificationKNN"); assert ({a.X, a.Y, a.NumNeighbors}, {x, y, 10}) assert ({a.NSMethod, a.Distance}, {"exhaustive", "euclidean"}) assert ({a.BucketSize}, {50}) ***** test x = [1, 2, 3; 4, 5, 6; 7, 8, 9; 3, 2, 1]; y = ["a"; "a"; "b"; "b"]; k = 10; a = fitcknn (x, y, "NumNeighbors" ,k, "NSMethod", "exhaustive"); assert (class (a), "ClassificationKNN"); assert ({a.X, a.Y, a.NumNeighbors}, {x, y, 10}) assert ({a.NSMethod, a.Distance}, {"exhaustive", "euclidean"}) assert ({a.BucketSize}, {50}) ***** test x = [1, 2, 3; 4, 5, 6; 7, 8, 9; 3, 2, 1]; y = ["a"; "a"; "b"; "b"]; k = 10; a = fitcknn (x, y, "NumNeighbors" ,k, "Distance", "hamming"); assert (class (a), "ClassificationKNN"); assert ({a.X, a.Y, a.NumNeighbors}, {x, y, 10}) assert ({a.NSMethod, a.Distance}, {"exhaustive", "hamming"}) assert ({a.BucketSize}, {50}) ***** test x = [1, 2, 3; 4, 5, 6; 7, 8, 9; 3, 2, 1]; y = ["a"; "a"; "b"; "b"]; weights = ones (4,1); a = fitcknn (x, y, "Standardize", 1); assert (class (a), "ClassificationKNN"); assert ({a.X, a.Y, a.NumNeighbors}, {x, y, 1}) assert ({a.NSMethod, a.Distance}, {"kdtree", "euclidean"}) assert ({a.Standardize}, {true}) assert ({a.Sigma}, {std(x, [], 1)}) assert ({a.Mu}, {[3.75, 4.25, 4.75]}) ***** test x = [1, 2, 3; 4, 5, 6; 7, 8, 9; 3, 2, 1]; y = ["a"; "a"; "b"; "b"]; weights = ones (4,1); a = fitcknn (x, y, "Standardize", false); assert (class (a), "ClassificationKNN"); assert ({a.X, a.Y, a.NumNeighbors}, {x, y, 1}) assert ({a.NSMethod, a.Distance}, {"kdtree", "euclidean"}) assert ({a.Standardize}, {false}) assert ({a.Sigma}, {[]}) assert ({a.Mu}, {[]}) ***** test x = [1, 2, 3; 4, 5, 6; 7, 8, 9; 3, 2, 1]; y = ["a"; "a"; "b"; "b"]; s = ones (1, 3); a = fitcknn (x, y, "Scale" , s, "Distance", "seuclidean"); assert (class (a), "ClassificationKNN"); assert ({a.DistParameter}, {s}) assert ({a.NSMethod, a.Distance}, {"exhaustive", "seuclidean"}) assert ({a.BucketSize}, {50}) ***** test x = [1, 2, 3; 4, 5, 6; 7, 8, 9; 3, 2, 1]; y = ["a"; "a"; "b"; "b"]; a = fitcknn (x, y, "Exponent" , 5, "Distance", "minkowski"); assert (class (a), "ClassificationKNN"); assert (a.DistParameter, 5) assert ({a.NSMethod, a.Distance}, {"kdtree", "minkowski"}) ***** test x = [1, 2, 3; 4, 5, 6; 7, 8, 9; 3, 2, 1]; y = ["a"; "a"; "b"; "b"]; a = fitcknn (x, y, "Exponent" , 5, "Distance", "minkowski", ... "NSMethod", "exhaustive"); assert (class (a), "ClassificationKNN"); assert (a.DistParameter, 5) assert ({a.NSMethod, a.Distance}, {"exhaustive", "minkowski"}) ***** test x = [1, 2, 3; 4, 5, 6; 7, 8, 9; 3, 2, 1]; y = ["a"; "a"; "b"; "b"]; a = fitcknn (x, y, "BucketSize" , 20, "distance", "mahalanobis"); assert (class (a), "ClassificationKNN"); assert ({a.NSMethod, a.Distance}, {"exhaustive", "mahalanobis"}) assert ({a.BucketSize}, {20}) ***** test x = [1, 2, 3; 4, 5, 6; 7, 8, 9; 3, 2, 1]; y = ["a"; "a"; "b"; "b"]; a = fitcknn (x, y, "IncludeTies", true); assert (class (a), "ClassificationKNN"); assert (a.IncludeTies, true); assert ({a.NSMethod, a.Distance}, {"kdtree", "euclidean"}) ***** test x = [1, 2, 3; 4, 5, 6; 7, 8, 9; 3, 2, 1]; y = ["a"; "a"; "b"; "b"]; a = fitcknn (x, y); assert (class (a), "ClassificationKNN"); assert (a.IncludeTies, false); assert ({a.NSMethod, a.Distance}, {"kdtree", "euclidean"}) ***** test x = [1, 2, 3; 4, 5, 6; 7, 8, 9; 3, 2, 1]; y = ["a"; "a"; "b"; "b"]; a = fitcknn (x, y); assert (class (a), "ClassificationKNN") assert (a.Prior, [0.5; 0.5]) assert ({a.NSMethod, a.Distance}, {"kdtree", "euclidean"}) assert ({a.BucketSize}, {50}) ***** test x = [1, 2, 3; 4, 5, 6; 7, 8, 9; 3, 2, 1]; y = ["a"; "a"; "b"; "b"]; prior = [0.5; 0.5]; a = fitcknn (x, y, "Prior", "empirical"); assert (class (a), "ClassificationKNN") assert (a.Prior, prior) assert ({a.NSMethod, a.Distance}, {"kdtree", "euclidean"}) assert ({a.BucketSize}, {50}) ***** test x = [1, 2, 3; 4, 5, 6; 7, 8, 9; 3, 2, 1]; y = ["a"; "a"; "a"; "b"]; prior = [0.75; 0.25]; a = fitcknn (x, y, "Prior", "empirical"); assert (class (a), "ClassificationKNN") assert (a.Prior, prior) assert ({a.NSMethod, a.Distance}, {"kdtree", "euclidean"}) assert ({a.BucketSize}, {50}) ***** test x = [1, 2, 3; 4, 5, 6; 7, 8, 9; 3, 2, 1]; y = ["a"; "a"; "a"; "b"]; prior = [0.5; 0.5]; a = fitcknn (x, y, "Prior", "uniform"); assert (class (a), "ClassificationKNN") assert (a.Prior, prior) assert ({a.NSMethod, a.Distance}, {"kdtree", "euclidean"}) assert ({a.BucketSize}, {50}) ***** test x = [1, 2, 3; 4, 5, 6; 7, 8, 9; 3, 2, 1]; y = ["a"; "a"; "b"; "b"]; cost = eye (2); a = fitcknn (x, y, "Cost", cost); assert (class (a), "ClassificationKNN") assert (a.Cost, [1, 0; 0, 1]) assert ({a.NSMethod, a.Distance}, {"kdtree", "euclidean"}) assert ({a.BucketSize}, {50}) ***** test x = [1, 2, 3; 4, 5, 6; 7, 8, 9; 3, 2, 1]; y = ["a"; "a"; "b"; "b"]; cost = eye (2); a = fitcknn (x, y, "Cost", cost, "Distance", "hamming" ); assert (class (a), "ClassificationKNN") assert (a.Cost, [1, 0; 0, 1]) assert ({a.NSMethod, a.Distance}, {"exhaustive", "hamming"}) assert ({a.BucketSize}, {50}) ***** error fitcknn () ***** error fitcknn (ones (4,1)) ***** error fitcknn (ones (4,2), ones (4, 1), "K") ***** error fitcknn (ones (4,2), ones (3, 1)) ***** error fitcknn (ones (4,2), ones (3, 1), "K", 2) 25 tests, 25 passed, 0 known failure, 0 skipped [inst/jackknife.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/jackknife.m ***** demo for k = 1:1000 rand ("seed", k); # for reproducibility x = rand (10, 1); s(k) = std (x); jackstat = jackknife (@std, x); j(k) = 10 * std (x) - 9 * mean (jackstat); endfor figure(); hist ([s', j'], 0:sqrt(1/12)/10:2*sqrt(1/12)) ***** demo for k = 1:1000 randn ("seed", k); # for reproducibility x = randn (1, 50); rand ("seed", k); # for reproducibility y = rand (1, 50); jackstat = jackknife (@(x) std(x{1})/std(x{2}), y, x); j(k) = 50 * std (y) / std (x) - 49 * mean (jackstat); v(k) = sumsq ((50 * std (y) / std (x) - 49 * jackstat) - j(k)) / (50 * 49); endfor t = (j - sqrt (1 / 12)) ./ sqrt (v); figure(); plot (sort (tcdf (t, 49)), ... "-;Almost linear mapping indicates good fit with t-distribution.;") ***** test ##Example from Quenouille, Table 1 d=[0.18 4.00 1.04 0.85 2.14 1.01 3.01 2.33 1.57 2.19]; jackstat = jackknife ( @(x) 1/mean(x), d ); assert ( 10 / mean(d) - 9 * mean(jackstat), 0.5240, 1e-5 ); 1 test, 1 passed, 0 known failure, 0 skipped [inst/clusterdata.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/clusterdata.m ***** demo randn ("seed", 1) # for reproducibility r1 = randn (10, 2) * 0.25 + 1; randn ("seed", 5) # for reproducibility r2 = randn (20, 2) * 0.5 - 1; X = [r1; r2]; wnl = warning ("off", "Octave:linkage_savemem", "local"); T = clusterdata (X, "linkage", "ward", "MaxClust", 2); scatter (X(:,1), X(:,2), 36, T, "filled"); ***** error ... clusterdata () ***** error ... clusterdata (1) ***** error clusterdata ([1 1], "Bogus", 1) ***** error clusterdata ([1 1], "Depth", 1) 4 tests, 4 passed, 0 known failure, 0 skipped [inst/evalclusters.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/evalclusters.m ***** error evalclusters () ***** error evalclusters ([1 1;0 1]) ***** error evalclusters ([1 1;0 1], "kmeans") ***** error <'x' must be a numeric*> evalclusters ("abc", "kmeans", "gap") ***** error evalclusters ([1 1;0 1], "xxx", "gap") ***** error evalclusters ([1 1;0 1], [1 2], "gap") ***** error evalclusters ([1 1;0 1], 1.2, "gap") ***** error evalclusters ([1 1;0 1], [1; 2], 123) ***** error evalclusters ([1 1;0 1], [1; 2], "xxx") ***** error <'KList' can be empty*> evalclusters ([1 1;0 1], "kmeans", "gap") ***** error evalclusters ([1 1;0 1], [1; 2], "gap", 1) ***** error evalclusters ([1 1;0 1], [1; 2], "gap", 1, 1) ***** error evalclusters ([1 1;0 1], [1; 2], "gap", "xxx", 1) ***** error <'KList'*> evalclusters ([1 1;0 1], [1; 2], "gap", "KList", [-1 0]) ***** error <'KList'*> evalclusters ([1 1;0 1], [1; 2], "gap", "KList", [1 .5]) ***** error <'KList'*> evalclusters ([1 1;0 1], [1; 2], "gap", "KList", [1 1; 1 1]) ***** error evalclusters ([1 1;0 1], [1; 2], "gap", ... "distance", "a") ***** error evalclusters ([1 1;0 1], [1; 2], "daviesbouldin", ... "distance", "a") ***** error evalclusters ([1 1;0 1], [1; 2], "gap", ... "clusterpriors", "equal") ***** error evalclusters ([1 1;0 1], [1; 2], ... "silhouette", "clusterpriors", "xxx") ***** error <'clust' must be a clustering*> evalclusters ([1 1;0 1], [1; 2], "gap") ***** test load fisheriris; eva = evalclusters(meas, "kmeans", "calinskiharabasz", "KList", [1:6]); assert(isa(eva, "CalinskiHarabaszEvaluation")); assert(eva.NumObservations, 150); assert(eva.OptimalK, 3); assert(eva.InspectedK, [1 2 3 4 5 6]); 22 tests, 22 passed, 0 known failure, 0 skipped [inst/procrustes.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/procrustes.m ***** demo ## Create some random points in two dimensions n = 10; randn ("seed", 1); X = normrnd (0, 1, [n, 2]); ## Those same points, rotated, scaled, translated, plus some noise S = [0.5, -sqrt(3)/2; sqrt(3)/2, 0.5]; # rotate 60 degrees Y = normrnd (0.5*X*S + 2, 0.05, n, 2); ## Conform Y to X, plot original X and Y, and transformed Y [d, Z] = procrustes (X, Y); plot (X(:,1), X(:,2), "rx", Y(:,1), Y(:,2), "b.", Z(:,1), Z(:,2), "bx"); ***** demo ## Find Procrustes distance and plot superimposed shape X = [40 88; 51 88; 35 78; 36 75; 39 72; 44 71; 48 71; 52 74; 55 77]; Y = [36 43; 48 42; 31 26; 33 28; 37 30; 40 31; 45 30; 48 28; 51 24]; plot (X(:,1),X(:,2),"x"); hold on plot (Y(:,1),Y(:,2),"o"); xlim ([0 100]); ylim ([0 100]); legend ("Target shape (X)", "Source shape (Y)"); [d, Z] = procrustes (X, Y) plot (Z(:,1), Z(:,2), "s"); legend ("Target shape (X)", "Source shape (Y)", "Transformed shape (Z)"); hold off ***** demo ## Apply Procrustes transformation to larger set of points ## Create matrices with landmark points for two triangles X = [5, 0; 5, 5; 8, 5]; # target Y = [0, 0; 1, 0; 1, 1]; # source ## Create a matrix with more points on the source triangle Y_mp = [linspace(Y(1,1),Y(2,1),10)', linspace(Y(1,2),Y(2,2),10)'; ... linspace(Y(2,1),Y(3,1),10)', linspace(Y(2,2),Y(3,2),10)'; ... linspace(Y(3,1),Y(1,1),10)', linspace(Y(3,2),Y(1,2),10)']; ## Plot both shapes, including the larger set of points for the source shape plot ([X(:,1); X(1,1)], [X(:,2); X(1,2)], "bx-"); hold on plot ([Y(:,1); Y(1,1)], [Y(:,2); Y(1,2)], "ro-", "MarkerFaceColor", "r"); plot (Y_mp(:,1), Y_mp(:,2), "ro"); xlim ([-1 10]); ylim ([-1 6]); legend ("Target shape (X)", "Source shape (Y)", ... "More points on Y", "Location", "northwest"); hold off ## Obtain the Procrustes transformation [d, Z, transform] = procrustes (X, Y) ## Use the Procrustes transformation to superimpose the more points (Y_mp) ## on the source shape onto the target shape, and then visualize the results. Z_mp = transform.b * Y_mp * transform.T + transform.c(1,:); figure plot ([X(:,1); X(1,1)], [X(:,2); X(1,2)], "bx-"); hold on plot ([Y(:,1); Y(1,1)], [Y(:,2); Y(1,2)], "ro-", "MarkerFaceColor", "r"); plot (Y_mp(:,1), Y_mp(:,2), "ro"); xlim ([-1 10]); ylim ([-1 6]); plot ([Z(:,1); Z(1,1)],[Z(:,2); Z(1,2)],"ks-","MarkerFaceColor","k"); plot (Z_mp(:,1),Z_mp(:,2),"ks"); legend ("Target shape (X)", "Source shape (Y)", ... "More points on Y", "Transformed source shape (Z)", ... "Transformed additional points", "Location", "northwest"); hold off ***** demo ## Compare shapes without reflection T = [33, 93; 33, 87; 33, 80; 31, 72; 32, 65; 32, 58; 30, 72; ... 28, 72; 25, 69; 22, 64; 23, 59; 26, 57; 30, 57]; S = [48, 83; 48, 77; 48, 70; 48, 65; 49, 59; 49, 56; 50, 66; ... 52, 66; 56, 65; 58, 61; 57, 57; 54, 56; 51, 55]; plot (T(:,1), T(:,2), "x-"); hold on plot (S(:,1), S(:,2), "o-"); legend ("Target shape (d)", "Source shape (b)"); hold off d_false = procrustes (T, S, "reflection", false); printf ("Procrustes distance without reflection: %f\n", d_false); d_true = procrustes (T, S, "reflection", true); printf ("Procrustes distance with reflection: %f\n", d_true); d_best = procrustes (T, S, "reflection", "best"); printf ("Procrustes distance with best fit: %f\n", d_true); ***** error procrustes (); ***** error procrustes (1, 2, 3, 4, 5, 6); ***** error ... procrustes (ones (2, 2, 2), ones (2, 2, 2)); ***** error ... procrustes ([1, 2; -3, 4; 2, 3], [1, 2; -3, 4; 2, 3+i]); ***** error ... procrustes ([1, 2; -3, 4; 2, 3], [1, 2; -3, 4; 2, NaN]); ***** error ... procrustes ([1, 2; -3, 4; 2, 3], [1, 2; -3, 4; 2, Inf]); ***** error ... procrustes (ones (10 ,3), ones (11, 3)); ***** error ... procrustes (ones (10 ,3), ones (10, 4)); ***** error ... procrustes (ones (10 ,3), ones (10, 3), "reflection"); ***** error ... procrustes (ones (10 ,3), ones (10, 3), true); ***** error ... procrustes (ones (10 ,3), ones (10, 3), "scaling", 0); ***** error ... procrustes (ones (10 ,3), ones (10, 3), "scaling", [true true]); ***** error ... procrustes (ones (10 ,3), ones (10, 3), "reflection", 1); ***** error ... procrustes (ones (10 ,3), ones (10, 3), "reflection", "some"); ***** error ... procrustes (ones (10 ,3), ones (10, 3), "param1", "some"); 15 tests, 15 passed, 0 known failure, 0 skipped [inst/anovan.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/anovan.m ***** demo # Two-sample unpaired test on independent samples (equivalent to Student's # t-test). Note that the absolute value of t-statistic can be obtained by # taking the square root of the reported F statistic. In this example, # t = sqrt (1.44) = 1.20. score = [54 23 45 54 45 43 34 65 77 46 65]'; gender = {"male" "male" "male" "male" "male" "female" "female" "female" ... "female" "female" "female"}'; [P, ATAB, STATS] = anovan (score, gender, "display", "on", "varnames", "gender"); ***** demo # Two-sample paired test on dependent or matched samples equivalent to a # paired t-test. As for the first example, the t-statistic can be obtained by # taking the square root of the reported F statistic. Note that the interaction # between treatment x subject was dropped from the full model by assigning # subject as a random factor ('). score = [4.5 5.6; 3.7 6.4; 5.3 6.4; 5.4 6.0; 3.9 5.7]'; treatment = {"before" "after"; "before" "after"; "before" "after"; "before" "after"; "before" "after"}'; subject = {"GS" "GS"; "JM" "JM"; "HM" "HM"; "JW" "JW"; "PS" "PS"}'; [P, ATAB, STATS] = anovan (score(:), {treatment(:), subject(:)}, ... "model", "full", "random", 2, "sstype", 2, ... "varnames", {"treatment", "subject"}, ... "display", "on"); ***** demo # One-way ANOVA on the data from a study on the strength of structural beams, # in Hogg and Ledolter (1987) Engineering Statistics. New York: MacMillan strength = [82 86 79 83 84 85 86 87 74 82 ... 78 75 76 77 79 79 77 78 82 79]'; alloy = {"st","st","st","st","st","st","st","st", ... "al1","al1","al1","al1","al1","al1", ... "al2","al2","al2","al2","al2","al2"}'; [P, ATAB, STATS] = anovan (strength, alloy, "display", "on", ... "varnames", "alloy"); ***** demo # One-way repeated measures ANOVA on the data from a study on the number of # words recalled by 10 subjects for three time condtions, in Loftus & Masson # (1994) Psychon Bull Rev. 1(4):476-490, Table 2. Note that the interaction # between seconds x subject was dropped from the full model by assigning # subject as a random factor ('). words = [10 13 13; 6 8 8; 11 14 14; 22 23 25; 16 18 20; ... 15 17 17; 1 1 4; 12 15 17; 9 12 12; 8 9 12]; seconds = [1 2 5; 1 2 5; 1 2 5; 1 2 5; 1 2 5; ... 1 2 5; 1 2 5; 1 2 5; 1 2 5; 1 2 5;]; subject = [ 1 1 1; 2 2 2; 3 3 3; 4 4 4; 5 5 5; ... 6 6 6; 7 7 7; 8 8 8; 9 9 9; 10 10 10]; [P, ATAB, STATS] = anovan (words(:), {seconds(:), subject(:)}, ... "model", "full", "random", 2, "sstype", 2, ... "display", "on", "varnames", {"seconds", "subject"}); ***** demo # Balanced two-way ANOVA with interaction on the data from a study of popcorn # brands and popper types, in Hogg and Ledolter (1987) Engineering Statistics. # New York: MacMillan popcorn = [5.5, 4.5, 3.5; 5.5, 4.5, 4.0; 6.0, 4.0, 3.0; ... 6.5, 5.0, 4.0; 7.0, 5.5, 5.0; 7.0, 5.0, 4.5]; brands = {"Gourmet", "National", "Generic"; ... "Gourmet", "National", "Generic"; ... "Gourmet", "National", "Generic"; ... "Gourmet", "National", "Generic"; ... "Gourmet", "National", "Generic"; ... "Gourmet", "National", "Generic"}; popper = {"oil", "oil", "oil"; "oil", "oil", "oil"; "oil", "oil", "oil"; ... "air", "air", "air"; "air", "air", "air"; "air", "air", "air"}; [P, ATAB, STATS] = anovan (popcorn(:), {brands(:), popper(:)}, ... "display", "on", "model", "full", ... "varnames", {"brands", "popper"}); ***** demo # Unbalanced two-way ANOVA (2x2) on the data from a study on the effects of # gender and having a college degree on salaries of company employees, # in Maxwell, Delaney and Kelly (2018): Chapter 7, Table 15 salary = [24 26 25 24 27 24 27 23 15 17 20 16, ... 25 29 27 19 18 21 20 21 22 19]'; gender = {"f" "f" "f" "f" "f" "f" "f" "f" "f" "f" "f" "f"... "m" "m" "m" "m" "m" "m" "m" "m" "m" "m"}'; degree = [1 1 1 1 1 1 1 1 0 0 0 0 1 1 1 0 0 0 0 0 0 0]'; [P, ATAB, STATS] = anovan (salary, {gender, degree}, "model", "full", ... "sstype", 3, "display", "on", "varnames", ... {"gender", "degree"}); ***** demo # Unbalanced two-way ANOVA (3x2) on the data from a study of the effect of # adding sugar and/or milk on the tendency of coffee to make people babble, # in from Navarro (2019): 16.10 sugar = {"real" "fake" "fake" "real" "real" "real" "none" "none" "none" ... "fake" "fake" "fake" "real" "real" "real" "none" "none" "fake"}'; milk = {"yes" "no" "no" "yes" "yes" "no" "yes" "yes" "yes" ... "no" "no" "yes" "no" "no" "no" "no" "no" "yes"}'; babble = [4.6 4.4 3.9 5.6 5.1 5.5 3.9 3.5 3.7... 5.6 4.7 5.9 6.0 5.4 6.6 5.8 5.3 5.7]'; [P, ATAB, STATS] = anovan (babble, {sugar, milk}, "model", "full", ... "sstype", 3, "display", "on", ... "varnames", {"sugar", "milk"}); ***** demo # Unbalanced three-way ANOVA (3x2x2) on the data from a study of the effects # of three different drugs, biofeedback and diet on patient blood pressure, # adapted* from Maxwell, Delaney and Kelly (2018): Chapter 8, Table 12 # * Missing values introduced to make the sample sizes unequal to test the # calculation of different types of sums-of-squares drug = {"X" "X" "X" "X" "X" "X" "X" "X" "X" "X" "X" "X" ... "X" "X" "X" "X" "X" "X" "X" "X" "X" "X" "X" "X"; "Y" "Y" "Y" "Y" "Y" "Y" "Y" "Y" "Y" "Y" "Y" "Y" ... "Y" "Y" "Y" "Y" "Y" "Y" "Y" "Y" "Y" "Y" "Y" "Y"; "Z" "Z" "Z" "Z" "Z" "Z" "Z" "Z" "Z" "Z" "Z" "Z" ... "Z" "Z" "Z" "Z" "Z" "Z" "Z" "Z" "Z" "Z" "Z" "Z"}; feedback = [1 1 1 1 1 1 1 1 1 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0; 1 1 1 1 1 1 1 1 1 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0; 1 1 1 1 1 1 1 1 1 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0]; diet = [0 0 0 0 0 0 1 1 1 1 1 1 0 0 0 0 0 0 1 1 1 1 1 1; 0 0 0 0 0 0 1 1 1 1 1 1 0 0 0 0 0 0 1 1 1 1 1 1; 0 0 0 0 0 0 1 1 1 1 1 1 0 0 0 0 0 0 1 1 1 1 1 1]; BP = [170 175 165 180 160 158 161 173 157 152 181 190 ... 173 194 197 190 176 198 164 190 169 164 176 175; 186 194 201 215 219 209 164 166 159 182 187 174 ... 189 194 217 206 199 195 171 173 196 199 180 NaN; 180 187 199 170 204 194 162 184 183 156 180 173 ... 202 228 190 206 224 204 205 199 170 160 NaN NaN]; [P, ATAB, STATS] = anovan (BP(:), {drug(:), feedback(:), diet(:)}, ... "model", "full", "sstype", 3, ... "display", "on", ... "varnames", {"drug", "feedback", "diet"}); ***** demo # Balanced three-way ANOVA (2x2x2) with one of the factors being a blocking # factor. The data is from a randomized block design study on the effects # of antioxidant treatment on glutathione-S-transferase (GST) levels in # different mouse strains, from Festing (2014), ILAR Journal, 55(3):427-476. # Note that all interactions involving block were dropped from the full model # by assigning block as a random factor ('). measurement = [444 614 423 625 408 856 447 719 ... 764 831 586 782 609 1002 606 766]'; strain= {"NIH","NIH","BALB/C","BALB/C","A/J","A/J","129/Ola","129/Ola", ... "NIH","NIH","BALB/C","BALB/C","A/J","A/J","129/Ola","129/Ola"}'; treatment={"C" "T" "C" "T" "C" "T" "C" "T" "C" "T" "C" "T" "C" "T" "C" "T"}'; block = [1 1 1 1 1 1 1 1 2 2 2 2 2 2 2 2]'; [P, ATAB, STATS] = anovan (measurement/10, {strain, treatment, block}, ... "sstype", 2, "model", "full", "random", 3, ... "display", "on", ... "varnames", {"strain", "treatment", "block"}); ***** demo # One-way ANCOVA on data from a study of the additive effects of species # and temperature on chirpy pulses of crickets, from Stitch, The Worst Stats # Text eveR pulse = [67.9 65.1 77.3 78.7 79.4 80.4 85.8 86.6 87.5 89.1 ... 98.6 100.8 99.3 101.7 44.3 47.2 47.6 49.6 50.3 51.8 ... 60 58.5 58.9 60.7 69.8 70.9 76.2 76.1 77 77.7 84.7]'; temp = [20.8 20.8 24 24 24 24 26.2 26.2 26.2 26.2 28.4 ... 29 30.4 30.4 17.2 18.3 18.3 18.3 18.9 18.9 20.4 ... 21 21 22.1 23.5 24.2 25.9 26.5 26.5 26.5 28.6]'; species = {"ex" "ex" "ex" "ex" "ex" "ex" "ex" "ex" "ex" "ex" "ex" ... "ex" "ex" "ex" "niv" "niv" "niv" "niv" "niv" "niv" "niv" ... "niv" "niv" "niv" "niv" "niv" "niv" "niv" "niv" "niv" "niv"}; [P, ATAB, STATS] = anovan (pulse, {species, temp}, "model", "linear", ... "continuous", 2, "sstype", "h", "display", "on", ... "varnames", {"species", "temp"}); ***** demo # Factorial ANCOVA on data from a study of the effects of treatment and # exercise on stress reduction score after adjusting for age. Data from R # datarium package). score = [95.6 82.2 97.2 96.4 81.4 83.6 89.4 83.8 83.3 85.7 ... 97.2 78.2 78.9 91.8 86.9 84.1 88.6 89.8 87.3 85.4 ... 81.8 65.8 68.1 70.0 69.9 75.1 72.3 70.9 71.5 72.5 ... 84.9 96.1 94.6 82.5 90.7 87.0 86.8 93.3 87.6 92.4 ... 100. 80.5 92.9 84.0 88.4 91.1 85.7 91.3 92.3 87.9 ... 91.7 88.6 75.8 75.7 75.3 82.4 80.1 86.0 81.8 82.5]'; treatment = {"yes" "yes" "yes" "yes" "yes" "yes" "yes" "yes" "yes" "yes" ... "yes" "yes" "yes" "yes" "yes" "yes" "yes" "yes" "yes" "yes" ... "yes" "yes" "yes" "yes" "yes" "yes" "yes" "yes" "yes" "yes" ... "no" "no" "no" "no" "no" "no" "no" "no" "no" "no" ... "no" "no" "no" "no" "no" "no" "no" "no" "no" "no" ... "no" "no" "no" "no" "no" "no" "no" "no" "no" "no"}'; exercise = {"lo" "lo" "lo" "lo" "lo" "lo" "lo" "lo" "lo" "lo" ... "mid" "mid" "mid" "mid" "mid" "mid" "mid" "mid" "mid" "mid" ... "hi" "hi" "hi" "hi" "hi" "hi" "hi" "hi" "hi" "hi" ... "lo" "lo" "lo" "lo" "lo" "lo" "lo" "lo" "lo" "lo" ... "mid" "mid" "mid" "mid" "mid" "mid" "mid" "mid" "mid" "mid" ... "hi" "hi" "hi" "hi" "hi" "hi" "hi" "hi" "hi" "hi"}'; age = [59 65 70 66 61 65 57 61 58 55 62 61 60 59 55 57 60 63 62 57 ... 58 56 57 59 59 60 55 53 55 58 68 62 61 54 59 63 60 67 60 67 ... 75 54 57 62 65 60 58 61 65 57 56 58 58 58 52 53 60 62 61 61]'; [P, ATAB, STATS] = anovan (score, {treatment, exercise, age}, ... "model", [1 0 0; 0 1 0; 0 0 1; 1 1 0], ... "continuous", 3, "sstype", "h", "display", "on", ... "varnames", {"treatment", "exercise", "age"}); ***** demo # Unbalanced one-way ANOVA with custom, orthogonal contrasts. The statistics # relating to the contrasts are shown in the table of model parameters, and # can be retrieved from the STATS.coeffs output. dv = [ 8.706 10.362 11.552 6.941 10.983 10.092 6.421 14.943 15.931 ... 22.968 18.590 16.567 15.944 21.637 14.492 17.965 18.851 22.891 ... 22.028 16.884 17.252 18.325 25.435 19.141 21.238 22.196 18.038 ... 22.628 31.163 26.053 24.419 32.145 28.966 30.207 29.142 33.212 ... 25.694 ]'; g = [1 1 1 1 1 1 1 1 2 2 2 2 2 3 3 3 3 3 3 3 3 ... 4 4 4 4 4 4 4 5 5 5 5 5 5 5 5 5]'; C = [ 0.4001601 0.3333333 0.5 0.0 0.4001601 0.3333333 -0.5 0.0 0.4001601 -0.6666667 0.0 0.0 -0.6002401 0.0000000 0.0 0.5 -0.6002401 0.0000000 0.0 -0.5]; [P,ATAB, STATS] = anovan (dv, g, "contrasts", C, "varnames", "score", ... "alpha", 0.05, "display", "on"); ***** demo # One-way ANOVA with the linear model fit by weighted least squares to # account for heteroskedasticity. In this example, the variance appears # proportional to the outcome, so weights have been estimated by initially # fitting the model without weights and regressing the absolute residuals on # the fitted values. Although this data could have been analysed by Welch's # ANOVA test, the approach here can generalize to ANOVA models with more than # one factor. g = [1, 1, 1, 1, 1, 1, 1, 1, ... 2, 2, 2, 2, 2, 2, 2, 2, ... 3, 3, 3, 3, 3, 3, 3, 3]'; y = [13, 16, 16, 7, 11, 5, 1, 9, ... 10, 25, 66, 43, 47, 56, 6, 39, ... 11, 39, 26, 35, 25, 14, 24, 17]'; [P,ATAB,STATS] = anovan(y, g, "display", "off"); fitted = STATS.X * STATS.coeffs(:,1); # fitted values b = polyfit (fitted, abs (STATS.resid), 1); v = polyval (b, fitted); # Variance as a function of the fitted values figure("Name", "Regression of the absolute residuals on the fitted values"); plot (fitted, abs (STATS.resid),'ob');hold on; plot(fitted,v,'-r'); hold off; xlabel("Fitted values"); ylabel("Absolute residuals"); [P,ATAB,STATS] = anovan (y, g, "weights", v.^-1); ***** test score = [54 23 45 54 45 43 34 65 77 46 65]'; gender = {'male' 'male' 'male' 'male' 'male' 'female' 'female' 'female' ... 'female' 'female' 'female'}'; [P, T, STATS] = anovan (score,gender,'display','off'); assert (P(1), 0.2612876773271042, 1e-09); # compared to p calculated by MATLAB anovan assert (sqrt(T{2,6}), abs(1.198608733288208), 1e-09); # compared to abs(t) calculated from sqrt(F) by MATLAB anovan assert (P(1), 0.2612876773271047, 1e-09); # compared to p calculated by MATLAB ttest2 assert (sqrt(T{2,6}), abs(-1.198608733288208), 1e-09); # compared to abs(t) calculated by MATLAB ttest2 ***** test score = [4.5 5.6; 3.7 6.4; 5.3 6.4; 5.4 6.0; 3.9 5.7]'; treatment = {'before' 'after'; 'before' 'after'; 'before' 'after'; 'before' 'after'; 'before' 'after'}'; subject = {'GS' 'GS'; 'JM' 'JM'; 'HM' 'HM'; 'JW' 'JW'; 'PS' 'PS'}'; [P, ATAB, STATS] = anovan (score(:),{treatment(:),subject(:)},'display','off','sstype',2); assert (P(1), 0.016004356735364, 1e-09); # compared to p calculated by MATLAB anovan assert (sqrt(ATAB{2,6}), abs(4.00941576558195), 1e-09); # compared to abs(t) calculated from sqrt(F) by MATLAB anovan assert (P(1), 0.016004356735364, 1e-09); # compared to p calculated by MATLAB ttest2 assert (sqrt(ATAB{2,6}), abs(-4.00941576558195), 1e-09); # compared to abs(t) calculated by MATLAB ttest2 ***** test strength = [82 86 79 83 84 85 86 87 74 82 ... 78 75 76 77 79 79 77 78 82 79]'; alloy = {'st','st','st','st','st','st','st','st', ... 'al1','al1','al1','al1','al1','al1', ... 'al2','al2','al2','al2','al2','al2'}'; [P, ATAB, STATS] = anovan (strength,{alloy},'display','off'); assert (P(1), 0.000152643638830491, 1e-09); assert (ATAB{2,6}, 15.4, 1e-09); ***** test words = [10 13 13; 6 8 8; 11 14 14; 22 23 25; 16 18 20; ... 15 17 17; 1 1 4; 12 15 17; 9 12 12; 8 9 12]; subject = [ 1 1 1; 2 2 2; 3 3 3; 4 4 4; 5 5 5; ... 6 6 6; 7 7 7; 8 8 8; 9 9 9; 10 10 10]; seconds = [1 2 5; 1 2 5; 1 2 5; 1 2 5; 1 2 5; ... 1 2 5; 1 2 5; 1 2 5; 1 2 5; 1 2 5;]; [P, ATAB, STATS] = anovan (words(:),{seconds(:),subject(:)},'model','full','random',2,'sstype',2,'display','off'); assert (P(1), 1.51865926758752e-07, 1e-09); assert (ATAB{2,2}, 52.2666666666667, 1e-09); assert (ATAB{3,2}, 942.533333333333, 1e-09); assert (ATAB{4,2}, 11.0666666666667, 1e-09); ***** test popcorn = [5.5, 4.5, 3.5; 5.5, 4.5, 4.0; 6.0, 4.0, 3.0; ... 6.5, 5.0, 4.0; 7.0, 5.5, 5.0; 7.0, 5.0, 4.5]; brands = {'Gourmet', 'National', 'Generic'; ... 'Gourmet', 'National', 'Generic'; ... 'Gourmet', 'National', 'Generic'; ... 'Gourmet', 'National', 'Generic'; ... 'Gourmet', 'National', 'Generic'; ... 'Gourmet', 'National', 'Generic'}; popper = {'oil', 'oil', 'oil'; 'oil', 'oil', 'oil'; 'oil', 'oil', 'oil'; ... 'air', 'air', 'air'; 'air', 'air', 'air'; 'air', 'air', 'air'}; [P, ATAB, STATS] = anovan (popcorn(:),{brands(:),popper(:)},'display','off','model','full'); assert (P(1), 7.67895738278171e-07, 1e-09); assert (P(2), 0.000100373896304998, 1e-09); assert (P(3), 0.746215396636649, 1e-09); assert (ATAB{2,6}, 56.7, 1e-09); assert (ATAB{3,6}, 32.4, 1e-09); assert (ATAB{4,6}, 0.29999999999997, 1e-09); ***** test salary = [24 26 25 24 27 24 27 23 15 17 20 16, ... 25 29 27 19 18 21 20 21 22 19]'; gender = {'f' 'f' 'f' 'f' 'f' 'f' 'f' 'f' 'f' 'f' 'f' 'f'... 'm' 'm' 'm' 'm' 'm' 'm' 'm' 'm' 'm' 'm'}'; degree = [1 1 1 1 1 1 1 1 0 0 0 0 1 1 1 0 0 0 0 0 0 0]'; [P, ATAB, STATS] = anovan (salary,{gender,degree},'model','full','sstype',1,'display','off'); assert (P(1), 0.747462549227232, 1e-09); assert (P(2), 1.03809316857694e-08, 1e-09); assert (P(3), 0.523689833702691, 1e-09); assert (ATAB{2,2}, 0.296969696969699, 1e-09); assert (ATAB{3,2}, 272.391841491841, 1e-09); assert (ATAB{4,2}, 1.17482517482512, 1e-09); assert (ATAB{5,2}, 50.0000000000001, 1e-09); [P, ATAB, STATS] = anovan (salary,{degree,gender},'model','full','sstype',1,'display','off'); assert (P(1), 2.53445097305047e-08, 1e-09); assert (P(2), 0.00388133678528749, 1e-09); assert (P(3), 0.523689833702671, 1e-09); assert (ATAB{2,2}, 242.227272727273, 1e-09); assert (ATAB{3,2}, 30.4615384615384, 1e-09); assert (ATAB{4,2}, 1.17482517482523, 1e-09); assert (ATAB{5,2}, 50.0000000000001, 1e-09); [P, ATAB, STATS] = anovan (salary,{gender,degree},'model','full','sstype',2,'display','off'); assert (P(1), 0.00388133678528743, 1e-09); assert (P(2), 1.03809316857694e-08, 1e-09); assert (P(3), 0.523689833702691, 1e-09); assert (ATAB{2,2}, 30.4615384615385, 1e-09); assert (ATAB{3,2}, 272.391841491841, 1e-09); assert (ATAB{4,2}, 1.17482517482512, 1e-09); assert (ATAB{5,2}, 50.0000000000001, 1e-09); [P, ATAB, STATS] = anovan (salary,{gender,degree},'model','full','sstype',3,'display','off'); assert (P(1), 0.00442898146583742, 1e-09); assert (P(2), 1.30634252053587e-08, 1e-09); assert (P(3), 0.523689833702691, 1e-09); assert (ATAB{2,2}, 29.3706293706294, 1e-09); assert (ATAB{3,2}, 264.335664335664, 1e-09); assert (ATAB{4,2}, 1.17482517482512, 1e-09); assert (ATAB{5,2}, 50.0000000000001, 1e-09); ***** test sugar = {'real' 'fake' 'fake' 'real' 'real' 'real' 'none' 'none' 'none' ... 'fake' 'fake' 'fake' 'real' 'real' 'real' 'none' 'none' 'fake'}'; milk = {'yes' 'no' 'no' 'yes' 'yes' 'no' 'yes' 'yes' 'yes' ... 'no' 'no' 'yes' 'no' 'no' 'no' 'no' 'no' 'yes'}'; babble = [4.6 4.4 3.9 5.6 5.1 5.5 3.9 3.5 3.7... 5.6 4.7 5.9 6.0 5.4 6.6 5.8 5.3 5.7]'; [P, ATAB, STATS] = anovan (babble,{sugar,milk},'model','full','sstype',1,'display','off'); assert (P(1), 0.0108632139833963, 1e-09); assert (P(2), 0.0810606976703546, 1e-09); assert (P(3), 0.00175433329935627, 1e-09); assert (ATAB{2,2}, 3.55752380952381, 1e-09); assert (ATAB{3,2}, 0.956108477471702, 1e-09); assert (ATAB{4,2}, 5.94386771300448, 1e-09); assert (ATAB{5,2}, 3.1625, 1e-09); [P, ATAB, STATS] = anovan (babble,{milk,sugar},'model','full','sstype',1,'display','off'); assert (P(1), 0.0373333189297505, 1e-09); assert (P(2), 0.017075098787169, 1e-09); assert (P(3), 0.00175433329935627, 1e-09); assert (ATAB{2,2}, 1.444, 1e-09); assert (ATAB{3,2}, 3.06963228699552, 1e-09); assert (ATAB{4,2}, 5.94386771300448, 1e-09); assert (ATAB{5,2}, 3.1625, 1e-09); [P, ATAB, STATS] = anovan (babble,{sugar,milk},'model','full','sstype',2,'display','off'); assert (P(1), 0.017075098787169, 1e-09); assert (P(2), 0.0810606976703546, 1e-09); assert (P(3), 0.00175433329935627, 1e-09); assert (ATAB{2,2}, 3.06963228699552, 1e-09); assert (ATAB{3,2}, 0.956108477471702, 1e-09); assert (ATAB{4,2}, 5.94386771300448, 1e-09); assert (ATAB{5,2}, 3.1625, 1e-09); [P, ATAB, STATS] = anovan (babble,{sugar,milk},'model','full','sstype',3,'display','off'); assert (P(1), 0.0454263063473954, 1e-09); assert (P(2), 0.0746719907091438, 1e-09); assert (P(3), 0.00175433329935627, 1e-09); assert (ATAB{2,2}, 2.13184977578476, 1e-09); assert (ATAB{3,2}, 1.00413461538462, 1e-09); assert (ATAB{4,2}, 5.94386771300448, 1e-09); assert (ATAB{5,2}, 3.1625, 1e-09); ***** test drug = {'X' 'X' 'X' 'X' 'X' 'X' 'X' 'X' 'X' 'X' 'X' 'X' ... 'X' 'X' 'X' 'X' 'X' 'X' 'X' 'X' 'X' 'X' 'X' 'X'; 'Y' 'Y' 'Y' 'Y' 'Y' 'Y' 'Y' 'Y' 'Y' 'Y' 'Y' 'Y' ... 'Y' 'Y' 'Y' 'Y' 'Y' 'Y' 'Y' 'Y' 'Y' 'Y' 'Y' 'Y'; 'Z' 'Z' 'Z' 'Z' 'Z' 'Z' 'Z' 'Z' 'Z' 'Z' 'Z' 'Z' ... 'Z' 'Z' 'Z' 'Z' 'Z' 'Z' 'Z' 'Z' 'Z' 'Z' 'Z' 'Z'}; feedback = [1 1 1 1 1 1 1 1 1 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0; 1 1 1 1 1 1 1 1 1 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0; 1 1 1 1 1 1 1 1 1 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0]; diet = [0 0 0 0 0 0 1 1 1 1 1 1 0 0 0 0 0 0 1 1 1 1 1 1; 0 0 0 0 0 0 1 1 1 1 1 1 0 0 0 0 0 0 1 1 1 1 1 1; 0 0 0 0 0 0 1 1 1 1 1 1 0 0 0 0 0 0 1 1 1 1 1 1]; BP = [170 175 165 180 160 158 161 173 157 152 181 190 ... 173 194 197 190 176 198 164 190 169 164 176 175; 186 194 201 215 219 209 164 166 159 182 187 174 ... 189 194 217 206 199 195 171 173 196 199 180 NaN; 180 187 199 170 204 194 162 184 183 156 180 173 ... 202 228 190 206 224 204 205 199 170 160 NaN NaN]; [P, ATAB, STATS] = anovan (BP(:),{drug(:),feedback(:),diet(:)},'model','full','sstype', 1,'display','off'); assert (P(1), 7.02561843825325e-05, 1e-09); assert (P(2), 0.000425806013389362, 1e-09); assert (P(3), 6.16780773446401e-07, 1e-09); assert (P(4), 0.261347622678438, 1e-09); assert (P(5), 0.0542278432357043, 1e-09); assert (P(6), 0.590353225626655, 1e-09); assert (P(7), 0.0861628249564267, 1e-09); assert (ATAB{2,2}, 3614.70355731226, 1e-09); assert (ATAB{3,2}, 2227.46639771024, 1e-09); assert (ATAB{4,2}, 5008.25614451819, 1e-09); assert (ATAB{5,2}, 437.066007908781, 1e-09); assert (ATAB{6,2}, 976.180770397332, 1e-09); assert (ATAB{7,2}, 46.616653365254, 1e-09); assert (ATAB{8,2}, 814.345251396648, 1e-09); assert (ATAB{9,2}, 9065.8, 1e-09); [P, ATAB, STATS] = anovan (BP(:),{drug(:),feedback(:),diet(:)},'model','full','sstype',2,'display','off'); assert (P(1), 9.4879638470754e-05, 1e-09); assert (P(2), 0.00124177666315809, 1e-09); assert (P(3), 6.86162012732911e-07, 1e-09); assert (P(4), 0.260856132341256, 1e-09); assert (P(5), 0.0523758623892078, 1e-09); assert (P(6), 0.590353225626655, 1e-09); assert (P(7), 0.0861628249564267, 1e-09); assert (ATAB{2,2}, 3481.72176560122, 1e-09); assert (ATAB{3,2}, 1837.08812970469, 1e-09); assert (ATAB{4,2}, 4957.20277938622, 1e-09); assert (ATAB{5,2}, 437.693674777847, 1e-09); assert (ATAB{6,2}, 988.431929811402, 1e-09); assert (ATAB{7,2}, 46.616653365254, 1e-09); assert (ATAB{8,2}, 814.345251396648, 1e-09); assert (ATAB{9,2}, 9065.8, 1e-09); [P, ATAB, STATS] = anovan (BP(:),{drug(:),feedback(:),diet(:)},'model','full','sstype', 3,'display','off'); assert (P(1), 0.000106518678028207, 1e-09); assert (P(2), 0.00125371366571508, 1e-09); assert (P(3), 5.30813260778464e-07, 1e-09); assert (P(4), 0.308353667232981, 1e-09); assert (P(5), 0.0562901327343161, 1e-09); assert (P(6), 0.599091042141092, 1e-09); assert (P(7), 0.0861628249564267, 1e-09); assert (ATAB{2,2}, 3430.88156424581, 1e-09); assert (ATAB{3,2}, 1833.68031496063, 1e-09); assert (ATAB{4,2}, 5080.48346456693, 1e-09); assert (ATAB{5,2}, 382.07709497207, 1e-09); assert (ATAB{6,2}, 963.037988826813, 1e-09); assert (ATAB{7,2}, 44.4519685039322, 1e-09); assert (ATAB{8,2}, 814.345251396648, 1e-09); assert (ATAB{9,2}, 9065.8, 1e-09); ***** test measurement = [444 614 423 625 408 856 447 719 ... 764 831 586 782 609 1002 606 766]'; strain= {'NIH','NIH','BALB/C','BALB/C','A/J','A/J','129/Ola','129/Ola', ... 'NIH','NIH','BALB/C','BALB/C','A/J','A/J','129/Ola','129/Ola'}'; treatment={'C' 'T' 'C' 'T' 'C' 'T' 'C' 'T' 'C' 'T' 'C' 'T' 'C' 'T' 'C' 'T'}'; block = [1 1 1 1 1 1 1 1 2 2 2 2 2 2 2 2]'; [P, ATAB, STATS] = anovan (measurement/10,{strain,treatment,block},'model','full','random',3,'display','off'); assert (P(1), 0.0914352969909372, 1e-09); assert (P(2), 5.04077373924908e-05, 1e-09); assert (P(4), 0.0283196918836667, 1e-09); assert (ATAB{2,2}, 286.132500000002, 1e-09); assert (ATAB{3,2}, 2275.29, 1e-09); assert (ATAB{4,2}, 1242.5625, 1e-09); assert (ATAB{5,2}, 495.905000000001, 1e-09); assert (ATAB{6,2}, 207.007499999999, 1e-09); ***** test pulse = [67.9 65.1 77.3 78.7 79.4 80.4 85.8 86.6 87.5 89.1 ... 98.6 100.8 99.3 101.7 44.3 47.2 47.6 49.6 50.3 51.8 ... 60 58.5 58.9 60.7 69.8 70.9 76.2 76.1 77 77.7 84.7]'; temp = [20.8 20.8 24 24 24 24 26.2 26.2 26.2 26.2 28.4 ... 29 30.4 30.4 17.2 18.3 18.3 18.3 18.9 18.9 20.4 ... 21 21 22.1 23.5 24.2 25.9 26.5 26.5 26.5 28.6]'; species = {'ex' 'ex' 'ex' 'ex' 'ex' 'ex' 'ex' 'ex' 'ex' 'ex' 'ex' ... 'ex' 'ex' 'ex' 'niv' 'niv' 'niv' 'niv' 'niv' 'niv' 'niv' ... 'niv' 'niv' 'niv' 'niv' 'niv' 'niv' 'niv' 'niv' 'niv' 'niv'}; [P, ATAB, STATS] = anovan (pulse,{species,temp},'model','linear','continuous',2,'sstype','h','display','off'); assert (P(1), 6.27153318786007e-14, 1e-09); assert (P(2), 2.48773241196644e-25, 1e-09); assert (ATAB{2,2}, 598.003953318404, 1e-09); assert (ATAB{3,2}, 4376.08256843712, 1e-09); assert (ATAB{4,2}, 89.3498685376726, 1e-09); assert (ATAB{2,6}, 187.399388123951, 1e-09); assert (ATAB{3,6}, 1371.35413763454, 1e-09); ***** test score = [95.6 82.2 97.2 96.4 81.4 83.6 89.4 83.8 83.3 85.7 ... 97.2 78.2 78.9 91.8 86.9 84.1 88.6 89.8 87.3 85.4 ... 81.8 65.8 68.1 70.0 69.9 75.1 72.3 70.9 71.5 72.5 ... 84.9 96.1 94.6 82.5 90.7 87.0 86.8 93.3 87.6 92.4 ... 100. 80.5 92.9 84.0 88.4 91.1 85.7 91.3 92.3 87.9 ... 91.7 88.6 75.8 75.7 75.3 82.4 80.1 86.0 81.8 82.5]'; treatment = {'yes' 'yes' 'yes' 'yes' 'yes' 'yes' 'yes' 'yes' 'yes' 'yes' ... 'yes' 'yes' 'yes' 'yes' 'yes' 'yes' 'yes' 'yes' 'yes' 'yes' ... 'yes' 'yes' 'yes' 'yes' 'yes' 'yes' 'yes' 'yes' 'yes' 'yes' ... 'no' 'no' 'no' 'no' 'no' 'no' 'no' 'no' 'no' 'no' ... 'no' 'no' 'no' 'no' 'no' 'no' 'no' 'no' 'no' 'no' ... 'no' 'no' 'no' 'no' 'no' 'no' 'no' 'no' 'no' 'no'}'; exercise = {'lo' 'lo' 'lo' 'lo' 'lo' 'lo' 'lo' 'lo' 'lo' 'lo' ... 'mid' 'mid' 'mid' 'mid' 'mid' 'mid' 'mid' 'mid' 'mid' 'mid' ... 'hi' 'hi' 'hi' 'hi' 'hi' 'hi' 'hi' 'hi' 'hi' 'hi' ... 'lo' 'lo' 'lo' 'lo' 'lo' 'lo' 'lo' 'lo' 'lo' 'lo' ... 'mid' 'mid' 'mid' 'mid' 'mid' 'mid' 'mid' 'mid' 'mid' 'mid' ... 'hi' 'hi' 'hi' 'hi' 'hi' 'hi' 'hi' 'hi' 'hi' 'hi'}'; age = [59 65 70 66 61 65 57 61 58 55 62 61 60 59 55 57 60 63 62 57 ... 58 56 57 59 59 60 55 53 55 58 68 62 61 54 59 63 60 67 60 67 ... 75 54 57 62 65 60 58 61 65 57 56 58 58 58 52 53 60 62 61 61]'; [P, ATAB, STATS] = anovan (score,{treatment,exercise,age},'model','full','continuous',3,'sstype','h','display','off'); assert (P(5), 0.9245630968248468, 1e-09); assert (P(6), 0.791115159521822, 1e-09); assert (P(7), 0.9296668751457956, 1e-09); [P, ATAB, STATS] = anovan (score,{treatment,exercise,age},'model',[1 0 0; 0 1 0; 0 0 1; 1 1 0],'continuous',3,'sstype','h','display','off'); assert (P(1), 0.00158132928938933, 1e-09); assert (P(2), 2.12537505039986e-07, 1e-09); assert (P(3), 0.00390292555160047, 1e-09); assert (P(4), 0.0164086580775543, 1e-09); assert (ATAB{2,6}, 11.0956027650549, 1e-09); assert (ATAB{3,6}, 20.8195665467178, 1e-09); assert (ATAB{4,6}, 9.10966630720186, 1e-09); assert (ATAB{5,6}, 4.4457923698584, 1e-09); ***** test dv = [ 8.706 10.362 11.552 6.941 10.983 10.092 6.421 14.943 15.931 ... 22.968 18.590 16.567 15.944 21.637 14.492 17.965 18.851 22.891 ... 22.028 16.884 17.252 18.325 25.435 19.141 21.238 22.196 18.038 ... 22.628 31.163 26.053 24.419 32.145 28.966 30.207 29.142 33.212 ... 25.694 ]'; g = [1 1 1 1 1 1 1 1 2 2 2 2 2 3 3 3 3 3 3 3 3 4 4 4 4 4 4 4 5 5 5 5 5 5 5 5 5]'; C = [ 0.4001601 0.3333333 0.5 0.0 0.4001601 0.3333333 -0.5 0.0 0.4001601 -0.6666667 0.0 0.0 -0.6002401 0.0000000 0.0 0.5 -0.6002401 0.0000000 0.0 -0.5]; [P,ATAB,STATS] = anovan (dv,g,'contrasts',{C},'display','off'); assert (STATS.coeffs(1,1), 19.4001, 1e-04); assert (STATS.coeffs(2,1), -9.3297, 1e-04); assert (STATS.coeffs(3,1), -5.0000, 1e-04); assert (STATS.coeffs(4,1), -8.0000, 1e-04); assert (STATS.coeffs(5,1), -8.0000, 1e-04); assert (STATS.coeffs(1,2), 0.4831, 1e-04); assert (STATS.coeffs(2,2), 0.9694, 1e-04); assert (STATS.coeffs(3,2), 1.3073, 1e-04); assert (STATS.coeffs(4,2), 1.6411, 1e-04); assert (STATS.coeffs(5,2), 1.4507, 1e-04); assert (STATS.coeffs(1,5), 40.161, 1e-03); assert (STATS.coeffs(2,5), -9.624, 1e-03); assert (STATS.coeffs(3,5), -3.825, 1e-03); assert (STATS.coeffs(4,5), -4.875, 1e-03); assert (STATS.coeffs(5,5), -5.515, 1e-03); assert (STATS.coeffs(2,6), 5.74e-11, 1e-12); assert (STATS.coeffs(3,6), 0.000572, 1e-06); assert (STATS.coeffs(4,6), 2.86e-05, 1e-07); assert (STATS.coeffs(5,6), 4.44e-06, 1e-08); 12 tests, 12 passed, 0 known failure, 0 skipped [inst/mhsample.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/mhsample.m ***** demo ## Define function to sample d = 2; mu = [-1; 2]; rand ("seed", 5) # for reproducibility Sigma = rand (d); Sigma = (Sigma + Sigma'); Sigma += eye (d) * abs (eigs (Sigma, 1, "sa")) * 1.1; pdf = @(x)(2*pi)^(-d/2)*det(Sigma)^-.5*exp(-.5*sum((x.'-mu).*(Sigma\(x.'-mu)),1)); ## Inputs start = ones (1, 2); nsamples = 500; sym = true; K = 500; m = 10; rand ("seed", 8) # for reproducibility proprnd = @(x) (rand (size (x)) - .5) * 3 + x; [smpl, accept] = mhsample (start, nsamples, "pdf", pdf, "proprnd", proprnd, ... "symmetric", sym, "burnin", K, "thin", m); figure; hold on; plot (smpl(:, 1), smpl(:, 2), 'x'); [x, y] = meshgrid (linspace (-6, 4), linspace(-3, 7)); z = reshape (pdf ([x(:), y(:)]), size(x)); mesh (x, y, z, "facecolor", "None"); ## Using sample points to find the volume of half a sphere with radius of .5 f = @(x) ((.25-(x(:,1)+1).^2-(x(:,2)-2).^2).^.5.*(((x(:,1)+1).^2+(x(:,2)-2).^2)<.25)).'; int = mean (f (smpl) ./ pdf (smpl)); errest = std (f (smpl) ./ pdf (smpl)) / nsamples ^ .5; trueerr = abs (2 / 3 * pi * .25 ^ (3 / 2) - int); printf ("Monte Carlo integral estimate int f(x) dx = %f\n", int); printf ("Monte Carlo integral error estimate %f\n", errest); printf ("The actual error %f\n", trueerr); mesh (x, y, reshape (f([x(:), y(:)]), size(x)), "facecolor", "None"); ***** demo ## Integrate truncated normal distribution to find normilization constant pdf = @(x) exp (-.5*x.^2)/(pi^.5*2^.5); nsamples = 1e3; rand ("seed", 5) # for reproducibility proprnd = @(x) (rand (size (x)) - .5) * 3 + x; [smpl, accept] = mhsample (1, nsamples, "pdf", pdf, "proprnd", proprnd, ... "symmetric", true, "thin", 4); f = @(x) exp(-.5 * x .^ 2) .* (x >= -2 & x <= 2); x = linspace (-3, 3, 1000); area(x, f(x)); xlabel ('x'); ylabel ('f(x)'); int = mean (f (smpl) ./ pdf (smpl)); errest = std (f (smpl) ./ pdf (smpl)) / nsamples^ .5; trueerr = abs (erf (2 ^ .5) * 2 ^ .5 * pi ^ .5 - int); printf ("Monte Carlo integral estimate int f(x) dx = %f\n", int); printf ("Monte Carlo integral error estimate %f\n", errest); printf ("The actual error %f\n", trueerr); ***** test nchain = 1e4; start = rand (nchain, 1); nsamples = 1e3; pdf = @(x) exp (-.5*(x-1).^2)/(2*pi)^.5; proppdf = @(x, y) 1/3; proprnd = @(x) 3 * (rand (size (x)) - .5) + x; [smpl, accept] = mhsample (start, nsamples, "pdf", pdf, "proppdf", proppdf, ... "proprnd", proprnd, "thin", 2, "nchain", nchain, ... "burnin", 0); assert (mean (mean (smpl, 1), 3), 1, .01); assert (mean (var (smpl, 1), 3), 1, .01) ***** error mhsample (); ***** error mhsample (1); ***** error mhsample (1, 1); ***** error mhsample (1, 1, "pdf", @(x)x); ***** error mhsample (1, 1, "pdf", @(x)x, "proprnd", @(x)x+rand(size(x))); 6 tests, 6 passed, 0 known failure, 0 skipped [inst/stepwisefit.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/stepwisefit.m ***** test % Sample data from Draper and Smith (n = 13, k = 4) X = [7 1 11 11 7 11 3 1 2 21 1 11 10; ... 26 29 56 31 52 55 71 31 54 47 40 66 68; ... 6 15 8 8 6 9 17 22 18 4 23 9 8; ... 60 52 20 47 33 22 6 44 22 26 34 12 12]'; y = [78.5 74.3 104.3 87.6 95.9 109.2 102.7 72.5 93.1 115.9 83.8 113.3 109.4]'; [X_use, b, bint, r, rint, stats] = stepwisefit(y, X); assert(X_use, [4 1]) assert(b, regress(y, [ones(size(y)) X(:, X_use)], 0.05)) [X_use, b, bint, r, rint, stats] = stepwisefit(y, X, 0.05, 0.1, "corr"); assert(X_use, [4 1]) assert(b, regress(y, [ones(size(y)) X(:, X_use)], 0.05)) [X_use, b, bint, r, rint, stats] = stepwisefit(y, X, [], [], "p"); assert(X_use, [4 1]) assert(b, regress(y, [ones(size(y)) X(:, X_use)], 0.05)) 1 test, 1 passed, 0 known failure, 0 skipped [inst/hmmviterbi.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/hmmviterbi.m ***** test sequence = [1, 2, 1, 1, 1, 2, 2, 1, 2, 3, 3, 3, ... 3, 2, 3, 1, 1, 1, 1, 3, 3, 2, 3, 1, 3]; transprob = [0.8, 0.2; 0.4, 0.6]; outprob = [0.2, 0.4, 0.4; 0.7, 0.2, 0.1]; vpath = hmmviterbi (sequence, transprob, outprob); expected = [1, 1, 2, 2, 2, 1, 1, 1, 1, 1, 1, 1, ... 1, 1, 1, 2, 2, 2, 2, 1, 1, 1, 1, 1, 1]; assert (vpath, expected); ***** test sequence = {"A", "B", "A", "A", "A", "B", "B", "A", "B", "C", "C", "C", ... "C", "B", "C", "A", "A", "A", "A", "C", "C", "B", "C", "A", "C"}; transprob = [0.8, 0.2; 0.4, 0.6]; outprob = [0.2, 0.4, 0.4; 0.7, 0.2, 0.1]; symbols = {"A", "B", "C"}; statenames = {"One", "Two"}; vpath = hmmviterbi (sequence, transprob, outprob, "symbols", symbols, ... "statenames", statenames); expected = {"One", "One", "Two", "Two", "Two", "One", "One", "One", ... "One", "One", "One", "One", "One", "One", "One", "Two", ... "Two", "Two", "Two", "One", "One", "One", "One", "One", "One"}; assert (vpath, expected); 2 tests, 2 passed, 0 known failure, 0 skipped [inst/binotest.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/binotest.m ***** demo % flip a coin 1000 times, showing 475 heads % Hypothesis: coin is fair, i.e. p=1/2 [h,p_val,ci] = binotest(475,1000,0.5) % Result: h = 0 : null hypothesis not rejected, coin could be fair % P value 0.12, i.e. hypothesis not rejected for alpha up to 12% % 0.444 <= p <= 0.506 with 95% confidence ***** demo % flip a coin 100 times, showing 65 heads % Hypothesis: coin shows less than 50% heads, i.e. p<=1/2 [h,p_val,ci] = binotest(65,100,0.5,'tail','left','alpha',0.01) % Result: h = 1 : null hypothesis is rejected, i.e. coin shows more heads than tails % P value 0.0018, i.e. hypothesis not rejected for alpha up to 0.18% % 0 <= p <= 0.76 with 99% confidence ***** test #example from https://en.wikipedia.org/wiki/Binomial_test [h,p_val,ci] = binotest (51,235,1/6); assert (p_val, 0.0437, 0.00005) [h,p_val,ci] = binotest (51,235,1/6,'tail','left'); assert (p_val, 0.027, 0.0005) 1 test, 1 passed, 0 known failure, 0 skipped [inst/gmdistribution.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/gmdistribution.m ***** test mu = eye(2); Sigma = eye(2); GM = gmdistribution (mu, Sigma); density = GM.pdf ([0 0; 1 1]); assert (density(1) - density(2), 0, 1e-6); [idx, nlogl, P, logpdf,M] = cluster (GM, eye(2)); assert (idx, [1; 2]); [idx2,nlogl2,P2,logpdf2] = GM.cluster (eye(2)); assert (nlogl - nlogl2, 0, 1e-6); [idx3,nlogl3,P3] = cluster (GM, eye(2)); assert (P - P3, zeros (2), 1e-6); [idx4,nlogl4] = cluster (GM, eye(2)); assert (size (nlogl4), [1 1]); idx5 = cluster (GM, eye(2)); assert (idx - idx5, zeros (2,1)); D = GM.mahal ([1;0]); assert (D - M(1,:), zeros (1,2), 1e-6); P = GM.posterior ([0 1]); assert (P - P2(2,:), zeros (1,2), 1e-6); R = GM.random(20); assert (size(R), [20, 2]); R = GM.random(); assert (size(R), [1, 2]); 1 test, 1 passed, 0 known failure, 0 skipped [inst/inconsistent.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/inconsistent.m ***** error inconsistent () ***** error inconsistent ([1 2 1], 2, 3) ***** error inconsistent (ones (2, 2)) ***** error inconsistent ([1 2 1], -1) ***** error inconsistent ([1 2 1], 1.3) ***** error inconsistent ([1 2 1], [1 1]) ***** error inconsistent (ones (2, 3)) ***** test load fisheriris; Z = linkage(meas, 'average', 'chebychev'); assert (cond (inconsistent (Z)), 39.9, 1e-3); 8 tests, 8 passed, 0 known failure, 0 skipped [inst/signtest.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/signtest.m ***** error signtest (); ***** error signtest ([]); ***** error signtest (ones(1,10), ones(1,8)); ***** error signtest (ones(1,10), ones(2,10)); ***** error signtest (ones(2,10), 0); ***** error signtest (ones(1,10), zeros(1,10), "alpha", 1.4) ***** error signtest (ones(1,10), zeros(1,10), "tail", "<") ***** error signtest (ones(1,10), zeros(1,10), "method", "some") ***** test [pval, h, stats] = signtest ([-ones(1, 1000) 1], 0, "tail", "left"); assert (pval, 1.091701889420221e-218, 1e-14); assert (h, 1); assert (stats.zval, -31.5437631079266, 1e-14); ***** test [pval, h, stats] = signtest ([-2 -1 0 2 1 3 1], 0); assert (pval, 0.6875000000000006, 1e-14); assert (h, 0); assert (stats.zval, NaN); assert (stats.sign, 4); ***** test [pval, h, stats] = signtest ([-2 -1 0 2 1 3 1], 0, "method", "approximate"); assert (pval, 0.6830913983096086, 1e-14); assert (h, 0); assert (stats.zval, 0.4082482904638631, 1e-14); assert (stats.sign, 4); 11 tests, 11 passed, 0 known failure, 0 skipped [inst/tiedrank.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/tiedrank.m ***** test mileage = [33.3, 34.5, 37.4; 33.4, 34.8, 36.8; ... 32.9, 33.8, 37.6; 32.6, 33.4, 36.6; ... 32.5, 33.7, 37.0; 33.0, 33.9, 36.7]; [r,tieadj] = tiedrank([10, 20, 30, 40, 50]); assert (r, [1, 2, 3, 4, 5]); assert (tieadj, 0); [r,tieadj] = tiedrank([10, 20, 30, 40, 50]'); assert (r, [1; 2; 3; 4; 5]); ***** test mileage = [33.3, 34.5, 37.4; 33.4, 34.8, 36.8; ... 32.9, 33.8, 37.6; 32.6, 33.4, 36.6; ... 32.5, 33.7, 37.0; 33.0, 33.9, 36.7]; [r,tieadj] = tiedrank([10, 20, 30, 40, 50], 1); assert (r, [1, 2, 3, 4, 5]); assert (tieadj, [0 0 0]'); 2 tests, 2 passed, 0 known failure, 0 skipped [inst/mahal.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/mahal.m ***** error mahal () ***** error mahal (1, 2, 3) ***** error mahal ("A", "B") ***** error mahal ([1, 2], ["A", "B"]) ***** error mahal (ones (2, 2, 2)) ***** error mahal (ones (2, 2), ones (2, 2, 2)) ***** error mahal (ones (2, 2), ones (2, 3)) ***** test X = [1 0; 0 1; 1 1; 0 0]; assert (mahal (X, X), [1.5; 1.5; 1.5; 1.5], 10*eps) assert (mahal (X, X+1), [7.5; 7.5; 1.5; 13.5], 10*eps) ***** assert (mahal ([true; true], [false; true]), [0.5; 0.5], eps) 9 tests, 9 passed, 0 known failure, 0 skipped [inst/harmmean.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/harmmean.m ***** test x = [0:10]; y = [x;x+5;x+10]; assert (harmmean (x), 0); m = [0 8.907635160795225 14.30854471766802]; assert (harmmean (y, 2), m', 4e-14); assert (harmmean (y, "all"), 0); y(2,4) = NaN; m(2) = 9.009855936313949; assert (harmmean (y, 2), [0 NaN m(3)]', 4e-14); assert (harmmean (y', "omitnan"), m, 4e-14); z = y + 20; assert (harmmean (z, "all"), NaN); assert (harmmean (z, "all", "includenan"), NaN); assert (harmmean (z, "all", "omitnan"), 29.1108719858295, 4e-14); m = [24.59488458841874 NaN 34.71244385944397]; assert (harmmean (z'), m, 4e-14); assert (harmmean (z', "includenan"), m, 4e-14); m(2) = 29.84104075528277; assert (harmmean (z', "omitnan"), m, 4e-14); assert (harmmean (z, 2, "omitnan"), m', 4e-14); ***** test x = repmat ([1:20;6:25], [5 2 6 3]); assert (size (harmmean (x, [3 2])), [10 1 1 3]); assert (size (harmmean (x, [1 2])), [1 1 6 3]); assert (size (harmmean (x, [1 2 4])), [1 1 6]); assert (size (harmmean (x, [1 4 3])), [1 40]); assert (size (harmmean (x, [1 2 3 4])), [1 1]); ***** test x = repmat ([1:20;6:25], [5 2 6 3]); m = repmat ([5.559045930488016;13.04950789021461], [5 1 1 3]); assert (harmmean (x, [3 2]), m, 4e-14); x(2,5,6,3) = NaN; m(2,3) = NaN; assert (harmmean (x, [3 2]), m, 4e-14); m(2,3) = 13.06617961315406; assert (harmmean (x, [3 2], "omitnan"), m, 4e-14); ***** error harmmean ("char") ***** error harmmean ([1 -1 3]) ***** error ... harmmean (repmat ([1:20;6:25], [5 2 6 3 5]), -1) ***** error ... harmmean (repmat ([1:20;6:25], [5 2 6 3 5]), 0) ***** error ... harmmean (repmat ([1:20;6:25], [5 2 6 3 5]), [1 1]) 8 tests, 8 passed, 0 known failure, 0 skipped [inst/knnsearch.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/knnsearch.m ***** demo ## find 10 nearest neighbour of a point using different distance metrics ## and compare the results by plotting load fisheriris X = meas(:,3:4); Y = species; point = [5, 1.45]; ## calculate 10 nearest-neighbours by minkowski distance [id, d] = knnsearch (X, point, "K", 10); ## calculate 10 nearest-neighbours by minkowski distance [idm, dm] = knnsearch (X, point, "K", 10, "distance", "minkowski", "p", 5); ## calculate 10 nearest-neighbours by chebychev distance [idc, dc] = knnsearch (X, point, "K", 10, "distance", "chebychev"); ## plotting the results gscatter (X(:,1), X(:,2), species, [.75 .75 0; 0 .75 .75; .75 0 .75], ".", 20); title ("Fisher's Iris Data - Nearest Neighbors with different types of distance metrics"); xlabel("Petal length (cm)"); ylabel("Petal width (cm)"); line (point(1), point(2), "marker", "X", "color", "k", ... "linewidth", 2, "displayname", "query point") line (X(id,1), X(id,2), "color", [0.5 0.5 0.5], "marker", "o", ... "linestyle", "none", "markersize", 10, "displayname", "eulcidean") line (X(idm,1), X(idm,2), "color", [0.5 0.5 0.5], "marker", "d", ... "linestyle", "none", "markersize", 10, "displayname", "Minkowski") line (X(idc,1), X(idc,2), "color", [0.5 0.5 0.5], "marker", "p", ... "linestyle", "none", "markersize", 10, "displayname", "chebychev") xlim ([4.5 5.5]); ylim ([1 2]); axis square; ***** demo ## knnsearch on iris dataset using kdtree method load fisheriris X = meas(:,3:4); gscatter (X(:,1), X(:,2), species, [.75 .75 0; 0 .75 .75; .75 0 .75], ".", 20); title ("Fisher's iris dataset : Nearest Neighbors with kdtree search"); ## new point to be predicted point = [5 1.45]; line (point(1), point(2), "marker", "X", "color", "k", ... "linewidth", 2, "displayname", "query point") ## knnsearch using kdtree method [idx, d] = knnsearch (X, point, "K", 10, "NSMethod", "kdtree"); ## plotting predicted neighbours line (X(idx,1), X(idx,2), "color", [0.5 0.5 0.5], "marker", "o", ... "linestyle", "none", "markersize", 10, ... "displayname", "nearest neighbour") xlim ([4 6]) ylim ([1 3]) axis square ## details of predicted labels tabulate (species(idx)) ctr = point - d(end); diameter = 2 * d(end); ## Draw a circle around the 10 nearest neighbors. h = rectangle ("position", [ctr, diameter, diameter], "curvature", [1 1]); ## here only 8 neighbours are plotted instead of 10 since the dataset ## contains duplicate values ***** shared X, Y X = [1, 2, 3, 4; 2, 3, 4, 5; 3, 4, 5, 6]; Y = [1, 2, 2, 3; 2, 3, 3, 4]; ***** test [idx, D] = knnsearch (X, Y, "Distance", "euclidean"); assert (idx, [1; 1]); assert (D, ones (2, 1) * sqrt (2)); ***** test eucldist = @(v,m) sqrt(sumsq(repmat(v,rows(m),1)-m,2)); [idx, D] = knnsearch (X, Y, "Distance", eucldist); assert (idx, [1; 1]); assert (D, ones (2, 1) * sqrt (2)); ***** test [idx, D] = knnsearch (X, Y, "Distance", "euclidean", "includeties", true); assert (iscell (idx), true); assert (iscell (D), true) assert (idx {1}, [1]); assert (idx {2}, [1, 2]); assert (D{1}, ones (1, 1) * sqrt (2)); assert (D{2}, ones (1, 2) * sqrt (2)); ***** test [idx, D] = knnsearch (X, Y, "Distance", "euclidean", "k", 2); assert (idx, [1, 2; 1, 2]); assert (D, [sqrt(2), 3.162277660168380; sqrt(2), sqrt(2)], 1e-14); ***** test [idx, D] = knnsearch (X, Y, "Distance", "seuclidean"); assert (idx, [1; 1]); assert (D, ones (2, 1) * sqrt (2)); ***** test [idx, D] = knnsearch (X, Y, "Distance", "seuclidean", "k", 2); assert (idx, [1, 2; 1, 2]); assert (D, [sqrt(2), 3.162277660168380; sqrt(2), sqrt(2)], 1e-14); ***** test xx = [1, 2; 1, 3; 2, 4; 3, 6]; yy = [2, 4; 2, 6]; [idx, D] = knnsearch (xx, yy, "Distance", "mahalanobis"); assert (idx, [3; 2]); assert (D, [0; 3.162277660168377], 1e-14); ***** test [idx, D] = knnsearch (X, Y, "Distance", "minkowski"); assert (idx, [1; 1]); assert (D, ones (2, 1) * sqrt (2)); ***** test [idx, D] = knnsearch (X, Y, "Distance", "minkowski", "p", 3); assert (idx, [1; 1]); assert (D, ones (2, 1) * 1.259921049894873, 1e-14); ***** test [idx, D] = knnsearch (X, Y, "Distance", "cityblock"); assert (idx, [1; 1]); assert (D, [2; 2]); ***** test [idx, D] = knnsearch (X, Y, "Distance", "chebychev"); assert (idx, [1; 1]); assert (D, [1; 1]); ***** test [idx, D] = knnsearch (X, Y, "Distance", "cosine"); assert (idx, [2; 3]); assert (D, [0.005674536395645; 0.002911214328620], 1e-14); ***** test [idx, D] = knnsearch (X, Y, "Distance", "correlation"); assert (idx, [1; 1]); assert (D, ones (2, 1) * 0.051316701949486, 1e-14); ***** test [idx, D] = knnsearch (X, Y, "Distance", "spearman"); assert (idx, [1; 1]); assert (D, ones (2, 1) * 0.051316701949486, 1e-14); ***** test [idx, D] = knnsearch (X, Y, "Distance", "hamming"); assert (idx, [1; 1]); assert (D, [0.5; 0.5]); ***** test [idx, D] = knnsearch (X, Y, "Distance", "jaccard"); assert (idx, [1; 1]); assert (D, [0.5; 0.5]); ***** test [idx, D] = knnsearch (X, Y, "Distance", "jaccard", "k", 2); assert (idx, [1, 2; 1, 2]); assert (D, [0.5, 1; 0.5, 0.5]); ***** test a = [1, 5; 1, 2; 2, 2; 1.5, 1.5; 5, 1; 2 -1.34; 1, -3; 4, -4; -3, 1; 8, 9]; b = [1, 1]; [idx, D] = knnsearch (a, b, "K", 5, "NSMethod", "kdtree", "includeties", true); assert (iscell (idx), true); assert (iscell (D), true) assert (cell2mat (idx), [4, 2, 3, 6, 1, 5, 7, 9]); assert (cell2mat (D), [0.7071, 1.0000, 1.4142, 2.5447, 4.0000, 4.0000, 4.0000, 4.0000],1e-4); ***** test a = [1, 5; 1, 2; 2, 2; 1.5, 1.5; 5, 1; 2 -1.34; 1, -3; 4, -4; -3, 1; 8, 9]; b = [1, 1]; [idx, D] = knnsearch (a, b, "K", 5, "NSMethod", "exhaustive", "includeties", true); assert (iscell (idx), true); assert (iscell (D), true) assert (cell2mat (idx), [4, 2, 3, 6, 1, 5, 7, 9]); assert (cell2mat (D), [0.7071, 1.0000, 1.4142, 2.5447, 4.0000, 4.0000, 4.0000, 4.0000],1e-4); ***** test a = [1, 5; 1, 2; 2, 2; 1.5, 1.5; 5, 1; 2 -1.34; 1, -3; 4, -4; -3, 1; 8, 9]; b = [1, 1]; [idx, D] = knnsearch (a, b, "K", 5, "NSMethod", "kdtree", "includeties", false); assert (iscell (idx), false); assert (iscell (D), false) assert (idx, [4, 2, 3, 6, 1]); assert (D, [0.7071, 1.0000, 1.4142, 2.5447, 4.0000],1e-4); ***** test a = [1, 5; 1, 2; 2, 2; 1.5, 1.5; 5, 1; 2 -1.34; 1, -3; 4, -4; -3, 1; 8, 9]; b = [1, 1]; [idx, D] = knnsearch (a, b, "K", 5, "NSMethod", "exhaustive", "includeties", false); assert (iscell (idx), false); assert (iscell (D), false) assert (idx, [4, 2, 3, 6, 1]); assert (D, [0.7071, 1.0000, 1.4142, 2.5447, 4.0000],1e-4); ***** test load fisheriris a = meas; b = min(meas); [idx, D] = knnsearch (a, b, "K", 5, "NSMethod", "kdtree"); assert (idx, [42, 9, 14, 39, 13]); assert (D, [0.5099, 0.9950, 1.0050, 1.0536, 1.1874],1e-4); ***** test load fisheriris a = meas; b = mean(meas); [idx, D] = knnsearch (a, b, "K", 5, "NSMethod", "kdtree"); assert (idx, [65, 83, 89, 72, 100]); assert (D, [0.3451, 0.3869, 0.4354, 0.4481, 0.4625],1e-4); ***** test load fisheriris a = meas; b = max(meas); [idx, D] = knnsearch (a, b, "K", 5, "NSMethod", "kdtree"); assert (idx, [118, 132, 110, 106, 136]); assert (D, [0.7280, 0.9274, 1.3304, 1.5166, 1.6371],1e-4); ***** test load fisheriris a = meas; b = max(meas); [idx, D] = knnsearch (a, b, "K", 5, "includeties", true); assert ( iscell (idx), true); assert ( iscell (D), true); assert (cell2mat (idx), [118, 132, 110, 106, 136]); assert (cell2mat (D), [0.7280, 0.9274, 1.3304, 1.5166, 1.6371],1e-4); ***** error knnsearch (1) ***** error ... knnsearch (ones (4, 5), ones (4)) ***** error ... knnsearch (ones (4, 2), ones (3, 2), "Distance", "euclidean", "some", "some") ***** error ... knnsearch (ones (4, 5), ones (1, 5), "scale", ones (1, 5), "P", 3) ***** error ... knnsearch (ones (4, 5), ones (1, 5), "K", 0) ***** error ... knnsearch (ones (4, 5), ones (1, 5), "P",-2) ***** error ... knnsearch (ones (4, 5), ones (1, 5), "scale", ones(4,5), "distance", "euclidean") ***** error ... knnsearch (ones (4, 5), ones (1, 5), "cov", ["some" "some"]) ***** error ... knnsearch (ones (4, 5), ones (1, 5), "cov", ones(4,5), "distance", "euclidean") ***** error ... knnsearch (ones (4, 5), ones (1, 5), "bucketsize", -1) ***** error ... knnsearch (ones (4, 5), ones (1, 5), "NSmethod", "kdtree", "distance", "cosine") ***** error ... knnsearch (ones (4, 5), ones (1, 5), "NSmethod", "kdtree", "distance", "mahalanobis") ***** error ... knnsearch (ones (4, 5), ones (1, 5), "NSmethod", "kdtree", "distance", "correlation") ***** error ... knnsearch (ones (4, 5), ones (1, 5), "NSmethod", "kdtree", "distance", "seuclidean") ***** error ... knnsearch (ones (4, 5), ones (1, 5), "NSmethod", "kdtree", "distance", "spearman") ***** error ... knnsearch (ones (4, 5), ones (1, 5), "NSmethod", "kdtree", "distance", "hamming") ***** error ... knnsearch (ones (4, 5), ones (1, 5), "NSmethod", "kdtree", "distance", "jaccard") 42 tests, 42 passed, 0 known failure, 0 skipped [inst/histfit.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/histfit.m ***** demo histfit (randn (100, 1)) ***** test hf = figure ("visible", "off"); unwind_protect x = [2, 4, 3, 2, 4, 3, 2, 5, 6, 4, 7, 5, 9, 8, 10, 4, 11]; histfit (x); unwind_protect_cleanup close (hf); end_unwind_protect ***** test hf = figure ("visible", "off"); unwind_protect x = [2, 4, 3, 2, NaN, 3, 2, 5, 6, 4, 7, 5, 9, 8, 10, 4, 11]; histfit (x); unwind_protect_cleanup close (hf); end_unwind_protect ***** test hf = figure ("visible", "off"); unwind_protect x = [2, 4, 3, 2, NaN, 3, 2, 5, 6, 4, 7, 5, 9, 8, 10, 4, 11]; histfit (x, 3); unwind_protect_cleanup close (hf); end_unwind_protect ***** error histfit (); ***** error histfit ([x',x']); 5 tests, 5 passed, 0 known failure, 0 skipped [inst/crosstab.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/crosstab.m ***** error crosstab () ***** error crosstab (1) ***** error crosstab (ones (2), [1 1]) ***** error crosstab ([1 1], ones (2)) ***** error crosstab ([1], [1 2]) ***** error crosstab ([1 2], [1]) ***** test load carbig [table, chisq, p, labels] = crosstab (cyl4, when, org); assert (table(2,3,1), 38); assert (labels{3,3}, "Japan"); ***** test load carbig [table, chisq, p, labels] = crosstab (cyl4, when, org); assert (table(2,3,2), 17); assert (labels{1,3}, "USA"); 8 tests, 8 passed, 0 known failure, 0 skipped [inst/optimalleaforder.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/optimalleaforder.m ***** demo randn ("seed", 5) # for reproducibility X = randn (10, 2); D = pdist (X); tree = linkage(D, 'average'); optimalleaforder (tree, D, 'Transformation', 'linear') ***** error optimalleaforder () ***** error optimalleaforder (1) ***** error optimalleaforder (ones (2, 2), 1) ***** error optimalleaforder ([1 2 3], [1 2; 3 4], "criteria", 5) ***** error optimalleaforder ([1 2 1], [1 2 3]) ***** error optimalleaforder ([1 2 1], 1, "xxx", "xxx") ***** error optimalleaforder ([1 2 1], 1, "Transformation", "xxx") 7 tests, 7 passed, 0 known failure, 0 skipped [inst/plsregress.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/plsregress.m ***** demo ## Perform Partial Least-Squares Regression ## Load the spectra data set and use the near infrared (NIR) spectral ## intensities (NIR) as the predictor and the corresponding octave ## ratings (octave) as the response. load spectra ## Perform PLS regression with 10 components [xload, yload, xscore, yscore, coef, ptcVar] = plsregress (NIR, octane, 10); ## Plot the percentage of explained variance in the response variable ## (PCTVAR) as a function of the number of components. plot (1:10, cumsum (100 * ptcVar(2,:)), "-ro"); xlim ([1, 10]); xlabel ("Number of PLS components"); ylabel ("Percentage of Explained Variance in octane"); title ("Explained Variance per PLS components"); ## Compute the fitted response and display the residuals. octane_fitted = [ones(size(NIR,1),1), NIR] * coef; residuals = octane - octane_fitted; figure stem (residuals, "color", "r", "markersize", 4, "markeredgecolor", "r") xlabel ("Observations"); ylabel ("Residuals"); title ("Residuals in octane's fitted responce"); ***** demo ## Calculate Variable Importance in Projection (VIP) for PLS Regression ## Load the spectra data set and use the near infrared (NIR) spectral ## intensities (NIR) as the predictor and the corresponding octave ## ratings (octave) as the response. Variables with a VIP score greater than ## 1 are considered important for the projection of the PLS regression model. load spectra ## Perform PLS regression with 10 components [xload, yload, xscore, yscore, coef, pctVar, mse, stats] = ... plsregress (NIR, octane, 10); ## Calculate the normalized PLS weights W0 = stats.W ./ sqrt(sum(stats.W.^2,1)); ## Calculate the VIP scores for 10 components nobs = size (xload, 1); SS = sum (xscore .^ 2, 1) .* sum (yload .^ 2, 1); VIPscore = sqrt (nobs * sum (SS .* (W0 .^ 2), 2) ./ sum (SS, 2)); ## Find variables with a VIP score greater than or equal to 1 VIPidx = find (VIPscore >= 1); ## Plot the VIP scores scatter (1:length (VIPscore), VIPscore, "xb"); hold on scatter (VIPidx, VIPscore (VIPidx), "xr"); plot ([1, length(VIPscore)], [1, 1], "--k"); hold off axis ("tight"); xlabel ("Predictor Variables"); ylabel ("VIP scores"); title ("VIP scores for each predictror variable with 10 components"); ***** test load spectra [xload, yload, xscore, yscore, coef, pctVar] = plsregress (NIR, octane, 10); xload1_out = [-0.0170, 0.0039, 0.0095, 0.0258, 0.0025, ... -0.0075, 0.0000, 0.0018, -0.0027, 0.0020]; yload_out = [6.6384, 9.3106, 2.0505, 0.6471, 0.9625, ... 0.5905, 0.4244, 0.2437, 0.3516, 0.2548]; xscore1_out = [-0.0401, -0.1764, -0.0340, 0.1669, 0.1041, ... -0.2067, 0.0457, 0.1565, 0.0706, -0.1471]; yscore1_out = [-12.4635, -15.0003, 0.0638, 0.0652, -0.0070, ... -0.0634, 0.0062, -0.0012, -0.0151, -0.0173]; assert (xload(1,:), xload1_out, 1e-4); assert (yload, yload_out, 1e-4); assert (xscore(1,:), xscore1_out, 1e-4); assert (yscore(1,:), yscore1_out, 1e-4); ***** test load spectra [xload, yload, xscore, yscore, coef, pctVar] = plsregress (NIR, octane, 5); xload1_out = [-0.0170, 0.0039, 0.0095, 0.0258, 0.0025]; yload_out = [6.6384, 9.3106, 2.0505, 0.6471, 0.9625]; xscore1_out = [-0.0401, -0.1764, -0.0340, 0.1669, 0.1041]; yscore1_out = [-12.4635, -15.0003, 0.0638, 0.0652, -0.0070]; assert (xload(1,:), xload1_out, 1e-4); assert (yload, yload_out, 1e-4); assert (xscore(1,:), xscore1_out, 1e-4); assert (yscore(1,:), yscore1_out, 1e-4); ***** error plsregress (1) ***** error plsregress (1, "asd") ***** error plsregress (1, {1,2,3}) ***** error plsregress ("asd", 1) ***** error plsregress ({1,2,3}, 1) ***** error ... plsregress (ones (20,3), ones (15,1)) ***** error ... plsregress (ones (20,3), ones (20,1), 0) ***** error ... plsregress (ones (20,3), ones (20,1), -5) ***** error ... plsregress (ones (20,3), ones (20,1), 3.2) ***** error ... plsregress (ones (20,3), ones (20,1), [2, 3]) ***** error ... plsregress (ones (20,3), ones (20,1), 4) ***** error ... plsregress (ones (20,3), ones (20,1), 3, "cv", 4.5) ***** error ... plsregress (ones (20,3), ones (20,1), 3, "cv", -1) ***** error ... plsregress (ones (20,3), ones (20,1), 3, "cv", "somestring") ***** error ... plsregress (ones (20,3), ones (20,1), 3, "cv", 3, "mcreps", 2.2) ***** error ... plsregress (ones (20,3), ones (20,1), 3, "cv", 3, "mcreps", -2) ***** error ... plsregress (ones (20,3), ones (20,1), 3, "cv", 3, "mcreps", [1, 2]) ***** error ... plsregress (ones (20,3), ones (20,1), 3, "Name", 3, "mcreps", 1) ***** error ... plsregress (ones (20,3), ones (20,1), 3, "cv", 3, "Name", 1) ***** error ... plsregress (ones (20,3), ones (20,1), 3, "mcreps", 2) ***** error ... plsregress (ones (20,3), ones (20,1), 3, "cv", "resubstitution", "mcreps", 2) ***** error plsregress (1, 2) 24 tests, 24 passed, 0 known failure, 0 skipped [inst/vartest2.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/vartest2.m ***** error vartest2 (); ***** error vartest2 (ones (20,1)); ***** error ... vartest2 (rand (20,1), 5); ***** error ... vartest2 (rand (20,1), rand (25,1)*2, "alpha", 0); ***** error ... vartest2 (rand (20,1), rand (25,1)*2, "alpha", 1.2); ***** error ... vartest2 (rand (20,1), rand (25,1)*2, "alpha", "some"); ***** error ... vartest2 (rand (20,1), rand (25,1)*2, "alpha", [0.05, 0.001]); ***** error ... vartest2 (rand (20,1), rand (25,1)*2, "tail", [0.05, 0.001]); ***** error ... vartest2 (rand (20,1), rand (25,1)*2, "tail", "some"); ***** error ... vartest2 (rand (20,1), rand (25,1)*2, "dim", 3); ***** error ... vartest2 (rand (20,1), rand (25,1)*2, "alpha", 0.001, "dim", 3); ***** error ... vartest2 (rand (20,1), rand (25,1)*2, "some", 3); ***** error ... vartest2 (rand (20,1), rand (25,1)*2, "some"); ***** test load carsmall [h, pval, ci, stat] = vartest2 (MPG(Model_Year==82), MPG(Model_Year==76)); assert (h, 0); assert (pval, 0.6288022362718455, 1e-13); assert (ci, [0.4139; 1.7193], 1e-4); assert (stat.fstat, 0.8384, 1e-4); assert (stat.df1, 30); assert (stat.df2, 33); 14 tests, 14 passed, 0 known failure, 0 skipped [inst/normplot.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/normplot.m ***** demo h = normplot([1:20]); ***** demo h = normplot([1:20;5:2:44]'); ***** demo ax = newplot(); h = normplot(ax, [1:20]); ax = gca; h = normplot(ax, [-10:10]); set (ax, "xlim", [-11, 21]); ***** error normplot (); ***** error normplot (23); ***** error normplot (23, [1:20]); ***** error normplot (ones(3,4,5)); ***** test hf = figure ("visible", "off"); unwind_protect ax = newplot (hf); h = normplot (ax, [1:20]); ax = gca; h = normplot(ax, [-10:10]); set (ax, "xlim", [-11, 21]); unwind_protect_cleanup close (hf); end_unwind_protect ***** test hf = figure ("visible", "off"); unwind_protect h = normplot([1:20;5:2:44]'); unwind_protect_cleanup close (hf); end_unwind_protect 6 tests, 6 passed, 0 known failure, 0 skipped [inst/datasample.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/datasample.m ***** error datasample(); ***** error datasample(1); ***** error datasample({1, 2, 3}, 1); ***** error datasample([1 2], -1); ***** error datasample([1 2], 1.5); ***** error datasample([1 2], [1 1]); ***** error datasample([1 2], 'g', [1 1]); ***** error datasample([1 2], 1, -1); ***** error datasample([1 2], 1, 1.5); ***** error datasample([1 2], 1, [1 1]); ***** error datasample([1 2], 1, 1, "Replace", -2); ***** error datasample([1 2], 1, 1, "Weights", "abc"); ***** error datasample([1 2], 1, 1, "Weights", [1 -2 3]); ***** error datasample([1 2], 1, 1, "Weights", ones (2)); ***** error datasample([1 2], 1, 1, "Weights", [1 2 3]); ***** test dat = randn (10, 4); assert (size (datasample (dat, 3, 1)), [3 4]); ***** test dat = randn (10, 4); assert (size (datasample (dat, 3, 2)), [10 3]); 17 tests, 17 passed, 0 known failure, 0 skipped [inst/ztest2.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/ztest2.m ***** error ztest2 (); ***** error ztest2 (1); ***** error ztest2 (1, 2); ***** error ztest2 (1, 2, 3); ***** error ... ztest2 (1, 2, 3, 4, "alpha") ***** error ... ztest2 (1, 2, 3, 4, "alpha", 0); ***** error ... ztest2 (1, 2, 3, 4, "alpha", 1.2); ***** error ... ztest2 (1, 2, 3, 4, "alpha", "val"); ***** error ... ztest2 (1, 2, 3, 4, "tail", "val"); ***** error ... ztest2 (1, 2, 3, 4, "alpha", 0.01, "tail", "val"); ***** error ... ztest2 (1, 2, 3, 4, "alpha", 0.01, "tail", "both", "badoption", 3); 11 tests, 11 passed, 0 known failure, 0 skipped [inst/princomp.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/princomp.m ***** shared COEFF,SCORE,latent,tsquare,m,x,R,V,lambda,i,S,F ***** test x=[7 4 3 4 1 8 6 3 5 8 6 1 8 5 7 7 2 9 5 3 3 9 5 8 7 4 5 8 2 2]; R = corrcoef (x); [V, lambda] = eig (R); [~, i] = sort(diag(lambda), "descend"); #arrange largest PC first S = V(:, i) * diag(sqrt(diag(lambda)(i))); ## contribution of first 2 PCs to each original variable ***** assert(diag(S(:, 1:2)*S(:, 1:2)'), [0.8662; 0.8420; 0.9876], 1E-4); B = V(:, i) * diag( 1./ sqrt(diag(lambda)(i))); F = zscore(x)*B; [COEFF,SCORE,latent,tsquare] = princomp(zscore(x, 1)); ***** assert(tsquare,sumsq(F, 2),1E4*eps); ***** test x=[1,2,3;2,1,3]'; [COEFF,SCORE,latent,tsquare] = princomp(x); m=[sqrt(2),sqrt(2);sqrt(2),-sqrt(2);-2*sqrt(2),0]/2; m(:,1) = m(:,1)*sign(COEFF(1,1)); m(:,2) = m(:,2)*sign(COEFF(1,2)); ***** assert(COEFF,m(1:2,:),10*eps); ***** assert(SCORE,-m,10*eps); ***** assert(latent,[1.5;.5],10*eps); ***** assert(tsquare,[4;4;4]/3,10*eps); ***** test x=x'; [COEFF,SCORE,latent,tsquare] = princomp(x); m=[sqrt(2),sqrt(2),0;-sqrt(2),sqrt(2),0;0,0,2]/2; m(:,1) = m(:,1)*sign(COEFF(1,1)); m(:,2) = m(:,2)*sign(COEFF(1,2)); m(:,3) = m(:,3)*sign(COEFF(3,3)); ***** assert(COEFF,m,10*eps); ***** assert(SCORE(:,1),-m(1:2,1),10*eps); ***** assert(SCORE(:,2:3),zeros(2),10*eps); ***** assert(latent,[1;0;0],10*eps); ***** assert(tsquare,[0.5;0.5],10*eps) ***** test [COEFF,SCORE,latent,tsquare] = princomp(x, "econ"); ***** assert(COEFF,m(:, 1),10*eps); ***** assert(SCORE,-m(1:2,1),10*eps); ***** assert(latent,[1],10*eps); ***** assert(tsquare,[0.5;0.5],10*eps) 19 tests, 19 passed, 0 known failure, 0 skipped [inst/crossval.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/crossval.m ***** test load fisheriris y = meas(:, 1); X = [ones(size(y)) meas(:, 2:4)]; f = @(X1, y1, X2, y2) meansq (y2 - X2*regress(y1, X1)); results0 = crossval (f, X, y); results1 = crossval (f, X, y, 'KFold', 10); folds = 5; results2 = crossval (f, X, y, 'KFold', folds); results3 = crossval (f, X, y, 'Partition', cvpartition (numel (y), 'KFold', folds)); results4 = crossval (f, X, y, 'LeaveOut', 1); mcreps = 2; n_holdout = 20; results5 = crossval (f, X, y, 'HoldOut', n_holdout, 'mcreps', mcreps); ## ensure equal representation of iris species in the training set -- tends ## to slightly reduce cross-validation mean square error results6 = crossval (f, X, y, 'KFold', 5, 'stratify', grp2idx(species)); assert (results0, results1, 2e-15); assert (results2, results3, 5e-17); assert (size(results4), [1 numel(y)]); assert (mean(results4), 0.1018, 1e-4); assert (size(results5), [mcreps 1]); warning: strmatch is obsolete; use strncmp or strcmp instead 1 test, 1 passed, 0 known failure, 0 skipped [inst/correlation_test.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/correlation_test.m ***** error correlation_test (); ***** error correlation_test (1); ***** error ... correlation_test ([1 2 NaN]', [2 3 4]'); ***** error ... correlation_test ([1 2 Inf]', [2 3 4]'); ***** error ... correlation_test ([1 2 3+i]', [2 3 4]'); ***** error ... correlation_test ([1 2 3]', [2 3 NaN]'); ***** error ... correlation_test ([1 2 3]', [2 3 Inf]'); ***** error ... correlation_test ([1 2 3]', [3 4 3+i]'); ***** error ... correlation_test ([1 2 3]', [3 4 4 5]'); ***** error ... correlation_test ([1 2 3]', [2 3 4]', "alpha", 0); ***** error ... correlation_test ([1 2 3]', [2 3 4]', "alpha", 1.2); ***** error ... correlation_test ([1 2 3]', [2 3 4]', "alpha", [.02 .1]); ***** error ... correlation_test ([1 2 3]', [2 3 4]', "alpha", "a"); ***** error ... correlation_test ([1 2 3]', [2 3 4]', "some", 0.05); ***** error ... correlation_test ([1 2 3]', [2 3 4]', "tail", "val"); ***** error ... correlation_test ([1 2 3]', [2 3 4]', "alpha", 0.01, "tail", "val"); ***** error ... correlation_test ([1 2 3]', [2 3 4]', "method", 0.01); ***** error ... correlation_test ([1 2 3]', [2 3 4]', "method", "some"); ***** test x = [6 7 7 9 10 12 13 14 15 17]; y = [19 22 27 25 30 28 30 29 25 32]; [h, pval, stats] = correlation_test (x, y); assert (stats.corrcoef, corr (x', y'), 1e-14); assert (pval, 0.0223, 1e-4); ***** test x = [6 7 7 9 10 12 13 14 15 17]'; y = [19 22 27 25 30 28 30 29 25 32]'; [h, pval, stats] = correlation_test (x, y); assert (stats.corrcoef, corr (x, y), 1e-14); assert (pval, 0.0223, 1e-4); 20 tests, 20 passed, 0 known failure, 0 skipped [inst/dist_stat/gpstat.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/dist_stat/gpstat.m ***** error gpstat () ***** error gpstat (1) ***** error gpstat (1, 2) ***** error gpstat ({}, 2, 3) ***** error gpstat (1, "", 3) ***** error gpstat (1, 2, "") ***** error gpstat (i, 2, 3) ***** error gpstat (1, i, 3) ***** error gpstat (1, 2, i) ***** error ... gpstat (ones (3), ones (2), 3) ***** error ... gpstat (ones (2), 2, ones (3)) ***** error ... gpstat (1, ones (2), ones (3)) ***** shared x, y x = [-Inf, -1, 0, 1/2, 1, Inf]; y = [0, 0.5, 1, 2, Inf, Inf]; ***** assert (gpstat (x, ones (1,6), zeros (1,6)), y, eps) ***** assert (gpstat (single (x), 1, 0), single (y), eps("single")) ***** assert (gpstat (x, single (1), 0), single (y), eps("single")) ***** assert (gpstat (x, 1, single (0)), single (y), eps("single")) ***** assert (gpstat (single ([x, NaN]), 1, 0), single ([y, NaN]), eps("single")) ***** assert (gpstat ([x, NaN], single (1), 0), single ([y, NaN]), eps("single")) ***** assert (gpstat ([x, NaN], 1, single (0)), single ([y, NaN]), eps("single")) 19 tests, 19 passed, 0 known failure, 0 skipped [inst/dist_stat/invgstat.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/dist_stat/invgstat.m ***** error invgstat () ***** error invgstat (1) ***** error invgstat ({}, 2) ***** error invgstat (1, "") ***** error invgstat (i, 2) ***** error invgstat (1, i) ***** error ... invgstat (ones (3), ones (2)) ***** error ... invgstat (ones (2), ones (3)) ***** test [m, v] = invgstat (1, 1); assert (m, 1); assert (v, 1); ***** test [m, v] = invgstat (2, 1); assert (m, 2); assert (v, 8); ***** test [m, v] = invgstat (2, 2); assert (m, 2); assert (v, 4); ***** test [m, v] = invgstat (2, 2.5); assert (m, 2); assert (v, 3.2); ***** test [m, v] = invgstat (1.5, 0.5); assert (m, 1.5); assert (v, 6.75); 13 tests, 13 passed, 0 known failure, 0 skipped [inst/dist_stat/poisstat.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/dist_stat/poisstat.m ***** error poisstat () ***** error poisstat ({}) ***** error poisstat ("") ***** error poisstat (i) ***** test lambda = 1 ./ (1:6); [m, v] = poisstat (lambda); assert (m, lambda); assert (v, lambda); 5 tests, 5 passed, 0 known failure, 0 skipped [inst/dist_stat/evstat.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/dist_stat/evstat.m ***** error evstat () ***** error evstat (1) ***** error evstat ({}, 2) ***** error evstat (1, "") ***** error evstat (i, 2) ***** error evstat (1, i) ***** error ... evstat (ones (3), ones (2)) ***** error ... evstat (ones (2), ones (3)) ***** shared x, y0, y1 x = [-5, 0, 1, 2, 3]; y0 = [NaN, NaN, 0.4228, 0.8456, 1.2684]; y1 = [-5.5772, -3.4633, -3.0405, -2.6177, -2.1949]; ***** assert (evstat (x, x), y0, 1e-4) ***** assert (evstat (x, x+6), y1, 1e-4) ***** assert (evstat (x, x-6), NaN (1,5)) 11 tests, 11 passed, 0 known failure, 0 skipped [inst/dist_stat/nbinstat.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/dist_stat/nbinstat.m ***** error nbinstat () ***** error nbinstat (1) ***** error nbinstat ({}, 2) ***** error nbinstat (1, "") ***** error nbinstat (i, 2) ***** error nbinstat (1, i) ***** error ... nbinstat (ones (3), ones (2)) ***** error ... nbinstat (ones (2), ones (3)) ***** test r = 1:4; ps = 0.2:0.2:0.8; [m, v] = nbinstat (r, ps); expected_m = [ 4.0000, 3.0000, 2.0000, 1.0000]; expected_v = [20.0000, 7.5000, 3.3333, 1.2500]; assert (m, expected_m, 0.001); assert (v, expected_v, 0.001); ***** test r = 1:4; [m, v] = nbinstat (r, 0.5); expected_m = [1, 2, 3, 4]; expected_v = [2, 4, 6, 8]; assert (m, expected_m, 0.001); assert (v, expected_v, 0.001); 10 tests, 10 passed, 0 known failure, 0 skipped [inst/dist_stat/betastat.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/dist_stat/betastat.m ***** error betastat () ***** error betastat (1) ***** error betastat ({}, 2) ***** error betastat (1, "") ***** error betastat (i, 2) ***** error betastat (1, i) ***** error ... betastat (ones (3), ones (2)) ***** error ... betastat (ones (2), ones (3)) ***** test a = -2:6; b = 0.4:0.2:2; [m, v] = betastat (a, b); expected_m = [NaN NaN NaN 1/2 2/3.2 3/4.4 4/5.6 5/6.8 6/8]; expected_v = [NaN NaN NaN 0.0833, 0.0558, 0.0402, 0.0309, 0.0250, 0.0208]; assert (m, expected_m, eps*100); assert (v, expected_v, 0.001); ***** test a = -2:1:6; [m, v] = betastat (a, 1.5); expected_m = [NaN NaN NaN 1/2.5 2/3.5 3/4.5 4/5.5 5/6.5 6/7.5]; expected_v = [NaN NaN NaN 0.0686, 0.0544, 0.0404, 0.0305, 0.0237, 0.0188]; assert (m, expected_m); assert (v, expected_v, 0.001); ***** test a = [14 Inf 10 NaN 10]; b = [12 9 NaN Inf 12]; [m, v] = betastat (a, b); expected_m = [14/26 NaN NaN NaN 10/22]; expected_v = [168/18252 NaN NaN NaN 120/11132]; assert (m, expected_m); assert (v, expected_v); ***** assert (nthargout (1:2, @betastat, 5, []), {[], []}) ***** assert (nthargout (1:2, @betastat, [], 5), {[], []}) ***** assert (size (betastat (rand (10, 5, 4), rand (10, 5, 4))), [10 5 4]) ***** assert (size (betastat (rand (10, 5, 4), 7)), [10 5 4]) 15 tests, 15 passed, 0 known failure, 0 skipped [inst/dist_stat/unidstat.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/dist_stat/unidstat.m ***** error unidstat () ***** error unidstat ({}) ***** error unidstat ("") ***** error unidstat (i) ***** test N = 1:6; [m, v] = unidstat (N); expected_m = [1.0000, 1.5000, 2.0000, 2.5000, 3.0000, 3.5000]; expected_v = [0.0000, 0.2500, 0.6667, 1.2500, 2.0000, 2.9167]; assert (m, expected_m, 0.001); assert (v, expected_v, 0.001); 5 tests, 5 passed, 0 known failure, 0 skipped [inst/dist_stat/hnstat.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/dist_stat/hnstat.m ***** error hnstat () ***** error hnstat (1) ***** error hnstat ({}, 2) ***** error hnstat (1, "") ***** error hnstat (i, 2) ***** error hnstat (1, i) ***** error ... hnstat (ones (3), ones (2)) ***** error ... hnstat (ones (2), ones (3)) ***** test [m, v] = hnstat (0, 1); assert (m, 0.7979, 1e-4); assert (v, 0.3634, 1e-4); ***** test [m, v] = hnstat (2, 1); assert (m, 2.7979, 1e-4); assert (v, 0.3634, 1e-4); ***** test [m, v] = hnstat (2, 2); assert (m, 3.5958, 1e-4); assert (v, 1.4535, 1e-4); ***** test [m, v] = hnstat (2, 2.5); assert (m, 3.9947, 1e-4); assert (v, 2.2711, 1e-4); ***** test [m, v] = hnstat (1.5, 0.5); assert (m, 1.8989, 1e-4); assert (v, 0.0908, 1e-4); ***** test [m, v] = hnstat (-1.5, 0.5); assert (m, -1.1011, 1e-4); assert (v, 0.0908, 1e-4); 14 tests, 14 passed, 0 known failure, 0 skipped [inst/dist_stat/wblstat.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/dist_stat/wblstat.m ***** error wblstat () ***** error wblstat (1) ***** error wblstat ({}, 2) ***** error wblstat (1, "") ***** error wblstat (i, 2) ***** error wblstat (1, i) ***** error ... wblstat (ones (3), ones (2)) ***** error ... wblstat (ones (2), ones (3)) ***** test lambda = 3:8; k = 1:6; [m, v] = wblstat (lambda, k); expected_m = [3.0000, 3.5449, 4.4649, 5.4384, 6.4272, 7.4218]; expected_v = [9.0000, 3.4336, 2.6333, 2.3278, 2.1673, 2.0682]; assert (m, expected_m, 0.001); assert (v, expected_v, 0.001); ***** test k = 1:6; [m, v] = wblstat (6, k); expected_m = [ 6.0000, 5.3174, 5.3579, 5.4384, 5.5090, 5.5663]; expected_v = [36.0000, 7.7257, 3.7920, 2.3278, 1.5923, 1.1634]; assert (m, expected_m, 0.001); assert (v, expected_v, 0.001); 10 tests, 10 passed, 0 known failure, 0 skipped [inst/dist_stat/burrstat.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/dist_stat/burrstat.m ***** error burrstat () ***** error burrstat (1) ***** error burrstat (1, 2) ***** error burrstat ({}, 2, 3) ***** error burrstat (1, "", 3) ***** error burrstat (1, 2, "") ***** error burrstat (i, 2, 3) ***** error burrstat (1, i, 3) ***** error burrstat (1, 2, i) ***** error ... burrstat (ones (3), ones (2), 3) ***** error ... burrstat (ones (2), 2, ones (3)) ***** error ... burrstat (1, ones (2), ones (3)) ***** test [m, v] = burrstat (1, 2, 5); assert (m, 0.4295, 1e-4); assert (v, 0.0655, 1e-4); ***** test [m, v] = burrstat (1, 1, 1); assert (m, Inf); assert (v, Inf); ***** test [m, v] = burrstat (2, 4, 1); assert (m, 2.2214, 1e-4); assert (v, 1.3484, 1e-4); 15 tests, 15 passed, 0 known failure, 0 skipped [inst/dist_stat/binostat.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/dist_stat/binostat.m ***** error binostat () ***** error binostat (1) ***** error binostat ({}, 2) ***** error binostat (1, "") ***** error binostat (i, 2) ***** error binostat (1, i) ***** error ... binostat (ones (3), ones (2)) ***** error ... binostat (ones (2), ones (3)) ***** test n = 1:6; ps = 0:0.2:1; [m, v] = binostat (n, ps); expected_m = [0.00, 0.40, 1.20, 2.40, 4.00, 6.00]; expected_v = [0.00, 0.32, 0.72, 0.96, 0.80, 0.00]; assert (m, expected_m, 0.001); assert (v, expected_v, 0.001); ***** test n = 1:6; [m, v] = binostat (n, 0.5); expected_m = [0.50, 1.00, 1.50, 2.00, 2.50, 3.00]; expected_v = [0.25, 0.50, 0.75, 1.00, 1.25, 1.50]; assert (m, expected_m, 0.001); assert (v, expected_v, 0.001); ***** test n = [-Inf -3 5 0.5 3 NaN 100, Inf]; [m, v] = binostat (n, 0.5); assert (isnan (m), [true true false true false true false false]) assert (isnan (v), [true true false true false true false false]) assert (m(end), Inf); assert (v(end), Inf); ***** assert (nthargout (1:2, @binostat, 5, []), {[], []}) ***** assert (nthargout (1:2, @binostat, [], 5), {[], []}) ***** assert (size (binostat (randi (100, 10, 5, 4), rand (10, 5, 4))), [10 5 4]) ***** assert (size (binostat (randi (100, 10, 5, 4), 7)), [10 5 4]) 15 tests, 15 passed, 0 known failure, 0 skipped [inst/dist_stat/raylstat.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/dist_stat/raylstat.m ***** error raylstat () ***** error raylstat ({}) ***** error raylstat ("") ***** error raylstat (i) ***** test sigma = 1:6; [m, v] = raylstat (sigma); expected_m = [1.2533, 2.5066, 3.7599, 5.0133, 6.2666, 7.5199]; expected_v = [0.4292, 1.7168, 3.8628, 6.8673, 10.7301, 15.4513]; assert (m, expected_m, 0.001); assert (v, expected_v, 0.001); 5 tests, 5 passed, 0 known failure, 0 skipped [inst/dist_stat/gevstat.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/dist_stat/gevstat.m ***** error gevstat () ***** error gevstat (1) ***** error gevstat (1, 2) ***** error gevstat ({}, 2, 3) ***** error gevstat (1, "", 3) ***** error gevstat (1, 2, "") ***** error gevstat (i, 2, 3) ***** error gevstat (1, i, 3) ***** error gevstat (1, 2, i) ***** error ... gevstat (ones (3), ones (2), 3) ***** error ... gevstat (ones (2), 2, ones (3)) ***** error ... gevstat (1, ones (2), ones (3)) ***** test k = [-1, -0.5, 0, 0.2, 0.4, 0.5, 1]; sigma = 2; mu = 1; [m, v] = gevstat (k, sigma, mu); expected_m = [1, 1.4551, 2.1544, 2.6423, 3.4460, 4.0898, Inf]; expected_v = [4, 3.4336, 6.5797, 13.3761, 59.3288, Inf, Inf]; assert (m, expected_m, -0.001); assert (v, expected_v, -0.001); 13 tests, 13 passed, 0 known failure, 0 skipped [inst/dist_stat/hygestat.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/dist_stat/hygestat.m ***** error hygestat () ***** error hygestat (1) ***** error hygestat (1, 2) ***** error hygestat ({}, 2, 3) ***** error hygestat (1, "", 3) ***** error hygestat (1, 2, "") ***** error hygestat (i, 2, 3) ***** error hygestat (1, i, 3) ***** error hygestat (1, 2, i) ***** error ... hygestat (ones (3), ones (2), 3) ***** error ... hygestat (ones (2), 2, ones (3)) ***** error ... hygestat (1, ones (2), ones (3)) ***** test m = 4:9; k = 0:5; n = 1:6; [mn, v] = hygestat (m, k, n); expected_mn = [0.0000, 0.4000, 1.0000, 1.7143, 2.5000, 3.3333]; expected_v = [0.0000, 0.2400, 0.4000, 0.4898, 0.5357, 0.5556]; assert (mn, expected_mn, 0.001); assert (v, expected_v, 0.001); ***** test m = 4:9; k = 0:5; [mn, v] = hygestat (m, k, 2); expected_mn = [0.0000, 0.4000, 0.6667, 0.8571, 1.0000, 1.1111]; expected_v = [0.0000, 0.2400, 0.3556, 0.4082, 0.4286, 0.4321]; assert (mn, expected_mn, 0.001); assert (v, expected_v, 0.001); 14 tests, 14 passed, 0 known failure, 0 skipped [inst/dist_stat/loglstat.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/dist_stat/loglstat.m ***** error loglstat () ***** error loglstat (1) ***** error loglstat ({}, 2) ***** error loglstat (1, "") ***** error loglstat (i, 2) ***** error loglstat (1, i) ***** error ... loglstat (ones (3), ones (2)) ***** error ... loglstat (ones (2), ones (3)) ***** test [m, v] = loglstat (0, 1); assert (m, Inf, 0.001); assert (v, Inf, 0.001); ***** test [m, v] = loglstat (0, 0.8); assert (m, 4.2758, 0.001); assert (v, Inf, 0.001); ***** test [m, v] = loglstat (0, 0.6); assert (m, 1.9820, 0.001); assert (v, Inf, 0.001); ***** test [m, v] = loglstat (0, 0.4); assert (m, 1.3213, 0.001); assert (v, 2.5300, 0.001); ***** test [m, v] = loglstat (0, 0.2); assert (m, 1.0690, 0.001); assert (v, 0.1786, 0.001); 13 tests, 13 passed, 0 known failure, 0 skipped [inst/dist_stat/unifstat.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/dist_stat/unifstat.m ***** error unifstat () ***** error unifstat (1) ***** error unifstat ({}, 2) ***** error unifstat (1, "") ***** error unifstat (i, 2) ***** error unifstat (1, i) ***** error ... unifstat (ones (3), ones (2)) ***** error ... unifstat (ones (2), ones (3)) ***** test a = 1:6; b = 2:2:12; [m, v] = unifstat (a, b); expected_m = [1.5000, 3.0000, 4.5000, 6.0000, 7.5000, 9.0000]; expected_v = [0.0833, 0.3333, 0.7500, 1.3333, 2.0833, 3.0000]; assert (m, expected_m, 0.001); assert (v, expected_v, 0.001); ***** test a = 1:6; [m, v] = unifstat (a, 10); expected_m = [5.5000, 6.0000, 6.5000, 7.0000, 7.5000, 8.0000]; expected_v = [6.7500, 5.3333, 4.0833, 3.0000, 2.0833, 1.3333]; assert (m, expected_m, 0.001); assert (v, expected_v, 0.001); 10 tests, 10 passed, 0 known failure, 0 skipped [inst/dist_stat/nctstat.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/dist_stat/nctstat.m ***** error nctstat () ***** error nctstat (1) ***** error nctstat ({}, 2) ***** error nctstat (1, "") ***** error nctstat (i, 2) ***** error nctstat (1, i) ***** error ... nctstat (ones (3), ones (2)) ***** error ... nctstat (ones (2), ones (3)) ***** shared df, mu df = [2, 0, -1, 1, 4]; mu = [1, NaN, 3, -1, 2]; ***** assert (nctstat (df, mu), [1.7725, NaN, NaN, NaN, 2.5066], 1e-4); ***** assert (nctstat ([df(1:2), df(4:5)], 1), [1.7725, NaN, NaN, 1.2533], 1e-4); ***** assert (nctstat ([df(1:2), df(4:5)], 3), [5.3174, NaN, NaN, 3.7599], 1e-4); ***** assert (nctstat ([df(1:2), df(4:5)], 2), [3.5449, NaN, NaN, 2.5066], 1e-4); ***** assert (nctstat (2, [mu(1), mu(3:5)]), [1.7725,5.3174,-1.7725,3.5449], 1e-4); ***** assert (nctstat (0, [mu(1), mu(3:5)]), [NaN, NaN, NaN, NaN]); ***** assert (nctstat (1, [mu(1), mu(3:5)]), [NaN, NaN, NaN, NaN]); ***** assert (nctstat (4, [mu(1), mu(3:5)]), [1.2533,3.7599,-1.2533,2.5066], 1e-4); 16 tests, 16 passed, 0 known failure, 0 skipped [inst/dist_stat/ncx2stat.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/dist_stat/ncx2stat.m ***** error ncx2stat () ***** error ncx2stat (1) ***** error ncx2stat ({}, 2) ***** error ncx2stat (1, "") ***** error ncx2stat (i, 2) ***** error ncx2stat (1, i) ***** error ... ncx2stat (ones (3), ones (2)) ***** error ... ncx2stat (ones (2), ones (3)) ***** shared df, d1 df = [2, 0, -1, 1, 4]; d1 = [1, NaN, 3, -1, 2]; ***** assert (ncx2stat (df, d1), [3, NaN, NaN, NaN, 6]); ***** assert (ncx2stat ([df(1:2), df(4:5)], 1), [3, NaN, 2, 5]); ***** assert (ncx2stat ([df(1:2), df(4:5)], 3), [5, NaN, 4, 7]); ***** assert (ncx2stat ([df(1:2), df(4:5)], 2), [4, NaN, 3, 6]); ***** assert (ncx2stat (2, [d1(1), d1(3:5)]), [3, 5, NaN, 4]); ***** assert (ncx2stat (0, [d1(1), d1(3:5)]), [NaN, NaN, NaN, NaN]); ***** assert (ncx2stat (1, [d1(1), d1(3:5)]), [2, 4, NaN, 3]); ***** assert (ncx2stat (4, [d1(1), d1(3:5)]), [5, 7, NaN, 6]); 16 tests, 16 passed, 0 known failure, 0 skipped [inst/dist_stat/ricestat.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/dist_stat/ricestat.m ***** error ricestat () ***** error ricestat (1) ***** error ricestat ({}, 2) ***** error ricestat (1, "") ***** error ricestat (i, 2) ***** error ricestat (1, i) ***** error ... ricestat (ones (3), ones (2)) ***** error ... ricestat (ones (2), ones (3)) ***** shared s, sigma s = [2, 0, -1, 1, 4]; sigma = [1, NaN, 3, -1, 2]; ***** assert (ricestat (s, sigma), [2.2724, NaN, NaN, NaN, 4.5448], 1e-4); ***** assert (ricestat ([s(1:2), s(4:5)], 1), [2.2724, 1.2533, 1.5486, 4.1272], 1e-4); ***** assert (ricestat ([s(1:2), s(4:5)], 3), [4.1665, 3.7599, 3.8637, 5.2695], 1e-4); ***** assert (ricestat ([s(1:2), s(4:5)], 2), [3.0971, 2.5066, 2.6609, 4.5448], 1e-4); ***** assert (ricestat (2, [sigma(1), sigma(3:5)]), [2.2724, 4.1665, NaN, 3.0971], 1e-4); ***** assert (ricestat (0, [sigma(1), sigma(3:5)]), [1.2533, 3.7599, NaN, 2.5066], 1e-4); ***** assert (ricestat (1, [sigma(1), sigma(3:5)]), [1.5486, 3.8637, NaN, 2.6609], 1e-4); ***** assert (ricestat (4, [sigma(1), sigma(3:5)]), [4.1272, 5.2695, NaN, 4.5448], 1e-4); 16 tests, 16 passed, 0 known failure, 0 skipped [inst/dist_stat/fstat.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/dist_stat/fstat.m ***** error fstat () ***** error fstat (1) ***** error fstat ({}, 2) ***** error fstat (1, "") ***** error fstat (i, 2) ***** error fstat (1, i) ***** error ... fstat (ones (3), ones (2)) ***** error ... fstat (ones (2), ones (3)) ***** test df1 = 1:6; df2 = 5:10; [m, v] = fstat (df1, df2); expected_mn = [1.6667, 1.5000, 1.4000, 1.3333, 1.2857, 1.2500]; expected_v = [22.2222, 6.7500, 3.4844, 2.2222, 1.5869, 1.2153]; assert (m, expected_mn, 0.001); assert (v, expected_v, 0.001); ***** test df1 = 1:6; [m, v] = fstat (df1, 5); expected_mn = [1.6667, 1.6667, 1.6667, 1.6667, 1.6667, 1.6667]; expected_v = [22.2222, 13.8889, 11.1111, 9.7222, 8.8889, 8.3333]; assert (m, expected_mn, 0.001); assert (v, expected_v, 0.001); 10 tests, 10 passed, 0 known failure, 0 skipped [inst/dist_stat/expstat.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/dist_stat/expstat.m ***** error expstat () ***** error expstat ({}) ***** error expstat ("") ***** error expstat (i) ***** test mu = 1:6; [m, v] = expstat (mu); assert (m, [1, 2, 3, 4, 5, 6], 0.001); assert (v, [1, 4, 9, 16, 25, 36], 0.001); 5 tests, 5 passed, 0 known failure, 0 skipped [inst/dist_stat/ncfstat.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/dist_stat/ncfstat.m ***** error ncfstat () ***** error ncfstat (1) ***** error ncfstat (1, 2) ***** error ncfstat ({}, 2, 3) ***** error ncfstat (1, "", 3) ***** error ncfstat (1, 2, "") ***** error ncfstat (i, 2, 3) ***** error ncfstat (1, i, 3) ***** error ncfstat (1, 2, i) ***** error ... ncfstat (ones (3), ones (2), 3) ***** error ... ncfstat (ones (2), 2, ones (3)) ***** error ... ncfstat (1, ones (2), ones (3)) ***** shared df1, df2, lambda df1 = [2, 0, -1, 1, 4, 5]; df2 = [2, 4, -1, 5, 6, 7]; lambda = [1, NaN, 3, 0, 2, -1]; ***** assert (ncfstat (df1, df2, lambda), [NaN, NaN, NaN, 1.6667, 2.25, 1.12], 1e-4); ***** assert (ncfstat (df1(4:6), df2(4:6), 1), [3.3333, 1.8750, 1.6800], 1e-4); ***** assert (ncfstat (df1(4:6), df2(4:6), 2), [5.0000, 2.2500, 1.9600], 1e-4); ***** assert (ncfstat (df1(4:6), df2(4:6), 3), [6.6667, 2.6250, 2.2400], 1e-4); ***** assert (ncfstat (2, [df2(1), df2(4:6)], 5), [NaN,5.8333,5.2500,4.9000], 1e-4); ***** assert (ncfstat (0, [df2(1), df2(4:6)], 5), [NaN, Inf, Inf, Inf]); ***** assert (ncfstat (1, [df2(1), df2(4:6)], 5), [NaN, 10, 9, 8.4], 1e-14); ***** assert (ncfstat (4, [df2(1), df2(4:6)], 5), [NaN, 3.75, 3.375, 3.15], 1e-14); 20 tests, 20 passed, 0 known failure, 0 skipped [inst/dist_stat/geostat.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/dist_stat/geostat.m ***** error geostat () ***** error geostat ({}) ***** error geostat ("") ***** error geostat (i) ***** test ps = 1 ./ (1:6); [m, v] = geostat (ps); assert (m, [0, 1, 2, 3, 4, 5], 0.001); assert (v, [0, 2, 6, 12, 20, 30], 0.001); 5 tests, 5 passed, 0 known failure, 0 skipped [inst/dist_stat/normstat.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/dist_stat/normstat.m ***** error normstat () ***** error normstat (1) ***** error normstat ({}, 2) ***** error normstat (1, "") ***** error normstat (i, 2) ***** error normstat (1, i) ***** error ... normstat (ones (3), ones (2)) ***** error ... normstat (ones (2), ones (3)) ***** test mu = 1:6; sigma = 0.2:0.2:1.2; [m, v] = normstat (mu, sigma); expected_v = [0.0400, 0.1600, 0.3600, 0.6400, 1.0000, 1.4400]; assert (m, mu); assert (v, expected_v, 0.001); ***** test sigma = 0.2:0.2:1.2; [m, v] = normstat (0, sigma); expected_mn = [0, 0, 0, 0, 0, 0]; expected_v = [0.0400, 0.1600, 0.3600, 0.6400, 1.0000, 1.4400]; assert (m, expected_mn, 0.001); assert (v, expected_v, 0.001); 10 tests, 10 passed, 0 known failure, 0 skipped [inst/dist_stat/chi2stat.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/dist_stat/chi2stat.m ***** error chi2stat () ***** error chi2stat ({}) ***** error chi2stat ("") ***** error chi2stat (i) ***** test df = 1:6; [m, v] = chi2stat (df); assert (m, df); assert (v, [2, 4, 6, 8, 10, 12], 0.001); 5 tests, 5 passed, 0 known failure, 0 skipped [inst/dist_stat/gamstat.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/dist_stat/gamstat.m ***** error gamstat () ***** error gamstat (1) ***** error gamstat ({}, 2) ***** error gamstat (1, "") ***** error gamstat (i, 2) ***** error gamstat (1, i) ***** error ... gamstat (ones (3), ones (2)) ***** error ... gamstat (ones (2), ones (3)) ***** test a = 1:6; b = 1:0.2:2; [m, v] = gamstat (a, b); expected_m = [1.00, 2.40, 4.20, 6.40, 9.00, 12.00]; expected_v = [1.00, 2.88, 5.88, 10.24, 16.20, 24.00]; assert (m, expected_m, 0.001); assert (v, expected_v, 0.001); ***** test a = 1:6; [m, v] = gamstat (a, 1.5); expected_m = [1.50, 3.00, 4.50, 6.00, 7.50, 9.00]; expected_v = [2.25, 4.50, 6.75, 9.00, 11.25, 13.50]; assert (m, expected_m, 0.001); assert (v, expected_v, 0.001); 10 tests, 10 passed, 0 known failure, 0 skipped [inst/dist_stat/nakastat.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/dist_stat/nakastat.m ***** error nakastat () ***** error nakastat (1) ***** error nakastat ({}, 2) ***** error nakastat (1, "") ***** error nakastat (i, 2) ***** error nakastat (1, i) ***** error ... nakastat (ones (3), ones (2)) ***** error ... nakastat (ones (2), ones (3)) ***** test [m, v] = nakastat (1, 1); assert (m, 0.8862269254, 1e-10); assert (v, 0.2146018366, 1e-10); ***** test [m, v] = nakastat (1, 2); assert (m, 1.25331413731, 1e-10); assert (v, 0.42920367321, 1e-10); ***** test [m, v] = nakastat (2, 1); assert (m, 0.93998560299, 1e-10); assert (v, 0.11642706618, 1e-10); 11 tests, 11 passed, 0 known failure, 0 skipped [inst/dist_stat/logistat.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/dist_stat/logistat.m ***** error logistat () ***** error logistat (1) ***** error logistat ({}, 2) ***** error logistat (1, "") ***** error logistat (i, 2) ***** error logistat (1, i) ***** error ... logistat (ones (3), ones (2)) ***** error ... logistat (ones (2), ones (3)) ***** test [m, v] = logistat (0, 1); assert (m, 0); assert (v, 3.2899, 0.001); ***** test [m, v] = logistat (0, 0.8); assert (m, 0); assert (v, 2.1055, 0.001); ***** test [m, v] = logistat (1, 0.6); assert (m, 1); assert (v, 1.1844, 0.001); ***** test [m, v] = logistat (0, 0.4); assert (m, 0); assert (v, 0.5264, 0.001); ***** test [m, v] = logistat (-1, 0.2); assert (m, -1); assert (v, 0.1316, 0.001); 13 tests, 13 passed, 0 known failure, 0 skipped [inst/dist_stat/tstat.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/dist_stat/tstat.m ***** error tstat () ***** error tstat ({}) ***** error tstat ("") ***** error tstat (i) ***** test df = 3:8; [m, v] = tstat (df); expected_m = [0, 0, 0, 0, 0, 0]; expected_v = [3.0000, 2.0000, 1.6667, 1.5000, 1.4000, 1.3333]; assert (m, expected_m); assert (v, expected_v, 0.001); 5 tests, 5 passed, 0 known failure, 0 skipped [inst/dist_stat/tlsstat.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/dist_stat/tlsstat.m ***** error tlsstat () ***** error tlsstat (1) ***** error tlsstat (1, 2) ***** error tlsstat ({}, 2, 3) ***** error tlsstat (1, "", 3) ***** error tlsstat (1, 2, ["d"]) ***** error tlsstat (i, 2, 3) ***** error tlsstat (1, i, 3) ***** error tlsstat (1, 2, i) ***** error ... tlsstat (ones (3), ones (2), 1) ***** error ... tlsstat (ones (2), 1, ones (3)) ***** error ... tlsstat (1, ones (2), ones (3)) ***** test [m, v] = tlsstat (0, 1, 0); assert (m, NaN); assert (v, NaN); ***** test [m, v] = tlsstat (0, 1, 1); assert (m, NaN); assert (v, NaN); ***** test [m, v] = tlsstat (2, 1, 1); assert (m, NaN); assert (v, NaN); ***** test [m, v] = tlsstat (-2, 1, 1); assert (m, NaN); assert (v, NaN); ***** test [m, v] = tlsstat (0, 1, 2); assert (m, 0); assert (v, NaN); ***** test [m, v] = tlsstat (2, 1, 2); assert (m, 2); assert (v, NaN); ***** test [m, v] = tlsstat (-2, 1, 2); assert (m, -2); assert (v, NaN); ***** test [m, v] = tlsstat (0, 2, 2); assert (m, 0); assert (v, NaN); ***** test [m, v] = tlsstat (2, 2, 2); assert (m, 2); assert (v, NaN); ***** test [m, v] = tlsstat (-2, 2, 2); assert (m, -2); assert (v, NaN); ***** test [m, v] = tlsstat (0, 1, 3); assert (m, 0); assert (v, 3); ***** test [m, v] = tlsstat (0, 2, 3); assert (m, 0); assert (v, 6); ***** test [m, v] = tlsstat (2, 1, 3); assert (m, 2); assert (v, 3); ***** test [m, v] = tlsstat (2, 2, 3); assert (m, 2); assert (v, 6); ***** test [m, v] = tlsstat (-2, 1, 3); assert (m, -2); assert (v, 3); ***** test [m, v] = tlsstat (-2, 2, 3); assert (m, -2); assert (v, 6); 28 tests, 28 passed, 0 known failure, 0 skipped [inst/dist_stat/bisastat.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/dist_stat/bisastat.m ***** error bisastat () ***** error bisastat (1) ***** error bisastat ({}, 2) ***** error bisastat (1, "") ***** error bisastat (i, 2) ***** error bisastat (1, i) ***** error ... bisastat (ones (3), ones (2)) ***** error ... bisastat (ones (2), ones (3)) ***** test beta = 1:6; gamma = 1:0.2:2; [m, v] = bisastat (beta, gamma); expected_m = [1.50, 3.44, 5.94, 9.12, 13.10, 18]; expected_v = [2.25, 16.128, 60.858, 172.032, 409.050, 864]; assert (m, expected_m, 1e-2); assert (v, expected_v, 1e-3); ***** test beta = 1:6; [m, v] = bisastat (beta, 1.5); expected_m = [2.125, 4.25, 6.375, 8.5, 10.625, 12.75]; expected_v = [8.5781, 34.3125, 77.2031, 137.2500, 214.4531, 308.8125]; assert (m, expected_m, 1e-3); assert (v, expected_v, 1e-4); 10 tests, 10 passed, 0 known failure, 0 skipped [inst/dist_stat/plstat.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/dist_stat/plstat.m ***** shared x, Fx x = [0, 1, 3, 4, 7, 10]; Fx = [0, 0.2, 0.5, 0.6, 0.7, 1]; ***** assert (plstat (x, Fx), 4.15) ***** test [m, v] = plstat (x, Fx); assert (v, 10.3775, 1e-14) ***** error plstat () ***** error plstat (1) ***** error ... plstat ([0, 1, 2], [0, 1]) ***** error ... plstat ([0], [1]) ***** error ... plstat ([0, 1, 2], [0, 1, 1.5]) ***** error ... plstat ([0, 1, 2], [0, i, 1]) ***** error ... plstat ([0, i, 2], [0, 0.5, 1]) ***** error ... plstat ([0, i, 2], [0, 0.5i, 1]) 10 tests, 10 passed, 0 known failure, 0 skipped [inst/dist_stat/tristat.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/dist_stat/tristat.m ***** error tristat () ***** error tristat (1) ***** error tristat (1, 2) ***** error tristat ("i", 2, 1) ***** error tristat (0, "d", 1) ***** error tristat (0, 3, {}) ***** error tristat (i, 2, 1) ***** error tristat (0, i, 1) ***** error tristat (0, 3, i) ***** test a = 1:5; b = 3:7; c = 5:9; [m, v] = tristat (a, b, c); expected_m = [3, 4, 5, 6, 7]; assert (m, expected_m); assert (v, ones (1, 5) * (2/3)); 10 tests, 10 passed, 0 known failure, 0 skipped [inst/dist_stat/lognstat.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/dist_stat/lognstat.m ***** error lognstat () ***** error lognstat (1) ***** error lognstat ({}, 2) ***** error lognstat (1, "") ***** error lognstat (i, 2) ***** error lognstat (1, i) ***** error ... lognstat (ones (3), ones (2)) ***** error ... lognstat (ones (2), ones (3)) ***** test mu = 0:0.2:1; sigma = 0.2:0.2:1.2; [m, v] = lognstat (mu, sigma); expected_m = [1.0202, 1.3231, 1.7860, 2.5093, 3.6693, 5.5845]; expected_v = [0.0425, 0.3038, 1.3823, 5.6447, 23.1345, 100.4437]; assert (m, expected_m, 0.001); assert (v, expected_v, 0.001); ***** test sigma = 0.2:0.2:1.2; [m, v] = lognstat (0, sigma); expected_m = [1.0202, 1.0833, 1.1972, 1.3771, 1.6487, 2.0544]; expected_v = [0.0425, 0.2036, 0.6211, 1.7002, 4.6708, 13.5936]; assert (m, expected_m, 0.001); assert (v, expected_v, 0.001); 10 tests, 10 passed, 0 known failure, 0 skipped [inst/silhouette.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/silhouette.m ***** demo load fisheriris; X = meas(:,3:4); cidcs = kmeans (X, 3, "Replicates", 5); silhouette (X, cidcs); y_labels(cidcs([1 51 101])) = unique (species); set (gca, "yticklabel", y_labels); title ("Fisher's iris data"); ***** error silhouette (); ***** error silhouette ([1 2; 1 1]); ***** error silhouette ([1 2; 1 1], [1 2 3]'); ***** error silhouette ([1 2; 1 1], [1 2]', "xxx"); 4 tests, 4 passed, 0 known failure, 0 skipped [inst/ridge.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/ridge.m ***** demo ## Perform ridge regression for a range of ridge parameters and observe ## how the coefficient estimates change based on the acetylene dataset. load acetylene X = [x1, x2, x3]; x1x2 = x1 .* x2; x1x3 = x1 .* x3; x2x3 = x2 .* x3; D = [x1, x2, x3, x1x2, x1x3, x2x3]; k = 0:1e-5:5e-3; b = ridge (y, D, k); figure plot (k, b, "LineWidth", 2) ylim ([-100, 100]) grid on xlabel ("Ridge Parameter") ylabel ("Standardized Coefficient") title ("Ridge Trace") legend ("x1", "x2", "x3", "x1x2", "x1x3", "x2x3") ***** demo load carbig X = [Acceleration Weight Displacement Horsepower]; y = MPG; n = length(y); rand("seed",1); % For reproducibility c = cvpartition(n,'HoldOut',0.3); idxTrain = training(c,1); idxTest = ~idxTrain; idxTrain = training(c,1); idxTest = ~idxTrain; k = 5; b = ridge(y(idxTrain),X(idxTrain,:),k,0); % Predict MPG values for the test data using the model. yhat = b(1) + X(idxTest,:)*b(2:end); scatter(y(idxTest),yhat) hold on plot(y(idxTest),y(idxTest),"r") xlabel('Actual MPG') ylabel('Predicted MPG') hold off ***** test b = ridge ([1 2 3 4]', [1 2 3 4; 2 3 4 5]', 1); assert (b, [0.5533; 0.5533], 1e-4); ***** test b = ridge ([1 2 3 4]', [1 2 3 4; 2 3 4 5]', 2); assert (b, [0.4841; 0.4841], 1e-4); ***** test load acetylene x = [x1, x2, x3]; b = ridge (y, x, 0); assert (b,[10.2273;1.97128;-0.601818],1e-4); ***** test load acetylene x = [x1, x2, x3]; b = ridge (y, x, 0.0005); assert (b,[10.2233;1.9712;-0.6056],1e-4); ***** test load acetylene x = [x1, x2, x3]; b = ridge (y, x, 0.001); assert (b,[10.2194;1.9711;-0.6094],1e-4); ***** test load acetylene x = [x1, x2, x3]; b = ridge (y, x, 0.002); assert (b,[10.2116;1.9709;-0.6169],1e-4); ***** test load acetylene x = [x1, x2, x3]; b = ridge (y, x, 0.005); assert (b,[10.1882;1.9704;-0.6393],1e-4); ***** test load acetylene x = [x1, x2, x3]; b = ridge (y, x, 0.01); assert (b,[10.1497;1.9695;-0.6761],1e-4); ***** error ridge (1) ***** error ridge (1, 2) ***** error ridge (ones (3), ones (3), 2) ***** error ridge ([1, 2], ones (2), 2) ***** error ridge ([], ones (3), 2) ***** error ridge (ones (5,1), [], 2) ***** error ... ridge ([1; 2; 3; 4; 5], ones (3), 3) ***** error ... ridge ([1; 2; 3], ones (3), 3, 2) ***** error ... ridge ([1; 2; 3], ones (3), 3, "some") 17 tests, 17 passed, 0 known failure, 0 skipped [inst/mnrfit.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/mnrfit.m ***** error mnrfit (ones (50,1)) ***** error ... mnrfit ({1 ;2 ;3 ;4 ;5}, ones (5,1)) ***** error ... mnrfit (ones (50, 4, 2), ones (50, 1)) ***** error ... mnrfit (ones (50, 4), ones (50, 1, 3)) ***** error ... mnrfit (ones (50, 4), ones (45,1)) ***** error ... mnrfit (ones (5, 4), {1 ;2 ;3 ;4 ;5}) ***** error ... mnrfit (ones (5, 4), ones (5, 1), "model") ***** error ... mnrfit (ones (5, 4), {"q","q";"w","w";"q","q";"w","w";"q","q"}) ***** error ... mnrfit (ones (5, 4), [1, 2; 1, 2; 1, 2; 1, 2; 1, 2]) ***** error ... mnrfit (ones (5, 4), [1; -1; 1; 2; 1]) ***** error ... mnrfit (ones (5, 4), [1; 2; 3; 2; 1], "model", "nominal") ***** error ... mnrfit (ones (5, 4), [1; 2; 3; 2; 1], "model", "hierarchical") ***** error ... mnrfit (ones (5, 4), [1; 2; 3; 2; 1], "model", "whatever") 13 tests, 13 passed, 0 known failure, 0 skipped [inst/pcares.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/pcares.m ***** demo x = [ 7 26 6 60; 1 29 15 52; 11 56 8 20; 11 31 8 47; 7 52 6 33; 11 55 9 22; 3 71 17 6; 1 31 22 44; 2 54 18 22; 21 47 4 26; 1 40 23 34; 11 66 9 12; 10 68 8 12]; ## As we increase the number of principal components, the norm ## of the residuals matrix will decrease r1 = pcares (x,1); n1 = norm (r1) r2 = pcares (x,2); n2 = norm (r2) r3 = pcares (x,3); n3 = norm (r3) r4 = pcares (x,4); n4 = norm (r4) ***** test load hald r1 = pcares (ingredients,1); r2 = pcares (ingredients,2); r3 = pcares (ingredients,3); assert (r1(1,:), [2.0350, 2.8304, -6.8378, 3.0879], 1e-4); assert (r2(1,:), [-2.4037, 2.6930, -1.6482, 2.3425], 1e-4); assert (r3(1,:), [ 0.2008, 0.1957, 0.2045, 0.1921], 1e-4); ***** error pcares (ones (20, 3)) ***** error ... pcares (ones (30, 2), 3) 3 tests, 3 passed, 0 known failure, 0 skipped [inst/hmmgenerate.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/hmmgenerate.m ***** test len = 25; transprob = [0.8, 0.2; 0.4, 0.6]; outprob = [0.2, 0.4, 0.4; 0.7, 0.2, 0.1]; [sequence, states] = hmmgenerate (len, transprob, outprob); assert (length (sequence), len); assert (length (states), len); assert (min (sequence) >= 1); assert (max (sequence) <= columns (outprob)); assert (min (states) >= 1); assert (max (states) <= rows (transprob)); ***** test len = 25; transprob = [0.8, 0.2; 0.4, 0.6]; outprob = [0.2, 0.4, 0.4; 0.7, 0.2, 0.1]; symbols = {"A", "B", "C"}; statenames = {"One", "Two"}; [sequence, states] = hmmgenerate (len, transprob, outprob, ... "symbols", symbols, "statenames", statenames); assert (length (sequence), len); assert (length (states), len); assert (strcmp (sequence, "A") + strcmp (sequence, "B") + ... strcmp (sequence, "C") == ones (1, len)); assert (strcmp (states, "One") + strcmp (states, "Two") == ones (1, len)); 2 tests, 2 passed, 0 known failure, 0 skipped [inst/sigma_pts.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/sigma_pts.m ***** demo K = [1 0.5; 0.5 1]; # covaraince matrix # calculate and build associated ellipse [R,S,~] = svd (K); theta = atan2 (R(2,1), R(1,1)); v = sqrt (diag (S)); v = v .* [cos(theta) sin(theta); -sin(theta) cos(theta)]; t = linspace (0, 2*pi, 100).'; xe = v(1,1) * cos (t) + v(2,1) * sin (t); ye = v(1,2) * cos (t) + v(2,2) * sin (t); figure(1); clf; hold on # Plot ellipse and axes line ([0 0; v(:,1).'],[0 0; v(:,2).']) plot (xe,ye,'-r'); col = 'rgb'; l = [-1.8 -1 1.5]; for li = 1:3 p = sigma_pts (2, [], K, l(li)); tmp = plot (p(2:end,1), p(2:end,2), ['x' col(li)], ... p(1,1), p(1,2), ['o' col(li)]); h(li) = tmp(1); endfor hold off axis image legend (h, arrayfun (@(x) sprintf ("l:%.2g", x), l, "unif", 0)); ***** test p = sigma_pts (5); assert (mean (p), zeros(1,5), sqrt(eps)); assert (cov (p), eye(5), sqrt(eps)); ***** test m = randn(1, 5); p = sigma_pts (5, m); assert (mean (p), m, sqrt(eps)); assert (cov (p), eye(5), sqrt(eps)); ***** test x = linspace (0,1,5); K = exp (- (x.' - x).^2/ 0.5); p = sigma_pts (5, [], K); assert (mean (p), zeros(1,5), sqrt(eps)); assert (cov (p), K, sqrt(eps)); ***** error sigma_pts(2,1); ***** error sigma_pts(2,[],1); ***** error sigma_pts(2,1,1); ***** error sigma_pts(2,[0.5 0.5],[-1 0; 0 0]); 7 tests, 7 passed, 0 known failure, 0 skipped [inst/manovacluster.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/manovacluster.m ***** demo load carbig X = [MPG Acceleration Weight Displacement]; [d, p, stats] = manova1 (X, Origin); manovacluster (stats) ***** test hf = figure ("visible", "off"); unwind_protect load carbig X = [MPG Acceleration Weight Displacement]; [d, p, stats] = manova1 (X, Origin); manovacluster (stats); unwind_protect_cleanup close (hf); end_unwind_protect ***** error manovacluster (stats, "some"); 2 tests, 2 passed, 0 known failure, 0 skipped [inst/dist_fit/binolike.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/dist_fit/binolike.m ***** assert (binolike ([3, 0.333], [0:3]), 6.8302, 1e-4) ***** assert (binolike ([3, 0.333], 0), 1.2149, 1e-4) ***** assert (binolike ([3, 0.333], 1), 0.8109, 1e-4) ***** assert (binolike ([3, 0.333], 2), 1.5056, 1e-4) ***** assert (binolike ([3, 0.333], 3), 3.2988, 1e-4) ***** test [nlogL, acov] = binolike ([3, 0.333], 3); assert (acov(4), 0.0740, 1e-4) ***** error binolike (3.25) ***** error binolike ([5, 0.2], ones (2)) ***** error ... binolike ([1, 0.2, 3], [1, 3, 5, 7]) ***** error binolike ([1.5, 0.2], 1) ***** error binolike ([-1, 0.2], 1) ***** error binolike ([Inf, 0.2], 1) ***** error binolike ([5, 1.2], [3, 5]) ***** error binolike ([5, -0.2], [3, 5]) ***** error ... binolike ([5, 0.5], ones (10, 1), ones (8,1)) ***** error ... binolike ([5, 0.5], ones (1, 8), [1 1 1 1 1 1 1 -1]) ***** error binolike ([5, 0.2], [-1, 3]) ***** error binolike ([5, 0.2], [3, 5, 7]) 18 tests, 18 passed, 0 known failure, 0 skipped [inst/dist_fit/evfit.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/dist_fit/evfit.m ***** demo ## Sample 3 populations from different extreme value distibutions rand ("seed", 1); # for reproducibility r1 = evrnd (2, 5, 400, 1); rand ("seed", 12); # for reproducibility r2 = evrnd (-5, 3, 400, 1); rand ("seed", 13); # for reproducibility r3 = evrnd (14, 8, 400, 1); r = [r1, r2, r3]; ## Plot them normalized and fix their colors hist (r, 25, 0.4); h = findobj (gca, "Type", "patch"); set (h(1), "facecolor", "c"); set (h(2), "facecolor", "g"); set (h(3), "facecolor", "r"); ylim ([0, 0.28]) xlim ([-30, 30]); hold on ## Estimate their MU and SIGMA parameters mu_sigmaA = evfit (r(:,1)); mu_sigmaB = evfit (r(:,2)); mu_sigmaC = evfit (r(:,3)); ## Plot their estimated PDFs x = [min(r(:)):max(r(:))]; y = evpdf (x, mu_sigmaA(1), mu_sigmaA(2)); plot (x, y, "-pr"); y = evpdf (x, mu_sigmaB(1), mu_sigmaB(2)); plot (x, y, "-sg"); y = evpdf (x, mu_sigmaC(1), mu_sigmaC(2)); plot (x, y, "-^c"); legend ({"Normalized HIST of sample 1 with μ=2 and σ=5", ... "Normalized HIST of sample 2 with μ=-5 and σ=3", ... "Normalized HIST of sample 3 with μ=14 and σ=8", ... sprintf("PDF for sample 1 with estimated μ=%0.2f and σ=%0.2f", ... mu_sigmaA(1), mu_sigmaA(2)), ... sprintf("PDF for sample 2 with estimated μ=%0.2f and σ=%0.2f", ... mu_sigmaB(1), mu_sigmaB(2)), ... sprintf("PDF for sample 3 with estimated μ=%0.2f and σ=%0.2f", ... mu_sigmaC(1), mu_sigmaC(2))}) title ("Three population samples from different extreme value distibutions") hold off ***** test x = 1:50; [paramhat, paramci] = evfit (x); paramhat_out = [32.6811, 13.0509]; paramci_out = [28.8504, 10.5294; 36.5118, 16.1763]; assert (paramhat, paramhat_out, 1e-4); assert (paramci, paramci_out, 1e-4); ***** test x = 1:50; [paramhat, paramci] = evfit (x, 0.01); paramci_out = [27.6468, 9.8426; 37.7155, 17.3051]; assert (paramci, paramci_out, 1e-4); ***** error evfit (ones (2,5)); ***** error evfit (single (ones (1,5))); ***** error evfit ([1, 2, 3, 4, NaN]); ***** error evfit ([1, 2, 3, 4, 5], 1.2); ***** error evfit ([1 2 3], 0.05, [], [1 5]) ***** error evfit ([1 2 3], 0.05, [], [1 5 -1]) ***** error ... evfit ([1:10], 0.05, [], [], 5) 9 tests, 9 passed, 0 known failure, 0 skipped [inst/dist_fit/ricelike.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/dist_fit/ricelike.m ***** test nlogL = ricelike ([15.3057344, 17.6668458], [1:50]); assert (nlogL, 204.5230311010569, 1e-12); ***** test nlogL = ricelike ([2.312346885, 1.681228265], [1:5]); assert (nlogL, 8.65562164930058, 1e-12); ***** error ricelike (3.25) ***** error ricelike ([5, 0.2], ones (2)) ***** error ... ricelike ([1, 0.2, 3], [1, 3, 5, 7]) ***** error ... ricelike ([1.5, 0.2], [1:5], [0, 0, 0]) ***** error ... ricelike ([1.5, 0.2], [1:5], [0, 0, 0, 0, 0], [1, 1, 1]) ***** error ... ricelike ([1.5, 0.2], [1:5], [], [1, 1, 1]) ***** error ... ricelike ([1.5, 0.2], [1:5], [], [1, 1, 1, 0, -1]) 9 tests, 9 passed, 0 known failure, 0 skipped [inst/dist_fit/gumbellike.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/dist_fit/gumbellike.m ***** test x = 1:50; [nlogL, avar] = gumbellike ([2.3, 1.2], x); avar_out = [-1.2778e-13, 3.1859e-15; 3.1859e-15, -7.9430e-17]; assert (nlogL, 3.242264755689906e+17, 1e-14); assert (avar, avar_out, 1e-3); ***** test x = 1:50; [nlogL, avar] = gumbellike ([2.3, 1.2], x * 0.5); avar_out = [-7.6094e-05, 3.9819e-06; 3.9819e-06, -2.0836e-07]; assert (nlogL, 481898704.0472211, 1e-6); assert (avar, avar_out, 1e-3); ***** test x = 1:50; [nlogL, avar] = gumbellike ([21, 15], x); avar_out = [11.73913876598908, -5.9546128523121216; ... -5.954612852312121, 3.708060045170236]; assert (nlogL, 223.7612479380652, 1e-13); assert (avar, avar_out, 1e-14); ***** error gumbellike ([12, 15]); ***** error gumbellike ([12, 15, 3], [1:50]); ***** error gumbellike ([12, 3], ones (10, 2)); ***** error gumbellike ([12, 15], [1:50], [1, 2, 3]); ***** error gumbellike ([12, 15], [1:50], [], [1, 2, 3]); 8 tests, 8 passed, 0 known failure, 0 skipped [inst/dist_fit/gevlike.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/dist_fit/gevlike.m ***** test x = 1; k = 0.2; sigma = 0.3; mu = 0.5; [L, C] = gevlike ([k sigma mu], x); expected_L = 0.75942; expected_C = [-0.12547 1.77884 1.06731; 1.77884 16.40761 8.48877; 1.06731 8.48877 0.27979]; assert (L, expected_L, 0.001); assert (C, inv (expected_C), 0.001); ***** test x = 1; k = 0; sigma = 0.3; mu = 0.5; [L, C] = gevlike ([k sigma mu], x); expected_L = 0.65157; expected_C = [0.090036 3.41229 2.047337; 3.412229 24.760027 12.510190; 2.047337 12.510190 2.098618]; assert (L, expected_L, 0.001); assert (C, inv (expected_C), 0.001); ***** test x = -5:-1; k = -0.2; sigma = 0.3; mu = 0.5; [L, C] = gevlike ([k sigma mu], x); expected_L = 3786.4; expected_C = [1.6802e-07, 4.6110e-06, 8.7297e-05; ... 4.6110e-06, 7.5693e-06, 1.2034e-05; ... 8.7297e-05, 1.2034e-05, -0.0019125]; assert (L, expected_L, -0.001); assert (C, expected_C, -0.001); ***** test x = -5:0; k = -0.2; sigma = 0.3; mu = 0.5; [L, C] = gevlike ([k sigma mu], x, [1, 1, 1, 1, 1, 0]); expected_L = 3786.4; expected_C = [1.6802e-07, 4.6110e-06, 8.7297e-05; ... 4.6110e-06, 7.5693e-06, 1.2034e-05; ... 8.7297e-05, 1.2034e-05, -0.0019125]; assert (L, expected_L, -0.001); assert (C, expected_C, -0.001); ***** error gevlike (3.25) ***** error gevlike ([1, 2, 3], ones (2)) ***** error ... gevlike ([1, 2], [1, 3, 5, 7]) ***** error ... gevlike ([1, 2, 3, 4], [1, 3, 5, 7]) ***** error ... gevlike ([5, 0.2, 1], ones (10, 1), ones (8,1)) ***** error ... gevlike ([5, 0.2, 1], ones (1, 8), [1 1 1 1 1 1 1 -1]) ***** error ... gevlike ([5, 0.2, 1], ones (1, 8), [1 1 1 1 1 1 1 1.5]) 11 tests, 11 passed, 0 known failure, 0 skipped [inst/dist_fit/hnlike.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/dist_fit/hnlike.m ***** test x = 1:20; paramhat = hnfit (x, 0); [nlogL, acov] = hnlike (paramhat, x); assert (nlogL, 64.179177404891300, 1e-14); ***** test x = 1:20; paramhat = hnfit (x, 0); [nlogL, acov] = hnlike (paramhat, x, ones (1, 20)); assert (nlogL, 64.179177404891300, 1e-14); ***** error ... hnlike ([12, 15]); ***** error hnlike ([12, 15, 3], [1:50]); ***** error hnlike ([3], [1:50]); ***** error ... hnlike ([0, 3], ones (2)); ***** error ... hnlike ([0, 3], [1, 2, 3, 4, 5+i]); ***** error ... hnlike ([1, 2], ones (10, 1), ones (8,1)) ***** error ... hnlike ([1, 2], ones (1, 8), [1 1 1 1 1 1 1 -1]) 9 tests, 9 passed, 0 known failure, 0 skipped [inst/dist_fit/loglfit.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/dist_fit/loglfit.m ***** demo ## Sample 3 populations from different log-logistic distibutions rand ("seed", 5) # for reproducibility r1 = loglrnd (0, 1, 2000, 1); rand ("seed", 2) # for reproducibility r2 = loglrnd (0, 0.5, 2000, 1); rand ("seed", 7) # for reproducibility r3 = loglrnd (0, 0.125, 2000, 1); r = [r1, r2, r3]; ## Plot them normalized and fix their colors hist (r, [0.05:0.1:2.5], 10); h = findobj (gca, "Type", "patch"); set (h(1), "facecolor", "c"); set (h(2), "facecolor", "g"); set (h(3), "facecolor", "r"); ylim ([0, 3.5]); xlim ([0, 2.0]); hold on ## Estimate their MU and LAMBDA parameters a_bA = loglfit (r(:,1)); a_bB = loglfit (r(:,2)); a_bC = loglfit (r(:,3)); ## Plot their estimated PDFs x = [0.01:0.1:2.01]; y = loglpdf (x, a_bA(1), a_bA(2)); plot (x, y, "-pr"); y = loglpdf (x, a_bB(1), a_bB(2)); plot (x, y, "-sg"); y = loglpdf (x, a_bC(1), a_bC(2)); plot (x, y, "-^c"); legend ({"Normalized HIST of sample 1 with α=1 and β=1", ... "Normalized HIST of sample 2 with α=1 and β=2", ... "Normalized HIST of sample 3 with α=1 and β=8", ... sprintf("PDF for sample 1 with estimated α=%0.2f and β=%0.2f", ... a_bA(1), a_bA(2)), ... sprintf("PDF for sample 2 with estimated α=%0.2f and β=%0.2f", ... a_bB(1), a_bB(2)), ... sprintf("PDF for sample 3 with estimated α=%0.2f and β=%0.2f", ... a_bC(1), a_bC(2))}) title ("Three population samples from different log-logistic distibutions") hold off ***** test [paramhat, paramci] = loglfit ([1:50]); paramhat_out = [3.09717, 0.468525]; paramci_out = [2.87261, 0.370616; 3.32174, 0.5923]; assert (paramhat, paramhat_out, 1e-5); assert (paramci, paramci_out, 1e-5); ***** test paramhat = loglfit ([1:5]); paramhat_out = [1.01124, 0.336449]; assert (paramhat, paramhat_out, 1e-5); ***** test paramhat = loglfit ([1:6], [], [], [1 1 1 1 1 0]); paramhat_out = [1.01124, 0.336449]; assert (paramhat, paramhat_out, 1e-4); ***** test paramhat = loglfit ([1:5], [], [], [1 1 1 1 2]); paramhat_out = loglfit ([1:5, 5]); assert (paramhat, paramhat_out, 1e-4); ***** error loglfit (ones (2,5)); ***** error loglfit ([1, 2, 3, 4, 5], 1.2); ***** error loglfit ([1, 2, 3, 4, 5], 0); ***** error loglfit ([1, 2, 3, 4, 5], "alpha"); ***** error ... loglfit ([1, 2, 3, 4, 5], 0.05, [1 1 0]); ***** error ... loglfit ([1, 2, 3, 4, 5], [], [1 1 0 1 1]'); ***** error ... loglfit ([1, 2, 3, 4, 5], 0.05, zeros (1,5), [1 1 0]); ***** error ... loglfit ([1, 2, 3, 4, 5], [], [], [1 1 0 1 1]'); ***** error ... loglfit ([1, 2, 3, 4, 5], 0.05, [], [], 2); 13 tests, 13 passed, 0 known failure, 0 skipped [inst/dist_fit/evlike.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/dist_fit/evlike.m ***** test x = 1:50; [nlogL, acov] = evlike ([2.3, 1.2], x); avar_out = [-1.2778e-13, 3.1859e-15; 3.1859e-15, -7.9430e-17]; assert (nlogL, 3.242264755689906e+17, 1e-14); assert (acov, avar_out, 1e-3); ***** test x = 1:50; [nlogL, acov] = evlike ([2.3, 1.2], x * 0.5); avar_out = [-7.6094e-05, 3.9819e-06; 3.9819e-06, -2.0836e-07]; assert (nlogL, 481898704.0472211, 1e-6); assert (acov, avar_out, 1e-3); ***** test x = 1:50; [nlogL, acov] = evlike ([21, 15], x); avar_out = [11.73913876598908, -5.9546128523121216; ... -5.954612852312121, 3.708060045170236]; assert (nlogL, 223.7612479380652, 1e-13); assert (acov, avar_out, 1e-14); ***** error evlike ([12, 15]) ***** error evlike ([12, 15, 3], [1:50]) ***** error evlike ([12, 3], ones (10, 2)) ***** error ... evlike ([12, 15], [1:50], [1, 2, 3]) ***** error ... evlike ([12, 15], [1:50], [], [1, 2, 3]) 8 tests, 8 passed, 0 known failure, 0 skipped [inst/dist_fit/betalike.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/dist_fit/betalike.m ***** test x = 0.01:0.02:0.99; [nlogL, avar] = betalike ([2.3, 1.2], x); avar_out = [0.03691678, 0.02803056; 0.02803056, 0.03965629]; assert (nlogL, 17.873477715879040, 3e-14); assert (avar, avar_out, 1e-7); ***** test x = 0.01:0.02:0.99; [nlogL, avar] = betalike ([1, 4], x); avar_out = [0.02793282, 0.02717274; 0.02717274, 0.03993361]; assert (nlogL, 79.648061114839550, 1e-13); assert (avar, avar_out, 1e-7); ***** test x = 0.00:0.02:1; [nlogL, avar] = betalike ([1, 4], x); avar_out = [0.00000801564765, 0.00000131397245; ... 0.00000131397245, 0.00070827639442]; assert (nlogL, 573.2008434477486, 1e-10); assert (avar, avar_out, 1e-14); ***** error ... betalike ([12, 15]); ***** error betalike ([12, 15, 3], [1:50]); ***** error ... betalike ([12, 15], ones (10, 1), ones (8,1)) ***** error ... betalike ([12, 15], ones (1, 8), [1 1 1 1 1 1 1 -1]) ***** error ... betalike ([12, 15], ones (1, 8), [1 1 1 1 1 1 1 1.5]) 8 tests, 8 passed, 0 known failure, 0 skipped [inst/dist_fit/geofit.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/dist_fit/geofit.m ***** demo ## Sample 2 populations from different geometric distibutions rande ("seed", 1); # for reproducibility r1 = geornd (0.15, 1000, 1); rande ("seed", 2); # for reproducibility r2 = geornd (0.5, 1000, 1); r = [r1, r2]; ## Plot them normalized and fix their colors hist (r, 0:0.5:20.5, 1); h = findobj (gca, "Type", "patch"); set (h(1), "facecolor", "c"); set (h(2), "facecolor", "g"); hold on ## Estimate their probability of success pshatA = geofit (r(:,1)); pshatB = geofit (r(:,2)); ## Plot their estimated PDFs x = [0:15]; y = geopdf (x, pshatA); plot (x, y, "-pg"); y = geopdf (x, pshatB); plot (x, y, "-sc"); xlim ([0, 15]) ylim ([0, 0.6]) legend ({"Normalized HIST of sample 1 with ps=0.15", ... "Normalized HIST of sample 2 with ps=0.50", ... sprintf("PDF for sample 1 with estimated ps=%0.2f", ... mean (pshatA)), ... sprintf("PDF for sample 2 with estimated ps=%0.2f", ... mean (pshatB))}) title ("Two population samples from different geometric distibutions") hold off ***** test x = 0:5; [pshat, psci] = geofit (x); assert (pshat, 0.2857, 1e-4); assert (psci, [0.092499; 0.478929], 1e-5); ***** test x = 0:5; [pshat, psci] = geofit (x, [], [1 1 1 1 1 1]); assert (pshat, 0.2857, 1e-4); assert (psci, [0.092499; 0.478929], 1e-5); ***** assert (geofit ([1 1 2 3]), geofit ([1 2 3], [] ,[2 1 1])) ***** error geofit () ***** error geofit (-1, [1 2 3 3]) ***** error geofit (1, 0) ***** error geofit (1, 1.2) ***** error geofit (1, [0.02 0.05]) ***** error ... geofit ([1.5, 0.2], [], [0, 0, 0, 0, 0]) ***** error ... geofit ([1.5, 0.2], [], [1, 1, 1]) 10 tests, 10 passed, 0 known failure, 0 skipped [inst/dist_fit/gplike.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/dist_fit/gplike.m ***** test k = 0.8937; sigma = 1.3230; theta = 1; x = [2.2196, 11.9301, 4.3673, 1.0949, 6.5626, ... 1.2109, 1.8576, 1.0039, 12.7917, 2.2590]; [nlogL, acov] = gplike ([k, sigma, theta], x); assert (nlogL, 21.736, 1e-3); assert (acov, [0.7249, -0.7351, 0; -0.7351, 1.3040, 0; 0, 0, 0], 1e-4); ***** assert (gplike ([2, 3, 0], 4), 3.047536764863501, 1e-14) ***** assert (gplike ([2, 3, 4], 8), 3.047536764863501, 1e-14) ***** assert (gplike ([1, 2, 0], 4), 2.890371757896165, 1e-14) ***** assert (gplike ([1, 2, 4], 8), 2.890371757896165, 1e-14) ***** assert (gplike ([2, 3, 0], [1:10]), 32.57864322725392, 1e-14) ***** assert (gplike ([2, 3, 2], [1:10] + 2), 32.57864322725392, 1e-14) ***** assert (gplike ([2, 3, 0], [1:10], ones (1,10)), 32.57864322725392, 1e-14) ***** assert (gplike ([1, 2, 0], [1:10]), 31.65666282460443, 1e-14) ***** assert (gplike ([1, 2, 3], [1:10] + 3), 31.65666282460443, 1e-14) ***** assert (gplike ([1, 2, 0], [1:10], ones (1,10)), 31.65666282460443, 1e-14) ***** assert (gplike ([1, NaN, 0], [1:10]), NaN) ***** error gplike () ***** error gplike (1) ***** error gplike ([1, 2, 0], []) ***** error gplike ([1, 2, 0], ones (2)) ***** error gplike (2, [1:10]) ***** error gplike ([2, 3], [1:10]) ***** error ... gplike ([1, 2, 0], ones (10, 1), ones (8,1)) ***** error ... gplike ([1, 2, 0], ones (1, 8), [1 1 1 1 1 1 1 -1]) 20 tests, 20 passed, 0 known failure, 0 skipped [inst/dist_fit/invgfit.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/dist_fit/invgfit.m ***** demo ## Sample 3 populations from different inverse Gaussian distibutions rand ("seed", 5); randn ("seed", 5); # for reproducibility r1 = invgrnd (1, 0.2, 2000, 1); rand ("seed", 2); randn ("seed", 2); # for reproducibility r2 = invgrnd (1, 3, 2000, 1); rand ("seed", 7); randn ("seed", 7); # for reproducibility r3 = invgrnd (3, 1, 2000, 1); r = [r1, r2, r3]; ## Plot them normalized and fix their colors hist (r, [0.1:0.1:3.2], 9); h = findobj (gca, "Type", "patch"); set (h(1), "facecolor", "c"); set (h(2), "facecolor", "g"); set (h(3), "facecolor", "r"); ylim ([0, 3]); xlim ([0, 3]); hold on ## Estimate their MU and LAMBDA parameters mu_lambdaA = invgfit (r(:,1)); mu_lambdaB = invgfit (r(:,2)); mu_lambdaC = invgfit (r(:,3)); ## Plot their estimated PDFs x = [0:0.1:3]; y = invgpdf (x, mu_lambdaA(1), mu_lambdaA(2)); plot (x, y, "-pr"); y = invgpdf (x, mu_lambdaB(1), mu_lambdaB(2)); plot (x, y, "-sg"); y = invgpdf (x, mu_lambdaC(1), mu_lambdaC(2)); plot (x, y, "-^c"); hold off legend ({"Normalized HIST of sample 1 with μ=1 and λ=0.5", ... "Normalized HIST of sample 2 with μ=2 and λ=0.3", ... "Normalized HIST of sample 3 with μ=4 and λ=0.5", ... sprintf("PDF for sample 1 with estimated μ=%0.2f and λ=%0.2f", ... mu_lambdaA(1), mu_lambdaA(2)), ... sprintf("PDF for sample 2 with estimated μ=%0.2f and λ=%0.2f", ... mu_lambdaB(1), mu_lambdaB(2)), ... sprintf("PDF for sample 3 with estimated μ=%0.2f and λ=%0.2f", ... mu_lambdaC(1), mu_lambdaC(2))}) title ("Three population samples from different inverse Gaussian distibutions") hold off ***** test paramhat = invgfit ([1:50]); paramhat_out = [25.5, 19.6973]; assert (paramhat, paramhat_out, 1e-4); ***** test paramhat = invgfit ([1:5]); paramhat_out = [3, 8.1081]; assert (paramhat, paramhat_out, 1e-4); ***** error invgfit (ones (2,5)); ***** error invgfit ([-1 2 3 4]); ***** error invgfit ([1, 2, 3, 4, 5], 1.2); ***** error invgfit ([1, 2, 3, 4, 5], 0); ***** error invgfit ([1, 2, 3, 4, 5], "alpha"); ***** error ... invgfit ([1, 2, 3, 4, 5], 0.05, [1 1 0]); ***** error ... invgfit ([1, 2, 3, 4, 5], [], [1 1 0 1 1]'); ***** error ... invgfit ([1, 2, 3, 4, 5], 0.05, zeros (1,5), [1 1 0]); ***** error ... invgfit ([1, 2, 3, 4, 5], [], [], [1 1 0 1 1]'); ***** error ... invgfit ([1, 2, 3, 4, 5], 0.05, [], [], 2); 12 tests, 12 passed, 0 known failure, 0 skipped [inst/dist_fit/gevfit_lmom.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/dist_fit/gevfit_lmom.m ***** xtest <31070> data = 1:50; [pfit, pci] = gevfit_lmom (data); expected_p = [-0.28 15.01 20.22]'; assert (pfit, expected_p, 0.1); 1 test, 1 passed, 0 known failure, 0 skipped [inst/dist_fit/raylfit.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/dist_fit/raylfit.m ***** demo ## Sample 3 populations from 3 different Rayleigh distibutions rand ("seed", 2); # for reproducibility r1 = raylrnd (1, 1000, 1); rand ("seed", 2); # for reproducibility r2 = raylrnd (2, 1000, 1); rand ("seed", 3); # for reproducibility r3 = raylrnd (4, 1000, 1); r = [r1, r2, r3]; ## Plot them normalized and fix their colors hist (r, [0.5:0.5:10.5], 2); h = findobj (gca, "Type", "patch"); set (h(1), "facecolor", "c"); set (h(2), "facecolor", "g"); set (h(3), "facecolor", "r"); hold on ## Estimate their lambda parameter sigmaA = raylfit (r(:,1)); sigmaB = raylfit (r(:,2)); sigmaC = raylfit (r(:,3)); ## Plot their estimated PDFs x = [0:0.1:10]; y = raylpdf (x, sigmaA); plot (x, y, "-pr"); y = raylpdf (x, sigmaB); plot (x, y, "-sg"); y = raylpdf (x, sigmaC); plot (x, y, "-^c"); xlim ([0, 10]) ylim ([0, 0.7]) legend ({"Normalized HIST of sample 1 with σ=1", ... "Normalized HIST of sample 2 with σ=2", ... "Normalized HIST of sample 3 with σ=4", ... sprintf("PDF for sample 1 with estimated σ=%0.2f", ... sigmaA), ... sprintf("PDF for sample 2 with estimated σ=%0.2f", ... sigmaB), ... sprintf("PDF for sample 3 with estimated σ=%0.2f", ... sigmaC)}) title ("Three population samples from different Rayleigh distibutions") hold off ***** test x = [1 3 2 4 5 4 3 4]; [shat, sci] = raylfit (x); assert (shat, 2.4495, 1e-4) assert (sci, [1.8243; 3.7279], 1e-4) ***** test x = [1 3 2 4 5 4 3 4]; [shat, sci] = raylfit (x, 0.01); assert (shat, 2.4495, 1e-4) assert (sci, [1.6738; 4.3208], 1e-4) ***** test x = [1 2 3 4 5]; f = [1 1 2 3 1]; [shat, sci] = raylfit (x, [], [], f); assert (shat, 2.4495, 1e-4) assert (sci, [1.8243; 3.7279], 1e-4) ***** test x = [1 2 3 4 5]; f = [1 1 2 3 1]; [shat, sci] = raylfit (x, 0.01, [], f); assert (shat, 2.4495, 1e-4) assert (sci, [1.6738; 4.3208], 1e-4) ***** test x = [1 2 3 4 5 6]; c = [0 0 0 0 0 1]; f = [1 1 2 3 1 1]; [shat, sci] = raylfit (x, 0.01, c, f); assert (shat, 2.4495, 1e-4) assert (sci, [1.6738; 4.3208], 1e-4) ***** error raylfit (ones (2,5)); ***** error raylfit ([1 2 -1 3]) ***** error raylfit ([1 2 3], 0) ***** error raylfit ([1 2 3], 1.2) ***** error raylfit ([1 2 3], [0.02 0.05]) ***** error ... raylfit ([1, 2, 3, 4, 5], 0.05, [1 1 0]); ***** error ... raylfit ([1, 2, 3, 4, 5], [], [1 1 0 1 1]'); ***** error ... raylfit ([1, 2, 3, 4, 5], 0.05, zeros (1,5), [1 1 0]); ***** error ... raylfit ([1, 2, 3, 4, 5], [], [], [1 1 0 1 1]'); ***** error raylfit ([1 2 3], [], [], [1 5]) ***** error raylfit ([1 2 3], [], [], [1 5 -1]) 16 tests, 16 passed, 0 known failure, 0 skipped [inst/dist_fit/tlsfit.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/dist_fit/tlsfit.m ***** demo ## Sample 3 populations from 3 different location-scale T distibutions randn ("seed", 1); # for reproducibility randg ("seed", 2); # for reproducibility r1 = tlsrnd (-4, 3, 1, 2000, 1); randn ("seed", 3); # for reproducibility randg ("seed", 4); # for reproducibility r2 = tlsrnd (0, 3, 1, 2000, 1); randn ("seed", 5); # for reproducibility randg ("seed", 6); # for reproducibility r3 = tlsrnd (5, 5, 4, 2000, 1); r = [r1, r2, r3]; ## Plot them normalized and fix their colors hist (r, [-21:21], [1, 1, 1]); h = findobj (gca, "Type", "patch"); set (h(1), "facecolor", "c"); set (h(2), "facecolor", "g"); set (h(3), "facecolor", "r"); ylim ([0, 0.25]); xlim ([-20, 20]); hold on ## Estimate their lambda parameter mu_sigma_nuA = tlsfit (r(:,1)); mu_sigma_nuB = tlsfit (r(:,2)); mu_sigma_nuC = tlsfit (r(:,3)); ## Plot their estimated PDFs x = [-20:0.1:20]; y = tlspdf (x, mu_sigma_nuA(1), mu_sigma_nuA(2), mu_sigma_nuA(3)); plot (x, y, "-pr"); y = tlspdf (x, mu_sigma_nuB(1), mu_sigma_nuB(2), mu_sigma_nuB(3)); plot (x, y, "-sg"); y = tlspdf (x, mu_sigma_nuC(1), mu_sigma_nuC(2), mu_sigma_nuC(3)); plot (x, y, "-^c"); hold off legend ({"Normalized HIST of sample 1 with μ=0, σ=2 and nu=1", ... "Normalized HIST of sample 2 with μ=5, σ=2 and nu=1", ... "Normalized HIST of sample 3 with μ=3, σ=4 and nu=3", ... sprintf("PDF for sample 1 with estimated μ=%0.2f, σ=%0.2f, and ν=%0.2f", ... mu_sigma_nuA(1), mu_sigma_nuA(2), mu_sigma_nuA(3)), ... sprintf("PDF for sample 2 with estimated μ=%0.2f, σ=%0.2f, and ν=%0.2f", ... mu_sigma_nuB(1), mu_sigma_nuB(2), mu_sigma_nuB(3)), ... sprintf("PDF for sample 3 with estimated μ=%0.2f, σ=%0.2f, and ν=%0.2f", ... mu_sigma_nuC(1), mu_sigma_nuC(2), mu_sigma_nuC(3))}) title ("Three population samples from different location-scale T distibutions") hold off ***** test x = [-1.2352, -0.2741, 0.1726, 7.4356, 1.0392, 16.4165]; [paramhat, paramci] = tlsfit (x); paramhat_out = [0.035893, 0.862711, 0.649261]; paramci_out = [-0.949034, 0.154655, 0.181080; 1.02082, 4.812444, 2.327914]; assert (paramhat, paramhat_out, 1e-6); assert (paramci, paramci_out, 1e-5); ***** test x = [-1.2352, -0.2741, 0.1726, 7.4356, 1.0392, 16.4165]; [paramhat, paramci] = tlsfit (x, 0.01); paramci_out = [-1.2585, 0.0901, 0.1212; 1.3303, 8.2591, 3.4771]; assert (paramci, paramci_out, 1e-4); ***** error tlsfit (ones (2,5)); ***** error tlsfit ([1, 2, 3, 4, 5], 1.2); ***** error tlsfit ([1, 2, 3, 4, 5], 0); ***** error tlsfit ([1, 2, 3, 4, 5], "alpha"); ***** error ... tlsfit ([1, 2, 3, 4, 5], 0.05, [1 1 0]); ***** error ... tlsfit ([1, 2, 3, 4, 5], [], [1 1 0 1 1]'); ***** error ... tlsfit ([1, 2, 3, 4, 5], 0.05, zeros (1,5), [1 1 0]); ***** error ... tlsfit ([1, 2, 3, 4, 5], [], [], [1 1 0 1 1]'); ***** error ... tlsfit ([1, 2, 3, 4, 5], [], [], [1 1 0 1 -1]); ***** error ... tlsfit ([1, 2, 3, 4, 5], 0.05, [], [], 2); 12 tests, 12 passed, 0 known failure, 0 skipped [inst/dist_fit/nakalike.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/dist_fit/nakalike.m ***** test nlogL = nakalike ([0.735504, 858.5], [1:50]); assert (nlogL, 202.8689, 1e-4); ***** test nlogL = nakalike ([1.17404, 11], [1:5]); assert (nlogL, 8.6976, 1e-4); ***** test nlogL = nakalike ([1.17404, 11], [1:5], [], [1, 1, 1, 1, 1]); assert (nlogL, 8.6976, 1e-4); ***** test nlogL = nakalike ([1.17404, 11], [1:6], [], [1, 1, 1, 1, 1, 0]); assert (nlogL, 8.6976, 1e-4); ***** error nakalike (3.25) ***** error nakalike ([5, 0.2], ones (2)) ***** error ... nakalike ([1, 0.2, 3], [1, 3, 5, 7]) ***** error ... nakalike ([1.5, 0.2], [1:5], [0, 0, 0]) ***** error ... nakalike ([1.5, 0.2], [1:5], [0, 0, 0, 0, 0], [1, 1, 1]) ***** error ... nakalike ([1.5, 0.2], [1:5], [], [1, 1, 1]) ***** error ... nakalike ([1.5, 0.2], [1:5], [], [1, 1, 1, 1, -1]) 11 tests, 11 passed, 0 known failure, 0 skipped [inst/dist_fit/lognfit.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/dist_fit/lognfit.m ***** demo ## Sample 3 populations from 3 different log-normal distibutions randn ("seed", 1); # for reproducibility r1 = lognrnd (0, 0.25, 1000, 1); randn ("seed", 2); # for reproducibility r2 = lognrnd (0, 0.5, 1000, 1); randn ("seed", 3); # for reproducibility r3 = lognrnd (0, 1, 1000, 1); r = [r1, r2, r3]; ## Plot them normalized and fix their colors hist (r, 30, 2); h = findobj (gca, "Type", "patch"); set (h(1), "facecolor", "c"); set (h(2), "facecolor", "g"); set (h(3), "facecolor", "r"); hold on ## Estimate their mu and sigma parameters mu_sigmaA = lognfit (r(:,1)); mu_sigmaB = lognfit (r(:,2)); mu_sigmaC = lognfit (r(:,3)); ## Plot their estimated PDFs x = [0:0.1:6]; y = lognpdf (x, mu_sigmaA(1), mu_sigmaA(2)); plot (x, y, "-pr"); y = lognpdf (x, mu_sigmaB(1), mu_sigmaB(2)); plot (x, y, "-sg"); y = lognpdf (x, mu_sigmaC(1), mu_sigmaC(2)); plot (x, y, "-^c"); ylim ([0, 2]) xlim ([0, 6]) hold off legend ({"Normalized HIST of sample 1 with mu=0, σ=0.25", ... "Normalized HIST of sample 2 with mu=0, σ=0.5", ... "Normalized HIST of sample 3 with mu=0, σ=1", ... sprintf("PDF for sample 1 with estimated mu=%0.2f and σ=%0.2f", ... mu_sigmaA(1), mu_sigmaA(2)), ... sprintf("PDF for sample 2 with estimated mu=%0.2f and σ=%0.2f", ... mu_sigmaB(1), mu_sigmaB(2)), ... sprintf("PDF for sample 3 with estimated mu=%0.2f and σ=%0.2f", ... mu_sigmaC(1), mu_sigmaC(2))}, "location", "northeast") title ("Three population samples from different log-normal distibutions") hold off ***** test randn ("seed", 1); x = lognrnd (3, 5, [1000, 1]); [paramhat, paramci] = lognfit (x, 0.01); assert (paramci(1,1) < 3); assert (paramci(1,2) > 3); assert (paramci(2,1) < 5); assert (paramci(2,2) > 5); ***** error ... lognfit (ones (20,3)) ***** error ... lognfit ({1, 2, 3, 4, 5}) ***** error ... lognfit ([-1, 2, 3, 4, 5]) ***** error lognfit (ones (20,1), 0) ***** error lognfit (ones (20,1), -0.3) ***** error lognfit (ones (20,1), 1.2) ***** error lognfit (ones (20,1), [0.05, 0.1]) ***** error lognfit (ones (20,1), 0.02+i) ***** error ... lognfit (ones (20,1), [], zeros(15,1)) ***** error ... lognfit (ones (20,1), [], zeros(20,1), ones(25,1)) ***** error lognfit (ones (20,1), [], zeros(20,1), ones(20,1), "options") 12 tests, 12 passed, 0 known failure, 0 skipped [inst/dist_fit/normfit.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/dist_fit/normfit.m ***** demo ## Sample 3 populations from 3 different normal distibutions randn ("seed", 1); # for reproducibility r1 = normrnd (2, 5, 5000, 1); randn ("seed", 2); # for reproducibility r2 = normrnd (5, 2, 5000, 1); randn ("seed", 3); # for reproducibility r3 = normrnd (9, 4, 5000, 1); r = [r1, r2, r3]; ## Plot them normalized and fix their colors hist (r, 15, 0.4); h = findobj (gca, "Type", "patch"); set (h(1), "facecolor", "c"); set (h(2), "facecolor", "g"); set (h(3), "facecolor", "r"); hold on ## Estimate their mu and sigma parameters [muhat, sigmahat] = normfit (r); ## Plot their estimated PDFs x = [min(r(:)):max(r(:))]; y = normpdf (x, muhat(1), sigmahat(1)); plot (x, y, "-pr"); y = normpdf (x, muhat(2), sigmahat(2)); plot (x, y, "-sg"); y = normpdf (x, muhat(3), sigmahat(3)); plot (x, y, "-^c"); ylim ([0, 0.5]) xlim ([-20, 20]) hold off legend ({"Normalized HIST of sample 1 with mu=2, σ=5", ... "Normalized HIST of sample 2 with mu=5, σ=2", ... "Normalized HIST of sample 3 with mu=9, σ=4", ... sprintf("PDF for sample 1 with estimated mu=%0.2f and σ=%0.2f", ... muhat(1), sigmahat(1)), ... sprintf("PDF for sample 2 with estimated mu=%0.2f and σ=%0.2f", ... muhat(2), sigmahat(2)), ... sprintf("PDF for sample 3 with estimated mu=%0.2f and σ=%0.2f", ... muhat(3), sigmahat(3))}, "location", "northwest") title ("Three population samples from different normal distibutions") hold off ***** test load lightbulb idx = find (lightbulb(:,2) == 0); censoring = lightbulb(idx,3) == 1; [muHat, sigmaHat] = normfit (lightbulb(idx,1), [], censoring); assert (muHat, 9496.59586737857, 1e-11); assert (sigmaHat, 3064.021012796456, 2e-12); ***** test randn ("seed", 234); x = normrnd (3, 5, [1000, 1]); [muHat, sigmaHat, muCI, sigmaCI] = normfit (x, 0.01); assert (muCI(1) < 3); assert (muCI(2) > 3); assert (sigmaCI(1) < 5); assert (sigmaCI(2) > 5); ***** error ... normfit (ones (3,3,3)) ***** error ... normfit (ones (20,3), [], zeros (20,1)) ***** error normfit (ones (20,1), 0) ***** error normfit (ones (20,1), -0.3) ***** error normfit (ones (20,1), 1.2) ***** error normfit (ones (20,1), [0.05 0.1]) ***** error normfit (ones (20,1), 0.02+i) ***** error ... normfit (ones (20,1), [], zeros(15,1)) ***** error ... normfit (ones (20,1), [], zeros(20,1), ones(25,1)) ***** error ... normfit (ones (5,1), [], zeros(5,1), [1, 2, 1, 2, -1]') ***** error normfit (ones (20,1), [], zeros(20,1), ones(20,1), "options") 13 tests, 13 passed, 0 known failure, 0 skipped [inst/dist_fit/poissfit.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/dist_fit/poissfit.m ***** demo ## Sample 3 populations from 3 different Poisson distibutions randp ("seed", 2); # for reproducibility r1 = poissrnd (1, 1000, 1); randp ("seed", 2); # for reproducibility r2 = poissrnd (4, 1000, 1); randp ("seed", 3); # for reproducibility r3 = poissrnd (10, 1000, 1); r = [r1, r2, r3]; ## Plot them normalized and fix their colors hist (r, [0:20], 1); h = findobj (gca, "Type", "patch"); set (h(1), "facecolor", "c"); set (h(2), "facecolor", "g"); set (h(3), "facecolor", "r"); hold on ## Estimate their lambda parameter lambdahat = poissfit (r); ## Plot their estimated PDFs x = [0:20]; y = poisspdf (x, lambdahat(1)); plot (x, y, "-pr"); y = poisspdf (x, lambdahat(2)); plot (x, y, "-sg"); y = poisspdf (x, lambdahat(3)); plot (x, y, "-^c"); xlim ([0, 20]) ylim ([0, 0.4]) legend ({"Normalized HIST of sample 1 with λ=1", ... "Normalized HIST of sample 2 with λ=4", ... "Normalized HIST of sample 3 with λ=10", ... sprintf("PDF for sample 1 with estimated λ=%0.2f", ... lambdahat(1)), ... sprintf("PDF for sample 2 with estimated λ=%0.2f", ... lambdahat(2)), ... sprintf("PDF for sample 3 with estimated λ=%0.2f", ... lambdahat(3))}) title ("Three population samples from different Poisson distibutions") hold off ***** test x = [1 3 2 4 5 4 3 4]; [lhat, lci] = poissfit (x); assert (lhat, 3.25) assert (lci, [2.123007901949543; 4.762003010390628], 1e-14) ***** test x = [1 3 2 4 5 4 3 4]; [lhat, lci] = poissfit (x, 0.01); assert (lhat, 3.25) assert (lci, [1.842572740234582; 5.281369033298528], 1e-14) ***** test x = [1 2 3 4 5]; f = [1 1 2 3 1]; [lhat, lci] = poissfit (x, [], f); assert (lhat, 3.25) assert (lci, [2.123007901949543; 4.762003010390628], 1e-14) ***** test x = [1 2 3 4 5]; f = [1 1 2 3 1]; [lhat, lci] = poissfit (x, 0.01, f); assert (lhat, 3.25) assert (lci, [1.842572740234582; 5.281369033298528], 1e-14) ***** error poissfit ([1 2 -1 3]) ***** error poissfit ([1 2 3], 0) ***** error poissfit ([1 2 3], 1.2) ***** error poissfit ([1 2 3], [0.02 0.05]) ***** error poissfit ([1 2 3], [], [1 5]) ***** error poissfit ([1 2 3], [], [1 5 -1]) 10 tests, 10 passed, 0 known failure, 0 skipped [inst/dist_fit/ricefit.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/dist_fit/ricefit.m ***** demo ## Sample 3 populations from different Gamma distibutions randg ("seed", 5); # for reproducibility randp ("seed", 6); r1 = ricernd (1, 2, 3000, 1); randg ("seed", 2); # for reproducibility randp ("seed", 8); r2 = ricernd (2, 4, 3000, 1); randg ("seed", 7); # for reproducibility randp ("seed", 9); r3 = ricernd (7.5, 1, 3000, 1); r = [r1, r2, r3]; ## Plot them normalized and fix their colors hist (r, 75, 4); h = findobj (gca, "Type", "patch"); set (h(1), "facecolor", "c"); set (h(2), "facecolor", "g"); set (h(3), "facecolor", "r"); ylim ([0, 0.7]); xlim ([0, 12]); hold on ## Estimate their α and β parameters s_sigmaA = ricefit (r(:,1)); s_sigmaB = ricefit (r(:,2)); s_sigmaC = ricefit (r(:,3)); ## Plot their estimated PDFs x = [0.01,0.1:0.2:18]; y = ricepdf (x, s_sigmaA(1), s_sigmaA(2)); plot (x, y, "-pr"); y = ricepdf (x, s_sigmaB(1), s_sigmaB(2)); plot (x, y, "-sg"); y = ricepdf (x, s_sigmaC(1), s_sigmaC(2)); plot (x, y, "-^c"); hold off legend ({"Normalized HIST of sample 1 with s=1 and σ=2", ... "Normalized HIST of sample 2 with s=2 and σ=4", ... "Normalized HIST of sample 3 with s=7.5 and σ=1", ... sprintf("PDF for sample 1 with estimated s=%0.2f and σ=%0.2f", ... s_sigmaA(1), s_sigmaA(2)), ... sprintf("PDF for sample 2 with estimated s=%0.2f and σ=%0.2f", ... s_sigmaB(1), s_sigmaB(2)), ... sprintf("PDF for sample 3 with estimated s=%0.2f and σ=%0.2f", ... s_sigmaC(1), s_sigmaC(2))}) title ("Three population samples from different Rician distibutions") hold off ***** test [paramhat, paramci] = ricefit ([1:50]); assert (paramhat, [15.3057, 17.6668], 1e-4); assert (paramci, [9.5468, 11.7802; 24.5383, 26.4952], 1e-4); ***** test [paramhat, paramci] = ricefit ([1:50], 0.01); assert (paramhat, [15.3057, 17.6668], 1e-4); assert (paramci, [8.2309, 10.3717; 28.4615, 30.0934], 1e-4); ***** test [paramhat, paramci] = ricefit ([1:5]); assert (paramhat, [2.3123, 1.6812], 1e-4); assert (paramci, [1.0819, 0.6376; 4.9424, 4.4331], 1e-4); ***** test [paramhat, paramci] = ricefit ([1:5], 0.01); assert (paramhat, [2.3123, 1.6812], 1e-4); assert (paramci, [0.8521, 0.4702; 6.2747, 6.0120], 1e-4); ***** test freq = [1 1 1 1 5]; [paramhat, paramci] = ricefit ([1:5], [], [], freq); assert (paramhat, [3.5181, 1.5565], 1e-4); assert (paramci, [2.5893, 0.9049; 4.7801, 2.6772], 1e-4); ***** test censor = [1 0 0 0 0]; [paramhat, paramci] = ricefit ([1:5], [], censor); assert (paramhat, [3.2978, 1.1527], 1e-4); assert (paramci, [2.3192, 0.5476; 4.6895, 2.4261], 1e-4); ***** assert (class (ricefit (single ([1:50]))), "single") ***** error ricefit (ones (2)) ***** error ricefit ([1:50], 1) ***** error ricefit ([1:50], -1) ***** error ricefit ([1:50], {0.05}) ***** error ricefit ([1:50], "k") ***** error ricefit ([1:50], i) ***** error ricefit ([1:50], [0.01 0.02]) ***** error ricefit ([1:50], [], [1 1]) ***** error ricefit ([1:50], [], [], [1 1]) ***** error ... ricefit ([1:5], [], [], [1, 1, 2, 1, -1]) ***** error ricefit ([1 2 3 -4]) ***** error ricefit ([1 2 0], [], [1 0 0]) 19 tests, 19 passed, 0 known failure, 0 skipped [inst/dist_fit/nbinfit.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/dist_fit/nbinfit.m ***** demo ## Sample 2 populations from different negative binomial distibutions randp ("seed", 5); randg ("seed", 5); # for reproducibility r1 = nbinrnd (2, 0.15, 5000, 1); randp ("seed", 8); randg ("seed", 8); # for reproducibility r2 = nbinrnd (5, 0.2, 5000, 1); r = [r1, r2]; ## Plot them normalized and fix their colors hist (r, [0:51], 1); h = findobj (gca, "Type", "patch"); set (h(1), "facecolor", "c"); set (h(2), "facecolor", "g"); hold on ## Estimate their probability of success r_psA = nbinfit (r(:,1)); r_psB = nbinfit (r(:,2)); ## Plot their estimated PDFs x = [0:40]; y = nbinpdf (x, r_psA(1), r_psA(2)); plot (x, y, "-pg"); x = [min(r(:,2)):max(r(:,2))]; y = nbinpdf (x, r_psB(1), r_psB(2)); plot (x, y, "-sc"); ylim ([0, 0.1]) xlim ([0, 50]) legend ({"Normalized HIST of sample 1 with r=2 and ps=0.15", ... "Normalized HIST of sample 2 with r=5 and ps=0.2", ... sprintf("PDF for sample 1 with estimated r=%0.2f and ps=%0.2f", ... r_psA(1), r_psA(2)), ... sprintf("PDF for sample 2 with estimated r=%0.2f and ps=%0.2f", ... r_psB(1), r_psB(2))}) title ("Two population samples from negative different binomial distibutions") hold off ***** test [paramhat, paramci] = nbinfit ([1:50]); assert (paramhat, [2.420857, 0.086704], 1e-6); assert (paramci(:,1), [1.382702; 3.459012], 1e-6); assert (paramci(:,2), [0.049676; 0.123732], 1e-6); ***** test [paramhat, paramci] = nbinfit ([1:20]); assert (paramhat, [3.588233, 0.254697], 1e-6); assert (paramci(:,1), [0.451693; 6.724774], 1e-6); assert (paramci(:,2), [0.081143; 0.428251], 1e-6); ***** test [paramhat, paramci] = nbinfit ([1:10]); assert (paramhat, [8.8067, 0.6156], 1e-4); assert (paramci(:,1), [0; 30.7068], 1e-4); assert (paramci(:,2), [0.0217; 1], 1e-4); ***** test [paramhat, paramci] = nbinfit ([1:10], 0.05, ones (1, 10)); assert (paramhat, [8.8067, 0.6156], 1e-4); assert (paramci(:,1), [0; 30.7068], 1e-4); assert (paramci(:,2), [0.0217; 1], 1e-4); ***** test [paramhat, paramci] = nbinfit ([1:11], 0.05, [ones(1, 10), 0]); assert (paramhat, [8.8067, 0.6156], 1e-4); assert (paramci(:,1), [0; 30.7068], 1e-4); assert (paramci(:,2), [0.0217; 1], 1e-4); ***** error nbinfit ([-1 2 3 3]) ***** error nbinfit (ones (2)) ***** error nbinfit ([1 2 1.2 3]) ***** error nbinfit ([1 2 3], 0) ***** error nbinfit ([1 2 3], 1.2) ***** error nbinfit ([1 2 3], [0.02 0.05]) ***** error ... nbinfit ([1, 2, 3, 4, 5], 0.05, [1, 2, 3, 2]); ***** error ... nbinfit ([1, 2, 3, 4, 5], 0.05, [1, 2, 3, 2, -1]); ***** error ... nbinfit ([1, 2, 3, 4, 5], 0.05, [1, 2, 3, 2, 1.5]); ***** error ... nbinfit ([1, 2, 3, 4, 5], 0.05, struct ("option", 234)); ***** error ... nbinfit ([1, 2, 3, 4, 5], 0.05, ones (1,5), struct ("option", 234)); 16 tests, 16 passed, 0 known failure, 0 skipped [inst/dist_fit/gevfit.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/dist_fit/gevfit.m ***** demo ## Sample 2 populations from 2 different exponential distibutions rand ("seed", 1); # for reproducibility r1 = gevrnd (-0.5, 1, 2, 5000, 1); rand ("seed", 2); # for reproducibility r2 = gevrnd (0, 1, -4, 5000, 1); r = [r1, r2]; ## Plot them normalized and fix their colors hist (r, 50, 5); h = findobj (gca, "Type", "patch"); set (h(1), "facecolor", "c"); set (h(2), "facecolor", "g"); hold on ## Estimate their k, sigma, and mu parameters k_sigma_muA = gevfit (r(:,1)); k_sigma_muB = gevfit (r(:,2)); ## Plot their estimated PDFs x = [-10:0.5:20]; y = gevpdf (x, k_sigma_muA(1), k_sigma_muA(2), k_sigma_muA(3)); plot (x, y, "-pr"); y = gevpdf (x, k_sigma_muB(1), k_sigma_muB(2), k_sigma_muB(3)); plot (x, y, "-sg"); ylim ([0, 0.7]) xlim ([-7, 5]) legend ({"Normalized HIST of sample 1 with k=-0.5, σ=1, μ=2", ... "Normalized HIST of sample 2 with k=0, σ=1, μ=-4", sprintf("PDF for sample 1 with estimated k=%0.2f, σ=%0.2f, μ=%0.2f", ... k_sigma_muA(1), k_sigma_muA(2), k_sigma_muA(3)), ... sprintf("PDF for sample 3 with estimated k=%0.2f, σ=%0.2f, μ=%0.2f", ... k_sigma_muB(1), k_sigma_muB(2), k_sigma_muB(3))}) title ("Two population samples from different exponential distibutions") hold off ***** test x = 1:50; [pfit, pci] = gevfit (x); pfit_out = [-0.4407, 15.1923, 21.5309]; pci_out = [-0.7532, 11.5878, 16.5686; -0.1282, 19.9183, 26.4926]; assert (pfit, pfit_out, 1e-3); assert (pci, pci_out, 1e-3); ***** test x = 1:2:50; [pfit, pci] = gevfit (x); pfit_out = [-0.4434, 15.2024, 21.0532]; pci_out = [-0.8904, 10.3439, 14.0168; 0.0035, 22.3429, 28.0896]; assert (pfit, pfit_out, 1e-3); assert (pci, pci_out, 1e-3); ***** error gevfit (ones (2,5)); ***** error gevfit ([1, 2, 3, 4, 5], 1.2); ***** error gevfit ([1, 2, 3, 4, 5], 0); ***** error gevfit ([1, 2, 3, 4, 5], "alpha"); ***** error ... gevfit ([1, 2, 3, 4, 5], 0.05, [1, 2, 3, 2]); ***** error ... gevfit ([1, 2, 3, 4, 5], 0.05, [1, 2, 3, 2, -1]); ***** error ... gevfit ([1, 2, 3, 4, 5], 0.05, [1, 2, 3, 2, 1.5]); ***** error ... gevfit ([1, 2, 3, 4, 5], 0.05, struct ("option", 234)); ***** error ... gevfit ([1, 2, 3, 4, 5], 0.05, ones (1,5), struct ("option", 234)); 11 tests, 11 passed, 0 known failure, 0 skipped [inst/dist_fit/poisslike.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/dist_fit/poisslike.m ***** test x = [1 3 2 4 5 4 3 4]; [nlogL, avar] = poisslike (3.25, x); assert (nlogL, 13.9533, 1e-4) ***** test x = [1 2 3 4 5]; f = [1 1 2 3 1]; [nlogL, avar] = poisslike (3.25, x, f); assert (nlogL, 13.9533, 1e-4) ***** error poisslike (1) ***** error poisslike ([1 2 3], [1 2]) ***** error ... poisslike (3.25, ones (10, 2)) ***** error ... poisslike (3.25, [1 2 3 -4 5]) ***** error ... poisslike (3.25, ones (10, 1), ones (8,1)) ***** error ... poisslike (3.25, ones (1, 8), [1 1 1 1 1 1 1 -1]) 8 tests, 8 passed, 0 known failure, 0 skipped [inst/dist_fit/logilike.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/dist_fit/logilike.m ***** test nlogL = logilike ([25.5, 8.7725], [1:50]); assert (nlogL, 206.6769, 1e-4); ***** test nlogL = logilike ([3, 0.8645], [1:5]); assert (nlogL, 9.0699, 1e-4); ***** error logilike (3.25) ***** error logilike ([5, 0.2], ones (2)) ***** error ... logilike ([1, 0.2, 3], [1, 3, 5, 7]) ***** error ... logilike ([1.5, 0.2], [1:5], [0, 0, 0]) ***** error ... logilike ([1.5, 0.2], [1:5], [0, 0, 0, 0, 0], [1, 1, 1]) ***** error ... logilike ([1.5, 0.2], [1:5], [], [1, 1, 1]) 8 tests, 8 passed, 0 known failure, 0 skipped [inst/dist_fit/normlike.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/dist_fit/normlike.m ***** error normlike ([12, 15]); ***** error normlike ([12, 15], ones (2)); ***** error ... normlike ([12, 15, 3], [1:50]); ***** error ... normlike ([12, 15], [1:50], [1, 2, 3]); ***** error ... normlike ([12, 15], [1:50], [], [1, 2, 3]); ***** error ... normlike ([12, 15], [1:5], [], [1, 2, 3, 2, -1]); ***** test x = 1:50; [nlogL, avar] = normlike ([2.3, 1.2], x); avar_out = [7.5767e-01, -1.8850e-02; -1.8850e-02, 4.8750e-04]; assert (nlogL, 13014.95883783327, 1e-10); assert (avar, avar_out, 1e-4); ***** test x = 1:50; [nlogL, avar] = normlike ([2.3, 1.2], x * 0.5); avar_out = [3.0501e-01, -1.5859e-02; -1.5859e-02, 9.1057e-04]; assert (nlogL, 2854.802587833265, 1e-10); assert (avar, avar_out, 1e-4); ***** test x = 1:50; [nlogL, avar] = normlike ([21, 15], x); avar_out = [5.460474308300396, -1.600790513833993; ... -1.600790513833993, 2.667984189723321]; assert (nlogL, 206.738325604233, 1e-12); assert (avar, avar_out, 1e-14); ***** test x = 1:50; censor = ones (1, 50); censor([2, 4, 6, 8, 12, 14]) = 0; [nlogL, avar] = normlike ([2.3, 1.2], x, censor); avar_out = [3.0501e-01, -1.5859e-02; -1.5859e-02, 9.1057e-04]; assert (nlogL, Inf); assert (avar, [NaN, NaN; NaN, NaN]); ***** test x = 1:50; censor = ones (1, 50); censor([2, 4, 6, 8, 12, 14]) = 0; [nlogL, avar] = normlike ([21, 15], x, censor); avar_out = [24.4824488866131, -10.6649544179636; ... -10.6649544179636, 6.22827849965737]; assert (nlogL, 86.9254371829733, 1e-12); assert (avar, avar_out, 8e-14); 11 tests, 11 passed, 0 known failure, 0 skipped [inst/dist_fit/gpfit.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/dist_fit/gpfit.m ***** demo ## Sample 2 populations from different generalized Pareto distibutions ## Assume location parameter θ is known theta = 0; rand ("seed", 5); # for reproducibility r1 = gprnd (1, 2, theta, 20000, 1); rand ("seed", 2); # for reproducibility r2 = gprnd (3, 1, theta, 20000, 1); r = [r1, r2]; ## Plot them normalized and fix their colors hist (r, [0.1:0.2:100], 5); h = findobj (gca, "Type", "patch"); set (h(1), "facecolor", "r"); set (h(2), "facecolor", "c"); ylim ([0, 1]); xlim ([0, 5]); hold on ## Estimate their α and β parameters k_sigmaA = gpfit (r(:,1), theta); k_sigmaB = gpfit (r(:,2), theta); ## Plot their estimated PDFs x = [0.01, 0.1:0.2:18]; y = gppdf (x, k_sigmaA(1), k_sigmaA(2), theta); plot (x, y, "-pc"); y = gppdf (x, k_sigmaB(1), k_sigmaB(2), theta); plot (x, y, "-sr"); hold off legend ({"Normalized HIST of sample 1 with k=1 and σ=2", ... "Normalized HIST of sample 2 with k=2 and σ=2", ... sprintf("PDF for sample 1 with estimated k=%0.2f and σ=%0.2f", ... k_sigmaA(1), k_sigmaA(2)), ... sprintf("PDF for sample 3 with estimated k=%0.2f and σ=%0.2f", ... k_sigmaB(1), k_sigmaB(2))}) title ("Three population samples from different generalized Pareto distibutions") text (2, 0.7, "Known location parameter θ = 0") hold off ***** test k = 0.8937; sigma = 1.3230; theta = 1; x = [2.2196, 11.9301, 4.3673, 1.0949, 6.5626, ... 1.2109, 1.8576, 1.0039, 12.7917, 2.2590]; [hat, ci] = gpfit (x, theta); assert (hat, [k, sigma, theta], 1e-4); assert (ci, [-0.7750, 0.2437, 1; 2.5624, 7.1820, 1], 1e-4); ***** error gpfit () ***** error gpfit (1) ***** error gpfit ([0.2, 0.5+i], 0); ***** error gpfit (ones (2,2) * 0.5, 0); ***** error ... gpfit ([0.5, 1.2], [0, 1]); ***** error ... gpfit ([0.5, 1.2], 5+i); ***** error ... gpfit ([1:5], 2); ***** error gpfit ([0.01:0.1:0.99], 0, 1.2); ***** error gpfit ([0.01:0.1:0.99], 0, i); ***** error gpfit ([0.01:0.1:0.99], 0, -1); ***** error gpfit ([0.01:0.1:0.99], 0, [0.05, 0.01]); ***** error gpfit ([1 2 3], 0, [], [1 5]) ***** error gpfit ([1 2 3], 0, [], [1 5 -1]) ***** error ... gpfit ([1:10], 1, 0.05, [], 5) 15 tests, 15 passed, 0 known failure, 0 skipped [inst/dist_fit/unidfit.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/dist_fit/unidfit.m ***** demo ## Sample 2 populations from different discrete uniform distibutions rand ("seed", 1); # for reproducibility r1 = unidrnd (5, 1000, 1); rand ("seed", 2); # for reproducibility r2 = unidrnd (9, 1000, 1); r = [r1, r2]; ## Plot them normalized and fix their colors hist (r, 0:0.5:20.5, 1); h = findobj (gca, "Type", "patch"); set (h(1), "facecolor", "c"); set (h(2), "facecolor", "g"); hold on ## Estimate their probability of success NhatA = unidfit (r(:,1)); NhatB = unidfit (r(:,2)); ## Plot their estimated PDFs x = [0:10]; y = unidpdf (x, NhatA); plot (x, y, "-pg"); y = unidpdf (x, NhatB); plot (x, y, "-sc"); xlim ([0, 10]) ylim ([0, 0.4]) legend ({"Normalized HIST of sample 1 with N=5", ... "Normalized HIST of sample 2 with N=9", ... sprintf("PDF for sample 1 with estimated N=%0.2f", NhatA), ... sprintf("PDF for sample 2 with estimated N=%0.2f", NhatB)}) title ("Two population samples from different discrete uniform distibutions") hold off ***** test x = 0:5; [Nhat, Nci] = unidfit (x); assert (Nhat, 5); assert (Nci, [5; 9]); ***** test x = 0:5; [Nhat, Nci] = unidfit (x, [], [1 1 1 1 1 1]); assert (Nhat, 5); assert (Nci, [5; 9]); ***** assert (unidfit ([1 1 2 3]), unidfit ([1 2 3], [] ,[2 1 1])) ***** error unidfit () ***** error unidfit (-1, [1 2 3 3]) ***** error unidfit (1, 0) ***** error unidfit (1, 1.2) ***** error unidfit (1, [0.02 0.05]) ***** error ... unidfit ([1.5, 0.2], [], [0, 0, 0, 0, 0]) ***** error ... unidfit ([1.5, 0.2], [], [1, 1, 1]) ***** error ... unidfit ([1.5, 0.2], [], [1, -1]) 11 tests, 11 passed, 0 known failure, 0 skipped [inst/dist_fit/rayllike.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/dist_fit/rayllike.m ***** test x = [1 3 2 4 5 4 3 4]; [nlogL, acov] = rayllike (3.25, x); assert (nlogL, 14.7442, 1e-4) ***** test x = [1 2 3 4 5]; f = [1 1 2 3 1]; [nlogL, acov] = rayllike (3.25, x, [], f); assert (nlogL, 14.7442, 1e-4) ***** test x = [1 2 3 4 5 6]; f = [1 1 2 3 1 0]; [nlogL, acov] = rayllike (3.25, x, [], f); assert (nlogL, 14.7442, 1e-4) ***** test x = [1 2 3 4 5 6]; c = [0 0 0 0 0 1]; f = [1 1 2 3 1 0]; [nlogL, acov] = rayllike (3.25, x, c, f); assert (nlogL, 14.7442, 1e-4) ***** error rayllike (1) ***** error rayllike ([1 2 3], [1 2]) ***** error ... rayllike (3.25, ones (10, 2)) ***** error ... rayllike (3.25, [1 2 3 -4 5]) ***** error ... rayllike (3.25, [1, 2, 3, 4, 5], [1 1 0]); ***** error ... rayllike (3.25, [1, 2, 3, 4, 5], [1 1 0 1 1]'); ***** error ... rayllike (3.25, [1, 2, 3, 4, 5], zeros (1,5), [1 1 0]); ***** error ... rayllike (3.25, [1, 2, 3, 4, 5], [], [1 1 0 1 1]'); ***** error ... rayllike (3.25, ones (1, 8), [], [1 1 1 1 1 1 1 -1]) 13 tests, 13 passed, 0 known failure, 0 skipped [inst/dist_fit/nbinlike.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/dist_fit/nbinlike.m ***** assert (nbinlike ([2.42086, 0.0867043], [1:50]), 205.5942, 1e-4) ***** assert (nbinlike ([3.58823, 0.254697], [1:20]), 63.6435, 1e-4) ***** assert (nbinlike ([8.80671, 0.615565], [1:10]), 24.7410, 1e-4) ***** assert (nbinlike ([22.1756, 0.831306], [1:8]), 17.9528, 1e-4) ***** assert (nbinlike ([22.1756, 0.831306], [1:9], [ones(1,8), 0]), 17.9528, 1e-4) ***** error nbinlike (3.25) ***** error nbinlike ([5, 0.2], ones (2)) ***** error nbinlike ([5, 0.2], [-1, 3]) ***** error ... nbinlike ([1, 0.2, 3], [1, 3, 5, 7]) ***** error nbinlike ([-5, 0.2], [1:15]) ***** error nbinlike ([0, 0.2], [1:15]) ***** error nbinlike ([5, 1.2], [3, 5]) ***** error nbinlike ([5, -0.2], [3, 5]) ***** error ... nbinlike ([5, 0.2], ones (10, 1), ones (8,1)) ***** error ... nbinlike ([5, 0.2], ones (1, 8), [1 1 1 1 1 1 1 -1]) ***** error ... nbinlike ([5, 0.2], ones (1, 8), [1 1 1 1 1 1 1 1.5]) 16 tests, 16 passed, 0 known failure, 0 skipped [inst/dist_fit/logllike.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/dist_fit/logllike.m ***** test [nlogL, acov] = logllike ([3.09717, 0.468525], [1:50]); assert (nlogL, 211.2965, 1e-4); assert (acov, [0.0131, -0.0007; -0.0007, 0.0031], 1e-4); ***** test [nlogL, acov] = logllike ([1.01124, 0.336449], [1:5]); assert (nlogL, 9.2206, 1e-4); assert (acov, [0.0712, -0.0032; -0.0032, 0.0153], 1e-4); ***** error logllike (3.25) ***** error logllike ([5, 0.2], ones (2)) ***** error ... logllike ([1, 0.2, 3], [1, 3, 5, 7]) ***** error ... logllike ([1.5, 0.2], [1:5], [0, 0, 0]) ***** error ... logllike ([1.5, 0.2], [1:5], [0, 0, 0, 0, 0], [1, 1, 1]) ***** error ... logllike ([1.5, 0.2], [1:5], [], [1, 1, 1]) 8 tests, 8 passed, 0 known failure, 0 skipped [inst/dist_fit/expfit.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/dist_fit/expfit.m ***** demo ## Sample 3 populations from 3 different exponential distibutions rande ("seed", 1); # for reproducibility r1 = exprnd (2, 4000, 1); rande ("seed", 2); # for reproducibility r2 = exprnd (5, 4000, 1); rande ("seed", 3); # for reproducibility r3 = exprnd (12, 4000, 1); r = [r1, r2, r3]; ## Plot them normalized and fix their colors hist (r, 48, 0.52); h = findobj (gca, "Type", "patch"); set (h(1), "facecolor", "c"); set (h(2), "facecolor", "g"); set (h(3), "facecolor", "r"); hold on ## Estimate their mu parameter muhat = expfit (r); ## Plot their estimated PDFs x = [0:max(r(:))]; y = exppdf (x, muhat(1)); plot (x, y, "-pr"); y = exppdf (x, muhat(2)); plot (x, y, "-sg"); y = exppdf (x, muhat(3)); plot (x, y, "-^c"); ylim ([0, 0.6]) xlim ([0, 40]) legend ({"Normalized HIST of sample 1 with μ=2", ... "Normalized HIST of sample 2 with μ=5", ... "Normalized HIST of sample 3 with μ=12", ... sprintf("PDF for sample 1 with estimated μ=%0.2f", muhat(1)), ... sprintf("PDF for sample 2 with estimated μ=%0.2f", muhat(2)), ... sprintf("PDF for sample 3 with estimated μ=%0.2f", muhat(3))}) title ("Three population samples from different exponential distibutions") hold off ***** assert (expfit (1), 1) ***** assert (expfit (1:3), 2) ***** assert (expfit ([1:3]'), 2) ***** assert (expfit (1:3, []), 2) ***** assert (expfit (1:3, [], [], []), 2) ***** assert (expfit (magic (3)), [5 5 5]) ***** assert (expfit (cat (3, magic (3), 2*magic (3))), cat (3,[5 5 5], [10 10 10])) ***** assert (expfit (1:3, 0.1, [0 0 0], [1 1 1]), 2) ***** assert (expfit ([1:3]', 0.1, [0 0 0]', [1 1 1]'), 2) ***** assert (expfit (1:3, 0.1, [0 0 0]', [1 1 1]'), 2) ***** assert (expfit (1:3, 0.1, [1 0 0], [1 1 1]), 3) ***** assert (expfit (1:3, 0.1, [0 0 0], [4 1 1]), 1.5) ***** assert (expfit (1:3, 0.1, [1 0 0], [4 1 1]), 4.5) ***** assert (expfit (1:3, 0.1, [1 0 1], [4 1 1]), 9) ***** assert (expfit (1:3, 0.1, [], [-1 1 1]), 4) ***** assert (expfit (1:3, 0.1, [], [0.5 1 1]), 2.2) ***** assert (expfit (1:3, 0.1, [1 1 1]), NaN) ***** assert (expfit (1:3, 0.1, [], [0 0 0]), NaN) ***** assert (expfit (reshape (1:9, [3 3])), [2 5 8]) ***** assert (expfit (reshape (1:9, [3 3]), [], eye(3)), [3 7.5 12]) ***** assert (expfit (reshape (1:9, [3 3]), [], 2*eye(3)), [3 7.5 12]) ***** assert (expfit (reshape (1:9, [3 3]), [], [], [2 2 2; 1 1 1; 1 1 1]), ... [1.75 4.75 7.75]) ***** assert (expfit (reshape (1:9, [3 3]), [], [], [2 2 2; 1 1 1; 1 1 1]), ... [1.75 4.75 7.75]) ***** assert (expfit (reshape (1:9, [3 3]), [], eye(3), [2 2 2; 1 1 1; 1 1 1]), ... [3.5 19/3 31/3]) ***** assert ([~,muci] = expfit (1:3, 0), [0; Inf]) ***** assert ([~,muci] = expfit (1:3, 2), [Inf; 0]) ***** assert ([~,muci] = expfit (1:3, 0.1, [1 1 1]), [NaN; NaN]) ***** assert ([~,muci] = expfit (1:3, 0.1, [], [0 0 0]), [NaN; NaN]) ***** assert ([~,muci] = expfit (1:3, -1), [NaN; NaN]) ***** assert ([~,muci] = expfit (1:3, 5), [NaN; NaN]) ***** assert ([~,muci] = expfit (1:3), [0.830485728373393; 9.698190330474096], ... 1000*eps) ***** assert ([~,muci] = expfit (1:3, 0.1), ... [0.953017262058213; 7.337731146400207], 1000*eps) ***** assert ([~,muci] = expfit ([1:3;2:4]), ... [0.538440777613095, 0.897401296021825, 1.256361814430554; ... 12.385982973214016, 20.643304955356694, 28.900626937499371], ... 1000*eps) ***** assert ([~,muci] = expfit ([1:3;2:4], [], [1 1 1; 0 0 0]), ... 100*[0.008132550920455, 0.013554251534091, 0.018975952147727; ... 1.184936706156216, 1.974894510260360, 2.764852314364504], ... 1000*eps) ***** assert ([~,muci] = expfit ([1:3;2:4], [], [], [3 3 3; 1 1 1]), ... [0.570302756652583, 1.026544961974649, 1.482787167296715; ... 4.587722594914109, 8.257900670845396, 11.928078746776684], ... 1000*eps) ***** assert ([~,muci] = expfit ([1:3;2:4], [], [0 0 0; 1 1 1], [3 3 3; 1 1 1]), ... [0.692071440311161, 1.245728592560089, 1.799385744809018; ... 8.081825275395081, 14.547285495711145, 21.012745716027212], ... 1000*eps) ***** test x = reshape (1:8, [4 2]); x(4) = NaN; [muhat,muci] = expfit (x); assert ({muhat, muci}, {[NaN, 6.5], ... [NaN, 2.965574334593430;NaN, 23.856157493553368]}, 1000*eps); ***** test x = magic (3); censor = [0 1 0; 0 1 0; 0 1 0]; freq = [1 1 0; 1 1 0; 1 1 0]; [muhat,muci] = expfit (x, [], censor, freq); assert ({muhat, muci}, {[5 NaN NaN], ... [[2.076214320933482; 24.245475826185242],NaN(2)]}, 1000*eps); ***** error expfit () ***** error expfit (1,2,3,4,5) ***** error [a b censor] = expfit (1) ***** error expfit (1, [1 2]) ***** error expfit ([-1 2 3 4 5]) ***** error expfit ([1:5], [], "test") ***** error expfit ([1:5], [], [], "test") ***** error expfit ([1:5], [], [0 0 0 0]) ***** error expfit ([1:5], [], [], [1 1 1 1]) 47 tests, 47 passed, 0 known failure, 0 skipped [inst/dist_fit/betafit.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/dist_fit/betafit.m ***** demo ## Sample 2 populations from different Beta distibutions randg ("seed", 1); # for reproducibility r1 = betarnd (2, 5, 500, 1); randg ("seed", 2); # for reproducibility r2 = betarnd (2, 2, 500, 1); r = [r1, r2]; ## Plot them normalized and fix their colors hist (r, 12, 15); h = findobj (gca, "Type", "patch"); set (h(1), "facecolor", "c"); set (h(2), "facecolor", "g"); hold on ## Estimate their shape parameters a_b_A = betafit (r(:,1)); a_b_B = betafit (r(:,2)); ## Plot their estimated PDFs x = [min(r(:)):0.01:max(r(:))]; y = betapdf (x, a_b_A(1), a_b_A(2)); plot (x, y, "-pr"); y = betapdf (x, a_b_B(1), a_b_B(2)); plot (x, y, "-sg"); ylim ([0, 4]) legend ({"Normalized HIST of sample 1 with α=2 and β=5", ... "Normalized HIST of sample 2 with α=2 and β=2", ... sprintf("PDF for sample 1 with estimated α=%0.2f and β=%0.2f", ... a_b_A(1), a_b_A(2)), ... sprintf("PDF for sample 2 with estimated α=%0.2f and β=%0.2f", ... a_b_B(1), a_b_B(2))}) title ("Two population samples from different Beta distibutions") hold off ***** test x = 0.01:0.02:0.99; [paramhat, paramci] = betafit (x); paramhat_out = [1.0199, 1.0199]; paramci_out = [0.6947, 0.6947; 1.4974, 1.4974]; assert (paramhat, paramhat_out, 1e-4); assert (paramci, paramci_out, 1e-4); ***** test x = 0.01:0.02:0.99; [paramhat, paramci] = betafit (x, 0.01); paramci_out = [0.6157, 0.6157; 1.6895, 1.6895]; assert (paramci, paramci_out, 1e-4); ***** test x = 0.00:0.02:1; [paramhat, paramci] = betafit (x); paramhat_out = [0.0875, 0.1913]; paramci_out = [0.0822, 0.1490; 0.0931, 0.2455]; assert (paramhat, paramhat_out, 1e-4); assert (paramci, paramci_out, 1e-4); ***** error betafit ([0.2, 0.5+i]); ***** error betafit (ones (2,2) * 0.5); ***** error betafit ([0.5, 1.2]); ***** error betafit ([0.1, 0.1]); ***** error betafit ([0.01:0.1:0.99], 1.2); ***** error ... betafit ([0.01:0.01:0.05], 0.05, [1, 2, 3, 2]); ***** error ... betafit ([0.01:0.01:0.05], 0.05, [1, 2, 3, 2, -1]); ***** error ... betafit ([0.01:0.01:0.05], 0.05, [1, 2, 3, 2, 1.5]); ***** error ... betafit ([0.01:0.01:0.05], 0.05, struct ("option", 234)); ***** error ... betafit ([0.01:0.01:0.05], 0.05, ones (1,5), struct ("option", 234)); 13 tests, 13 passed, 0 known failure, 0 skipped [inst/dist_fit/burrlike.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/dist_fit/burrlike.m ***** error burrlike (3.25) ***** error burrlike ([1, 2, 3], ones (2)) ***** error burrlike ([1, 2, 3], [-1, 3]) ***** error ... burrlike ([1, 2], [1, 3, 5, 7]) ***** error ... burrlike ([1, 2, 3, 4], [1, 3, 5, 7]) ***** error ... burrlike ([1, 2, 3], [1:5], [0, 0, 0]) ***** error ... burrlike ([1, 2, 3], [1:5], [0, 0, 0, 0, 0], [1, 1, 1]) ***** error ... burrlike ([1, 2, 3], [1:5], [], [1, 1, 1]) 8 tests, 8 passed, 0 known failure, 0 skipped [inst/dist_fit/logifit.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/dist_fit/logifit.m ***** demo ## Sample 3 populations from different logistic distibutions rand ("seed", 5) # for reproducibility r1 = logirnd (2, 1, 2000, 1); rand ("seed", 2) # for reproducibility r2 = logirnd (5, 2, 2000, 1); rand ("seed", 7) # for reproducibility r3 = logirnd (9, 4, 2000, 1); r = [r1, r2, r3]; ## Plot them normalized and fix their colors hist (r, [-6:20], 1); h = findobj (gca, "Type", "patch"); set (h(1), "facecolor", "c"); set (h(2), "facecolor", "g"); set (h(3), "facecolor", "r"); ylim ([0, 0.3]); xlim ([-5, 20]); hold on ## Estimate their MU and LAMBDA parameters mu_sA = logifit (r(:,1)); mu_sB = logifit (r(:,2)); mu_sC = logifit (r(:,3)); ## Plot their estimated PDFs x = [-5:0.5:20]; y = logipdf (x, mu_sA(1), mu_sA(2)); plot (x, y, "-pr"); y = logipdf (x, mu_sB(1), mu_sB(2)); plot (x, y, "-sg"); y = logipdf (x, mu_sC(1), mu_sC(2)); plot (x, y, "-^c"); hold off legend ({"Normalized HIST of sample 1 with μ=1 and s=0.5", ... "Normalized HIST of sample 2 with μ=2 and s=0.3", ... "Normalized HIST of sample 3 with μ=4 and s=0.5", ... sprintf("PDF for sample 1 with estimated μ=%0.2f and s=%0.2f", ... mu_sA(1), mu_sA(2)), ... sprintf("PDF for sample 2 with estimated μ=%0.2f and s=%0.2f", ... mu_sB(1), mu_sB(2)), ... sprintf("PDF for sample 3 with estimated μ=%0.2f and s=%0.2f", ... mu_sC(1), mu_sC(2))}) title ("Three population samples from different logistic distibutions") hold off ***** test paramhat = logifit ([1:50]); paramhat_out = [25.5, 8.7724]; assert (paramhat, paramhat_out, 1e-4); ***** test paramhat = logifit ([1:5]); paramhat_out = [3, 0.8645]; assert (paramhat, paramhat_out, 1e-4); ***** test paramhat = logifit ([1:6], [], [], [1 1 1 1 1 0]); paramhat_out = [3, 0.8645]; assert (paramhat, paramhat_out, 1e-4); ***** test paramhat = logifit ([1:5], [], [], [1 1 1 1 2]); paramhat_out = logifit ([1:5, 5]); assert (paramhat, paramhat_out, 1e-4); ***** error logifit (ones (2,5)); ***** error logifit ([1, 2, 3, 4, 5], 1.2); ***** error logifit ([1, 2, 3, 4, 5], 0); ***** error logifit ([1, 2, 3, 4, 5], "alpha"); ***** error ... logifit ([1, 2, 3, 4, 5], 0.05, [1 1 0]); ***** error ... logifit ([1, 2, 3, 4, 5], [], [1 1 0 1 1]'); ***** error ... logifit ([1, 2, 3, 4, 5], 0.05, zeros (1,5), [1 1 0]); ***** error ... logifit ([1, 2, 3, 4, 5], [], [], [1 1 0 1 1]'); ***** error ... logifit ([1, 2, 3, 4, 5], 0.05, [], [], 2); 13 tests, 13 passed, 0 known failure, 0 skipped [inst/dist_fit/gamfit.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/dist_fit/gamfit.m ***** demo ## Sample 3 populations from different Gamma distibutions randg ("seed", 5); # for reproducibility r1 = gamrnd (1, 2, 2000, 1); randg ("seed", 2); # for reproducibility r2 = gamrnd (2, 2, 2000, 1); randg ("seed", 7); # for reproducibility r3 = gamrnd (7.5, 1, 2000, 1); r = [r1, r2, r3]; ## Plot them normalized and fix their colors hist (r, 75, 4); h = findobj (gca, "Type", "patch"); set (h(1), "facecolor", "c"); set (h(2), "facecolor", "g"); set (h(3), "facecolor", "r"); ylim ([0, 0.62]); xlim ([0, 12]); hold on ## Estimate their α and β parameters a_bA = gamfit (r(:,1)); a_bB = gamfit (r(:,2)); a_bC = gamfit (r(:,3)); ## Plot their estimated PDFs x = [0.01,0.1:0.2:18]; y = gampdf (x, a_bA(1), a_bA(2)); plot (x, y, "-pr"); y = gampdf (x, a_bB(1), a_bB(2)); plot (x, y, "-sg"); y = gampdf (x, a_bC(1), a_bC(2)); plot (x, y, "-^c"); hold off legend ({"Normalized HIST of sample 1 with α=1 and β=2", ... "Normalized HIST of sample 2 with α=2 and β=2", ... "Normalized HIST of sample 3 with α=7.5 and β=1", ... sprintf("PDF for sample 1 with estimated α=%0.2f and β=%0.2f", ... a_bA(1), a_bA(2)), ... sprintf("PDF for sample 2 with estimated α=%0.2f and β=%0.2f", ... a_bB(1), a_bB(2)), ... sprintf("PDF for sample 3 with estimated α=%0.2f and β=%0.2f", ... a_bC(1), a_bC(2))}) title ("Three population samples from different Gamma distibutions") hold off ***** shared x x = [1.2 1.6 1.7 1.8 1.9 2.0 2.2 2.6 3.0 3.5 4.0 4.8 5.6 6.6 7.6]; ***** test [paramhat, paramci] = gamfit (x); assert (paramhat, [3.4248, 0.9752], 1e-4); assert (paramci, [1.7287, 0.4670; 6.7852, 2.0366], 1e-4); ***** test [paramhat, paramci] = gamfit (x, 0.01); assert (paramhat, [3.4248, 0.9752], 1e-4); assert (paramci, [1.3945, 0.3705; 8.4113, 2.5668], 1e-4); ***** test freq = [1 1 1 1 2 1 1 1 1 2 1 1 1 1 2]; [paramhat, paramci] = gamfit (x, [], [], freq); assert (paramhat, [3.3025, 1.0615], 1e-4); assert (paramci, [1.7710, 0.5415; 6.1584, 2.0806], 1e-4); ***** test [paramhat, paramci] = gamfit (x, [], [], [1:15]); assert (paramhat, [4.4484, 0.9689], 1e-4); assert (paramci, [3.4848, 0.7482; 5.6785, 1.2546], 1e-4); ***** test [paramhat, paramci] = gamfit (x, 0.01, [], [1:15]); assert (paramhat, [4.4484, 0.9689], 1e-4); assert (paramci, [3.2275, 0.6899; 6.1312, 1.3608], 1e-4); ***** test cens = [0 0 0 0 1 0 0 0 0 0 0 0 0 0 0]; [paramhat, paramci] = gamfit (x, [], cens, [1:15]); assert (paramhat, [4.7537, 0.9308], 1e-4); assert (paramci, [3.7123, 0.7162; 6.0872, 1.2097], 1e-4); ***** test cens = [0 0 0 0 1 0 0 0 0 0 0 0 0 0 0]; freq = [1 1 1 1 2 1 1 1 1 2 1 1 1 1 2]; [paramhat, paramci] = gamfit (x, [], cens, freq); assert (paramhat, [3.4736, 1.0847], 1e-4); assert (paramci, [1.8286, 0.5359; 6.5982, 2.1956], 1e-4); ***** test [paramhat, paramci] = gamfit ([1 1 1 1 1 1]); assert (paramhat, [Inf, 0]); assert (paramci, [Inf, 0; Inf, 0]); ***** test [paramhat, paramci] = gamfit ([1 1 1 1 1 1], [], [1 1 1 1 1 1]); assert (paramhat, [NaN, NaN]); assert (paramci, [NaN, NaN; NaN, NaN]); ***** test [paramhat, paramci] = gamfit ([1 1 1 1 1 1], [], [], [1 1 1 1 1 1]); assert (paramhat, [Inf, 0]); assert (paramci, [Inf, 0; Inf, 0]); ***** assert (class (gamfit (single (x))), "single") ***** error gamfit (ones (2)) ***** error gamfit (x, 1) ***** error gamfit (x, -1) ***** error gamfit (x, {0.05}) ***** error gamfit (x, "a") ***** error gamfit (x, i) ***** error gamfit (x, [0.01 0.02]) ***** error gamfit ([1 2 3], 0.05, [], [1 5]) ***** error gamfit ([1 2 3], 0.05, [], [1 5 -1]) ***** error ... gamfit ([1:10], 0.05, [], [], 5) ***** error gamfit ([1 2 3 -4]) ***** error ... gamfit ([1 2 0], [], [1 0 0]) 23 tests, 23 passed, 0 known failure, 0 skipped [inst/dist_fit/gamlike.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/dist_fit/gamlike.m ***** test [nlogL, acov] = gamlike([2, 3], [2, 3, 4, 5, 6, 7, 8, 9]); assert (nlogL, 19.4426, 1e-4); assert (acov, [2.7819, -5.0073; -5.0073, 9.6882], 1e-4); ***** test [nlogL, acov] = gamlike([2, 3], [5:45]); assert (nlogL, 305.8070, 1e-4); assert (acov, [0.0423, -0.0087; -0.0087, 0.0167], 1e-4); ***** test [nlogL, acov] = gamlike([2, 13], [5:45]); assert (nlogL, 163.2261, 1e-4); assert (acov, [0.2362, -1.6631; -1.6631, 13.9440], 1e-4); ***** error ... gamlike ([12, 15]) ***** error gamlike ([12, 15, 3], [1:50]) ***** error gamlike ([12, 3], ones (10, 2)) ***** error ... gamlike ([12, 15], [1:50], [1, 2, 3]) ***** error ... gamlike ([12, 15], [1:50], [], [1, 2, 3]) 8 tests, 8 passed, 0 known failure, 0 skipped [inst/dist_fit/lognlike.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/dist_fit/lognlike.m ***** test x = 1:50; [nlogL, avar] = lognlike ([0, 0.25], x); avar_out = [-5.4749e-03, 2.8308e-04; 2.8308e-04, -1.1916e-05]; assert (nlogL, 3962.330333301793, 1e-10); assert (avar, avar_out, 1e-7); ***** test x = 1:50; [nlogL, avar] = lognlike ([0, 0.25], x * 0.5); avar_out = [-7.6229e-03, 4.8722e-04; 4.8722e-04, -2.6754e-05]; assert (nlogL, 2473.183051225747, 1e-10); assert (avar, avar_out, 1e-7); ***** test x = 1:50; [nlogL, avar] = lognlike ([0, 0.5], x); avar_out = [-2.1152e-02, 2.2017e-03; 2.2017e-03, -1.8535e-04]; assert (nlogL, 1119.072424020455, 1e-12); assert (avar, avar_out, 1e-6); ***** test x = 1:50; censor = ones (1, 50); censor([2, 4, 6, 8, 12, 14]) = 0; [nlogL, avar] = lognlike ([0, 0.5], x, censor); avar_out = [-1.9823e-02, 2.0370e-03; 2.0370e-03, -1.6618e-04]; assert (nlogL, 1091.746371145497, 1e-12); assert (avar, avar_out, 1e-6); ***** test x = 1:50; censor = ones (1, 50); censor([2, 4, 6, 8, 12, 14]) = 0; [nlogL, avar] = lognlike ([0, 1], x, censor); avar_out = [-6.8634e-02, 1.3968e-02; 1.3968e-02, -2.1664e-03]; assert (nlogL, 349.3969104144271, 1e-12); assert (avar, avar_out, 1e-6); ***** error ... lognlike ([12, 15]); ***** error lognlike ([12, 15], ones (2)); ***** error ... lognlike ([12, 15, 3], [1:50]); ***** error ... lognlike ([12, 15], [1:50], [1, 2, 3]); ***** error ... lognlike ([12, 15], [1:50], [], [1, 2, 3]); 10 tests, 10 passed, 0 known failure, 0 skipped [inst/dist_fit/unifit.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/dist_fit/unifit.m ***** demo ## Sample 2 populations from different continuous uniform distibutions rand ("seed", 5); # for reproducibility r1 = unifrnd (2, 5, 2000, 1); rand ("seed", 6); # for reproducibility r2 = unifrnd (3, 9, 2000, 1); r = [r1, r2]; ## Plot them normalized and fix their colors hist (r, 0:0.5:10, 2); h = findobj (gca, "Type", "patch"); set (h(1), "facecolor", "c"); set (h(2), "facecolor", "g"); hold on ## Estimate their probability of success a_bA = unifit (r(:,1)); a_bB = unifit (r(:,2)); ## Plot their estimated PDFs x = [0:10]; y = unifpdf (x, a_bA(1), a_bA(2)); plot (x, y, "-pg"); y = unifpdf (x, a_bB(1), a_bB(2)); plot (x, y, "-sc"); xlim ([1, 10]) ylim ([0, 0.5]) legend ({"Normalized HIST of sample 1 with a=2 and b=5", ... "Normalized HIST of sample 2 with a=3 and b=9", ... sprintf("PDF for sample 1 with estimated a=%0.2f and b=%0.2f", ... a_bA(1), a_bA(2)), ... sprintf("PDF for sample 2 with estimated a=%0.2f and b=%0.2f", ... a_bB(1), a_bB(2))}) title ("Two population samples from different continuous uniform distibutions") hold off ***** test x = 0:5; [paramhat, paramci] = unifit (x); assert (paramhat, [0, 5]); assert (paramci, [-3.2377, 8.2377; 0, 5], 1e-4); ***** test x = 0:5; [paramhat, paramci] = unifit (x, [], [1 1 1 1 1 1]); assert (paramhat, [0, 5]); assert (paramci, [-3.2377, 8.2377; 0, 5], 1e-4); ***** assert (unifit ([1 1 2 3]), unifit ([1 2 3], [] ,[2 1 1])) ***** error unifit () ***** error unifit (-1, [1 2 3 3]) ***** error unifit (1, 0) ***** error unifit (1, 1.2) ***** error unifit (1, [0.02 0.05]) ***** error ... unifit ([1.5, 0.2], [], [0, 0, 0, 0, 0]) ***** error ... unifit ([1.5, 0.2], [], [1, -1]) ***** error ... unifit ([1.5, 0.2], [], [1, 1, 1]) 11 tests, 11 passed, 0 known failure, 0 skipped [inst/dist_fit/binofit.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/dist_fit/binofit.m ***** demo ## Sample 2 populations from different binomial distibutions rand ("seed", 1); # for reproducibility r1 = binornd (50, 0.15, 1000, 1); rand ("seed", 2); # for reproducibility r2 = binornd (100, 0.5, 1000, 1); r = [r1, r2]; ## Plot them normalized and fix their colors hist (r, 23, 0.35); h = findobj (gca, "Type", "patch"); set (h(1), "facecolor", "c"); set (h(2), "facecolor", "g"); hold on ## Estimate their probability of success pshatA = binofit (r(:,1), 50); pshatB = binofit (r(:,2), 100); ## Plot their estimated PDFs x = [min(r(:,1)):max(r(:,1))]; y = binopdf (x, 50, mean (pshatA)); plot (x, y, "-pg"); x = [min(r(:,2)):max(r(:,2))]; y = binopdf (x, 100, mean (pshatB)); plot (x, y, "-sc"); ylim ([0, 0.2]) legend ({"Normalized HIST of sample 1 with ps=0.15", ... "Normalized HIST of sample 2 with ps=0.50", ... sprintf("PDF for sample 1 with estimated ps=%0.2f", ... mean (pshatA)), ... sprintf("PDF for sample 2 with estimated ps=%0.2f", ... mean (pshatB))}) title ("Two population samples from different binomial distibutions") hold off ***** test x = 0:3; [pshat, psci] = binofit (x, 3); assert (pshat, [0, 0.3333, 0.6667, 1], 1e-4); assert (psci(1,:), [0, 0.7076], 1e-4); assert (psci(2,:), [0.0084, 0.9057], 1e-4); assert (psci(3,:), [0.0943, 0.9916], 1e-4); assert (psci(4,:), [0.2924, 1.0000], 1e-4); ***** error ... binofit ([1 2 3 4]) ***** error ... binofit ([-1, 4, 3, 2], [1, 2, 3, 3]) ***** error binofit (ones(2), [1, 2, 3, 3]) ***** error ... binofit ([1, 4, 3, 2], [1, 2, -1, 3]) ***** error ... binofit ([1, 4, 3, 2], [5, 5, 5]) ***** error ... binofit ([1, 4, 3, 2], [5, 3, 5, 5]) ***** error binofit ([1, 2, 1], 3, 1.2); ***** error binofit ([1, 2, 1], 3, 0); ***** error binofit ([1, 2, 1], 3, "alpha"); 10 tests, 10 passed, 0 known failure, 0 skipped [inst/dist_fit/explike.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/dist_fit/explike.m ***** test x = 12; beta = 5; [L, V] = explike (beta, x); expected_L = 4.0094; expected_V = 6.5789; assert (L, expected_L, 0.001); assert (V, expected_V, 0.001); ***** test x = 1:5; beta = 2; [L, V] = explike (beta, x); expected_L = 10.9657; expected_V = 0.4; assert (L, expected_L, 0.001); assert (V, expected_V, 0.001); ***** error explike () ***** error explike (2) ***** error explike ([12, 3], [1:50]) ***** error explike (3, ones (10, 2)) ***** error ... explike (3, [1:50], [1, 2, 3]) ***** error ... explike (3, [1:50], [], [1, 2, 3]) 8 tests, 8 passed, 0 known failure, 0 skipped [inst/dist_fit/nakafit.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/dist_fit/nakafit.m ***** demo ## Sample 3 populations from different Nakagami distibutions randg ("seed", 5) # for reproducibility r1 = nakarnd (0.5, 1, 2000, 1); randg ("seed", 2) # for reproducibility r2 = nakarnd (5, 1, 2000, 1); randg ("seed", 7) # for reproducibility r3 = nakarnd (2, 2, 2000, 1); r = [r1, r2, r3]; ## Plot them normalized and fix their colors hist (r, [0.05:0.1:3.5], 10); h = findobj (gca, "Type", "patch"); set (h(1), "facecolor", "c"); set (h(2), "facecolor", "g"); set (h(3), "facecolor", "r"); ylim ([0, 2.5]); xlim ([0, 3.0]); hold on ## Estimate their MU and LAMBDA parameters mu_omegaA = nakafit (r(:,1)); mu_omegaB = nakafit (r(:,2)); mu_omegaC = nakafit (r(:,3)); ## Plot their estimated PDFs x = [0.01:0.1:3.01]; y = nakapdf (x, mu_omegaA(1), mu_omegaA(2)); plot (x, y, "-pr"); y = nakapdf (x, mu_omegaB(1), mu_omegaB(2)); plot (x, y, "-sg"); y = nakapdf (x, mu_omegaC(1), mu_omegaC(2)); plot (x, y, "-^c"); legend ({"Normalized HIST of sample 1 with μ=0.5 and ω=1", ... "Normalized HIST of sample 2 with μ=5 and ω=1", ... "Normalized HIST of sample 3 with μ=2 and ω=2", ... sprintf("PDF for sample 1 with estimated μ=%0.2f and ω=%0.2f", ... mu_omegaA(1), mu_omegaA(2)), ... sprintf("PDF for sample 2 with estimated μ=%0.2f and ω=%0.2f", ... mu_omegaB(1), mu_omegaB(2)), ... sprintf("PDF for sample 3 with estimated μ=%0.2f and ω=%0.2f", ... mu_omegaC(1), mu_omegaC(2))}) title ("Three population samples from different Nakagami distibutions") hold off ***** test paramhat = nakafit ([1:50]); paramhat_out = [0.7355, 858.5]; assert (paramhat, paramhat_out, 1e-4); ***** test paramhat = nakafit ([1:5]); paramhat_out = [1.1740, 11]; assert (paramhat, paramhat_out, 1e-4); ***** test paramhat = nakafit ([1:6], [], [], [1 1 1 1 1 0]); paramhat_out = [1.1740, 11]; assert (paramhat, paramhat_out, 1e-4); ***** test paramhat = nakafit ([1:5], [], [], [1 1 1 1 2]); paramhat_out = nakafit ([1:5, 5]); assert (paramhat, paramhat_out, 1e-4); ***** error nakafit (ones (2,5)); ***** error nakafit ([1, 2, 3, 4, 5], 1.2); ***** error nakafit ([1, 2, 3, 4, 5], 0); ***** error nakafit ([1, 2, 3, 4, 5], "alpha"); ***** error ... nakafit ([1, 2, 3, 4, 5], 0.05, [1 1 0]); ***** error ... nakafit ([1, 2, 3, 4, 5], [], [1 1 0 1 1]'); ***** error ... nakafit ([1, 2, 3, 4, 5], 0.05, zeros (1,5), [1 1 0]); ***** error ... nakafit ([1, 2, 3, 4, 5], [], [], [1 1 0 1 1]'); ***** error ... nakafit ([1, 2, 3, 4, 5], [], [], [1 1 -1 1 1]); ***** error ... nakafit ([1, 2, 3, 4, 5], [], [], [1 1 1.5 1 1]); ***** error ... nakafit ([1, 2, 3, 4, 5], 0.05, [], [], 2); 15 tests, 15 passed, 0 known failure, 0 skipped [inst/dist_fit/tlslike.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/dist_fit/tlslike.m ***** test x = [-1.2352, -0.2741, 0.1726, 7.4356, 1.0392, 16.4165]; [nlogL, acov] = tlslike ([0.035893, 0.862711, 0.649261], x); acov_out = [0.2525, 0.0670, 0.0288; ... 0.0670, 0.5724, 0.1786; ... 0.0288, 0.1786, 0.1789]; assert (nlogL, 17.9979636579, 1e-10); assert (acov, acov_out, 1e-4); ***** error tlslike ([12, 15, 1]); ***** error tlslike ([12, 15], [1:50]); ***** error tlslike ([12, 3, 1], ones (10, 2)); ***** error tlslike ([12, 15, 1], [1:50], [1, 2, 3]); ***** error tlslike ([12, 15, 1], [1:50], [], [1, 2, 3]); ***** error tlslike ([12, 15, 1], [1:3], [], [1, 2, -3]); 7 tests, 7 passed, 0 known failure, 0 skipped [inst/dist_fit/bisafit.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/dist_fit/bisafit.m ***** demo ## Sample 3 populations from different Birnbaum-Saunders distibutions rand ("seed", 5); # for reproducibility r1 = bisarnd (1, 0.5, 2000, 1); rand ("seed", 2); # for reproducibility r2 = bisarnd (2, 0.3, 2000, 1); rand ("seed", 7); # for reproducibility r3 = bisarnd (4, 0.5, 2000, 1); r = [r1, r2, r3]; ## Plot them normalized and fix their colors hist (r, 80, 4.2); h = findobj (gca, "Type", "patch"); set (h(1), "facecolor", "c"); set (h(2), "facecolor", "g"); set (h(3), "facecolor", "r"); ylim ([0, 1.1]); xlim ([0, 8]); hold on ## Estimate their α and β parameters beta_gammaA = bisafit (r(:,1)); beta_gammaB = bisafit (r(:,2)); beta_gammaC = bisafit (r(:,3)); ## Plot their estimated PDFs x = [0:0.1:8]; y = bisapdf (x, beta_gammaA(1), beta_gammaA(2)); plot (x, y, "-pr"); y = bisapdf (x, beta_gammaB(1), beta_gammaB(2)); plot (x, y, "-sg"); y = bisapdf (x, beta_gammaC(1), beta_gammaC(2)); plot (x, y, "-^c"); hold off legend ({"Normalized HIST of sample 1 with β=1 and γ=0.5", ... "Normalized HIST of sample 2 with β=2 and γ=0.3", ... "Normalized HIST of sample 3 with β=4 and γ=0.5", ... sprintf("PDF for sample 1 with estimated β=%0.2f and γ=%0.2f", ... beta_gammaA(1), beta_gammaA(2)), ... sprintf("PDF for sample 2 with estimated β=%0.2f and γ=%0.2f", ... beta_gammaB(1), beta_gammaB(2)), ... sprintf("PDF for sample 3 with estimated β=%0.2f and γ=%0.2f", ... beta_gammaC(1), beta_gammaC(2))}) title ("Three population samples from different Birnbaum-Saunders distibutions") hold off ***** test paramhat = bisafit ([1:50]); paramhat_out = [16.2649, 1.0156]; assert (paramhat, paramhat_out, 1e-4); ***** test paramhat = bisafit ([1:5]); paramhat_out = [2.5585, 0.5839]; assert (paramhat, paramhat_out, 1e-4); ***** error bisafit (ones (2,5)); ***** error bisafit ([-1 2 3 4]); ***** error bisafit ([1, 2, 3, 4, 5], 1.2); ***** error bisafit ([1, 2, 3, 4, 5], 0); ***** error bisafit ([1, 2, 3, 4, 5], "alpha"); ***** error ... bisafit ([1, 2, 3, 4, 5], 0.05, [1 1 0]); ***** error ... bisafit ([1, 2, 3, 4, 5], [], [1 1 0 1 1]'); ***** error ... bisafit ([1, 2, 3, 4, 5], 0.05, zeros (1,5), [1 1 0]); ***** error ... bisafit ([1, 2, 3, 4, 5], [], [], [1 1 0 1 1]'); ***** error ... bisafit ([1, 2, 3, 4, 5], 0.05, [], [], 2); 12 tests, 12 passed, 0 known failure, 0 skipped [inst/dist_fit/gumbelfit.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/dist_fit/gumbelfit.m ***** demo ## Sample 3 populations from different Gumbel distibutions rand ("seed", 1); # for reproducibility r1 = gumbelrnd (2, 5, 400, 1); rand ("seed", 11); # for reproducibility r2 = gumbelrnd (-5, 3, 400, 1); rand ("seed", 16); # for reproducibility r3 = gumbelrnd (14, 8, 400, 1); r = [r1, r2, r3]; ## Plot them normalized and fix their colors hist (r, 25, 0.32); h = findobj (gca, "Type", "patch"); set (h(1), "facecolor", "c"); set (h(2), "facecolor", "g"); set (h(3), "facecolor", "r"); ylim ([0, 0.28]) xlim ([-11, 50]); hold on ## Estimate their MU and BETA parameters mu_betaA = gumbelfit (r(:,1)); mu_betaB = gumbelfit (r(:,2)); mu_betaC = gumbelfit (r(:,3)); ## Plot their estimated PDFs x = [min(r(:)):max(r(:))]; y = gumbelpdf (x, mu_betaA(1), mu_betaA(2)); plot (x, y, "-pr"); y = gumbelpdf (x, mu_betaB(1), mu_betaB(2)); plot (x, y, "-sg"); y = gumbelpdf (x, mu_betaC(1), mu_betaC(2)); plot (x, y, "-^c"); legend ({"Normalized HIST of sample 1 with μ=2 and β=5", ... "Normalized HIST of sample 2 with μ=-5 and β=3", ... "Normalized HIST of sample 3 with μ=14 and β=8", ... sprintf("PDF for sample 1 with estimated μ=%0.2f and β=%0.2f", ... mu_betaA(1), mu_betaA(2)), ... sprintf("PDF for sample 2 with estimated μ=%0.2f and β=%0.2f", ... mu_betaB(1), mu_betaB(2)), ... sprintf("PDF for sample 3 with estimated μ=%0.2f and β=%0.2f", ... mu_betaC(1), mu_betaC(2))}) title ("Three population samples from different Gumbel distibutions") hold off ***** test x = 1:50; [paramhat, paramci] = gumbelfit (x); paramhat_out = [18.3188, 13.0509]; paramci_out = [14.4882, 10.5294; 22.1495, 16.1763]; assert (paramhat, paramhat_out, 1e-4); assert (paramci, paramci_out, 1e-4); ***** test x = 1:50; [paramhat, paramci] = gumbelfit (x, 0.01); paramci_out = [13.2845, 9.8426; 23.3532, 17.3051]; assert (paramci, paramci_out, 1e-4); ***** error gumbelfit (ones (2,5)); ***** error ... gumbelfit (single (ones (1,5))); ***** error ... gumbelfit ([1, 2, 3, 4, NaN]); ***** error gumbelfit ([1, 2, 3, 4, 5], 1.2); ***** error ... gumbelfit ([1, 2, 3, 4, 5], 0.05, [1 1 0]); ***** error ... gumbelfit ([1, 2, 3, 4, 5], 0.05, [], [1 1 0]); ***** error gamfit ([1, 2, 3], 0.05, [], [1 5 -1]) ***** error ... gumbelfit ([1, 2, 3, 4, 5], 0.05, [], [], 2); 10 tests, 10 passed, 0 known failure, 0 skipped [inst/dist_fit/wbllike.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/dist_fit/wbllike.m ***** test x = 1:50; [nlogL, acov] = wbllike ([2.3, 1.2], x); avar_out = [0.0250, 0.0062; 0.0062, 0.0017]; assert (nlogL, 945.9589180651594, 1e-12); assert (acov, avar_out, 1e-4); ***** test x = 1:50; [nlogL, acov] = wbllike ([2.3, 1.2], x * 0.5); avar_out = [-0.3238, -0.1112; -0.1112, -0.0376]; assert (nlogL, 424.9879809704742, 6e-14); assert (acov, avar_out, 1e-4); ***** test x = 1:50; [nlogL, acov] = wbllike ([21, 15], x); avar_out = [-0.00001236, -0.00001166; -0.00001166, -0.00001009]; assert (nlogL, 1635190.328991511, 1e-8); assert (acov, avar_out, 1e-8); ***** error wbllike ([12, 15]); ***** error wbllike ([12, 15, 3], [1:50]); ***** error wbllike ([12, 3], ones (10, 2)); ***** error wbllike ([12, 15], [1:50], [1, 2, 3]); ***** error wbllike ([12, 15], [1:50], [], [1, 2, 3]); ***** error ... wbllike ([12, 15], [1:5], [], [1, 2, 3, -1, 0]); 9 tests, 9 passed, 0 known failure, 0 skipped [inst/dist_fit/invglike.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/dist_fit/invglike.m ***** test nlogL = invglike ([25.5, 19.6973], [1:50]); assert (nlogL, 219.1516, 1e-4); ***** test nlogL = invglike ([3, 8.1081], [1:5]); assert (nlogL, 9.0438, 1e-4); ***** error invglike (3.25) ***** error invglike ([5, 0.2], ones (2)) ***** error invglike ([5, 0.2], [-1, 3]) ***** error ... invglike ([1, 0.2, 3], [1, 3, 5, 7]) ***** error ... invglike ([1.5, 0.2], [1:5], [0, 0, 0]) ***** error ... invglike ([1.5, 0.2], [1:5], [0, 0, 0, 0, 0], [1, 1, 1]) ***** error ... invglike ([1.5, 0.2], [1:5], [], [1, 1, 1]) 9 tests, 9 passed, 0 known failure, 0 skipped [inst/dist_fit/wblfit.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/dist_fit/wblfit.m ***** demo ## Sample 3 populations from 3 different Weibull distibutions rande ("seed", 1); # for reproducibility r1 = wblrnd(2, 4, 2000, 1); rande ("seed", 2); # for reproducibility r2 = wblrnd(5, 2, 2000, 1); rande ("seed", 5); # for reproducibility r3 = wblrnd(1, 5, 2000, 1); r = [r1, r2, r3]; ## Plot them normalized and fix their colors hist (r, 30, [2.5 2.1 3.2]); h = findobj (gca, "Type", "patch"); set (h(1), "facecolor", "c"); set (h(2), "facecolor", "g"); set (h(3), "facecolor", "r"); ylim ([0, 2]); xlim ([0, 10]); hold on ## Estimate their lambda parameter lambda_kA = wblfit (r(:,1)); lambda_kB = wblfit (r(:,2)); lambda_kC = wblfit (r(:,3)); ## Plot their estimated PDFs x = [0:0.1:15]; y = wblpdf (x, lambda_kA(1), lambda_kA(2)); plot (x, y, "-pr"); y = wblpdf (x, lambda_kB(1), lambda_kB(2)); plot (x, y, "-sg"); y = wblpdf (x, lambda_kC(1), lambda_kC(2)); plot (x, y, "-^c"); hold off legend ({"Normalized HIST of sample 1 with λ=2 and k=4", ... "Normalized HIST of sample 2 with λ=5 and k=2", ... "Normalized HIST of sample 3 with λ=1 and k=5", ... sprintf("PDF for sample 1 with estimated λ=%0.2f and k=%0.2f", ... lambda_kA(1), lambda_kA(2)), ... sprintf("PDF for sample 2 with estimated λ=%0.2f and k=%0.2f", ... lambda_kB(1), lambda_kB(2)), ... sprintf("PDF for sample 3 with estimated λ=%0.2f and k=%0.2f", ... lambda_kC(1), lambda_kC(2))}) title ("Three population samples from different Weibull distibutions") hold off ***** test x = 1:50; [paramhat, paramci] = wblfit (x); paramhat_out = [28.3636, 1.7130]; paramci_out = [23.9531, 1.3551; 33.5861, 2.1655]; assert (paramhat, paramhat_out, 1e-4); assert (paramci, paramci_out, 1e-4); ***** test x = 1:50; [paramhat, paramci] = wblfit (x, 0.01); paramci_out = [22.7143, 1.2589; 35.4179, 2.3310]; assert (paramci, paramci_out, 1e-4); ***** error wblfit (ones (2,5)); ***** error wblfit ([-1 2 3 4]); ***** error wblfit ([1, 2, 3, 4, 5], 1.2); ***** error wblfit ([1, 2, 3, 4, 5], 0); ***** error wblfit ([1, 2, 3, 4, 5], "alpha"); ***** error ... wblfit ([1, 2, 3, 4, 5], 0.05, [1 1 0]); ***** error ... wblfit ([1, 2, 3, 4, 5], [], [1 1 0 1 1]'); ***** error ... wblfit ([1, 2, 3, 4, 5], 0.05, zeros (1,5), [1 1 0]); ***** error ... wblfit ([1, 2, 3, 4, 5], [], [], [1 1 0 -1 1]); ***** error ... wblfit ([1, 2, 3, 4, 5], [], [], [1 1 0 1 1]'); ***** error ... wblfit ([1, 2, 3, 4, 5], 0.05, [], [], 2); 13 tests, 13 passed, 0 known failure, 0 skipped [inst/dist_fit/bisalike.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/dist_fit/bisalike.m ***** test nlogL = bisalike ([16.2649, 1.0156], [1:50]); assert (nlogL, 215.5905, 1e-4); ***** test nlogL = bisalike ([2.5585, 0.5839], [1:5]); assert (nlogL, 8.9950, 1e-4); ***** error bisalike (3.25) ***** error bisalike ([5, 0.2], ones (2)) ***** error bisalike ([5, 0.2], [-1, 3]) ***** error ... bisalike ([1, 0.2, 3], [1, 3, 5, 7]) ***** error ... bisalike ([1.5, 0.2], [1:5], [0, 0, 0]) ***** error ... bisalike ([1.5, 0.2], [1:5], [0, 0, 0, 0, 0], [1, 1, 1]) ***** error ... bisalike ([1.5, 0.2], [1:5], [], [1, 1, 1]) 9 tests, 9 passed, 0 known failure, 0 skipped [inst/dist_fit/hnfit.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/dist_fit/hnfit.m ***** demo ## Sample 2 populations from different half-normal distibutions rand ("seed", 1); # for reproducibility r1 = hnrnd (0, 5, 5000, 1); rand ("seed", 2); # for reproducibility r2 = hnrnd (0, 2, 5000, 1); r = [r1, r2]; ## Plot them normalized and fix their colors hist (r, [0.5:20], 1); h = findobj (gca, "Type", "patch"); set (h(1), "facecolor", "c"); set (h(2), "facecolor", "g"); hold on ## Estimate their shape parameters mu_sigmaA = hnfit (r(:,1), 0); mu_sigmaB = hnfit (r(:,2), 0); ## Plot their estimated PDFs x = [0:0.2:10]; y = hnpdf (x, mu_sigmaA(1), mu_sigmaA(2)); plot (x, y, "-pr"); y = hnpdf (x, mu_sigmaB(1), mu_sigmaB(2)); plot (x, y, "-sg"); xlim ([0, 10]) ylim ([0, 0.5]) legend ({"Normalized HIST of sample 1 with μ=0 and σ=5", ... "Normalized HIST of sample 2 with μ=0 and σ=2", ... sprintf("PDF for sample 1 with estimated μ=%0.2f and σ=%0.2f", ... mu_sigmaA(1), mu_sigmaA(2)), ... sprintf("PDF for sample 2 with estimated μ=%0.2f and σ=%0.2f", ... mu_sigmaB(1), mu_sigmaB(2))}) title ("Two population samples from different half-normal distibutions") hold off ***** test x = 1:20; [paramhat, paramci] = hnfit (x, 0); assert (paramhat, [0, 11.9791], 1e-4); assert (paramci, [0, 9.1648; 0, 17.2987], 1e-4); ***** test x = 1:20; [paramhat, paramci] = hnfit (x, 0, 0.01); assert (paramci, [0, 8.4709; 0, 19.6487], 1e-4); ***** error hnfit () ***** error hnfit (1) ***** error hnfit ([0.2, 0.5+i], 0); ***** error hnfit (ones (2,2) * 0.5, 0); ***** error ... hnfit ([0.5, 1.2], [0, 1]); ***** error ... hnfit ([0.5, 1.2], 5+i); ***** error ... hnfit ([1:5], 2); ***** error hnfit ([0.01:0.1:0.99], 0, 1.2); ***** error hnfit ([0.01:0.1:0.99], 0, i); ***** error hnfit ([0.01:0.1:0.99], 0, -1); ***** error hnfit ([0.01:0.1:0.99], 0, [0.05, 0.01]); ***** error hnfit ([1 2 3], 0, [], [1 5]) ***** error hnfit ([1 2 3], 0, [], [1 5 -1]) 15 tests, 15 passed, 0 known failure, 0 skipped [inst/dist_fit/burrfit.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/dist_fit/burrfit.m ***** demo ## Sample 3 populations from different Burr type XII distibutions rand ("seed", 4); # for reproducibility r1 = burrrnd (3.5, 2, 2.5, 10000, 1); rand ("seed", 2); # for reproducibility r2 = burrrnd (1, 3, 1, 10000, 1); rand ("seed", 9); # for reproducibility r3 = burrrnd (0.5, 2, 3, 10000, 1); r = [r1, r2, r3]; ## Plot them normalized and fix their colors hist (r, [0.1:0.2:20], [18, 5, 3]); h = findobj (gca, "Type", "patch"); set (h(1), "facecolor", "c"); set (h(2), "facecolor", "g"); set (h(3), "facecolor", "r"); ylim ([0, 3]); xlim ([0, 5]); hold on ## Estimate their α and β parameters lambda_c_kA = burrfit (r(:,1)); lambda_c_kB = burrfit (r(:,2)); lambda_c_kC = burrfit (r(:,3)); ## Plot their estimated PDFs x = [0.01:0.15:15]; y = burrpdf (x, lambda_c_kA(1), lambda_c_kA(2), lambda_c_kA(3)); plot (x, y, "-pr"); y = burrpdf (x, lambda_c_kB(1), lambda_c_kB(2), lambda_c_kB(3)); plot (x, y, "-sg"); y = burrpdf (x, lambda_c_kC(1), lambda_c_kC(2), lambda_c_kC(3)); plot (x, y, "-^c"); hold off legend ({"Normalized HIST of sample 1 with λ=3.5, c=2, and k=2.5", ... "Normalized HIST of sample 2 with λ=1, c=3, and k=1", ... "Normalized HIST of sample 3 with λ=0.5, c=2, and k=3", ... sprintf("PDF for sample 1 with estimated λ=%0.2f, c=%0.2f, and k=%0.2f", ... lambda_c_kA(1), lambda_c_kA(2), lambda_c_kA(3)), ... sprintf("PDF for sample 2 with estimated λ=%0.2f, c=%0.2f, and k=%0.2f", ... lambda_c_kB(1), lambda_c_kB(2), lambda_c_kB(3)), ... sprintf("PDF for sample 3 with estimated λ=%0.2f, c=%0.2f, and k=%0.2f", ... lambda_c_kC(1), lambda_c_kC(2), lambda_c_kC(3))}) title ("Three population samples from different Burr type XII distibutions") hold off ***** test l = 1; c = 2; k = 3; r = burrrnd (l, c, k, 100000, 1); lambda_c_kA = burrfit (r); assert (lambda_c_kA(1), l, 0.2); assert (lambda_c_kA(2), c, 0.2); assert (lambda_c_kA(3), k, 0.3); ***** test l = 0.5; c = 1; k = 3; r = burrrnd (l, c, k, 100000, 1); lambda_c_kA = burrfit (r); assert (lambda_c_kA(1), l, 0.2); assert (lambda_c_kA(2), c, 0.2); assert (lambda_c_kA(3), k, 0.3); ***** test l = 1; c = 3; k = 1; r = burrrnd (l, c, k, 100000, 1); lambda_c_kA = burrfit (r); assert (lambda_c_kA(1), l, 0.2); assert (lambda_c_kA(2), c, 0.2); assert (lambda_c_kA(3), k, 0.3); ***** test l = 3; c = 2; k = 1; r = burrrnd (l, c, k, 100000, 1); lambda_c_kA = burrfit (r); assert (lambda_c_kA(1), l, 0.2); assert (lambda_c_kA(2), c, 0.2); assert (lambda_c_kA(3), k, 0.3); ***** test l = 4; c = 2; k = 4; r = burrrnd (l, c, k, 100000, 1); lambda_c_kA = burrfit (r); assert (lambda_c_kA(1), l, 0.2); assert (lambda_c_kA(2), c, 0.2); assert (lambda_c_kA(3), k, 0.3); ***** error burrfit (ones (2,5)); ***** error burrfit ([-1 2 3 4]); ***** error burrfit ([1, 2, 3, 4, 5], 1.2); ***** error burrfit ([1, 2, 3, 4, 5], 0); ***** error burrfit ([1, 2, 3, 4, 5], "alpha"); ***** error ... burrfit ([1, 2, 3, 4, 5], 0.05, [1 1 0]); ***** error ... burrfit ([1, 2, 3, 4, 5], [], [1 1 0 1 1]'); ***** error burrfit ([1, 2, 3, 4, 5], 0.05, [], [1, 1, 5]) ***** error burrfit ([1, 2, 3, 4, 5], 0.05, [], [1, 5, 1, 1, -1]) ***** error ... burrfit ([1:10], 0.05, [], [], 5) 15 tests, 15 passed, 0 known failure, 0 skipped [inst/cluster.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/cluster.m ***** error cluster () ***** error cluster ([1 1], "Cutoff", 1) ***** error cluster ([1 2 1], "Bogus", 1) ***** error cluster ([1 2 1], "Cutoff", -1) ***** error cluster ([1 2 1], "Cutoff", 1, "Bogus", 1) ***** test 6 tests, 6 passed, 0 known failure, 0 skipped [inst/probit.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/probit.m ***** assert (probit ([-1, 0, 0.5, 1, 2]), [NaN, -Inf, 0, Inf, NaN]) ***** assert (probit ([0.2, 0.99]), norminv ([0.2, 0.99])) ***** error probit () ***** error probit (1, 2) 4 tests, 4 passed, 0 known failure, 0 skipped [inst/cdfplot.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/cdfplot.m ***** demo x = randn(100,1); cdfplot (x); ***** test hf = figure ("visible", "off"); unwind_protect x = [2, 4, 3, 2, 4, 3, 2, 5, 6, 4]; [hCDF, stats] = cdfplot (x); assert (stats.min, 2); assert (stats.max, 6); assert (stats.median, 3.5); assert (stats.std, 1.35400640077266, 1e-14); unwind_protect_cleanup close (hf); end_unwind_protect ***** test hf = figure ("visible", "off"); unwind_protect x = randn(100,1); cdfplot (x); unwind_protect_cleanup close (hf); end_unwind_protect ***** error cdfplot (); ***** error cdfplot ([x',x']); ***** error cdfplot ([NaN, NaN, NaN, NaN]); 5 tests, 5 passed, 0 known failure, 0 skipped [inst/logit.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/logit.m ***** test p = [0.01:0.01:0.99]; assert (logit (p), log (p ./ (1-p)), 25*eps); ***** assert (logit ([-1, 0, 0.5, 1, 2]), [NaN, -Inf, 0, +Inf, NaN]) ***** error logit () ***** error logit (1, 2) 4 tests, 4 passed, 0 known failure, 0 skipped [inst/standardizeMissing.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/standardizeMissing.m ***** assert (standardizeMissing (1, 1), NaN) ***** assert (standardizeMissing (1, 0), 1) ***** assert (standardizeMissing (eye(2), 1), [NaN 0;0 NaN]) ***** assert (standardizeMissing ([1:3;4:6], [2 3; 4 5]), [1, NaN, NaN; NaN, NaN, 6]) ***** assert (standardizeMissing (cat (3,1,2,3,4), 3), cat (3,1,2,NaN,4)) ***** assert (standardizeMissing ('foo', 'a'), 'foo') ***** assert (standardizeMissing ('foo', 'f'), ' oo') ***** assert (standardizeMissing ('foo', 'o'), 'f ') ***** assert (standardizeMissing ('foo', 'oo'), 'f ') ***** assert (standardizeMissing ({'foo'}, 'f'), {'foo'}) ***** assert (standardizeMissing ({'foo'}, {'f'}), {'foo'}) ***** assert (standardizeMissing ({'foo'}, 'test'), {'foo'}) ***** assert (standardizeMissing ({'foo'}, {'test'}), {'foo'}) ***** assert (standardizeMissing ({'foo'}, 'foo'), {''}) ***** assert (standardizeMissing ({'foo'}, {'foo'}), {''}) ***** assert (standardizeMissing (['foo';'bar'], 'oar'), ['f ';'b ']) ***** assert (standardizeMissing (['foo';'bar'], ['o';'a';'r']), ['f ';'b ']) ***** assert (standardizeMissing (['foo';'bar'], ['o ';'ar']), ['f ';'b ']) ***** assert (standardizeMissing ({'foo','bar'}, 'foo'), {'','bar'}) ***** assert (standardizeMissing ({'foo','bar'}, 'f'), {'foo','bar'}) ***** assert (standardizeMissing ({'foo','bar'}, {'foo', 'a'}), {'','bar'}) ***** assert (standardizeMissing ({'foo'}, {'f', 'oo'}), {'foo'}) ***** assert (standardizeMissing ({'foo','bar'}, {'foo'}), {'','bar'}) ***** assert (standardizeMissing ({'foo','bar'}, {'foo', 'a'}), {'','bar'}) ***** assert (standardizeMissing (double (1), single (1)), double (NaN)) ***** assert (standardizeMissing (single (1), single (1)), single (NaN)) ***** assert (standardizeMissing (single (1), double (1)), single (NaN)) ***** assert (standardizeMissing (single (1), true), single (NaN)) ***** assert (standardizeMissing (double (1), int32(1)), double (NaN)) ***** assert (standardizeMissing (true, true), true) ***** assert (standardizeMissing (true, 1), true) ***** assert (standardizeMissing (int32 (1), int32 (1)), int32 (1)) ***** assert (standardizeMissing (int32 (1), 1), int32 (1)) ***** assert (standardizeMissing (uint32 (1), uint32 (1)), uint32 (1)) ***** assert (standardizeMissing (uint32 (1), 1), uint32 (1)) ***** error standardizeMissing (); ***** error standardizeMissing (1); ***** error standardizeMissing (1,2,3); ***** error standardizeMissing ({'abc', 1}, 1); ***** error standardizeMissing (struct ('a','b'), 1); ***** error <'indicator' and 'A' must have > standardizeMissing ([1 2 3], {1}); ***** error <'indicator' and 'A' must have > standardizeMissing ([1 2 3], 'a'); ***** error <'indicator' and 'A' must have > standardizeMissing ([1 2 3], struct ('a', 1)); ***** error <'indicator' and 'A' must have > standardizeMissing ('foo', 1); ***** error <'indicator' and 'A' must have > standardizeMissing ('foo', {1}); ***** error <'indicator' and 'A' must have > standardizeMissing ('foo', {'f'}); ***** error <'indicator' and 'A' must have > standardizeMissing ('foo', struct ('a', 1)); ***** error <'indicator' and 'A' must have > standardizeMissing ({'foo'}, 1); ***** error <'indicator' and 'A' must have > standardizeMissing ({'foo'}, 1); 49 tests, 49 passed, 0 known failure, 0 skipped [inst/kmeans.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/kmeans.m ***** demo ## Generate a two-cluster problem randn ("seed", 31) # for reproducibility C1 = randn (100, 2) + 1; randn ("seed", 32) # for reproducibility C2 = randn (100, 2) - 1; data = [C1; C2]; ## Perform clustering rand ("seed", 1) # for reproducibility [idx, centers] = kmeans (data, 2); ## Plot the result figure; plot (data (idx==1, 1), data (idx==1, 2), "ro"); hold on; plot (data (idx==2, 1), data (idx==2, 2), "bs"); plot (centers (:, 1), centers (:, 2), "kv", "markersize", 10); hold off; ***** demo ## Cluster data using k-means clustering, then plot the cluster regions ## Load Fisher's iris data set and use the petal lengths and widths as ## predictors load fisheriris X = meas(:,3:4); figure; plot (X(:,1), X(:,2), "k*", "MarkerSize", 5); title ("Fisher's Iris Data"); xlabel ("Petal Lengths (cm)"); ylabel ("Petal Widths (cm)"); ## Cluster the data. Specify k = 3 clusters rand ("seed", 1) # for reproducibility [idx, C] = kmeans (X, 3); x1 = min (X(:,1)):0.01:max (X(:,1)); x2 = min (X(:,2)):0.01:max (X(:,2)); [x1G, x2G] = meshgrid (x1, x2); XGrid = [x1G(:), x2G(:)]; idx2Region = kmeans (XGrid, 3, "MaxIter", 1, "Start", C); figure; gscatter (XGrid(:,1), XGrid(:,2), idx2Region, ... [0, 0.75, 0.75; 0.75, 0, 0.75; 0.75, 0.75, 0], ".."); hold on; plot (X(:,1), X(:,2), "k*", "MarkerSize", 5); title ("Fisher's Iris Data"); xlabel ("Petal Lengths (cm)"); ylabel ("Petal Widths (cm)"); legend ("Region 1", "Region 2", "Region 3", "Data", "Location", "SouthEast"); hold off ***** demo ## Partition Data into Two Clusters randn ("seed", 1) # for reproducibility r1 = randn (100, 2) * 0.75 + ones (100, 2); randn ("seed", 2) # for reproducibility r2 = randn (100, 2) * 0.5 - ones (100, 2); X = [r1; r2]; figure; plot (X(:,1), X(:,2), "."); title ("Randomly Generated Data"); rand ("seed", 1) # for reproducibility [idx, C] = kmeans (X, 2, "Distance", "cityblock", ... "Replicates", 5, "Display", "final"); figure; plot (X(idx==1,1), X(idx==1,2), "r.", "MarkerSize", 12); hold on plot(X(idx==2,1), X(idx==2,2), "b.", "MarkerSize", 12); plot (C(:,1), C(:,2), "kx", "MarkerSize", 15, "LineWidth", 3); legend ("Cluster 1", "Cluster 2", "Centroids", "Location", "NorthWest"); title ("Cluster Assignments and Centroids"); hold off ***** demo ## Assign New Data to Existing Clusters ## Generate a training data set using three distributions randn ("seed", 5) # for reproducibility r1 = randn (100, 2) * 0.75 + ones (100, 2); randn ("seed", 7) # for reproducibility r2 = randn (100, 2) * 0.5 - ones (100, 2); randn ("seed", 9) # for reproducibility r3 = randn (100, 2) * 0.75; X = [r1; r2; r3]; ## Partition the training data into three clusters by using kmeans rand ("seed", 1) # for reproducibility [idx, C] = kmeans (X, 3); ## Plot the clusters and the cluster centroids figure gscatter (X(:,1), X(:,2), idx, "bgm", "***"); hold on plot (C(:,1), C(:,2), "kx"); legend ("Cluster 1", "Cluster 2", "Cluster 3", "Cluster Centroid") ## Generate a test data set randn ("seed", 25) # for reproducibility r1 = randn (100, 2) * 0.75 + ones (100, 2); randn ("seed", 27) # for reproducibility r2 = randn (100, 2) * 0.5 - ones (100, 2); randn ("seed", 29) # for reproducibility r3 = randn (100, 2) * 0.75; Xtest = [r1; r2; r3]; ## Classify the test data set using the existing clusters ## Find the nearest centroid from each test data point by using pdist2 D = pdist2 (C, Xtest, "euclidean"); [group, ~] = find (D == min (D)); ## Plot the test data and label the test data using idx_test with gscatter gscatter (Xtest(:,1), Xtest(:,2), group, "bgm", "ooo"); legend ("Cluster 1", "Cluster 2", "Cluster 3", "Cluster Centroid", ... "Data classified to Cluster 1", "Data classified to Cluster 2", ... "Data classified to Cluster 3", "Location", "NorthWest"); title ("Assign New Data to Existing Clusters"); ***** test samples = 4; dims = 3; k = 2; [cls, c, d, z] = kmeans (rand (samples,dims), k, "start", rand (k,dims, 5), "emptyAction", "singleton"); assert (size (cls), [samples, 1]); assert (size (c), [k, dims]); assert (size (d), [k, 1]); assert (size (z), [samples, k]); ***** test samples = 4; dims = 3; k = 2; [cls, c, d, z] = kmeans (rand (samples,dims), [], "start", rand (k,dims, 5), "emptyAction", "singleton"); assert (size (cls), [samples, 1]); assert (size (c), [k, dims]); assert (size (d), [k, 1]); assert (size (z), [samples, k]); ***** test [cls, c] = kmeans ([1 0; 2 0], 2, "start", [8,0;0,8], "emptyaction", "drop"); assert (cls, [1; 1]); assert (c, [1.5, 0; NA, NA]); ***** test kmeans (rand (4,3), 2, "start", rand (2,3, 5), "replicates", 5, "emptyAction", "singleton"); ***** test kmeans (rand (3,4), 2, "start", "sample", "emptyAction", "singleton"); ***** test kmeans (rand (3,4), 2, "start", "plus", "emptyAction", "singleton"); ***** test kmeans (rand (3,4), 2, "start", "cluster", "emptyAction", "singleton"); ***** test kmeans (rand (3,4), 2, "start", "uniform", "emptyAction", "singleton"); ***** test kmeans (rand (4,3), 2, "distance", "sqeuclidean", "emptyAction", "singleton"); ***** test kmeans (rand (4,3), 2, "distance", "cityblock", "emptyAction", "singleton"); ***** test kmeans (rand (4,3), 2, "distance", "cosine", "emptyAction", "singleton"); ***** test kmeans (rand (4,3), 2, "distance", "correlation", "emptyAction", "singleton"); ***** test kmeans (rand (4,3), 2, "distance", "hamming", "emptyAction", "singleton"); ***** test kmeans ([1 0; 1.1 0], 2, "start", eye(2), "emptyaction", "singleton"); ***** error kmeans (rand (3,2), 4); ***** error kmeans ([1 0; 1.1 0], 2, "start", eye(2), "emptyaction", "panic"); ***** error kmeans (rand (4,3), 2, "start", rand (2,3, 5), "replicates", 1); ***** error kmeans (rand (4,3), 2, "start", rand (2,2)); ***** error kmeans (rand (4,3), 2, "distance", "manhattan"); ***** error kmeans (rand (3,4), 2, "start", "normal"); ***** error kmeans (rand (4,3), 2, "replicates", i); ***** error kmeans (rand (4,3), 2, "replicates", -1); ***** error kmeans (rand (4,3), 2, "replicates", []); ***** error kmeans (rand (4,3), 2, "replicates", [1 2]); ***** error kmeans (rand (4,3), 2, "replicates", "one"); ***** error kmeans (rand (4,3), 2, "MAXITER", i); ***** error kmeans (rand (4,3), 2, "MaxIter", -1); ***** error kmeans (rand (4,3), 2, "maxiter", []); ***** error kmeans (rand (4,3), 2, "maxiter", [1 2]); ***** error kmeans (rand (4,3), 2, "maxiter", "one"); ***** error kmeans ([1 0; 1.1 0], 2, "start", eye(2), "emptyaction", "error"); 31 tests, 31 passed, 0 known failure, 0 skipped [inst/glmfit.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/glmfit.m ***** test rand ("seed", 1); X = rand (50, 1); b_true = [0.4; 1.5]; mu_true = exp (b_true(1) + b_true(2) * X); randp ("seed", 1); y = poissrnd (mu_true); b = glmfit(X, y, "poisson", "link", "log"); assert(b(1), b_true(1), 0.5); assert(b(2), b_true(2), 0.5); 1 test, 1 passed, 0 known failure, 0 skipped [inst/manova1.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/manova1.m ***** demo load carbig [d,p] = manova1([MPG, Acceleration, Weight, Displacement], Origin) ***** test load carbig [d,p] = manova1([MPG, Acceleration, Weight, Displacement], Origin); assert (d, 3); assert (p, [0, 3.140583347827075e-07, 0.007510999577743149, ... 0.1934100745898493]', [1e-12, 1e-12, 1e-12, 1e-12]'); ***** test load carbig [d,p] = manova1([MPG, Acceleration, Weight], Origin); assert (d, 2); assert (p, [0, 0.00516082975137544, 0.1206528056514453]', ... [1e-12, 1e-12, 1e-12]'); 2 tests, 2 passed, 0 known failure, 0 skipped [inst/ecdf.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/ecdf.m ***** demo y = exprnd (10, 50, 1); ## random failure times are exponential(10) d = exprnd (20, 50, 1); ## drop-out times are exponential(20) t = min (y, d); ## we observe the minimum of these times censored = (y > d); ## we also observe whether the subject failed ## Calculate and plot the empirical cdf and confidence bounds [f, x, flo, fup] = ecdf (t, "censoring", censored); stairs (x, f); hold on; stairs (x, flo, "r:"); stairs (x, fup, "r:"); ## Superimpose a plot of the known true cdf xx = 0:.1:max (t); yy = 1 - exp (-xx / 10); plot (xx, yy, "g-"); hold off; ***** demo R = wblrnd (100, 2, 100, 1); ecdf (R, "Function", "survivor", "Alpha", 0.01, "Bounds", "on"); hold on x = 1:1:250; wblsurv = 1 - cdf ("weibull", x, 100, 2); plot (x, wblsurv, "g-", "LineWidth", 2) legend ("Empirical survivor function", "Lower confidence bound", ... "Upper confidence bound", "Weibull survivor function", ... "Location", "northeast"); hold off ***** error ecdf (); ***** error ecdf (randi (15,2)); ***** error ecdf ([3,2,4,3+2i,5]); ***** error kstest ([2,3,4,5,6],"tail"); ***** error kstest ([2,3,4,5,6],"tail", "whatever"); ***** error kstest ([2,3,4,5,6],"function", ""); ***** error kstest ([2,3,4,5,6],"badoption", 0.51); ***** error kstest ([2,3,4,5,6],"tail", 0); ***** error kstest ([2,3,4,5,6],"alpha", 0); ***** error kstest ([2,3,4,5,6],"alpha", NaN); ***** error kstest ([NaN,NaN,NaN,NaN,NaN],"tail", "unequal"); ***** error kstest ([2,3,4,5,6],"alpha", 0.05, "CDF", [2,3,4;1,3,4;1,2,1]); ***** test hf = figure ("visible", "off"); unwind_protect x = [2, 3, 4, 3, 5, 4, 6, 5, 8, 3, 7, 8, 9, 0]; [F, x, Flo, Fup] = ecdf (x); F_out = [0; 0.0714; 0.1429; 0.3571; 0.5; 0.6429; 0.7143; 0.7857; 0.9286; 1]; assert (F, F_out, ones (10,1) * 1e-4); x_out = [0 0 2 3 4 5 6 7 8 9]'; assert (x, x_out); Flo_out = [NaN, 0, 0, 0.1061, 0.2381, 0.3919, 0.4776, 0.5708, 0.7937, NaN]'; assert (Flo, Flo_out, ones (10,1) * 1e-4); Fup_out = [NaN, 0.2063, 0.3262, 0.6081, 0.7619, 0.8939, 0.9509, 1, 1, NaN]'; assert (Fup, Fup_out, ones (10,1) * 1e-4); unwind_protect_cleanup close (hf); end_unwind_protect ***** test hf = figure ("visible", "off"); unwind_protect x = [2, 3, 4, 3, 5, 4, 6, 5, 8, 3, 7, 8, 9, 0]; ecdf (x); unwind_protect_cleanup close (hf); end_unwind_protect 14 tests, 14 passed, 0 known failure, 0 skipped [inst/logistic_regression.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/logistic_regression.m ***** test # Output compared to following MATLAB commands # [B, DEV, STATS] = mnrfit(X,Y+1,'model','ordinal'); # P = mnrval(B,X) X = [1.489381332449196, 1.1534152241851305; ... 1.8110085304863965, 0.9449666896938425; ... -0.04453299665130296, 0.34278203449678646; ... -0.36616019468850347, 1.130254275908322; ... 0.15339143291005095, -0.7921044310668951; ... -1.6031878794469698, -1.8343471035233376; ... -0.14349521143198166, -0.6762996896828459; ... -0.4403818557740143, -0.7921044310668951; ... -0.7372685001160434, -0.027793137932169563; ... -0.11875465773681024, 0.5512305689880763]; Y = [1,1,1,1,1,0,0,0,0,0]'; [INTERCEPT, SLOPE, DEV, DL, D2L, P] = logistic_regression (Y, X, false); ***** test # Output compared to following MATLAB commands # [B, DEV, STATS] = mnrfit(X,Y+1,'model','ordinal'); load carbig X = [Acceleration Displacement Horsepower Weight]; miles = [1,1,1,1,1,1,1,1,1,1,NaN,NaN,NaN,NaN,NaN,1,1,NaN,1,1,2,2,1,2,2,2, ... 2,2,2,2,2,1,1,1,1,2,2,2,2,NaN,2,1,1,2,1,1,1,1,1,1,1,1,1,2,2,1,2, ... 2,3,3,3,3,2,2,2,2,2,2,2,1,1,1,1,1,1,1,1,1,2,1,1,1,1,1,2,2,2,2,2, ... 2,2,2,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,2,2,1,1,1,1,1,2,2,2,1,2,2, ... 2,1,1,3,2,2,2,1,2,2,1,2,2,2,1,3,2,3,2,1,1,1,1,1,1,1,1,3,2,2,3,3, ... 2,2,2,2,2,3,2,1,1,1,1,1,1,1,1,1,1,1,2,2,1,3,2,2,2,2,2,2,1,3,2,2, ... 2,2,2,3,2,2,2,2,2,1,1,1,1,2,2,2,2,3,2,3,3,2,1,1,1,3,3,2,2,2,1,2, ... 2,1,1,1,1,1,3,3,3,2,3,1,1,1,1,1,2,2,1,1,1,1,1,3,2,2,2,3,3,3,3,2, ... 2,2,4,3,3,4,3,2,2,2,2,2,2,2,2,2,2,2,1,1,2,1,1,1,3,2,2,3,2,2,2,2, ... 2,1,2,1,3,3,2,2,2,2,2,1,1,1,1,1,1,2,1,3,3,3,2,2,2,2,2,3,3,3,3,2, ... 2,2,3,4,3,3,3,2,2,2,2,3,3,3,3,3,4,2,4,4,4,3,3,4,4,3,3,3,2,3,2,3, ... 2,2,2,2,3,4,4,3,3,3,3,3,3,3,3,3,3,3,3,3,3,2,NaN,3,2,2,2,2,2,1,2, ... 2,3,3,3,2,2,2,3,3,3,3,3,3,3,3,3,3,3,2,3,2,2,3,3,2,2,4,3,2,3]'; [INTERCEPT, SLOPE, DEV, DL, D2L, P] = logistic_regression (miles, X, false); assert (DEV, 433.197174495549, 1e-05); assert (INTERCEPT(1), -16.6895155618903, 1e-05); assert (INTERCEPT(2), -11.7207818178493, 1e-05); assert (INTERCEPT(3), -8.0605768506075, 1e-05); assert (SLOPE(1), 0.104762463756714, 1e-05); assert (SLOPE(2), 0.0103357623191891, 1e-05); assert (SLOPE(3), 0.0645199313242276, 1e-05); assert (SLOPE(4), 0.00166377028388103, 1e-05); 2 tests, 2 passed, 0 known failure, 0 skipped [inst/wblplot.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/wblplot.m ***** demo x = [16 34 53 75 93 120]; wblplot (x); ***** demo x = [2 3 5 7 11 13 17 19 23 29 31 37 41 43 47 53 59 61 67]'; c = [0 1 0 1 0 1 1 1 0 0 1 0 1 0 1 1 0 1 1]'; [h, p] = wblplot (x, c); p ***** demo x = [16, 34, 53, 75, 93, 120, 150, 191, 240 ,339]; [h, p] = wblplot (x, [], [], 0.05); p ## Benchmark Reliasoft eta = 146.2545 beta 1.1973 rho = 0.9999 ***** demo x = [46 64 83 105 123 150 150]; c = [0 0 0 0 0 0 1]; f = [1 1 1 1 1 1 4]; wblplot (x, c, f, 0.05); ***** demo x = [46 64 83 105 123 150 150]; c = [0 0 0 0 0 0 1]; f = [1 1 1 1 1 1 4]; ## Subtract 30.92 from x to simulate a 3 parameter wbl with gamma = 30.92 wblplot (x - 30.92, c, f, 0.05); ***** test hf = figure ("visible", "off"); unwind_protect x = [16, 34, 53, 75, 93, 120, 150, 191, 240 ,339]; [h, p] = wblplot (x, [], [], 0.05); assert (numel (h), 4) assert (p(1), 146.2545, 1E-4) assert (p(2), 1.1973, 1E-4) assert (p(3), 0.9999, 5E-5) unwind_protect_cleanup close (hf); end_unwind_protect 1 test, 1 passed, 0 known failure, 0 skipped [inst/regress_gp.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/regress_gp.m ***** demo ## Linear fitting of 1D Data rand ("seed", 125); X = 2 * rand (5, 1) - 1; randn ("seed", 25); Y = 2 * X - 1 + 0.3 * randn (5, 1); ## Points for interpolation/extrapolation Xfit = linspace (-2, 2, 10)'; ## Fit regression model [Yfit, Yint, m] = regress_gp (X, Y, Xfit); ## Plot fitted data plot (X, Y, "xk", Xfit, Yfit, "r-", Xfit, Yint, "b-"); title ("Gaussian process regression with linear kernel"); ***** demo ## Linear fitting of 2D Data rand ("seed", 135); X = 2 * rand (4, 2) - 1; randn ("seed", 35); Y = 2 * X(:,1) - 3 * X(:,2) - 1 + 1 * randn (4, 1); ## Mesh for interpolation/extrapolation [x1, x2] = meshgrid (linspace (-1, 1, 10)); Xfit = [x1(:), x2(:)]; ## Fit regression model [Ypred, Yint, Ysd] = regress_gp (X, Y, Xfit); Ypred = reshape (Ypred, 10, 10); YintU = reshape (Yint(:,1), 10, 10); YintL = reshape (Yint(:,2), 10, 10); ## Plot fitted data plot3 (X(:,1), X(:,2), Y, ".k", "markersize", 16); hold on; h = mesh (x1, x2, Ypred, zeros (10, 10)); set (h, "facecolor", "none", "edgecolor", "yellow"); h = mesh (x1, x2, YintU, ones (10, 10)); set (h, "facecolor", "none", "edgecolor", "cyan"); h = mesh (x1, x2, YintL, ones (10, 10)); set (h, "facecolor", "none", "edgecolor", "cyan"); hold off axis tight view (75, 25) title ("Gaussian process regression with linear kernel"); ***** demo ## Projection over basis function with linear kernel pp = [2, 2, 0.3, 1]; n = 10; rand ("seed", 145); X = 2 * rand (n, 1) - 1; randn ("seed", 45); Y = polyval (pp, X) + 0.3 * randn (n, 1); ## Powers px = [sqrt(abs(X)), X, X.^2, X.^3]; ## Points for interpolation/extrapolation Xfit = linspace (-1, 1, 100)'; pxi = [sqrt(abs(Xfit)), Xfit, Xfit.^2, Xfit.^3]; ## Define a prior covariance assuming that the sqrt component is not present Sp = 100 * eye (size (px, 2) + 1); Sp(2,2) = 1; # We don't believe the sqrt(abs(X)) is present ## Fit regression model [Yfit, Yint, Ysd] = regress_gp (px, Y, pxi, Sp); ## Plot fitted data plot (X, Y, "xk;Data;", Xfit, Yfit, "r-;Estimation;", ... Xfit, polyval (pp, Xfit), "g-;True;"); axis tight axis manual hold on plot (Xfit, Yint(:,1), "m-;Upper bound;", Xfit, Yint(:,2), "b-;Lower bound;"); hold off title ("Linear kernel over basis function with prior covariance"); ***** demo ## Projection over basis function with linear kernel pp = [2, 2, 0.3, 1]; n = 10; rand ("seed", 145); X = 2 * rand (n, 1) - 1; randn ("seed", 45); Y = polyval (pp, X) + 0.3 * randn (n, 1); ## Powers px = [sqrt(abs(X)), X, X.^2, X.^3]; ## Points for interpolation/extrapolation Xfit = linspace (-1, 1, 100)'; pxi = [sqrt(abs(Xfit)), Xfit, Xfit.^2, Xfit.^3]; ## Fit regression model without any assumption on prior covariance [Yfit, Yint, Ysd] = regress_gp (px, Y, pxi); ## Plot fitted data plot (X, Y, "xk;Data;", Xfit, Yfit, "r-;Estimation;", ... Xfit, polyval (pp, Xfit), "g-;True;"); axis tight axis manual hold on plot (Xfit, Yint(:,1), "m-;Upper bound;", Xfit, Yint(:,2), "b-;Lower bound;"); hold off title ("Linear kernel over basis function without prior covariance"); ***** demo ## Projection over basis function with rbf kernel pp = [2, 2, 0.3, 1]; n = 10; rand ("seed", 145); X = 2 * rand (n, 1) - 1; randn ("seed", 45); Y = polyval (pp, X) + 0.3 * randn (n, 1); ## Powers px = [sqrt(abs(X)), X, X.^2, X.^3]; ## Points for interpolation/extrapolation Xfit = linspace (-1, 1, 100)'; pxi = [sqrt(abs(Xfit)), Xfit, Xfit.^2, Xfit.^3]; ## Fit regression model with RBF kernel (standard parameters) [Yfit, Yint, Ysd] = regress_gp (px, Y, pxi, "rbf"); ## Plot fitted data plot (X, Y, "xk;Data;", Xfit, Yfit, "r-;Estimation;", ... Xfit, polyval (pp, Xfit), "g-;True;"); axis tight axis manual hold on plot (Xfit, Yint(:,1), "m-;Upper bound;", Xfit, Yint(:,2), "b-;Lower bound;"); hold off title ("RBF kernel over basis function with standard parameters"); text (-0.5, 4, "theta = 5\n g = 0.01"); ***** demo ## Projection over basis function with rbf kernel pp = [2, 2, 0.3, 1]; n = 10; rand ("seed", 145); X = 2 * rand (n, 1) - 1; randn ("seed", 45); Y = polyval (pp, X) + 0.3 * randn (n, 1); ## Powers px = [sqrt(abs(X)), X, X.^2, X.^3]; ## Points for interpolation/extrapolation Xfit = linspace (-1, 1, 100)'; pxi = [sqrt(abs(Xfit)), Xfit, Xfit.^2, Xfit.^3]; ## Fit regression model with RBF kernel with different parameters [Yfit, Yint, Ysd] = regress_gp (px, Y, pxi, "rbf", 10, 0.01); ## Plot fitted data plot (X, Y, "xk;Data;", Xfit, Yfit, "r-;Estimation;", ... Xfit, polyval (pp, Xfit), "g-;True;"); axis tight axis manual hold on plot (Xfit, Yint(:,1), "m-;Upper bound;", Xfit, Yint(:,2), "b-;Lower bound;"); hold off title ("GP regression with RBF kernel and non default parameters"); text (-0.5, 4, "theta = 10\n g = 0.01"); ## Fit regression model with RBF kernel with different parameters [Yfit, Yint, Ysd] = regress_gp (px, Y, pxi, "rbf", 50, 0.01); ## Plot fitted data figure plot (X, Y, "xk;Data;", Xfit, Yfit, "r-;Estimation;", ... Xfit, polyval (pp, Xfit), "g-;True;"); axis tight axis manual hold on plot (Xfit, Yint(:,1), "m-;Upper bound;", Xfit, Yint(:,2), "b-;Lower bound;"); hold off title ("GP regression with RBF kernel and non default parameters"); text (-0.5, 4, "theta = 50\n g = 0.01"); ## Fit regression model with RBF kernel with different parameters [Yfit, Yint, Ysd] = regress_gp (px, Y, pxi, "rbf", 50, 0.001); ## Plot fitted data figure plot (X, Y, "xk;Data;", Xfit, Yfit, "r-;Estimation;", ... Xfit, polyval (pp, Xfit), "g-;True;"); axis tight axis manual hold on plot (Xfit, Yint(:,1), "m-;Upper bound;", Xfit, Yint(:,2), "b-;Lower bound;"); hold off title ("GP regression with RBF kernel and non default parameters"); text (-0.5, 4, "theta = 50\n g = 0.001"); ## Fit regression model with RBF kernel with different parameters [Yfit, Yint, Ysd] = regress_gp (px, Y, pxi, "rbf", 50, 0.05); ## Plot fitted data figure plot (X, Y, "xk;Data;", Xfit, Yfit, "r-;Estimation;", ... Xfit, polyval (pp, Xfit), "g-;True;"); axis tight axis manual hold on plot (Xfit, Yint(:,1), "m-;Upper bound;", Xfit, Yint(:,2), "b-;Lower bound;"); hold off title ("GP regression with RBF kernel and non default parameters"); text (-0.5, 4, "theta = 50\n g = 0.05"); ***** demo ## RBF fitting on noiseless 1D Data x = [0:2*pi/7:2*pi]'; y = 5 * sin (x); ## Predictive grid of 500 equally spaced locations xi = [-0.5:(2*pi+1)/499:2*pi+0.5]'; ## Fit regression model with RBF kernel [Yfit, Yint, Ysd] = regress_gp (x, y, xi, "rbf"); ## Plot fitted data r = mvnrnd (Yfit, diag (Ysd)', 50); plot (xi, r', "c-"); hold on plot (xi, Yfit, "r-;Estimation;", xi, Yint, "b-;Confidence interval;"); plot (x, y, ".k;Predictor points;", "markersize", 20) plot (xi, 5 * sin (xi), "-y;True Function;"); xlim ([-0.5,2*pi+0.5]); ylim ([-10,10]); hold off title ("GP regression with RBF kernel on noiseless 1D data"); text (0, -7, "theta = 5\n g = 0.01"); ***** demo ## RBF fitting on noisy 1D Data x = [0:2*pi/7:2*pi]'; x = [x; x]; y = 5 * sin (x) + randn (size (x)); ## Predictive grid of 500 equally spaced locations xi = [-0.5:(2*pi+1)/499:2*pi+0.5]'; ## Fit regression model with RBF kernel [Yfit, Yint, Ysd] = regress_gp (x, y, xi, "rbf"); ## Plot fitted data r = mvnrnd (Yfit, diag (Ysd)', 50); plot (xi, r', "c-"); hold on plot (xi, Yfit, "r-;Estimation;", xi, Yint, "b-;Confidence interval;"); plot (x, y, ".k;Predictor points;", "markersize", 20) plot (xi, 5 * sin (xi), "-y;True Function;"); xlim ([-0.5,2*pi+0.5]); ylim ([-10,10]); hold off title ("GP regression with RBF kernel on noisy 1D data"); text (0, -7, "theta = 5\n g = 0.01"); ***** error regress_gp (ones (20, 2)) ***** error regress_gp (ones (20, 2), ones (20, 1)) ***** error ... regress_gp (ones (20, 2, 3), ones (20, 1), ones (20, 2)) ***** error ... regress_gp (ones (20, 2), ones (20, 2), ones (20, 2)) ***** error ... regress_gp (ones (20, 2), ones (15, 1), ones (20, 2)) ***** error ... regress_gp (ones (20, 2), ones (20, 1), ones (20, 3)) ***** error ... regress_gp (ones (20, 2), ones (20, 1), ones (10, 2), {[3]}) ***** error ... regress_gp (ones (20, 2), ones (20, 1), ones (10, 2), "kernel") ***** error ... regress_gp (ones (20, 2), ones (20, 1), ones (10, 2), "rbf", ones (4)) ***** error ... regress_gp (ones (20, 2), ones (20, 1), ones (10, 2), "linear", 1) ***** error ... regress_gp (ones (20, 2), ones (20, 1), ones (10, 2), "rbf", "value") ***** error ... regress_gp (ones (20, 2), ones (20, 1), ones (10, 2), "rbf", {5}) ***** error ... regress_gp (ones (20, 2), ones (20, 1), ones (10, 2), ones (3), 5) ***** error ... regress_gp (ones (20, 2), ones (20, 1), ones (10, 2), "linear", 5) ***** error ... regress_gp (ones (20, 2), ones (20, 1), ones (10, 2), "rbf", 5, {5}) ***** error ... regress_gp (ones (20, 2), ones (20, 1), ones (10, 2), "rbf", 5, ones (2)) ***** error ... regress_gp (ones (20, 2), ones (20, 1), ones (10, 2), 5, 0.01, [1, 1]) ***** error ... regress_gp (ones (20, 2), ones (20, 1), ones (10, 2), 5, 0.01, "f") ***** error ... regress_gp (ones (20, 2), ones (20, 1), ones (10, 2), 5, 0.01, "f") ***** error ... regress_gp (ones (20, 2), ones (20, 1), ones (10, 2), "rbf", 5, 0.01, "f") ***** error ... regress_gp (ones (20, 2), ones (20, 1), ones (10, 2), "rbf", 5, 0.01, [1, 1]) ***** error ... regress_gp (ones (20, 2), ones (20, 1), ones (10, 2), "linear", 1) 22 tests, 22 passed, 0 known failure, 0 skipped [inst/anova1.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/anova1.m ***** demo x = meshgrid (1:6); randn ("seed", 15); # for reproducibility x = x + normrnd (0, 1, 6, 6); anova1 (x, [], 'off'); ***** demo x = meshgrid (1:6); randn ("seed", 15); # for reproducibility x = x + normrnd (0, 1, 6, 6); [p, atab] = anova1(x); ***** demo x = ones (50, 4) .* [-2, 0, 1, 5]; randn ("seed", 13); # for reproducibility x = x + normrnd (0, 2, 50, 4); groups = {"A", "B", "C", "D"}; anova1 (x, groups); ***** demo y = [54 87 45; 23 98 39; 45 64 51; 54 77 49; 45 89 50; 47 NaN 55]; g = [1 2 3 ; 1 2 3 ; 1 2 3 ; 1 2 3 ; 1 2 3 ; 1 2 3 ]; anova1 (y(:), g(:), "on", "unequal"); ***** test data = [1.006, 0.996, 0.998, 1.000, 0.992, 0.993, 1.002, 0.999, 0.994, 1.000, ... 0.998, 1.006, 1.000, 1.002, 0.997, 0.998, 0.996, 1.000, 1.006, 0.988, ... 0.991, 0.987, 0.997, 0.999, 0.995, 0.994, 1.000, 0.999, 0.996, 0.996, ... 1.005, 1.002, 0.994, 1.000, 0.995, 0.994, 0.998, 0.996, 1.002, 0.996, ... 0.998, 0.998, 0.982, 0.990, 1.002, 0.984, 0.996, 0.993, 0.980, 0.996, ... 1.009, 1.013, 1.009, 0.997, 0.988, 1.002, 0.995, 0.998, 0.981, 0.996, ... 0.990, 1.004, 0.996, 1.001, 0.998, 1.000, 1.018, 1.010, 0.996, 1.002, ... 0.998, 1.000, 1.006, 1.000, 1.002, 0.996, 0.998, 0.996, 1.002, 1.006, ... 1.002, 0.998, 0.996, 0.995, 0.996, 1.004, 1.004, 0.998, 0.999, 0.991, ... 0.991, 0.995, 0.984, 0.994, 0.997, 0.997, 0.991, 0.998, 1.004, 0.997]; group = [1:10] .* ones (10,10); group = group(:); [p, tbl] = anova1 (data, group, "off"); assert (p, 0.022661, 1e-6); assert (tbl{2,5}, 2.2969, 1e-4); assert (tbl{2,3}, 9, 0); assert (tbl{4,2}, 0.003903, 1e-6); data = reshape (data, 10, 10); [p, tbl, stats] = anova1 (data, [], "off"); assert (p, 0.022661, 1e-6); assert (tbl{2,5}, 2.2969, 1e-4); assert (tbl{2,3}, 9, 0); assert (tbl{4,2}, 0.003903, 1e-6); means = [0.998, 0.9991, 0.9954, 0.9982, 0.9919, 0.9988, 1.0015, 1.0004, 0.9983, 0.9948]; N = 10 * ones (1, 10); assert (stats.means, means, 1e-6); assert (length (stats.gnames), 10, 0); assert (stats.n, N, 0); ***** test y = [54 87 45; 23 98 39; 45 64 51; 54 77 49; 45 89 50; 47 NaN 55]; g = [1 2 3 ; 1 2 3 ; 1 2 3 ; 1 2 3 ; 1 2 3 ; 1 2 3 ]; [p, tbl] = anova1 (y(:), g(:), "off", "equal"); assert (p, 0.00004163, 1e-6); assert (tbl{2,5}, 22.573418, 1e-6); assert (tbl{2,3}, 2, 0); assert (tbl{3,3}, 14, 0); [p, tbl] = anova1 (y(:), g(:), "off", "unequal"); assert (p, 0.00208877, 1e-8); assert (tbl{2,5}, 15.523192, 1e-6); assert (tbl{2,3}, 2, 0); assert (tbl{2,4}, 7.5786897, 1e-6); 2 tests, 2 passed, 0 known failure, 0 skipped [inst/qqplot.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/qqplot.m ***** test hf = figure ("visible", "off"); unwind_protect qqplot ([2 3 3 4 4 5 6 5 6 7 8 9 8 7 8 9 0 8 7 6 5 4 6 13 8 15 9 9]); unwind_protect_cleanup close (hf); end_unwind_protect ***** error qqplot () ***** error qqplot ({1}) ***** error qqplot (ones (2,2)) ***** error qqplot (1, "foobar") ***** error qqplot ([1 2 3], "foobar") 6 tests, 6 passed, 0 known failure, 0 skipped [inst/violin.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/violin.m ***** demo clf x = zeros (9e2, 10); for i=1:10 x(:,i) = (0.1 * randn (3e2, 3) * (randn (3,1) + 1) + 2 * randn (1,3))(:); endfor h = violin (x, "color", "c"); axis tight set (h.violin, "linewidth", 2); set (gca, "xgrid", "on"); xlabel ("Variables") ylabel ("Values") ***** demo clf data = {randn(100,1)*5+140, randn(130,1)*8+135}; subplot (1,2,1) title ("Grade 3 heights - vertical"); set (gca, "xtick", 1:2, "xticklabel", {"girls"; "boys"}); violin (data, "Nbins", 10); axis tight subplot(1,2,2) title ("Grade 3 heights - horizontal"); set (gca, "ytick", 1:2, "yticklabel", {"girls"; "boys"}); violin (data, "horizontal", "Nbins", 10); axis tight ***** demo clf data = exprnd (0.1, 500,4); violin (data, "nbins", {5,10,50,100}); axis ([0 5 0 max(data(:))]) ***** demo clf data = exprnd (0.1, 500,4); violin (data, "color", jet(4)); axis ([0 5 0 max(data(:))]) ***** demo clf data = repmat(exprnd (0.1, 500,1), 1, 4); violin (data, "width", linspace (0.1,0.5,4)); axis ([0 5 0 max(data(:))]) ***** demo clf data = repmat(exprnd (0.1, 500,1), 1, 4); violin (data, "nbins", [5,10,50,100], "smoothfactor", [4 4 8 10]); axis ([0 5 0 max(data(:))]) ***** test hf = figure ("visible", "off"); unwind_protect data = exprnd (0.1, 500,4); violin (data, "color", jet(4)); axis ([0 5 0 max(data(:))]) unwind_protect_cleanup close (hf); end_unwind_protect ***** test hf = figure ("visible", "off"); unwind_protect data = {randn(100,1)*5+140, randn(130,1)*8+135}; subplot (1,2,1) title ("Grade 3 heights - vertical"); set (gca, "xtick", 1:2, "xticklabel", {"girls"; "boys"}); violin (data, "Nbins", 10); axis tight unwind_protect_cleanup close (hf); end_unwind_protect ***** test hf = figure ("visible", "off"); unwind_protect data = {randn(100,1)*5+140, randn(130,1)*8+135}; subplot (1,2,1) title ("Grade 3 heights - vertical"); set (gca, "xtick", 1:2, "xticklabel", {"girls"; "boys"}); violin (data, "Nbins", 10); axis tight subplot(1,2,2) title ("Grade 3 heights - horizontal"); set (gca, "ytick", 1:2, "yticklabel", {"girls"; "boys"}); violin (data, "horizontal", "Nbins", 10); axis tight unwind_protect_cleanup close (hf); end_unwind_protect ***** test hf = figure ("visible", "off"); unwind_protect data = repmat(exprnd (0.1, 500,1), 1, 4); violin (data, "nbins", [5,10,50,100], "smoothfactor", [4 4 8 10]); axis ([0 5 0 max(data(:))]) unwind_protect_cleanup close (hf); end_unwind_protect ***** test hf = figure ("visible", "off"); unwind_protect data = repmat(exprnd (0.1, 500,1), 1, 4); violin (data, "width", linspace (0.1,0.5,4)); axis ([0 5 0 max(data(:))]) unwind_protect_cleanup close (hf); end_unwind_protect 5 tests, 5 passed, 0 known failure, 0 skipped [inst/squareform.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/squareform.m ***** shared v, m v = 1:6; m = [0 1 2 3;1 0 4 5;2 4 0 6;3 5 6 0]; ***** assert (squareform (v), m) ***** assert (squareform (squareform (v)), v) ***** assert (squareform (m), v) ***** assert (squareform (v'), m) ***** assert (squareform (1), [0 1;1 0]) ***** assert (squareform (1, "tomatrix"), [0 1; 1 0]) ***** assert (squareform (0, "tovector"), zeros (1, 0)) ***** warning squareform ([0 1 2; 3 0 4; 5 6 0]); ***** test for c = {@single, @double, @uint8, @uint32, @uint64} f = c{1}; assert (squareform (f (v)), f (m)) assert (squareform (f (m)), f (v)) endfor 9 tests, 9 passed, 0 known failure, 0 skipped [inst/hotelling_t2test.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/hotelling_t2test.m ***** error hotelling_t2test (); ***** error ... hotelling_t2test (1); ***** error ... hotelling_t2test (ones(2,2,2)); ***** error ... hotelling_t2test (ones(20,2), [0, 0], "alpha", 1); ***** error ... hotelling_t2test (ones(20,2), [0, 0], "alpha", -0.2); ***** error ... hotelling_t2test (ones(20,2), [0, 0], "alpha", "a"); ***** error ... hotelling_t2test (ones(20,2), [0, 0], "alpha", [0.01, 0.05]); ***** error ... hotelling_t2test (ones(20,2), [0, 0], "name", 0.01); ***** error ... hotelling_t2test (ones(20,1), [0, 0]); ***** error ... hotelling_t2test (ones(4,5), [0, 0, 0, 0, 0]); ***** error ... hotelling_t2test (ones(20,5), [0, 0, 0, 0]); ***** test randn ("seed", 1); x = randn (50000, 5); [h, pval, stats] = hotelling_t2test (x); assert (h, 0); assert (stats.df1, 5); assert (stats.df2, 49995); ***** test randn ("seed", 1); x = randn (50000, 5); [h, pval, stats] = hotelling_t2test (x, ones (1, 5) * 10); assert (h, 1); assert (stats.df1, 5); assert (stats.df2, 49995); 13 tests, 13 passed, 0 known failure, 0 skipped [inst/cophenet.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/cophenet.m ***** demo randn ("seed", 5) # for reproducibility X = randn (10,2); y = pdist (X); Z = linkage (y, "average"); cophenet (Z, y) ***** error cophenet () ***** error cophenet (1) ***** error ... cophenet (ones (2,2), 1) ***** error ... cophenet ([1 2 1], "a") ***** error ... cophenet ([1 2 1], [1 2]) 5 tests, 5 passed, 0 known failure, 0 skipped [inst/randsample.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/randsample.m ***** test n = 20; k = 5; x = randsample(n, k); assert (size(x), [1 k]); x = randsample(n, k, true); assert (size(x), [1 k]); x = randsample(n, k, false); assert (size(x), [1 k]); x = randsample(n, k, true, ones(n, 1)); assert (size(x), [1 k]); x = randsample(1:n, k); assert (size(x), [1 k]); x = randsample(1:n, k, true); assert (size(x), [1 k]); x = randsample(1:n, k, false); assert (size(x), [1 k]); x = randsample(1:n, k, true, ones(n, 1)); assert (size(x), [1 k]); x = randsample((1:n)', k); assert (size(x), [k 1]); x = randsample((1:n)', k, true); assert (size(x), [k 1]); x = randsample((1:n)', k, false); assert (size(x), [k 1]); x = randsample((1:n)', k, true, ones(n, 1)); assert (size(x), [k 1]); n = 10; k = 100; x = randsample(n, k, true, 1:n); assert (size(x), [1 k]); x = randsample((1:n)', k, true); assert (size(x), [k 1]); x = randsample(k, k, false, 1:k); assert (size(x), [1 k]); 1 test, 1 passed, 0 known failure, 0 skipped [inst/chi2test.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/chi2test.m ***** error chi2test (); ***** error chi2test ([1, 2, 3, 4, 5]); ***** error chi2test ([1, 2; 2, 1+3i]); ***** error chi2test ([NaN, 6; 34, 12]); ***** error ... p = chi2test (ones (3, 3), "mutual", []); ***** error ... p = chi2test (ones (3, 3, 3), "testtype", 2); ***** error ... p = chi2test (ones (3, 3, 3), "mutual"); ***** error ... p = chi2test (ones (3, 3, 3), "joint", ["a"]); ***** error ... p = chi2test (ones (3, 3, 3), "joint", [2, 3]); ***** error ... p = chi2test (ones (3, 3, 3, 4), "mutual", []) ***** warning p = chi2test (ones (2)); ***** warning p = chi2test (ones (3, 2)); ***** warning p = chi2test (0.4 * ones (3)); ***** test x = [11, 3, 8; 2, 9, 14; 12, 13, 28]; p = chi2test (x); assert (p, 0.017787, 1e-6); ***** test x = [11, 3, 8; 2, 9, 14; 12, 13, 28]; [p, chisq] = chi2test (x); assert (chisq, 11.9421, 1e-4); ***** test x = [11, 3, 8; 2, 9, 14; 12, 13, 28]; [p, chisq, df] = chi2test (x); assert (df, 4); ***** test ***** shared x x(:,:,1) = [59, 32; 9,16]; x(:,:,2) = [55, 24;12,33]; x(:,:,3) = [107,80;17,56];%! ***** assert (chi2test (x), 2.282063427117009e-11, 1e-14); ***** assert (chi2test (x, "mutual", []), 2.282063427117009e-11, 1e-14); ***** assert (chi2test (x, "joint", 1), 1.164834895206468e-11, 1e-14); ***** assert (chi2test (x, "joint", 2), 7.771350230001417e-11, 1e-14); ***** assert (chi2test (x, "joint", 3), 0.07151361728026107, 1e-14); ***** assert (chi2test (x, "marginal", 1), 0, 1e-14); ***** assert (chi2test (x, "marginal", 2), 6.347555814301131e-11, 1e-14); ***** assert (chi2test (x, "marginal", 3), 0, 1e-14); ***** assert (chi2test (x, "conditional", 1), 0.2303114201312508, 1e-14); ***** assert (chi2test (x, "conditional", 2), 0.0958810684407079, 1e-14); ***** assert (chi2test (x, "conditional", 3), 2.648037344954446e-11, 1e-14); ***** assert (chi2test (x, "homogeneous", []), 0.4485579470993741, 1e-14); ***** test [pval, chisq, df, E] = chi2test (x); assert (chisq, 64.0982, 1e-4); assert (df, 7); assert (E(:,:,1), [42.903, 39.921; 17.185, 15.991], ones (2, 2) * 1e-3); ***** test [pval, chisq, df, E] = chi2test (x, "joint", 2); assert (chisq, 56.0943, 1e-4); assert (df, 5); assert (E(:,:,2), [40.922, 23.310; 38.078, 21.690], ones (2, 2) * 1e-3); ***** test [pval, chisq, df, E] = chi2test (x, "marginal", 3); assert (chisq, 146.6058, 1e-4); assert (df, 9); assert (E(:,1,1), [61.642; 57.358], ones (2, 1) * 1e-3); ***** test [pval, chisq, df, E] = chi2test (x, "conditional", 3); assert (chisq, 52.2509, 1e-4); assert (df, 3); assert (E(:,:,1), [53.345, 37.655; 14.655, 10.345], ones (2, 2) * 1e-3); ***** test [pval, chisq, df, E] = chi2test (x, "homogeneous", []); assert (chisq, 1.6034, 1e-4); assert (df, 2); assert (E(:,:,1), [60.827, 31.382; 7.173, 16.618], ones (2, 2) * 1e-3); 34 tests, 34 passed, 0 known failure, 0 skipped [inst/boxplot.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/boxplot.m ***** demo axis ([0, 3]); randn ("seed", 1); # for reproducibility girls = randn (10, 1) * 5 + 140; randn ("seed", 2); # for reproducibility boys = randn (13, 1) * 8 + 135; boxplot ({girls, boys}); set (gca (), "xtick", [1 2], "xticklabel", {"girls", "boys"}) title ("Grade 3 heights"); ***** demo randn ("seed", 7); # for reproducibility A = randn (10, 1) * 5 + 140; randn ("seed", 8); # for reproducibility B = randn (25, 1) * 8 + 135; randn ("seed", 9); # for reproducibility C = randn (20, 1) * 6 + 165; data = [A; B; C]; groups = [(ones (10, 1)); (ones (25, 1) * 2); (ones (20, 1) * 3)]; labels = {"Team A", "Team B", "Team C"}; pos = [2, 1, 3]; boxplot (data, groups, "Notch", "on", "Labels", labels, "Positions", pos, ... "OutlierTags", "on", "BoxStyle", "filled"); title ("Example of Group splitting with paired vectors"); ***** demo randn ("seed", 1); # for reproducibility data = randn (100, 9); boxplot (data, "notch", "on", "boxstyle", "filled", ... "colors", "ygcwkmb", "whisker", 1.2); title ("Example of different colors specified with characters"); ***** demo randn ("seed", 5); # for reproducibility data = randn (100, 13); colors = [0.7 0.7 0.7; ... 0.0 0.4 0.9; ... 0.7 0.4 0.3; ... 0.7 0.1 0.7; ... 0.8 0.7 0.4; ... 0.1 0.8 0.5; ... 0.9 0.9 0.2]; boxplot (data, "notch", "on", "boxstyle", "filled", ... "colors", colors, "whisker", 1.3, "boxwidth", "proportional"); title ("Example of different colors specified as RGB values"); ***** error boxplot ("a") ***** error boxplot ({[1 2 3], "a"}) ***** error boxplot ([1 2 3], 1, {2, 3}) ***** error boxplot ([1 2 3], {"a", "b"}) ***** error <'Notch' input argument accepts> boxplot ([1:10], "notch", "any") ***** error boxplot ([1:10], "notch", i) ***** error boxplot ([1:10], "notch", {}) ***** error boxplot (1, "symbol", 1) ***** error <'Orientation' input argument accepts only> boxplot (1, "orientation", "diagonal") ***** error boxplot (1, "orientation", {}) ***** error <'Whisker' input argument accepts only> boxplot (1, "whisker", "a") ***** error <'Whisker' input argument accepts only> boxplot (1, "whisker", [1 3]) ***** error <'OutlierTags' input argument accepts only> boxplot (3, "OutlierTags", "maybe") ***** error boxplot (3, "OutlierTags", {}) ***** error <'Sample_IDs' input argument accepts only> boxplot (1, "sample_IDs", 1) ***** error <'BoxWidth' input argument accepts only> boxplot (1, "boxwidth", 2) ***** error <'BoxWidth' input argument accepts only> boxplot (1, "boxwidth", "anything") ***** error <'Widths' input argument accepts only> boxplot (5, "widths", "a") ***** error <'Widths' input argument accepts only> boxplot (5, "widths", [1:4]) ***** error <'Widths' input argument accepts only> boxplot (5, "widths", []) ***** error <'CapWidths' input argument accepts only> boxplot (5, "capwidths", "a") ***** error <'CapWidths' input argument accepts only> boxplot (5, "capwidths", [1:4]) ***** error <'CapWidths' input argument accepts only> boxplot (5, "capwidths", []) ***** error <'BoxStyle' input argument accepts only> boxplot (1, "Boxstyle", 1) ***** error <'BoxStyle' input argument accepts only> boxplot (1, "Boxstyle", "garbage") ***** error <'Positions' input argument accepts only> boxplot (1, "positions", "aa") ***** error <'Labels' input argument accepts only> boxplot (3, "labels", [1 5]) ***** error <'Colors' input argument accepts only> boxplot (1, "colors", {}) ***** error <'Colors' input argument accepts only> boxplot (2, "colors", [1 2 3 4]) ***** error boxplot (randn (10, 3), 'Sample_IDs', {"a", "b"}) ***** error boxplot (rand (3, 3), [1 2]) ***** test hf = figure ("visible", "off"); unwind_protect [a, b] = boxplot (rand (10, 3)); assert (size (a), [7, 3]); assert (numel (b.box), 3); assert (numel (b.whisker), 12); assert (numel (b.median), 3); unwind_protect_cleanup close (hf); end_unwind_protect ***** test hf = figure ("visible", "off"); unwind_protect [~, b] = boxplot (rand (10, 3), "BoxStyle", "filled", "colors", "ybc"); assert (numel (b.box_fill), 3); unwind_protect_cleanup close (hf); end_unwind_protect 33 tests, 33 passed, 0 known failure, 0 skipped [inst/grp2idx.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/grp2idx.m ***** test in = [true false false true]; out = {[1; 2; 2; 1] {"1"; "0"} [true; false]}; assert (nthargout (1:3, @grp2idx, in), out) assert (nthargout (1:3, @grp2idx, in), nthargout (1:3, @grp2idx, in')) ***** test assert (nthargout (1:3, @grp2idx, [false, true]), {[1; 2] {"0"; "1"} [false; true]}); assert (nthargout (1:3, @grp2idx, [true, false]), {[1; 2] {"1"; "0"} [true; false]}); ***** assert (nthargout (1:3, @grp2idx, ["oct"; "sci"; "oct"; "oct"; "sci"]), {[1; 2; 1; 1; 2] {"oct"; "sci"} ["oct"; "sci"]}); ***** assert (nthargout (1:3, @grp2idx, {"oct"; "sci"; "oct"; "oct"; "sci"}), {[1; 2; 1; 1; 2] {"oct"; "sci"} {"oct"; "sci"}}); ***** assert (nthargout (1:3, @grp2idx, [ 1 -3 -2 -3 -3 2 1 -1 3 -3]), {[1; 2; 3; 2; 2; 4; 1; 5; 6; 2], {"1"; "-3"; "-2"; "2"; "-1"; "3"}, ... [1; -3; -2; 2; -1; 3]}); ***** assert (nthargout (1:3, @grp2idx, [2 2 3 NaN 2 3]), {[1; 1; 2; NaN; 1; 2] {"2"; "3"} [2; 3]}) ***** assert (nthargout (1:3, @grp2idx, {"et" "sa" "sa" "" "et"}), {[1; 2; 2; NaN; 1] {"et"; "sa"} {"et"; "sa"}}) ***** test assert (nthargout (1:3, @grp2idx, ["sci"; "oct"; "sci"; "oct"; "oct"]), {[1; 2; 1; 2; 2] {"sci"; "oct"} ["sci"; "oct"]}); ***** test assert (nthargout (1:3, @grp2idx, {"sci"; "oct"; "sci"; "oct"; "oct"}), {[1; 2; 1; 2; 2] {"sci"; "oct"} {"sci"; "oct"}}); ***** test assert (nthargout (1:3, @grp2idx, {"sa" "et" "et" "" "sa"}), {[1; 2; 2; NaN; 1] {"sa"; "et"} {"sa"; "et"}}) 10 tests, 10 passed, 0 known failure, 0 skipped [inst/slicesample.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/slicesample.m ***** demo ## Define function to sample d = 2; mu = [-1; 2]; rand ("seed", 5) # for reproducibility Sigma = rand (d); Sigma = (Sigma + Sigma'); Sigma += eye (d)*abs (eigs (Sigma, 1, "sa")) * 1.1; pdf = @(x)(2*pi)^(-d/2)*det(Sigma)^-.5*exp(-.5*sum((x.'-mu).*(Sigma\(x.'-mu)),1)); ## Inputs start = ones (1,2); nsamples = 500; K = 500; m = 10; rande ("seed", 4); rand ("seed", 5) # for reproducibility [smpl, accept] = slicesample (start, nsamples, "pdf", pdf, "burnin", K, "thin", m, "width", [20, 30]); figure; hold on; plot (smpl(:,1), smpl(:,2), 'x'); [x, y] = meshgrid (linspace (-6,4), linspace(-3,7)); z = reshape (pdf ([x(:), y(:)]), size(x)); mesh (x, y, z, "facecolor", "None"); ## Using sample points to find the volume of half a sphere with radius of .5 f = @(x) ((.25-(x(:,1)+1).^2-(x(:,2)-2).^2).^.5.*(((x(:,1)+1).^2+(x(:,2)-2).^2)<.25)).'; int = mean (f (smpl) ./ pdf (smpl)); errest = std (f (smpl) ./ pdf (smpl)) / nsamples^.5; trueerr = abs (2/3*pi*.25^(3/2)-int); fprintf ("Monte Carlo integral estimate int f(x) dx = %f\n", int); fprintf ("Monte Carlo integral error estimate %f\n", errest); fprintf ("The actual error %f\n", trueerr); mesh (x,y,reshape (f([x(:), y(:)]), size(x)), "facecolor", "None"); ***** demo ## Integrate truncated normal distribution to find normilization constant pdf = @(x) exp (-.5*x.^2)/(pi^.5*2^.5); nsamples = 1e3; rande ("seed", 4); rand ("seed", 5) # for reproducibility [smpl, accept] = slicesample (1, nsamples, "pdf", pdf, "thin", 4); f = @(x) exp (-.5 * x .^ 2) .* (x >= -2 & x <= 2); x = linspace (-3, 3, 1000); area (x, f(x)); xlabel ("x"); ylabel ("f(x)"); int = mean (f (smpl) ./ pdf (smpl)); errest = std (f (smpl) ./ pdf (smpl)) / nsamples ^ 0.5; trueerr = abs (erf (2 ^ 0.5) * 2 ^ 0.5 * pi ^ 0.5 - int); fprintf("Monte Carlo integral estimate int f(x) dx = %f\n", int); fprintf("Monte Carlo integral error estimate %f\n", errest); fprintf("The actual error %f\n", trueerr); ***** test start = 0.5; nsamples = 1e3; pdf = @(x) exp (-.5*(x-1).^2)/(2*pi)^.5; [smpl, accept] = slicesample (start, nsamples, "pdf", pdf, "thin", 2, "burnin", 0, "width", 5); assert (mean (smpl, 1), 1, .1); assert (var (smpl, 1), 1, .2); ***** error slicesample (); ***** error slicesample (1); ***** error slicesample (1, 1); 4 tests, 4 passed, 0 known failure, 0 skipped [inst/confusionmat.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/confusionmat.m ***** test Yt = [8 5 6 8 5 3 1 6 4 2 5 3 1 4]'; Yp = [8 5 6 8 5 2 3 4 4 5 5 7 2 6]'; C = [0 1 1 0 0 0 0 0; 0 0 0 0 1 0 0 0; 0 1 0 0 0 0 1 0; 0 0 0 1 0 1 0 0; ... 0 0 0 0 3 0 0 0; 0 0 0 1 0 1 0 0; 0 0 0 0 0 0 0 0; 0 0 0 0 0 0 0 2]; assert (confusionmat (Yt, Yp), C) 1 test, 1 passed, 0 known failure, 0 skipped [inst/cl_multinom.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/cl_multinom.m ***** demo CL = cl_multinom ([27; 43; 19; 11], 10000, 0.05) ***** error cl_multinom (); ***** error cl_multinom (1, 2, 3, 4, 5); ***** error ... cl_multinom (1, 2, 3, 4); ***** error ... cl_multinom (1, 2, 3, "some string"); 4 tests, 4 passed, 0 known failure, 0 skipped [inst/barttest.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/barttest.m ***** error barttest () ***** error barttest ([2,NaN;3,4]) ***** error barttest (ones (30, 4), "alpha") ***** error barttest (ones (30, 4), 0) ***** error barttest (ones (30, 4), 1.2) ***** error barttest (ones (30, 4), [0.2, 0.05]) ***** error barttest (ones (30, 1)) ***** error barttest (ones (30, 1), 0.05) ***** test x = [2, 3, 4, 5, 6, 7, 8, 9; 1, 2, 3, 4, 5, 6, 7, 8]'; [ndim, pval, chisq] = barttest (x); assert (ndim, 2); assert (pval, 0); ## assert (chisq, 512.0558, 1e-4); Result differs between octave 6 and 7 ? ***** test x = [0.53767, 0.62702, -0.10224, -0.25485, 1.4193, 1.5237 ; ... 1.8339, 1.6452, -0.24145, -0.23444, 0.29158, 0.1634 ; ... -2.2588, -2.1351, 0.31286, 0.39396, 0.19781, 0.20995 ; ... 0.86217, 1.0835, 0.31286, 0.46499, 1.5877, 1.495 ; ... 0.31877, 0.38454, -0.86488, -0.63839, -0.80447, -0.7536 ; ... -1.3077, -1.1487, -0.030051, -0.017629, 0.69662, 0.60497 ; ... -0.43359, -0.32672, -0.16488, -0.37364, 0.83509, 0.89586 ; ... 0.34262, 0.29639, 0.62771, 0.51672, -0.24372, -0.13698 ; ... 3.5784, 3.5841, 1.0933, 0.93258, 0.21567, 0.455 ; ... 2.7694, 2.6307, 1.1093, 1.4298, -1.1658, -1.1816 ; ... -1.3499, -1.2111, -0.86365, -0.94186, -1.148, -1.4381 ; ... 3.0349, 2.8428, 0.077359, 0.18211, 0.10487, -0.014613; ... 0.7254, 0.56737, -1.2141, -1.2291, 0.72225, 0.90612 ; ... -0.063055,-0.17662, -1.1135, -0.97701, 2.5855, 2.4084 ; ... 0.71474, 0.29225, -0.0068493, -0.11468, -0.66689, -0.52466 ; ... -0.20497, -7.8874e-06, 1.5326, 1.3195, 0.18733, 0.20296 ; ... -0.12414, -0.077029, -0.76967, -0.96262, -0.082494, 0.121 ; ... 1.4897, 1.3683, 0.37138, 0.43653, -1.933, -2.1903 ; ... 1.409, 1.5882, -0.22558, -0.24835, -0.43897, -0.46247 ; ... 1.4172, 1.1616, 1.1174, 1.0785, -1.7947, -1.9471 ]; [ndim, pval, chisq] = barttest (x); assert (ndim, 3); assert (pval, [0; 0; 0; 0.52063; 0.34314], 1e-5); chisq_out = [251.6802; 210.2670; 153.1773; 4.2026; 2.1392]; assert (chisq, chisq_out, 1e-4); 10 tests, 10 passed, 0 known failure, 0 skipped [inst/dist_fun/gevpdf.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/dist_fun/gevpdf.m ***** demo ## Plot various PDFs from the generalized extreme value distribution x = -1:0.001:10; y1 = gevpdf (x, 1, 1, 1); y2 = gevpdf (x, 0.5, 1, 1); y3 = gevpdf (x, 1, 1, 5); y4 = gevpdf (x, 1, 2, 5); y5 = gevpdf (x, 1, 5, 5); y6 = gevpdf (x, 1, 0.5, 5); plot (x, y1, "-b", x, y2, "-g", x, y3, "-r", ... x, y4, "-c", x, y5, "-m", x, y6, "-k") grid on xlim ([-1, 10]) ylim ([0, 1.1]) legend ({"k = 1, σ = 1, μ = 1", "k = 0.5, σ = 1, μ = 1", ... "k = 1, σ = 1, μ = 5", "k = 1, σ = 2, μ = 5", ... "k = 1, σ = 5, μ = 5", "k = 1, σ = 0.5, μ = 5"}, ... "location", "northeast") title ("Generalized extreme value PDF") xlabel ("values in x") ylabel ("density") ***** test x = 0:0.5:2.5; sigma = 1:6; k = 1; mu = 0; y = gevpdf (x, k, sigma, mu); expected_y = [0.367879 0.143785 0.088569 0.063898 0.049953 0.040997]; assert (y, expected_y, 0.001); ***** test x = -0.5:0.5:2.5; sigma = 0.5; k = 1; mu = 0; y = gevpdf (x, k, sigma, mu); expected_y = [0 0.735759 0.303265 0.159229 0.097350 0.065498 0.047027]; assert (y, expected_y, 0.001); ***** test # check for continuity for k near 0 x = 1; sigma = 0.5; k = -0.03:0.01:0.03; mu = 0; y = gevpdf (x, k, sigma, mu); expected_y = [0.23820 0.23764 0.23704 0.23641 0.23576 0.23508 0.23438]; assert (y, expected_y, 0.001); ***** error gevpdf () ***** error gevpdf (1) ***** error gevpdf (1, 2) ***** error gevpdf (1, 2, 3) ***** error ... gevpdf (ones (3), ones (2), ones(2), ones(2)) ***** error ... gevpdf (ones (2), ones (3), ones(2), ones(2)) ***** error ... gevpdf (ones (2), ones (2), ones(3), ones(2)) ***** error ... gevpdf (ones (2), ones (2), ones(2), ones(3)) ***** error gevpdf (i, 2, 3, 4) ***** error gevpdf (1, i, 3, 4) ***** error gevpdf (1, 2, i, 4) ***** error gevpdf (1, 2, 3, i) 15 tests, 15 passed, 0 known failure, 0 skipped [inst/dist_fun/plinv.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/dist_fun/plinv.m ***** demo ## Plot various iCDFs from the Piecewise linear distribution p = 0.001:0.001:0.999; x1 = [0, 1, 3, 4, 7, 10]; Fx1 = [0, 0.2, 0.5, 0.6, 0.7, 1]; x2 = [0, 2, 5, 6, 7, 8]; Fx2 = [0, 0.1, 0.3, 0.6, 0.9, 1]; data1 = plinv (p, x1, Fx1); data2 = plinv (p, x2, Fx2); plot (p, data1, "-b", p, data2, "-g") grid on legend ({"x1, Fx1", "x2, Fx2"}, "location", "northwest") title ("Piecewise linear iCDF") xlabel ("probability") ylabel ("values in data") ***** test p = 0:0.2:1; data = plinv (p, [0, 1], [0, 1]); assert (data, p); ***** test p = 0:0.2:1; data = plinv (p, [0, 2], [0, 1]); assert (data, 2 * p); ***** test p = 0:0.2:1; data_out = 1:6; data = plinv (p, [0, 1], [0, 0.5]); assert (data, [0, 0.4, 0.8, NA, NA, NA]); ***** test p = 0:0.2:1; data_out = 1:6; data = plinv (p, [0, 0.5], [0, 1]); assert (data, [0:0.1:0.5]); ***** error plinv () ***** error plinv (1) ***** error plinv (1, 2) ***** error ... plinv (1, [0, 1, 2], [0, 1]) ***** error ... plinv (1, [0], [1]) ***** error ... plinv (1, [0, 1, 2], [0, 1, 1.5]) ***** error ... plinv (1, [0, 1, 2], [0, i, 1]) ***** error ... plinv (i, [0, 1, 2], [0, 0.5, 1]) ***** error ... plinv (1, [0, i, 2], [0, 0.5, 1]) ***** error ... plinv (1, [0, 1, 2], [0, 0.5i, 1]) 14 tests, 14 passed, 0 known failure, 0 skipped [inst/dist_fun/unidinv.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/dist_fun/unidinv.m ***** demo ## Plot various iCDFs from the discrete uniform distribution p = 0.001:0.001:0.999; x1 = unidinv (p, 5); x2 = unidinv (p, 9); plot (p, x1, "-b", p, x2, "-g") grid on xlim ([0, 1]) ylim ([0, 10]) legend ({"N = 5", "N = 9"}, "location", "northwest") title ("Discrete uniform iCDF") xlabel ("probability") ylabel ("values in x") ***** shared p p = [-1 0 0.5 1 2]; ***** assert (unidinv (p, 10*ones (1,5)), [NaN NaN 5 10 NaN], eps) ***** assert (unidinv (p, 10), [NaN NaN 5 10 NaN], eps) ***** assert (unidinv (p, 10*[0 1 NaN 1 1]), [NaN NaN NaN 10 NaN], eps) ***** assert (unidinv ([p(1:2) NaN p(4:5)], 10), [NaN NaN NaN 10 NaN], eps) ***** assert (unidinv ([p, NaN], 10), [NaN NaN 5 10 NaN NaN], eps) ***** assert (unidinv (single ([p, NaN]), 10), single ([NaN NaN 5 10 NaN NaN]), eps) ***** assert (unidinv ([p, NaN], single (10)), single ([NaN NaN 5 10 NaN NaN]), eps) ***** error unidinv () ***** error unidinv (1) ***** error ... unidinv (ones (3), ones (2)) ***** error ... unidinv (ones (2), ones (3)) ***** error unidinv (i, 2) ***** error unidinv (2, i) 13 tests, 13 passed, 0 known failure, 0 skipped [inst/dist_fun/nbinpdf.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/dist_fun/nbinpdf.m ***** demo ## Plot various PDFs from the negative binomial distribution x = 0:40; y1 = nbinpdf (x, 2, 0.15); y2 = nbinpdf (x, 5, 0.2); y3 = nbinpdf (x, 4, 0.4); y4 = nbinpdf (x, 10, 0.3); plot (x, y1, "*r", x, y2, "*g", x, y3, "*k", x, y4, "*m") grid on xlim ([0, 40]) ylim ([0, 0.12]) legend ({"r = 2, ps = 0.15", "r = 5, ps = 0.2", "r = 4, p = 0.4", ... "r = 10, ps = 0.3"}, "location", "northeast") title ("Negative binomial PDF") xlabel ("values in x (number of failures)") ylabel ("density") ***** shared x, y x = [-1 0 1 2 Inf]; y = [0 1/2 1/4 1/8 NaN]; ***** assert (nbinpdf (x, ones (1,5), 0.5*ones (1,5)), y) ***** assert (nbinpdf (x, 1, 0.5*ones (1,5)), y) ***** assert (nbinpdf (x, ones (1,5), 0.5), y) ***** assert (nbinpdf (x, [0 1 NaN 1.5 Inf], 0.5), [NaN 1/2 NaN 1.875*0.5^1.5/4 NaN], eps) ***** assert (nbinpdf (x, 1, 0.5*[-1 NaN 4 1 1]), [NaN NaN NaN y(4:5)]) ***** assert (nbinpdf ([x, NaN], 1, 0.5), [y, NaN]) ***** assert (nbinpdf (single ([x, NaN]), 1, 0.5), single ([y, NaN])) ***** assert (nbinpdf ([x, NaN], single (1), 0.5), single ([y, NaN])) ***** assert (nbinpdf ([x, NaN], 1, single (0.5)), single ([y, NaN])) ***** error nbinpdf () ***** error nbinpdf (1) ***** error nbinpdf (1, 2) ***** error ... nbinpdf (ones (3), ones (2), ones (2)) ***** error ... nbinpdf (ones (2), ones (3), ones (2)) ***** error ... nbinpdf (ones (2), ones (2), ones (3)) ***** error nbinpdf (i, 2, 2) ***** error nbinpdf (2, i, 2) ***** error nbinpdf (2, 2, i) 18 tests, 18 passed, 0 known failure, 0 skipped [inst/dist_fun/fcdf.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/dist_fun/fcdf.m ***** demo ## Plot various CDFs from the F distribution x = 0.01:0.01:4; p1 = fcdf (x, 1, 2); p2 = fcdf (x, 2, 1); p3 = fcdf (x, 5, 2); p4 = fcdf (x, 10, 1); p5 = fcdf (x, 100, 100); plot (x, p1, "-b", x, p2, "-g", x, p3, "-r", x, p4, "-c", x, p5, "-m") grid on legend ({"df1 = 1, df2 = 2", "df1 = 2, df2 = 1", ... "df1 = 5, df2 = 2", "df1 = 10, df2 = 1", ... "df1 = 100, df2 = 100"}, "location", "southeast") title ("F CDF") xlabel ("values in x") ylabel ("probability") ***** shared x, y x = [-1, 0, 0.5, 1, 2, Inf]; y = [0, 0, 1/3, 1/2, 2/3, 1]; ***** assert (fcdf (x, 2*ones (1,6), 2*ones (1,6)), y, eps) ***** assert (fcdf (x, 2, 2*ones (1,6)), y, eps) ***** assert (fcdf (x, 2*ones (1,6), 2), y, eps) ***** assert (fcdf (x, [0 NaN Inf 2 2 2], 2), [NaN NaN 0.1353352832366127 y(4:6)], eps) ***** assert (fcdf (x, 2, [0 NaN Inf 2 2 2]), [NaN NaN 0.3934693402873666 y(4:6)], eps) ***** assert (fcdf ([x(1:2) NaN x(4:6)], 2, 2), [y(1:2) NaN y(4:6)], eps) ***** assert (fcdf ([x, NaN], 2, 2), [y, NaN], eps) ***** assert (fcdf (single ([x, NaN]), 2, 2), single ([y, NaN]), eps ("single")) ***** assert (fcdf ([x, NaN], single (2), 2), single ([y, NaN]), eps ("single")) ***** assert (fcdf ([x, NaN], 2, single (2)), single ([y, NaN]), eps ("single")) ***** error fcdf () ***** error fcdf (1) ***** error fcdf (1, 2) ***** error fcdf (1, 2, 3, 4) ***** error fcdf (1, 2, 3, "tail") ***** error ... fcdf (ones (3), ones (2), ones (2)) ***** error ... fcdf (ones (2), ones (3), ones (2)) ***** error ... fcdf (ones (2), ones (2), ones (3)) ***** error fcdf (i, 2, 2) ***** error fcdf (2, i, 2) ***** error fcdf (2, 2, i) 21 tests, 21 passed, 0 known failure, 0 skipped [inst/dist_fun/plpdf.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/dist_fun/plpdf.m ***** demo ## Plot various PDFs from the Piecewise linear distribution data = 0:0.01:10; x1 = [0, 1, 3, 4, 7, 10]; Fx1 = [0, 0.2, 0.5, 0.6, 0.7, 1]; x2 = [0, 2, 5, 6, 7, 8]; Fx2 = [0, 0.1, 0.3, 0.6, 0.9, 1]; y1 = plpdf (data, x1, Fx1); y2 = plpdf (data, x2, Fx2); plot (data, y1, "-b", data, y2, "g") grid on ylim ([0, 0.6]) xlim ([0, 10]) legend ({"x1, Fx1", "x2, Fx2"}, "location", "northeast") title ("Piecewise linear CDF") xlabel ("values in data") ylabel ("density") ***** shared x, Fx x = [0, 1, 3, 4, 7, 10]; Fx = [0, 0.2, 0.5, 0.6, 0.7, 1]; ***** assert (plpdf (0.5, x, Fx), 0.2, eps); ***** assert (plpdf (1.5, x, Fx), 0.15, eps); ***** assert (plpdf (3.5, x, Fx), 0.1, eps); ***** assert (plpdf (5, x, Fx), 0.1/3, eps); ***** assert (plpdf (8, x, Fx), 0.1, eps); ***** error plpdf () ***** error plpdf (1) ***** error plpdf (1, 2) ***** error ... plpdf (1, [0, 1, 2], [0, 1]) ***** error ... plpdf (1, [0], [1]) ***** error ... plpdf (1, [0, 1, 2], [0, 1, 1.5]) ***** error ... plpdf (1, [0, 1, 2], [0, i, 1]) ***** error ... plpdf (i, [0, 1, 2], [0, 0.5, 1]) ***** error ... plpdf (1, [0, i, 2], [0, 0.5, 1]) ***** error ... plpdf (1, [0, 1, 2], [0, 0.5i, 1]) 15 tests, 15 passed, 0 known failure, 0 skipped [inst/dist_fun/burrpdf.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/dist_fun/burrpdf.m ***** demo ## Plot various PDFs from the Burr type XII distribution x = 0.001:0.001:3; y1 = burrpdf (x, 1, 1, 1); y2 = burrpdf (x, 1, 1, 2); y3 = burrpdf (x, 1, 1, 3); y4 = burrpdf (x, 1, 2, 1); y5 = burrpdf (x, 1, 3, 1); y6 = burrpdf (x, 1, 0.5, 2); plot (x, y1, "-b", x, y2, "-g", x, y3, "-r", ... x, y4, "-c", x, y5, "-m", x, y6, "-k") grid on ylim ([0, 2]) legend ({"λ = 1, c = 1, k = 1", "λ = 1, c = 1, k = 2", ... "λ = 1, c = 1, k = 3", "λ = 1, c = 2, k = 1", ... "λ = 1, c = 3, k = 1", "λ = 1, c = 0.5, k = 2"}, ... "location", "northeast") title ("Burr type XII PDF") xlabel ("values in x") ylabel ("density") ***** shared x, y x = [-1, 0, 1, 2, Inf]; y = [0, 1, 1/4, 1/9, 0]; ***** assert (burrpdf (x, ones(1,5), ones (1,5), ones (1,5)), y) ***** assert (burrpdf (x, 1, 1, 1), y) ***** assert (burrpdf (x, [1, 1, NaN, 1, 1], 1, 1), [y(1:2), NaN, y(4:5)]) ***** assert (burrpdf (x, 1, [1, 1, NaN, 1, 1], 1), [y(1:2), NaN, y(4:5)]) ***** assert (burrpdf (x, 1, 1, [1, 1, NaN, 1, 1]), [y(1:2), NaN, y(4:5)]) ***** assert (burrpdf ([x, NaN], 1, 1, 1), [y, NaN]) ***** assert (burrpdf (single ([x, NaN]), 1, 1, 1), single ([y, NaN])) ***** assert (burrpdf ([x, NaN], single (1), 1, 1), single ([y, NaN])) ***** assert (burrpdf ([x, NaN], 1, single (1), 1), single ([y, NaN])) ***** assert (burrpdf ([x, NaN], 1, 1, single (1)), single ([y, NaN])) ***** error burrpdf () ***** error burrpdf (1) ***** error burrpdf (1, 2) ***** error burrpdf (1, 2, 3) ***** error ... burrpdf (1, 2, 3, 4, 5) ***** error ... burrpdf (ones (3), ones (2), ones(2), ones(2)) ***** error ... burrpdf (ones (2), ones (3), ones(2), ones(2)) ***** error ... burrpdf (ones (2), ones (2), ones(3), ones(2)) ***** error ... burrpdf (ones (2), ones (2), ones(2), ones(3)) ***** error burrpdf (i, 2, 3, 4) ***** error burrpdf (1, i, 3, 4) ***** error burrpdf (1, 2, i, 4) ***** error burrpdf (1, 2, 3, i) 23 tests, 23 passed, 0 known failure, 0 skipped [inst/dist_fun/gppdf.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/dist_fun/gppdf.m ***** demo ## Plot various PDFs from the generalized Pareto distribution x = 0:0.001:5; y1 = gppdf (x, 1, 1, 0); y2 = gppdf (x, 5, 1, 0); y3 = gppdf (x, 20, 1, 0); y4 = gppdf (x, 1, 2, 0); y5 = gppdf (x, 5, 2, 0); y6 = gppdf (x, 20, 2, 0); plot (x, y1, "-b", x, y2, "-g", x, y3, "-r", ... x, y4, "-c", x, y5, "-m", x, y6, "-k") grid on xlim ([0, 5]) ylim ([0, 1]) legend ({"k = 1, σ = 1, θ = 0", "k = 5, σ = 1, θ = 0", ... "k = 20, σ = 1, θ = 0", "k = 1, σ = 2, θ = 0", ... "k = 5, σ = 2, θ = 0", "k = 20, σ = 2, θ = 0"}, ... "location", "northeast") title ("Generalized Pareto PDF") xlabel ("values in x") ylabel ("density") ***** shared x, y1, y2, y3 x = [-Inf, -1, 0, 1/2, 1, Inf]; y1 = [0, 0, 1, 0.6065306597126334, 0.36787944117144233, 0]; y2 = [0, 0, 1, 4/9, 1/4, 0]; y3 = [0, 0, 1, 1, 1, 0]; ***** assert (gppdf (x, zeros (1,6), ones (1,6), zeros (1,6)), y1, eps) ***** assert (gppdf (x, 0, 1, zeros (1,6)), y1, eps) ***** assert (gppdf (x, 0, ones (1,6), 0), y1, eps) ***** assert (gppdf (x, zeros (1,6), 1, 0), y1, eps) ***** assert (gppdf (x, 0, 1, 0), y1, eps) ***** assert (gppdf (x, 0, 1, [0, 0, 0, NaN, 0, 0]), [y1(1:3), NaN, y1(5:6)]) ***** assert (gppdf (x, 0, [1, 1, 1, NaN, 1, 1], 0), [y1(1:3), NaN, y1(5:6)]) ***** assert (gppdf (x, [0, 0, 0, NaN, 0, 0], 1, 0), [y1(1:3), NaN, y1(5:6)]) ***** assert (gppdf ([x(1:3), NaN, x(5:6)], 0, 1, 0), [y1(1:3), NaN, y1(5:6)]) ***** assert (gppdf (x, ones (1,6), ones (1,6), zeros (1,6)), y2, eps) ***** assert (gppdf (x, 1, 1, zeros (1,6)), y2, eps) ***** assert (gppdf (x, 1, ones (1,6), 0), y2, eps) ***** assert (gppdf (x, ones (1,6), 1, 0), y2, eps) ***** assert (gppdf (x, 1, 1, 0), y2, eps) ***** assert (gppdf (x, 1, 1, [0, 0, 0, NaN, 0, 0]), [y2(1:3), NaN, y2(5:6)]) ***** assert (gppdf (x, 1, [1, 1, 1, NaN, 1, 1], 0), [y2(1:3), NaN, y2(5:6)]) ***** assert (gppdf (x, [1, 1, 1, NaN, 1, 1], 1, 0), [y2(1:3), NaN, y2(5:6)]) ***** assert (gppdf ([x(1:3), NaN, x(5:6)], 1, 1, 0), [y2(1:3), NaN, y2(5:6)]) ***** assert (gppdf (x, -ones (1,6), ones (1,6), zeros (1,6)), y3, eps) ***** assert (gppdf (x, -1, 1, zeros (1,6)), y3, eps) ***** assert (gppdf (x, -1, ones (1,6), 0), y3, eps) ***** assert (gppdf (x, -ones (1,6), 1, 0), y3, eps) ***** assert (gppdf (x, -1, 1, 0), y3, eps) ***** assert (gppdf (x, -1, 1, [0, 0, 0, NaN, 0, 0]), [y3(1:3), NaN, y3(5:6)]) ***** assert (gppdf (x, -1, [1, 1, 1, NaN, 1, 1], 0), [y3(1:3), NaN, y3(5:6)]) ***** assert (gppdf (x, [-1, -1, -1, NaN, -1, -1], 1, 0), [y3(1:3), NaN, y3(5:6)]) ***** assert (gppdf ([x(1:3), NaN, x(5:6)], -1, 1, 0), [y3(1:3), NaN, y3(5:6)]) ***** assert (gppdf (single ([x, NaN]), 0, 1, 0), single ([y1, NaN])) ***** assert (gppdf ([x, NaN], 0, 1, single (0)), single ([y1, NaN])) ***** assert (gppdf ([x, NaN], 0, single (1), 0), single ([y1, NaN])) ***** assert (gppdf ([x, NaN], single (0), 1, 0), single ([y1, NaN])) ***** assert (gppdf (single ([x, NaN]), 1, 1, 0), single ([y2, NaN])) ***** assert (gppdf ([x, NaN], 1, 1, single (0)), single ([y2, NaN])) ***** assert (gppdf ([x, NaN], 1, single (1), 0), single ([y2, NaN])) ***** assert (gppdf ([x, NaN], single (1), 1, 0), single ([y2, NaN])) ***** assert (gppdf (single ([x, NaN]), -1, 1, 0), single ([y3, NaN])) ***** assert (gppdf ([x, NaN], -1, 1, single (0)), single ([y3, NaN])) ***** assert (gppdf ([x, NaN], -1, single (1), 0), single ([y3, NaN])) ***** assert (gppdf ([x, NaN], single (-1), 1, 0), single ([y3, NaN])) ***** error gpcdf () ***** error gpcdf (1) ***** error gpcdf (1, 2) ***** error gpcdf (1, 2, 3) ***** error ... gpcdf (ones (3), ones (2), ones(2), ones(2)) ***** error ... gpcdf (ones (2), ones (3), ones(2), ones(2)) ***** error ... gpcdf (ones (2), ones (2), ones(3), ones(2)) ***** error ... gpcdf (ones (2), ones (2), ones(2), ones(3)) ***** error gpcdf (i, 2, 3, 4) ***** error gpcdf (1, i, 3, 4) ***** error gpcdf (1, 2, i, 4) ***** error gpcdf (1, 2, 3, i) 51 tests, 51 passed, 0 known failure, 0 skipped [inst/dist_fun/invgcdf.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/dist_fun/invgcdf.m ***** demo ## Plot various CDFs from the inverse Gaussian distribution x = 0:0.001:3; p1 = invgcdf (x, 1, 0.2); p2 = invgcdf (x, 1, 1); p3 = invgcdf (x, 1, 3); p4 = invgcdf (x, 3, 0.2); p5 = invgcdf (x, 3, 1); plot (x, p1, "-b", x, p2, "-g", x, p3, "-r", x, p4, "-c", x, p5, "-y") grid on xlim ([0, 3]) legend ({"μ = 1, σ = 0.2", "μ = 1, σ = 1", "μ = 1, σ = 3", ... "μ = 3, σ = 0.2", "μ = 3, σ = 1"}, "location", "southeast") title ("Inverse Gaussian CDF") xlabel ("values in x") ylabel ("probability") ***** shared x, p1, p1u, y2, y2u, y3, y3u x = [-Inf, -1, 0, 1/2, 1, Inf]; p1 = [0, 0, 0, 0.3650, 0.6681, 1]; p1u = [1, 1, 1, 0.6350, 0.3319, 0]; ***** assert (invgcdf (x, ones (1,6), ones (1,6)), p1, 1e-4) ***** assert (invgcdf (x, 1, 1), p1, 1e-4) ***** assert (invgcdf (x, 1, ones (1,6)), p1, 1e-4) ***** assert (invgcdf (x, ones (1,6), 1), p1, 1e-4) ***** assert (invgcdf (x, 1, [1, 1, 1, NaN, 1, 1]), [p1(1:3), NaN, p1(5:6)], 1e-4) ***** assert (invgcdf (x, [1, 1, 1, NaN, 1, 1], 1), [p1(1:3), NaN, p1(5:6)], 1e-4) ***** assert (invgcdf ([x(1:3), NaN, x(5:6)], 1, 1), [p1(1:3), NaN, p1(5:6)], 1e-4) ***** assert (invgcdf (x, ones (1,6), ones (1,6), "upper"), p1u, 1e-4) ***** assert (invgcdf (x, 1, 1, "upper"), p1u, 1e-4) ***** assert (invgcdf (x, 1, ones (1,6), "upper"), p1u, 1e-4) ***** assert (invgcdf (x, ones (1,6), 1, "upper"), p1u, 1e-4) ***** assert (class (invgcdf (single ([x, NaN]), 1, 1)), "single") ***** assert (class (invgcdf ([x, NaN], 1, single (1))), "single") ***** assert (class (invgcdf ([x, NaN], single (1), 1)), "single") ***** error invgcdf () ***** error invgcdf (1) ***** error invgcdf (1, 2) ***** error invgcdf (1, 2, 3, "tail") ***** error invgcdf (1, 2, 3, 5) ***** error ... invgcdf (ones (3), ones (2), ones(2)) ***** error ... invgcdf (ones (2), ones (3), ones(2)) ***** error ... invgcdf (ones (2), ones (2), ones(3)) ***** error invgcdf (i, 2, 3) ***** error invgcdf (1, i, 3) ***** error invgcdf (1, 2, i) 25 tests, 25 passed, 0 known failure, 0 skipped [inst/dist_fun/gumbelpdf.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/dist_fun/gumbelpdf.m ***** demo ## Plot various PDFs from the Extreme value distribution x = -5:0.001:20; y1 = gumbelpdf (x, 0.5, 2); y2 = gumbelpdf (x, 1.0, 2); y3 = gumbelpdf (x, 1.5, 3); y4 = gumbelpdf (x, 3.0, 4); plot (x, y1, "-b", x, y2, "-g", x, y3, "-r", x, y4, "-c") grid on ylim ([0, 0.2]) legend ({"μ = 0.5, β = 2", "μ = 1.0, β = 2", ... "μ = 1.5, β = 3", "μ = 3.0, β = 4"}, "location", "northeast") title ("Extreme value PDF") xlabel ("values in x") ylabel ("density") ***** shared x, y0, y1 x = [-5, 0, 1, 2, 3]; y0 = [0, 0.3679, 0.2547, 0.1182, 0.0474]; y1 = [0, 0.1794, 0.3679, 0.2547, 0.1182]; ***** assert (gumbelpdf (x), y0, 1e-4) ***** assert (gumbelpdf (x, zeros (1,5), ones (1,5)), y0, 1e-4) ***** assert (gumbelpdf (x, ones (1,5), ones (1,5)), y1, 1e-4) ***** error gumbelpdf () ***** error ... gumbelpdf (ones (3), ones (2), ones (2)) ***** error gumbelpdf (i, 2, 2) ***** error gumbelpdf (2, i, 2) ***** error gumbelpdf (2, 2, i) 8 tests, 8 passed, 0 known failure, 0 skipped [inst/dist_fun/unidpdf.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/dist_fun/unidpdf.m ***** demo ## Plot various PDFs from the discrete uniform distribution x = 0:10; y1 = unidpdf (x, 5); y2 = unidpdf (x, 9); plot (x, y1, "*b", x, y2, "*g") grid on xlim ([0, 10]) ylim ([0, 0.25]) legend ({"N = 5", "N = 9"}, "location", "northeast") title ("Descrete uniform PDF") xlabel ("values in x") ylabel ("density") ***** shared x, y x = [-1 0 1 2 10 11]; y = [0 0 0.1 0.1 0.1 0]; ***** assert (unidpdf (x, 10*ones (1,6)), y) ***** assert (unidpdf (x, 10), y) ***** assert (unidpdf (x, 10*[0 NaN 1 1 1 1]), [NaN NaN y(3:6)]) ***** assert (unidpdf ([x, NaN], 10), [y, NaN]) ***** assert (unidpdf (single ([x, NaN]), 10), single ([y, NaN])) ***** assert (unidpdf ([x, NaN], single (10)), single ([y, NaN])) ***** error unidpdf () ***** error unidpdf (1) ***** error ... unidpdf (ones (3), ones (2)) ***** error ... unidpdf (ones (2), ones (3)) ***** error unidpdf (i, 2) ***** error unidpdf (2, i) 12 tests, 12 passed, 0 known failure, 0 skipped [inst/dist_fun/binocdf.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/dist_fun/binocdf.m ***** demo ## Plot various CDFs from the binomial distribution x = 0:40; p1 = binocdf (x, 20, 0.5); p2 = binocdf (x, 20, 0.7); p3 = binocdf (x, 40, 0.5); plot (x, p1, "*b", x, p2, "*g", x, p3, "*r") grid on legend ({"n = 20, ps = 0.5", "n = 20, ps = 0.7", ... "n = 40, ps = 0.5"}, "location", "southeast") title ("Binomial CDF") xlabel ("values in x (number of successes)") ylabel ("probability") ***** shared x, p, p1 x = [-1 0 1 2 3]; p = [0 1/4 3/4 1 1]; p1 = 1 - p; ***** assert (binocdf (x, 2 * ones (1, 5), 0.5 * ones (1, 5)), p, eps) ***** assert (binocdf (x, 2, 0.5 * ones (1, 5)), p, eps) ***** assert (binocdf (x, 2 * ones (1, 5), 0.5), p, eps) ***** assert (binocdf (x, 2 * [0 -1 NaN 1.1 1], 0.5), [0 NaN NaN NaN 1]) ***** assert (binocdf (x, 2, 0.5 * [0 -1 NaN 3 1]), [0 NaN NaN NaN 1]) ***** assert (binocdf ([x(1:2) NaN x(4:5)], 2, 0.5), [p(1:2) NaN p(4:5)], eps) ***** assert (binocdf (99, 100, 0.1, "upper"), 1e-100, 1e-112); ***** assert (binocdf (x, 2 * ones (1, 5), 0.5*ones (1,5), "upper"), p1, eps) ***** assert (binocdf (x, 2, 0.5 * ones (1, 5), "upper"), p1, eps) ***** assert (binocdf (x, 2 * ones (1, 5), 0.5, "upper"), p1, eps) ***** assert (binocdf (x, 2 * [0 -1 NaN 1.1 1], 0.5, "upper"), [1 NaN NaN NaN 0]) ***** assert (binocdf (x, 2, 0.5 * [0 -1 NaN 3 1], "upper"), [1 NaN NaN NaN 0]) ***** assert (binocdf ([x(1:2) NaN x(4:5)], 2, 0.5, "upper"), [p1(1:2) NaN p1(4:5)]) ***** assert (binocdf ([x, NaN], 2, 0.5), [p, NaN], eps) ***** assert (binocdf (single ([x, NaN]), 2, 0.5), single ([p, NaN])) ***** assert (binocdf ([x, NaN], single (2), 0.5), single ([p, NaN])) ***** assert (binocdf ([x, NaN], 2, single (0.5)), single ([p, NaN])) ***** error binocdf () ***** error binocdf (1) ***** error binocdf (1, 2) ***** error binocdf (1, 2, 3, 4, 5) ***** error binocdf (1, 2, 3, "tail") ***** error binocdf (1, 2, 3, 4) ***** error ... binocdf (ones (3), ones (2), ones (2)) ***** error ... binocdf (ones (2), ones (3), ones (2)) ***** error ... binocdf (ones (2), ones (2), ones (3)) ***** error binocdf (i, 2, 2) ***** error binocdf (2, i, 2) ***** error binocdf (2, 2, i) 29 tests, 29 passed, 0 known failure, 0 skipped [inst/dist_fun/cauchyinv.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/dist_fun/cauchyinv.m ***** demo ## Plot various iCDFs from the Cauchy distribution p = 0.001:0.001:0.999; x1 = cauchyinv (p, 0, 0.5); x2 = cauchyinv (p, 0, 1); x3 = cauchyinv (p, 0, 2); x4 = cauchyinv (p, -2, 1); plot (p, x1, "-b", p, x2, "-g", p, x3, "-r", p, x4, "-c") grid on ylim ([-5, 5]) legend ({"x0 = 0, γ = 0.5", "x0 = 0, γ = 1", ... "x0 = 0, γ = 2", "x0 = -2, γ = 1"}, "location", "northwest") title ("Cauchy iCDF") xlabel ("probability") ylabel ("values in x") ***** shared p p = [-1 0 0.5 1 2]; ***** assert (cauchyinv (p, ones (1,5), 2 * ones (1,5)), [NaN -Inf 1 Inf NaN], eps) ***** assert (cauchyinv (p, 1, 2 * ones (1,5)), [NaN -Inf 1 Inf NaN], eps) ***** assert (cauchyinv (p, ones (1,5), 2), [NaN -Inf 1 Inf NaN], eps) ***** assert (cauchyinv (p, [1 -Inf NaN Inf 1], 2), [NaN NaN NaN NaN NaN]) ***** assert (cauchyinv (p, 1, 2 * [1 0 NaN Inf 1]), [NaN NaN NaN NaN NaN]) ***** assert (cauchyinv ([p(1:2) NaN p(4:5)], 1, 2), [NaN -Inf NaN Inf NaN]) ***** assert (cauchyinv ([p, NaN], 1, 2), [NaN -Inf 1 Inf NaN NaN], eps) ***** assert (cauchyinv (single ([p, NaN]), 1, 2), ... single ([NaN -Inf 1 Inf NaN NaN]), eps ("single")) ***** assert (cauchyinv ([p, NaN], single (1), 2), ... single ([NaN -Inf 1 Inf NaN NaN]), eps ("single")) ***** assert (cauchyinv ([p, NaN], 1, single (2)), ... single ([NaN -Inf 1 Inf NaN NaN]), eps ("single")) ***** error cauchyinv () ***** error cauchyinv (1) ***** error ... cauchyinv (1, 2) ***** error cauchyinv (1, 2, 3, 4) ***** error ... cauchyinv (ones (3), ones (2), ones(2)) ***** error ... cauchyinv (ones (2), ones (3), ones(2)) ***** error ... cauchyinv (ones (2), ones (2), ones(3)) ***** error cauchyinv (i, 4, 3) ***** error cauchyinv (1, i, 3) ***** error cauchyinv (1, 4, i) 20 tests, 20 passed, 0 known failure, 0 skipped [inst/dist_fun/frnd.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/dist_fun/frnd.m ***** assert (size (frnd (1, 1)), [1 1]) ***** assert (size (frnd (1, ones (2,1))), [2, 1]) ***** assert (size (frnd (1, ones (2,2))), [2, 2]) ***** assert (size (frnd (ones (2,1), 1)), [2, 1]) ***** assert (size (frnd (ones (2,2), 1)), [2, 2]) ***** assert (size (frnd (1, 1, 3)), [3, 3]) ***** assert (size (frnd (1, 1, [4, 1])), [4, 1]) ***** assert (size (frnd (1, 1, 4, 1)), [4, 1]) ***** assert (size (frnd (1, 1, 4, 1, 5)), [4, 1, 5]) ***** assert (size (frnd (1, 1, 0, 1)), [0, 1]) ***** assert (size (frnd (1, 1, 1, 0)), [1, 0]) ***** assert (size (frnd (1, 1, 1, 2, 0, 5)), [1, 2, 0, 5]) ***** assert (class (frnd (1, 1)), "double") ***** assert (class (frnd (1, single (1))), "single") ***** assert (class (frnd (1, single ([1, 1]))), "single") ***** assert (class (frnd (single (1), 1)), "single") ***** assert (class (frnd (single ([1, 1]), 1)), "single") ***** error frnd () ***** error frnd (1) ***** error ... frnd (ones (3), ones (2)) ***** error ... frnd (ones (2), ones (3)) ***** error frnd (i, 2, 3) ***** error frnd (1, i, 3) ***** error ... frnd (1, 2, -1) ***** error ... frnd (1, 2, 1.2) ***** error ... frnd (1, 2, ones (2)) ***** error ... frnd (1, 2, [2 -1 2]) ***** error ... frnd (1, 2, [2 0 2.5]) ***** error ... frnd (1, 2, 2, -1, 5) ***** error ... frnd (1, 2, 2, 1.5, 5) ***** error ... frnd (2, ones (2), 3) ***** error ... frnd (2, ones (2), [3, 2]) ***** error ... frnd (2, ones (2), 3, 2) 33 tests, 33 passed, 0 known failure, 0 skipped [inst/dist_fun/mnpdf.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/dist_fun/mnpdf.m ***** test x = [1, 4, 2]; pk = [0.2, 0.5, 0.3]; y = mnpdf (x, pk); assert (y, 0.11812, 0.001); ***** test x = [1, 4, 2; 1, 0, 9]; pk = [0.2, 0.5, 0.3; 0.1, 0.1, 0.8]; y = mnpdf (x, pk); assert (y, [0.11812; 0.13422], 0.001); 2 tests, 2 passed, 0 known failure, 0 skipped [inst/dist_fun/hnpdf.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/dist_fun/hnpdf.m ***** demo ## Plot various PDFs from the half-normal distribution x = 0:0.001:10; y1 = hnpdf (x, 0, 1); y2 = hnpdf (x, 0, 2); y3 = hnpdf (x, 0, 3); y4 = hnpdf (x, 0, 5); plot (x, y1, "-b", x, y2, "-g", x, y3, "-r", x, y4, "-c") grid on xlim ([0, 10]) ylim ([0, 0.9]) legend ({"μ = 0, σ = 1", "μ = 0, σ = 2", ... "μ = 0, σ = 3", "μ = 0, σ = 5"}, "location", "northeast") title ("Half-normal PDF") xlabel ("values in x") ylabel ("density") ***** demo ## Plot half-normal against normal probability density function x = -5:0.001:5; y1 = hnpdf (x, 0, 1); y2 = normpdf (x); plot (x, y1, "-b", x, y2, "-g") grid on xlim ([-5, 5]) ylim ([0, 0.9]) legend ({"half-normal with μ = 0, σ = 1", ... "standart normal (μ = 0, σ = 1)"}, "location", "northeast") title ("Half-normal against standard normal PDF") xlabel ("values in x") ylabel ("density") ***** shared x, y x = [-Inf, -1, 0, 1/2, 1, Inf]; y = [0, 0, 0.7979, 0.7041, 0.4839, 0]; ***** assert (hnpdf ([x, NaN], 0, 1), [y, NaN], 1e-4) ***** assert (hnpdf (x, 0, [-2, -1, 0, 1, 1, 1]), [nan(1,3), y([4:6])], 1e-4) ***** assert (class (hncdf (single ([x, NaN]), 0, 1)), "single") ***** assert (class (hncdf ([x, NaN], 0, single (1))), "single") ***** assert (class (hncdf ([x, NaN], single (0), 1)), "single") ***** error hnpdf () ***** error hnpdf (1) ***** error hnpdf (1, 2) ***** error ... hnpdf (1, ones (2), ones (3)) ***** error ... hnpdf (ones (2), 1, ones (3)) ***** error ... hnpdf (ones (2), ones (3), 1) ***** error hnpdf (i, 2, 3) ***** error hnpdf (1, i, 3) ***** error hnpdf (1, 2, i) 14 tests, 14 passed, 0 known failure, 0 skipped [inst/dist_fun/ncx2inv.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/dist_fun/ncx2inv.m ***** demo ## Plot various iCDFs from the noncentral chi-squared distribution p = 0.001:0.001:0.999; x1 = ncx2inv (p, 2, 1); x2 = ncx2inv (p, 2, 2); x3 = ncx2inv (p, 2, 3); x4 = ncx2inv (p, 4, 1); x5 = ncx2inv (p, 4, 2); x6 = ncx2inv (p, 4, 3); plot (p, x1, "-r", p, x2, "-g", p, x3, "-k", ... p, x4, "-m", p, x5, "-c", p, x6, "-y") grid on ylim ([0, 10]) legend ({"df = 2, λ = 1", "df = 2, λ = 2", ... "df = 2, λ = 3", "df = 4, λ = 1", ... "df = 4, λ = 2", "df = 4, λ = 3"}, "location", "northwest") title ("Noncentral chi-squared iCDF") xlabel ("probability") ylabel ("values in x") ***** demo ## Compare the noncentral chi-squared CDF with LAMBDA = 2 to the ## chi-squared CDF with the same number of degrees of freedom (4). p = 0.001:0.001:0.999; x1 = ncx2inv (p, 4, 2); x2 = chi2inv (p, 4); plot (p, x1, "-", p, x2, "-"); grid on ylim ([0, 10]) legend ({"Noncentral χ^2(4,2)", "χ^2(4)"}, "location", "northwest") title ("Noncentral chi-squared vs chi-squared quantile functions") xlabel ("probability") ylabel ("values in x") ***** test x = [0,0.3443,0.7226,1.1440,1.6220,2.1770,2.8436,3.6854,4.8447,6.7701,Inf]; assert (ncx2inv ([0:0.1:1], 2, 1), x, 1e-4); ***** test x = [0,0.8295,1.6001,2.3708,3.1785,4.0598,5.0644,6.2765,7.8763,10.4199,Inf]; assert (ncx2inv ([0:0.1:1], 2, 3), x, 1e-4); ***** test x = [0,0.5417,1.3483,2.1796,3.0516,4.0003,5.0777,6.3726,8.0748,10.7686,Inf]; assert (ncx2inv ([0:0.1:1], 1, 4), x, 1e-4); ***** test x = [0.1808, 0.6456, 1.1842, 1.7650, 2.3760, 3.0105]; assert (ncx2inv (0.05, [1, 2, 3, 4, 5, 6], 4), x, 1e-4); ***** test x = [0.4887, 0.6699, 0.9012, 1.1842, 1.5164, 1.8927]; assert (ncx2inv (0.05, 3, [1, 2, 3, 4, 5, 6]), x, 1e-4); ***** test x = [1.3941, 1.6824, 2.0103, 2.3760, NaN, 3.2087]; assert (ncx2inv (0.05, 5, [1, 2, 3, 4, -1, 6]), x, 1e-4); ***** test assert (ncx2inv (0.996, 5, 8), 35.51298862765576, 2e-13); ***** error ncx2inv () ***** error ncx2inv (1) ***** error ncx2inv (1, 2) ***** error ... ncx2inv (ones (3), ones (2), ones (2)) ***** error ... ncx2inv (ones (2), ones (3), ones (2)) ***** error ... ncx2inv (ones (2), ones (2), ones (3)) ***** error ncx2inv (i, 2, 2) ***** error ncx2inv (2, i, 2) ***** error ncx2inv (2, 2, i) 16 tests, 16 passed, 0 known failure, 0 skipped [inst/dist_fun/tlsrnd.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/dist_fun/tlsrnd.m ***** assert (size (tlsrnd (1, 2, 3)), [1, 1]) ***** assert (size (tlsrnd (ones (2,1), 2, 3)), [2, 1]) ***** assert (size (tlsrnd (ones (2,2), 2, 3)), [2, 2]) ***** assert (size (tlsrnd (1, 2, 3, 3)), [3, 3]) ***** assert (size (tlsrnd (1, 2, 3, [4 1])), [4, 1]) ***** assert (size (tlsrnd (1, 2, 3, 4, 1)), [4, 1]) ***** assert (size (tlsrnd (1, 2, 3, 4, 1)), [4, 1]) ***** assert (size (tlsrnd (1, 2, 3, 4, 1, 5)), [4, 1, 5]) ***** assert (size (tlsrnd (1, 2, 3, 0, 1)), [0, 1]) ***** assert (size (tlsrnd (1, 2, 3, 1, 0)), [1, 0]) ***** assert (size (tlsrnd (1, 2, 3, 1, 2, 0, 5)), [1, 2, 0, 5]) ***** assert (tlsrnd (1, 2, 0, 1, 1), NaN) ***** assert (tlsrnd (1, 2, [0, 0, 0], [1, 3]), [NaN, NaN, NaN]) ***** assert (class (tlsrnd (1, 2, 3)), "double") ***** assert (class (tlsrnd (single (1), 2, 3)), "single") ***** assert (class (tlsrnd (single ([1, 1]), 2, 3)), "single") ***** assert (class (tlsrnd (1, single (2), 3)), "single") ***** assert (class (tlsrnd (1, single ([2, 2]), 3)), "single") ***** assert (class (tlsrnd (1, 2, single (3))), "single") ***** assert (class (tlsrnd (1, 2, single ([3, 3]))), "single") ***** error tlsrnd () ***** error tlsrnd (1) ***** error tlsrnd (1, 2) ***** error ... tlsrnd (ones (3), ones (2), 1) ***** error ... tlsrnd (ones (2), 1, ones (3)) ***** error ... tlsrnd (1, ones (2), ones (3)) ***** error tlsrnd (i, 2, 3) ***** error tlsrnd (1, i, 3) ***** error tlsrnd (1, 2, i) ***** error ... tlsrnd (1, 2, 3, -1) ***** error ... tlsrnd (1, 2, 3, 1.2) ***** error ... tlsrnd (1, 2, 3, ones (2)) ***** error ... tlsrnd (1, 2, 3, [2 -1 2]) ***** error ... tlsrnd (1, 2, 3, [2 0 2.5]) ***** error ... tlsrnd (ones (2), 2, 3, ones (2)) ***** error ... tlsrnd (1, 2, 3, 2, -1, 5) ***** error ... tlsrnd (1, 2, 3, 2, 1.5, 5) ***** error ... tlsrnd (ones (2,2), 2, 3, 3) ***** error ... tlsrnd (1, ones (2,2), 3, 3) ***** error ... tlsrnd (1, 2, ones (2,2), 3) ***** error ... tlsrnd (1, 2, ones (2,2), [3, 3]) ***** error ... tlsrnd (1, 2, ones (2,2), 2, 3) 42 tests, 42 passed, 0 known failure, 0 skipped [inst/dist_fun/cauchyrnd.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/dist_fun/cauchyrnd.m ***** assert (size (cauchyrnd (1, 1)), [1 1]) ***** assert (size (cauchyrnd (1, ones (2,1))), [2, 1]) ***** assert (size (cauchyrnd (1, ones (2,2))), [2, 2]) ***** assert (size (cauchyrnd (ones (2,1), 1)), [2, 1]) ***** assert (size (cauchyrnd (ones (2,2), 1)), [2, 2]) ***** assert (size (cauchyrnd (1, 1, 3)), [3, 3]) ***** assert (size (cauchyrnd (1, 1, [4, 1])), [4, 1]) ***** assert (size (cauchyrnd (1, 1, 4, 1)), [4, 1]) ***** assert (size (cauchyrnd (1, 1, 4, 1, 5)), [4, 1, 5]) ***** assert (size (cauchyrnd (1, 1, 0, 1)), [0, 1]) ***** assert (size (cauchyrnd (1, 1, 1, 0)), [1, 0]) ***** assert (size (cauchyrnd (1, 1, 1, 2, 0, 5)), [1, 2, 0, 5]) ***** assert (class (cauchyrnd (1, 1)), "double") ***** assert (class (cauchyrnd (1, single (1))), "single") ***** assert (class (cauchyrnd (1, single ([1, 1]))), "single") ***** assert (class (cauchyrnd (single (1), 1)), "single") ***** assert (class (cauchyrnd (single ([1, 1]), 1)), "single") ***** error cauchyrnd () ***** error cauchyrnd (1) ***** error ... cauchyrnd (ones (3), ones (2)) ***** error ... cauchyrnd (ones (2), ones (3)) ***** error cauchyrnd (i, 2, 3) ***** error cauchyrnd (1, i, 3) ***** error ... cauchyrnd (1, 2, -1) ***** error ... cauchyrnd (1, 2, 1.2) ***** error ... cauchyrnd (1, 2, ones (2)) ***** error ... cauchyrnd (1, 2, [2 -1 2]) ***** error ... cauchyrnd (1, 2, [2 0 2.5]) ***** error ... cauchyrnd (1, 2, 2, -1, 5) ***** error ... cauchyrnd (1, 2, 2, 1.5, 5) ***** error ... cauchyrnd (2, ones (2), 3) ***** error ... cauchyrnd (2, ones (2), [3, 2]) ***** error ... cauchyrnd (2, ones (2), 3, 2) 33 tests, 33 passed, 0 known failure, 0 skipped [inst/dist_fun/nakapdf.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/dist_fun/nakapdf.m ***** demo ## Plot various PDFs from the Nakagami distribution x = 0:0.01:3; y1 = nakapdf (x, 0.5, 1); y2 = nakapdf (x, 1, 1); y3 = nakapdf (x, 1, 2); y4 = nakapdf (x, 1, 3); y5 = nakapdf (x, 2, 1); y6 = nakapdf (x, 2, 2); y7 = nakapdf (x, 5, 1); plot (x, y1, "-r", x, y2, "-g", x, y3, "-y", x, y4, "-m", ... x, y5, "-k", x, y6, "-b", x, y7, "-c") grid on xlim ([0, 3]) ylim ([0, 2]) legend ({"μ = 0.5, ω = 1", "μ = 1, ω = 1", "μ = 1, ω = 2", ... "μ = 1, ω = 3", "μ = 2, ω = 1", "μ = 2, ω = 2", ... "μ = 5, ω = 1"}, "location", "northeast") title ("Nakagami PDF") xlabel ("values in x") ylabel ("density") ***** shared x, y x = [-1, 0, 1, 2, Inf]; y = [0, 0, 0.73575888234288467, 0.073262555554936715, 0]; ***** assert (nakapdf (x, ones (1,5), ones (1,5)), y, eps) ***** assert (nakapdf (x, 1, 1), y, eps) ***** assert (nakapdf (x, [1, 1, NaN, 1, 1], 1), [y(1:2), NaN, y(4:5)], eps) ***** assert (nakapdf (x, 1, [1, 1, NaN, 1, 1]), [y(1:2), NaN, y(4:5)], eps) ***** assert (nakapdf ([x, NaN], 1, 1), [y, NaN], eps) ***** assert (nakapdf (single ([x, NaN]), 1, 1), single ([y, NaN])) ***** assert (nakapdf ([x, NaN], single (1), 1), single ([y, NaN])) ***** assert (nakapdf ([x, NaN], 1, single (1)), single ([y, NaN])) ***** error nakapdf () ***** error nakapdf (1) ***** error nakapdf (1, 2) ***** error ... nakapdf (ones (3), ones (2), ones(2)) ***** error ... nakapdf (ones (2), ones (3), ones(2)) ***** error ... nakapdf (ones (2), ones (2), ones(3)) ***** error nakapdf (i, 4, 3) ***** error nakapdf (1, i, 3) ***** error nakapdf (1, 4, i) 17 tests, 17 passed, 0 known failure, 0 skipped [inst/dist_fun/gevcdf.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/dist_fun/gevcdf.m ***** demo ## Plot various CDFs from the generalized extreme value distribution x = -1:0.001:10; p1 = gevcdf (x, 1, 1, 1); p2 = gevcdf (x, 0.5, 1, 1); p3 = gevcdf (x, 1, 1, 5); p4 = gevcdf (x, 1, 2, 5); p5 = gevcdf (x, 1, 5, 5); p6 = gevcdf (x, 1, 0.5, 5); plot (x, p1, "-b", x, p2, "-g", x, p3, "-r", ... x, p4, "-c", x, p5, "-m", x, p6, "-k") grid on xlim ([-1, 10]) legend ({"k = 1, σ = 1, μ = 1", "k = 0.5, σ = 1, μ = 1", ... "k = 1, σ = 1, μ = 5", "k = 1, σ = 2, μ = 5", ... "k = 1, σ = 5, μ = 5", "k = 1, σ = 0.5, μ = 5"}, ... "location", "southeast") title ("Generalized extreme value CDF") xlabel ("values in x") ylabel ("probability") ***** test x = 0:0.5:2.5; sigma = 1:6; k = 1; mu = 0; p = gevcdf (x, k, sigma, mu); expected_p = [0.36788, 0.44933, 0.47237, 0.48323, 0.48954, 0.49367]; assert (p, expected_p, 0.001); ***** test x = -0.5:0.5:2.5; sigma = 0.5; k = 1; mu = 0; p = gevcdf (x, k, sigma, mu); expected_p = [0, 0.36788, 0.60653, 0.71653, 0.77880, 0.81873, 0.84648]; assert (p, expected_p, 0.001); ***** test # check for continuity for k near 0 x = 1; sigma = 0.5; k = -0.03:0.01:0.03; mu = 0; p = gevcdf (x, k, sigma, mu); expected_p = [0.88062, 0.87820, 0.87580, 0.87342, 0.87107, 0.86874, 0.86643]; assert (p, expected_p, 0.001); ***** error gevcdf () ***** error gevcdf (1) ***** error gevcdf (1, 2) ***** error gevcdf (1, 2, 3) ***** error ... gevcdf (1, 2, 3, 4, 5, 6) ***** error gevcdf (1, 2, 3, 4, "tail") ***** error gevcdf (1, 2, 3, 4, 5) ***** error ... gevcdf (ones (3), ones (2), ones(2), ones(2)) ***** error ... gevcdf (ones (2), ones (3), ones(2), ones(2)) ***** error ... gevcdf (ones (2), ones (2), ones(3), ones(2)) ***** error ... gevcdf (ones (2), ones (2), ones(2), ones(3)) ***** error gevcdf (i, 2, 3, 4) ***** error gevcdf (1, i, 3, 4) ***** error gevcdf (1, 2, i, 4) ***** error gevcdf (1, 2, 3, i) 18 tests, 18 passed, 0 known failure, 0 skipped [inst/dist_fun/jsucdf.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/dist_fun/jsucdf.m ***** error jsucdf () ***** error jsucdf (1, 2, 3, 4) ***** error ... jsucdf (1, ones (2), ones (3)) 3 tests, 3 passed, 0 known failure, 0 skipped [inst/dist_fun/nakacdf.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/dist_fun/nakacdf.m ***** demo ## Plot various CDFs from the Nakagami distribution x = 0:0.01:3; p1 = nakacdf (x, 0.5, 1); p2 = nakacdf (x, 1, 1); p3 = nakacdf (x, 1, 2); p4 = nakacdf (x, 1, 3); p5 = nakacdf (x, 2, 1); p6 = nakacdf (x, 2, 2); p7 = nakacdf (x, 5, 1); plot (x, p1, "-r", x, p2, "-g", x, p3, "-y", x, p4, "-m", ... x, p5, "-k", x, p6, "-b", x, p7, "-c") grid on xlim ([0, 3]) legend ({"μ = 0.5, ω = 1", "μ = 1, ω = 1", "μ = 1, ω = 2", ... "μ = 1, ω = 3", "μ = 2, ω = 1", "μ = 2, ω = 2", ... "μ = 5, ω = 1"}, "location", "southeast") title ("Nakagami CDF") xlabel ("values in x") ylabel ("probability") ***** shared x, y x = [-1, 0, 1, 2, Inf]; y = [0, 0, 0.63212055882855778, 0.98168436111126578, 1]; ***** assert (nakacdf (x, ones (1,5), ones (1,5)), y, eps) ***** assert (nakacdf (x, 1, 1), y, eps) ***** assert (nakacdf (x, [1, 1, NaN, 1, 1], 1), [y(1:2), NaN, y(4:5)]) ***** assert (nakacdf (x, 1, [1, 1, NaN, 1, 1]), [y(1:2), NaN, y(4:5)]) ***** assert (nakacdf ([x, NaN], 1, 1), [y, NaN], eps) ***** assert (nakacdf (single ([x, NaN]), 1, 1), single ([y, NaN]), eps("single")) ***** assert (nakacdf ([x, NaN], single (1), 1), single ([y, NaN]), eps("single")) ***** assert (nakacdf ([x, NaN], 1, single (1)), single ([y, NaN]), eps("single")) ***** error nakacdf () ***** error nakacdf (1) ***** error nakacdf (1, 2) ***** error nakacdf (1, 2, 3, "tail") ***** error nakacdf (1, 2, 3, 4) ***** error ... nakacdf (ones (3), ones (2), ones (2)) ***** error ... nakacdf (ones (2), ones (3), ones (2)) ***** error ... nakacdf (ones (2), ones (2), ones (3)) ***** error nakacdf (i, 2, 2) ***** error nakacdf (2, i, 2) ***** error nakacdf (2, 2, i) 19 tests, 19 passed, 0 known failure, 0 skipped [inst/dist_fun/raylcdf.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/dist_fun/raylcdf.m ***** demo ## Plot various CDFs from the Rayleigh distribution x = 0:0.01:10; p1 = raylcdf (x, 0.5); p2 = raylcdf (x, 1); p3 = raylcdf (x, 2); p4 = raylcdf (x, 3); p5 = raylcdf (x, 4); plot (x, p1, "-b", x, p2, "g", x, p3, "-r", x, p4, "-m", x, p5, "-k") grid on ylim ([0, 1]) legend ({"σ = 0.5", "σ = 1", "σ = 2", ... "σ = 3", "σ = 4"}, "location", "southeast") title ("Rayleigh CDF") xlabel ("values in x") ylabel ("probability") ***** test x = 0:0.5:2.5; sigma = 1:6; p = raylcdf (x, sigma); expected_p = [0.0000, 0.0308, 0.0540, 0.0679, 0.0769, 0.0831]; assert (p, expected_p, 0.001); ***** test x = 0:0.5:2.5; p = raylcdf (x, 0.5); expected_p = [0.0000, 0.3935, 0.8647, 0.9889, 0.9997, 1.0000]; assert (p, expected_p, 0.001); ***** shared x, p x = [-1, 0, 1, 2, Inf]; p = [0, 0, 0.39346934028737, 0.86466471676338, 1]; ***** assert (raylcdf (x, 1), p, 1e-14) ***** assert (raylcdf (x, 1, "upper"), 1 - p, 1e-14) ***** error raylcdf () ***** error raylcdf (1) ***** error raylcdf (1, 2, "uper") ***** error raylcdf (1, 2, 3) ***** error ... raylcdf (ones (3), ones (2)) ***** error ... raylcdf (ones (2), ones (3)) ***** error raylcdf (i, 2) ***** error raylcdf (2, i) 12 tests, 12 passed, 0 known failure, 0 skipped [inst/dist_fun/exprnd.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/dist_fun/exprnd.m ***** assert (size (exprnd (2)), [1, 1]) ***** assert (size (exprnd (ones (2,1))), [2, 1]) ***** assert (size (exprnd (ones (2,2))), [2, 2]) ***** assert (size (exprnd (1, 3)), [3, 3]) ***** assert (size (exprnd (1, [4 1])), [4, 1]) ***** assert (size (exprnd (1, 4, 1)), [4, 1]) ***** assert (size (exprnd (1, 4, 1)), [4, 1]) ***** assert (size (exprnd (1, 4, 1, 5)), [4, 1, 5]) ***** assert (size (exprnd (1, 0, 1)), [0, 1]) ***** assert (size (exprnd (1, 1, 0)), [1, 0]) ***** assert (size (exprnd (1, 1, 2, 0, 5)), [1, 2, 0, 5]) ***** assert (class (exprnd (2)), "double") ***** assert (class (exprnd (single (2))), "single") ***** assert (class (exprnd (single ([2 2]))), "single") ***** error exprnd () ***** error exprnd (i) ***** error ... exprnd (1, -1) ***** error ... exprnd (1, 1.2) ***** error ... exprnd (1, ones (2)) ***** error ... exprnd (1, [2 -1 2]) ***** error ... exprnd (1, [2 0 2.5]) ***** error ... exprnd (ones (2), ones (2)) ***** error ... exprnd (1, 2, -1, 5) ***** error ... exprnd (1, 2, 1.5, 5) ***** error exprnd (ones (2,2), 3) ***** error exprnd (ones (2,2), [3, 2]) ***** error exprnd (ones (2,2), 2, 3) 27 tests, 27 passed, 0 known failure, 0 skipped [inst/dist_fun/logiinv.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/dist_fun/logiinv.m ***** demo ## Plot various iCDFs from the logistic distribution p = 0.001:0.001:0.999; x1 = logiinv (p, 5, 2); x2 = logiinv (p, 9, 3); x3 = logiinv (p, 9, 4); x4 = logiinv (p, 6, 2); x5 = logiinv (p, 2, 1); plot (p, x1, "-b", p, x2, "-g", p, x3, "-r", p, x4, "-c", p, x5, "-m") grid on legend ({"μ = 5, σ = 2", "μ = 9, σ = 3", "μ = 9, σ = 4", ... "μ = 6, σ = 2", "μ = 2, σ = 1"}, "location", "southeast") title ("Logistic iCDF") xlabel ("probability") ylabel ("x") ***** test p = [0.01:0.01:0.99]; assert (logiinv (p, 0, 1), log (p ./ (1-p)), 25*eps); ***** shared p p = [-1 0 0.5 1 2]; ***** assert (logiinv (p, 0, 1), [NaN -Inf 0 Inf NaN]) ***** assert (logiinv (p, 0, [-1, 0, 1, 2, 3]), [NaN NaN 0 Inf NaN]) ***** assert (logiinv ([p, NaN], 0, 1), [NaN -Inf 0 Inf NaN NaN]) ***** assert (logiinv (single ([p, NaN]), 0, 1), single ([NaN -Inf 0 Inf NaN NaN])) ***** assert (logiinv ([p, NaN], single (0), 1), single ([NaN -Inf 0 Inf NaN NaN])) ***** assert (logiinv ([p, NaN], 0, single (1)), single ([NaN -Inf 0 Inf NaN NaN])) ***** error logiinv () ***** error logiinv (1) ***** error ... logiinv (1, 2) ***** error ... logiinv (1, ones (2), ones (3)) ***** error ... logiinv (ones (2), 1, ones (3)) ***** error ... logiinv (ones (2), ones (3), 1) ***** error logiinv (i, 2, 3) ***** error logiinv (1, i, 3) ***** error logiinv (1, 2, i) 16 tests, 16 passed, 0 known failure, 0 skipped [inst/dist_fun/mvtcdf.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/dist_fun/mvtcdf.m ***** demo ## Compute the cdf of a multivariate Student's t distribution with ## correlation parameters rho = [1, 0.4; 0.4, 1] and 2 degrees of freedom. rho = [1, 0.4; 0.4, 1]; df = 2; [X1, X2] = meshgrid (linspace (-2, 2, 25)', linspace (-2, 2, 25)'); X = [X1(:), X2(:)]; p = mvtcdf (X, rho, df); surf (X1, X2, reshape (p, 25, 25)); title ("Bivariate Student's t cummulative distribution function"); ***** test x = [1, 2]; rho = [1, 0.5; 0.5, 1]; df = 4; a = [-1, 0]; assert (mvtcdf(a, x, rho, df), 0.294196905339283, 1e-14); ***** test x = [1, 2;2, 4;1, 5]; rho = [1, 0.5; 0.5, 1]; df = 4; p =[0.790285178602166; 0.938703291727784; 0.81222737321336]; assert (mvtcdf(x, rho, df), p, 1e-14); ***** test x = [1, 2, 2, 4, 1, 5]; rho = eye (6); rho(rho == 0) = 0.5; df = 4; assert (mvtcdf(x, rho, df), 0.6874, 1e-4); ***** error mvtcdf (1) ***** error mvtcdf (1, 2) ***** error ... mvtcdf (1, [2, 3; 3, 2], 1) ***** error ... mvtcdf ([2, 3, 4], ones (2), 1) ***** error ... mvtcdf ([1, 2, 3], [2, 3], ones (2), 1) ***** error ... mvtcdf ([2, 3], ones (2), [1, 2, 3]) ***** error ... mvtcdf ([2, 3], [1, 0.5; 0.5, 1], [1, 2, 3]) 10 tests, 10 passed, 0 known failure, 0 skipped [inst/dist_fun/exppdf.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/dist_fun/exppdf.m ***** demo ## Plot various PDFs from the exponential distribution x = 0:0.01:5; y1 = exppdf (x, 2/3); y2 = exppdf (x, 1.0); y3 = exppdf (x, 2.0); plot (x, y1, "-b", x, y2, "-g", x, y3, "-r") grid on ylim ([0, 1.5]) legend ({"μ = 2/3", "μ = 1", "μ = 2"}, "location", "northeast") title ("Exponential PDF") xlabel ("values in x") ylabel ("density") ***** shared x,y x = [-1 0 0.5 1 Inf]; y = gampdf (x, 1, 2); ***** assert (exppdf (x, 2*ones (1,5)), y) ***** assert (exppdf (x, 2*[1 0 NaN 1 1]), [y(1) NaN NaN y(4:5)]) ***** assert (exppdf ([x, NaN], 2), [y, NaN]) ***** assert (exppdf (single ([x, NaN]), 2), single ([y, NaN])) ***** assert (exppdf ([x, NaN], single (2)), single ([y, NaN])) ***** error exppdf () ***** error exppdf (1,2,3) ***** error ... exppdf (ones (3), ones (2)) ***** error ... exppdf (ones (2), ones (3)) ***** error exppdf (i, 2) ***** error exppdf (2, i) 11 tests, 11 passed, 0 known failure, 0 skipped [inst/dist_fun/tripdf.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/dist_fun/tripdf.m ***** demo ## Plot various CDFs from the triangular distribution x = 0.001:0.001:10; y1 = tripdf (x, 3, 4, 6); y2 = tripdf (x, 1, 2, 5); y3 = tripdf (x, 2, 3, 9); y4 = tripdf (x, 2, 5, 9); plot (x, y1, "-b", x, y2, "-g", x, y3, "-r", x, y4, "-c") grid on xlim ([0, 10]) legend ({"a = 3, b = 4, c = 6", "a = 1, b = 2, c = 5", ... "a = 2, b = 3, c = 9", "a = 2, b = 5, c = 9"}, ... "location", "northeast") title ("Triangular CDF") xlabel ("values in x") ylabel ("probability") ***** shared x, y, deps x = [-1, 0, 0.1, 0.5, 0.9, 1, 2] + 1; y = [0, 0, 0.4, 2, 0.4, 0, 0]; deps = 2*eps; ***** assert (tripdf (x, ones (1,7), 1.5*ones (1,7), 2*ones (1,7)), y, deps) ***** assert (tripdf (x, 1*ones (1,7), 1.5, 2), y, deps) ***** assert (tripdf (x, 1, 1.5, 2*ones (1,7)), y, deps) ***** assert (tripdf (x, 1, 1.5*ones (1,7), 2), y, deps) ***** assert (tripdf (x, 1, 1.5, 2), y, deps) ***** assert (tripdf (x, [1, 1, NaN, 1, 1, 1, 1], 1.5, 2), [y(1:2), NaN, y(4:7)], deps) ***** assert (tripdf (x, 1, 1.5, 2*[1, 1, NaN, 1, 1, 1, 1]), [y(1:2), NaN, y(4:7)], deps) ***** assert (tripdf (x, 1, 1.5*[1, 1, NaN, 1, 1, 1, 1], 2), [y(1:2), NaN, y(4:7)], deps) ***** assert (tripdf ([x, NaN], 1, 1.5, 2), [y, NaN], deps) ***** assert (tripdf (single ([x, NaN]), 1, 1.5, 2), single ([y, NaN]), eps("single")) ***** assert (tripdf ([x, NaN], single (1), 1.5, 2), single ([y, NaN]), eps("single")) ***** assert (tripdf ([x, NaN], 1, 1.5, single (2)), single ([y, NaN]), eps("single")) ***** assert (tripdf ([x, NaN], 1, single (1.5), 2), single ([y, NaN]), eps("single")) ***** error tripdf () ***** error tripdf (1) ***** error tripdf (1, 2) ***** error tripdf (1, 2, 3) ***** error ... tripdf (1, 2, 3, 4, 5) ***** error ... tripdf (ones (3), ones (2), ones(2), ones(2)) ***** error ... tripdf (ones (2), ones (3), ones(2), ones(2)) ***** error ... tripdf (ones (2), ones (2), ones(3), ones(2)) ***** error ... tripdf (ones (2), ones (2), ones(2), ones(3)) ***** error tripdf (i, 2, 3, 4) ***** error tripdf (1, i, 3, 4) ***** error tripdf (1, 2, i, 4) ***** error tripdf (1, 2, 3, i) 26 tests, 26 passed, 0 known failure, 0 skipped [inst/dist_fun/nctinv.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/dist_fun/nctinv.m ***** demo ## Plot various iCDFs from the noncentral T distribution p = 0.001:0.001:0.999; x1 = nctinv (p, 1, 0); x2 = nctinv (p, 4, 0); x3 = nctinv (p, 1, 2); x4 = nctinv (p, 4, 2); plot (p, x1, "-r", p, x2, "-g", p, x3, "-k", p, x4, "-m") grid on ylim ([-5, 5]) legend ({"df = 1, μ = 0", "df = 4, μ = 0", ... "df = 1, μ = 2", "df = 4, μ = 2"}, "location", "northwest") title ("Noncentral T iCDF") xlabel ("probability") ylabel ("values in x") ***** demo ## Compare the noncentral T iCDF with MU = 1 to the T iCDF ## with the same number of degrees of freedom (10). p = 0.001:0.001:0.999; x1 = nctinv (p, 10, 1); x2 = tinv (p, 10); plot (p, x1, "-", p, x2, "-"); grid on ylim ([-5, 5]) legend ({"Noncentral T(10,1)", "T(10)"}, "location", "northwest") title ("Noncentral T vs T quantile functions") xlabel ("probability") ylabel ("values in x") ***** test x = [-Inf,-0.3347,0.1756,0.5209,0.8279,1.1424,1.5021,1.9633,2.6571,4.0845,Inf]; assert (nctinv ([0:0.1:1], 2, 1), x, 1e-4); ***** test x = [-Inf,1.5756,2.0827,2.5343,3.0043,3.5406,4.2050,5.1128,6.5510,9.6442,Inf]; assert (nctinv ([0:0.1:1], 2, 3), x, 1e-4); ***** test x = [-Inf,2.2167,2.9567,3.7276,4.6464,5.8455,7.5619,10.3327,15.7569,31.8159,Inf]; assert (nctinv ([0:0.1:1], 1, 4), x, 1e-4); ***** test x = [1.7791 1.9368 2.0239 2.0801 2.1195 2.1489]; assert (nctinv (0.05, [1, 2, 3, 4, 5, 6], 4), x, 1e-4); ***** test x = [-0.7755, 0.3670, 1.2554, 2.0239, 2.7348, 3.4154]; assert (nctinv (0.05, 3, [1, 2, 3, 4, 5, 6]), x, 1e-4); ***** test x = [-0.7183, 0.3624, 1.2878, 2.1195, -3.5413, 3.6430]; assert (nctinv (0.05, 5, [1, 2, 3, 4, -1, 6]), x, 1e-4); ***** test assert (nctinv (0.996, 5, 8), 30.02610554063658, 2e-11); ***** error nctinv () ***** error nctinv (1) ***** error nctinv (1, 2) ***** error ... nctinv (ones (3), ones (2), ones (2)) ***** error ... nctinv (ones (2), ones (3), ones (2)) ***** error ... nctinv (ones (2), ones (2), ones (3)) ***** error nctinv (i, 2, 2) ***** error nctinv (2, i, 2) ***** error nctinv (2, 2, i) 16 tests, 16 passed, 0 known failure, 0 skipped [inst/dist_fun/ncfpdf.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/dist_fun/ncfpdf.m ***** demo ## Plot various PDFs from the noncentral F distribution x = 0:0.01:5; y1 = ncfpdf (x, 2, 5, 1); y2 = ncfpdf (x, 2, 5, 2); y3 = ncfpdf (x, 5, 10, 1); y4 = ncfpdf (x, 10, 20, 10); plot (x, y1, "-r", x, y2, "-g", x, y3, "-k", x, y4, "-m") grid on xlim ([0, 5]) ylim ([0, 0.8]) legend ({"df1 = 2, df2 = 5, λ = 1", "df1 = 2, df2 = 5, λ = 2", ... "df1 = 5, df2 = 10, λ = 1", "df1 = 10, df2 = 20, λ = 10"}, ... "location", "northeast") title ("Noncentral F PDF") xlabel ("values in x") ylabel ("density") ***** demo ## Compare the noncentral F PDF with LAMBDA = 10 to the F PDF with the ## same number of numerator and denominator degrees of freedom (5, 20) x = 0.01:0.1:10.01; y1 = ncfpdf (x, 5, 20, 10); y2 = fpdf (x, 5, 20); plot (x, y1, "-", x, y2, "-"); grid on xlim ([0, 10]) ylim ([0, 0.8]) legend ({"Noncentral F(5,20,10)", "F(5,20)"}, "location", "northeast") title ("Noncentral F vs F PDFs") xlabel ("values in x") ylabel ("density") ***** shared x1, df1, df2, lambda x1 = [-Inf, 2, NaN, 4, Inf]; df1 = [2, 0, -1, 1, 4]; df2 = [2, 4, 5, 6, 8]; lambda = [1, NaN, 3, -1, 2]; ***** assert (ncfpdf (x1, df1, df2, lambda), [0, NaN, NaN, NaN, NaN]); ***** assert (ncfpdf (x1, df1, df2, 1), [0, NaN, NaN, ... 0.05607937264237208, NaN], 1e-14); ***** assert (ncfpdf (x1, df1, df2, 3), [0, NaN, NaN, ... 0.080125760971946518, NaN], 1e-14); ***** assert (ncfpdf (x1, df1, df2, 2), [0, NaN, NaN, ... 0.0715902008258656, NaN], 1e-14); ***** assert (ncfpdf (x1, 3, 5, lambda), [0, NaN, NaN, NaN, NaN]); ***** assert (ncfpdf (2, df1, df2, lambda), [0.1254046999837947, NaN, NaN, ... NaN, 0.2152571783045893], 1e-14); ***** assert (ncfpdf (4, df1, df2, lambda), [0.05067089541001374, NaN, NaN, ... NaN, 0.05560846335398539], 1e-14); ***** error ncfpdf () ***** error ncfpdf (1) ***** error ncfpdf (1, 2) ***** error ncfpdf (1, 2, 3) ***** error ... ncfpdf (ones (3), ones (2), ones (2), ones (2)) ***** error ... ncfpdf (ones (2), ones (3), ones (2), ones (2)) ***** error ... ncfpdf (ones (2), ones (2), ones (3), ones (2)) ***** error ... ncfpdf (ones (2), ones (2), ones (2), ones (3)) ***** error ncfpdf (i, 2, 2, 2) ***** error ncfpdf (2, i, 2, 2) ***** error ncfpdf (2, 2, i, 2) ***** error ncfpdf (2, 2, 2, i) 19 tests, 19 passed, 0 known failure, 0 skipped [inst/dist_fun/ncx2rnd.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/dist_fun/ncx2rnd.m ***** assert (size (ncx2rnd (1, 1)), [1 1]) ***** assert (size (ncx2rnd (1, ones (2,1))), [2, 1]) ***** assert (size (ncx2rnd (1, ones (2,2))), [2, 2]) ***** assert (size (ncx2rnd (ones (2,1), 1)), [2, 1]) ***** assert (size (ncx2rnd (ones (2,2), 1)), [2, 2]) ***** assert (size (ncx2rnd (1, 1, 3)), [3, 3]) ***** assert (size (ncx2rnd (1, 1, [4, 1])), [4, 1]) ***** assert (size (ncx2rnd (1, 1, 4, 1)), [4, 1]) ***** assert (size (ncx2rnd (1, 1, 4, 1, 5)), [4, 1, 5]) ***** assert (size (ncx2rnd (1, 1, 0, 1)), [0, 1]) ***** assert (size (ncx2rnd (1, 1, 1, 0)), [1, 0]) ***** assert (size (ncx2rnd (1, 1, 1, 2, 0, 5)), [1, 2, 0, 5]) ***** assert (class (ncx2rnd (1, 1)), "double") ***** assert (class (ncx2rnd (1, single (1))), "single") ***** assert (class (ncx2rnd (1, single ([1, 1]))), "single") ***** assert (class (ncx2rnd (single (1), 1)), "single") ***** assert (class (ncx2rnd (single ([1, 1]), 1)), "single") ***** error ncx2rnd () ***** error ncx2rnd (1) ***** error ... ncx2rnd (ones (3), ones (2)) ***** error ... ncx2rnd (ones (2), ones (3)) ***** error ncx2rnd (i, 2) ***** error ncx2rnd (1, i) ***** error ... ncx2rnd (1, 2, -1) ***** error ... ncx2rnd (1, 2, 1.2) ***** error ... ncx2rnd (1, 2, ones (2)) ***** error ... ncx2rnd (1, 2, [2 -1 2]) ***** error ... ncx2rnd (1, 2, [2 0 2.5]) ***** error ... ncx2rnd (1, 2, 2, -1, 5) ***** error ... ncx2rnd (1, 2, 2, 1.5, 5) ***** error ... ncx2rnd (2, ones (2), 3) ***** error ... ncx2rnd (2, ones (2), [3, 2]) ***** error ... ncx2rnd (2, ones (2), 3, 2) 33 tests, 33 passed, 0 known failure, 0 skipped [inst/dist_fun/hygeinv.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/dist_fun/hygeinv.m ***** demo ## Plot various iCDFs from the hypergeometric distribution p = 0.001:0.001:0.999; x1 = hygeinv (p, 500, 50, 100); x2 = hygeinv (p, 500, 60, 200); x3 = hygeinv (p, 500, 70, 300); plot (p, x1, "-b", p, x2, "-g", p, x3, "-r") grid on ylim ([0, 60]) legend ({"m = 500, k = 50, n = 100", "m = 500, k = 60, n = 200", ... "m = 500, k = 70, n = 300"}, "location", "northwest") title ("Hypergeometric iCDF") xlabel ("probability") ylabel ("values in p (number of successes)") ***** shared p p = [-1 0 0.5 1 2]; ***** assert (hygeinv (p, 4*ones (1,5), 2*ones (1,5), 2*ones (1,5)), [NaN 0 1 2 NaN]) ***** assert (hygeinv (p, 4*ones (1,5), 2, 2), [NaN 0 1 2 NaN]) ***** assert (hygeinv (p, 4, 2*ones (1,5), 2), [NaN 0 1 2 NaN]) ***** assert (hygeinv (p, 4, 2, 2*ones (1,5)), [NaN 0 1 2 NaN]) ***** assert (hygeinv (p, 4*[1 -1 NaN 1.1 1], 2, 2), [NaN NaN NaN NaN NaN]) ***** assert (hygeinv (p, 4, 2*[1 -1 NaN 1.1 1], 2), [NaN NaN NaN NaN NaN]) ***** assert (hygeinv (p, 4, 5, 2), [NaN NaN NaN NaN NaN]) ***** assert (hygeinv (p, 4, 2, 2*[1 -1 NaN 1.1 1]), [NaN NaN NaN NaN NaN]) ***** assert (hygeinv (p, 4, 2, 5), [NaN NaN NaN NaN NaN]) ***** assert (hygeinv ([p(1:2) NaN p(4:5)], 4, 2, 2), [NaN 0 NaN 2 NaN]) ***** assert (hygeinv ([p, NaN], 4, 2, 2), [NaN 0 1 2 NaN NaN]) ***** assert (hygeinv (single ([p, NaN]), 4, 2, 2), single ([NaN 0 1 2 NaN NaN])) ***** assert (hygeinv ([p, NaN], single (4), 2, 2), single ([NaN 0 1 2 NaN NaN])) ***** assert (hygeinv ([p, NaN], 4, single (2), 2), single ([NaN 0 1 2 NaN NaN])) ***** assert (hygeinv ([p, NaN], 4, 2, single (2)), single ([NaN 0 1 2 NaN NaN])) ***** error hygeinv () ***** error hygeinv (1) ***** error hygeinv (1,2) ***** error hygeinv (1,2,3) ***** error ... hygeinv (ones (2), ones (3), 1, 1) ***** error ... hygeinv (1, ones (2), ones (3), 1) ***** error ... hygeinv (1, 1, ones (2), ones (3)) ***** error hygeinv (i, 2, 2, 2) ***** error hygeinv (2, i, 2, 2) ***** error hygeinv (2, 2, i, 2) ***** error hygeinv (2, 2, 2, i) 26 tests, 26 passed, 0 known failure, 0 skipped [inst/dist_fun/wblcdf.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/dist_fun/wblcdf.m ***** demo ## Plot various CDFs from the Weibull distribution x = 0:0.001:2.5; p1 = wblcdf (x, 1, 0.5); p2 = wblcdf (x, 1, 1); p3 = wblcdf (x, 1, 1.5); p4 = wblcdf (x, 1, 5); plot (x, p1, "-b", x, p2, "-r", x, p3, "-m", x, p4, "-g") grid on legend ({"λ = 1, k = 0.5", "λ = 1, k = 1", ... "λ = 1, k = 1.5", "λ = 1, k = 5"}, "location", "southeast") title ("Weibull CDF") xlabel ("values in x") ylabel ("probability") ***** shared x, y x = [-1 0 0.5 1 Inf]; y = [0, 1-exp(-x(2:4)), 1]; ***** assert (wblcdf (x, ones (1,5), ones (1,5)), y) ***** assert (wblcdf (x, ones (1,5), ones (1,5), "upper"), 1 - y) ***** assert (wblcdf (x, "upper"), 1 - y) ***** assert (wblcdf (x, 1, ones (1,5)), y) ***** assert (wblcdf (x, ones (1,5), 1), y) ***** assert (wblcdf (x, [0 1 NaN Inf 1], 1), [NaN 0 NaN 0 1]) ***** assert (wblcdf (x, [0 1 NaN Inf 1], 1, "upper"), 1 - [NaN 0 NaN 0 1]) ***** assert (wblcdf (x, 1, [0 1 NaN Inf 1]), [NaN 0 NaN y(4:5)]) ***** assert (wblcdf (x, 1, [0 1 NaN Inf 1], "upper"), 1 - [NaN 0 NaN y(4:5)]) ***** assert (wblcdf ([x(1:2) NaN x(4:5)], 1, 1), [y(1:2) NaN y(4:5)]) ***** assert (wblcdf ([x(1:2) NaN x(4:5)], 1, 1, "upper"), 1 - [y(1:2) NaN y(4:5)]) ***** assert (wblcdf ([x, NaN], 1, 1), [y, NaN]) ***** assert (wblcdf (single ([x, NaN]), 1, 1), single ([y, NaN])) ***** assert (wblcdf ([x, NaN], single (1), 1), single ([y, NaN])) ***** assert (wblcdf ([x, NaN], 1, single (1)), single ([y, NaN])) ***** error wblcdf () ***** error wblcdf (1,2,3,4,5,6,7) ***** error wblcdf (1, 2, 3, 4, "uper") ***** error ... wblcdf (ones (3), ones (2), ones (2)) ***** error wblcdf (2, 3, 4, [1, 2]) ***** error ... [p, plo, pup] = wblcdf (1, 2, 3) ***** error [p, plo, pup] = ... wblcdf (1, 2, 3, [1, 0; 0, 1], 0) ***** error [p, plo, pup] = ... wblcdf (1, 2, 3, [1, 0; 0, 1], 1.22) ***** error [p, plo, pup] = ... wblcdf (1, 2, 3, [1, 0; 0, 1], "alpha", "upper") ***** error wblcdf (i, 2, 2) ***** error wblcdf (2, i, 2) ***** error wblcdf (2, 2, i) ***** error ... [p, plo, pup] =wblcdf (1, 2, 3, [1, 0; 0, -inf], 0.04) 28 tests, 28 passed, 0 known failure, 0 skipped [inst/dist_fun/plcdf.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/dist_fun/plcdf.m ***** demo ## Plot various CDFs from the Piecewise linear distribution data = 0:0.01:10; x1 = [0, 1, 3, 4, 7, 10]; Fx1 = [0, 0.2, 0.5, 0.6, 0.7, 1]; x2 = [0, 2, 5, 6, 7, 8]; Fx2 = [0, 0.1, 0.3, 0.6, 0.9, 1]; p1 = plcdf (data, x1, Fx1); p2 = plcdf (data, x2, Fx2); plot (data, p1, "-b", data, p2, "g") grid on ylim ([0, 1]) xlim ([0, 10]) legend ({"x1, Fx1", "x2, Fx2"}, "location", "southeast") title ("Piecewise linear CDF") xlabel ("values in data") ylabel ("probability") ***** test data = 0:0.2:1; p = plcdf (data, [0, 1], [0, 1]); assert (p, data); ***** test data = 0:0.2:1; p = plcdf (data, [0, 2], [0, 1]); assert (p, 0.5 * data); ***** test data = 0:0.2:1; p = plcdf (data, [0, 1], [0, 0.5]); assert (p, 0.5 * data); ***** test data = 0:0.2:1; p = plcdf (data, [0, 0.5], [0, 1]); assert (p, [0, 0.4, 0.8, 1, 1, 1]); ***** test data = 0:0.2:1; p = plcdf (data, [0, 1], [0, 1], "upper"); assert (p, 1 - data); ***** error plcdf () ***** error plcdf (1) ***** error plcdf (1, 2) ***** error plcdf (1, 2, 3, "uper") ***** error plcdf (1, 2, 3, 4) ***** error ... plcdf (1, [0, 1, 2], [0, 1]) ***** error ... plcdf (1, [0], [1]) ***** error ... plcdf (1, [0, 1, 2], [0, 1, 1.5]) ***** error ... plcdf (1, [0, 1, 2], [0, i, 1]) ***** error ... plcdf (i, [0, 1, 2], [0, 0.5, 1]) ***** error ... plcdf (1, [0, i, 2], [0, 0.5, 1]) ***** error ... plcdf (1, [0, 1, 2], [0, 0.5i, 1]) 17 tests, 17 passed, 0 known failure, 0 skipped [inst/dist_fun/evinv.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/dist_fun/evinv.m ***** demo ## Plot various iCDFs from the extreme value distribution p = 0.001:0.001:0.999; x1 = evinv (p, 0.5, 2); x2 = evinv (p, 1.0, 2); x3 = evinv (p, 1.5, 3); x4 = evinv (p, 3.0, 4); plot (p, x1, "-b", p, x2, "-g", p, x3, "-r", p, x4, "-c") grid on ylim ([-10, 10]) legend ({"μ = 0.5, σ = 2", "μ = 1.0, σ = 2", ... "μ = 1.5, σ = 3", "μ = 3.0, σ = 4"}, "location", "northwest") title ("Extreme value iCDF") xlabel ("probability") ylabel ("values in x") ***** shared p, x p = [0, 0.05, 0.5 0.95]; x = [-Inf, -2.9702, -0.3665, 1.0972]; ***** assert (evinv (p), x, 1e-4) ***** assert (evinv (p, zeros (1,4), ones (1,4)), x, 1e-4) ***** assert (evinv (p, 0, ones (1,4)), x, 1e-4) ***** assert (evinv (p, zeros (1,4), 1), x, 1e-4) ***** assert (evinv (p, [0, -Inf, NaN, Inf], 1), [-Inf, -Inf, NaN, Inf], 1e-4) ***** assert (evinv (p, 0, [Inf, NaN, -1, 0]), [-Inf, NaN, NaN, NaN], 1e-4) ***** assert (evinv ([p(1:2), NaN, p(4)], 0, 1), [x(1:2), NaN, x(4)], 1e-4) ***** assert (evinv ([p, NaN], 0, 1), [x, NaN], 1e-4) ***** assert (evinv (single ([p, NaN]), 0, 1), single ([x, NaN]), 1e-4) ***** assert (evinv ([p, NaN], single (0), 1), single ([x, NaN]), 1e-4) ***** assert (evinv ([p, NaN], 0, single (1)), single ([x, NaN]), 1e-4) ***** error evinv () ***** error evinv (1,2,3,4,5,6) ***** error ... evinv (ones (3), ones (2), ones (2)) ***** error ... [p, plo, pup] = evinv (2, 3, 4, [1, 2]) ***** error ... [p, plo, pup] = evinv (1, 2, 3) ***** error [p, plo, pup] = ... evinv (1, 2, 3, [1, 0; 0, 1], 0) ***** error [p, plo, pup] = ... evinv (1, 2, 3, [1, 0; 0, 1], 1.22) ***** error evinv (i, 2, 2) ***** error evinv (2, i, 2) ***** error evinv (2, 2, i) ***** error ... [p, plo, pup] = evinv (1, 2, 3, [-1, -10; -Inf, -Inf], 0.04) 22 tests, 22 passed, 0 known failure, 0 skipped [inst/dist_fun/mnrnd.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/dist_fun/mnrnd.m ***** test n = 10; pk = [0.2, 0.5, 0.3]; r = mnrnd (n, pk); assert (size (r), size (pk)); assert (all (r >= 0)); assert (all (round (r) == r)); assert (sum (r) == n); ***** test n = 10 * ones (3, 1); pk = [0.2, 0.5, 0.3]; r = mnrnd (n, pk); assert (size (r), [length(n), length(pk)]); assert (all (r >= 0)); assert (all (round (r) == r)); assert (all (sum (r, 2) == n)); ***** test n = (1:2)'; pk = [0.2, 0.5, 0.3; 0.1, 0.1, 0.8]; r = mnrnd (n, pk); assert (size (r), size (pk)); assert (all (r >= 0)); assert (all (round (r) == r)); assert (all (sum (r, 2) == n)); 3 tests, 3 passed, 0 known failure, 0 skipped [inst/dist_fun/gamcdf.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/dist_fun/gamcdf.m ***** demo ## Plot various CDFs from the Gamma distribution x = 0:0.01:20; p1 = gamcdf (x, 1, 2); p2 = gamcdf (x, 2, 2); p3 = gamcdf (x, 3, 2); p4 = gamcdf (x, 5, 1); p5 = gamcdf (x, 9, 0.5); p6 = gamcdf (x, 7.5, 1); p7 = gamcdf (x, 0.5, 1); plot (x, p1, "-r", x, p2, "-g", x, p3, "-y", x, p4, "-m", ... x, p5, "-k", x, p6, "-b", x, p7, "-c") grid on legend ({"α = 1, β = 2", "α = 2, β = 2", "α = 3, β = 2", ... "α = 5, β = 1", "α = 9, β = 0.5", "α = 7.5, β = 1", ... "α = 0.5, β = 1"}, "location", "southeast") title ("Gamma CDF") xlabel ("values in x") ylabel ("probability") ***** shared x, y, u x = [-1, 0, 0.5, 1, 2, Inf]; y = [0, gammainc(x(2:end), 1)]; u = [0, NaN, NaN, 1, 0.1353352832366127, 0]; ***** assert (gamcdf (x, ones (1,6), ones (1,6)), y, eps) ***** assert (gamcdf (x, ones (1,6), ones (1,6), []), y, eps) ***** assert (gamcdf (x, 1, ones (1,6)), y, eps) ***** assert (gamcdf (x, ones (1,6), 1), y, eps) ***** assert (gamcdf (x, [0, -Inf, NaN, Inf, 1, 1], 1), [1, NaN, NaN, 0, y(5:6)], eps) ***** assert (gamcdf (x, [0, -Inf, NaN, Inf, 1, 1], 1, "upper"), u, eps) ***** assert (gamcdf (x, 1, [0, -Inf, NaN, Inf, 1, 1]), [NaN, NaN, NaN, 0, y(5:6)], eps) ***** assert (gamcdf ([x(1:2), NaN, x(4:6)], 1, 1), [y(1:2), NaN, y(4:6)], eps) ***** assert (gamcdf ([x, NaN], 1, 1), [y, NaN]) ***** assert (gamcdf (single ([x, NaN]), 1, 1), single ([y, NaN]), eps ("single")) ***** assert (gamcdf ([x, NaN], single (1), 1), single ([y, NaN]), eps ("single")) ***** assert (gamcdf ([x, NaN], 1, single (1)), single ([y, NaN]), eps ("single")) ***** error gamcdf () ***** error gamcdf (1) ***** error gamcdf (1, 2, 3, 4, 5, 6, 7) ***** error gamcdf (1, 2, 3, "uper") ***** error gamcdf (1, 2, 3, 4, 5, "uper") ***** error gamcdf (2, 3, 4, [1, 2]) ***** error ... [p, plo, pup] = gamcdf (1, 2, 3) ***** error ... [p, plo, pup] = gamcdf (1, 2, 3, "upper") ***** error [p, plo, pup] = ... gamcdf (1, 2, 3, [1, 0; 0, 1], 0) ***** error [p, plo, pup] = ... gamcdf (1, 2, 3, [1, 0; 0, 1], 1.22) ***** error [p, plo, pup] = ... gamcdf (1, 2, 3, [1, 0; 0, 1], "alpha", "upper") ***** error ... gamcdf (ones (3), ones (2), ones (2)) ***** error ... gamcdf (ones (2), ones (3), ones (2)) ***** error ... gamcdf (ones (2), ones (2), ones (3)) ***** error gamcdf (i, 2, 2) ***** error gamcdf (2, i, 2) ***** error gamcdf (2, 2, i) ***** error ... [p, plo, pup] = gamcdf (1, 2, 3, [1, 0; 0, -inf], 0.04) 30 tests, 30 passed, 0 known failure, 0 skipped [inst/dist_fun/copularnd.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/dist_fun/copularnd.m ***** test theta = 0.5; r = copularnd ("Gaussian", theta); assert (size (r), [1, 2]); assert (all ((r >= 0) & (r <= 1))); ***** test theta = 0.5; df = 2; r = copularnd ("t", theta, df); assert (size (r), [1, 2]); assert (all ((r >= 0) & (r <= 1))); ***** test theta = 0.5; r = copularnd ("Clayton", theta); assert (size (r), [1, 2]); assert (all ((r >= 0) & (r <= 1))); ***** test theta = 0.5; n = 2; r = copularnd ("Clayton", theta, n); assert (size (r), [n, 2]); assert (all ((r >= 0) & (r <= 1))); ***** test theta = [1; 2]; n = 2; d = 3; r = copularnd ("Clayton", theta, n, d); assert (size (r), [n, d]); assert (all ((r >= 0) & (r <= 1))); 5 tests, 5 passed, 0 known failure, 0 skipped [inst/dist_fun/cauchycdf.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/dist_fun/cauchycdf.m ***** demo ## Plot various CDFs from the Cauchy distribution x = -5:0.01:5; p1 = cauchycdf (x, 0, 0.5); p2 = cauchycdf (x, 0, 1); p3 = cauchycdf (x, 0, 2); p4 = cauchycdf (x, -2, 1); plot (x, p1, "-b", x, p2, "-g", x, p3, "-r", x, p4, "-c") grid on xlim ([-5, 5]) legend ({"x0 = 0, γ = 0.5", "x0 = 0, γ = 1", ... "x0 = 0, γ = 2", "x0 = -2, γ = 1"}, "location", "southeast") title ("Cauchy CDF") xlabel ("values in x") ylabel ("probability") ***** shared x, y x = [-1 0 0.5 1 2]; y = 1/pi * atan ((x-1) / 2) + 1/2; ***** assert (cauchycdf (x, ones (1,5), 2*ones (1,5)), y) ***** assert (cauchycdf (x, 1, 2*ones (1,5)), y) ***** assert (cauchycdf (x, ones (1,5), 2), y) ***** assert (cauchycdf (x, [-Inf 1 NaN 1 Inf], 2), [NaN y(2) NaN y(4) NaN]) ***** assert (cauchycdf (x, 1, 2*[0 1 NaN 1 Inf]), [NaN y(2) NaN y(4) NaN]) ***** assert (cauchycdf ([x(1:2) NaN x(4:5)], 1, 2), [y(1:2) NaN y(4:5)]) ***** assert (cauchycdf ([x, NaN], 1, 2), [y, NaN]) ***** assert (cauchycdf (single ([x, NaN]), 1, 2), single ([y, NaN]), eps ("single")) ***** assert (cauchycdf ([x, NaN], single (1), 2), single ([y, NaN]), eps ("single")) ***** assert (cauchycdf ([x, NaN], 1, single (2)), single ([y, NaN]), eps ("single")) ***** error cauchycdf () ***** error cauchycdf (1) ***** error ... cauchycdf (1, 2) ***** error ... cauchycdf (1, 2, 3, 4, 5) ***** error cauchycdf (1, 2, 3, "tail") ***** error cauchycdf (1, 2, 3, 4) ***** error ... cauchycdf (ones (3), ones (2), ones (2)) ***** error ... cauchycdf (ones (2), ones (3), ones (2)) ***** error ... cauchycdf (ones (2), ones (2), ones (3)) ***** error cauchycdf (i, 2, 2) ***** error cauchycdf (2, i, 2) ***** error cauchycdf (2, 2, i) 22 tests, 22 passed, 0 known failure, 0 skipped [inst/dist_fun/chi2rnd.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/dist_fun/chi2rnd.m ***** assert (size (chi2rnd (2)), [1, 1]) ***** assert (size (chi2rnd (ones (2,1))), [2, 1]) ***** assert (size (chi2rnd (ones (2,2))), [2, 2]) ***** assert (size (chi2rnd (1, 3)), [3, 3]) ***** assert (size (chi2rnd (1, [4 1])), [4, 1]) ***** assert (size (chi2rnd (1, 4, 1)), [4, 1]) ***** assert (size (chi2rnd (1, 4, 1)), [4, 1]) ***** assert (size (chi2rnd (1, 4, 1, 5)), [4, 1, 5]) ***** assert (size (chi2rnd (1, 0, 1)), [0, 1]) ***** assert (size (chi2rnd (1, 1, 0)), [1, 0]) ***** assert (size (chi2rnd (1, 1, 2, 0, 5)), [1, 2, 0, 5]) ***** assert (class (chi2rnd (2)), "double") ***** assert (class (chi2rnd (single (2))), "single") ***** assert (class (chi2rnd (single ([2 2]))), "single") ***** error chi2rnd () ***** error chi2rnd (i) ***** error ... chi2rnd (1, -1) ***** error ... chi2rnd (1, 1.2) ***** error ... chi2rnd (1, ones (2)) ***** error ... chi2rnd (1, [2 -1 2]) ***** error ... chi2rnd (1, [2 0 2.5]) ***** error ... chi2rnd (ones (2), ones (2)) ***** error ... chi2rnd (1, 2, -1, 5) ***** error ... chi2rnd (1, 2, 1.5, 5) ***** error chi2rnd (ones (2,2), 3) ***** error chi2rnd (ones (2,2), [3, 2]) ***** error chi2rnd (ones (2,2), 2, 3) 27 tests, 27 passed, 0 known failure, 0 skipped [inst/dist_fun/chi2cdf.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/dist_fun/chi2cdf.m ***** demo ## Plot various CDFs from the chi-squared distribution x = 0:0.01:8; p1 = chi2cdf (x, 1); p2 = chi2cdf (x, 2); p3 = chi2cdf (x, 3); p4 = chi2cdf (x, 4); p5 = chi2cdf (x, 6); p6 = chi2cdf (x, 9); plot (x, p1, "-b", x, p2, "-g", x, p3, "-r", ... x, p4, "-c", x, p5, "-m", x, p6, "-y") grid on xlim ([0, 8]) legend ({"df = 1", "df = 2", "df = 3", ... "df = 4", "df = 6", "df = 9"}, "location", "southeast") title ("Chi-squared CDF") xlabel ("values in x") ylabel ("probability") ***** shared x, p, u x = [-1, 0, 0.5, 1, 2]; p = [0, (1 - exp (-x(2:end) / 2))]; u = [1, 0, NaN, 0.3934693402873666, 0.6321205588285577]; ***** assert (chi2cdf (x, 2 * ones (1,5)), p, eps) ***** assert (chi2cdf (x, 2), p, eps) ***** assert (chi2cdf (x, 2 * [1, 0, NaN, 1, 1]), [p(1), 1, NaN, p(4:5)], eps) ***** assert (chi2cdf (x, 2 * [1, 0, NaN, 1, 1], "upper"), ... [p(1), 1, NaN, u(4:5)], eps) ***** assert (chi2cdf ([x(1:2), NaN, x(4:5)], 2), [p(1:2), NaN, p(4:5)], eps) ***** assert (chi2cdf ([x, NaN], 2), [p, NaN], eps) ***** assert (chi2cdf (single ([x, NaN]), 2), single ([p, NaN]), eps ("single")) ***** assert (chi2cdf ([x, NaN], single (2)), single ([p, NaN]), eps ("single")) ***** error chi2cdf () ***** error chi2cdf (1) ***** error chi2cdf (1, 2, 3, 4) ***** error chi2cdf (1, 2, 3) ***** error chi2cdf (1, 2, "uper") ***** error ... chi2cdf (ones (3), ones (2)) ***** error ... chi2cdf (ones (2), ones (3)) ***** error chi2cdf (i, 2) ***** error chi2cdf (2, i) 17 tests, 17 passed, 0 known failure, 0 skipped [inst/dist_fun/vmrnd.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/dist_fun/vmrnd.m ***** assert (size (vmrnd (1, 1)), [1 1]) ***** assert (size (vmrnd (1, ones (2,1))), [2, 1]) ***** assert (size (vmrnd (1, ones (2,2))), [2, 2]) ***** assert (size (vmrnd (ones (2,1), 1)), [2, 1]) ***** assert (size (vmrnd (ones (2,2), 1)), [2, 2]) ***** assert (size (vmrnd (1, 1, 3)), [3, 3]) ***** assert (size (vmrnd (1, 1, [4, 1])), [4, 1]) ***** assert (size (vmrnd (1, 1, 4, 1)), [4, 1]) ***** assert (size (vmrnd (1, 1, 4, 1, 5)), [4, 1, 5]) ***** assert (size (vmrnd (1, 1, 0, 1)), [0, 1]) ***** assert (size (vmrnd (1, 1, 1, 0)), [1, 0]) ***** assert (size (vmrnd (1, 1, 1, 2, 0, 5)), [1, 2, 0, 5]) ***** assert (class (vmrnd (1, 1)), "double") ***** assert (class (vmrnd (1, single (1))), "single") ***** assert (class (vmrnd (1, single ([1, 1]))), "single") ***** assert (class (vmrnd (single (1), 1)), "single") ***** assert (class (vmrnd (single ([1, 1]), 1)), "single") ***** error vmrnd () ***** error vmrnd (1) ***** error ... vmrnd (ones (3), ones (2)) ***** error ... vmrnd (ones (2), ones (3)) ***** error vmrnd (i, 2, 3) ***** error vmrnd (1, i, 3) ***** error ... vmrnd (1, 2, -1) ***** error ... vmrnd (1, 2, 1.2) ***** error ... vmrnd (1, 2, ones (2)) ***** error ... vmrnd (1, 2, [2 -1 2]) ***** error ... vmrnd (1, 2, [2 0 2.5]) ***** error ... vmrnd (1, 2, 2, -1, 5) ***** error ... vmrnd (1, 2, 2, 1.5, 5) ***** error ... vmrnd (2, ones (2), 3) ***** error ... vmrnd (2, ones (2), [3, 2]) ***** error ... vmrnd (2, ones (2), 3, 2) 33 tests, 33 passed, 0 known failure, 0 skipped [inst/dist_fun/bisapdf.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/dist_fun/bisapdf.m ***** demo ## Plot various PDFs from the Birnbaum-Saunders distribution x = 0.01:0.01:4; y1 = bisapdf (x, 1, 0.5); y2 = bisapdf (x, 1, 1); y3 = bisapdf (x, 1, 2); y4 = bisapdf (x, 1, 5); y5 = bisapdf (x, 1, 10); plot (x, y1, "-b", x, y2, "-g", x, y3, "-r", x, y4, "-c", x, y5, "-m") grid on ylim ([0, 1.5]) legend ({"β = 1 ,γ = 0.5", "β = 1, γ = 1", "β = 1, γ = 2", ... "β = 1, γ = 5", "β = 1, γ = 10"}, "location", "northeast") title ("Birnbaum-Saunders PDF") xlabel ("values in x") ylabel ("density") ***** demo ## Plot various PDFs from the Birnbaum-Saunders distribution x = 0.01:0.01:6; y1 = bisapdf (x, 1, 0.3); y2 = bisapdf (x, 2, 0.3); y3 = bisapdf (x, 1, 0.5); y4 = bisapdf (x, 3, 0.5); y5 = bisapdf (x, 5, 0.5); plot (x, y1, "-b", x, y2, "-g", x, y3, "-r", x, y4, "-c", x, y5, "-m") grid on ylim ([0, 1.5]) legend ({"β = 1, γ = 0.3", "β = 2, γ = 0.3", "β = 1, γ = 0.5", ... "β = 3, γ = 0.5", "β = 5, γ = 0.5"}, "location", "northeast") title ("Birnbaum-Saunders CDF") xlabel ("values in x") ylabel ("density") ***** shared x, y x = [-1, 0, 1, 2, Inf]; y = [0, 0, 0.3989422804014327, 0.1647717335503959, 0]; ***** assert (bisapdf (x, ones (1,5), ones (1,5)), y, eps) ***** assert (bisapdf (x, 1, 1), y, eps) ***** assert (bisapdf (x, 1, ones (1,5)), y, eps) ***** assert (bisapdf (x, ones (1,5), 1), y, eps) ***** assert (bisapdf (x, 1, [1, 1, NaN, 1, 1]), [y(1:2), NaN, y(4:5)], eps) ***** assert (bisapdf (x, [1, 1, NaN, 1, 1], 1), [y(1:2), NaN, y(4:5)], eps) ***** assert (bisapdf ([x, NaN], 1, 1), [y, NaN], eps) ***** assert (bisapdf (single ([x, NaN]), 1, 1), single ([y, NaN]), eps ("single")) ***** assert (bisapdf ([x, NaN], 1, single (1)), single ([y, NaN]), eps ("single")) ***** assert (bisapdf ([x, NaN], single (1), 1), single ([y, NaN]), eps ("single")) ***** error bisapdf () ***** error bisapdf (1) ***** error bisapdf (1, 2) ***** error bisapdf (1, 2, 3, 4) ***** error ... bisapdf (ones (3), ones (2), ones(2)) ***** error ... bisapdf (ones (2), ones (3), ones(2)) ***** error ... bisapdf (ones (2), ones (2), ones(3)) ***** error bisapdf (i, 4, 3) ***** error bisapdf (1, i, 3) ***** error bisapdf (1, 4, i) 20 tests, 20 passed, 0 known failure, 0 skipped [inst/dist_fun/unifcdf.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/dist_fun/unifcdf.m ***** demo ## Plot various CDFs from the continuous uniform distribution x = 0:0.1:10; p1 = unifcdf (x, 2, 5); p2 = unifcdf (x, 3, 9); plot (x, p1, "-b", x, p2, "-g") grid on xlim ([0, 10]) ylim ([0, 1]) legend ({"a = 2, b = 5", "a = 3, b = 9"}, "location", "southeast") title ("Continuous uniform CDF") xlabel ("values in x") ylabel ("probability") ***** shared x, y x = [-1 0 0.5 1 2] + 1; y = [0 0 0.5 1 1]; ***** assert (unifcdf (x, ones (1,5), 2*ones (1,5)), y) ***** assert (unifcdf (x, ones (1,5), 2*ones (1,5), "upper"), 1 - y) ***** assert (unifcdf (x, 1, 2*ones (1,5)), y) ***** assert (unifcdf (x, 1, 2*ones (1,5), "upper"), 1 - y) ***** assert (unifcdf (x, ones (1,5), 2), y) ***** assert (unifcdf (x, ones (1,5), 2, "upper"), 1 - y) ***** assert (unifcdf (x, [2 1 NaN 1 1], 2), [NaN 0 NaN 1 1]) ***** assert (unifcdf (x, [2 1 NaN 1 1], 2, "upper"), 1 - [NaN 0 NaN 1 1]) ***** assert (unifcdf (x, 1, 2*[0 1 NaN 1 1]), [NaN 0 NaN 1 1]) ***** assert (unifcdf (x, 1, 2*[0 1 NaN 1 1], "upper"), 1 - [NaN 0 NaN 1 1]) ***** assert (unifcdf ([x(1:2) NaN x(4:5)], 1, 2), [y(1:2) NaN y(4:5)]) ***** assert (unifcdf ([x(1:2) NaN x(4:5)], 1, 2, "upper"), 1 - [y(1:2) NaN y(4:5)]) ***** assert (unifcdf ([x, NaN], 1, 2), [y, NaN]) ***** assert (unifcdf (single ([x, NaN]), 1, 2), single ([y, NaN])) ***** assert (unifcdf ([x, NaN], single (1), 2), single ([y, NaN])) ***** assert (unifcdf ([x, NaN], 1, single (2)), single ([y, NaN])) ***** error unifcdf () ***** error unifcdf (1) ***** error unifcdf (1, 2) ***** error unifcdf (1, 2, 3, 4) ***** error unifcdf (1, 2, 3, "tail") ***** error ... unifcdf (ones (3), ones (2), ones (2)) ***** error ... unifcdf (ones (2), ones (3), ones (2)) ***** error ... unifcdf (ones (2), ones (2), ones (3)) ***** error unifcdf (i, 2, 2) ***** error unifcdf (2, i, 2) ***** error unifcdf (2, 2, i) 27 tests, 27 passed, 0 known failure, 0 skipped [inst/dist_fun/gpcdf.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/dist_fun/gpcdf.m ***** demo ## Plot various CDFs from the generalized Pareto distribution x = 0:0.001:5; p1 = gpcdf (x, 1, 1, 0); p2 = gpcdf (x, 5, 1, 0); p3 = gpcdf (x, 20, 1, 0); p4 = gpcdf (x, 1, 2, 0); p5 = gpcdf (x, 5, 2, 0); p6 = gpcdf (x, 20, 2, 0); plot (x, p1, "-b", x, p2, "-g", x, p3, "-r", ... x, p4, "-c", x, p5, "-m", x, p6, "-k") grid on xlim ([0, 5]) legend ({"k = 1, σ = 1, θ = 0", "k = 5, σ = 1, θ = 0", ... "k = 20, σ = 1, θ = 0", "k = 1, σ = 2, θ = 0", ... "k = 5, σ = 2, θ = 0", "k = 20, σ = 2, θ = 0"}, ... "location", "northwest") title ("Generalized Pareto CDF") xlabel ("values in x") ylabel ("probability") ***** shared x, y1, y1u, y2, y2u, y3, y3u x = [-Inf, -1, 0, 1/2, 1, Inf]; y1 = [0, 0, 0, 0.3934693402873666, 0.6321205588285577, 1]; y1u = [1, 1, 1, 0.6065306597126334, 0.3678794411714423, 0]; y2 = [0, 0, 0, 1/3, 1/2, 1]; y2u = [1, 1, 1, 2/3, 1/2, 0]; y3 = [0, 0, 0, 1/2, 1, 1]; y3u = [1, 1, 1, 1/2, 0, 0]; ***** assert (gpcdf (x, zeros (1,6), ones (1,6), zeros (1,6)), y1, eps) ***** assert (gpcdf (x, 0, 1, zeros (1,6)), y1, eps) ***** assert (gpcdf (x, 0, ones (1,6), 0), y1, eps) ***** assert (gpcdf (x, zeros (1,6), 1, 0), y1, eps) ***** assert (gpcdf (x, 0, 1, 0), y1, eps) ***** assert (gpcdf (x, 0, 1, [0, 0, 0, NaN, 0, 0]), [y1(1:3), NaN, y1(5:6)], eps) ***** assert (gpcdf (x, 0, [1, 1, 1, NaN, 1, 1], 0), [y1(1:3), NaN, y1(5:6)], eps) ***** assert (gpcdf (x, [0, 0, 0, NaN, 0, 0], 1, 0), [y1(1:3), NaN, y1(5:6)], eps) ***** assert (gpcdf ([x(1:3), NaN, x(5:6)], 0, 1, 0), [y1(1:3), NaN, y1(5:6)], eps) ***** assert (gpcdf (x, zeros (1,6), ones (1,6), zeros (1,6), "upper"), y1u, eps) ***** assert (gpcdf (x, 0, 1, zeros (1,6), "upper"), y1u, eps) ***** assert (gpcdf (x, 0, ones (1,6), 0, "upper"), y1u, eps) ***** assert (gpcdf (x, zeros (1,6), 1, 0, "upper"), y1u, eps) ***** assert (gpcdf (x, 0, 1, 0, "upper"), y1u, eps) ***** assert (gpcdf (x, ones (1,6), ones (1,6), zeros (1,6)), y2, eps) ***** assert (gpcdf (x, 1, 1, zeros (1,6)), y2, eps) ***** assert (gpcdf (x, 1, ones (1,6), 0), y2, eps) ***** assert (gpcdf (x, ones (1,6), 1, 0), y2, eps) ***** assert (gpcdf (x, 1, 1, 0), y2, eps) ***** assert (gpcdf (x, 1, 1, [0, 0, 0, NaN, 0, 0]), [y2(1:3), NaN, y2(5:6)], eps) ***** assert (gpcdf (x, 1, [1, 1, 1, NaN, 1, 1], 0), [y2(1:3), NaN, y2(5:6)], eps) ***** assert (gpcdf (x, [1, 1, 1, NaN, 1, 1], 1, 0), [y2(1:3), NaN, y2(5:6)], eps) ***** assert (gpcdf ([x(1:3), NaN, x(5:6)], 1, 1, 0), [y2(1:3), NaN, y2(5:6)], eps) ***** assert (gpcdf (x, ones (1,6), ones (1,6), zeros (1,6), "upper"), y2u, eps) ***** assert (gpcdf (x, 1, 1, zeros (1,6), "upper"), y2u, eps) ***** assert (gpcdf (x, 1, ones (1,6), 0, "upper"), y2u, eps) ***** assert (gpcdf (x, ones (1,6), 1, 0, "upper"), y2u, eps) ***** assert (gpcdf (x, 1, 1, 0, "upper"), y2u, eps) ***** assert (gpcdf (x, 1, 1, [0, 0, 0, NaN, 0, 0], "upper"), ... [y2u(1:3), NaN, y2u(5:6)], eps) ***** assert (gpcdf (x, 1, [1, 1, 1, NaN, 1, 1], 0, "upper"), ... [y2u(1:3), NaN, y2u(5:6)], eps) ***** assert (gpcdf (x, [1, 1, 1, NaN, 1, 1], 1, 0, "upper"), ... [y2u(1:3), NaN, y2u(5:6)], eps) ***** assert (gpcdf ([x(1:3), NaN, x(5:6)], 1, 1, 0, "upper"), ... [y2u(1:3), NaN, y2u(5:6)], eps) ***** assert (gpcdf (x, -ones (1,6), ones (1,6), zeros (1,6)), y3, eps) ***** assert (gpcdf (x, -1, 1, zeros (1,6)), y3, eps) ***** assert (gpcdf (x, -1, ones (1,6), 0), y3, eps) ***** assert (gpcdf (x, -ones (1,6), 1, 0), y3, eps) ***** assert (gpcdf (x, -1, 1, 0), y3, eps) ***** assert (gpcdf (x, -1, 1, [0, 0, 0, NaN, 0, 0]), [y3(1:3), NaN, y3(5:6)], eps) ***** assert (gpcdf (x, -1, [1, 1, 1, NaN, 1, 1], 0), [y3(1:3), NaN, y3(5:6)], eps) ***** assert (gpcdf (x, [-1, -1, -1, NaN, -1, -1], 1, 0), [y3(1:3), NaN, y3(5:6)], eps) ***** assert (gpcdf ([x(1:3), NaN, x(5:6)], -1, 1, 0), [y3(1:3), NaN, y3(5:6)], eps) ***** assert (gpcdf (x, -ones (1,6), ones (1,6), zeros (1,6), "upper"), y3u, eps) ***** assert (gpcdf (x, -1, 1, zeros (1,6), "upper"), y3u, eps) ***** assert (gpcdf (x, -1, ones (1,6), 0, "upper"), y3u, eps) ***** assert (gpcdf (x, -ones (1,6), 1, 0, "upper"), y3u, eps) ***** assert (gpcdf (x, -1, 1, 0, "upper"), y3u, eps) ***** assert (gpcdf (x, -1, 1, [0, 0, 0, NaN, 0, 0], "upper"), ... [y3u(1:3), NaN, y3u(5:6)], eps) ***** assert (gpcdf (x, -1, [1, 1, 1, NaN, 1, 1], 0, "upper"), ... [y3u(1:3), NaN, y3u(5:6)], eps) ***** assert (gpcdf (x, [-1, -1, -1, NaN, -1, -1], 1, 0, "upper"), ... [y3u(1:3), NaN, y3u(5:6)], eps) ***** assert (gpcdf ([x(1:3), NaN, x(5:6)], -1, 1, 0, "upper"), ... [y3u(1:3), NaN, y3u(5:6)], eps) ***** assert (gpcdf (single ([x, NaN]), 0, 1, 0), single ([y1, NaN]), eps("single")) ***** assert (gpcdf ([x, NaN], 0, 1, single (0)), single ([y1, NaN]), eps("single")) ***** assert (gpcdf ([x, NaN], 0, single (1), 0), single ([y1, NaN]), eps("single")) ***** assert (gpcdf ([x, NaN], single (0), 1, 0), single ([y1, NaN]), eps("single")) ***** assert (gpcdf (single ([x, NaN]), 1, 1, 0), single ([y2, NaN]), eps("single")) ***** assert (gpcdf ([x, NaN], 1, 1, single (0)), single ([y2, NaN]), eps("single")) ***** assert (gpcdf ([x, NaN], 1, single (1), 0), single ([y2, NaN]), eps("single")) ***** assert (gpcdf ([x, NaN], single (1), 1, 0), single ([y2, NaN]), eps("single")) ***** assert (gpcdf (single ([x, NaN]), -1, 1, 0), single ([y3, NaN]), eps("single")) ***** assert (gpcdf ([x, NaN], -1, 1, single (0)), single ([y3, NaN]), eps("single")) ***** assert (gpcdf ([x, NaN], -1, single (1), 0), single ([y3, NaN]), eps("single")) ***** assert (gpcdf ([x, NaN], single (-1), 1, 0), single ([y3, NaN]), eps("single")) ***** error gpcdf () ***** error gpcdf (1) ***** error gpcdf (1, 2) ***** error gpcdf (1, 2, 3) ***** error gpcdf (1, 2, 3, 4, "tail") ***** error gpcdf (1, 2, 3, 4, 5) ***** error ... gpcdf (ones (3), ones (2), ones(2), ones(2)) ***** error ... gpcdf (ones (2), ones (3), ones(2), ones(2)) ***** error ... gpcdf (ones (2), ones (2), ones(3), ones(2)) ***** error ... gpcdf (ones (2), ones (2), ones(2), ones(3)) ***** error gpcdf (i, 2, 3, 4) ***** error gpcdf (1, i, 3, 4) ***** error gpcdf (1, 2, i, 4) ***** error gpcdf (1, 2, 3, i) 76 tests, 76 passed, 0 known failure, 0 skipped [inst/dist_fun/bisacdf.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/dist_fun/bisacdf.m ***** demo ## Plot various CDFs from the Birnbaum-Saunders distribution x = 0.01:0.01:4; p1 = bisacdf (x, 1, 0.5); p2 = bisacdf (x, 1, 1); p3 = bisacdf (x, 1, 2); p4 = bisacdf (x, 1, 5); p5 = bisacdf (x, 1, 10); plot (x, p1, "-b", x, p2, "-g", x, p3, "-r", x, p4, "-c", x, p5, "-m") grid on legend ({"β = 1, γ = 0.5", "β = 1, γ = 1", "β = 1, γ = 2", ... "β = 1, γ = 5", "β = 1, γ = 10"}, "location", "southeast") title ("Birnbaum-Saunders CDF") xlabel ("values in x") ylabel ("probability") ***** demo ## Plot various CDFs from the Birnbaum-Saunders distribution x = 0.01:0.01:6; p1 = bisacdf (x, 1, 0.3); p2 = bisacdf (x, 2, 0.3); p3 = bisacdf (x, 1, 0.5); p4 = bisacdf (x, 3, 0.5); p5 = bisacdf (x, 5, 0.5); plot (x, p1, "-b", x, p2, "-g", x, p3, "-r", x, p4, "-c", x, p5, "-m") grid on legend ({"β = 1, γ = 0.3", "β = 2, γ = 0.3", "β = 1, γ = 0.5", ... "β = 3, γ = 0.5", "β = 5, γ = 0.5"}, "location", "southeast") title ("Birnbaum-Saunders CDF") xlabel ("values in x") ylabel ("probability") ***** shared x, y x = [-1, 0, 1, 2, Inf]; y = [0, 0, 1/2, 0.76024993890652337, 1]; ***** assert (bisacdf (x, ones (1,5), ones (1,5)), y, eps) ***** assert (bisacdf (x, 1, 1), y, eps) ***** assert (bisacdf (x, 1, ones (1,5)), y, eps) ***** assert (bisacdf (x, ones (1,5), 1), y, eps) ***** assert (bisacdf (x, 1, 1), y, eps) ***** assert (bisacdf (x, 1, [1, 1, NaN, 1, 1]), [y(1:2), NaN, y(4:5)], eps) ***** assert (bisacdf (x, [1, 1, NaN, 1, 1], 1), [y(1:2), NaN, y(4:5)], eps) ***** assert (bisacdf ([x, NaN], 1, 1), [y, NaN], eps) ***** assert (bisacdf (single ([x, NaN]), 1, 1), single ([y, NaN]), eps ("single")) ***** assert (bisacdf ([x, NaN], 1, single (1)), single ([y, NaN]), eps ("single")) ***** assert (bisacdf ([x, NaN], single (1), 1), single ([y, NaN]), eps ("single")) ***** error bisacdf () ***** error bisacdf (1) ***** error bisacdf (1, 2) ***** error ... bisacdf (1, 2, 3, 4, 5) ***** error bisacdf (1, 2, 3, "tail") ***** error bisacdf (1, 2, 3, 4) ***** error ... bisacdf (ones (3), ones (2), ones(2)) ***** error ... bisacdf (ones (2), ones (3), ones(2)) ***** error ... bisacdf (ones (2), ones (2), ones(3)) ***** error bisacdf (i, 4, 3) ***** error bisacdf (1, i, 3) ***** error bisacdf (1, 4, i) 23 tests, 23 passed, 0 known failure, 0 skipped [inst/dist_fun/finv.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/dist_fun/finv.m ***** demo ## Plot various iCDFs from the F distribution p = 0.001:0.001:0.999; x1 = finv (p, 1, 1); x2 = finv (p, 2, 1); x3 = finv (p, 5, 2); x4 = finv (p, 10, 1); x5 = finv (p, 100, 100); plot (p, x1, "-b", p, x2, "-g", p, x3, "-r", p, x4, "-c", p, x5, "-m") grid on ylim ([0, 4]) legend ({"df1 = 1, df2 = 2", "df1 = 2, df2 = 1", ... "df1 = 5, df2 = 2", "df1 = 10, df2 = 1", ... "df1 = 100, df2 = 100"}, "location", "northwest") title ("F iCDF") xlabel ("probability") ylabel ("values in x") ***** shared p p = [-1 0 0.5 1 2]; ***** assert (finv (p, 2*ones (1,5), 2*ones (1,5)), [NaN 0 1 Inf NaN]) ***** assert (finv (p, 2, 2*ones (1,5)), [NaN 0 1 Inf NaN]) ***** assert (finv (p, 2*ones (1,5), 2), [NaN 0 1 Inf NaN]) ***** assert (finv (p, [2 -Inf NaN Inf 2], 2), [NaN NaN NaN NaN NaN]) ***** assert (finv (p, 2, [2 -Inf NaN Inf 2]), [NaN NaN NaN NaN NaN]) ***** assert (finv ([p(1:2) NaN p(4:5)], 2, 2), [NaN 0 NaN Inf NaN]) ***** assert (finv ([p, NaN], 2, 2), [NaN 0 1 Inf NaN NaN]) ***** assert (finv (single ([p, NaN]), 2, 2), single ([NaN 0 1 Inf NaN NaN])) ***** assert (finv ([p, NaN], single (2), 2), single ([NaN 0 1 Inf NaN NaN])) ***** assert (finv ([p, NaN], 2, single (2)), single ([NaN 0 1 Inf NaN NaN])) ***** error finv () ***** error finv (1) ***** error finv (1,2) ***** error ... finv (ones (3), ones (2), ones (2)) ***** error ... finv (ones (2), ones (3), ones (2)) ***** error ... finv (ones (2), ones (2), ones (3)) ***** error finv (i, 2, 2) ***** error finv (2, i, 2) ***** error finv (2, 2, i) 19 tests, 19 passed, 0 known failure, 0 skipped [inst/dist_fun/gamrnd.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/dist_fun/gamrnd.m ***** assert (size (gamrnd (1, 1)), [1 1]) ***** assert (size (gamrnd (1, ones (2,1))), [2, 1]) ***** assert (size (gamrnd (1, ones (2,2))), [2, 2]) ***** assert (size (gamrnd (ones (2,1), 1)), [2, 1]) ***** assert (size (gamrnd (ones (2,2), 1)), [2, 2]) ***** assert (size (gamrnd (1, 1, 3)), [3, 3]) ***** assert (size (gamrnd (1, 1, [4, 1])), [4, 1]) ***** assert (size (gamrnd (1, 1, 4, 1)), [4, 1]) ***** assert (size (gamrnd (1, 1, 4, 1, 5)), [4, 1, 5]) ***** assert (size (gamrnd (1, 1, 0, 1)), [0, 1]) ***** assert (size (gamrnd (1, 1, 1, 0)), [1, 0]) ***** assert (size (gamrnd (1, 1, 1, 2, 0, 5)), [1, 2, 0, 5]) ***** assert (class (gamrnd (1, 1)), "double") ***** assert (class (gamrnd (1, single (1))), "single") ***** assert (class (gamrnd (1, single ([1, 1]))), "single") ***** assert (class (gamrnd (single (1), 1)), "single") ***** assert (class (gamrnd (single ([1, 1]), 1)), "single") ***** error gamrnd () ***** error gamrnd (1) ***** error ... gamrnd (ones (3), ones (2)) ***** error ... gamrnd (ones (2), ones (3)) ***** error gamrnd (i, 2, 3) ***** error gamrnd (1, i, 3) ***** error ... gamrnd (1, 2, -1) ***** error ... gamrnd (1, 2, 1.2) ***** error ... gamrnd (1, 2, ones (2)) ***** error ... gamrnd (1, 2, [2 -1 2]) ***** error ... gamrnd (1, 2, [2 0 2.5]) ***** error ... gamrnd (1, 2, 2, -1, 5) ***** error ... gamrnd (1, 2, 2, 1.5, 5) ***** error ... gamrnd (2, ones (2), 3) ***** error ... gamrnd (2, ones (2), [3, 2]) ***** error ... gamrnd (2, ones (2), 3, 2) 33 tests, 33 passed, 0 known failure, 0 skipped [inst/dist_fun/raylrnd.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/dist_fun/raylrnd.m ***** assert (size (raylrnd (2)), [1, 1]) ***** assert (size (raylrnd (ones (2,1))), [2, 1]) ***** assert (size (raylrnd (ones (2,2))), [2, 2]) ***** assert (size (raylrnd (1, 3)), [3, 3]) ***** assert (size (raylrnd (1, [4 1])), [4, 1]) ***** assert (size (raylrnd (1, 4, 1)), [4, 1]) ***** assert (size (raylrnd (1, 4, 1)), [4, 1]) ***** assert (size (raylrnd (1, 4, 1, 5)), [4, 1, 5]) ***** assert (size (raylrnd (1, 0, 1)), [0, 1]) ***** assert (size (raylrnd (1, 1, 0)), [1, 0]) ***** assert (size (raylrnd (1, 1, 2, 0, 5)), [1, 2, 0, 5]) ***** assert (raylrnd (0, 1, 1), NaN) ***** assert (raylrnd ([0, 0, 0], [1, 3]), [NaN, NaN, NaN]) ***** assert (class (raylrnd (2)), "double") ***** assert (class (raylrnd (single (2))), "single") ***** assert (class (raylrnd (single ([2 2]))), "single") ***** error raylrnd () ***** error raylrnd (i) ***** error ... raylrnd (1, -1) ***** error ... raylrnd (1, 1.2) ***** error ... raylrnd (1, ones (2)) ***** error ... raylrnd (1, [2 -1 2]) ***** error ... raylrnd (1, [2 0 2.5]) ***** error ... raylrnd (ones (2), ones (2)) ***** error ... raylrnd (1, 2, -1, 5) ***** error ... raylrnd (1, 2, 1.5, 5) ***** error raylrnd (ones (2,2), 3) ***** error raylrnd (ones (2,2), [3, 2]) ***** error raylrnd (ones (2,2), 2, 3) 29 tests, 29 passed, 0 known failure, 0 skipped [inst/dist_fun/mvnrnd.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/dist_fun/mvnrnd.m ***** error mvnrnd () ***** error mvnrnd ([2, 3, 4]) ***** error mvnrnd (ones (2, 2, 2), ones (1, 2, 3, 4)) ***** error mvnrnd (ones (1, 3), ones (1, 2, 3, 4)) ***** assert (size (mvnrnd ([2, 3, 4], [2, 2, 2])), [1, 3]) ***** assert (size (mvnrnd ([2, 3, 4], [2, 2, 2], 10)), [10, 3]) 6 tests, 6 passed, 0 known failure, 0 skipped [inst/dist_fun/burrinv.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/dist_fun/burrinv.m ***** demo ## Plot various iCDFs from the Burr type XII distribution p = 0.001:0.001:0.999; x1 = burrinv (p, 1, 1, 1); x2 = burrinv (p, 1, 1, 2); x3 = burrinv (p, 1, 1, 3); x4 = burrinv (p, 1, 2, 1); x5 = burrinv (p, 1, 3, 1); x6 = burrinv (p, 1, 0.5, 2); plot (p, x1, "-b", p, x2, "-g", p, x3, "-r", ... p, x4, "-c", p, x5, "-m", p, x6, "-k") grid on ylim ([0, 5]) legend ({"λ = 1, c = 1, k = 1", "λ = 1, c = 1, k = 2", ... "λ = 1, c = 1, k = 3", "λ = 1, c = 2, k = 1", ... "λ = 1, c = 3, k = 1", "λ = 1, c = 0.5, k = 2"}, ... "location", "northwest") title ("Burr type XII iCDF") xlabel ("probability") ylabel ("values in x") ***** shared p, y p = [-Inf, -1, 0, 1/2, 1, 2, Inf]; y = [NaN, NaN, 0, 1 , Inf, NaN, NaN]; ***** assert (burrinv (p, ones (1,7), ones (1,7), ones(1,7)), y, eps) ***** assert (burrinv (p, 1, 1, 1), y, eps) ***** assert (burrinv (p, [1, 1, 1, NaN, 1, 1, 1], 1, 1), [y(1:3), NaN, y(5:7)], eps) ***** assert (burrinv (p, 1, [1, 1, 1, NaN, 1, 1, 1], 1), [y(1:3), NaN, y(5:7)], eps) ***** assert (burrinv (p, 1, 1, [1, 1, 1, NaN, 1, 1, 1]), [y(1:3), NaN, y(5:7)], eps) ***** assert (burrinv ([p, NaN], 1, 1, 1), [y, NaN], eps) ***** assert (burrinv (single ([p, NaN]), 1, 1, 1), single ([y, NaN]), eps("single")) ***** assert (burrinv ([p, NaN], single (1), 1, 1), single ([y, NaN]), eps("single")) ***** assert (burrinv ([p, NaN], 1, single (1), 1), single ([y, NaN]), eps("single")) ***** assert (burrinv ([p, NaN], 1, 1, single (1)), single ([y, NaN]), eps("single")) ***** error burrinv () ***** error burrinv (1) ***** error burrinv (1, 2) ***** error burrinv (1, 2, 3) ***** error ... burrinv (1, 2, 3, 4, 5) ***** error ... burrinv (ones (3), ones (2), ones(2), ones(2)) ***** error ... burrinv (ones (2), ones (3), ones(2), ones(2)) ***** error ... burrinv (ones (2), ones (2), ones(3), ones(2)) ***** error ... burrinv (ones (2), ones (2), ones(2), ones(3)) ***** error burrinv (i, 2, 3, 4) ***** error burrinv (1, i, 3, 4) ***** error burrinv (1, 2, i, 4) ***** error burrinv (1, 2, 3, i) 23 tests, 23 passed, 0 known failure, 0 skipped [inst/dist_fun/loglpdf.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/dist_fun/loglpdf.m ***** demo ## Plot various PDFs from the log-logistic distribution x = 0.001:0.001:2; y1 = loglpdf (x, log (1), 1/0.5); y2 = loglpdf (x, log (1), 1); y3 = loglpdf (x, log (1), 1/2); y4 = loglpdf (x, log (1), 1/4); y5 = loglpdf (x, log (1), 1/8); plot (x, y1, "-b", x, y2, "-g", x, y3, "-r", x, y4, "-c", x, y5, "-m") grid on ylim ([0,3]) legend ({"σ = 2 (β = 0.5)", "σ = 1 (β = 1)", "σ = 0.5 (β = 2)", ... "σ = 0.25 (β = 4)", "σ = 0.125 (β = 8)"}, "location", "northeast") title ("Log-logistic PDF") xlabel ("values in x") ylabel ("density") text (0.1, 2.8, "μ = 0 (α = 1), values of σ (β) as shown in legend") ***** shared out1, out2 out1 = [0, 0, 1, 0.2500, 0.1111, 0.0625, 0.0400, 0.0278, 0]; out2 = [0, 0, 0.0811, 0.0416, 0.0278, 0.0207, 0.0165, 0]; ***** assert (loglpdf ([-1,0,realmin,1:5,Inf], 0, 1), out1, 1e-4) ***** assert (loglpdf ([-1,0,realmin,1:5,Inf], 0, 1), out1, 1e-4) ***** assert (loglpdf ([-1:5,Inf], 1, 3), out2, 1e-4) ***** assert (class (loglpdf (single (1), 2, 3)), "single") ***** assert (class (loglpdf (1, single (2), 3)), "single") ***** assert (class (loglpdf (1, 2, single (3))), "single") ***** error loglpdf (1) ***** error loglpdf (1, 2) ***** error ... loglpdf (1, ones (2), ones (3)) ***** error ... loglpdf (ones (2), 1, ones (3)) ***** error ... loglpdf (ones (2), ones (3), 1) ***** error loglpdf (i, 2, 3) ***** error loglpdf (1, i, 3) ***** error loglpdf (1, 2, i) 14 tests, 14 passed, 0 known failure, 0 skipped [inst/dist_fun/bvtcdf.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/dist_fun/bvtcdf.m ***** test x = [1, 2]; rho = [1, 0.5; 0.5, 1]; df = 4; assert (bvtcdf(x, rho(2), df), mvtcdf(x, rho, df), 1e-14); ***** test x = [3, 2;2, 4;1, 5]; rho = [1, 0.5; 0.5, 1]; df = 4; assert (bvtcdf(x, rho(2), df), mvtcdf(x, rho, df), 1e-14); 2 tests, 2 passed, 0 known failure, 0 skipped [inst/dist_fun/vmpdf.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/dist_fun/vmpdf.m ***** demo ## Plot various PDFs from the von Mises distribution x1 = [-pi:0.1:pi]; y1 = vmpdf (x1, 0, 0.5); y2 = vmpdf (x1, 0, 1); y3 = vmpdf (x1, 0, 2); y4 = vmpdf (x1, 0, 4); plot (x1, y1, "-r", x1, y2, "-g", x1, y3, "-b", x1, y4, "-c") grid on xlim ([-pi, pi]) ylim ([0, 0.8]) legend ({"μ = 0, k = 0.5", "μ = 0, k = 1", ... "μ = 0, k = 2", "μ = 0, k = 4"}, "location", "northwest") title ("Von Mises PDF") xlabel ("values in x") ylabel ("density") ***** shared x, y0, y1 x = [-pi:pi/2:pi]; y0 = [0.046245, 0.125708, 0.341710, 0.125708, 0.046245]; y1 = [0.046245, 0.069817, 0.654958, 0.014082, 0.000039]; ***** assert (vmpdf (x, 0, 1), y0, 1e-5) ***** assert (vmpdf (x, zeros (1,5), ones (1,5)), y0, 1e-6) ***** assert (vmpdf (x, 0, [1 2 3 4 5]), y1, 1e-6) ***** assert (isa (vmpdf (single (pi), 0, 1), "single"), true) ***** assert (isa (vmpdf (pi, single (0), 1), "single"), true) ***** assert (isa (vmpdf (pi, 0, single (1)), "single"), true) ***** error vmpdf () ***** error vmpdf (1) ***** error vmpdf (1, 2) ***** error ... vmpdf (ones (3), ones (2), ones (2)) ***** error ... vmpdf (ones (2), ones (3), ones (2)) ***** error ... vmpdf (ones (2), ones (2), ones (3)) ***** error vmpdf (i, 2, 2) ***** error vmpdf (2, i, 2) ***** error vmpdf (2, 2, i) 15 tests, 15 passed, 0 known failure, 0 skipped [inst/dist_fun/laplacernd.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/dist_fun/laplacernd.m ***** assert (size (laplacernd (1, 1)), [1 1]) ***** assert (size (laplacernd (1, ones (2,1))), [2, 1]) ***** assert (size (laplacernd (1, ones (2,2))), [2, 2]) ***** assert (size (laplacernd (ones (2,1), 1)), [2, 1]) ***** assert (size (laplacernd (ones (2,2), 1)), [2, 2]) ***** assert (size (laplacernd (1, 1, 3)), [3, 3]) ***** assert (size (laplacernd (1, 1, [4, 1])), [4, 1]) ***** assert (size (laplacernd (1, 1, 4, 1)), [4, 1]) ***** assert (size (laplacernd (1, 1, 4, 1, 5)), [4, 1, 5]) ***** assert (size (laplacernd (1, 1, 0, 1)), [0, 1]) ***** assert (size (laplacernd (1, 1, 1, 0)), [1, 0]) ***** assert (size (laplacernd (1, 1, 1, 2, 0, 5)), [1, 2, 0, 5]) ***** assert (class (laplacernd (1, 1)), "double") ***** assert (class (laplacernd (1, single (1))), "single") ***** assert (class (laplacernd (1, single ([1, 1]))), "single") ***** assert (class (laplacernd (single (1), 1)), "single") ***** assert (class (laplacernd (single ([1, 1]), 1)), "single") ***** error laplacernd () ***** error laplacernd (1) ***** error ... laplacernd (ones (3), ones (2)) ***** error ... laplacernd (ones (2), ones (3)) ***** error laplacernd (i, 2, 3) ***** error laplacernd (1, i, 3) ***** error ... laplacernd (1, 2, -1) ***** error ... laplacernd (1, 2, 1.2) ***** error ... laplacernd (1, 2, ones (2)) ***** error ... laplacernd (1, 2, [2 -1 2]) ***** error ... laplacernd (1, 2, [2 0 2.5]) ***** error ... laplacernd (1, 2, 2, -1, 5) ***** error ... laplacernd (1, 2, 2, 1.5, 5) ***** error ... laplacernd (2, ones (2), 3) ***** error ... laplacernd (2, ones (2), [3, 2]) ***** error ... laplacernd (2, ones (2), 3, 2) 33 tests, 33 passed, 0 known failure, 0 skipped [inst/dist_fun/hninv.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/dist_fun/hninv.m ***** demo ## Plot various iCDFs from the half-normal distribution p = 0.001:0.001:0.999; x1 = hninv (p, 0, 1); x2 = hninv (p, 0, 2); x3 = hninv (p, 0, 3); x4 = hninv (p, 0, 5); plot (p, x1, "-b", p, x2, "-g", p, x3, "-r", p, x4, "-c") grid on ylim ([0, 10]) legend ({"μ = 0, σ = 1", "μ = 0, σ = 2", ... "μ = 0, σ = 3", "μ = 0, σ = 5"}, "location", "northwest") title ("Half-normal iCDF") xlabel ("probability") ylabel ("x") ***** shared p, x p = [0, 0.3829, 0.6827, 1]; x = [0, 1/2, 1, Inf]; ***** assert (hninv (p, 0, 1), x, 1e-4); ***** assert (hninv (p, 5, 1), x + 5, 1e-4); ***** assert (hninv (p, 0, ones (1,4)), x, 1e-4); ***** assert (hninv (p, 0, [-1, 0, 1, 1]), [NaN, NaN, x(3:4)], 1e-4) ***** assert (class (hninv (single ([p, NaN]), 0, 1)), "single") ***** assert (class (hninv ([p, NaN], single (0), 1)), "single") ***** assert (class (hninv ([p, NaN], 0, single (1))), "single") ***** error hninv (1) ***** error hninv (1, 2) ***** error ... hninv (1, ones (2), ones (3)) ***** error ... hninv (ones (2), 1, ones (3)) ***** error ... hninv (ones (2), ones (3), 1) ***** error hninv (i, 2, 3) ***** error hninv (1, i, 3) ***** error hninv (1, 2, i) 15 tests, 15 passed, 0 known failure, 0 skipped [inst/dist_fun/invginv.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/dist_fun/invginv.m ***** demo ## Plot various iCDFs from the inverse Gaussian distribution p = 0.001:0.001:0.999; x1 = invginv (p, 1, 0.2); x2 = invginv (p, 1, 1); x3 = invginv (p, 1, 3); x4 = invginv (p, 3, 0.2); x5 = invginv (p, 3, 1); plot (p, x1, "-b", p, x2, "-g", p, x3, "-r", p, x4, "-c", p, x5, "-y") grid on ylim ([0, 3]) legend ({"μ = 1, σ = 0.2", "μ = 1, σ = 1", "μ = 1, σ = 3", ... "μ = 3, σ = 0.2", "μ = 3, σ = 1"}, "location", "northwest") title ("Inverse Gaussian iCDF") xlabel ("probability") ylabel ("x") ***** shared p, x p = [0, 0.3829, 0.6827, 1]; x = [0, 0.5207, 1.0376, Inf]; ***** assert (invginv (p, 1, 1), x, 1e-4); ***** assert (invginv (p, 1, ones (1,4)), x, 1e-4); ***** assert (invginv (p, 1, [-1, 0, 1, 1]), [NaN, NaN, x(3:4)], 1e-4) ***** assert (invginv (p, [-1, 0, 1, 1], 1), [NaN, NaN, x(3:4)], 1e-4) ***** assert (class (invginv (single ([p, NaN]), 0, 1)), "single") ***** assert (class (invginv ([p, NaN], single (0), 1)), "single") ***** assert (class (invginv ([p, NaN], 0, single (1))), "single") ***** error invginv (1) ***** error invginv (1, 2) ***** error ... invginv (1, ones (2), ones (3)) ***** error ... invginv (ones (2), 1, ones (3)) ***** error ... invginv (ones (2), ones (3), 1) ***** error invginv (i, 2, 3) ***** error invginv (1, i, 3) ***** error invginv (1, 2, i) 15 tests, 15 passed, 0 known failure, 0 skipped [inst/dist_fun/tlscdf.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/dist_fun/tlscdf.m ***** demo ## Plot various CDFs from the location-scale Student's T distribution x = -8:0.01:8; p1 = tlscdf (x, 0, 1, 1); p2 = tlscdf (x, 0, 2, 2); p3 = tlscdf (x, 3, 2, 5); p4 = tlscdf (x, -1, 3, Inf); plot (x, p1, "-b", x, p2, "-g", x, p3, "-r", x, p4, "-m") grid on xlim ([-8, 8]) ylim ([0, 1]) legend ({"mu = 0, sigma = 1, nu = 1", "mu = 0, sigma = 2, nu = 2", ... "mu = 3, sigma = 2, nu = 5", 'mu = -1, sigma = 3, nu = \infty'}, ... "location", "northwest") title ("Location-scale Student's T CDF") xlabel ("values in x") ylabel ("probability") ***** shared x,y x = [-Inf 0 1 Inf]; y = [0 1/2 3/4 1]; ***** assert (tlscdf (x, 0, 1, ones (1,4)), y, eps) ***** assert (tlscdf (x, 0, 1, 1), y, eps) ***** assert (tlscdf (x, 0, 1, [0 1 NaN 1]), [NaN 1/2 NaN 1], eps) ***** assert (tlscdf ([x(1:2) NaN x(4)], 0, 1, 1), [y(1:2) NaN y(4)], eps) ***** assert (tlscdf (2, 0, 1, 3, "upper"), 0.0697, 1e-4) ***** assert (tlscdf (205, 0, 1, 5, "upper"), 2.6206e-11, 1e-14) ***** assert (tlscdf ([x, NaN], 0, 1, 1), [y, NaN], eps) ***** assert (tlscdf (single ([x, NaN]), 0, 1, 1), single ([y, NaN]), eps ("single")) ***** assert (tlscdf ([x, NaN], single (0), 1, 1), single ([y, NaN]), eps ("single")) ***** assert (tlscdf ([x, NaN], 0, single (1), 1), single ([y, NaN]), eps ("single")) ***** assert (tlscdf ([x, NaN], 0, 1, single (1)), single ([y, NaN]), eps ("single")) ***** error tlscdf () ***** error tlscdf (1) ***** error tlscdf (1, 2) ***** error tlscdf (1, 2, 3) ***** error tlscdf (1, 2, 3, 4, "uper") ***** error tlscdf (1, 2, 3, 4, 5) ***** error ... tlscdf (ones (3), ones (2), 1, 1) ***** error ... tlscdf (ones (3), 1, ones (2), 1) ***** error ... tlscdf (ones (3), 1, 1, ones (2)) ***** error ... tlscdf (ones (3), ones (2), 1, 1, "upper") ***** error ... tlscdf (ones (3), 1, ones (2), 1, "upper") ***** error ... tlscdf (ones (3), 1, 1, ones (2), "upper") ***** error tlscdf (i, 2, 1, 1) ***** error tlscdf (2, i, 1, 1) ***** error tlscdf (2, 1, i, 1) ***** error tlscdf (2, 1, 1, i) 27 tests, 27 passed, 0 known failure, 0 skipped [inst/dist_fun/nbincdf.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/dist_fun/nbincdf.m ***** demo ## Plot various CDFs from the negative binomial distribution x = 0:50; p1 = nbincdf (x, 2, 0.15); p2 = nbincdf (x, 5, 0.2); p3 = nbincdf (x, 4, 0.4); p4 = nbincdf (x, 10, 0.3); plot (x, p1, "*r", x, p2, "*g", x, p3, "*k", x, p4, "*m") grid on xlim ([0, 40]) legend ({"r = 2, ps = 0.15", "r = 5, ps = 0.2", "r = 4, p = 0.4", ... "r = 10, ps = 0.3"}, "location", "southeast") title ("Negative binomial CDF") xlabel ("values in x (number of failures)") ylabel ("probability") ***** shared x, y x = [-1 0 1 2 Inf]; y = [0 1/2 3/4 7/8 1]; ***** assert (nbincdf (x, ones (1,5), 0.5*ones (1,5)), y) ***** assert (nbincdf (x, 1, 0.5*ones (1,5)), y) ***** assert (nbincdf (x, ones (1,5), 0.5), y) ***** assert (nbincdf (x, ones (1,5), 0.5, "upper"), 1 - y, eps) ***** assert (nbincdf ([x(1:3) 0 x(5)], [0 1 NaN 1.5 Inf], 0.5), ... [NaN 1/2 NaN nbinpdf(0,1.5,0.5) NaN], eps) ***** assert (nbincdf (x, 1, 0.5*[-1 NaN 4 1 1]), [NaN NaN NaN y(4:5)]) ***** assert (nbincdf ([x(1:2) NaN x(4:5)], 1, 0.5), [y(1:2) NaN y(4:5)]) ***** assert (nbincdf ([x, NaN], 1, 0.5), [y, NaN]) ***** assert (nbincdf (single ([x, NaN]), 1, 0.5), single ([y, NaN])) ***** assert (nbincdf ([x, NaN], single (1), 0.5), single ([y, NaN])) ***** assert (nbincdf ([x, NaN], 1, single (0.5)), single ([y, NaN])) ***** error nbincdf () ***** error nbincdf (1) ***** error nbincdf (1, 2) ***** error nbincdf (1, 2, 3, 4) ***** error nbincdf (1, 2, 3, "some") ***** error ... nbincdf (ones (3), ones (2), ones (2)) ***** error ... nbincdf (ones (2), ones (3), ones (2)) ***** error ... nbincdf (ones (2), ones (2), ones (3)) ***** error nbincdf (i, 2, 2) ***** error nbincdf (2, i, 2) ***** error nbincdf (2, 2, i) 22 tests, 22 passed, 0 known failure, 0 skipped [inst/dist_fun/logipdf.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/dist_fun/logipdf.m ***** demo ## Plot various PDFs from the logistic distribution x = -5:0.01:20; y1 = logipdf (x, 5, 2); y2 = logipdf (x, 9, 3); y3 = logipdf (x, 9, 4); y4 = logipdf (x, 6, 2); y5 = logipdf (x, 2, 1); plot (x, y1, "-b", x, y2, "-g", x, y3, "-r", x, y4, "-c", x, y5, "-m") grid on ylim ([0, 0.3]) legend ({"μ = 5, σ = 2", "μ = 9, σ = 3", "μ = 9, σ = 4", ... "μ = 6, σ = 2", "μ = 2, σ = 1"}, "location", "northeast") title ("Logistic PDF") xlabel ("values in x") ylabel ("density") ***** shared x, y x = [-Inf -log(4) 0 log(4) Inf]; y = [0, 0.16, 1/4, 0.16, 0]; ***** assert (logipdf ([x, NaN], 0, 1), [y, NaN], eps) ***** assert (logipdf (x, 0, [-2, -1, 0, 1, 2]), [nan(1, 3), y([4:5])], eps) ***** assert (logipdf (single ([x, NaN]), 0, 1), single ([y, NaN]), eps ("single")) ***** assert (logipdf ([x, NaN], single (0), 1), single ([y, NaN]), eps ("single")) ***** assert (logipdf ([x, NaN], 0, single (1)), single ([y, NaN]), eps ("single")) ***** error logipdf () ***** error logipdf (1) ***** error ... logipdf (1, 2) ***** error ... logipdf (1, ones (2), ones (3)) ***** error ... logipdf (ones (2), 1, ones (3)) ***** error ... logipdf (ones (2), ones (3), 1) ***** error logipdf (i, 2, 3) ***** error logipdf (1, i, 3) ***** error logipdf (1, 2, i) 14 tests, 14 passed, 0 known failure, 0 skipped [inst/dist_fun/poissrnd.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/dist_fun/poissrnd.m ***** assert (size (poissrnd (2)), [1, 1]) ***** assert (size (poissrnd (ones (2,1))), [2, 1]) ***** assert (size (poissrnd (ones (2,2))), [2, 2]) ***** assert (size (poissrnd (1, 3)), [3, 3]) ***** assert (size (poissrnd (1, [4 1])), [4, 1]) ***** assert (size (poissrnd (1, 4, 1)), [4, 1]) ***** assert (size (poissrnd (1, 4, 1)), [4, 1]) ***** assert (size (poissrnd (1, 4, 1, 5)), [4, 1, 5]) ***** assert (size (poissrnd (1, 0, 1)), [0, 1]) ***** assert (size (poissrnd (1, 1, 0)), [1, 0]) ***** assert (size (poissrnd (1, 1, 2, 0, 5)), [1, 2, 0, 5]) ***** assert (poissrnd (0, 1, 1), 0) ***** assert (poissrnd ([0, 0, 0], [1, 3]), [0 0 0]) ***** assert (class (poissrnd (2)), "double") ***** assert (class (poissrnd (single (2))), "single") ***** assert (class (poissrnd (single ([2 2]))), "single") ***** error poissrnd () ***** error poissrnd (i) ***** error ... poissrnd (1, -1) ***** error ... poissrnd (1, 1.2) ***** error ... poissrnd (1, ones (2)) ***** error ... poissrnd (1, [2 -1 2]) ***** error ... poissrnd (1, [2 0 2.5]) ***** error ... poissrnd (ones (2), ones (2)) ***** error ... poissrnd (1, 2, -1, 5) ***** error ... poissrnd (1, 2, 1.5, 5) ***** error poissrnd (ones (2,2), 3) ***** error poissrnd (ones (2,2), [3, 2]) ***** error poissrnd (ones (2,2), 2, 3) 29 tests, 29 passed, 0 known failure, 0 skipped [inst/dist_fun/norminv.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/dist_fun/norminv.m ***** demo ## Plot various iCDFs from the normal distribution p = 0.001:0.001:0.999; x1 = norminv (p, 0, 0.5); x2 = norminv (p, 0, 1); x3 = norminv (p, 0, 2); x4 = norminv (p, -2, 0.8); plot (p, x1, "-b", p, x2, "-g", p, x3, "-r", p, x4, "-c") grid on ylim ([-5, 5]) legend ({"μ = 0, σ = 0.5", "μ = 0, σ = 1", ... "μ = 0, σ = 2", "μ = -2, σ = 0.8"}, "location", "northwest") title ("Normal iCDF") xlabel ("probability") ylabel ("values in x") ***** shared p p = [-1 0 0.5 1 2]; ***** assert (norminv (p, ones (1,5), ones (1,5)), [NaN -Inf 1 Inf NaN]) ***** assert (norminv (p, 1, ones (1,5)), [NaN -Inf 1 Inf NaN]) ***** assert (norminv (p, ones (1,5), 1), [NaN -Inf 1 Inf NaN]) ***** assert (norminv (p, [1 -Inf NaN Inf 1], 1), [NaN NaN NaN NaN NaN]) ***** assert (norminv (p, 1, [1 0 NaN Inf 1]), [NaN NaN NaN NaN NaN]) ***** assert (norminv ([p(1:2) NaN p(4:5)], 1, 1), [NaN -Inf NaN Inf NaN]) ***** assert (norminv (p), probit (p)) ***** assert (norminv (0.31254), probit (0.31254)) ***** assert (norminv ([p, NaN], 1, 1), [NaN -Inf 1 Inf NaN NaN]) ***** assert (norminv (single ([p, NaN]), 1, 1), single ([NaN -Inf 1 Inf NaN NaN])) ***** assert (norminv ([p, NaN], single (1), 1), single ([NaN -Inf 1 Inf NaN NaN])) ***** assert (norminv ([p, NaN], 1, single (1)), single ([NaN -Inf 1 Inf NaN NaN])) ***** error norminv () ***** error ... norminv (ones (3), ones (2), ones (2)) ***** error ... norminv (ones (2), ones (3), ones (2)) ***** error ... norminv (ones (2), ones (2), ones (3)) ***** error norminv (i, 2, 2) ***** error norminv (2, i, 2) ***** error norminv (2, 2, i) 19 tests, 19 passed, 0 known failure, 0 skipped [inst/dist_fun/tricdf.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/dist_fun/tricdf.m ***** demo ## Plot various CDFs from the triangular distribution x = 0.001:0.001:10; p1 = tricdf (x, 3, 4, 6); p2 = tricdf (x, 1, 2, 5); p3 = tricdf (x, 2, 3, 9); p4 = tricdf (x, 2, 5, 9); plot (x, p1, "-b", x, p2, "-g", x, p3, "-r", x, p4, "-c") grid on xlim ([0, 10]) legend ({"a = 3, b = 4, c = 6", "a = 1, b = 2, c = 5", ... "a = 2, b = 3, c = 9", "a = 2, b = 5, c = 9"}, ... "location", "southeast") title ("Triangular CDF") xlabel ("values in x") ylabel ("probability") ***** shared x, y x = [-1, 0, 0.1, 0.5, 0.9, 1, 2] + 1; y = [0, 0, 0.02, 0.5, 0.98, 1 1]; ***** assert (tricdf (x, ones (1,7), 1.5 * ones (1, 7), 2 * ones (1, 7)), y, eps) ***** assert (tricdf (x, 1 * ones (1, 7), 1.5, 2), y, eps) ***** assert (tricdf (x, 1 * ones (1, 7), 1.5, 2, "upper"), 1 - y, eps) ***** assert (tricdf (x, 1, 1.5, 2 * ones (1, 7)), y, eps) ***** assert (tricdf (x, 1, 1.5 * ones (1, 7), 2), y, eps) ***** assert (tricdf (x, 1, 1.5, 2), y, eps) ***** assert (tricdf (x, [1, 1, NaN, 1, 1, 1, 1], 1.5, 2), ... [y(1:2), NaN, y(4:7)], eps) ***** assert (tricdf (x, 1, 1.5, 2*[1, 1, NaN, 1, 1, 1, 1]), ... [y(1:2), NaN, y(4:7)], eps) ***** assert (tricdf (x, 1, 1.5, 2*[1, 1, NaN, 1, 1, 1, 1]), ... [y(1:2), NaN, y(4:7)], eps) ***** assert (tricdf ([x, NaN], 1, 1.5, 2), [y, NaN], eps) ***** assert (tricdf (single ([x, NaN]), 1, 1.5, 2), ... single ([y, NaN]), eps("single")) ***** assert (tricdf ([x, NaN], single (1), 1.5, 2), ... single ([y, NaN]), eps("single")) ***** assert (tricdf ([x, NaN], 1, single (1.5), 2), ... single ([y, NaN]), eps("single")) ***** assert (tricdf ([x, NaN], 1, 1.5, single (2)), ... single ([y, NaN]), eps("single")) ***** error tricdf () ***** error tricdf (1) ***** error tricdf (1, 2) ***** error tricdf (1, 2, 3) ***** error ... tricdf (1, 2, 3, 4, 5, 6) ***** error tricdf (1, 2, 3, 4, "tail") ***** error tricdf (1, 2, 3, 4, 5) ***** error ... tricdf (ones (3), ones (2), ones(2), ones(2)) ***** error ... tricdf (ones (2), ones (3), ones(2), ones(2)) ***** error ... tricdf (ones (2), ones (2), ones(3), ones(2)) ***** error ... tricdf (ones (2), ones (2), ones(2), ones(3)) ***** error tricdf (i, 2, 3, 4) ***** error tricdf (1, i, 3, 4) ***** error tricdf (1, 2, i, 4) ***** error tricdf (1, 2, 3, i) 29 tests, 29 passed, 0 known failure, 0 skipped [inst/dist_fun/evpdf.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/dist_fun/evpdf.m ***** demo ## Plot various PDFs from the Extreme value distribution x = -10:0.001:10; y1 = evpdf (x, 0.5, 2); y2 = evpdf (x, 1.0, 2); y3 = evpdf (x, 1.5, 3); y4 = evpdf (x, 3.0, 4); plot (x, y1, "-b", x, y2, "-g", x, y3, "-r", x, y4, "-c") grid on ylim ([0, 0.2]) legend ({"μ = 0.5, σ = 2", "μ = 1.0, σ = 2", ... "μ = 1.5, σ = 3", "μ = 3.0, σ = 4"}, "location", "northeast") title ("Extreme value PDF") xlabel ("values in x") ylabel ("density") ***** shared x, y0, y1 x = [-5, 0, 1, 2, 3]; y0 = [0.0067, 0.3679, 0.1794, 0.0046, 0]; y1 = [0.0025, 0.2546, 0.3679, 0.1794, 0.0046]; ***** assert (evpdf (x), y0, 1e-4) ***** assert (evpdf (x, zeros (1,5), ones (1,5)), y0, 1e-4) ***** assert (evpdf (x, ones (1,5), ones (1,5)), y1, 1e-4) ***** error evpdf () ***** error ... evpdf (ones (3), ones (2), ones (2)) ***** error evpdf (i, 2, 2) ***** error evpdf (2, i, 2) ***** error evpdf (2, 2, i) 8 tests, 8 passed, 0 known failure, 0 skipped [inst/dist_fun/unifrnd.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/dist_fun/unifrnd.m ***** assert (size (unifrnd (1, 1)), [1 1]) ***** assert (size (unifrnd (1, ones (2,1))), [2, 1]) ***** assert (size (unifrnd (1, ones (2,2))), [2, 2]) ***** assert (size (unifrnd (ones (2,1), 1)), [2, 1]) ***** assert (size (unifrnd (ones (2,2), 1)), [2, 2]) ***** assert (size (unifrnd (1, 1, 3)), [3, 3]) ***** assert (size (unifrnd (1, 1, [4, 1])), [4, 1]) ***** assert (size (unifrnd (1, 1, 4, 1)), [4, 1]) ***** assert (size (unifrnd (1, 1, 4, 1, 5)), [4, 1, 5]) ***** assert (size (unifrnd (1, 1, 0, 1)), [0, 1]) ***** assert (size (unifrnd (1, 1, 1, 0)), [1, 0]) ***** assert (size (unifrnd (1, 1, 1, 2, 0, 5)), [1, 2, 0, 5]) ***** assert (class (unifrnd (1, 1)), "double") ***** assert (class (unifrnd (1, single (1))), "single") ***** assert (class (unifrnd (1, single ([1, 1]))), "single") ***** assert (class (unifrnd (single (1), 1)), "single") ***** assert (class (unifrnd (single ([1, 1]), 1)), "single") ***** error unifrnd () ***** error unifrnd (1) ***** error ... unifrnd (ones (3), ones (2)) ***** error ... unifrnd (ones (2), ones (3)) ***** error unifrnd (i, 2, 3) ***** error unifrnd (1, i, 3) ***** error ... unifrnd (1, 2, -1) ***** error ... unifrnd (1, 2, 1.2) ***** error ... unifrnd (1, 2, ones (2)) ***** error ... unifrnd (1, 2, [2 -1 2]) ***** error ... unifrnd (1, 2, [2 0 2.5]) ***** error ... unifrnd (1, 2, 2, -1, 5) ***** error ... unifrnd (1, 2, 2, 1.5, 5) ***** error ... unifrnd (2, ones (2), 3) ***** error ... unifrnd (2, ones (2), [3, 2]) ***** error ... unifrnd (2, ones (2), 3, 2) 33 tests, 33 passed, 0 known failure, 0 skipped [inst/dist_fun/gevrnd.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/dist_fun/gevrnd.m ***** assert(size (gevrnd (1,2,1)), [1, 1]); ***** assert(size (gevrnd (ones(2,1), 2, 1)), [2, 1]); ***** assert(size (gevrnd (ones(2,2), 2, 1)), [2, 2]); ***** assert(size (gevrnd (1, 2*ones(2,1), 1)), [2, 1]); ***** assert(size (gevrnd (1, 2*ones(2,2), 1)), [2, 2]); ***** assert(size (gevrnd (1, 2, 1, 3)), [3, 3]); ***** assert(size (gevrnd (1, 2, 1, [4 1])), [4, 1]); ***** assert(size (gevrnd (1, 2, 1, 4, 1)), [4, 1]); ***** assert (class (gevrnd (1,1,1)), "double") ***** assert (class (gevrnd (single (1),1,1)), "single") ***** assert (class (gevrnd (single ([1 1]),1,1)), "single") ***** assert (class (gevrnd (1,single (1),1)), "single") ***** assert (class (gevrnd (1,single ([1 1]),1)), "single") ***** assert (class (gevrnd (1,1,single (1))), "single") ***** assert (class (gevrnd (1,1,single ([1 1]))), "single") ***** error gevrnd () ***** error gevrnd (1) ***** error gevrnd (1, 2) ***** error ... gevrnd (ones (3), ones (2), ones (2)) ***** error ... gevrnd (ones (2), ones (3), ones (2)) ***** error ... gevrnd (ones (2), ones (2), ones (3)) ***** error gevrnd (i, 2, 3) ***** error gevrnd (1, i, 3) ***** error gevrnd (1, 2, i) ***** error ... gevrnd (1, 2, 3, -1) ***** error ... gevrnd (1, 2, 3, 1.2) ***** error ... gevrnd (1, 2, 3, ones (2)) ***** error ... gevrnd (1, 2, 3, [2 -1 2]) ***** error ... gevrnd (1, 2, 3, [2 0 2.5]) ***** error ... gevrnd (1, 2, 3, 2, -1, 5) ***** error ... gevrnd (1, 2, 3, 2, 1.5, 5) ***** error ... gevrnd (2, ones (2), 2, 3) ***** error ... gevrnd (2, ones (2), 2, [3, 2]) ***** error ... gevrnd (2, ones (2), 2, 3, 2) 34 tests, 34 passed, 0 known failure, 0 skipped [inst/dist_fun/copulapdf.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/dist_fun/copulapdf.m ***** test x = [0.2:0.2:0.6; 0.2:0.2:0.6]; theta = [1; 2]; y = copulapdf ("Clayton", x, theta); expected_p = [0.9872; 0.7295]; assert (y, expected_p, 0.001); ***** test x = [0.2:0.2:0.6; 0.2:0.2:0.6]; y = copulapdf ("Gumbel", x, 2); expected_p = [0.9468; 0.9468]; assert (y, expected_p, 0.001); ***** test x = [0.2, 0.6; 0.2, 0.6]; theta = [1; 2]; y = copulapdf ("Frank", x, theta); expected_p = [0.9378; 0.8678]; assert (y, expected_p, 0.001); ***** test x = [0.2, 0.6; 0.2, 0.6]; theta = [0.3; 0.7]; y = copulapdf ("AMH", x, theta); expected_p = [0.9540; 0.8577]; assert (y, expected_p, 0.001); 4 tests, 4 passed, 0 known failure, 0 skipped [inst/dist_fun/tpdf.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/dist_fun/tpdf.m ***** demo ## Plot various PDFs from the Student's T distribution x = -5:0.01:5; y1 = tpdf (x, 1); y2 = tpdf (x, 2); y3 = tpdf (x, 5); y4 = tpdf (x, Inf); plot (x, y1, "-b", x, y2, "-g", x, y3, "-r", x, y4, "-m") grid on xlim ([-5, 5]) ylim ([0, 0.41]) legend ({"df = 1", "df = 2", ... "df = 5", 'df = \infty'}, "location", "northeast") title ("Student's T PDF") xlabel ("values in x") ylabel ("density") ***** test x = rand (10,1); y = 1./(pi * (1 + x.^2)); assert (tpdf (x, 1), y, 5*eps); ***** shared x, y x = [-Inf 0 0.5 1 Inf]; y = 1./(pi * (1 + x.^2)); ***** assert (tpdf (x, ones (1,5)), y, eps) ***** assert (tpdf (x, 1), y, eps) ***** assert (tpdf (x, [0 NaN 1 1 1]), [NaN NaN y(3:5)], eps) ***** assert (tpdf (x, Inf), normpdf (x)) ***** assert (tpdf ([x, NaN], 1), [y, NaN], eps) ***** assert (tpdf (single ([x, NaN]), 1), single ([y, NaN]), eps ("single")) ***** assert (tpdf ([x, NaN], single (1)), single ([y, NaN]), eps ("single")) ***** error tpdf () ***** error tpdf (1) ***** error ... tpdf (ones (3), ones (2)) ***** error ... tpdf (ones (2), ones (3)) ***** error tpdf (i, 2) ***** error tpdf (2, i) 14 tests, 14 passed, 0 known failure, 0 skipped [inst/dist_fun/poissinv.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/dist_fun/poissinv.m ***** demo ## Plot various iCDFs from the Poisson distribution p = 0.001:0.001:0.999; x1 = poissinv (p, 13); x2 = poissinv (p, 4); x3 = poissinv (p, 10); plot (p, x1, "-b", p, x2, "-g", p, x3, "-r") grid on ylim ([0, 20]) legend ({"λ = 1", "λ = 4", "λ = 10"}, "location", "northwest") title ("Poisson iCDF") xlabel ("probability") ylabel ("values in x (number of occurences)") ***** shared p p = [-1 0 0.5 1 2]; ***** assert (poissinv (p, ones (1,5)), [NaN 0 1 Inf NaN]) ***** assert (poissinv (p, 1), [NaN 0 1 Inf NaN]) ***** assert (poissinv (p, [1 0 NaN 1 1]), [NaN NaN NaN Inf NaN]) ***** assert (poissinv ([p(1:2) NaN p(4:5)], 1), [NaN 0 NaN Inf NaN]) ***** assert (poissinv ([p, NaN], 1), [NaN 0 1 Inf NaN NaN]) ***** assert (poissinv (single ([p, NaN]), 1), single ([NaN 0 1 Inf NaN NaN])) ***** assert (poissinv ([p, NaN], single (1)), single ([NaN 0 1 Inf NaN NaN])) ***** error poissinv () ***** error poissinv (1) ***** error ... poissinv (ones (3), ones (2)) ***** error ... poissinv (ones (2), ones (3)) ***** error poissinv (i, 2) ***** error poissinv (2, i) 13 tests, 13 passed, 0 known failure, 0 skipped [inst/dist_fun/geopdf.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/dist_fun/geopdf.m ***** demo ## Plot various PDFs from the geometric distribution x = 0:10; y1 = geopdf (x, 0.2); y2 = geopdf (x, 0.5); y3 = geopdf (x, 0.7); plot (x, y1, "*b", x, y2, "*g", x, y3, "*r") grid on ylim ([0, 0.8]) legend ({"ps = 0.2", "ps = 0.5", "ps = 0.7"}, "location", "northeast") title ("Geometric PDF") xlabel ("values in x (number of failures)") ylabel ("density") ***** shared x, y x = [-1 0 1 Inf]; y = [0, 1/2, 1/4, NaN]; ***** assert (geopdf (x, 0.5*ones (1,4)), y) ***** assert (geopdf (x, 0.5), y) ***** assert (geopdf (x, 0.5*[-1 NaN 4 1]), [NaN NaN NaN y(4)]) ***** assert (geopdf ([x, NaN], 0.5), [y, NaN]) ***** assert (geopdf (single ([x, NaN]), 0.5), single ([y, NaN]), 5*eps ("single")) ***** assert (geopdf ([x, NaN], single (0.5)), single ([y, NaN]), 5*eps ("single")) ***** error geopdf () ***** error geopdf (1) ***** error geopdf (1,2,3) ***** error geopdf (ones (3), ones (2)) ***** error geopdf (ones (2), ones (3)) ***** error geopdf (i, 2) ***** error geopdf (2, i) 13 tests, 13 passed, 0 known failure, 0 skipped [inst/dist_fun/nbinrnd.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/dist_fun/nbinrnd.m ***** assert (size (nbinrnd (1, 0.5)), [1 1]) ***** assert (size (nbinrnd (1, 0.5 * ones (2,1))), [2, 1]) ***** assert (size (nbinrnd (1, 0.5 * ones (2,2))), [2, 2]) ***** assert (size (nbinrnd (ones (2,1), 0.5)), [2, 1]) ***** assert (size (nbinrnd (ones (2,2), 0.5)), [2, 2]) ***** assert (size (nbinrnd (1, 0.5, 3)), [3, 3]) ***** assert (size (nbinrnd (1, 0.5, [4, 1])), [4, 1]) ***** assert (size (nbinrnd (1, 0.5, 4, 1)), [4, 1]) ***** assert (size (nbinrnd (1, 0.5, 4, 1, 5)), [4, 1, 5]) ***** assert (size (nbinrnd (1, 0.5, 0, 1)), [0, 1]) ***** assert (size (nbinrnd (1, 0.5, 1, 0)), [1, 0]) ***** assert (size (nbinrnd (1, 0.5, 1, 2, 0, 5)), [1, 2, 0, 5]) ***** assert (class (nbinrnd (1, 0.5)), "double") ***** assert (class (nbinrnd (1, single (0.5))), "single") ***** assert (class (nbinrnd (1, single ([0.5, 0.5]))), "single") ***** assert (class (nbinrnd (single (1), 0.5)), "single") ***** assert (class (nbinrnd (single ([1, 1]), 0.5)), "single") ***** error nbinrnd () ***** error nbinrnd (1) ***** error ... nbinrnd (ones (3), ones (2)) ***** error ... nbinrnd (ones (2), ones (3)) ***** error nbinrnd (i, 2, 3) ***** error nbinrnd (1, i, 3) ***** error ... nbinrnd (1, 2, -1) ***** error ... nbinrnd (1, 2, 1.2) ***** error ... nbinrnd (1, 2, ones (2)) ***** error ... nbinrnd (1, 2, [2 -1 2]) ***** error ... nbinrnd (1, 2, [2 0 2.5]) ***** error ... nbinrnd (1, 2, 2, -1, 5) ***** error ... nbinrnd (1, 2, 2, 1.5, 5) ***** error ... nbinrnd (2, ones (2), 3) ***** error ... nbinrnd (2, ones (2), [3, 2]) ***** error ... nbinrnd (2, ones (2), 3, 2) 33 tests, 33 passed, 0 known failure, 0 skipped [inst/dist_fun/wienrnd.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/dist_fun/wienrnd.m ***** error wienrnd (0) ***** error wienrnd (1, 3, -50) ***** error wienrnd (5, 0) ***** error wienrnd (0.4, 3, 5) ***** error wienrnd ([1 4], 3, 5) 5 tests, 5 passed, 0 known failure, 0 skipped [inst/dist_fun/plrnd.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/dist_fun/plrnd.m ***** shared x, Fx x = [0, 1, 3, 4, 7, 10]; Fx = [0, 0.2, 0.5, 0.6, 0.7, 1]; ***** assert (size (plrnd (x, Fx)), [1, 1]) ***** assert (size (plrnd (x, Fx, 3)), [3, 3]) ***** assert (size (plrnd (x, Fx, [4, 1])), [4, 1]) ***** assert (size (plrnd (x, Fx, 4, 1)), [4, 1]) ***** assert (size (plrnd (x, Fx, 4, 1, 5)), [4, 1, 5]) ***** assert (size (plrnd (x, Fx, 0, 1)), [0, 1]) ***** assert (size (plrnd (x, Fx, 1, 0)), [1, 0]) ***** assert (size (plrnd (x, Fx, 1, 2, 0, 5)), [1, 2, 0, 5]) ***** assert (class (plrnd (x, Fx)), "double") ***** assert (class (plrnd (x, single (Fx))), "single") ***** assert (class (plrnd (single (x), Fx)), "single") ***** error plrnd () ***** error plrnd (1) ***** error ... plrnd ([0, 1, 2], [0, 1]) ***** error ... plrnd ([0], [1]) ***** error ... plrnd ([0, 1, 2], [0, 1, 1.5]) ***** error ... plrnd ([0, 1, 2], [0, i, 1]) ***** error ... plrnd ([0, i, 2], [0, 0.5, 1]) ***** error ... plrnd ([0, i, 2], [0, 0.5i, 1]) ***** error ... plrnd (x, Fx, -1) ***** error ... plrnd (x, Fx, 1.2) ***** error ... plrnd (x, Fx, ones (2)) ***** error ... plrnd (x, Fx, [2 -1 2]) ***** error ... plrnd (x, Fx, [2 0 2.5]) ***** error ... plrnd (x, Fx, 2, -1, 5) ***** error ... plrnd (x, Fx, 2, 1.5, 5) 26 tests, 26 passed, 0 known failure, 0 skipped [inst/dist_fun/unidcdf.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/dist_fun/unidcdf.m ***** demo ## Plot various CDFs from the discrete uniform distribution x = 0:10; p1 = unidcdf (x, 5); p2 = unidcdf (x, 9); plot (x, p1, "*b", x, p2, "*g") grid on xlim ([0, 10]) ylim ([0, 1]) legend ({"N = 5", "N = 9"}, "location", "southeast") title ("Discrete uniform CDF") xlabel ("values in x") ylabel ("probability") ***** shared x, y x = [0 1 2.5 10 11]; y = [0, 0.1 0.2 1.0 1.0]; ***** assert (unidcdf (x, 10*ones (1,5)), y) ***** assert (unidcdf (x, 10*ones (1,5), "upper"), 1 - y) ***** assert (unidcdf (x, 10), y) ***** assert (unidcdf (x, 10, "upper"), 1 - y) ***** assert (unidcdf (x, 10*[0 1 NaN 1 1]), [NaN 0.1 NaN y(4:5)]) ***** assert (unidcdf ([x(1:2) NaN Inf x(5)], 10), [y(1:2) NaN 1 y(5)]) ***** assert (unidcdf ([x, NaN], 10), [y, NaN]) ***** assert (unidcdf (single ([x, NaN]), 10), single ([y, NaN])) ***** assert (unidcdf ([x, NaN], single (10)), single ([y, NaN])) ***** error unidcdf () ***** error unidcdf (1) ***** error unidcdf (1, 2, 3) ***** error unidcdf (1, 2, "tail") ***** error ... unidcdf (ones (3), ones (2)) ***** error ... unidcdf (ones (2), ones (3)) ***** error unidcdf (i, 2) ***** error unidcdf (2, i) 17 tests, 17 passed, 0 known failure, 0 skipped [inst/dist_fun/unifinv.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/dist_fun/unifinv.m ***** demo ## Plot various iCDFs from the continuous uniform distribution p = 0.001:0.001:0.999; x1 = unifinv (p, 2, 5); x2 = unifinv (p, 3, 9); plot (p, x1, "-b", p, x2, "-g") grid on xlim ([0, 1]) ylim ([0, 10]) legend ({"a = 2, b = 5", "a = 3, b = 9"}, "location", "northwest") title ("Continuous uniform iCDF") xlabel ("probability") ylabel ("values in x") ***** shared p p = [-1 0 0.5 1 2]; ***** assert (unifinv (p, ones (1,5), 2*ones (1,5)), [NaN 1 1.5 2 NaN]) ***** assert (unifinv (p, 0, 1), [NaN 1 1.5 2 NaN] - 1) ***** assert (unifinv (p, 1, 2*ones (1,5)), [NaN 1 1.5 2 NaN]) ***** assert (unifinv (p, ones (1,5), 2), [NaN 1 1.5 2 NaN]) ***** assert (unifinv (p, [1 2 NaN 1 1], 2), [NaN NaN NaN 2 NaN]) ***** assert (unifinv (p, 1, 2*[1 0 NaN 1 1]), [NaN NaN NaN 2 NaN]) ***** assert (unifinv ([p(1:2) NaN p(4:5)], 1, 2), [NaN 1 NaN 2 NaN]) ***** assert (unifinv ([p, NaN], 1, 2), [NaN 1 1.5 2 NaN NaN]) ***** assert (unifinv (single ([p, NaN]), 1, 2), single ([NaN 1 1.5 2 NaN NaN])) ***** assert (unifinv ([p, NaN], single (1), 2), single ([NaN 1 1.5 2 NaN NaN])) ***** assert (unifinv ([p, NaN], 1, single (2)), single ([NaN 1 1.5 2 NaN NaN])) ***** error unifinv () ***** error unifinv (1, 2) ***** error ... unifinv (ones (3), ones (2), ones (2)) ***** error ... unifinv (ones (2), ones (3), ones (2)) ***** error ... unifinv (ones (2), ones (2), ones (3)) ***** error unifinv (i, 2, 2) ***** error unifinv (2, i, 2) ***** error unifinv (2, 2, i) 19 tests, 19 passed, 0 known failure, 0 skipped [inst/dist_fun/trnd.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/dist_fun/trnd.m ***** assert (size (trnd (2)), [1, 1]) ***** assert (size (trnd (ones (2,1))), [2, 1]) ***** assert (size (trnd (ones (2,2))), [2, 2]) ***** assert (size (trnd (1, 3)), [3, 3]) ***** assert (size (trnd (1, [4 1])), [4, 1]) ***** assert (size (trnd (1, 4, 1)), [4, 1]) ***** assert (size (trnd (1, 4, 1)), [4, 1]) ***** assert (size (trnd (1, 4, 1, 5)), [4, 1, 5]) ***** assert (size (trnd (1, 0, 1)), [0, 1]) ***** assert (size (trnd (1, 1, 0)), [1, 0]) ***** assert (size (trnd (1, 1, 2, 0, 5)), [1, 2, 0, 5]) ***** assert (trnd (0, 1, 1), NaN) ***** assert (trnd ([0, 0, 0], [1, 3]), [NaN, NaN, NaN]) ***** assert (class (trnd (2)), "double") ***** assert (class (trnd (single (2))), "single") ***** assert (class (trnd (single ([2 2]))), "single") ***** error trnd () ***** error trnd (i) ***** error ... trnd (1, -1) ***** error ... trnd (1, 1.2) ***** error ... trnd (1, ones (2)) ***** error ... trnd (1, [2 -1 2]) ***** error ... trnd (1, [2 0 2.5]) ***** error ... trnd (ones (2), ones (2)) ***** error ... trnd (1, 2, -1, 5) ***** error ... trnd (1, 2, 1.5, 5) ***** error trnd (ones (2,2), 3) ***** error trnd (ones (2,2), [3, 2]) ***** error trnd (ones (2,2), 2, 3) 29 tests, 29 passed, 0 known failure, 0 skipped [inst/dist_fun/invgpdf.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/dist_fun/invgpdf.m ***** demo ## Plot various PDFs from the inverse Gaussian distribution x = 0:0.001:3; y1 = invgpdf (x, 1, 0.2); y2 = invgpdf (x, 1, 1); y3 = invgpdf (x, 1, 3); y4 = invgpdf (x, 3, 0.2); y5 = invgpdf (x, 3, 1); plot (x, y1, "-b", x, y2, "-g", x, y3, "-r", x, y4, "-c", x, y5, "-y") grid on xlim ([0, 3]) ylim ([0, 3]) legend ({"μ = 1, σ = 0.2", "μ = 1, σ = 1", "μ = 1, σ = 3", ... "μ = 3, σ = 0.2", "μ = 3, σ = 1"}, "location", "northeast") title ("Inverse Gaussian PDF") xlabel ("values in x") ylabel ("density") ***** shared x, y x = [-Inf, -1, 0, 1/2, 1, Inf]; y = [0, 0, 0, 0.8788, 0.3989, 0]; ***** assert (invgpdf ([x, NaN], 1, 1), [y, NaN], 1e-4) ***** assert (invgpdf (x, 1, [-2, -1, 0, 1, 1, 1]), [nan(1,3), y([4:6])], 1e-4) ***** assert (class (hncdf (single ([x, NaN]), 1, 1)), "single") ***** assert (class (hncdf ([x, NaN], 1, single (1))), "single") ***** assert (class (hncdf ([x, NaN], single (1), 1)), "single") ***** error invgpdf () ***** error invgpdf (1) ***** error invgpdf (1, 2) ***** error ... invgpdf (1, ones (2), ones (3)) ***** error ... invgpdf (ones (2), 1, ones (3)) ***** error ... invgpdf (ones (2), ones (3), 1) ***** error invgpdf (i, 2, 3) ***** error invgpdf (1, i, 3) ***** error invgpdf (1, 2, i) 14 tests, 14 passed, 0 known failure, 0 skipped [inst/dist_fun/gumbelrnd.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/dist_fun/gumbelrnd.m ***** assert (size (gumbelrnd (1, 1)), [1 1]) ***** assert (size (gumbelrnd (1, ones (2,1))), [2, 1]) ***** assert (size (gumbelrnd (1, ones (2,2))), [2, 2]) ***** assert (size (gumbelrnd (ones (2,1), 1)), [2, 1]) ***** assert (size (gumbelrnd (ones (2,2), 1)), [2, 2]) ***** assert (size (gumbelrnd (1, 1, 3)), [3, 3]) ***** assert (size (gumbelrnd (1, 1, [4, 1])), [4, 1]) ***** assert (size (gumbelrnd (1, 1, 4, 1)), [4, 1]) ***** assert (size (gumbelrnd (1, 1, 4, 1, 5)), [4, 1, 5]) ***** assert (size (gumbelrnd (1, 1, 0, 1)), [0, 1]) ***** assert (size (gumbelrnd (1, 1, 1, 0)), [1, 0]) ***** assert (size (gumbelrnd (1, 1, 1, 2, 0, 5)), [1, 2, 0, 5]) ***** assert (class (gumbelrnd (1, 1)), "double") ***** assert (class (gumbelrnd (1, single (1))), "single") ***** assert (class (gumbelrnd (1, single ([1, 1]))), "single") ***** assert (class (gumbelrnd (single (1), 1)), "single") ***** assert (class (gumbelrnd (single ([1, 1]), 1)), "single") ***** error gumbelrnd () ***** error gumbelrnd (1) ***** error ... gumbelrnd (ones (3), ones (2)) ***** error ... gumbelrnd (ones (2), ones (3)) ***** error gumbelrnd (i, 2, 3) ***** error gumbelrnd (1, i, 3) ***** error ... gumbelrnd (1, 2, -1) ***** error ... gumbelrnd (1, 2, 1.2) ***** error ... gumbelrnd (1, 2, ones (2)) ***** error ... gumbelrnd (1, 2, [2 -1 2]) ***** error ... gumbelrnd (1, 2, [2 0 2.5]) ***** error ... gumbelrnd (1, 2, 2, -1, 5) ***** error ... gumbelrnd (1, 2, 2, 1.5, 5) ***** error ... gumbelrnd (2, ones (2), 3) ***** error ... gumbelrnd (2, ones (2), [3, 2]) ***** error ... gumbelrnd (2, ones (2), 3, 2) 33 tests, 33 passed, 0 known failure, 0 skipped [inst/dist_fun/ricecdf.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/dist_fun/ricecdf.m ***** demo ## Plot various CDFs from the Rician distribution x = 0:0.01:10; p1 = ricecdf (x, 0, 1); p2 = ricecdf (x, 0.5, 1); p3 = ricecdf (x, 1, 1); p4 = ricecdf (x, 2, 1); p5 = ricecdf (x, 4, 1); plot (x, p1, "-b", x, p2, "g", x, p3, "-r", x, p4, "-m", x, p5, "-k") grid on ylim ([0, 1]) xlim ([0, 8]) legend ({"s = 0, σ = 1", "s = 0.5, σ = 1", "s = 1, σ = 1", ... "s = 2, σ = 1", "s = 4, σ = 1"}, "location", "southeast") title ("Rician CDF") xlabel ("values in x") ylabel ("probability") ***** demo ## Plot various CDFs from the Rician distribution x = 0:0.01:10; p1 = ricecdf (x, 0, 0.5); p2 = ricecdf (x, 0, 2); p3 = ricecdf (x, 0, 3); p4 = ricecdf (x, 2, 2); p5 = ricecdf (x, 4, 2); plot (x, p1, "-b", x, p2, "g", x, p3, "-r", x, p4, "-m", x, p5, "-k") grid on ylim ([0, 1]) xlim ([0, 8]) legend ({"ν = 0, σ = 0.5", "ν = 0, σ = 2", "ν = 0, σ = 3", ... "ν = 2, σ = 2", "ν = 4, σ = 2"}, "location", "southeast") title ("Rician CDF") xlabel ("values in x") ylabel ("probability") ***** test x = 0:0.5:2.5; s = 1:6; p = ricecdf (x, s, 1); expected_p = [0.0000, 0.0179, 0.0108, 0.0034, 0.0008, 0.0001]; assert (p, expected_p, 0.001); ***** test x = 0:0.5:2.5; sigma = 1:6; p = ricecdf (x, 1, sigma); expected_p = [0.0000, 0.0272, 0.0512, 0.0659, 0.0754, 0.0820]; assert (p, expected_p, 0.001); ***** test x = 0:0.5:2.5; p = ricecdf (x, 0, 1); expected_p = [0.0000, 0.1175, 0.3935, 0.6753, 0.8647, 0.9561]; assert (p, expected_p, 0.001); ***** test x = 0:0.5:2.5; p = ricecdf (x, 1, 1); expected_p = [0.0000, 0.0735, 0.2671, 0.5120, 0.7310, 0.8791]; assert (p, expected_p, 0.001); ***** shared x, p x = [-1, 0, 1, 2, Inf]; p = [0, 0, 0.26712019620318, 0.73098793996409, 1]; ***** assert (ricecdf (x, 1, 1), p, 1e-14) ***** assert (ricecdf (x, 1, 1, "upper"), 1 - p, 1e-14) ***** error ricecdf () ***** error ricecdf (1) ***** error ricecdf (1, 2) ***** error ricecdf (1, 2, 3, "uper") ***** error ricecdf (1, 2, 3, 4) ***** error ... ricecdf (ones (3), ones (2), ones (2)) ***** error ... ricecdf (ones (2), ones (3), ones (2)) ***** error ... ricecdf (ones (2), ones (2), ones (3)) ***** error ricecdf (i, 2, 3) ***** error ricecdf (2, i, 3) ***** error ricecdf (2, 2, i) 17 tests, 17 passed, 0 known failure, 0 skipped [inst/dist_fun/gaminv.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/dist_fun/gaminv.m ***** demo ## Plot various iCDFs from the Gamma distribution p = 0.001:0.001:0.999; x1 = gaminv (p, 1, 2); x2 = gaminv (p, 2, 2); x3 = gaminv (p, 3, 2); x4 = gaminv (p, 5, 1); x5 = gaminv (p, 9, 0.5); x6 = gaminv (p, 7.5, 1); x7 = gaminv (p, 0.5, 1); plot (p, x1, "-r", p, x2, "-g", p, x3, "-y", p, x4, "-m", ... p, x5, "-k", p, x6, "-b", p, x7, "-c") ylim ([0, 20]) grid on legend ({"α = 1, β = 2", "α = 2, β = 2", "α = 3, β = 2", ... "α = 5, β = 1", "α = 9, β = 0.5", "α = 7.5, β = 1", ... "α = 0.5, β = 1"}, "location", "northwest") title ("Gamma iCDF") xlabel ("probability") ylabel ("x") ***** shared p p = [-1 0 0.63212055882855778 1 2]; ***** assert (gaminv (p, ones (1,5), ones (1,5)), [NaN 0 1 Inf NaN], eps) ***** assert (gaminv (p, 1, ones (1,5)), [NaN 0 1 Inf NaN], eps) ***** assert (gaminv (p, ones (1,5), 1), [NaN 0 1 Inf NaN], eps) ***** assert (gaminv (p, [1 -Inf NaN Inf 1], 1), [NaN NaN NaN NaN NaN]) ***** assert (gaminv (p, 1, [1 -Inf NaN Inf 1]), [NaN NaN NaN NaN NaN]) ***** assert (gaminv ([p(1:2) NaN p(4:5)], 1, 1), [NaN 0 NaN Inf NaN]) ***** assert (gaminv ([p(1:2) NaN p(4:5)], 1, 1), [NaN 0 NaN Inf NaN]) ***** assert (gaminv (1e-16, 1, 1), 1e-16, eps) ***** assert (gaminv (1e-16, 1, 2), 2e-16, eps) ***** assert (gaminv (1e-20, 3, 5), 1.957434012161815e-06, eps) ***** assert (gaminv (1e-15, 1, 1), 1e-15, eps) ***** assert (gaminv (1e-35, 1, 1), 1e-35, eps) ***** assert (gaminv ([p, NaN], 1, 1), [NaN 0 1 Inf NaN NaN], eps) ***** assert (gaminv (single ([p, NaN]), 1, 1), single ([NaN 0 1 Inf NaN NaN]), ... eps ("single")) ***** assert (gaminv ([p, NaN], single (1), 1), single ([NaN 0 1 Inf NaN NaN]), ... eps ("single")) ***** assert (gaminv ([p, NaN], 1, single (1)), single ([NaN 0 1 Inf NaN NaN]), ... eps ("single")) ***** error gaminv () ***** error gaminv (1) ***** error gaminv (1,2) ***** error ... gaminv (ones (3), ones (2), ones (2)) ***** error ... gaminv (ones (2), ones (3), ones (2)) ***** error ... gaminv (ones (2), ones (2), ones (3)) ***** error gaminv (i, 2, 2) ***** error gaminv (2, i, 2) ***** error gaminv (2, 2, i) 25 tests, 25 passed, 0 known failure, 0 skipped [inst/dist_fun/gumbelinv.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/dist_fun/gumbelinv.m ***** demo ## Plot various iCDFs from the Gumbel distribution p = 0.001:0.001:0.999; x1 = gumbelinv (p, 0.5, 2); x2 = gumbelinv (p, 1.0, 2); x3 = gumbelinv (p, 1.5, 3); x4 = gumbelinv (p, 3.0, 4); plot (p, x1, "-b", p, x2, "-g", p, x3, "-r", p, x4, "-c") grid on ylim ([-5, 20]) legend ({"μ = 0.5, β = 2", "μ = 1.0, β = 2", ... "μ = 1.5, β = 3", "μ = 3.0, β = 4"}, "location", "northwest") title ("Gumbel iCDF") xlabel ("probability") ylabel ("values in x") ***** shared p, x p = [0, 0.05, 0.5 0.95]; x = [-Inf, -1.0972, 0.3665, 2.9702]; ***** assert (gumbelinv (p), x, 1e-4) ***** assert (gumbelinv (p, zeros (1,4), ones (1,4)), x, 1e-4) ***** assert (gumbelinv (p, 0, ones (1,4)), x, 1e-4) ***** assert (gumbelinv (p, zeros (1,4), 1), x, 1e-4) ***** assert (gumbelinv (p, [0, -Inf, NaN, Inf], 1), [-Inf, Inf, NaN, -Inf], 1e-4) ***** assert (gumbelinv (p, 0, [Inf, NaN, -1, 0]), [-Inf, NaN, NaN, NaN], 1e-4) ***** assert (gumbelinv ([p(1:2), NaN, p(4)], 0, 1), [x(1:2), NaN, x(4)], 1e-4) ***** assert (gumbelinv ([p, NaN], 0, 1), [x, NaN], 1e-4) ***** assert (gumbelinv (single ([p, NaN]), 0, 1), single ([x, NaN]), 1e-4) ***** assert (gumbelinv ([p, NaN], single (0), 1), single ([x, NaN]), 1e-4) ***** assert (gumbelinv ([p, NaN], 0, single (1)), single ([x, NaN]), 1e-4) ***** error gumbelinv () ***** error gumbelinv (1,2,3,4,5,6) ***** error ... gumbelinv (ones (3), ones (2), ones (2)) ***** error ... [p, plo, pup] = gumbelinv (2, 3, 4, [1, 2]) ***** error ... [p, plo, pup] = gumbelinv (1, 2, 3) ***** error [p, plo, pup] = ... gumbelinv (1, 2, 3, [1, 0; 0, 1], 0) ***** error [p, plo, pup] = ... gumbelinv (1, 2, 3, [1, 0; 0, 1], 1.22) ***** error gumbelinv (i, 2, 2) ***** error gumbelinv (2, i, 2) ***** error gumbelinv (2, 2, i) ***** error ... [p, plo, pup] = gumbelinv (1, 2, 3, [-1, 10; -Inf, -Inf], 0.04) 22 tests, 22 passed, 0 known failure, 0 skipped [inst/dist_fun/nakarnd.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/dist_fun/nakarnd.m ***** assert (size (nakarnd (1, 1)), [1 1]) ***** assert (size (nakarnd (1, ones (2,1))), [2, 1]) ***** assert (size (nakarnd (1, ones (2,2))), [2, 2]) ***** assert (size (nakarnd (ones (2,1), 1)), [2, 1]) ***** assert (size (nakarnd (ones (2,2), 1)), [2, 2]) ***** assert (size (nakarnd (1, 1, 3)), [3, 3]) ***** assert (size (nakarnd (1, 1, [4, 1])), [4, 1]) ***** assert (size (nakarnd (1, 1, 4, 1)), [4, 1]) ***** assert (size (nakarnd (1, 1, 4, 1, 5)), [4, 1, 5]) ***** assert (size (nakarnd (1, 1, 0, 1)), [0, 1]) ***** assert (size (nakarnd (1, 1, 1, 0)), [1, 0]) ***** assert (size (nakarnd (1, 1, 1, 2, 0, 5)), [1, 2, 0, 5]) ***** assert (class (nakarnd (1, 1)), "double") ***** assert (class (nakarnd (1, single (1))), "single") ***** assert (class (nakarnd (1, single ([1, 1]))), "single") ***** assert (class (nakarnd (single (1), 1)), "single") ***** assert (class (nakarnd (single ([1, 1]), 1)), "single") ***** error nakarnd () ***** error nakarnd (1) ***** error ... nakarnd (ones (3), ones (2)) ***** error ... nakarnd (ones (2), ones (3)) ***** error nakarnd (i, 2, 3) ***** error nakarnd (1, i, 3) ***** error ... nakarnd (1, 2, -1) ***** error ... nakarnd (1, 2, 1.2) ***** error ... nakarnd (1, 2, ones (2)) ***** error ... nakarnd (1, 2, [2 -1 2]) ***** error ... nakarnd (1, 2, [2 0 2.5]) ***** error ... nakarnd (1, 2, 2, -1, 5) ***** error ... nakarnd (1, 2, 2, 1.5, 5) ***** error ... nakarnd (2, ones (2), 3) ***** error ... nakarnd (2, ones (2), [3, 2]) ***** error ... nakarnd (2, ones (2), 3, 2) 33 tests, 33 passed, 0 known failure, 0 skipped [inst/dist_fun/mvtpdf.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/dist_fun/mvtpdf.m ***** demo ## Compute the pdf of a multivariate t distribution with correlation ## parameters rho = [1 .4; .4 1] and 2 degrees of freedom. rho = [1, 0.4; 0.4, 1]; df = 2; [X1, X2] = meshgrid (linspace (-2, 2, 25)', linspace (-2, 2, 25)'); X = [X1(:), X2(:)]; y = mvtpdf (X, rho, df); surf (X1, X2, reshape (y, 25, 25)); title ("Bivariate Student's t probability density function"); ***** assert (mvtpdf ([0 0], eye(2), 1), 0.1591549, 1E-7) ***** assert (mvtpdf ([1 0], [1 0.5; 0.5 1], 2), 0.06615947, 1E-7) ***** assert (mvtpdf ([1 0.4 0; 1.2 0.5 0.5; 1.4 0.6 1], ... [1 0.5 0.3; 0.5 1 0.6; 0.3 0.6 1], [5 6 7]), ... [0.04713313 0.03722421 0.02069011]', 1E-7) 3 tests, 3 passed, 0 known failure, 0 skipped [inst/dist_fun/hygecdf.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/dist_fun/hygecdf.m ***** demo ## Plot various CDFs from the hypergeometric distribution x = 0:60; p1 = hygecdf (x, 500, 50, 100); p2 = hygecdf (x, 500, 60, 200); p3 = hygecdf (x, 500, 70, 300); plot (x, p1, "*b", x, p2, "*g", x, p3, "*r") grid on xlim ([0, 60]) legend ({"m = 500, k = 50, n = 100", "m = 500, k = 60, n = 200", ... "m = 500, k = 70, n = 300"}, "location", "southeast") title ("Hypergeometric CDF") xlabel ("values in x (number of successes)") ylabel ("probability") ***** shared x, y x = [-1 0 1 2 3]; y = [0 1/6 5/6 1 1]; ***** assert (hygecdf (x, 4*ones (1,5), 2, 2), y, 5*eps) ***** assert (hygecdf (x, 4, 2*ones (1,5), 2), y, 5*eps) ***** assert (hygecdf (x, 4, 2, 2*ones (1,5)), y, 5*eps) ***** assert (hygecdf (x, 4*[1 -1 NaN 1.1 1], 2, 2), [y(1) NaN NaN NaN y(5)], 5*eps) ***** assert (hygecdf (x, 4*[1 -1 NaN 1.1 1], 2, 2, "upper"), ... [y(5) NaN NaN NaN y(1)], 5*eps) ***** assert (hygecdf (x, 4, 2*[1 -1 NaN 1.1 1], 2), [y(1) NaN NaN NaN y(5)], 5*eps) ***** assert (hygecdf (x, 4, 2*[1 -1 NaN 1.1 1], 2, "upper"), ... [y(5) NaN NaN NaN y(1)], 5*eps) ***** assert (hygecdf (x, 4, 5, 2), [NaN NaN NaN NaN NaN]) ***** assert (hygecdf (x, 4, 2, 2*[1 -1 NaN 1.1 1]), [y(1) NaN NaN NaN y(5)], 5*eps) ***** assert (hygecdf (x, 4, 2, 2*[1 -1 NaN 1.1 1], "upper"), ... [y(5) NaN NaN NaN y(1)], 5*eps) ***** assert (hygecdf (x, 4, 2, 5), [NaN NaN NaN NaN NaN]) ***** assert (hygecdf ([x(1:2) NaN x(4:5)], 4, 2, 2), [y(1:2) NaN y(4:5)], 5*eps) ***** test p = hygecdf (x, 10, [1 2 3 4 5], 2, "upper"); assert (p, [1, 34/90, 2/30, 0, 0], 10*eps); ***** test p = hygecdf (2*x, 10, [1 2 3 4 5], 2, "upper"); assert (p, [1, 34/90, 0, 0, 0], 10*eps); ***** assert (hygecdf ([x, NaN], 4, 2, 2), [y, NaN], 5*eps) ***** assert (hygecdf (single ([x, NaN]), 4, 2, 2), single ([y, NaN]), ... eps ("single")) ***** assert (hygecdf ([x, NaN], single (4), 2, 2), single ([y, NaN]), ... eps ("single")) ***** assert (hygecdf ([x, NaN], 4, single (2), 2), single ([y, NaN]), ... eps ("single")) ***** assert (hygecdf ([x, NaN], 4, 2, single (2)), single ([y, NaN]), ... eps ("single")) ***** error hygecdf () ***** error hygecdf (1) ***** error hygecdf (1,2) ***** error hygecdf (1,2,3) ***** error hygecdf (1,2,3,4,5) ***** error hygecdf (1,2,3,4,"uper") ***** error ... hygecdf (ones (2), ones (3), 1, 1) ***** error ... hygecdf (1, ones (2), ones (3), 1) ***** error ... hygecdf (1, 1, ones (2), ones (3)) ***** error hygecdf (i, 2, 2, 2) ***** error hygecdf (2, i, 2, 2) ***** error hygecdf (2, 2, i, 2) ***** error hygecdf (2, 2, 2, i) 32 tests, 32 passed, 0 known failure, 0 skipped [inst/dist_fun/betacdf.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/dist_fun/betacdf.m ***** demo ## Plot various CDFs from the Beta distribution x = 0:0.005:1; p1 = betacdf (x, 0.5, 0.5); p2 = betacdf (x, 5, 1); p3 = betacdf (x, 1, 3); p4 = betacdf (x, 2, 2); p5 = betacdf (x, 2, 5); plot (x, p1, "-b", x, p2, "-g", x, p3, "-r", x, p4, "-c", x, p5, "-m") grid on legend ({"α = β = 0.5", "α = 5, β = 1", "α = 1, β = 3", ... "α = 2, β = 2", "α = 2, β = 5"}, "location", "northwest") title ("Beta CDF") xlabel ("values in x") ylabel ("probability") ***** shared x, y, x1, x2 x = [-1 0 0.5 1 2]; y = [0 0 0.75 1 1]; ***** assert (betacdf (x, ones (1, 5), 2 * ones (1, 5)), y) ***** assert (betacdf (x, 1, 2 * ones (1, 5)), y) ***** assert (betacdf (x, ones (1, 5), 2), y) ***** assert (betacdf (x, [0 1 NaN 1 1], 2), [NaN 0 NaN 1 1]) ***** assert (betacdf (x, 1, 2 * [0 1 NaN 1 1]), [NaN 0 NaN 1 1]) ***** assert (betacdf ([x(1:2) NaN x(4:5)], 1, 2), [y(1:2) NaN y(4:5)]) x1 = [0.1:0.2:0.9]; ***** assert (betacdf (x1, 2, 2), [0.028, 0.216, 0.5, 0.784, 0.972], 1e-14); ***** assert (betacdf (x1, 2, 2, "upper"), 1 - [0.028, 0.216, 0.5, 0.784, 0.972],... 1e-14); x2 = [1, 2, 3]; ***** assert (betacdf (0.5, x2, x2), [0.5, 0.5, 0.5], 1e-14); ***** assert (betacdf ([x, NaN], 1, 2), [y, NaN]) ***** assert (betacdf (single ([x, NaN]), 1, 2), single ([y, NaN])) ***** assert (betacdf ([x, NaN], single (1), 2), single ([y, NaN])) ***** assert (betacdf ([x, NaN], 1, single (2)), single ([y, NaN])) ***** error betacdf () ***** error betacdf (1) ***** error betacdf (1, 2) ***** error betacdf (1, 2, 3, 4, 5) ***** error betacdf (1, 2, 3, "tail") ***** error betacdf (1, 2, 3, 4) ***** error ... betacdf (ones (3), ones (2), ones (2)) ***** error ... betacdf (ones (2), ones (3), ones (2)) ***** error ... betacdf (ones (2), ones (2), ones (3)) ***** error betacdf (i, 2, 2) ***** error betacdf (2, i, 2) ***** error betacdf (2, 2, i) 25 tests, 25 passed, 0 known failure, 0 skipped [inst/dist_fun/logncdf.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/dist_fun/logncdf.m ***** demo ## Plot various CDFs from the log-normal distribution x = 0:0.01:3; p1 = logncdf (x, 0, 1); p2 = logncdf (x, 0, 0.5); p3 = logncdf (x, 0, 0.25); plot (x, p1, "-b", x, p2, "-g", x, p3, "-r") grid on legend ({"μ = 0, σ = 1", "μ = 0, σ = 0.5", "μ = 0, σ = 0.25"}, ... "location", "southeast") title ("Log-normal CDF") xlabel ("values in x") ylabel ("probability") ***** shared x, y x = [-1, 0, 1, e, Inf]; y = [0, 0, 0.5, 1/2+1/2*erf(1/2), 1]; ***** assert (logncdf (x, zeros (1,5), sqrt(2)*ones (1,5)), y, eps) ***** assert (logncdf (x, zeros (1,5), sqrt(2)*ones (1,5), []), y, eps) ***** assert (logncdf (x, 0, sqrt(2)*ones (1,5)), y, eps) ***** assert (logncdf (x, zeros (1,5), sqrt(2)), y, eps) ***** assert (logncdf (x, [0 1 NaN 0 1], sqrt(2)), [0 0 NaN y(4:5)], eps) ***** assert (logncdf (x, 0, sqrt(2)*[0 NaN Inf 1 1]), [NaN NaN y(3:5)], eps) ***** assert (logncdf ([x(1:3) NaN x(5)], 0, sqrt(2)), [y(1:3) NaN y(5)], eps) ***** assert (logncdf ([x, NaN], 0, sqrt(2)), [y, NaN], eps) ***** assert (logncdf (single ([x, NaN]), 0, sqrt(2)), single ([y, NaN]), eps ("single")) ***** assert (logncdf ([x, NaN], single (0), sqrt(2)), single ([y, NaN]), eps ("single")) ***** assert (logncdf ([x, NaN], 0, single (sqrt(2))), single ([y, NaN]), eps ("single")) ***** error logncdf () ***** error logncdf (1,2,3,4,5,6,7) ***** error logncdf (1, 2, 3, 4, "uper") ***** error ... logncdf (ones (3), ones (2), ones (2)) ***** error logncdf (2, 3, 4, [1, 2]) ***** error ... [p, plo, pup] = logncdf (1, 2, 3) ***** error [p, plo, pup] = ... logncdf (1, 2, 3, [1, 0; 0, 1], 0) ***** error [p, plo, pup] = ... logncdf (1, 2, 3, [1, 0; 0, 1], 1.22) ***** error [p, plo, pup] = ... logncdf (1, 2, 3, [1, 0; 0, 1], "alpha", "upper") ***** error logncdf (i, 2, 2) ***** error logncdf (2, i, 2) ***** error logncdf (2, 2, i) ***** error ... [p, plo, pup] =logncdf (1, 2, 3, [1, 0; 0, -inf], 0.04) 24 tests, 24 passed, 0 known failure, 0 skipped [inst/dist_fun/cauchypdf.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/dist_fun/cauchypdf.m ***** demo ## Plot various PDFs from the Cauchy distribution x = -5:0.01:5; y1 = cauchypdf (x, 0, 0.5); y2 = cauchypdf (x, 0, 1); y3 = cauchypdf (x, 0, 2); y4 = cauchypdf (x, -2, 1); plot (x, y1, "-b", x, y2, "-g", x, y3, "-r", x, y4, "-c") grid on xlim ([-5, 5]) ylim ([0, 0.7]) legend ({"x0 = 0, γ = 0.5", "x0 = 0, γ = 1", ... "x0 = 0, γ = 2", "x0 = -2, γ = 1"}, "location", "northeast") title ("Cauchy PDF") xlabel ("values in x") ylabel ("density") ***** shared x, y x = [-1 0 0.5 1 2]; y = 1/pi * ( 2 ./ ((x-1).^2 + 2^2) ); ***** assert (cauchypdf (x, ones (1,5), 2*ones (1,5)), y) ***** assert (cauchypdf (x, 1, 2*ones (1,5)), y) ***** assert (cauchypdf (x, ones (1,5), 2), y) ***** assert (cauchypdf (x, [-Inf 1 NaN 1 Inf], 2), [NaN y(2) NaN y(4) NaN]) ***** assert (cauchypdf (x, 1, 2*[0 1 NaN 1 Inf]), [NaN y(2) NaN y(4) NaN]) ***** assert (cauchypdf ([x, NaN], 1, 2), [y, NaN]) ***** assert (cauchypdf (single ([x, NaN]), 1, 2), single ([y, NaN]), eps ("single")) ***** assert (cauchypdf ([x, NaN], single (1), 2), single ([y, NaN]), eps ("single")) ***** assert (cauchypdf ([x, NaN], 1, single (2)), single ([y, NaN]), eps ("single")) ***** test x = rand (10, 1); assert (cauchypdf (x, 0, 1), tpdf (x, 1), eps); ***** error cauchypdf () ***** error cauchypdf (1) ***** error ... cauchypdf (1, 2) ***** error cauchypdf (1, 2, 3, 4) ***** error ... cauchypdf (ones (3), ones (2), ones(2)) ***** error ... cauchypdf (ones (2), ones (3), ones(2)) ***** error ... cauchypdf (ones (2), ones (2), ones(3)) ***** error cauchypdf (i, 4, 3) ***** error cauchypdf (1, i, 3) ***** error cauchypdf (1, 4, i) 20 tests, 20 passed, 0 known failure, 0 skipped [inst/dist_fun/tlspdf.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/dist_fun/tlspdf.m ***** demo ## Plot various PDFs from the Student's T distribution x = -8:0.01:8; y1 = tlspdf (x, 0, 1, 1); y2 = tlspdf (x, 0, 2, 2); y3 = tlspdf (x, 3, 2, 5); y4 = tlspdf (x, -1, 3, Inf); plot (x, y1, "-b", x, y2, "-g", x, y3, "-r", x, y4, "-m") grid on xlim ([-8, 8]) ylim ([0, 0.41]) legend ({"mu = 0, sigma = 1, nu = 1", "mu = 0, sigma = 2, nu = 2", ... "mu = 3, sigma = 2, nu = 5", 'mu = -1, sigma = 3, nu = \infty'}, ... "location", "northwest") title ("Location-scale Student's T PDF") xlabel ("values in x") ylabel ("density") ***** test x = rand (10,1); y = 1./(pi * (1 + x.^2)); assert (tlspdf (x, 0, 1, 1), y, 5*eps); assert (tlspdf (x+5, 5, 1, 1), y, 5*eps); assert (tlspdf (x.*2, 0, 2, 1), y./2, 5*eps); ***** shared x, y x = [-Inf 0 0.5 1 Inf]; y = 1./(pi * (1 + x.^2)); ***** assert (tlspdf (x, 0, 1, ones (1,5)), y, eps) ***** assert (tlspdf (x, 0, 1, 1), y, eps) ***** assert (tlspdf (x, 0, 1, [0 NaN 1 1 1]), [NaN NaN y(3:5)], eps) ***** assert (tlspdf (x, 0, 1, Inf), normpdf (x)) ***** assert (class (tlspdf ([x, NaN], 1, 1, 1)), "double") ***** assert (class (tlspdf (single ([x, NaN]), 1, 1, 1)), "single") ***** assert (class (tlspdf ([x, NaN], single (1), 1, 1)), "single") ***** assert (class (tlspdf ([x, NaN], 1, single (1), 1)), "single") ***** assert (class (tlspdf ([x, NaN], 1, 1, single (1))), "single") ***** error tlspdf () ***** error tlspdf (1) ***** error tlspdf (1, 2) ***** error tlspdf (1, 2, 3) ***** error ... tlspdf (ones (3), ones (2), 1, 1) ***** error ... tlspdf (ones (2), 1, ones (3), 1) ***** error ... tlspdf (ones (2), 1, 1, ones (3)) ***** error tlspdf (i, 2, 1, 1) ***** error tlspdf (2, i, 1, 1) ***** error tlspdf (2, 1, i, 1) ***** error tlspdf (2, 1, 1, i) 21 tests, 21 passed, 0 known failure, 0 skipped [inst/dist_fun/unifpdf.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/dist_fun/unifpdf.m ***** demo ## Plot various PDFs from the continuous uniform distribution x = 0:0.001:10; y1 = unifpdf (x, 2, 5); y2 = unifpdf (x, 3, 9); plot (x, y1, "-b", x, y2, "-g") grid on xlim ([0, 10]) ylim ([0, 0.4]) legend ({"a = 2, b = 5", "a = 3, b = 9"}, "location", "northeast") title ("Continuous uniform PDF") xlabel ("values in x") ylabel ("density") ***** shared x, y x = [-1 0 0.5 1 2] + 1; y = [0 1 1 1 0]; ***** assert (unifpdf (x, ones (1,5), 2*ones (1,5)), y) ***** assert (unifpdf (x, 1, 2*ones (1,5)), y) ***** assert (unifpdf (x, ones (1,5), 2), y) ***** assert (unifpdf (x, [2 NaN 1 1 1], 2), [NaN NaN y(3:5)]) ***** assert (unifpdf (x, 1, 2*[0 NaN 1 1 1]), [NaN NaN y(3:5)]) ***** assert (unifpdf ([x, NaN], 1, 2), [y, NaN]) ***** assert (unifpdf (x, 0, 1), [1 1 0 0 0]) ***** assert (unifpdf (single ([x, NaN]), 1, 2), single ([y, NaN])) ***** assert (unifpdf (single ([x, NaN]), single (1), 2), single ([y, NaN])) ***** assert (unifpdf ([x, NaN], 1, single (2)), single ([y, NaN])) ***** error unifpdf () ***** error unifpdf (1) ***** error unifpdf (1, 2) ***** error ... unifpdf (ones (3), ones (2), ones (2)) ***** error ... unifpdf (ones (2), ones (3), ones (2)) ***** error ... unifpdf (ones (2), ones (2), ones (3)) ***** error unifpdf (i, 2, 2) ***** error unifpdf (2, i, 2) ***** error unifpdf (2, 2, i) 19 tests, 19 passed, 0 known failure, 0 skipped [inst/dist_fun/jsupdf.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/dist_fun/jsupdf.m ***** error jsupdf () ***** error jsupdf (1, 2, 3, 4) ***** error ... jsupdf (1, ones (2), ones (3)) 3 tests, 3 passed, 0 known failure, 0 skipped [inst/dist_fun/tlsinv.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/dist_fun/tlsinv.m ***** demo ## Plot various iCDFs from the location-scale Student's T distribution p = 0.001:0.001:0.999; x1 = tlsinv (p, 0, 1, 1); x2 = tlsinv (p, 0, 2, 2); x3 = tlsinv (p, 3, 2, 5); x4 = tlsinv (p, -1, 3, Inf); plot (p, x1, "-b", p, x2, "-g", p, x3, "-r", p, x4, "-m") grid on xlim ([0, 1]) ylim ([-8, 8]) legend ({"mu = 0, sigma = 1, nu = 1", "mu = 0, sigma = 2, nu = 2", ... "mu = 3, sigma = 2, nu = 5", 'mu = -1, sigma = 3, nu = \infty'}, ... "location", "southeast") title ("Location-scale Student's T iCDF") xlabel ("probability") ylabel ("values in x") ***** shared p p = [-1 0 0.5 1 2]; ***** assert (tlsinv (p, 0, 1, ones (1,5)), [NaN -Inf 0 Inf NaN]) ***** assert (tlsinv (p, 0, 1, 1), [NaN -Inf 0 Inf NaN], eps) ***** assert (tlsinv (p, 0, 1, [1 0 NaN 1 1]), [NaN NaN NaN Inf NaN], eps) ***** assert (tlsinv ([p(1:2) NaN p(4:5)], 0, 1, 1), [NaN -Inf NaN Inf NaN]) ***** assert (class (tlsinv ([p, NaN], 0, 1, 1)), "double") ***** assert (class (tlsinv (single ([p, NaN]), 0, 1, 1)), "single") ***** assert (class (tlsinv ([p, NaN], single (0), 1, 1)), "single") ***** assert (class (tlsinv ([p, NaN], 0, single (1), 1)), "single") ***** assert (class (tlsinv ([p, NaN], 0, 1, single (1))), "single") ***** error tlsinv () ***** error tlsinv (1) ***** error tlsinv (1, 2) ***** error tlsinv (1, 2, 3) ***** error ... tlsinv (ones (3), ones (2), 1, 1) ***** error ... tlsinv (ones (2), 1, ones (3), 1) ***** error ... tlsinv (ones (2), 1, 1, ones (3)) ***** error tlsinv (i, 2, 3, 4) ***** error tlsinv (2, i, 3, 4) ***** error tlsinv (2, 2, i, 4) ***** error tlsinv (2, 2, 3, i) 20 tests, 20 passed, 0 known failure, 0 skipped [inst/dist_fun/lognpdf.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/dist_fun/lognpdf.m ***** demo ## Plot various PDFs from the log-normal distribution x = 0:0.01:5; y1 = lognpdf (x, 0, 1); y2 = lognpdf (x, 0, 0.5); y3 = lognpdf (x, 0, 0.25); plot (x, y1, "-b", x, y2, "-g", x, y3, "-r") grid on ylim ([0, 2]) legend ({"μ = 0, σ = 1", "μ = 0, σ = 0.5", "μ = 0, σ = 0.25"}, ... "location", "northeast") title ("Log-normal PDF") xlabel ("values in x") ylabel ("density") ***** shared x, y x = [-1 0 e Inf]; y = [0, 0, 1/(e*sqrt(2*pi)) * exp(-1/2), 0]; ***** assert (lognpdf (x, zeros (1,4), ones (1,4)), y, eps) ***** assert (lognpdf (x, 0, ones (1,4)), y, eps) ***** assert (lognpdf (x, zeros (1,4), 1), y, eps) ***** assert (lognpdf (x, [0 1 NaN 0], 1), [0 0 NaN y(4)], eps) ***** assert (lognpdf (x, 0, [0 NaN Inf 1]), [NaN NaN NaN y(4)], eps) ***** assert (lognpdf ([x, NaN], 0, 1), [y, NaN], eps) ***** assert (lognpdf (single ([x, NaN]), 0, 1), single ([y, NaN]), eps ("single")) ***** assert (lognpdf ([x, NaN], single (0), 1), single ([y, NaN]), eps ("single")) ***** assert (lognpdf ([x, NaN], 0, single (1)), single ([y, NaN]), eps ("single")) ***** error lognpdf () ***** error lognpdf (1,2,3,4) ***** error lognpdf (ones (3), ones (2), ones (2)) ***** error lognpdf (ones (2), ones (3), ones (2)) ***** error lognpdf (ones (2), ones (2), ones (3)) ***** error lognpdf (i, 2, 2) ***** error lognpdf (2, i, 2) ***** error lognpdf (2, 2, i) 17 tests, 17 passed, 0 known failure, 0 skipped [inst/dist_fun/loglcdf.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/dist_fun/loglcdf.m ***** demo ## Plot various CDFs from the log-logistic distribution x = 0:0.001:2; p1 = loglcdf (x, log (1), 1/0.5); p2 = loglcdf (x, log (1), 1); p3 = loglcdf (x, log (1), 1/2); p4 = loglcdf (x, log (1), 1/4); p5 = loglcdf (x, log (1), 1/8); plot (x, p1, "-b", x, p2, "-g", x, p3, "-r", x, p4, "-c", x, p5, "-m") legend ({"σ = 2 (β = 0.5)", "σ = 1 (β = 1)", "σ = 0.5 (β = 2)", ... "σ = 0.25 (β = 4)", "σ = 0.125 (β = 8)"}, "location", "northwest") grid on title ("Log-logistic CDF") xlabel ("values in x") ylabel ("probability") text (0.05, 0.64, "μ = 0 (α = 1), values of σ (β) as shown in legend") ***** shared out1, out2 out1 = [0, 0.5, 0.66666667, 0.75, 0.8, 0.83333333]; out2 = [0, 0.4174, 0.4745, 0.5082, 0.5321, 0.5506]; ***** assert (loglcdf ([0:5], 0, 1), out1, 1e-8) ***** assert (loglcdf ([0:5], 0, 1, "upper"), 1 - out1, 1e-8) ***** assert (loglcdf ([0:5], 0, 1), out1, 1e-8) ***** assert (loglcdf ([0:5], 0, 1, "upper"), 1 - out1, 1e-8) ***** assert (loglcdf ([0:5], 1, 3), out2, 1e-4) ***** assert (loglcdf ([0:5], 1, 3, "upper"), 1 - out2, 1e-4) ***** assert (class (loglcdf (single (1), 2, 3)), "single") ***** assert (class (loglcdf (1, single (2), 3)), "single") ***** assert (class (loglcdf (1, 2, single (3))), "single") ***** error loglcdf (1) ***** error loglcdf (1, 2) ***** error ... loglcdf (1, 2, 3, 4) ***** error ... loglcdf (1, 2, 3, "uper") ***** error ... loglcdf (1, ones (2), ones (3)) ***** error ... loglcdf (1, ones (2), ones (3), "upper") ***** error ... loglcdf (ones (2), 1, ones (3)) ***** error ... loglcdf (ones (2), 1, ones (3), "upper") ***** error ... loglcdf (ones (2), ones (3), 1) ***** error ... loglcdf (ones (2), ones (3), 1, "upper") ***** error loglcdf (i, 2, 3) ***** error loglcdf (i, 2, 3, "upper") ***** error loglcdf (1, i, 3) ***** error loglcdf (1, i, 3, "upper") ***** error loglcdf (1, 2, i) ***** error loglcdf (1, 2, i, "upper") 25 tests, 25 passed, 0 known failure, 0 skipped [inst/dist_fun/ncx2pdf.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/dist_fun/ncx2pdf.m ***** demo ## Plot various PDFs from the noncentral chi-squared distribution x = 0:0.1:10; y1 = ncx2pdf (x, 2, 1); y2 = ncx2pdf (x, 2, 2); y3 = ncx2pdf (x, 2, 3); y4 = ncx2pdf (x, 4, 1); y5 = ncx2pdf (x, 4, 2); y6 = ncx2pdf (x, 4, 3); plot (x, y1, "-r", x, y2, "-g", x, y3, "-k", ... x, y4, "-m", x, y5, "-c", x, y6, "-y") grid on xlim ([0, 10]) ylim ([0, 0.32]) legend ({"df = 2, λ = 1", "df = 2, λ = 2", ... "df = 2, λ = 3", "df = 4, λ = 1", ... "df = 4, λ = 2", "df = 4, λ = 3"}, "location", "northeast") title ("Noncentral chi-squared PDF") xlabel ("values in x") ylabel ("density") ***** demo ## Compare the noncentral chi-squared PDF with LAMBDA = 2 to the ## chi-squared PDF with the same number of degrees of freedom (4). x = 0:0.1:10; y1 = ncx2pdf (x, 4, 2); y2 = chi2pdf (x, 4); plot (x, y1, "-", x, y2, "-"); grid on xlim ([0, 10]) ylim ([0, 0.32]) legend ({"Noncentral T(10,1)", "T(10)"}, "location", "northwest") title ("Noncentral chi-squared vs chi-squared PDFs") xlabel ("values in x") ylabel ("density") ***** shared x1, df, d1 x1 = [-Inf, 2, NaN, 4, Inf]; df = [2, 0, -1, 1, 4]; d1 = [1, NaN, 3, -1, 2]; ***** assert (ncx2pdf (x1, df, d1), [0, NaN, NaN, NaN, 0]); ***** assert (ncx2pdf (x1, df, 1), [0, 0.07093996461786045, NaN, ... 0.06160064323277038, 0], 1e-14); ***** assert (ncx2pdf (x1, df, 3), [0, 0.1208364909271113, NaN, ... 0.09631299762429098, 0], 1e-14); ***** assert (ncx2pdf (x1, df, 2), [0, 0.1076346446244688, NaN, ... 0.08430464047296625, 0], 1e-14); ***** assert (ncx2pdf (x1, 2, d1), [0, NaN, NaN, NaN, 0]); ***** assert (ncx2pdf (2, df, d1), [0.1747201674611283, NaN, NaN, ... NaN, 0.1076346446244688], 1e-14); ***** assert (ncx2pdf (4, df, d1), [0.09355987820265799, NaN, NaN, ... NaN, 0.1192317192431485], 1e-14); ***** error ncx2pdf () ***** error ncx2pdf (1) ***** error ncx2pdf (1, 2) ***** error ... ncx2pdf (ones (3), ones (2), ones (2)) ***** error ... ncx2pdf (ones (2), ones (3), ones (2)) ***** error ... ncx2pdf (ones (2), ones (2), ones (3)) ***** error ncx2pdf (i, 2, 2) ***** error ncx2pdf (2, i, 2) ***** error ncx2pdf (2, 2, i) 16 tests, 16 passed, 0 known failure, 0 skipped [inst/dist_fun/logirnd.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/dist_fun/logirnd.m ***** assert (size (logirnd (1, 1)), [1 1]) ***** assert (size (logirnd (1, ones (2,1))), [2, 1]) ***** assert (size (logirnd (1, ones (2,2))), [2, 2]) ***** assert (size (logirnd (ones (2,1), 1)), [2, 1]) ***** assert (size (logirnd (ones (2,2), 1)), [2, 2]) ***** assert (size (logirnd (1, 1, 3)), [3, 3]) ***** assert (size (logirnd (1, 1, [4, 1])), [4, 1]) ***** assert (size (logirnd (1, 1, 4, 1)), [4, 1]) ***** assert (size (logirnd (1, 1, 4, 1, 5)), [4, 1, 5]) ***** assert (size (logirnd (1, 1, 0, 1)), [0, 1]) ***** assert (size (logirnd (1, 1, 1, 0)), [1, 0]) ***** assert (size (logirnd (1, 1, 1, 2, 0, 5)), [1, 2, 0, 5]) ***** assert (class (logirnd (1, 1)), "double") ***** assert (class (logirnd (1, single (1))), "single") ***** assert (class (logirnd (1, single ([1, 1]))), "single") ***** assert (class (logirnd (single (1), 1)), "single") ***** assert (class (logirnd (single ([1, 1]), 1)), "single") ***** error logirnd () ***** error logirnd (1) ***** error ... logirnd (ones (3), ones (2)) ***** error ... logirnd (ones (2), ones (3)) ***** error logirnd (i, 2, 3) ***** error logirnd (1, i, 3) ***** error ... logirnd (1, 2, -1) ***** error ... logirnd (1, 2, 1.2) ***** error ... logirnd (1, 2, ones (2)) ***** error ... logirnd (1, 2, [2 -1 2]) ***** error ... logirnd (1, 2, [2 0 2.5]) ***** error ... logirnd (1, 2, 2, -1, 5) ***** error ... logirnd (1, 2, 2, 1.5, 5) ***** error ... logirnd (2, ones (2), 3) ***** error ... logirnd (2, ones (2), [3, 2]) ***** error ... logirnd (2, ones (2), 3, 2) 33 tests, 33 passed, 0 known failure, 0 skipped [inst/dist_fun/fpdf.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/dist_fun/fpdf.m ***** demo ## Plot various PDFs from the F distribution x = 0.01:0.01:4; y1 = fpdf (x, 1, 1); y2 = fpdf (x, 2, 1); y3 = fpdf (x, 5, 2); y4 = fpdf (x, 10, 1); y5 = fpdf (x, 100, 100); plot (x, y1, "-b", x, y2, "-g", x, y3, "-r", x, y4, "-c", x, y5, "-m") grid on ylim ([0, 2.5]) legend ({"df1 = 1, df2 = 2", "df1 = 2, df2 = 1", ... "df1 = 5, df2 = 2", "df1 = 10, df2 = 1", ... "df1 = 100, df2 = 100"}, "location", "northeast") title ("F PDF") xlabel ("values in x") ylabel ("density") ***** shared x, y x = [-1 0 0.5 1 2]; y = [0 0 4/9 1/4 1/9]; ***** assert (fpdf (x, 2*ones (1,5), 2*ones (1,5)), y, eps) ***** assert (fpdf (x, 2, 2*ones (1,5)), y, eps) ***** assert (fpdf (x, 2*ones (1,5), 2), y, eps) ***** assert (fpdf (x, [0 NaN Inf 2 2], 2), [NaN NaN NaN y(4:5)], eps) ***** assert (fpdf (x, 2, [0 NaN Inf 2 2]), [NaN NaN NaN y(4:5)], eps) ***** assert (fpdf ([x, NaN], 2, 2), [y, NaN], eps) ***** test #F (x, 1, df1) == T distribution (sqrt (x), df1) / sqrt (x) rand ("seed", 1234); # for reproducibility xr = rand (10,1); xr = xr(x > 0.1 & x < 0.9); yr = tpdf (sqrt (xr), 2) ./ sqrt (xr); assert (fpdf (xr, 1, 2), yr, 5*eps); ***** assert (fpdf (single ([x, NaN]), 2, 2), single ([y, NaN]), eps ("single")) ***** assert (fpdf ([x, NaN], single (2), 2), single ([y, NaN]), eps ("single")) ***** assert (fpdf ([x, NaN], 2, single (2)), single ([y, NaN]), eps ("single")) ***** error fpdf () ***** error fpdf (1) ***** error fpdf (1,2) ***** error ... fpdf (ones (3), ones (2), ones (2)) ***** error ... fpdf (ones (2), ones (3), ones (2)) ***** error ... fpdf (ones (2), ones (2), ones (3)) ***** error fpdf (i, 2, 2) ***** error fpdf (2, i, 2) ***** error fpdf (2, 2, i) 19 tests, 19 passed, 0 known failure, 0 skipped [inst/dist_fun/chi2pdf.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/dist_fun/chi2pdf.m ***** demo ## Plot various PDFs from the chi-squared distribution x = 0:0.01:8; y1 = chi2pdf (x, 1); y2 = chi2pdf (x, 2); y3 = chi2pdf (x, 3); y4 = chi2pdf (x, 4); y5 = chi2pdf (x, 6); y6 = chi2pdf (x, 9); plot (x, y1, "-b", x, y2, "-g", x, y3, "-r", ... x, y4, "-c", x, y5, "-m", x, y6, "-y") grid on xlim ([0, 8]) ylim ([0, 0.5]) legend ({"df = 1", "df = 2", "df = 3", ... "df = 4", "df = 6", "df = 9"}, "location", "northeast") title ("Chi-squared PDF") xlabel ("values in x") ylabel ("density") ***** shared x, y x = [-1 0 0.5 1 Inf]; y = [0, 1/2 * exp(-x(2:5)/2)]; ***** assert (chi2pdf (x, 2*ones (1,5)), y) ***** assert (chi2pdf (x, 2), y) ***** assert (chi2pdf (x, 2*[1 0 NaN 1 1]), [y(1) NaN NaN y(4:5)]) ***** assert (chi2pdf ([x, NaN], 2), [y, NaN]) ***** assert (chi2pdf (single ([x, NaN]), 2), single ([y, NaN])) ***** assert (chi2pdf ([x, NaN], single (2)), single ([y, NaN])) ***** error chi2pdf () ***** error chi2pdf (1) ***** error chi2pdf (1,2,3) ***** error ... chi2pdf (ones (3), ones (2)) ***** error ... chi2pdf (ones (2), ones (3)) ***** error chi2pdf (i, 2) ***** error chi2pdf (2, i) 13 tests, 13 passed, 0 known failure, 0 skipped [inst/dist_fun/geoinv.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/dist_fun/geoinv.m ***** demo ## Plot various iCDFs from the geometric distribution p = 0.001:0.001:0.999; x1 = geoinv (p, 0.2); x2 = geoinv (p, 0.5); x3 = geoinv (p, 0.7); plot (p, x1, "-b", p, x2, "-g", p, x3, "-r") grid on ylim ([0, 10]) legend ({"ps = 0.2", "ps = 0.5", "ps = 0.7"}, "location", "northwest") title ("Geometric iCDF") xlabel ("probability") ylabel ("values in x (number of failures)") ***** shared p p = [-1 0 0.75 1 2]; ***** assert (geoinv (p, 0.5*ones (1,5)), [NaN 0 1 Inf NaN]) ***** assert (geoinv (p, 0.5), [NaN 0 1 Inf NaN]) ***** assert (geoinv (p, 0.5*[1 -1 NaN 4 1]), [NaN NaN NaN NaN NaN]) ***** assert (geoinv ([p(1:2) NaN p(4:5)], 0.5), [NaN 0 NaN Inf NaN]) ***** assert (geoinv ([p, NaN], 0.5), [NaN 0 1 Inf NaN NaN]) ***** assert (geoinv (single ([p, NaN]), 0.5), single ([NaN 0 1 Inf NaN NaN])) ***** assert (geoinv ([p, NaN], single (0.5)), single ([NaN 0 1 Inf NaN NaN])) ***** error geoinv () ***** error geoinv (1) ***** error ... geoinv (ones (3), ones (2)) ***** error ... geoinv (ones (2), ones (3)) ***** error ... geoinv (i, 2) ***** error ... geoinv (2, i) 13 tests, 13 passed, 0 known failure, 0 skipped [inst/dist_fun/triinv.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/dist_fun/triinv.m ***** demo ## Plot various iCDFs from the triangular distribution p = 0.001:0.001:0.999; x1 = triinv (p, 3, 6, 4); x2 = triinv (p, 1, 5, 2); x3 = triinv (p, 2, 9, 3); x4 = triinv (p, 2, 9, 5); plot (p, x1, "-b", p, x2, "-g", p, x3, "-r", p, x4, "-c") grid on ylim ([0, 10]) legend ({"a = 3, b = 6, c = 4", "a = 1, b = 5, c = 2", ... "a = 2, b = 9, c = 3", "a = 2, b = 9, c = 5"}, ... "location", "northwest") title ("Triangular CDF") xlabel ("probability") ylabel ("values in x") ***** shared p, y p = [-1, 0, 0.02, 0.5, 0.98, 1, 2]; y = [NaN, 0, 0.1, 0.5, 0.9, 1, NaN] + 1; ***** assert (triinv (p, ones (1, 7), 1.5 * ones (1, 7), 2 * ones (1, 7)), y, eps) ***** assert (triinv (p, 1 * ones (1, 7), 1.5, 2), y, eps) ***** assert (triinv (p, 1, 1.5, 2 * ones (1, 7)), y, eps) ***** assert (triinv (p, 1, 1.5*ones (1,7), 2), y, eps) ***** assert (triinv (p, 1, 1.5, 2), y, eps) ***** assert (triinv (p, [1, 1, NaN, 1, 1, 1, 1], 1.5, 2), [y(1:2), NaN, y(4:7)], eps) ***** assert (triinv (p, 1, 1.5 * [1, 1, NaN, 1, 1, 1, 1], 2), [y(1:2), NaN, y(4:7)], eps) ***** assert (triinv (p, 1, 1.5, 2 * [1, 1, NaN, 1, 1, 1, 1]), [y(1:2), NaN, y(4:7)], eps) ***** assert (triinv ([p, NaN], 1, 1.5, 2), [y, NaN], eps) ***** assert (triinv (single ([p, NaN]), 1, 1.5, 2), single ([y, NaN]), eps('single')) ***** assert (triinv ([p, NaN], single (1), 1.5, 2), single ([y, NaN]), eps('single')) ***** assert (triinv ([p, NaN], 1, single (1.5), 2), single ([y, NaN]), eps('single')) ***** assert (triinv ([p, NaN], 1, 1.5, single (2)), single ([y, NaN]), eps('single')) ***** error triinv () ***** error triinv (1) ***** error triinv (1, 2) ***** error triinv (1, 2, 3) ***** error ... triinv (1, 2, 3, 4, 5) ***** error ... triinv (ones (3), ones (2), ones(2), ones(2)) ***** error ... triinv (ones (2), ones (3), ones(2), ones(2)) ***** error ... triinv (ones (2), ones (2), ones(3), ones(2)) ***** error ... triinv (ones (2), ones (2), ones(2), ones(3)) ***** error triinv (i, 2, 3, 4) ***** error triinv (1, i, 3, 4) ***** error triinv (1, 2, i, 4) ***** error triinv (1, 2, 3, i) 26 tests, 26 passed, 0 known failure, 0 skipped [inst/dist_fun/normrnd.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/dist_fun/normrnd.m ***** assert (size (normrnd (1, 1)), [1 1]) ***** assert (size (normrnd (1, ones (2,1))), [2, 1]) ***** assert (size (normrnd (1, ones (2,2))), [2, 2]) ***** assert (size (normrnd (ones (2,1), 1)), [2, 1]) ***** assert (size (normrnd (ones (2,2), 1)), [2, 2]) ***** assert (size (normrnd (1, 1, 3)), [3, 3]) ***** assert (size (normrnd (1, 1, [4, 1])), [4, 1]) ***** assert (size (normrnd (1, 1, 4, 1)), [4, 1]) ***** assert (size (normrnd (1, 1, 4, 1, 5)), [4, 1, 5]) ***** assert (size (normrnd (1, 1, 0, 1)), [0, 1]) ***** assert (size (normrnd (1, 1, 1, 0)), [1, 0]) ***** assert (size (normrnd (1, 1, 1, 2, 0, 5)), [1, 2, 0, 5]) ***** assert (class (normrnd (1, 1)), "double") ***** assert (class (normrnd (1, single (1))), "single") ***** assert (class (normrnd (1, single ([1, 1]))), "single") ***** assert (class (normrnd (single (1), 1)), "single") ***** assert (class (normrnd (single ([1, 1]), 1)), "single") ***** error normrnd () ***** error normrnd (1) ***** error ... normrnd (ones (3), ones (2)) ***** error ... normrnd (ones (2), ones (3)) ***** error normrnd (i, 2, 3) ***** error normrnd (1, i, 3) ***** error ... normrnd (1, 2, -1) ***** error ... normrnd (1, 2, 1.2) ***** error ... normrnd (1, 2, ones (2)) ***** error ... normrnd (1, 2, [2 -1 2]) ***** error ... normrnd (1, 2, [2 0 2.5]) ***** error ... normrnd (1, 2, 2, -1, 5) ***** error ... normrnd (1, 2, 2, 1.5, 5) ***** error ... normrnd (2, ones (2), 3) ***** error ... normrnd (2, ones (2), [3, 2]) ***** error ... normrnd (2, ones (2), 3, 2) 33 tests, 33 passed, 0 known failure, 0 skipped [inst/dist_fun/ncfcdf.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/dist_fun/ncfcdf.m ***** demo ## Plot various CDFs from the noncentral F distribution x = 0:0.01:5; p1 = ncfcdf (x, 2, 5, 1); p2 = ncfcdf (x, 2, 5, 2); p3 = ncfcdf (x, 5, 10, 1); p4 = ncfcdf (x, 10, 20, 10); plot (x, p1, "-r", x, p2, "-g", x, p3, "-k", x, p4, "-m") grid on xlim ([0, 5]) legend ({"df1 = 2, df2 = 5, λ = 1", "df1 = 2, df2 = 5, λ = 2", ... "df1 = 5, df2 = 10, λ = 1", "df1 = 10, df2 = 20, λ = 10"}, ... "location", "southeast") title ("Noncentral F CDF") xlabel ("values in x") ylabel ("probability") ***** demo ## Compare the noncentral F CDF with LAMBDA = 10 to the F CDF with the ## same number of numerator and denominator degrees of freedom (5, 20) x = 0.01:0.1:10.01; p1 = ncfcdf (x, 5, 20, 10); p2 = fcdf (x, 5, 20); plot (x, p1, "-", x, p2, "-"); grid on xlim ([0, 10]) legend ({"Noncentral F(5,20,10)", "F(5,20)"}, "location", "southeast") title ("Noncentral F vs F CDFs") xlabel ("values in x") ylabel ("probability") ***** test x = -2:0.1:2; p = ncfcdf (x, 10, 1, 3); assert (p([1:21]), zeros (1, 21), 1e-76); assert (p(22), 0.004530737275319753, 1e-14); assert (p(30), 0.255842099135669, 1e-14); assert (p(41), 0.4379890998457305, 1e-14); ***** test p = ncfcdf (12, 10, 3, 2); assert (p, 0.9582287900447416, 1e-14); ***** test p = ncfcdf (2, 3, 2, 1); assert (p, 0.5731985522994989, 1e-14); ***** test p = ncfcdf (2, 3, 2, 1, "upper"); assert (p, 0.4268014477004823, 1e-14); ***** test p = ncfcdf ([3, 6], 3, 2, 5, "upper"); assert (p, [0.530248523596927, 0.3350482341323044], 1e-14); ***** error ncfcdf () ***** error ncfcdf (1) ***** error ncfcdf (1, 2) ***** error ncfcdf (1, 2, 3) ***** error ncfcdf (1, 2, 3, 4, "tail") ***** error ncfcdf (1, 2, 3, 4, 5) ***** error ... ncfcdf (ones (3), ones (2), ones (2), ones (2)) ***** error ... ncfcdf (ones (2), ones (3), ones (2), ones (2)) ***** error ... ncfcdf (ones (2), ones (2), ones (3), ones (2)) ***** error ... ncfcdf (ones (2), ones (2), ones (2), ones (3)) ***** error ncfcdf (i, 2, 2, 2) ***** error ncfcdf (2, i, 2, 2) ***** error ncfcdf (2, 2, i, 2) ***** error ncfcdf (2, 2, 2, i) 19 tests, 19 passed, 0 known failure, 0 skipped [inst/dist_fun/mvnpdf.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/dist_fun/mvnpdf.m ***** demo mu = [1, -1]; sigma = [0.9, 0.4; 0.4, 0.3]; [X1, X2] = meshgrid (linspace (-1, 3, 25)', linspace (-3, 1, 25)'); x = [X1(:), X2(:)]; p = mvnpdf (x, mu, sigma); surf (X1, X2, reshape (p, 25, 25)); ***** error y = mvnpdf (); ***** error y = mvnpdf ([]); ***** error y = mvnpdf (ones (3,3,3)); ***** error ... y = mvnpdf (ones (10, 2), [4, 2, 3]); ***** error ... y = mvnpdf (ones (10, 2), [4, 2; 3, 2]); ***** error ... y = mvnpdf (ones (10, 2), ones (3, 3, 3)); ***** shared x, mu, sigma x = [1, 2, 5, 4, 6]; mu = [2, 0, -1, 1, 4]; sigma = [2, 2, 2, 2, 2]; ***** assert (mvnpdf (x), 1.579343404440977e-20, 1e-30); ***** assert (mvnpdf (x, mu), 1.899325144348102e-14, 1e-25); ***** assert (mvnpdf (x, mu, sigma), 2.449062307156273e-09, 1e-20); 9 tests, 9 passed, 0 known failure, 0 skipped [inst/dist_fun/wblinv.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/dist_fun/wblinv.m ***** demo ## Plot various iCDFs from the Weibull distribution p = 0.001:0.001:0.999; x1 = wblinv (p, 1, 0.5); x2 = wblinv (p, 1, 1); x3 = wblinv (p, 1, 1.5); x4 = wblinv (p, 1, 5); plot (p, x1, "-b", p, x2, "-r", p, x3, "-m", p, x4, "-g") ylim ([0, 2.5]) grid on legend ({"λ = 1, k = 0.5", "λ = 1, k = 1", ... "λ = 1, k = 1.5", "λ = 1, k = 5"}, "location", "northwest") title ("Weibull iCDF") xlabel ("probability") ylabel ("x") ***** shared p p = [-1 0 0.63212055882855778 1 2]; ***** assert (wblinv (p, ones (1,5), ones (1,5)), [NaN 0 1 Inf NaN], eps) ***** assert (wblinv (p, 1, ones (1,5)), [NaN 0 1 Inf NaN], eps) ***** assert (wblinv (p, ones (1,5), 1), [NaN 0 1 Inf NaN], eps) ***** assert (wblinv (p, [1 -1 NaN Inf 1], 1), [NaN NaN NaN NaN NaN]) ***** assert (wblinv (p, 1, [1 -1 NaN Inf 1]), [NaN NaN NaN NaN NaN]) ***** assert (wblinv ([p(1:2) NaN p(4:5)], 1, 1), [NaN 0 NaN Inf NaN]) ***** assert (wblinv ([p, NaN], 1, 1), [NaN 0 1 Inf NaN NaN], eps) ***** assert (wblinv (single ([p, NaN]), 1, 1), single ([NaN 0 1 Inf NaN NaN]), eps ("single")) ***** assert (wblinv ([p, NaN], single (1), 1), single ([NaN 0 1 Inf NaN NaN]), eps ("single")) ***** assert (wblinv ([p, NaN], 1, single (1)), single ([NaN 0 1 Inf NaN NaN]), eps ("single")) ***** error wblinv () ***** error wblinv (1,2,3,4) ***** error ... wblinv (ones (3), ones (2), ones (2)) ***** error ... wblinv (ones (2), ones (3), ones (2)) ***** error ... wblinv (ones (2), ones (2), ones (3)) ***** error wblinv (i, 2, 2) ***** error wblinv (2, i, 2) ***** error wblinv (2, 2, i) 18 tests, 18 passed, 0 known failure, 0 skipped [inst/dist_fun/raylpdf.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/dist_fun/raylpdf.m ***** demo ## Plot various PDFs from the Rayleigh distribution x = 0:0.01:10; y1 = raylpdf (x, 0.5); y2 = raylpdf (x, 1); y3 = raylpdf (x, 2); y4 = raylpdf (x, 3); y5 = raylpdf (x, 4); plot (x, y1, "-b", x, y2, "g", x, y3, "-r", x, y4, "-m", x, y5, "-k") grid on ylim ([0, 1.25]) legend ({"σ = 0,5", "σ = 1", "σ = 2", ... "σ = 3", "σ = 4"}, "location", "northeast") title ("Rayleigh PDF") xlabel ("values in x") ylabel ("density") ***** test x = 0:0.5:2.5; sigma = 1:6; y = raylpdf (x, sigma); expected_y = [0.0000, 0.1212, 0.1051, 0.0874, 0.0738, 0.0637]; assert (y, expected_y, 0.001); ***** test x = 0:0.5:2.5; y = raylpdf (x, 0.5); expected_y = [0.0000, 1.2131, 0.5413, 0.0667, 0.0027, 0.0000]; assert (y, expected_y, 0.001); ***** error raylpdf () ***** error raylpdf (1) ***** error ... raylpdf (ones (3), ones (2)) ***** error ... raylpdf (ones (2), ones (3)) ***** error raylpdf (i, 2) ***** error raylpdf (2, i) 8 tests, 8 passed, 0 known failure, 0 skipped [inst/dist_fun/gprnd.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/dist_fun/gprnd.m ***** assert (size (gprnd (0, 1, 0)), [1, 1]) ***** assert (size (gprnd (0, 1, zeros (2,1))), [2, 1]) ***** assert (size (gprnd (0, 1, zeros (2,2))), [2, 2]) ***** assert (size (gprnd (0, ones (2,1), 0)), [2, 1]) ***** assert (size (gprnd (0, ones (2,2), 0)), [2, 2]) ***** assert (size (gprnd (zeros (2,1), 1, 0)), [2, 1]) ***** assert (size (gprnd (zeros (2,2), 1, 0)), [2, 2]) ***** assert (size (gprnd (0, 1, 0, 3)), [3, 3]) ***** assert (size (gprnd (0, 1, 0, [4 1])), [4, 1]) ***** assert (size (gprnd (0, 1, 0, 4, 1)), [4, 1]) ***** assert (size (gprnd (1,1,0)), [1, 1]) ***** assert (size (gprnd (1, 1, zeros (2,1))), [2, 1]) ***** assert (size (gprnd (1, 1, zeros (2,2))), [2, 2]) ***** assert (size (gprnd (1, ones (2,1), 0)), [2, 1]) ***** assert (size (gprnd (1, ones (2,2), 0)), [2, 2]) ***** assert (size (gprnd (ones (2,1), 1, 0)), [2, 1]) ***** assert (size (gprnd (ones (2,2), 1, 0)), [2, 2]) ***** assert (size (gprnd (1, 1, 0, 3)), [3, 3]) ***** assert (size (gprnd (1, 1, 0, [4 1])), [4, 1]) ***** assert (size (gprnd (1, 1, 0, 4, 1)), [4, 1]) ***** assert (size (gprnd (-1, 1, 0)), [1, 1]) ***** assert (size (gprnd (-1, 1, zeros (2,1))), [2, 1]) ***** assert (size (gprnd (1, -1, zeros (2,2))), [2, 2]) ***** assert (size (gprnd (-1, ones (2,1), 0)), [2, 1]) ***** assert (size (gprnd (-1, ones (2,2), 0)), [2, 2]) ***** assert (size (gprnd (-ones (2,1), 1, 0)), [2, 1]) ***** assert (size (gprnd (-ones (2,2), 1, 0)), [2, 2]) ***** assert (size (gprnd (-1, 1, 0, 3)), [3, 3]) ***** assert (size (gprnd (-1, 1, 0, [4, 1])), [4, 1]) ***** assert (size (gprnd (-1, 1, 0, 4, 1)), [4, 1]) ***** assert (class (gprnd (0, 1, 0)), "double") ***** assert (class (gprnd (0, 1, single (0))), "single") ***** assert (class (gprnd (0, 1, single ([0, 0]))), "single") ***** assert (class (gprnd (0, single (1),0)), "single") ***** assert (class (gprnd (0, single ([1, 1]),0)), "single") ***** assert (class (gprnd (single (0), 1, 0)), "single") ***** assert (class (gprnd (single ([0, 0]), 1, 0)), "single") ***** error gprnd () ***** error gprnd (1) ***** error gprnd (1, 2) ***** error ... gprnd (ones (3), ones (2), ones (2)) ***** error ... gprnd (ones (2), ones (3), ones (2)) ***** error ... gprnd (ones (2), ones (2), ones (3)) ***** error gprnd (i, 2, 3) ***** error gprnd (1, i, 3) ***** error gprnd (1, 2, i) ***** error ... gprnd (1, 2, 3, -1) ***** error ... gprnd (1, 2, 3, 1.2) ***** error ... gprnd (1, 2, 3, ones (2)) ***** error ... gprnd (1, 2, 3, [2 -1 2]) ***** error ... gprnd (1, 2, 3, [2 0 2.5]) ***** error ... gprnd (1, 2, 3, 2, -1, 5) ***** error ... gprnd (1, 2, 3, 2, 1.5, 5) ***** error ... gprnd (2, ones (2), 2, 3) ***** error ... gprnd (2, ones (2), 2, [3, 2]) ***** error ... gprnd (2, ones (2), 2, 3, 2) 56 tests, 56 passed, 0 known failure, 0 skipped [inst/dist_fun/iwishpdf.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/dist_fun/iwishpdf.m ***** assert(iwishpdf(4, 3, 3.1), 0.04226595, 1E-7); ***** assert(iwishpdf([2 -0.3;-0.3 4], [1 0.3;0.3 1], 4), 1.60166e-05, 1E-10); ***** assert(iwishpdf([6 2 5; 2 10 -5; 5 -5 25], ... [9 5 5; 5 10 -8; 5 -8 22], 5.1), 4.946831e-12, 1E-17); ***** error iwishpdf () ***** error iwishpdf (1, 2) ***** error iwishpdf (1, 2, 0) 6 tests, 6 passed, 0 known failure, 0 skipped [inst/dist_fun/invgrnd.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/dist_fun/invgrnd.m ***** assert (size (invgrnd (1, 1, 1)), [1, 1]) ***** assert (size (invgrnd (1, 1, 2)), [2, 2]) ***** assert (size (invgrnd (1, 1, [2, 1])), [2, 1]) ***** assert (size (invgrnd (1, zeros (2, 2))), [2, 2]) ***** assert (size (invgrnd (1, ones (2, 1))), [2, 1]) ***** assert (size (invgrnd (1, ones (2, 2))), [2, 2]) ***** assert (size (invgrnd (ones (2, 1), 1)), [2, 1]) ***** assert (size (invgrnd (ones (2, 2), 1)), [2, 2]) ***** assert (size (invgrnd (1, 1, 3)), [3, 3]) ***** assert (size (invgrnd (1, 1, [4 1])), [4, 1]) ***** assert (size (invgrnd (1, 1, 4, 1)), [4, 1]) ***** test r = invgrnd (1, [1, 0, -1]); assert (r([2:3]), [NaN, NaN]) ***** assert (class (invgrnd (1, 0)), "double") ***** assert (class (invgrnd (1, single (0))), "single") ***** assert (class (invgrnd (1, single ([0 0]))), "single") ***** assert (class (invgrnd (1, single (1))), "single") ***** assert (class (invgrnd (1, single ([1 1]))), "single") ***** assert (class (invgrnd (single (1), 1)), "single") ***** assert (class (invgrnd (single ([1 1]), 1)), "single") ***** error invgrnd () ***** error invgrnd (1) ***** error ... invgrnd (ones (3), ones (2)) ***** error ... invgrnd (ones (2), ones (3)) ***** error invgrnd (i, 2, 3) ***** error invgrnd (1, i, 3) ***** error ... invgrnd (1, 2, -1) ***** error ... invgrnd (1, 2, 1.2) ***** error ... invgrnd (1, 2, ones (2)) ***** error ... invgrnd (1, 2, [2 -1 2]) ***** error ... invgrnd (1, 2, [2 0 2.5]) ***** error ... invgrnd (1, 2, 2, -1, 5) ***** error ... invgrnd (1, 2, 2, 1.5, 5) ***** error ... invgrnd (2, ones (2), 3) ***** error ... invgrnd (2, ones (2), [3, 2]) ***** error ... invgrnd (2, ones (2), 3, 2) 35 tests, 35 passed, 0 known failure, 0 skipped [inst/dist_fun/nctpdf.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/dist_fun/nctpdf.m ***** demo ## Plot various PDFs from the noncentral T distribution x = -5:0.01:10; y1 = nctpdf (x, 1, 0); y2 = nctpdf (x, 4, 0); y3 = nctpdf (x, 1, 2); y4 = nctpdf (x, 4, 2); plot (x, y1, "-r", x, y2, "-g", x, y3, "-k", x, y4, "-m") grid on xlim ([-5, 10]) ylim ([0, 0.4]) legend ({"df = 1, μ = 0", "df = 4, μ = 0", ... "df = 1, μ = 2", "df = 4, μ = 2"}, "location", "northeast") title ("Noncentral T PDF") xlabel ("values in x") ylabel ("density") ***** demo ## Compare the noncentral T PDF with MU = 1 to the T PDF ## with the same number of degrees of freedom (10). x = -5:0.1:5; y1 = nctpdf (x, 10, 1); y2 = tpdf (x, 10); plot (x, y1, "-", x, y2, "-"); grid on xlim ([-5, 5]) ylim ([0, 0.4]) legend ({"Noncentral χ^2(4,2)", "χ^2(4)"}, "location", "northwest") title ("Noncentral T vs T PDFs") xlabel ("values in x") ylabel ("density") ***** shared x1, df, mu x1 = [-Inf, 2, NaN, 4, Inf]; df = [2, 0, -1, 1, 4]; mu = [1, NaN, 3, -1, 2]; ***** assert (nctpdf (x1, df, mu), [0, NaN, NaN, 0.00401787561306999, 0], 1e-14); ***** assert (nctpdf (x1, df, 1), [0, NaN, NaN, 0.0482312135423008, 0], 1e-14); ***** assert (nctpdf (x1, df, 3), [0, NaN, NaN, 0.1048493126401585, 0], 1e-14); ***** assert (nctpdf (x1, df, 2), [0, NaN, NaN, 0.08137377919890307, 0], 1e-14); ***** assert (nctpdf (x1, 3, mu), [0, NaN, NaN, 0.001185305171654381, 0], 1e-14); ***** assert (nctpdf (2, df, mu), [0.1791097459405861, NaN, NaN, ... 0.0146500727180389, 0.3082302682110299], 1e-14); ***** assert (nctpdf (4, df, mu), [0.04467929612254971, NaN, NaN, ... 0.00401787561306999, 0.0972086534042828], 1e-14); ***** error nctpdf () ***** error nctpdf (1) ***** error nctpdf (1, 2) ***** error ... nctpdf (ones (3), ones (2), ones (2)) ***** error ... nctpdf (ones (2), ones (3), ones (2)) ***** error ... nctpdf (ones (2), ones (2), ones (3)) ***** error nctpdf (i, 2, 2) ***** error nctpdf (2, i, 2) ***** error nctpdf (2, 2, i) 16 tests, 16 passed, 0 known failure, 0 skipped [inst/dist_fun/copulacdf.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/dist_fun/copulacdf.m ***** test x = [0.2:0.2:0.6; 0.2:0.2:0.6]; theta = [1; 2]; p = copulacdf ("Clayton", x, theta); expected_p = [0.1395; 0.1767]; assert (p, expected_p, 0.001); ***** test x = [0.2:0.2:0.6; 0.2:0.2:0.6]; p = copulacdf ("Gumbel", x, 2); expected_p = [0.1464; 0.1464]; assert (p, expected_p, 0.001); ***** test x = [0.2:0.2:0.6; 0.2:0.2:0.6]; theta = [1; 2]; p = copulacdf ("Frank", x, theta); expected_p = [0.0699; 0.0930]; assert (p, expected_p, 0.001); ***** test x = [0.2:0.2:0.6; 0.2:0.2:0.6]; theta = [0.3; 0.7]; p = copulacdf ("AMH", x, theta); expected_p = [0.0629; 0.0959]; assert (p, expected_p, 0.001); ***** test x = [0.2:0.2:0.6; 0.2:0.1:0.4]; theta = [0.2, 0.1, 0.1, 0.05]; p = copulacdf ("FGM", x, theta); expected_p = [0.0558; 0.0293]; assert (p, expected_p, 0.001); 5 tests, 5 passed, 0 known failure, 0 skipped [inst/dist_fun/ncfinv.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/dist_fun/ncfinv.m ***** demo ## Plot various iCDFs from the noncentral F distribution p = 0.001:0.001:0.999; x1 = ncfinv (p, 2, 5, 1); x2 = ncfinv (p, 2, 5, 2); x3 = ncfinv (p, 5, 10, 1); x4 = ncfinv (p, 10, 20, 10); plot (p, x1, "-r", p, x2, "-g", p, x3, "-k", p, x4, "-m") grid on ylim ([0, 5]) legend ({"df1 = 2, df2 = 5, λ = 1", "df1 = 2, df2 = 5, λ = 2", ... "df1 = 5, df2 = 10, λ = 1", "df1 = 10, df2 = 20, λ = 10"}, ... "location", "northwest") title ("Noncentral F iCDF") xlabel ("probability") ylabel ("values in x") ***** demo ## Compare the noncentral F iCDF with LAMBDA = 10 to the F iCDF with the ## same number of numerator and denominator degrees of freedom (5, 20) p = 0.001:0.001:0.999; x1 = ncfinv (p, 5, 20, 10); x2 = finv (p, 5, 20); plot (p, x1, "-", p, x2, "-"); grid on ylim ([0, 10]) legend ({"Noncentral F(5,20,10)", "F(5,20)"}, "location", "northwest") title ("Noncentral F vs F quantile functions") xlabel ("probability") ylabel ("values in x") ***** test x = [0,0.1775,0.3864,0.6395,0.9564,1.3712,1.9471,2.8215,4.3679,8.1865,Inf]; assert (ncfinv ([0:0.1:1], 2, 3, 1), x, 1e-4); ***** test x = [0,0.7492,1.3539,2.0025,2.7658,3.7278,5.0324,6.9826,10.3955,18.7665,Inf]; assert (ncfinv ([0:0.1:1], 2, 3, 5), x, 1e-4); ***** test x = [0,0.2890,0.8632,1.5653,2.4088,3.4594,4.8442,6.8286,10.0983,17.3736,Inf]; assert (ncfinv ([0:0.1:1], 1, 4, 3), x, 1e-4); ***** test x = [0.078410, 0.212716, 0.288618, 0.335752, 0.367963, 0.391460]; assert (ncfinv (0.05, [1, 2, 3, 4, 5, 6], 10, 3), x, 1e-6); ***** test x = [0.2574, 0.2966, 0.3188, 0.3331, 0.3432, 0.3507]; assert (ncfinv (0.05, 5, [1, 2, 3, 4, 5, 6], 3), x, 1e-4); ***** test x = [1.6090, 1.8113, 1.9215, 1.9911, NaN, 2.0742]; assert (ncfinv (0.05, 1, [1, 2, 3, 4, -1, 6], 10), x, 1e-4); ***** test assert (ncfinv (0.996, 3, 5, 8), 58.0912074080671, 2e-13); ***** error ncfinv () ***** error ncfinv (1) ***** error ncfinv (1, 2) ***** error ncfinv (1, 2, 3) ***** error ... ncfinv (ones (3), ones (2), ones (2), ones (2)) ***** error ... ncfinv (ones (2), ones (3), ones (2), ones (2)) ***** error ... ncfinv (ones (2), ones (2), ones (3), ones (2)) ***** error ... ncfinv (ones (2), ones (2), ones (2), ones (3)) ***** error ncfinv (i, 2, 2, 2) ***** error ncfinv (2, i, 2, 2) ***** error ncfinv (2, 2, i, 2) ***** error ncfinv (2, 2, 2, i) 19 tests, 19 passed, 0 known failure, 0 skipped [inst/dist_fun/laplaceinv.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/dist_fun/laplaceinv.m ***** demo ## Plot various iCDFs from the Laplace distribution p = 0.001:0.001:0.999; x1 = cauchyinv (p, 0, 1); x2 = cauchyinv (p, 0, 2); x3 = cauchyinv (p, 0, 4); x4 = cauchyinv (p, -5, 4); plot (p, x1, "-b", p, x2, "-g", p, x3, "-r", p, x4, "-c") grid on ylim ([-10, 10]) legend ({"μ = 0, β = 1", "μ = 0, β = 2", ... "μ = 0, β = 4", "μ = -5, β = 4"}, "location", "northwest") title ("Laplace iCDF") xlabel ("probability") ylabel ("values in x") ***** shared p, x p = [-1 0 0.5 1 2]; x = [NaN, -Inf, 0, Inf, NaN]; ***** assert (laplaceinv (p, 0, 1), x) ***** assert (laplaceinv (p, 0, [-2, -1, 0, 1, 2]), [nan(1, 3), Inf, NaN]) ***** assert (laplaceinv ([p, NaN], 0, 1), [x, NaN]) ***** assert (laplaceinv (single ([p, NaN]), 0, 1), single ([x, NaN])) ***** assert (laplaceinv ([p, NaN], single (0), 1), single ([x, NaN])) ***** assert (laplaceinv ([p, NaN], 0, single (1)), single ([x, NaN])) ***** error laplaceinv () ***** error laplaceinv (1) ***** error ... laplaceinv (1, 2) ***** error laplaceinv (1, 2, 3, 4) ***** error ... laplaceinv (1, ones (2), ones (3)) ***** error ... laplaceinv (ones (2), 1, ones (3)) ***** error ... laplaceinv (ones (2), ones (3), 1) ***** error laplaceinv (i, 2, 3) ***** error laplaceinv (1, i, 3) ***** error laplaceinv (1, 2, i) 16 tests, 16 passed, 0 known failure, 0 skipped [inst/dist_fun/iwishrnd.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/dist_fun/iwishrnd.m ***** assert(size (iwishrnd (1,2,1)), [1, 1]); ***** assert(size (iwishrnd ([],2,1)), [1, 1]); ***** assert(size (iwishrnd ([3 1; 1 3], 2.00001, [], 1)), [2, 2]); ***** assert(size (iwishrnd (eye(2), 2, [], 3)), [2, 2, 3]); ***** error iwishrnd () ***** error iwishrnd (1) ***** error iwishrnd ([-3 1; 1 3],1) ***** error iwishrnd ([1; 1],1) 8 tests, 8 passed, 0 known failure, 0 skipped [inst/dist_fun/normcdf.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/dist_fun/normcdf.m ***** demo ## Plot various CDFs from the normal distribution x = -5:0.01:5; p1 = normcdf (x, 0, 0.5); p2 = normcdf (x, 0, 1); p3 = normcdf (x, 0, 2); p4 = normcdf (x, -2, 0.8); plot (x, p1, "-b", x, p2, "-g", x, p3, "-r", x, p4, "-c") grid on xlim ([-5, 5]) legend ({"μ = 0, σ = 0.5", "μ = 0, σ = 1", ... "μ = 0, σ = 2", "μ = -2, σ = 0.8"}, "location", "southeast") title ("Normal CDF") xlabel ("values in x") ylabel ("probability") ***** shared x, y x = [-Inf 1 2 Inf]; y = [0, 0.5, 1/2*(1+erf(1/sqrt(2))), 1]; ***** assert (normcdf (x, ones (1,4), ones (1,4)), y) ***** assert (normcdf (x, 1, ones (1,4)), y) ***** assert (normcdf (x, ones (1,4), 1), y) ***** assert (normcdf (x, [0, -Inf, NaN, Inf], 1), [0, 1, NaN, NaN]) ***** assert (normcdf (x, 1, [Inf, NaN, -1, 0]), [NaN, NaN, NaN, 1]) ***** assert (normcdf ([x(1:2), NaN, x(4)], 1, 1), [y(1:2), NaN, y(4)]) ***** assert (normcdf (x, "upper"), [1, 0.1587, 0.0228, 0], 1e-4) ***** assert (normcdf ([x, NaN], 1, 1), [y, NaN]) ***** assert (normcdf (single ([x, NaN]), 1, 1), single ([y, NaN]), eps ("single")) ***** assert (normcdf ([x, NaN], single (1), 1), single ([y, NaN]), eps ("single")) ***** assert (normcdf ([x, NaN], 1, single (1)), single ([y, NaN]), eps ("single")) ***** error normcdf () ***** error normcdf (1,2,3,4,5,6,7) ***** error normcdf (1, 2, 3, 4, "uper") ***** error ... normcdf (ones (3), ones (2), ones (2)) ***** error normcdf (2, 3, 4, [1, 2]) ***** error ... [p, plo, pup] = normcdf (1, 2, 3) ***** error [p, plo, pup] = ... normcdf (1, 2, 3, [1, 0; 0, 1], 0) ***** error [p, plo, pup] = ... normcdf (1, 2, 3, [1, 0; 0, 1], 1.22) ***** error [p, plo, pup] = ... normcdf (1, 2, 3, [1, 0; 0, 1], "alpha", "upper") ***** error normcdf (i, 2, 2) ***** error normcdf (2, i, 2) ***** error normcdf (2, 2, i) ***** error ... [p, plo, pup] =normcdf (1, 2, 3, [1, 0; 0, -inf], 0.04) 24 tests, 24 passed, 0 known failure, 0 skipped [inst/dist_fun/chi2inv.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/dist_fun/chi2inv.m ***** demo ## Plot various iCDFs from the chi-squared distribution p = 0.001:0.001:0.999; x1 = chi2inv (p, 1); x2 = chi2inv (p, 2); x3 = chi2inv (p, 3); x4 = chi2inv (p, 4); x5 = chi2inv (p, 6); x6 = chi2inv (p, 9); plot (p, x1, "-b", p, x2, "-g", p, x3, "-r", ... p, x4, "-c", p, x5, "-m", p, x6, "-y") grid on ylim ([0, 8]) legend ({"df = 1", "df = 2", "df = 3", ... "df = 4", "df = 6", "df = 9"}, "location", "northwest") title ("Chi-squared iCDF") xlabel ("probability") ylabel ("values in x") ***** shared p p = [-1 0 0.3934693402873666 1 2]; ***** assert (chi2inv (p, 2*ones (1,5)), [NaN 0 1 Inf NaN], 5*eps) ***** assert (chi2inv (p, 2), [NaN 0 1 Inf NaN], 5*eps) ***** assert (chi2inv (p, 2*[0 1 NaN 1 1]), [NaN 0 NaN Inf NaN], 5*eps) ***** assert (chi2inv ([p(1:2) NaN p(4:5)], 2), [NaN 0 NaN Inf NaN], 5*eps) ***** assert (chi2inv ([p, NaN], 2), [NaN 0 1 Inf NaN NaN], 5*eps) ***** assert (chi2inv (single ([p, NaN]), 2), single ([NaN 0 1 Inf NaN NaN]), 5*eps ("single")) ***** assert (chi2inv ([p, NaN], single (2)), single ([NaN 0 1 Inf NaN NaN]), 5*eps ("single")) ***** error chi2inv () ***** error chi2inv (1) ***** error chi2inv (1,2,3) ***** error ... chi2inv (ones (3), ones (2)) ***** error ... chi2inv (ones (2), ones (3)) ***** error chi2inv (i, 2) ***** error chi2inv (2, i) 14 tests, 14 passed, 0 known failure, 0 skipped [inst/dist_fun/expinv.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/dist_fun/expinv.m ***** demo ## Plot various iCDFs from the exponential distribution p = 0.001:0.001:0.999; x1 = expinv (p, 2/3); x2 = expinv (p, 1.0); x3 = expinv (p, 2.0); plot (p, x1, "-b", p, x2, "-g", p, x3, "-r") grid on ylim ([0, 5]) legend ({"μ = 2/3", "μ = 1", "μ = 2"}, "location", "northwest") title ("Exponential iCDF") xlabel ("probability") ylabel ("values in x") ***** shared p p = [-1 0 0.3934693402873666 1 2]; ***** assert (expinv (p, 2*ones (1,5)), [NaN 0 1 Inf NaN], eps) ***** assert (expinv (p, 2), [NaN 0 1 Inf NaN], eps) ***** assert (expinv (p, 2*[1 0 NaN 1 1]), [NaN NaN NaN Inf NaN], eps) ***** assert (expinv ([p(1:2) NaN p(4:5)], 2), [NaN 0 NaN Inf NaN], eps) ***** assert (expinv ([p, NaN], 2), [NaN 0 1 Inf NaN NaN], eps) ***** assert (expinv (single ([p, NaN]), 2), single ([NaN 0 1 Inf NaN NaN]), eps) ***** assert (expinv ([p, NaN], single (2)), single ([NaN 0 1 Inf NaN NaN]), eps) ***** error expinv () ***** error expinv (1, 2 ,3 ,4 ,5) ***** error ... expinv (ones (3), ones (2)) ***** error ... expinv (2, 3, [1, 2]) ***** error ... [x, xlo, xup] = expinv (1, 2) ***** error [x, xlo, xup] = ... expinv (1, 2, 3, 0) ***** error [x, xlo, xup] = ... expinv (1, 2, 3, 1.22) ***** error [x, xlo, xup] = ... expinv (1, 2, 3, [0.05, 0.1]) ***** error expinv (i, 2) ***** error expinv (2, i) ***** error ... [x, xlo, xup] = expinv (1, 2, -1, 0.04) 18 tests, 18 passed, 0 known failure, 0 skipped [inst/dist_fun/nakainv.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/dist_fun/nakainv.m ***** demo ## Plot various iCDFs from the Nakagami distribution p = 0.001:0.001:0.999; x1 = nakainv (p, 0.5, 1); x2 = nakainv (p, 1, 1); x3 = nakainv (p, 1, 2); x4 = nakainv (p, 1, 3); x5 = nakainv (p, 2, 1); x6 = nakainv (p, 2, 2); x7 = nakainv (p, 5, 1); plot (p, x1, "-r", p, x2, "-g", p, x3, "-y", p, x4, "-m", ... p, x5, "-k", p, x6, "-b", p, x7, "-c") grid on ylim ([0, 3]) legend ({"μ = 0.5, ω = 1", "μ = 1, ω = 1", "μ = 1, ω = 2", ... "μ = 1, ω = 3", "μ = 2, ω = 1", "μ = 2, ω = 2", ... "μ = 5, ω = 1"}, "location", "northwest") title ("Nakagami iCDF") xlabel ("probability") ylabel ("values in x") ***** shared p, y p = [-Inf, -1, 0, 1/2, 1, 2, Inf]; y = [NaN, NaN, 0, 0.83255461115769769, Inf, NaN, NaN]; ***** assert (nakainv (p, ones (1,7), ones (1,7)), y, eps) ***** assert (nakainv (p, 1, 1), y, eps) ***** assert (nakainv (p, [1, 1, 1, NaN, 1, 1, 1], 1), [y(1:3), NaN, y(5:7)], eps) ***** assert (nakainv (p, 1, [1, 1, 1, NaN, 1, 1, 1]), [y(1:3), NaN, y(5:7)], eps) ***** assert (nakainv ([p, NaN], 1, 1), [y, NaN], eps) ***** assert (nakainv (single ([p, NaN]), 1, 1), single ([y, NaN])) ***** assert (nakainv ([p, NaN], single (1), 1), single ([y, NaN])) ***** assert (nakainv ([p, NaN], 1, single (1)), single ([y, NaN])) ***** error nakainv () ***** error nakainv (1) ***** error nakainv (1, 2) ***** error ... nakainv (ones (3), ones (2), ones(2)) ***** error ... nakainv (ones (2), ones (3), ones(2)) ***** error ... nakainv (ones (2), ones (2), ones(3)) ***** error nakainv (i, 4, 3) ***** error nakainv (1, i, 3) ***** error nakainv (1, 4, i) 17 tests, 17 passed, 0 known failure, 0 skipped [inst/dist_fun/ricepdf.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/dist_fun/ricepdf.m ***** demo ## Plot various PDFs from the Rician distribution x = 0:0.01:8; y1 = ricepdf (x, 0, 1); y2 = ricepdf (x, 0.5, 1); y3 = ricepdf (x, 1, 1); y4 = ricepdf (x, 2, 1); y5 = ricepdf (x, 4, 1); plot (x, y1, "-b", x, y2, "-g", x, y3, "-r", x, y4, "-m", x, y5, "-k") grid on ylim ([0, 0.65]) xlim ([0, 8]) legend ({"s = 0, σ = 1", "s = 0.5, σ = 1", "s = 1, σ = 1", ... "s = 2, σ = 1", "s = 4, σ = 1"}, "location", "northeast") title ("Rician PDF") xlabel ("values in x") ylabel ("density") ***** shared x, y x = [-1 0 0.5 1 2]; y = [0 0 0.1073 0.1978 0.2846]; ***** assert (ricepdf (x, ones (1, 5), 2 * ones (1, 5)), y, 1e-4) ***** assert (ricepdf (x, 1, 2 * ones (1, 5)), y, 1e-4) ***** assert (ricepdf (x, ones (1, 5), 2), y, 1e-4) ***** assert (ricepdf (x, [0 NaN 1 1 1], 2), [0 NaN y(3:5)], 1e-4) ***** assert (ricepdf (x, 1, 2 * [0 NaN 1 1 1]), [0 NaN y(3:5)], 1e-4) ***** assert (ricepdf ([x, NaN], 1, 2), [y, NaN], 1e-4) ***** assert (ricepdf (single ([x, NaN]), 1, 2), single ([y, NaN]), 1e-4) ***** assert (ricepdf ([x, NaN], single (1), 2), single ([y, NaN]), 1e-4) ***** assert (ricepdf ([x, NaN], 1, single (2)), single ([y, NaN]), 1e-4) ***** error ricepdf () ***** error ricepdf (1) ***** error ricepdf (1,2) ***** error ricepdf (1,2,3,4) ***** error ... ricepdf (ones (3), ones (2), ones (2)) ***** error ... ricepdf (ones (2), ones (3), ones (2)) ***** error ... ricepdf (ones (2), ones (2), ones (3)) ***** error ricepdf (i, 2, 2) ***** error ricepdf (2, i, 2) ***** error ricepdf (2, 2, i) 19 tests, 19 passed, 0 known failure, 0 skipped [inst/dist_fun/normpdf.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/dist_fun/normpdf.m ***** demo ## Plot various PDFs from the normal distribution x = -5:0.01:5; y1 = normpdf (x, 0, 0.5); y2 = normpdf (x, 0, 1); y3 = normpdf (x, 0, 2); y4 = normpdf (x, -2, 0.8); plot (x, y1, "-b", x, y2, "-g", x, y3, "-r", x, y4, "-c") grid on xlim ([-5, 5]) ylim ([0, 0.9]) legend ({"μ = 0, σ = 0.5", "μ = 0, σ = 1", ... "μ = 0, σ = 2", "μ = -2, σ = 0.8"}, "location", "northeast") title ("Normal PDF") xlabel ("values in x") ylabel ("density") ***** shared x, y x = [-Inf, 1, 2, Inf]; y = 1 / sqrt (2 * pi) * exp (-(x - 1) .^ 2 / 2); ***** assert (normpdf (x, ones (1,4), ones (1,4)), y, eps) ***** assert (normpdf (x, 1, ones (1,4)), y, eps) ***** assert (normpdf (x, ones (1,4), 1), y, eps) ***** assert (normpdf (x, [0 -Inf NaN Inf], 1), [y(1) NaN NaN NaN], eps) ***** assert (normpdf (x, 1, [Inf NaN -1 0]), [NaN NaN NaN NaN], eps) ***** assert (normpdf ([x, NaN], 1, 1), [y, NaN], eps) ***** assert (normpdf (single ([x, NaN]), 1, 1), single ([y, NaN]), eps ("single")) ***** assert (normpdf ([x, NaN], single (1), 1), single ([y, NaN]), eps ("single")) ***** assert (normpdf ([x, NaN], 1, single (1)), single ([y, NaN]), eps ("single")) ***** error normpdf () ***** error ... normpdf (ones (3), ones (2), ones (2)) ***** error ... normpdf (ones (2), ones (3), ones (2)) ***** error ... normpdf (ones (2), ones (2), ones (3)) ***** error normpdf (i, 2, 2) ***** error normpdf (2, i, 2) ***** error normpdf (2, 2, i) 16 tests, 16 passed, 0 known failure, 0 skipped [inst/dist_fun/hygepdf.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/dist_fun/hygepdf.m ***** demo ## Plot various PDFs from the hypergeometric distribution x = 0:60; y1 = hygepdf (x, 500, 50, 100); y2 = hygepdf (x, 500, 60, 200); y3 = hygepdf (x, 500, 70, 300); plot (x, y1, "*b", x, y2, "*g", x, y3, "*r") grid on xlim ([0, 60]) ylim ([0, 0.18]) legend ({"m = 500, k = 50, μ = 100", "m = 500, k = 60, μ = 200", ... "m = 500, k = 70, μ = 300"}, "location", "northeast") title ("Hypergeometric PDF") xlabel ("values in x (number of successes)") ylabel ("density") ***** shared x, y x = [-1 0 1 2 3]; y = [0 1/6 4/6 1/6 0]; ***** assert (hygepdf (x, 4*ones (1,5), 2, 2), y, eps) ***** assert (hygepdf (x, 4, 2*ones (1,5), 2), y, eps) ***** assert (hygepdf (x, 4, 2, 2*ones (1,5)), y, eps) ***** assert (hygepdf (x, 4*[1 -1 NaN 1.1 1], 2, 2), [0 NaN NaN NaN 0], eps) ***** assert (hygepdf (x, 4, 2*[1 -1 NaN 1.1 1], 2), [0 NaN NaN NaN 0], eps) ***** assert (hygepdf (x, 4, 5, 2), [NaN NaN NaN NaN NaN], eps) ***** assert (hygepdf (x, 4, 2, 2*[1 -1 NaN 1.1 1]), [0 NaN NaN NaN 0], eps) ***** assert (hygepdf (x, 4, 2, 5), [NaN NaN NaN NaN NaN], eps) ***** assert (hygepdf ([x, NaN], 4, 2, 2), [y, NaN], eps) ***** assert (hygepdf (single ([x, NaN]), 4, 2, 2), single ([y, NaN]), eps("single")) ***** assert (hygepdf ([x, NaN], single (4), 2, 2), single ([y, NaN]), eps("single")) ***** assert (hygepdf ([x, NaN], 4, single (2), 2), single ([y, NaN]), eps("single")) ***** assert (hygepdf ([x, NaN], 4, 2, single (2)), single ([y, NaN]), eps("single")) ***** test z = zeros(3,5); z([4,5,6,8,9,12]) = [1, 0.5, 1/6, 0.5, 2/3, 1/6]; assert (hygepdf (x, 4, [0, 1, 2], 2, "vectorexpand"), z, eps); assert (hygepdf (x, 4, [0, 1, 2]', 2, "vectorexpand"), z, eps); assert (hygepdf (x', 4, [0, 1, 2], 2, "vectorexpand"), z, eps); assert (hygepdf (2, 4, [0 ,1, 2], 2, "vectorexpand"), z(:,4), eps); assert (hygepdf (x, 4, 1, 2, "vectorexpand"), z(2,:), eps); assert (hygepdf ([NaN, x], 4, [0 1 2]', 2, "vectorexpand"), [NaN(3,1), z], eps); ***** error hygepdf () ***** error hygepdf (1) ***** error hygepdf (1,2) ***** error hygepdf (1,2,3) ***** error ... hygepdf (1, ones (3), ones (2), ones (2)) ***** error ... hygepdf (1, ones (2), ones (3), ones (2)) ***** error ... hygepdf (1, ones (2), ones (2), ones (3)) ***** error hygepdf (i, 2, 2, 2) ***** error hygepdf (2, i, 2, 2) ***** error hygepdf (2, 2, i, 2) ***** error hygepdf (2, 2, 2, i) 25 tests, 25 passed, 0 known failure, 0 skipped [inst/dist_fun/tinv.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/dist_fun/tinv.m ***** demo ## Plot various iCDFs from the Student's T distribution p = 0.001:0.001:0.999; x1 = tinv (p, 1); x2 = tinv (p, 2); x3 = tinv (p, 5); x4 = tinv (p, Inf); plot (p, x1, "-b", p, x2, "-g", p, x3, "-r", p, x4, "-m") grid on xlim ([0, 1]) ylim ([-5, 5]) legend ({"df = 1", "df = 2", ... "df = 5", 'df = \infty'}, "location", "northwest") title ("Student's T iCDF") xlabel ("probability") ylabel ("values in x") ***** shared p p = [-1 0 0.5 1 2]; ***** assert (tinv (p, ones (1,5)), [NaN -Inf 0 Inf NaN]) ***** assert (tinv (p, 1), [NaN -Inf 0 Inf NaN], eps) ***** assert (tinv (p, [1 0 NaN 1 1]), [NaN NaN NaN Inf NaN], eps) ***** assert (tinv ([p(1:2) NaN p(4:5)], 1), [NaN -Inf NaN Inf NaN]) ***** assert (tinv ([p, NaN], 1), [NaN -Inf 0 Inf NaN NaN], eps) ***** assert (tinv (single ([p, NaN]), 1), single ([NaN -Inf 0 Inf NaN NaN]), eps ("single")) ***** assert (tinv ([p, NaN], single (1)), single ([NaN -Inf 0 Inf NaN NaN]), eps ("single")) ***** error tinv () ***** error tinv (1) ***** error ... tinv (ones (3), ones (2)) ***** error ... tinv (ones (2), ones (3)) ***** error tinv (i, 2) ***** error tinv (2, i) 13 tests, 13 passed, 0 known failure, 0 skipped [inst/dist_fun/ncx2cdf.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/dist_fun/ncx2cdf.m ***** demo ## Plot various CDFs from the noncentral chi-squared distribution x = 0:0.1:10; p1 = ncx2cdf (x, 2, 1); p2 = ncx2cdf (x, 2, 2); p3 = ncx2cdf (x, 2, 3); p4 = ncx2cdf (x, 4, 1); p5 = ncx2cdf (x, 4, 2); p6 = ncx2cdf (x, 4, 3); plot (x, p1, "-r", x, p2, "-g", x, p3, "-k", ... x, p4, "-m", x, p5, "-c", x, p6, "-y") grid on xlim ([0, 10]) legend ({"df = 2, λ = 1", "df = 2, λ = 2", ... "df = 2, λ = 3", "df = 4, λ = 1", ... "df = 4, λ = 2", "df = 4, λ = 3"}, "location", "southeast") title ("Noncentral chi-squared CDF") xlabel ("values in x") ylabel ("probability") ***** demo ## Compare the noncentral chi-squared CDF with LAMBDA = 2 to the ## chi-squared CDF with the same number of degrees of freedom (4). x = 0:0.1:10; p1 = ncx2cdf (x, 4, 2); p2 = chi2cdf (x, 4); plot (x, p1, "-", x, p2, "-") grid on xlim ([0, 10]) legend ({"Noncentral χ^2(4,2)", "χ^2(4)"}, "location", "northwest") title ("Noncentral chi-squared vs chi-squared CDFs") xlabel ("values in x") ylabel ("probability") ***** test x = -2:0.1:2; p = ncx2cdf (x, 10, 1); assert (p([1:21]), zeros (1, 21), 3e-84); assert (p(22), 1.521400636466575e-09, 1e-14); assert (p(30), 6.665480510026046e-05, 1e-14); assert (p(41), 0.002406447308399836, 1e-14); ***** test p = ncx2cdf (12, 10, 3); assert (p, 0.4845555602398649, 1e-14); ***** test p = ncx2cdf (2, 3, 2); assert (p, 0.2207330870741212, 1e-14); ***** test p = ncx2cdf (2, 3, 2, "upper"); assert (p, 0.7792669129258789, 1e-14); ***** test p = ncx2cdf ([3, 6], 3, 2, "upper"); assert (p, [0.6423318186400054, 0.3152299878943012], 1e-14); ***** error ncx2cdf () ***** error ncx2cdf (1) ***** error ncx2cdf (1, 2) ***** error ncx2cdf (1, 2, 3, "tail") ***** error ncx2cdf (1, 2, 3, 4) ***** error ... ncx2cdf (ones (3), ones (2), ones (2)) ***** error ... ncx2cdf (ones (2), ones (3), ones (2)) ***** error ... ncx2cdf (ones (2), ones (2), ones (3)) ***** error ncx2cdf (i, 2, 2) ***** error ncx2cdf (2, i, 2) ***** error ncx2cdf (2, 2, i) 16 tests, 16 passed, 0 known failure, 0 skipped [inst/dist_fun/binornd.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/dist_fun/binornd.m ***** assert (size (binornd (2, 1/2)), [1 1]) ***** assert (size (binornd (2 * ones (2, 1), 1/2)), [2, 1]) ***** assert (size (binornd (2 * ones (2, 2), 1/2)), [2, 2]) ***** assert (size (binornd (2, 1/2 * ones (2, 1))), [2, 1]) ***** assert (size (binornd (1, 1/2 * ones (2, 2))), [2, 2]) ***** assert (size (binornd (ones (2, 1), 1)), [2, 1]) ***** assert (size (binornd (ones (2, 2), 1)), [2, 2]) ***** assert (size (binornd (2, 1/2, 3)), [3, 3]) ***** assert (size (binornd (1, 1, [4, 1])), [4, 1]) ***** assert (size (binornd (1, 1, 4, 1)), [4, 1]) ***** assert (size (binornd (1, 1, 4, 1, 5)), [4, 1, 5]) ***** assert (size (binornd (1, 1, 0, 1)), [0, 1]) ***** assert (size (binornd (1, 1, 1, 0)), [1, 0]) ***** assert (size (binornd (1, 1, 1, 2, 0, 5)), [1, 2, 0, 5]) ***** assert (class (binornd (1, 1)), "double") ***** assert (class (binornd (1, single (0))), "single") ***** assert (class (binornd (1, single ([0, 0]))), "single") ***** assert (class (binornd (1, single (1), 2)), "single") ***** assert (class (binornd (1, single ([1, 1]), 1, 2)), "single") ***** assert (class (binornd (single (1), 1, 2)), "single") ***** assert (class (binornd (single ([1, 1]), 1, 1, 2)), "single") ***** error binornd () ***** error binornd (1) ***** error ... binornd (ones (3), ones (2)) ***** error ... binornd (ones (2), ones (3)) ***** error binornd (i, 2) ***** error binornd (1, i) ***** error ... binornd (1, 1/2, -1) ***** error ... binornd (1, 1/2, 1.2) ***** error ... binornd (1, 1/2, ones (2)) ***** error ... binornd (1, 1/2, [2 -1 2]) ***** error ... binornd (1, 1/2, [2 0 2.5]) ***** error ... binornd (1, 1/2, 2, -1, 5) ***** error ... binornd (1, 1/2, 2, 1.5, 5) ***** error ... binornd (2, 1/2 * ones (2), 3) ***** error ... binornd (2, 1/2 * ones (2), [3, 2]) ***** error ... binornd (2, 1/2 * ones (2), 3, 2) ***** error ... binornd (2 * ones (2), 1/2, 3) ***** error ... binornd (2 * ones (2), 1/2, [3, 2]) ***** error ... binornd (2 * ones (2), 1/2, 3, 2) 40 tests, 40 passed, 0 known failure, 0 skipped [inst/dist_fun/mvtrnd.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/dist_fun/mvtrnd.m ***** test rho = [1, 0.5; 0.5, 1]; df = 3; n = 10; r = mvtrnd (rho, df, n); assert (size (r), [10, 2]); ***** test rho = [1, 0.5; 0.5, 1]; df = [2; 3]; n = 2; r = mvtrnd (rho, df, 2); assert (size (r), [2, 2]); 2 tests, 2 passed, 0 known failure, 0 skipped [inst/dist_fun/lognrnd.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/dist_fun/lognrnd.m ***** assert (size (lognrnd (1, 1)), [1 1]) ***** assert (size (lognrnd (1, ones (2,1))), [2, 1]) ***** assert (size (lognrnd (1, ones (2,2))), [2, 2]) ***** assert (size (lognrnd (ones (2,1), 1)), [2, 1]) ***** assert (size (lognrnd (ones (2,2), 1)), [2, 2]) ***** assert (size (lognrnd (1, 1, 3)), [3, 3]) ***** assert (size (lognrnd (1, 1, [4, 1])), [4, 1]) ***** assert (size (lognrnd (1, 1, 4, 1)), [4, 1]) ***** assert (size (lognrnd (1, 1, 4, 1, 5)), [4, 1, 5]) ***** assert (size (lognrnd (1, 1, 0, 1)), [0, 1]) ***** assert (size (lognrnd (1, 1, 1, 0)), [1, 0]) ***** assert (size (lognrnd (1, 1, 1, 2, 0, 5)), [1, 2, 0, 5]) ***** assert (class (lognrnd (1, 1)), "double") ***** assert (class (lognrnd (1, single (1))), "single") ***** assert (class (lognrnd (1, single ([1, 1]))), "single") ***** assert (class (lognrnd (single (1), 1)), "single") ***** assert (class (lognrnd (single ([1, 1]), 1)), "single") ***** error lognrnd () ***** error lognrnd (1) ***** error ... lognrnd (ones (3), ones (2)) ***** error ... lognrnd (ones (2), ones (3)) ***** error lognrnd (i, 2, 3) ***** error lognrnd (1, i, 3) ***** error ... lognrnd (1, 2, -1) ***** error ... lognrnd (1, 2, 1.2) ***** error ... lognrnd (1, 2, ones (2)) ***** error ... lognrnd (1, 2, [2 -1 2]) ***** error ... lognrnd (1, 2, [2 0 2.5]) ***** error ... lognrnd (1, 2, 2, -1, 5) ***** error ... lognrnd (1, 2, 2, 1.5, 5) ***** error ... lognrnd (2, ones (2), 3) ***** error ... lognrnd (2, ones (2), [3, 2]) ***** error ... lognrnd (2, ones (2), 3, 2) 33 tests, 33 passed, 0 known failure, 0 skipped [inst/dist_fun/evcdf.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/dist_fun/evcdf.m ***** demo ## Plot various CDFs from the extreme value distribution x = -10:0.01:10; p1 = evcdf (x, 0.5, 2); p2 = evcdf (x, 1.0, 2); p3 = evcdf (x, 1.5, 3); p4 = evcdf (x, 3.0, 4); plot (x, p1, "-b", x, p2, "-g", x, p3, "-r", x, p4, "-c") grid on legend ({"μ = 0.5, σ = 2", "μ = 1.0, σ = 2", ... "μ = 1.5, σ = 3", "μ = 3.0, σ = 4"}, "location", "southeast") title ("Extreme value CDF") xlabel ("values in x") ylabel ("probability") ***** shared x, y x = [-Inf, 1, 2, Inf]; y = [0, 0.6321, 0.9340, 1]; ***** assert (evcdf (x, ones (1,4), ones (1,4)), y, 1e-4) ***** assert (evcdf (x, 1, ones (1,4)), y, 1e-4) ***** assert (evcdf (x, ones (1,4), 1), y, 1e-4) ***** assert (evcdf (x, [0, -Inf, NaN, Inf], 1), [0, 1, NaN, NaN], 1e-4) ***** assert (evcdf (x, 1, [Inf, NaN, -1, 0]), [NaN, NaN, NaN, NaN], 1e-4) ***** assert (evcdf ([x(1:2), NaN, x(4)], 1, 1), [y(1:2), NaN, y(4)], 1e-4) ***** assert (evcdf (x, "upper"), [1, 0.0660, 0.0006, 0], 1e-4) ***** assert (evcdf ([x, NaN], 1, 1), [y, NaN], 1e-4) ***** assert (evcdf (single ([x, NaN]), 1, 1), single ([y, NaN]), 1e-4) ***** assert (evcdf ([x, NaN], single (1), 1), single ([y, NaN]), 1e-4) ***** assert (evcdf ([x, NaN], 1, single (1)), single ([y, NaN]), 1e-4) ***** error evcdf () ***** error evcdf (1,2,3,4,5,6,7) ***** error evcdf (1, 2, 3, 4, "uper") ***** error ... evcdf (ones (3), ones (2), ones (2)) ***** error evcdf (2, 3, 4, [1, 2]) ***** error ... [p, plo, pup] = evcdf (1, 2, 3) ***** error [p, plo, pup] = ... evcdf (1, 2, 3, [1, 0; 0, 1], 0) ***** error [p, plo, pup] = ... evcdf (1, 2, 3, [1, 0; 0, 1], 1.22) ***** error [p, plo, pup] = ... evcdf (1, 2, 3, [1, 0; 0, 1], "alpha", "upper") ***** error evcdf (i, 2, 2) ***** error evcdf (2, i, 2) ***** error evcdf (2, 2, i) ***** error ... [p, plo, pup] = evcdf (1, 2, 3, [1, 0; 0, -inf], 0.04) 24 tests, 24 passed, 0 known failure, 0 skipped [inst/dist_fun/tcdf.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/dist_fun/tcdf.m ***** demo ## Plot various CDFs from the Student's T distribution x = -5:0.01:5; p1 = tcdf (x, 1); p2 = tcdf (x, 2); p3 = tcdf (x, 5); p4 = tcdf (x, Inf); plot (x, p1, "-b", x, p2, "-g", x, p3, "-r", x, p4, "-m") grid on xlim ([-5, 5]) ylim ([0, 1]) legend ({"df = 1", "df = 2", ... "df = 5", 'df = \infty'}, "location", "southeast") title ("Student's T CDF") xlabel ("values in x") ylabel ("probability") ***** shared x,y x = [-Inf 0 1 Inf]; y = [0 1/2 3/4 1]; ***** assert (tcdf (x, ones (1,4)), y, eps) ***** assert (tcdf (x, 1), y, eps) ***** assert (tcdf (x, [0 1 NaN 1]), [NaN 1/2 NaN 1], eps) ***** assert (tcdf ([x(1:2) NaN x(4)], 1), [y(1:2) NaN y(4)], eps) ***** assert (tcdf (2, 3, "upper"), 0.0697, 1e-4) ***** assert (tcdf (205, 5, "upper"), 2.6206e-11, 1e-14) ***** assert (tcdf ([x, NaN], 1), [y, NaN], eps) ***** assert (tcdf (single ([x, NaN]), 1), single ([y, NaN]), eps ("single")) ***** assert (tcdf ([x, NaN], single (1)), single ([y, NaN]), eps ("single")) ***** error tcdf () ***** error tcdf (1) ***** error tcdf (1, 2, "uper") ***** error tcdf (1, 2, 3) ***** error ... tcdf (ones (3), ones (2)) ***** error ... tcdf (ones (3), ones (2)) ***** error ... tcdf (ones (3), ones (2), "upper") ***** error tcdf (i, 2) ***** error tcdf (2, i) ***** shared tol_rel tol_rel = 10 * eps; ***** assert (tcdf (10^(-10), 2.5), 0.50000000003618087, -tol_rel) ***** assert (tcdf (10^(-11), 2.5), 0.50000000000361809, -tol_rel) ***** assert (tcdf (10^(-12), 2.5), 0.50000000000036181, -tol_rel) ***** assert (tcdf (10^(-13), 2.5), 0.50000000000003618, -tol_rel) ***** assert (tcdf (10^(-14), 2.5), 0.50000000000000362, -tol_rel) ***** assert (tcdf (10^(-15), 2.5), 0.50000000000000036, -tol_rel) ***** assert (tcdf (10^(-16), 2.5), 0.50000000000000004, -tol_rel) ***** assert (tcdf (-10^1, 2.5), 2.2207478836537124e-03, -tol_rel) ***** assert (tcdf (-10^2, 2.5), 7.1916492116661878e-06, -tol_rel) ***** assert (tcdf (-10^3, 2.5), 2.2747463948307452e-08, -tol_rel) ***** assert (tcdf (-10^4, 2.5), 7.1933970159922115e-11, -tol_rel) ***** assert (tcdf (-10^5, 2.5), 2.2747519231756221e-13, -tol_rel) 30 tests, 30 passed, 0 known failure, 0 skipped [inst/dist_fun/hygernd.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/dist_fun/hygernd.m ***** assert (size (hygernd (4,2,2)), [1, 1]) ***** assert (size (hygernd (4*ones (2,1), 2,2)), [2, 1]) ***** assert (size (hygernd (4*ones (2,2), 2,2)), [2, 2]) ***** assert (size (hygernd (4, 2*ones (2,1), 2)), [2, 1]) ***** assert (size (hygernd (4, 2*ones (2,2), 2)), [2, 2]) ***** assert (size (hygernd (4, 2, 2*ones (2,1))), [2, 1]) ***** assert (size (hygernd (4, 2, 2*ones (2,2))), [2, 2]) ***** assert (size (hygernd (4, 2, 2, 3)), [3, 3]) ***** assert (size (hygernd (4, 2, 2, [4 1])), [4, 1]) ***** assert (size (hygernd (4, 2, 2, 4, 1)), [4, 1]) ***** assert (class (hygernd (4,2,2)), "double") ***** assert (class (hygernd (single (4),2,2)), "single") ***** assert (class (hygernd (single ([4 4]),2,2)), "single") ***** assert (class (hygernd (4,single (2),2)), "single") ***** assert (class (hygernd (4,single ([2 2]),2)), "single") ***** assert (class (hygernd (4,2,single (2))), "single") ***** assert (class (hygernd (4,2,single ([2 2]))), "single") ***** error hygernd () ***** error hygernd (1) ***** error hygernd (1, 2) ***** error ... hygernd (ones (3), ones (2), ones (2)) ***** error ... hygernd (ones (2), ones (3), ones (2)) ***** error ... hygernd (ones (2), ones (2), ones (3)) ***** error hygernd (i, 2, 3) ***** error hygernd (1, i, 3) ***** error hygernd (1, 2, i) ***** error ... hygernd (1, 2, 3, -1) ***** error ... hygernd (1, 2, 3, 1.2) ***** error ... hygernd (1, 2, 3, ones (2)) ***** error ... hygernd (1, 2, 3, [2 -1 2]) ***** error ... hygernd (1, 2, 3, [2 0 2.5]) ***** error ... hygernd (1, 2, 3, 2, -1, 5) ***** error ... hygernd (1, 2, 3, 2, 1.5, 5) ***** error ... hygernd (2, ones (2), 2, 3) ***** error ... hygernd (2, ones (2), 2, [3, 2]) ***** error ... hygernd (2, ones (2), 2, 3, 2) 36 tests, 36 passed, 0 known failure, 0 skipped [inst/dist_fun/loglrnd.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/dist_fun/loglrnd.m ***** assert (size (loglrnd (1, 1)), [1 1]) ***** assert (size (loglrnd (1, ones (2,1))), [2, 1]) ***** assert (size (loglrnd (1, ones (2,2))), [2, 2]) ***** assert (size (loglrnd (ones (2,1), 1)), [2, 1]) ***** assert (size (loglrnd (ones (2,2), 1)), [2, 2]) ***** assert (size (loglrnd (1, 1, 3)), [3, 3]) ***** assert (size (loglrnd (1, 1, [4, 1])), [4, 1]) ***** assert (size (loglrnd (1, 1, 4, 1)), [4, 1]) ***** assert (size (loglrnd (1, 1, 4, 1, 5)), [4, 1, 5]) ***** assert (size (loglrnd (1, 1, 0, 1)), [0, 1]) ***** assert (size (loglrnd (1, 1, 1, 0)), [1, 0]) ***** assert (size (loglrnd (1, 1, 1, 2, 0, 5)), [1, 2, 0, 5]) ***** assert (class (loglrnd (1, 1)), "double") ***** assert (class (loglrnd (1, single (1))), "single") ***** assert (class (loglrnd (1, single ([1, 1]))), "single") ***** assert (class (loglrnd (single (1), 1)), "single") ***** assert (class (loglrnd (single ([1, 1]), 1)), "single") ***** error loglrnd () ***** error loglrnd (1) ***** error ... loglrnd (ones (3), ones (2)) ***** error ... loglrnd (ones (2), ones (3)) ***** error loglrnd (i, 2, 3) ***** error loglrnd (1, i, 3) ***** error ... loglrnd (1, 2, -1) ***** error ... loglrnd (1, 2, 1.2) ***** error ... loglrnd (1, 2, ones (2)) ***** error ... loglrnd (1, 2, [2 -1 2]) ***** error ... loglrnd (1, 2, [2 0 2.5]) ***** error ... loglrnd (1, 2, 2, -1, 5) ***** error ... loglrnd (1, 2, 2, 1.5, 5) ***** error ... loglrnd (2, ones (2), 3) ***** error ... loglrnd (2, ones (2), [3, 2]) ***** error ... loglrnd (2, ones (2), 3, 2) 33 tests, 33 passed, 0 known failure, 0 skipped [inst/dist_fun/binopdf.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/dist_fun/binopdf.m ***** demo ## Plot various PDFs from the binomial distribution x = 0:40; y1 = binopdf (x, 20, 0.5); y2 = binopdf (x, 20, 0.7); y3 = binopdf (x, 40, 0.5); plot (x, y1, "*b", x, y2, "*g", x, y3, "*r") grid on ylim ([0, 0.25]) legend ({"n = 20, ps = 0.5", "n = 20, ps = 0.7", ... "n = 40, ps = 0.5"}, "location", "northeast") title ("Binomial PDF") xlabel ("values in x (number of successes)") ylabel ("density") ***** shared x, y x = [-1 0 1 2 3]; y = [0 1/4 1/2 1/4 0]; ***** assert (binopdf (x, 2 * ones (1, 5), 0.5 * ones (1, 5)), y, eps) ***** assert (binopdf (x, 2, 0.5 * ones (1, 5)), y, eps) ***** assert (binopdf (x, 2 * ones (1, 5), 0.5), y, eps) ***** assert (binopdf (x, 2 * [0 -1 NaN 1.1 1], 0.5), [0 NaN NaN NaN 0]) ***** assert (binopdf (x, 2, 0.5 * [0 -1 NaN 3 1]), [0 NaN NaN NaN 0]) ***** assert (binopdf ([x, NaN], 2, 0.5), [y, NaN], eps) ***** assert (binopdf (cat (3, x, x), 2, 0.5), cat (3, y, y), eps) ***** assert (binopdf (1, 1, 1), 1) ***** assert (binopdf (0, 3, 0), 1) ***** assert (binopdf (2, 2, 1), 1) ***** assert (binopdf (1, 2, 1), 0) ***** assert (binopdf (0, 1.1, 0), NaN) ***** assert (binopdf (1, 2, -1), NaN) ***** assert (binopdf (1, 2, 1.5), NaN) ***** assert (binopdf ([], 1, 1), []) ***** assert (binopdf (1, [], 1), []) ***** assert (binopdf (1, 1, []), []) ***** assert (binopdf (ones (1, 0), 2, .5), ones(1, 0)) ***** assert (binopdf (ones (0, 1), 2, .5), ones(0, 1)) ***** assert (binopdf (ones (0, 1, 2), 2, .5), ones(0, 1, 2)) ***** assert (binopdf (1, ones (0, 1, 2), .5), ones(0, 1, 2)) ***** assert (binopdf (1, 2, ones (0, 1, 2)), ones(0, 1, 2)) ***** assert (binopdf (ones (1, 0, 2), 2, .5), ones(1, 0, 2)) ***** assert (binopdf (ones (1, 2, 0), 2, .5), ones(1, 2, 0)) ***** assert (binopdf (ones (0, 1, 2), NaN, .5), ones(0, 1, 2)) ***** assert (binopdf (ones (0, 1, 2), 2, NaN), ones(0, 1, 2)) ***** assert (binopdf (single ([x, NaN]), 2, 0.5), single ([y, NaN])) ***** assert (binopdf ([x, NaN], single (2), 0.5), single ([y, NaN])) ***** assert (binopdf ([x, NaN], 2, single (0.5)), single ([y, NaN])) ***** error binopdf () ***** error binopdf (1) ***** error binopdf (1, 2) ***** error binopdf (1, 2, 3, 4) ***** error ... binopdf (ones (3), ones (2), ones (2)) ***** error ... binopdf (ones (2), ones (3), ones (2)) ***** error ... binopdf (ones (2), ones (2), ones (3)) ***** error binopdf (i, 2, 2) ***** error binopdf (2, i, 2) ***** error binopdf (2, 2, i) 39 tests, 39 passed, 0 known failure, 0 skipped [inst/dist_fun/vmcdf.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/dist_fun/vmcdf.m ***** demo ## Plot various CDFs from the von Mises distribution x1 = [-pi:0.1:pi]; p1 = vmcdf (x1, 0, 0.5); p2 = vmcdf (x1, 0, 1); p3 = vmcdf (x1, 0, 2); p4 = vmcdf (x1, 0, 4); plot (x1, p1, "-r", x1, p2, "-g", x1, p3, "-b", x1, p4, "-c") grid on xlim ([-pi, pi]) legend ({"μ = 0, k = 0.5", "μ = 0, k = 1", ... "μ = 0, k = 2", "μ = 0, k = 4"}, "location", "northwest") title ("Von Mises CDF") xlabel ("values in x") ylabel ("probability") ***** shared x, p0, p1 x = [-pi:pi/2:pi]; p0 = [0, 0.10975, 0.5, 0.89025, 1]; p1 = [0, 0.03752, 0.5, 0.99622, 1]; ***** assert (vmcdf (x, 0, 1), p0, 1e-5) ***** assert (vmcdf (x, 0, 1, "upper"), 1 - p0, 1e-5) ***** assert (vmcdf (x, zeros (1,5), ones (1,5)), p0, 1e-5) ***** assert (vmcdf (x, zeros (1,5), ones (1,5), "upper"), 1 - p0, 1e-5) ***** assert (vmcdf (x, 0, [1 2 3 4 5]), p1, 1e-5) ***** assert (vmcdf (x, 0, [1 2 3 4 5], "upper"), 1 - p1, 1e-5) ***** assert (isa (vmcdf (single (pi), 0, 1), "single"), true) ***** assert (isa (vmcdf (pi, single (0), 1), "single"), true) ***** assert (isa (vmcdf (pi, 0, single (1)), "single"), true) ***** error vmcdf () ***** error vmcdf (1) ***** error vmcdf (1, 2) ***** error vmcdf (1, 2, 3, "tail") ***** error vmcdf (1, 2, 3, 4) ***** error ... vmcdf (ones (3), ones (2), ones (2)) ***** error ... vmcdf (ones (2), ones (3), ones (2)) ***** error ... vmcdf (ones (2), ones (2), ones (3)) ***** error vmcdf (i, 2, 2) ***** error vmcdf (2, i, 2) ***** error vmcdf (2, 2, i) 20 tests, 20 passed, 0 known failure, 0 skipped [inst/dist_fun/nctrnd.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/dist_fun/nctrnd.m ***** assert (size (nctrnd (1, 1)), [1 1]) ***** assert (size (nctrnd (1, ones (2,1))), [2, 1]) ***** assert (size (nctrnd (1, ones (2,2))), [2, 2]) ***** assert (size (nctrnd (ones (2,1), 1)), [2, 1]) ***** assert (size (nctrnd (ones (2,2), 1)), [2, 2]) ***** assert (size (nctrnd (1, 1, 3)), [3, 3]) ***** assert (size (nctrnd (1, 1, [4, 1])), [4, 1]) ***** assert (size (nctrnd (1, 1, 4, 1)), [4, 1]) ***** assert (size (nctrnd (1, 1, 4, 1, 5)), [4, 1, 5]) ***** assert (size (nctrnd (1, 1, 0, 1)), [0, 1]) ***** assert (size (nctrnd (1, 1, 1, 0)), [1, 0]) ***** assert (size (nctrnd (1, 1, 1, 2, 0, 5)), [1, 2, 0, 5]) ***** assert (class (nctrnd (1, 1)), "double") ***** assert (class (nctrnd (1, single (1))), "single") ***** assert (class (nctrnd (1, single ([1, 1]))), "single") ***** assert (class (nctrnd (single (1), 1)), "single") ***** assert (class (nctrnd (single ([1, 1]), 1)), "single") ***** error nctrnd () ***** error nctrnd (1) ***** error ... nctrnd (ones (3), ones (2)) ***** error ... nctrnd (ones (2), ones (3)) ***** error nctrnd (i, 2) ***** error nctrnd (1, i) ***** error ... nctrnd (1, 2, -1) ***** error ... nctrnd (1, 2, 1.2) ***** error ... nctrnd (1, 2, ones (2)) ***** error ... nctrnd (1, 2, [2 -1 2]) ***** error ... nctrnd (1, 2, [2 0 2.5]) ***** error ... nctrnd (1, 2, 2, -1, 5) ***** error ... nctrnd (1, 2, 2, 1.5, 5) ***** error ... nctrnd (2, ones (2), 3) ***** error ... nctrnd (2, ones (2), [3, 2]) ***** error ... nctrnd (2, ones (2), 3, 2) 33 tests, 33 passed, 0 known failure, 0 skipped [inst/dist_fun/geornd.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/dist_fun/geornd.m ***** assert (size (geornd (0.5)), [1, 1]) ***** assert (size (geornd (0.5*ones (2,1))), [2, 1]) ***** assert (size (geornd (0.5*ones (2,2))), [2, 2]) ***** assert (size (geornd (0.5, 3)), [3, 3]) ***** assert (size (geornd (0.5, [4 1])), [4, 1]) ***** assert (size (geornd (0.5, 4, 1)), [4, 1]) ***** assert (class (geornd (0.5)), "double") ***** assert (class (geornd (single (0.5))), "single") ***** assert (class (geornd (single ([0.5 0.5]))), "single") ***** assert (class (geornd (single (0))), "single") ***** assert (class (geornd (single (1))), "single") ***** error geornd () ***** error geornd (i) ***** error ... geornd (1, -1) ***** error ... geornd (1, 1.2) ***** error ... geornd (1, ones (2)) ***** error ... geornd (1, [2 -1 2]) ***** error ... geornd (1, [2 0 2.5]) ***** error ... geornd (ones (2), ones (2)) ***** error ... geornd (1, 2, -1, 5) ***** error ... geornd (1, 2, 1.5, 5) ***** error geornd (ones (2,2), 3) ***** error geornd (ones (2,2), [3, 2]) ***** error geornd (ones (2,2), 2, 3) 24 tests, 24 passed, 0 known failure, 0 skipped [inst/dist_fun/laplacepdf.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/dist_fun/laplacepdf.m ***** demo ## Plot various PDFs from the Laplace distribution x = -10:0.01:10; y1 = laplacepdf (x, 0, 1); y2 = laplacepdf (x, 0, 2); y3 = laplacepdf (x, 0, 4); y4 = laplacepdf (x, -5, 4); plot (x, y1, "-b", x, y2, "-g", x, y3, "-r", x, y4, "-c") grid on xlim ([-10, 10]) ylim ([0, 0.6]) legend ({"μ = 0, β = 1", "μ = 0, β = 2", ... "μ = 0, β = 4", "μ = -5, β = 4"}, "location", "northeast") title ("Laplace PDF") xlabel ("values in x") ylabel ("density") ***** shared x, y x = [-Inf -log(2) 0 log(2) Inf]; y = [0, 1/4, 1/2, 1/4, 0]; ***** assert (laplacepdf ([x, NaN], 0, 1), [y, NaN]) ***** assert (laplacepdf (x, 0, [-2, -1, 0, 1, 2]), [nan(1, 3), 0.25, 0]) ***** assert (laplacepdf (single ([x, NaN]), 0, 1), single ([y, NaN])) ***** assert (laplacepdf ([x, NaN], single (0), 1), single ([y, NaN])) ***** assert (laplacepdf ([x, NaN], 0, single (1)), single ([y, NaN])) ***** error laplacepdf () ***** error laplacepdf (1) ***** error ... laplacepdf (1, 2) ***** error laplacepdf (1, 2, 3, 4) ***** error ... laplacepdf (1, ones (2), ones (3)) ***** error ... laplacepdf (ones (2), 1, ones (3)) ***** error ... laplacepdf (ones (2), ones (3), 1) ***** error laplacepdf (i, 2, 3) ***** error laplacepdf (1, i, 3) ***** error laplacepdf (1, 2, i) 15 tests, 15 passed, 0 known failure, 0 skipped [inst/dist_fun/poisscdf.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/dist_fun/poisscdf.m ***** demo ## Plot various CDFs from the Poisson distribution x = 0:20; p1 = poisscdf (x, 1); p2 = poisscdf (x, 4); p3 = poisscdf (x, 10); plot (x, p1, "*b", x, p2, "*g", x, p3, "*r") grid on ylim ([0, 1]) legend ({"λ = 1", "λ = 4", "λ = 10"}, "location", "southeast") title ("Poisson CDF") xlabel ("values in x (number of occurences)") ylabel ("probability") ***** shared x, y x = [-1 0 1 2 Inf]; y = [0, gammainc(1, (x(2:4) +1), "upper"), 1]; ***** assert (poisscdf (x, ones (1,5)), y) ***** assert (poisscdf (x, 1), y) ***** assert (poisscdf (x, [1 0 NaN 1 1]), [y(1) 1 NaN y(4:5)]) ***** assert (poisscdf ([x(1:2) NaN Inf x(5)], 1), [y(1:2) NaN 1 y(5)]) ***** assert (poisscdf ([x, NaN], 1), [y, NaN]) ***** assert (poisscdf (single ([x, NaN]), 1), single ([y, NaN]), eps ("single")) ***** assert (poisscdf ([x, NaN], single (1)), single ([y, NaN]), eps ("single")) ***** error poisscdf () ***** error poisscdf (1) ***** error poisscdf (1, 2, 3) ***** error poisscdf (1, 2, "tail") ***** error ... poisscdf (ones (3), ones (2)) ***** error ... poisscdf (ones (2), ones (3)) ***** error poisscdf (i, 2) ***** error poisscdf (2, i) 15 tests, 15 passed, 0 known failure, 0 skipped [inst/dist_fun/ncfrnd.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/dist_fun/ncfrnd.m ***** assert (size (ncfrnd (1, 1, 1)), [1 1]) ***** assert (size (ncfrnd (1, ones (2,1), 1)), [2, 1]) ***** assert (size (ncfrnd (1, ones (2,2), 1)), [2, 2]) ***** assert (size (ncfrnd (ones (2,1), 1, 1)), [2, 1]) ***** assert (size (ncfrnd (ones (2,2), 1, 1)), [2, 2]) ***** assert (size (ncfrnd (1, 1, 1, 3)), [3, 3]) ***** assert (size (ncfrnd (1, 1, 1, [4, 1])), [4, 1]) ***** assert (size (ncfrnd (1, 1, 1, 4, 1)), [4, 1]) ***** assert (size (ncfrnd (1, 1, 1, 4, 1, 5)), [4, 1, 5]) ***** assert (size (ncfrnd (1, 1, 1, 0, 1)), [0, 1]) ***** assert (size (ncfrnd (1, 1, 1, 1, 0)), [1, 0]) ***** assert (size (ncfrnd (1, 1, 1, 1, 2, 0, 5)), [1, 2, 0, 5]) ***** assert (class (ncfrnd (1, 1, 1)), "double") ***** assert (class (ncfrnd (1, single (1), 1)), "single") ***** assert (class (ncfrnd (1, 1, single (1))), "single") ***** assert (class (ncfrnd (1, single ([1, 1]), 1)), "single") ***** assert (class (ncfrnd (1, 1, single ([1, 1]))), "single") ***** assert (class (ncfrnd (single (1), 1, 1)), "single") ***** assert (class (ncfrnd (single ([1, 1]), 1, 1)), "single") ***** error ncfrnd () ***** error ncfrnd (1) ***** error ncfrnd (1, 2) ***** error ... ncfrnd (ones (3), ones (2), ones (2)) ***** error ... ncfrnd (ones (2), ones (3), ones (2)) ***** error ... ncfrnd (ones (2), ones (2), ones (3)) ***** error ncfrnd (i, 2, 3) ***** error ncfrnd (1, i, 3) ***** error ncfrnd (1, 2, i) ***** error ... ncfrnd (1, 2, 3, -1) ***** error ... ncfrnd (1, 2, 3, 1.2) ***** error ... ncfrnd (1, 2, 3, ones (2)) ***** error ... ncfrnd (1, 2, 3, [2 -1 2]) ***** error ... ncfrnd (1, 2, 3, [2 0 2.5]) ***** error ... ncfrnd (1, 2, 3, 2, -1, 5) ***** error ... ncfrnd (1, 2, 3, 2, 1.5, 5) ***** error ... ncfrnd (2, ones (2), 2, 3) ***** error ... ncfrnd (2, ones (2), 2, [3, 2]) ***** error ... ncfrnd (2, ones (2), 2, 3, 2) 38 tests, 38 passed, 0 known failure, 0 skipped [inst/dist_fun/wishpdf.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/dist_fun/wishpdf.m ***** assert(wishpdf(4, 3, 3.1), 0.07702496, 1E-7); ***** assert(wishpdf([2 -0.3;-0.3 4], [1 0.3;0.3 1], 4), 0.004529741, 1E-7); ***** assert(wishpdf([6 2 5; 2 10 -5; 5 -5 25], [9 5 5; 5 10 -8; 5 -8 22], 5.1), 4.474865e-10, 1E-15); ***** error wishpdf () ***** error wishpdf (1, 2) ***** error wishpdf (1, 2, 0) ***** error wishpdf (1, 2) 7 tests, 7 passed, 0 known failure, 0 skipped [inst/dist_fun/gampdf.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/dist_fun/gampdf.m ***** demo ## Plot various PDFs from the Gamma distribution x = 0:0.01:20; y1 = gampdf (x, 1, 2); y2 = gampdf (x, 2, 2); y3 = gampdf (x, 3, 2); y4 = gampdf (x, 5, 1); y5 = gampdf (x, 9, 0.5); y6 = gampdf (x, 7.5, 1); y7 = gampdf (x, 0.5, 1); plot (x, y1, "-r", x, y2, "-g", x, y3, "-y", x, y4, "-m", ... x, y5, "-k", x, y6, "-b", x, y7, "-c") grid on ylim ([0,0.5]) legend ({"α = 1, β = 2", "α = 2, β = 2", "α = 3, β = 2", ... "α = 5, β = 1", "α = 9, β = 0.5", "α = 7.5, β = 1", ... "α = 0.5, β = 1"}, "location", "northeast") title ("Gamma PDF") xlabel ("values in x") ylabel ("density") ***** shared x, y x = [-1 0 0.5 1 Inf]; y = [0 exp(-x(2:end))]; ***** assert (gampdf (x, ones (1,5), ones (1,5)), y) ***** assert (gampdf (x, 1, ones (1,5)), y) ***** assert (gampdf (x, ones (1,5), 1), y) ***** assert (gampdf (x, [0 -Inf NaN Inf 1], 1), [NaN NaN NaN NaN y(5)]) ***** assert (gampdf (x, 1, [0 -Inf NaN Inf 1]), [NaN NaN NaN 0 y(5)]) ***** assert (gampdf ([x, NaN], 1, 1), [y, NaN]) ***** assert (gampdf (single ([x, NaN]), 1, 1), single ([y, NaN])) ***** assert (gampdf ([x, NaN], single (1), 1), single ([y, NaN])) ***** assert (gampdf ([x, NaN], 1, single (1)), single ([y, NaN])) ***** error gampdf () ***** error gampdf (1) ***** error gampdf (1,2) ***** error ... gampdf (ones (3), ones (2), ones (2)) ***** error ... gampdf (ones (2), ones (3), ones (2)) ***** error ... gampdf (ones (2), ones (2), ones (3)) ***** error gampdf (i, 2, 2) ***** error gampdf (2, i, 2) ***** error gampdf (2, 2, i) 18 tests, 18 passed, 0 known failure, 0 skipped [inst/dist_fun/ricernd.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/dist_fun/ricernd.m ***** assert (size (ricernd (2, 1/2)), [1, 1]) ***** assert (size (ricernd (2 * ones (2, 1), 1/2)), [2, 1]) ***** assert (size (ricernd (2 * ones (2, 2), 1/2)), [2, 2]) ***** assert (size (ricernd (2, 1/2 * ones (2, 1))), [2, 1]) ***** assert (size (ricernd (1, 1/2 * ones (2, 2))), [2, 2]) ***** assert (size (ricernd (ones (2, 1), 1)), [2, 1]) ***** assert (size (ricernd (ones (2, 2), 1)), [2, 2]) ***** assert (size (ricernd (2, 1/2, 3)), [3, 3]) ***** assert (size (ricernd (1, 1, [4, 1])), [4, 1]) ***** assert (size (ricernd (1, 1, 4, 1)), [4, 1]) ***** assert (size (ricernd (1, 1, 4, 1, 5)), [4, 1, 5]) ***** assert (size (ricernd (1, 1, 0, 1)), [0, 1]) ***** assert (size (ricernd (1, 1, 1, 0)), [1, 0]) ***** assert (size (ricernd (1, 1, 1, 2, 0, 5)), [1, 2, 0, 5]) ***** assert (class (ricernd (1, 1)), "double") ***** assert (class (ricernd (1, single (0))), "single") ***** assert (class (ricernd (1, single ([0, 0]))), "single") ***** assert (class (ricernd (1, single (1), 2)), "single") ***** assert (class (ricernd (1, single ([1, 1]), 1, 2)), "single") ***** assert (class (ricernd (single (1), 1, 2)), "single") ***** assert (class (ricernd (single ([1, 1]), 1, 1, 2)), "single") ***** error ricernd () ***** error ricernd (1) ***** error ... ricernd (ones (3), ones (2)) ***** error ... ricernd (ones (2), ones (3)) ***** error ricernd (i, 2) ***** error ricernd (1, i) ***** error ... ricernd (1, 1/2, -1) ***** error ... ricernd (1, 1/2, 1.2) ***** error ... ricernd (1, 1/2, ones (2)) ***** error ... ricernd (1, 1/2, [2 -1 2]) ***** error ... ricernd (1, 1/2, [2 0 2.5]) ***** error ... ricernd (1, 1/2, 2, -1, 5) ***** error ... ricernd (1, 1/2, 2, 1.5, 5) ***** error ... ricernd (2, 1/2 * ones (2), 3) ***** error ... ricernd (2, 1/2 * ones (2), [3, 2]) ***** error ... ricernd (2, 1/2 * ones (2), 3, 2) ***** error ... ricernd (2 * ones (2), 1/2, 3) ***** error ... ricernd (2 * ones (2), 1/2, [3, 2]) ***** error ... ricernd (2 * ones (2), 1/2, 3, 2) 40 tests, 40 passed, 0 known failure, 0 skipped [inst/dist_fun/unidrnd.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/dist_fun/unidrnd.m ***** assert (size (unidrnd (2)), [1, 1]) ***** assert (size (unidrnd (ones (2,1))), [2, 1]) ***** assert (size (unidrnd (ones (2,2))), [2, 2]) ***** assert (size (unidrnd (1, 3)), [3, 3]) ***** assert (size (unidrnd (1, [4 1])), [4, 1]) ***** assert (size (unidrnd (1, 4, 1)), [4, 1]) ***** assert (size (unidrnd (1, 4, 1)), [4, 1]) ***** assert (size (unidrnd (1, 4, 1, 5)), [4, 1, 5]) ***** assert (size (unidrnd (1, 0, 1)), [0, 1]) ***** assert (size (unidrnd (1, 1, 0)), [1, 0]) ***** assert (size (unidrnd (1, 1, 2, 0, 5)), [1, 2, 0, 5]) ***** assert (unidrnd (0, 1, 1), NaN) ***** assert (unidrnd ([0, 0, 0], [1, 3]), [NaN, NaN, NaN]) ***** assert (class (unidrnd (2)), "double") ***** assert (class (unidrnd (single (2))), "single") ***** assert (class (unidrnd (single ([2 2]))), "single") ***** error unidrnd () ***** error unidrnd (i) ***** error ... unidrnd (1, -1) ***** error ... unidrnd (1, 1.2) ***** error ... unidrnd (1, ones (2)) ***** error ... unidrnd (1, [2 -1 2]) ***** error ... unidrnd (1, [2 0 2.5]) ***** error ... unidrnd (ones (2), ones (2)) ***** error ... unidrnd (1, 2, -1, 5) ***** error ... unidrnd (1, 2, 1.5, 5) ***** error unidrnd (ones (2,2), 3) ***** error unidrnd (ones (2,2), [3, 2]) ***** error unidrnd (ones (2,2), 2, 3) 29 tests, 29 passed, 0 known failure, 0 skipped [inst/dist_fun/wblrnd.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/dist_fun/wblrnd.m ***** assert (size (wblrnd (1, 1)), [1 1]) ***** assert (size (wblrnd (1, ones (2,1))), [2, 1]) ***** assert (size (wblrnd (1, ones (2,2))), [2, 2]) ***** assert (size (wblrnd (ones (2,1), 1)), [2, 1]) ***** assert (size (wblrnd (ones (2,2), 1)), [2, 2]) ***** assert (size (wblrnd (1, 1, 3)), [3, 3]) ***** assert (size (wblrnd (1, 1, [4, 1])), [4, 1]) ***** assert (size (wblrnd (1, 1, 4, 1)), [4, 1]) ***** assert (size (wblrnd (1, 1, 4, 1, 5)), [4, 1, 5]) ***** assert (size (wblrnd (1, 1, 0, 1)), [0, 1]) ***** assert (size (wblrnd (1, 1, 1, 0)), [1, 0]) ***** assert (size (wblrnd (1, 1, 1, 2, 0, 5)), [1, 2, 0, 5]) ***** assert (class (wblrnd (1, 1)), "double") ***** assert (class (wblrnd (1, single (1))), "single") ***** assert (class (wblrnd (1, single ([1, 1]))), "single") ***** assert (class (wblrnd (single (1), 1)), "single") ***** assert (class (wblrnd (single ([1, 1]), 1)), "single") ***** error wblrnd () ***** error wblrnd (1) ***** error ... wblrnd (ones (3), ones (2)) ***** error ... wblrnd (ones (2), ones (3)) ***** error wblrnd (i, 2, 3) ***** error wblrnd (1, i, 3) ***** error ... wblrnd (1, 2, -1) ***** error ... wblrnd (1, 2, 1.2) ***** error ... wblrnd (1, 2, ones (2)) ***** error ... wblrnd (1, 2, [2 -1 2]) ***** error ... wblrnd (1, 2, [2 0 2.5]) ***** error ... wblrnd (1, 2, 2, -1, 5) ***** error ... wblrnd (1, 2, 2, 1.5, 5) ***** error ... wblrnd (2, ones (2), 3) ***** error ... wblrnd (2, ones (2), [3, 2]) ***** error ... wblrnd (2, ones (2), 3, 2) 33 tests, 33 passed, 0 known failure, 0 skipped [inst/dist_fun/mvncdf.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/dist_fun/mvncdf.m ***** demo mu = [1, -1]; Sigma = [0.9, 0.4; 0.4, 0.3]; [X1, X2] = meshgrid (linspace (-1, 3, 25)', linspace (-3, 1, 25)'); X = [X1(:), X2(:)]; p = mvncdf (X, mu, Sigma); Z = reshape (p, 25, 25); surf (X1, X2, Z); title ("Bivariate Normal Distribution"); ylabel "X1" xlabel "X2" ***** demo mu = [0, 0]; Sigma = [0.25, 0.3; 0.3, 1]; p = mvncdf ([0 0], [1 1], mu, Sigma); x1 = -3:.2:3; x2 = -3:.2:3; [X1, X2] = meshgrid (x1, x2); X = [X1(:), X2(:)]; p = mvnpdf (X, mu, Sigma); p = reshape (p, length (x2), length (x1)); contour (x1, x2, p, [0.0001, 0.001, 0.01, 0.05, 0.15, 0.25, 0.35]); xlabel ("x"); ylabel ("p"); title ("Probability over Rectangular Region"); line ([0, 0, 1, 1, 0], [1, 0, 0, 1, 1], "Linestyle", "--", "Color", "k"); ***** test fD = (-2:2)'; X = repmat (fD, 1, 4); p = mvncdf (X); assert (p, [0; 0.0006; 0.0625; 0.5011; 0.9121], ones (5, 1) * 1e-4); ***** test mu = [1, -1]; Sigma = [0.9, 0.4; 0.4, 0.3]; [X1,X2] = meshgrid (linspace (-1, 3, 25)', linspace (-3, 1, 25)'); X = [X1(:), X2(:)]; p = mvncdf (X, mu, Sigma); p_out = [0.00011878988774500, 0.00034404112322371, ... 0.00087682502191813, 0.00195221905058185, ... 0.00378235566873474, 0.00638175749734415, ... 0.00943764224329656, 0.01239164888125426, ... 0.01472750274376648, 0.01623228313374828]'; assert (p([1:10]), p_out, 1e-16); ***** test mu = [1, -1]; Sigma = [0.9, 0.4; 0.4, 0.3]; [X1,X2] = meshgrid (linspace (-1, 3, 25)', linspace (-3, 1, 25)'); X = [X1(:), X2(:)]; p = mvncdf (X, mu, Sigma); p_out = [0.8180695783608276, 0.8854485749482751, ... 0.9308108777385832, 0.9579855743025508, ... 0.9722897881414742, 0.9788150170059926, ... 0.9813597788804785, 0.9821977956568989, ... 0.9824283794464095, 0.9824809345614861]'; assert (p([616:625]), p_out, 2e-16); ***** test mu = [0, 0]; Sigma = [0.25, 0.3; 0.3, 1]; [p, err] = mvncdf ([0 0], [1 1], mu, Sigma); assert (p, 0.2097424404755626, 1e-16); assert (err, 1e-08); ***** test x = [1 2]; mu = [0.5 1.5]; sigma = [1.0 0.5; 0.5 1.0]; p = mvncdf (x, mu, sigma); assert (p, 0.546244443857090, 1e-15); ***** test x = [1 2]; mu = [0.5 1.5]; sigma = [1.0 0.5; 0.5 1.0]; a = [-inf 0]; p = mvncdf (a, x, mu, sigma); assert (p, 0.482672935215631, 1e-15); ***** error p = mvncdf (randn (25,26), [], eye (26)); ***** error p = mvncdf (randn (25,8), [], eye (9)); ***** error p = mvncdf (randn (25,4), randn (25,5), [], eye (4)); ***** error p = mvncdf (randn (25,4), randn (25,4), [2, 3; 2, 3], eye (4)); ***** error p = mvncdf (randn (25,4), randn (25,4), ones (1, 5), eye (4)); ***** error p = mvncdf ([-inf 0], [1, 2], [0.5 1.5], [1.0 0.5; 0.5 1.0], option); 12 tests, 12 passed, 0 known failure, 0 skipped [inst/dist_fun/wblpdf.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/dist_fun/wblpdf.m ***** demo ## Plot various PDFs from the Weibul distribution x = 0:0.001:2.5; y1 = wblpdf (x, 1, 0.5); y2 = wblpdf (x, 1, 1); y3 = wblpdf (x, 1, 1.5); y4 = wblpdf (x, 1, 5); plot (x, y1, "-b", x, y2, "-r", x, y3, "-m", x, y4, "-g") grid on ylim ([0, 2.5]) legend ({"λ = 5, k = 0.5", "λ = 9, k = 1", ... "λ = 6, k = 1.5", "λ = 2, k = 5"}, "location", "northeast") title ("Weibul PDF") xlabel ("values in x") ylabel ("density") ***** shared x,y x = [-1 0 0.5 1 Inf]; y = [0, exp(-x(2:4)), NaN]; ***** assert (wblpdf (x, ones (1,5), ones (1,5)), y) ***** assert (wblpdf (x, 1, ones (1,5)), y) ***** assert (wblpdf (x, ones (1,5), 1), y) ***** assert (wblpdf (x, [0 NaN Inf 1 1], 1), [NaN NaN NaN y(4:5)]) ***** assert (wblpdf (x, 1, [0 NaN Inf 1 1]), [NaN NaN NaN y(4:5)]) ***** assert (wblpdf ([x, NaN], 1, 1), [y, NaN]) ***** assert (wblpdf (single ([x, NaN]), 1, 1), single ([y, NaN])) ***** assert (wblpdf ([x, NaN], single (1), 1), single ([y, NaN])) ***** assert (wblpdf ([x, NaN], 1, single (1)), single ([y, NaN])) ***** error wblpdf () ***** error wblpdf (1,2,3,4) ***** error wblpdf (ones (3), ones (2), ones (2)) ***** error wblpdf (ones (2), ones (3), ones (2)) ***** error wblpdf (ones (2), ones (2), ones (3)) ***** error wblpdf (i, 2, 2) ***** error wblpdf (2, i, 2) ***** error wblpdf (2, 2, i) 17 tests, 17 passed, 0 known failure, 0 skipped [inst/dist_fun/bvncdf.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/dist_fun/bvncdf.m ***** demo mu = [1, -1]; sigma = [0.9, 0.4; 0.4, 0.3]; [X1, X2] = meshgrid (linspace (-1, 3, 25)', linspace (-3, 1, 25)'); x = [X1(:), X2(:)]; p = bvncdf (x, mu, sigma); Z = reshape (p, 25, 25); surf (X1, X2, Z); title ("Bivariate Normal Distribution"); ylabel "X1" xlabel "X2" ***** test mu = [1, -1]; sigma = [0.9, 0.4; 0.4, 0.3]; [X1,X2] = meshgrid (linspace (-1, 3, 25)', linspace (-3, 1, 25)'); x = [X1(:), X2(:)]; p = bvncdf (x, mu, sigma); p_out = [0.00011878988774500, 0.00034404112322371, ... 0.00087682502191813, 0.00195221905058185, ... 0.00378235566873474, 0.00638175749734415, ... 0.00943764224329656, 0.01239164888125426, ... 0.01472750274376648, 0.01623228313374828]'; assert (p([1:10]), p_out, 1e-16); ***** test mu = [1, -1]; sigma = [0.9, 0.4; 0.4, 0.3]; [X1,X2] = meshgrid (linspace (-1, 3, 25)', linspace (-3, 1, 25)'); x = [X1(:), X2(:)]; p = bvncdf (x, mu, sigma); p_out = [0.8180695783608276, 0.8854485749482751, ... 0.9308108777385832, 0.9579855743025508, ... 0.9722897881414742, 0.9788150170059926, ... 0.9813597788804785, 0.9821977956568989, ... 0.9824283794464095, 0.9824809345614861]'; assert (p([616:625]), p_out, 2e-16); ***** error bvncdf (randn (25,3), [], [1, 1; 1, 1]); ***** error bvncdf (randn (25,2), [], [1, 1; 1, 1]); ***** error bvncdf (randn (25,2), [], ones (3, 2)); 5 tests, 5 passed, 0 known failure, 0 skipped [inst/dist_fun/gevinv.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/dist_fun/gevinv.m ***** demo ## Plot various iCDFs from the generalized extreme value distribution p = 0.001:0.001:0.999; x1 = gevinv (p, 1, 1, 1); x2 = gevinv (p, 0.5, 1, 1); x3 = gevinv (p, 1, 1, 5); x4 = gevinv (p, 1, 2, 5); x5 = gevinv (p, 1, 5, 5); x6 = gevinv (p, 1, 0.5, 5); plot (p, x1, "-b", p, x2, "-g", p, x3, "-r", ... p, x4, "-c", p, x5, "-m", p, x6, "-k") grid on ylim ([-1, 10]) legend ({"k = 1, σ = 1, μ = 1", "k = 0.5, σ = 1, μ = 1", ... "k = 1, σ = 1, μ = 5", "k = 1, σ = 2, μ = 5", ... "k = 1, σ = 5, μ = 5", "k = 1, σ = 0.5, μ = 5"}, ... "location", "northwest") title ("Generalized extreme value iCDF") xlabel ("probability") ylabel ("values in x") ***** test p = 0.1:0.1:0.9; k = 0; sigma = 1; mu = 0; x = gevinv (p, k, sigma, mu); c = gevcdf(x, k, sigma, mu); assert (c, p, 0.001); ***** test p = 0.1:0.1:0.9; k = 1; sigma = 1; mu = 0; x = gevinv (p, k, sigma, mu); c = gevcdf(x, k, sigma, mu); assert (c, p, 0.001); ***** test p = 0.1:0.1:0.9; k = 0.3; sigma = 1; mu = 0; x = gevinv (p, k, sigma, mu); c = gevcdf(x, k, sigma, mu); assert (c, p, 0.001); ***** error gevinv () ***** error gevinv (1) ***** error gevinv (1, 2) ***** error gevinv (1, 2, 3) ***** error ... gevinv (ones (3), ones (2), ones(2), ones(2)) ***** error ... gevinv (ones (2), ones (3), ones(2), ones(2)) ***** error ... gevinv (ones (2), ones (2), ones(3), ones(2)) ***** error ... gevinv (ones (2), ones (2), ones(2), ones(3)) ***** error gevinv (i, 2, 3, 4) ***** error gevinv (1, i, 3, 4) ***** error gevinv (1, 2, i, 4) ***** error gevinv (1, 2, 3, i) 15 tests, 15 passed, 0 known failure, 0 skipped [inst/dist_fun/geocdf.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/dist_fun/geocdf.m ***** demo ## Plot various CDFs from the geometric distribution x = 0:10; p1 = geocdf (x, 0.2); p2 = geocdf (x, 0.5); p3 = geocdf (x, 0.7); plot (x, p1, "*b", x, p2, "*g", x, p3, "*r") grid on xlim ([0, 10]) legend ({"ps = 0.2", "ps = 0.5", "ps = 0.7"}, "location", "southeast") title ("Geometric CDF") xlabel ("values in x (number of failures)") ylabel ("probability") ***** test p = geocdf ([1, 2, 3, 4], 0.25); assert (p(1), 0.4375000000, 1e-14); assert (p(2), 0.5781250000, 1e-14); assert (p(3), 0.6835937500, 1e-14); assert (p(4), 0.7626953125, 1e-14); ***** test p = geocdf ([1, 2, 3, 4], 0.25, "upper"); assert (p(1), 0.5625000000, 1e-14); assert (p(2), 0.4218750000, 1e-14); assert (p(3), 0.3164062500, 1e-14); assert (p(4), 0.2373046875, 1e-14); ***** shared x, p x = [-1 0 1 Inf]; p = [0 0.5 0.75 1]; ***** assert (geocdf (x, 0.5*ones (1,4)), p) ***** assert (geocdf (x, 0.5), p) ***** assert (geocdf (x, 0.5*[-1 NaN 4 1]), [NaN NaN NaN p(4)]) ***** assert (geocdf ([x(1:2) NaN x(4)], 0.5), [p(1:2) NaN p(4)]) ***** assert (geocdf ([x, NaN], 0.5), [p, NaN]) ***** assert (geocdf (single ([x, NaN]), 0.5), single ([p, NaN])) ***** assert (geocdf ([x, NaN], single (0.5)), single ([p, NaN])) ***** error geocdf () ***** error geocdf (1) ***** error ... geocdf (ones (3), ones (2)) ***** error ... geocdf (ones (2), ones (3)) ***** error geocdf (i, 2) ***** error geocdf (2, i) ***** error geocdf (2, 3, "tail") ***** error geocdf (2, 3, 5) 17 tests, 17 passed, 0 known failure, 0 skipped [inst/dist_fun/gpinv.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/dist_fun/gpinv.m ***** demo ## Plot various iCDFs from the generalized Pareto distribution p = 0.001:0.001:0.999; x1 = gpinv (p, 1, 1, 0); x2 = gpinv (p, 5, 1, 0); x3 = gpinv (p, 20, 1, 0); x4 = gpinv (p, 1, 2, 0); x5 = gpinv (p, 5, 2, 0); x6 = gpinv (p, 20, 2, 0); plot (p, x1, "-b", p, x2, "-g", p, x3, "-r", ... p, x4, "-c", p, x5, "-m", p, x6, "-k") grid on ylim ([0, 5]) legend ({"k = 1, σ = 1, θ = 0", "k = 5, σ = 1, θ = 0", ... "k = 20, σ = 1, θ = 0", "k = 1, σ = 2, θ = 0", ... "k = 5, σ = 2, θ = 0", "k = 20, σ = 2, θ = 0"}, ... "location", "southeast") title ("Generalized Pareto iCDF") xlabel ("probability") ylabel ("values in x") ***** shared p, y1, y2, y3 p = [-1, 0, 1/2, 1, 2]; y1 = [NaN, 0, 0.6931471805599453, Inf, NaN]; y2 = [NaN, 0, 1, Inf, NaN]; y3 = [NaN, 0, 1/2, 1, NaN]; ***** assert (gpinv (p, zeros (1,5), ones (1,5), zeros (1,5)), y1) ***** assert (gpinv (p, 0, 1, zeros (1,5)), y1) ***** assert (gpinv (p, 0, ones (1,5), 0), y1) ***** assert (gpinv (p, zeros (1,5), 1, 0), y1) ***** assert (gpinv (p, 0, 1, 0), y1) ***** assert (gpinv (p, 0, 1, [0, 0, NaN, 0, 0]), [y1(1:2), NaN, y1(4:5)]) ***** assert (gpinv (p, 0, [1, 1, NaN, 1, 1], 0), [y1(1:2), NaN, y1(4:5)]) ***** assert (gpinv (p, [0, 0, NaN, 0, 0], 1, 0), [y1(1:2), NaN, y1(4:5)]) ***** assert (gpinv ([p(1:2), NaN, p(4:5)], 0, 1, 0), [y1(1:2), NaN, y1(4:5)]) ***** assert (gpinv (p, ones (1,5), ones (1,5), zeros (1,5)), y2) ***** assert (gpinv (p, 1, 1, zeros (1,5)), y2) ***** assert (gpinv (p, 1, ones (1,5), 0), y2) ***** assert (gpinv (p, ones (1,5), 1, 0), y2) ***** assert (gpinv (p, 1, 1, 0), y2) ***** assert (gpinv (p, 1, 1, [0, 0, NaN, 0, 0]), [y2(1:2), NaN, y2(4:5)]) ***** assert (gpinv (p, 1, [1, 1, NaN, 1, 1], 0), [y2(1:2), NaN, y2(4:5)]) ***** assert (gpinv (p, [1, 1, NaN, 1, 1], 1, 0), [y2(1:2), NaN, y2(4:5)]) ***** assert (gpinv ([p(1:2), NaN, p(4:5)], 1, 1, 0), [y2(1:2), NaN, y2(4:5)]) ***** assert (gpinv (p, -ones (1,5), ones (1,5), zeros (1,5)), y3) ***** assert (gpinv (p, -1, 1, zeros (1,5)), y3) ***** assert (gpinv (p, -1, ones (1,5), 0), y3) ***** assert (gpinv (p, -ones (1,5), 1, 0), y3) ***** assert (gpinv (p, -1, 1, 0), y3) ***** assert (gpinv (p, -1, 1, [0, 0, NaN, 0, 0]), [y3(1:2), NaN, y3(4:5)]) ***** assert (gpinv (p, -1, [1, 1, NaN, 1, 1], 0), [y3(1:2), NaN, y3(4:5)]) ***** assert (gpinv (p, -[1, 1, NaN, 1, 1], 1, 0), [y3(1:2), NaN, y3(4:5)]) ***** assert (gpinv ([p(1:2), NaN, p(4:5)], -1, 1, 0), [y3(1:2), NaN, y3(4:5)]) ***** assert (gpinv (single ([p, NaN]), 0, 1, 0), single ([y1, NaN])) ***** assert (gpinv ([p, NaN], 0, 1, single (0)), single ([y1, NaN])) ***** assert (gpinv ([p, NaN], 0, single (1), 0), single ([y1, NaN])) ***** assert (gpinv ([p, NaN], single (0), 1, 0), single ([y1, NaN])) ***** assert (gpinv (single ([p, NaN]), 1, 1, 0), single ([y2, NaN])) ***** assert (gpinv ([p, NaN], 1, 1, single (0)), single ([y2, NaN])) ***** assert (gpinv ([p, NaN], 1, single (1), 0), single ([y2, NaN])) ***** assert (gpinv ([p, NaN], single (1), 1, 0), single ([y2, NaN])) ***** assert (gpinv (single ([p, NaN]), -1, 1, 0), single ([y3, NaN])) ***** assert (gpinv ([p, NaN], -1, 1, single (0)), single ([y3, NaN])) ***** assert (gpinv ([p, NaN], -1, single (1), 0), single ([y3, NaN])) ***** assert (gpinv ([p, NaN], single (-1), 1, 0), single ([y3, NaN])) ***** error gpinv () ***** error gpinv (1) ***** error gpinv (1, 2) ***** error gpinv (1, 2, 3) ***** error ... gpinv (ones (3), ones (2), ones(2), ones(2)) ***** error ... gpinv (ones (2), ones (3), ones(2), ones(2)) ***** error ... gpinv (ones (2), ones (2), ones(3), ones(2)) ***** error ... gpinv (ones (2), ones (2), ones(2), ones(3)) ***** error gpinv (i, 2, 3, 4) ***** error gpinv (1, i, 3, 4) ***** error gpinv (1, 2, i, 4) ***** error gpinv (1, 2, 3, i) 51 tests, 51 passed, 0 known failure, 0 skipped [inst/dist_fun/bisarnd.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/dist_fun/bisarnd.m ***** assert (size (bisarnd (1, 1)), [1 1]) ***** assert (size (bisarnd (1, ones (2,1))), [2, 1]) ***** assert (size (bisarnd (1, ones (2,2))), [2, 2]) ***** assert (size (bisarnd (ones (2,1), 1)), [2, 1]) ***** assert (size (bisarnd (ones (2,2), 1)), [2, 2]) ***** assert (size (bisarnd (1, 1, 3)), [3, 3]) ***** assert (size (bisarnd (1, 1, [4, 1])), [4, 1]) ***** assert (size (bisarnd (1, 1, 4, 1)), [4, 1]) ***** assert (size (bisarnd (1, 1, 4, 1, 5)), [4, 1, 5]) ***** assert (size (bisarnd (1, 1, 0, 1)), [0, 1]) ***** assert (size (bisarnd (1, 1, 1, 0)), [1, 0]) ***** assert (size (bisarnd (1, 1, 1, 2, 0, 5)), [1, 2, 0, 5]) ***** assert (class (bisarnd (1, 1)), "double") ***** assert (class (bisarnd (1, single (1))), "single") ***** assert (class (bisarnd (1, single ([1, 1]))), "single") ***** assert (class (bisarnd (single (1), 1)), "single") ***** assert (class (bisarnd (single ([1, 1]), 1)), "single") ***** error bisarnd () ***** error bisarnd (1) ***** error ... bisarnd (ones (3), ones (2)) ***** error ... bisarnd (ones (2), ones (3)) ***** error bisarnd (i, 2, 3) ***** error bisarnd (1, i, 3) ***** error ... bisarnd (1, 2, -1) ***** error ... bisarnd (1, 2, 1.2) ***** error ... bisarnd (1, 2, ones (2)) ***** error ... bisarnd (1, 2, [2 -1 2]) ***** error ... bisarnd (1, 2, [2 0 2.5]) ***** error ... bisarnd (1, 2, 2, -1, 5) ***** error ... bisarnd (1, 2, 2, 1.5, 5) ***** error ... bisarnd (2, ones (2), 3) ***** error ... bisarnd (2, ones (2), [3, 2]) ***** error ... bisarnd (2, ones (2), 3, 2) 33 tests, 33 passed, 0 known failure, 0 skipped [inst/dist_fun/poisspdf.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/dist_fun/poisspdf.m ***** demo ## Plot various PDFs from the Poisson distribution x = 0:20; y1 = poisspdf (x, 1); y2 = poisspdf (x, 4); y3 = poisspdf (x, 10); plot (x, y1, "*b", x, y2, "*g", x, y3, "*r") grid on ylim ([0, 0.4]) legend ({"λ = 1", "λ = 4", "λ = 10"}, "location", "northeast") title ("Poisson PDF") xlabel ("values in x (number of occurences)") ylabel ("density") ***** shared x, y x = [-1 0 1 2 Inf]; y = [0, exp(-1)*[1 1 0.5], 0]; ***** assert (poisspdf (x, ones (1,5)), y, eps) ***** assert (poisspdf (x, 1), y, eps) ***** assert (poisspdf (x, [1 0 NaN 1 1]), [y(1) NaN NaN y(4:5)], eps) ***** assert (poisspdf ([x, NaN], 1), [y, NaN], eps) ***** assert (poisspdf (single ([x, NaN]), 1), single ([y, NaN]), eps ("single")) ***** assert (poisspdf ([x, NaN], single (1)), single ([y, NaN]), eps ("single")) ***** error poisspdf () ***** error poisspdf (1) ***** error ... poisspdf (ones (3), ones (2)) ***** error ... poisspdf (ones (2), ones (3)) ***** error poisspdf (i, 2) ***** error poisspdf (2, i) 12 tests, 12 passed, 0 known failure, 0 skipped [inst/dist_fun/trirnd.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/dist_fun/trirnd.m ***** assert (size (trirnd (1, 1.5, 2)), [1, 1]) ***** assert (size (trirnd (1 * ones (2, 1), 1.5, 2)), [2, 1]) ***** assert (size (trirnd (1 * ones (2, 2), 1.5, 2)), [2, 2]) ***** assert (size (trirnd (1, 1.5 * ones (2, 1), 2)), [2, 1]) ***** assert (size (trirnd (1, 1.5 * ones (2, 2), 2)), [2, 2]) ***** assert (size (trirnd (1, 1.5, 2 * ones (2, 1))), [2, 1]) ***** assert (size (trirnd (1, 1.5, 2 * ones (2, 2))), [2, 2]) ***** assert (size (trirnd (1, 1.5, 2, 3)), [3, 3]) ***** assert (size (trirnd (1, 1.5, 2, [4, 1])), [4, 1]) ***** assert (size (trirnd (1, 1.5, 2, 4, 1)), [4, 1]) ***** assert (class (trirnd (1, 1.5, 2)), "double") ***** assert (class (trirnd (single (1), 1.5, 2)), "single") ***** assert (class (trirnd (single ([1, 1]), 1.5, 2)), "single") ***** assert (class (trirnd (1, single (1.5), 2)), "single") ***** assert (class (trirnd (1, single ([1.5, 1.5]), 2)), "single") ***** assert (class (trirnd (1, 1.5, single (1.5))), "single") ***** assert (class (trirnd (1, 1.5, single ([2, 2]))), "single") ***** error trirnd () ***** error trirnd (1) ***** error trirnd (1, 2) ***** error ... trirnd (ones (3), 5 * ones (2), ones (2)) ***** error ... trirnd (ones (2), 5 * ones (3), ones (2)) ***** error ... trirnd (ones (2), 5 * ones (2), ones (3)) ***** error trirnd (i, 5, 3) ***** error trirnd (1, 5+i, 3) ***** error trirnd (1, 5, i) ***** error ... trirnd (1, 5, 3, -1) ***** error ... trirnd (1, 5, 3, 1.2) ***** error ... trirnd (1, 5, 3, ones (2)) ***** error ... trirnd (1, 5, 3, [2 -1 2]) ***** error ... trirnd (1, 5, 3, [2 0 2.5]) ***** error ... trirnd (1, 5, 3, 2, -1, 5) ***** error ... trirnd (1, 5, 3, 2, 1.5, 5) ***** error ... trirnd (2, 5 * ones (2), 2, 3) ***** error ... trirnd (2, 5 * ones (2), 2, [3, 2]) ***** error ... trirnd (2, 5 * ones (2), 2, 3, 2) 36 tests, 36 passed, 0 known failure, 0 skipped [inst/dist_fun/burrcdf.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/dist_fun/burrcdf.m ***** demo ## Plot various CDFs from the Burr type XII distribution x = 0.001:0.001:5; p1 = burrcdf (x, 1, 1, 1); p2 = burrcdf (x, 1, 1, 2); p3 = burrcdf (x, 1, 1, 3); p4 = burrcdf (x, 1, 2, 1); p5 = burrcdf (x, 1, 3, 1); p6 = burrcdf (x, 1, 0.5, 2); plot (x, p1, "-b", x, p2, "-g", x, p3, "-r", ... x, p4, "-c", x, p5, "-m", x, p6, "-k") grid on legend ({"λ = 1, c = 1, k = 1", "λ = 1, c = 1, k = 2", ... "λ = 1, c = 1, k = 3", "λ = 1, c = 2, k = 1", ... "λ = 1, c = 3, k = 1", "λ = 1, c = 0.5, k = 2"}, ... "location", "southeast") title ("Burr type XII CDF") xlabel ("values in x") ylabel ("probability") ***** shared x, y x = [-1, 0, 1, 2, Inf]; y = [0, 0, 1/2, 2/3, 1]; ***** assert (burrcdf (x, ones(1,5), ones (1,5), ones (1,5)), y, eps) ***** assert (burrcdf (x, 1, 1, 1), y, eps) ***** assert (burrcdf (x, [1, 1, NaN, 1, 1], 1, 1), [y(1:2), NaN, y(4:5)], eps) ***** assert (burrcdf (x, 1, [1, 1, NaN, 1, 1], 1), [y(1:2), NaN, y(4:5)], eps) ***** assert (burrcdf (x, 1, 1, [1, 1, NaN, 1, 1]), [y(1:2), NaN, y(4:5)], eps) ***** assert (burrcdf ([x, NaN], 1, 1, 1), [y, NaN], eps) ***** assert (burrcdf (single ([x, NaN]), 1, 1, 1), single ([y, NaN]), eps("single")) ***** assert (burrcdf ([x, NaN], single (1), 1, 1), single ([y, NaN]), eps("single")) ***** assert (burrcdf ([x, NaN], 1, single (1), 1), single ([y, NaN]), eps("single")) ***** assert (burrcdf ([x, NaN], 1, 1, single (1)), single ([y, NaN]), eps("single")) ***** error burrcdf () ***** error burrcdf (1) ***** error burrcdf (1, 2) ***** error burrcdf (1, 2, 3) ***** error ... burrcdf (1, 2, 3, 4, 5, 6) ***** error burrcdf (1, 2, 3, 4, "tail") ***** error burrcdf (1, 2, 3, 4, 5) ***** error ... burrcdf (ones (3), ones (2), ones(2), ones(2)) ***** error ... burrcdf (ones (2), ones (3), ones(2), ones(2)) ***** error ... burrcdf (ones (2), ones (2), ones(3), ones(2)) ***** error ... burrcdf (ones (2), ones (2), ones(2), ones(3)) ***** error burrcdf (i, 2, 3, 4) ***** error burrcdf (1, i, 3, 4) ***** error burrcdf (1, 2, i, 4) ***** error burrcdf (1, 2, 3, i) 25 tests, 25 passed, 0 known failure, 0 skipped [inst/dist_fun/laplacecdf.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/dist_fun/laplacecdf.m ***** demo ## Plot various CDFs from the Laplace distribution x = -10:0.01:10; p1 = laplacecdf (x, 0, 1); p2 = laplacecdf (x, 0, 2); p3 = laplacecdf (x, 0, 4); p4 = laplacecdf (x, -5, 4); plot (x, p1, "-b", x, p2, "-g", x, p3, "-r", x, p4, "-c") grid on xlim ([-10, 10]) legend ({"μ = 0, β = 1", "μ = 0, β = 2", ... "μ = 0, β = 4", "μ = -5, β = 4"}, "location", "southeast") title ("Laplace CDF") xlabel ("values in x") ylabel ("probability") ***** shared x, y x = [-Inf, -log(2), 0, log(2), Inf]; y = [0, 1/4, 1/2, 3/4, 1]; ***** assert (laplacecdf ([x, NaN], 0, 1), [y, NaN]) ***** assert (laplacecdf (x, 0, [-2, -1, 0, 1, 2]), [nan(1, 3), 0.75, 1]) ***** assert (laplacecdf (single ([x, NaN]), 0, 1), single ([y, NaN]), eps ("single")) ***** assert (laplacecdf ([x, NaN], single (0), 1), single ([y, NaN]), eps ("single")) ***** assert (laplacecdf ([x, NaN], 0, single (1)), single ([y, NaN]), eps ("single")) ***** error laplacecdf () ***** error laplacecdf (1) ***** error ... laplacecdf (1, 2) ***** error ... laplacecdf (1, 2, 3, 4, 5) ***** error laplacecdf (1, 2, 3, "tail") ***** error laplacecdf (1, 2, 3, 4) ***** error ... laplacecdf (ones (3), ones (2), ones (2)) ***** error ... laplacecdf (ones (2), ones (3), ones (2)) ***** error ... laplacecdf (ones (2), ones (2), ones (3)) ***** error laplacecdf (i, 2, 2) ***** error laplacecdf (2, i, 2) ***** error laplacecdf (2, 2, i) 17 tests, 17 passed, 0 known failure, 0 skipped [inst/dist_fun/betarnd.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/dist_fun/betarnd.m ***** assert (size (betarnd (2, 1/2)), [1 1]) ***** assert (size (betarnd (2 * ones (2, 1), 1/2)), [2, 1]) ***** assert (size (betarnd (2 * ones (2, 2), 1/2)), [2, 2]) ***** assert (size (betarnd (2, 1/2 * ones (2, 1))), [2, 1]) ***** assert (size (betarnd (1, 1/2 * ones (2, 2))), [2, 2]) ***** assert (size (betarnd (ones (2, 1), 1)), [2, 1]) ***** assert (size (betarnd (ones (2, 2), 1)), [2, 2]) ***** assert (size (betarnd (2, 1/2, 3)), [3, 3]) ***** assert (size (betarnd (1, 1, [4, 1])), [4, 1]) ***** assert (size (betarnd (1, 1, 4, 1)), [4, 1]) ***** assert (size (betarnd (1, 1, 4, 1, 5)), [4, 1, 5]) ***** assert (size (betarnd (1, 1, 0, 1)), [0, 1]) ***** assert (size (betarnd (1, 1, 1, 0)), [1, 0]) ***** assert (size (betarnd (1, 1, 1, 2, 0, 5)), [1, 2, 0, 5]) ***** assert (class (betarnd (1, 1)), "double") ***** assert (class (betarnd (1, single (0))), "single") ***** assert (class (betarnd (1, single ([0, 0]))), "single") ***** assert (class (betarnd (1, single (1), 2)), "single") ***** assert (class (betarnd (1, single ([1, 1]), 1, 2)), "single") ***** assert (class (betarnd (single (1), 1, 2)), "single") ***** assert (class (betarnd (single ([1, 1]), 1, 1, 2)), "single") ***** error betarnd () ***** error betarnd (1) ***** error ... betarnd (ones (3), ones (2)) ***** error ... betarnd (ones (2), ones (3)) ***** error betarnd (i, 2) ***** error betarnd (1, i) ***** error ... betarnd (1, 1/2, -1) ***** error ... betarnd (1, 1/2, 1.2) ***** error ... betarnd (1, 1/2, ones (2)) ***** error ... betarnd (1, 1/2, [2 -1 2]) ***** error ... betarnd (1, 1/2, [2 0 2.5]) ***** error ... betarnd (1, 1/2, 2, -1, 5) ***** error ... betarnd (1, 1/2, 2, 1.5, 5) ***** error ... betarnd (2, 1/2 * ones (2), 3) ***** error ... betarnd (2, 1/2 * ones (2), [3, 2]) ***** error ... betarnd (2, 1/2 * ones (2), 3, 2) ***** error ... betarnd (2 * ones (2), 1/2, 3) ***** error ... betarnd (2 * ones (2), 1/2, [3, 2]) ***** error ... betarnd (2 * ones (2), 1/2, 3, 2) 40 tests, 40 passed, 0 known failure, 0 skipped [inst/dist_fun/wishrnd.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/dist_fun/wishrnd.m ***** assert(size (wishrnd (1,2)), [1, 1]); ***** assert(size (wishrnd (1,2,[])), [1, 1]); ***** assert(size (wishrnd (1,2,1)), [1, 1]); ***** assert(size (wishrnd ([],2,1)), [1, 1]); ***** assert(size (wishrnd ([3 1; 1 3], 2.00001, [], 1)), [2, 2]); ***** assert(size (wishrnd (eye(2), 2, [], 3)), [2, 2, 3]); ***** error wishrnd () ***** error wishrnd (1) ***** error wishrnd ([1; 1], 2) 9 tests, 9 passed, 0 known failure, 0 skipped [inst/dist_fun/nctcdf.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/dist_fun/nctcdf.m ***** demo ## Plot various CDFs from the noncentral Τ distribution x = -5:0.01:5; p1 = nctcdf (x, 1, 0); p2 = nctcdf (x, 4, 0); p3 = nctcdf (x, 1, 2); p4 = nctcdf (x, 4, 2); plot (x, p1, "-r", x, p2, "-g", x, p3, "-k", x, p4, "-m") grid on xlim ([-5, 5]) legend ({"df = 1, μ = 0", "df = 4, μ = 0", ... "df = 1, μ = 2", "df = 4, μ = 2"}, "location", "southeast") title ("Noncentral Τ CDF") xlabel ("values in x") ylabel ("probability") ***** demo ## Compare the noncentral T CDF with MU = 1 to the T CDF ## with the same number of degrees of freedom (10). x = -5:0.1:5; p1 = nctcdf (x, 10, 1); p2 = tcdf (x, 10); plot (x, p1, "-", x, p2, "-") grid on xlim ([-5, 5]) legend ({"Noncentral T(10,1)", "T(10)"}, "location", "southeast") title ("Noncentral T vs T CDFs") xlabel ("values in x") ylabel ("probability") ***** test x = -2:0.1:2; p = nctcdf (x, 10, 1); assert (p(1), 0.003302485766631558, 1e-14); assert (p(2), 0.004084668193532631, 1e-14); assert (p(3), 0.005052800319478737, 1e-14); assert (p(41), 0.8076115625303751, 1e-14); ***** test p = nctcdf (12, 10, 3); assert (p, 0.9997719343243797, 1e-14); ***** test p = nctcdf (2, 3, 2); assert (p, 0.4430757822176028, 1e-14); ***** test p = nctcdf (2, 3, 2, "upper"); assert (p, 0.5569242177823971, 1e-14); ***** test p = nctcdf ([3, 6], 3, 2, "upper"); assert (p, [0.3199728259444777, 0.07064855592441913], 1e-14); ***** error nctcdf () ***** error nctcdf (1) ***** error nctcdf (1, 2) ***** error nctcdf (1, 2, 3, "tail") ***** error nctcdf (1, 2, 3, 4) ***** error ... nctcdf (ones (3), ones (2), ones (2)) ***** error ... nctcdf (ones (2), ones (3), ones (2)) ***** error ... nctcdf (ones (2), ones (2), ones (3)) ***** error nctcdf (i, 2, 2) ***** error nctcdf (2, i, 2) ***** error nctcdf (2, 2, i) 16 tests, 16 passed, 0 known failure, 0 skipped [inst/dist_fun/logicdf.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/dist_fun/logicdf.m ***** demo ## Plot various CDFs from the logistic distribution x = -5:0.01:20; p1 = logicdf (x, 5, 2); p2 = logicdf (x, 9, 3); p3 = logicdf (x, 9, 4); p4 = logicdf (x, 6, 2); p5 = logicdf (x, 2, 1); plot (x, p1, "-b", x, p2, "-g", x, p3, "-r", x, p4, "-c", x, p5, "-m") grid on legend ({"μ = 5, σ = 2", "μ = 9, σ = 3", "μ = 9, σ = 4", ... "μ = 6, σ = 2", "μ = 2, σ = 1"}, "location", "southeast") title ("Logistic CDF") xlabel ("values in x") ylabel ("probability") ***** shared x, y x = [-Inf -log(3) 0 log(3) Inf]; y = [0, 1/4, 1/2, 3/4, 1]; ***** assert (logicdf ([x, NaN], 0, 1), [y, NaN], eps) ***** assert (logicdf (x, 0, [-2, -1, 0, 1, 2]), [nan(1, 3), 0.75, 1]) ***** assert (logicdf (single ([x, NaN]), 0, 1), single ([y, NaN]), eps ("single")) ***** assert (logicdf ([x, NaN], single (0), 1), single ([y, NaN]), eps ("single")) ***** assert (logicdf ([x, NaN], 0, single (1)), single ([y, NaN]), eps ("single")) ***** error logicdf () ***** error logicdf (1) ***** error ... logicdf (1, 2) ***** error logicdf (1, 2, 3, "tail") ***** error logicdf (1, 2, 3, 4) ***** error ... logicdf (1, ones (2), ones (3)) ***** error ... logicdf (ones (2), 1, ones (3)) ***** error ... logicdf (ones (2), ones (3), 1) ***** error logicdf (i, 2, 3) ***** error logicdf (1, i, 3) ***** error logicdf (1, 2, i) 16 tests, 16 passed, 0 known failure, 0 skipped [inst/dist_fun/betapdf.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/dist_fun/betapdf.m ***** demo ## Plot various PDFs from the Beta distribution x = 0.001:0.001:0.999; y1 = betapdf (x, 0.5, 0.5); y2 = betapdf (x, 5, 1); y3 = betapdf (x, 1, 3); y4 = betapdf (x, 2, 2); y5 = betapdf (x, 2, 5); plot (x, y1, "-b", x, y2, "-g", x, y3, "-r", x, y4, "-c", x, y5, "-m") grid on ylim ([0, 2.5]) legend ({"α = β = 0.5", "α = 5, β = 1", "α = 1, β = 3", ... "α = 2, β = 2", "α = 2, β = 5"}, "location", "north") title ("Beta PDF") xlabel ("values in x") ylabel ("density") ***** shared x, y x = [-1 0 0.5 1 2]; y = [0 2 1 0 0]; ***** assert (betapdf (x, ones (1, 5), 2 * ones (1, 5)), y) ***** assert (betapdf (x, 1, 2 * ones (1, 5)), y) ***** assert (betapdf (x, ones (1, 5), 2), y) ***** assert (betapdf (x, [0 NaN 1 1 1], 2), [NaN NaN y(3:5)]) ***** assert (betapdf (x, 1, 2 * [0 NaN 1 1 1]), [NaN NaN y(3:5)]) ***** assert (betapdf ([x, NaN], 1, 2), [y, NaN]) ***** assert (betapdf (single ([x, NaN]), 1, 2), single ([y, NaN])) ***** assert (betapdf ([x, NaN], single (1), 2), single ([y, NaN])) ***** assert (betapdf ([x, NaN], 1, single (2)), single ([y, NaN])) ***** test x = rand (10,1); y = 1 ./ (pi * sqrt (x .* (1 - x))); assert (betapdf (x, 1/2, 1/2), y, 1e-12); ***** assert (betapdf (0.5, 1000, 1000), 35.678, 1e-3) ***** error betapdf () ***** error betapdf (1) ***** error betapdf (1,2) ***** error betapdf (1,2,3,4) ***** error ... betapdf (ones (3), ones (2), ones (2)) ***** error ... betapdf (ones (2), ones (3), ones (2)) ***** error ... betapdf (ones (2), ones (2), ones (3)) ***** error betapdf (i, 2, 2) ***** error betapdf (2, i, 2) ***** error betapdf (2, 2, i) 21 tests, 21 passed, 0 known failure, 0 skipped [inst/dist_fun/hncdf.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/dist_fun/hncdf.m ***** demo ## Plot various CDFs from the half-normal distribution x = 0:0.001:10; p1 = hncdf (x, 0, 1); p2 = hncdf (x, 0, 2); p3 = hncdf (x, 0, 3); p4 = hncdf (x, 0, 5); plot (x, p1, "-b", x, p2, "-g", x, p3, "-r", x, p4, "-c") grid on xlim ([0, 10]) legend ({"μ = 0, σ = 1", "μ = 0, σ = 2", ... "μ = 0, σ = 3", "μ = 0, σ = 5"}, "location", "southeast") title ("Half-normal CDF") xlabel ("values in x") ylabel ("probability") ***** demo ## Plot half-normal against normal cumulative distribution function x = -5:0.001:5; p1 = hncdf (x, 0, 1); p2 = normcdf (x); plot (x, p1, "-b", x, p2, "-g") grid on xlim ([-5, 5]) legend ({"half-normal with μ = 0, σ = 1", ... "standart normal (μ = 0, σ = 1)"}, "location", "southeast") title ("Half-normal against standard normal CDF") xlabel ("values in x") ylabel ("probability") ***** shared x, p1, p1u, y2, y2u, y3, y3u x = [-Inf, -1, 0, 1/2, 1, Inf]; p1 = [0, 0, 0, 0.3829, 0.6827, 1]; p1u = [1, 1, 1, 0.6171, 0.3173, 0]; ***** assert (hncdf (x, zeros (1,6), ones (1,6)), p1, 1e-4) ***** assert (hncdf (x, 0, 1), p1, 1e-4) ***** assert (hncdf (x, 0, ones (1,6)), p1, 1e-4) ***** assert (hncdf (x, zeros (1,6), 1), p1, 1e-4) ***** assert (hncdf (x, 0, [1, 1, 1, NaN, 1, 1]), [p1(1:3), NaN, p1(5:6)], 1e-4) ***** assert (hncdf (x, [0, 0, 0, NaN, 0, 0], 1), [p1(1:3), NaN, p1(5:6)], 1e-4) ***** assert (hncdf ([x(1:3), NaN, x(5:6)], 0, 1), [p1(1:3), NaN, p1(5:6)], 1e-4) ***** assert (hncdf (x, zeros (1,6), ones (1,6), "upper"), p1u, 1e-4) ***** assert (hncdf (x, 0, 1, "upper"), p1u, 1e-4) ***** assert (hncdf (x, 0, ones (1,6), "upper"), p1u, 1e-4) ***** assert (hncdf (x, zeros (1,6), 1, "upper"), p1u, 1e-4) ***** assert (class (hncdf (single ([x, NaN]), 0, 1)), "single") ***** assert (class (hncdf ([x, NaN], 0, single (1))), "single") ***** assert (class (hncdf ([x, NaN], single (0), 1)), "single") ***** error hncdf () ***** error hncdf (1) ***** error hncdf (1, 2) ***** error hncdf (1, 2, 3, "tail") ***** error hncdf (1, 2, 3, 5) ***** error ... hncdf (ones (3), ones (2), ones(2)) ***** error ... hncdf (ones (2), ones (3), ones(2)) ***** error ... hncdf (ones (2), ones (2), ones(3)) ***** error hncdf (i, 2, 3) ***** error hncdf (1, i, 3) ***** error hncdf (1, 2, i) 25 tests, 25 passed, 0 known failure, 0 skipped [inst/dist_fun/binoinv.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/dist_fun/binoinv.m ***** demo ## Plot various iCDFs from the binomial distribution p = 0.001:0.001:0.999; x1 = binoinv (p, 20, 0.5); x2 = binoinv (p, 20, 0.7); x3 = binoinv (p, 40, 0.5); plot (p, x1, "-b", p, x2, "-g", p, x3, "-r") grid on legend ({"n = 20, ps = 0.5", "n = 20, ps = 0.7", ... "n = 40, ps = 0.5"}, "location", "southeast") title ("Binomial iCDF") xlabel ("probability") ylabel ("values in x (number of successes)") ***** shared p p = [-1 0 0.5 1 2]; ***** assert (binoinv (p, 2*ones (1,5), 0.5*ones (1,5)), [NaN 0 1 2 NaN]) ***** assert (binoinv (p, 2, 0.5*ones (1,5)), [NaN 0 1 2 NaN]) ***** assert (binoinv (p, 2*ones (1,5), 0.5), [NaN 0 1 2 NaN]) ***** assert (binoinv (p, 2*[0 -1 NaN 1.1 1], 0.5), [NaN NaN NaN NaN NaN]) ***** assert (binoinv (p, 2, 0.5*[0 -1 NaN 3 1]), [NaN NaN NaN NaN NaN]) ***** assert (binoinv ([p(1:2) NaN p(4:5)], 2, 0.5), [NaN 0 NaN 2 NaN]) ***** assert (binoinv ([p, NaN], 2, 0.5), [NaN 0 1 2 NaN NaN]) ***** assert (binoinv (single ([p, NaN]), 2, 0.5), single ([NaN 0 1 2 NaN NaN])) ***** assert (binoinv ([p, NaN], single (2), 0.5), single ([NaN 0 1 2 NaN NaN])) ***** assert (binoinv ([p, NaN], 2, single (0.5)), single ([NaN 0 1 2 NaN NaN])) ***** shared x, tol x = magic (3) + 1; tol = 1; ***** assert (binoinv (binocdf (1:10, 11, 0.1), 11, 0.1), 1:10, tol) ***** assert (binoinv (binocdf (1:10, 2*(1:10), 0.1), 2*(1:10), 0.1), 1:10, tol) ***** assert (binoinv (binocdf (x, 2*x, 1./x), 2*x, 1./x), x, tol) ***** error binoinv () ***** error binoinv (1) ***** error binoinv (1,2) ***** error binoinv (1,2,3,4) ***** error ... binoinv (ones (3), ones (2), ones (2)) ***** error ... binoinv (ones (2), ones (3), ones (2)) ***** error ... binoinv (ones (2), ones (2), ones (3)) ***** error binoinv (i, 2, 2) ***** error binoinv (2, i, 2) ***** error binoinv (2, 2, i) 23 tests, 23 passed, 0 known failure, 0 skipped [inst/dist_fun/hnrnd.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/dist_fun/hnrnd.m ***** assert (size (hnrnd (1, 1, 1)), [1, 1]) ***** assert (size (hnrnd (1, 1, 2)), [2, 2]) ***** assert (size (hnrnd (1, 1, [2, 1])), [2, 1]) ***** assert (size (hnrnd (1, zeros (2, 2))), [2, 2]) ***** assert (size (hnrnd (1, ones (2, 1))), [2, 1]) ***** assert (size (hnrnd (1, ones (2, 2))), [2, 2]) ***** assert (size (hnrnd (ones (2, 1), 1)), [2, 1]) ***** assert (size (hnrnd (ones (2, 2), 1)), [2, 2]) ***** assert (size (hnrnd (1, 1, 3)), [3, 3]) ***** assert (size (hnrnd (1, 1, [4 1])), [4, 1]) ***** assert (size (hnrnd (1, 1, 4, 1)), [4, 1]) ***** test r = hnrnd (1, [1, 0, -1]); assert (r([2:3]), [NaN, NaN]) ***** assert (class (hnrnd (1, 0)), "double") ***** assert (class (hnrnd (1, single (0))), "single") ***** assert (class (hnrnd (1, single ([0 0]))), "single") ***** assert (class (hnrnd (1, single (1))), "single") ***** assert (class (hnrnd (1, single ([1 1]))), "single") ***** assert (class (hnrnd (single (1), 1)), "single") ***** assert (class (hnrnd (single ([1 1]), 1)), "single") ***** error hnrnd () ***** error hnrnd (1) ***** error ... hnrnd (ones (3), ones (2)) ***** error ... hnrnd (ones (2), ones (3)) ***** error hnrnd (i, 2, 3) ***** error hnrnd (1, i, 3) ***** error ... hnrnd (1, 2, -1) ***** error ... hnrnd (1, 2, 1.2) ***** error ... hnrnd (1, 2, ones (2)) ***** error ... hnrnd (1, 2, [2 -1 2]) ***** error ... hnrnd (1, 2, [2 0 2.5]) ***** error ... hnrnd (1, 2, 2, -1, 5) ***** error ... hnrnd (1, 2, 2, 1.5, 5) ***** error ... hnrnd (2, ones (2), 3) ***** error ... hnrnd (2, ones (2), [3, 2]) ***** error ... hnrnd (2, ones (2), 3, 2) 35 tests, 35 passed, 0 known failure, 0 skipped [inst/dist_fun/expcdf.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/dist_fun/expcdf.m ***** demo ## Plot various CDFs from the exponential distribution x = 0:0.01:5; p1 = expcdf (x, 2/3); p2 = expcdf (x, 1.0); p3 = expcdf (x, 2.0); plot (x, p1, "-b", x, p2, "-g", x, p3, "-r") grid on legend ({"μ = 2/3", "μ = 1", "μ = 2"}, "location", "southeast") title ("Exponential CDF") xlabel ("values in x") ylabel ("probability") ***** shared x, p x = [-1 0 0.5 1 Inf]; p = [0, 1 - exp(-x(2:end)/2)]; ***** assert (expcdf (x, 2*ones (1,5)), p) ***** assert (expcdf (x, 2), p) ***** assert (expcdf (x, 2*[1 0 NaN 1 1]), [0 NaN NaN p(4:5)]) ***** assert (expcdf ([x, NaN], 2), [p, NaN]) ***** assert (expcdf (single ([x, NaN]), 2), single ([p, NaN])) ***** assert (expcdf ([x, NaN], single (2)), single ([p, NaN])) ***** test [p, plo, pup] = expcdf (1, 2, 3); assert (p, 0.39346934028737, 1e-14); assert (plo, 0.08751307220484, 1e-14); assert (pup, 0.93476821257933, 1e-14); ***** test [p, plo, pup] = expcdf (1, 2, 2, 0.1); assert (p, 0.39346934028737, 1e-14); assert (plo, 0.14466318041675, 1e-14); assert (pup, 0.79808291849140, 1e-14); ***** test [p, plo, pup] = expcdf (1, 2, 2, 0.1, "upper"); assert (p, 0.60653065971263, 1e-14); assert (plo, 0.20191708150860, 1e-14); assert (pup, 0.85533681958325, 1e-14); ***** error expcdf () ***** error expcdf (1, 2 ,3 ,4 ,5, 6) ***** error expcdf (1, 2, 3, 4, "uper") ***** error ... expcdf (ones (3), ones (2)) ***** error ... expcdf (2, 3, [1, 2]) ***** error ... [p, plo, pup] = expcdf (1, 2) ***** error [p, plo, pup] = ... expcdf (1, 2, 3, 0) ***** error [p, plo, pup] = ... expcdf (1, 2, 3, 1.22) ***** error [p, plo, pup] = ... expcdf (1, 2, 3, "alpha", "upper") ***** error expcdf (i, 2) ***** error expcdf (2, i) ***** error ... [p, plo, pup] = expcdf (1, 2, -1, 0.04) 21 tests, 21 passed, 0 known failure, 0 skipped [inst/dist_fun/vminv.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/dist_fun/vminv.m ***** demo ## Plot various iCDFs from the von Mises distribution p1 = [0,0.005,0.01:0.01:0.1,0.15,0.2:0.1:0.8,0.85,0.9:0.01:0.99,0.995,1]; x1 = vminv (p1, 0, 0.5); x2 = vminv (p1, 0, 1); x3 = vminv (p1, 0, 2); x4 = vminv (p1, 0, 4); plot (p1, x1, "-r", p1, x2, "-g", p1, x3, "-b", p1, x4, "-c") grid on ylim ([-pi, pi]) legend ({"μ = 0, k = 0.5", "μ = 0, k = 1", ... "μ = 0, k = 2", "μ = 0, k = 4"}, "location", "northwest") title ("Von Mises iCDF") xlabel ("probability") ylabel ("values in x") ***** shared x, p0, p1 x = [-pi:pi/2:pi]; p0 = [0, 0.10975, 0.5, 0.89025, 1]; p1 = [0, 0.03752, 0.5, 0.99622, 1]; ***** assert (vminv (p0, 0, 1), x, 5e-5) ***** assert (vminv (p0, zeros (1,5), ones (1,5)), x, 5e-5) ***** assert (vminv (p1, 0, [1 2 3 4 5]), x, [5e-5, 5e-4, 5e-5, 5e-4, 5e-5]) ***** error vminv () ***** error vminv (1) ***** error vminv (1, 2) ***** error ... vminv (ones (3), ones (2), ones (2)) ***** error ... vminv (ones (2), ones (3), ones (2)) ***** error ... vminv (ones (2), ones (2), ones (3)) ***** error vminv (i, 2, 2) ***** error vminv (2, i, 2) ***** error vminv (2, 2, i) 12 tests, 12 passed, 0 known failure, 0 skipped [inst/dist_fun/logninv.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/dist_fun/logninv.m ***** demo ## Plot various iCDFs from the log-normal distribution p = 0.001:0.001:0.999; x1 = logninv (p, 0, 1); x2 = logninv (p, 0, 0.5); x3 = logninv (p, 0, 0.25); plot (p, x1, "-b", p, x2, "-g", p, x3, "-r") grid on ylim ([0, 3]) legend ({"μ = 0, σ = 1", "μ = 0, σ = 0.5", "μ = 0, σ = 0.25"}, ... "location", "northwest") title ("Log-normal iCDF") xlabel ("probability") ylabel ("values in x") ***** shared p p = [-1 0 0.5 1 2]; ***** assert (logninv (p, ones (1,5), ones (1,5)), [NaN 0 e Inf NaN]) ***** assert (logninv (p, 1, ones (1,5)), [NaN 0 e Inf NaN]) ***** assert (logninv (p, ones (1,5), 1), [NaN 0 e Inf NaN]) ***** assert (logninv (p, [1 1 NaN 0 1], 1), [NaN 0 NaN Inf NaN]) ***** assert (logninv (p, 1, [1 0 NaN Inf 1]), [NaN NaN NaN NaN NaN]) ***** assert (logninv ([p(1:2) NaN p(4:5)], 1, 2), [NaN 0 NaN Inf NaN]) ***** assert (logninv ([p, NaN], 1, 1), [NaN 0 e Inf NaN NaN]) ***** assert (logninv (single ([p, NaN]), 1, 1), single ([NaN 0 e Inf NaN NaN])) ***** assert (logninv ([p, NaN], single (1), 1), single ([NaN 0 e Inf NaN NaN])) ***** assert (logninv ([p, NaN], 1, single (1)), single ([NaN 0 e Inf NaN NaN])) ***** error logninv () ***** error logninv (1,2,3,4) ***** error logninv (ones (3), ones (2), ones (2)) ***** error logninv (ones (2), ones (3), ones (2)) ***** error logninv (ones (2), ones (2), ones (3)) ***** error logninv (i, 2, 2) ***** error logninv (2, i, 2) ***** error logninv (2, 2, i) 18 tests, 18 passed, 0 known failure, 0 skipped [inst/dist_fun/loglinv.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/dist_fun/loglinv.m ***** demo ## Plot various iCDFs from the log-logistic distribution p = 0.001:0.001:0.999; x1 = loglinv (p, log (1), 1/0.5); x2 = loglinv (p, log (1), 1); x3 = loglinv (p, log (1), 1/2); x4 = loglinv (p, log (1), 1/4); x5 = loglinv (p, log (1), 1/8); plot (p, x1, "-b", p, x2, "-g", p, x3, "-r", p, x4, "-c", p, x5, "-m") ylim ([0, 20]) grid on legend ({"σ = 2 (β = 0.5)", "σ = 1 (β = 1)", "σ = 0.5 (β = 2)", ... "σ = 0.25 (β = 4)", "σ = 0.125 (β = 8)"}, "location", "northwest") title ("Log-logistic iCDF") xlabel ("probability") ylabel ("x") text (0.03, 12.5, "μ = 0 (α = 1), values of σ (β) as shown in legend") ***** shared p, out1, out2 p = [-1, 0, 0.2, 0.5, 0.8, 0.95, 1, 2]; out1 = [NaN, 0, 0.25, 1, 4, 19, Inf, NaN]; out2 = [NaN, 0, 0.0424732, 2.718282, 173.970037, 18644.695061, Inf, NaN]; ***** assert (loglinv (p, 0, 1), out1, 1e-8) ***** assert (loglinv (p, 0, 1), out1, 1e-8) ***** assert (loglinv (p, 1, 3), out2, 1e-6) ***** assert (class (loglinv (single (1), 2, 3)), "single") ***** assert (class (loglinv (1, single (2), 3)), "single") ***** assert (class (loglinv (1, 2, single (3))), "single") ***** error loglinv (1) ***** error loglinv (1, 2) ***** error ... loglinv (1, ones (2), ones (3)) ***** error ... loglinv (ones (2), 1, ones (3)) ***** error ... loglinv (ones (2), ones (3), 1) ***** error loglinv (i, 2, 3) ***** error loglinv (1, i, 3) ***** error loglinv (1, 2, i) 14 tests, 14 passed, 0 known failure, 0 skipped [inst/dist_fun/nbininv.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/dist_fun/nbininv.m ***** demo ## Plot various iCDFs from the negative binomial distribution p = 0.001:0.001:0.999; x1 = nbininv (p, 2, 0.15); x2 = nbininv (p, 5, 0.2); x3 = nbininv (p, 4, 0.4); x4 = nbininv (p, 10, 0.3); plot (p, x1, "-r", p, x2, "-g", p, x3, "-k", p, x4, "-m") grid on ylim ([0, 40]) legend ({"r = 2, ps = 0.15", "r = 5, ps = 0.2", "r = 4, p = 0.4", ... "r = 10, ps = 0.3"}, "location", "northwest") title ("Negative binomial iCDF") xlabel ("probability") ylabel ("values in x (number of failures)") ***** shared p p = [-1 0 3/4 1 2]; ***** assert (nbininv (p, ones (1,5), 0.5*ones (1,5)), [NaN 0 1 Inf NaN]) ***** assert (nbininv (p, 1, 0.5*ones (1,5)), [NaN 0 1 Inf NaN]) ***** assert (nbininv (p, ones (1,5), 0.5), [NaN 0 1 Inf NaN]) ***** assert (nbininv (p, [1 0 NaN Inf 1], 0.5), [NaN NaN NaN NaN NaN]) ***** assert (nbininv (p, [1 0 1.5 Inf 1], 0.5), [NaN NaN 2 NaN NaN]) ***** assert (nbininv (p, 1, 0.5*[1 -Inf NaN Inf 1]), [NaN NaN NaN NaN NaN]) ***** assert (nbininv ([p(1:2) NaN p(4:5)], 1, 0.5), [NaN 0 NaN Inf NaN]) ***** assert (nbininv ([p, NaN], 1, 0.5), [NaN 0 1 Inf NaN NaN]) ***** assert (nbininv (single ([p, NaN]), 1, 0.5), single ([NaN 0 1 Inf NaN NaN])) ***** assert (nbininv ([p, NaN], single (1), 0.5), single ([NaN 0 1 Inf NaN NaN])) ***** assert (nbininv ([p, NaN], 1, single (0.5)), single ([NaN 0 1 Inf NaN NaN])) ***** shared y, tol y = magic (3) + 1; tol = 1; ***** assert (nbininv (nbincdf (1:10, 3, 0.1), 3, 0.1), 1:10, tol) ***** assert (nbininv (nbincdf (1:10, 3./(1:10), 0.1), 3./(1:10), 0.1), 1:10, tol) ***** assert (nbininv (nbincdf (y, 3./y, 1./y), 3./y, 1./y), y, tol) ***** error nbininv () ***** error nbininv (1) ***** error nbininv (1, 2) ***** error ... nbininv (ones (3), ones (2), ones (2)) ***** error ... nbininv (ones (2), ones (3), ones (2)) ***** error ... nbininv (ones (2), ones (2), ones (3)) ***** error nbininv (i, 2, 2) ***** error nbininv (2, i, 2) ***** error nbininv (2, 2, i) 23 tests, 23 passed, 0 known failure, 0 skipped [inst/dist_fun/gumbelcdf.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/dist_fun/gumbelcdf.m ***** demo ## Plot various CDFs from the Gumbel distribution x = -5:0.01:20; p1 = gumbelcdf (x, 0.5, 2); p2 = gumbelcdf (x, 1.0, 2); p3 = gumbelcdf (x, 1.5, 3); p4 = gumbelcdf (x, 3.0, 4); plot (x, p1, "-b", x, p2, "-g", x, p3, "-r", x, p4, "-c") grid on legend ({"μ = 0.5, β = 2", "μ = 1.0, β = 2", ... "μ = 1.5, β = 3", "μ = 3.0, β = 4"}, "location", "southeast") title ("Gumbel CDF") xlabel ("values in x") ylabel ("probability") ***** shared x, y x = [-Inf, 1, 2, Inf]; y = [0, 0.3679, 0.6922, 1]; ***** assert (gumbelcdf (x, ones (1,4), ones (1,4)), y, 1e-4) ***** assert (gumbelcdf (x, 1, ones (1,4)), y, 1e-4) ***** assert (gumbelcdf (x, ones (1,4), 1), y, 1e-4) ***** assert (gumbelcdf (x, [0, -Inf, NaN, Inf], 1), [0, 1, NaN, NaN], 1e-4) ***** assert (gumbelcdf (x, 1, [Inf, NaN, -1, 0]), [NaN, NaN, NaN, NaN], 1e-4) ***** assert (gumbelcdf ([x(1:2), NaN, x(4)], 1, 1), [y(1:2), NaN, y(4)], 1e-4) ***** assert (gumbelcdf (x, "upper"), [1, 0.3078, 0.1266, 0], 1e-4) ***** assert (gumbelcdf ([x, NaN], 1, 1), [y, NaN], 1e-4) ***** assert (gumbelcdf (single ([x, NaN]), 1, 1), single ([y, NaN]), 1e-4) ***** assert (gumbelcdf ([x, NaN], single (1), 1), single ([y, NaN]), 1e-4) ***** assert (gumbelcdf ([x, NaN], 1, single (1)), single ([y, NaN]), 1e-4) ***** error gumbelcdf () ***** error gumbelcdf (1,2,3,4,5,6,7) ***** error gumbelcdf (1, 2, 3, 4, "uper") ***** error ... gumbelcdf (ones (3), ones (2), ones (2)) ***** error gumbelcdf (2, 3, 4, [1, 2]) ***** error ... [p, plo, pup] = gumbelcdf (1, 2, 3) ***** error [p, plo, pup] = ... gumbelcdf (1, 2, 3, [1, 0; 0, 1], 0) ***** error [p, plo, pup] = ... gumbelcdf (1, 2, 3, [1, 0; 0, 1], 1.22) ***** error [p, plo, pup] = ... gumbelcdf (1, 2, 3, [1, 0; 0, 1], "alpha", "upper") ***** error gumbelcdf (i, 2, 2) ***** error gumbelcdf (2, i, 2) ***** error gumbelcdf (2, 2, i) ***** error ... [p, plo, pup] = gumbelcdf (1, 2, 3, [1, 0; 0, -inf], 0.04) 24 tests, 24 passed, 0 known failure, 0 skipped [inst/dist_fun/riceinv.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/dist_fun/riceinv.m ***** demo ## Plot various iCDFs from the Rician distribution p = 0.001:0.001:0.999; x1 = riceinv (p, 0, 1); x2 = riceinv (p, 0.5, 1); x3 = riceinv (p, 1, 1); x4 = riceinv (p, 2, 1); x5 = riceinv (p, 4, 1); plot (p, x1, "-b", p, x2, "-g", p, x3, "-r", p, x4, "-m", p, x5, "-k") grid on legend ({"s = 0, σ = 1", "s = 0.5, σ = 1", "s = 1, σ = 1", ... "s = 2, σ = 1", "s = 4, σ = 1"}, "location", "northwest") title ("Rician iCDF") xlabel ("probability") ylabel ("values in x") ***** shared p p = [-1 0 0.75 1 2]; ***** assert (riceinv (p, ones (1,5), 2*ones (1,5)), [NaN 0 3.5354 Inf NaN], 1e-4) ***** assert (riceinv (p, 1, 2*ones (1,5)), [NaN 0 3.5354 Inf NaN], 1e-4) ***** assert (riceinv (p, ones (1,5), 2), [NaN 0 3.5354 Inf NaN], 1e-4) ***** assert (riceinv (p, [1 0 NaN 1 1], 2), [NaN 0 NaN Inf NaN]) ***** assert (riceinv (p, 1, 2*[1 0 NaN 1 1]), [NaN NaN NaN Inf NaN]) ***** assert (riceinv ([p(1:2) NaN p(4:5)], 1, 2), [NaN 0 NaN Inf NaN]) ***** assert (riceinv ([p, NaN], 1, 2), [NaN 0 3.5354 Inf NaN NaN], 1e-4) ***** assert (riceinv (single ([p, NaN]), 1, 2), ... single ([NaN 0 3.5354 Inf NaN NaN]), 1e-4) ***** assert (riceinv ([p, NaN], single (1), 2), ... single ([NaN 0 3.5354 Inf NaN NaN]), 1e-4) ***** assert (riceinv ([p, NaN], 1, single (2)), ... single ([NaN 0 3.5354 Inf NaN NaN]), 1e-4) ***** error riceinv () ***** error riceinv (1) ***** error riceinv (1,2) ***** error riceinv (1,2,3,4) ***** error ... riceinv (ones (3), ones (2), ones (2)) ***** error ... riceinv (ones (2), ones (3), ones (2)) ***** error ... riceinv (ones (2), ones (2), ones (3)) ***** error riceinv (i, 2, 2) ***** error riceinv (2, i, 2) ***** error riceinv (2, 2, i) 20 tests, 20 passed, 0 known failure, 0 skipped [inst/dist_fun/betainv.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/dist_fun/betainv.m ***** demo ## Plot various iCDFs from the Beta distribution p = 0.001:0.001:0.999; x1 = betainv (p, 0.5, 0.5); x2 = betainv (p, 5, 1); x3 = betainv (p, 1, 3); x4 = betainv (p, 2, 2); x5 = betainv (p, 2, 5); plot (p, x1, "-b", p, x2, "-g", p, x3, "-r", p, x4, "-c", p, x5, "-m") grid on legend ({"α = β = 0.5", "α = 5, β = 1", "α = 1, β = 3", ... "α = 2, β = 2", "α = 2, β = 5"}, "location", "southeast") title ("Beta iCDF") xlabel ("probability") ylabel ("values in x") ***** shared p p = [-1 0 0.75 1 2]; ***** assert (betainv (p, ones (1,5), 2*ones (1,5)), [NaN 0 0.5 1 NaN], eps) ***** assert (betainv (p, 1, 2*ones (1,5)), [NaN 0 0.5 1 NaN], eps) ***** assert (betainv (p, ones (1,5), 2), [NaN 0 0.5 1 NaN], eps) ***** assert (betainv (p, [1 0 NaN 1 1], 2), [NaN NaN NaN 1 NaN]) ***** assert (betainv (p, 1, 2*[1 0 NaN 1 1]), [NaN NaN NaN 1 NaN]) ***** assert (betainv ([p(1:2) NaN p(4:5)], 1, 2), [NaN 0 NaN 1 NaN]) ***** assert (betainv ([p, NaN], 1, 2), [NaN 0 0.5 1 NaN NaN], eps) ***** assert (betainv (single ([p, NaN]), 1, 2), single ([NaN 0 0.5 1 NaN NaN])) ***** assert (betainv ([p, NaN], single (1), 2), single ([NaN 0 0.5 1 NaN NaN]), eps("single")) ***** assert (betainv ([p, NaN], 1, single (2)), single ([NaN 0 0.5 1 NaN NaN]), eps("single")) ***** error betainv () ***** error betainv (1) ***** error betainv (1,2) ***** error betainv (1,2,3,4) ***** error ... betainv (ones (3), ones (2), ones (2)) ***** error ... betainv (ones (2), ones (3), ones (2)) ***** error ... betainv (ones (2), ones (2), ones (3)) ***** error betainv (i, 2, 2) ***** error betainv (2, i, 2) ***** error betainv (2, 2, i) 20 tests, 20 passed, 0 known failure, 0 skipped [inst/dist_fun/evrnd.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/dist_fun/evrnd.m ***** assert (size (evrnd (1, 1)), [1 1]) ***** assert (size (evrnd (1, ones (2,1))), [2, 1]) ***** assert (size (evrnd (1, ones (2,2))), [2, 2]) ***** assert (size (evrnd (ones (2,1), 1)), [2, 1]) ***** assert (size (evrnd (ones (2,2), 1)), [2, 2]) ***** assert (size (evrnd (1, 1, 3)), [3, 3]) ***** assert (size (evrnd (1, 1, [4, 1])), [4, 1]) ***** assert (size (evrnd (1, 1, 4, 1)), [4, 1]) ***** assert (size (evrnd (1, 1, 4, 1, 5)), [4, 1, 5]) ***** assert (size (evrnd (1, 1, 0, 1)), [0, 1]) ***** assert (size (evrnd (1, 1, 1, 0)), [1, 0]) ***** assert (size (evrnd (1, 1, 1, 2, 0, 5)), [1, 2, 0, 5]) ***** assert (class (evrnd (1, 1)), "double") ***** assert (class (evrnd (1, single (1))), "single") ***** assert (class (evrnd (1, single ([1, 1]))), "single") ***** assert (class (evrnd (single (1), 1)), "single") ***** assert (class (evrnd (single ([1, 1]), 1)), "single") ***** error evrnd () ***** error evrnd (1) ***** error ... evrnd (ones (3), ones (2)) ***** error ... evrnd (ones (2), ones (3)) ***** error evrnd (i, 2, 3) ***** error evrnd (1, i, 3) ***** error ... evrnd (1, 2, -1) ***** error ... evrnd (1, 2, 1.2) ***** error ... evrnd (1, 2, ones (2)) ***** error ... evrnd (1, 2, [2 -1 2]) ***** error ... evrnd (1, 2, [2 0 2.5]) ***** error ... evrnd (1, 2, 2, -1, 5) ***** error ... evrnd (1, 2, 2, 1.5, 5) ***** error ... evrnd (2, ones (2), 3) ***** error ... evrnd (2, ones (2), [3, 2]) ***** error ... evrnd (2, ones (2), 3, 2) 33 tests, 33 passed, 0 known failure, 0 skipped [inst/dist_fun/burrrnd.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/dist_fun/burrrnd.m ***** assert (size (burrrnd (1, 1, 1)), [1 1]) ***** assert (size (burrrnd (ones (2,1), 1, 1)), [2, 1]) ***** assert (size (burrrnd (ones (2,2), 1, 1)), [2, 2]) ***** assert (size (burrrnd (1, ones (2,1), 1)), [2, 1]) ***** assert (size (burrrnd (1, ones (2,2), 1)), [2, 2]) ***** assert (size (burrrnd (1, 1, ones (2,1))), [2, 1]) ***** assert (size (burrrnd (1, 1, ones (2,2))), [2, 2]) ***** assert (size (burrrnd (1, 1, 1, 3)), [3, 3]) ***** assert (size (burrrnd (1, 1, 1, [4 1])), [4, 1]) ***** assert (size (burrrnd (1, 1, 1, 4, 1)), [4, 1]) ***** assert (class (burrrnd (1,1,1)), "double") ***** assert (class (burrrnd (single (1),1,1)), "single") ***** assert (class (burrrnd (single ([1 1]),1,1)), "single") ***** assert (class (burrrnd (1,single (1),1)), "single") ***** assert (class (burrrnd (1,single ([1 1]),1)), "single") ***** assert (class (burrrnd (1,1,single (1))), "single") ***** assert (class (burrrnd (1,1,single ([1 1]))), "single") ***** error burrrnd () ***** error burrrnd (1) ***** error burrrnd (1, 2) ***** error ... burrrnd (ones (3), ones (2), ones (2)) ***** error ... burrrnd (ones (2), ones (3), ones (2)) ***** error ... burrrnd (ones (2), ones (2), ones (3)) ***** error burrrnd (i, 2, 3) ***** error burrrnd (1, i, 3) ***** error burrrnd (1, 2, i) ***** error ... burrrnd (1, 2, 3, -1) ***** error ... burrrnd (1, 2, 3, 1.2) ***** error ... burrrnd (1, 2, 3, ones (2)) ***** error ... burrrnd (1, 2, 3, [2 -1 2]) ***** error ... burrrnd (1, 2, 3, [2 0 2.5]) ***** error ... burrrnd (1, 2, 3, 2, -1, 5) ***** error ... burrrnd (1, 2, 3, 2, 1.5, 5) ***** error ... burrrnd (2, ones (2), 2, 3) ***** error ... burrrnd (2, ones (2), 2, [3, 2]) ***** error ... burrrnd (2, ones (2), 2, 3, 2) 36 tests, 36 passed, 0 known failure, 0 skipped [inst/dist_fun/mvtcdfqmc.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/dist_fun/mvtcdfqmc.m ***** error mvtcdfqmc (1, 2, 3); ***** error mvtcdfqmc (1, 2, 3, 4, 5, 6, 7, 8); 2 tests, 2 passed, 0 known failure, 0 skipped [inst/dist_fun/bisainv.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/dist_fun/bisainv.m ***** demo ## Plot various iCDFs from the Birnbaum-Saunders distribution p = 0.001:0.001:0.999; x1 = bisainv (p, 1, 0.5); x2 = bisainv (p, 1, 1); x3 = bisainv (p, 1, 2); x4 = bisainv (p, 1, 5); x5 = bisainv (p, 1, 10); plot (p, x1, "-b", p, x2, "-g", p, x3, "-r", p, x4, "-c", p, x5, "-m") grid on ylim ([0, 10]) legend ({"β = 1, γ = 0.5", "β = 1, γ = 1", "β = 1, γ = 2", ... "β = 1, γ = 5", "β = 1, γ = 10"}, "location", "northwest") title ("Birnbaum-Saunders iCDF") xlabel ("probability") ylabel ("values in x") ***** demo ## Plot various iCDFs from the Birnbaum-Saunders distribution p = 0.001:0.001:0.999; x1 = bisainv (p, 1, 0.3); x2 = bisainv (p, 2, 0.3); x3 = bisainv (p, 1, 0.5); x4 = bisainv (p, 3, 0.5); x5 = bisainv (p, 5, 0.5); plot (p, x1, "-b", p, x2, "-g", p, x3, "-r", p, x4, "-c", p, x5, "-m") grid on ylim ([0, 10]) legend ({"β = 1, γ = 0.3", "β = 2, γ = 0.3", "β = 1, γ = 0.5", ... "β = 3, γ = 0.5", "β = 5, γ = 0.5"}, "location", "northwest") title ("Birnbaum-Saunders iCDF") xlabel ("probability") ylabel ("values in x") ***** shared p, y, f f = @(p,b,c) (b * (c * norminv (p) + sqrt (4 + (c * norminv(p))^2))^2) / 4; p = [-1, 0, 1/4, 1/2, 1, 2]; y = [NaN, 0, f(1/4, 1, 1), 1, Inf, NaN]; ***** assert (bisainv (p, ones (1,6), ones (1,6)), y) ***** assert (bisainv (p, 1, ones (1,6)), y) ***** assert (bisainv (p, ones (1,6), 1), y) ***** assert (bisainv (p, 1, 1), y) ***** assert (bisainv (p, 1, [1, 1, 1, NaN, 1, 1]), [y(1:3), NaN, y(5:6)]) ***** assert (bisainv (p, [1, 1, 1, NaN, 1, 1], 1), [y(1:3), NaN, y(5:6)]) ***** assert (bisainv ([p, NaN], 1, 1), [y, NaN]) ***** assert (bisainv (single ([p, NaN]), 1, 1), single ([y, NaN]), eps ("single")) ***** assert (bisainv ([p, NaN], 1, single (1)), single ([y, NaN]), eps ("single")) ***** assert (bisainv ([p, NaN], single (1), 1), single ([y, NaN]), eps ("single")) ***** error bisainv () ***** error bisainv (1) ***** error bisainv (1, 2) ***** error bisainv (1, 2, 3, 4) ***** error ... bisainv (ones (3), ones (2), ones(2)) ***** error ... bisainv (ones (2), ones (3), ones(2)) ***** error ... bisainv (ones (2), ones (2), ones(3)) ***** error bisainv (i, 4, 3) ***** error bisainv (1, i, 3) ***** error bisainv (1, 4, i) 20 tests, 20 passed, 0 known failure, 0 skipped [inst/dist_fun/raylinv.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/dist_fun/raylinv.m ***** demo ## Plot various iCDFs from the Rayleigh distribution p = 0.001:0.001:0.999; x1 = raylinv (p, 0.5); x2 = raylinv (p, 1); x3 = raylinv (p, 2); x4 = raylinv (p, 3); x5 = raylinv (p, 4); plot (p, x1, "-b", p, x2, "g", p, x3, "-r", p, x4, "-m", p, x5, "-k") grid on ylim ([0, 10]) legend ({"σ = 0,5", "σ = 1", "σ = 2", ... "σ = 3", "σ = 4"}, "location", "northwest") title ("Rayleigh iCDF") xlabel ("probability") ylabel ("values in x") ***** test p = 0:0.1:0.5; sigma = 1:6; x = raylinv (p, sigma); expected_x = [0.0000, 0.9181, 2.0041, 3.3784, 5.0538, 7.0645]; assert (x, expected_x, 0.001); ***** test p = 0:0.1:0.5; x = raylinv (p, 0.5); expected_x = [0.0000, 0.2295, 0.3340, 0.4223, 0.5054, 0.5887]; assert (x, expected_x, 0.001); ***** error raylinv () ***** error raylinv (1) ***** error ... raylinv (ones (3), ones (2)) ***** error ... raylinv (ones (2), ones (3)) ***** error raylinv (i, 2) ***** error raylinv (2, i) 8 tests, 8 passed, 0 known failure, 0 skipped [inst/cmdscale.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/cmdscale.m ***** shared m, n, X, D m = randi(100) + 1; n = randi(100) + 1; X = rand(m, n); D = pdist(X); ***** assert(norm(pdist(cmdscale(D))), norm(D), sqrt(eps)) ***** assert(norm(pdist(cmdscale(squareform(D)))), norm(D), sqrt(eps)) 2 tests, 2 passed, 0 known failure, 0 skipped [inst/vartest.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/vartest.m ***** error vartest (); ***** error vartest ([1, 2, 3, 4], -0.5); ***** error ... vartest ([1, 2, 3, 4], 1, "alpha", 0); ***** error ... vartest ([1, 2, 3, 4], 1, "alpha", 1.2); ***** error ... vartest ([1, 2, 3, 4], 1, "alpha", "val"); ***** error ... vartest ([1, 2, 3, 4], 1, "tail", "val"); ***** error ... vartest ([1, 2, 3, 4], 1, "alpha", 0.01, "tail", "val"); ***** error ... vartest ([1, 2, 3, 4], 1, "dim", 3); ***** error ... vartest ([1, 2, 3, 4], 1, "alpha", 0.01, "tail", "both", "dim", 3); ***** error ... vartest ([1, 2, 3, 4], 1, "alpha", 0.01, "tail", "both", "badoption", 3); ***** error ... vartest ([1, 2, 3, 4], 1, "alpha", 0.01, "tail"); ***** test load carsmall [h, pval, ci] = vartest (MPG, 7^2); assert (h, 1); assert (pval, 0.04335086742174443, 1e-14); assert (ci, [49.397; 88.039], 1e-3); 12 tests, 12 passed, 0 known failure, 0 skipped [inst/canoncorr.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/canoncorr.m ***** shared X,Y,A,B,r,U,V,k k = 10; X = [1:k; sin(1:k); cos(1:k)]'; Y = [tan(1:k); tanh((1:k)/k)]'; [A,B,r,U,V,stats] = canoncorr (X,Y); ***** assert (A, [-0.329229 0.072908; 0.074870 1.389318; -0.069302 -0.024109], 1E-6); ***** assert (B, [-0.017086 -0.398402; -4.475049 -0.824538], 1E-6); ***** assert (r, [0.99590 0.26754], 1E-5); ***** assert (U, center(X) * A, 10*eps); ***** assert (V, center(Y) * B, 10*eps); ***** assert (cov(U), eye(size(U, 2)), 10*eps); ***** assert (cov(V), eye(size(V, 2)), 10*eps); rand ("state", 1); [A,B,r] = canoncorr (rand(5, 10),rand(5, 20)); ***** assert (r, ones(1, 5), 10*eps); 8 tests, 8 passed, 0 known failure, 0 skipped [inst/kstest2.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/kstest2.m ***** error kstest2 ([1,2,3,4,5,5]) ***** error kstest2 (ones(2,4), [1,2,3,4,5,5]) ***** error kstest2 ([2,3,5,7,3+3i], [1,2,3,4,5,5]) ***** error kstest2 ([2,3,4,5,6],[3;5;7;8;7;6;5],"tail") ***** error kstest2 ([2,3,4,5,6],[3;5;7;8;7;6;5],"tail", "whatever") ***** error kstest2 ([2,3,4,5,6],[3;5;7;8;7;6;5],"badoption", 0.51) ***** error kstest2 ([2,3,4,5,6],[3;5;7;8;7;6;5],"tail", 0) ***** error kstest2 ([2,3,4,5,6],[3;5;7;8;7;6;5],"alpha", 0) ***** error kstest2 ([2,3,4,5,6],[3;5;7;8;7;6;5],"alpha", NaN) ***** error kstest2 ([NaN,NaN,NaN,NaN,NaN],[3;5;7;8;7;6;5],"tail", "unequal") ***** test load examgrades [h, p] = kstest2 (grades(:,1), grades(:,2)); assert (h, false); assert (p, 0.1222791870137312, 1e-14); ***** test load examgrades [h, p] = kstest2 (grades(:,1), grades(:,2), "tail", "larger"); assert (h, false); assert (p, 0.1844421391011258, 1e-14); ***** test load examgrades [h, p] = kstest2 (grades(:,1), grades(:,2), "tail", "smaller"); assert (h, false); assert (p, 0.06115357930171663, 1e-14); ***** test load examgrades [h, p] = kstest2 (grades(:,1), grades(:,2), "tail", "smaller", "alpha", 0.1); assert (h, true); assert (p, 0.06115357930171663, 1e-14); 14 tests, 14 passed, 0 known failure, 0 skipped [inst/adtest.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/adtest.m ***** error adtest (); ***** error adtest (ones (20,2)); ***** error adtest ([1+i,0-3i]); ***** error ... adtest (ones (20,1), "Distribution", "normal"); ***** error ... adtest (rand (20,1), "Distribution", {"normal", 5, 3}); ***** error ... adtest (rand (20,1), "Distribution", {"norm", 5}); ***** error ... adtest (rand (20,1), "Distribution", {"exp", 5, 4}); ***** error ... adtest (rand (20,1), "Distribution", {"ev", 5}); ***** error ... adtest (rand (20,1), "Distribution", {"logn", 5, 3, 2}); ***** error ... adtest (rand (20,1), "Distribution", {"Weibull", 5}); ***** error ... adtest (rand (20,1), "Distribution", 35); ***** error ... adtest (rand (20,1), "Name", "norm"); ***** error ... adtest (rand (20,1), "Name", {"norm", 75, 10}); ***** error ... adtest (rand (20,1), "Distribution", "norm", "Asymptotic", true); ***** error ... adtest (rand (20,1), "MCTol", 0.001, "Asymptotic", true); ***** error ... adtest (rand (20,1), "Distribution", {"norm", 5, 3}, "MCTol", 0.001, ... "Asymptotic", true); ***** error ... [h, pval, ADstat, CV] = adtest (ones (20,1), "Distribution", {"norm",5,3},... "Alpha", 0.000000001); ***** error ... [h, pval, ADstat, CV] = adtest (ones (20,1), "Distribution", {"norm",5,3},... "Alpha", 0.999999999); ***** error ... adtest (10); ***** warning ... randn ("seed", 34); adtest (ones (20,1), "Alpha", 0.000001); ***** warning ... randn ("seed", 34); adtest (normrnd(0,1,100,1), "Alpha", 0.99999); ***** warning ... randn ("seed", 34); adtest (normrnd(0,1,100,1), "Alpha", 0.00001); ***** test load examgrades x = grades(:,1); [h, pval, adstat, cv] = adtest (x); assert (h, false); assert (pval, 0.1854, 1e-4); assert (adstat, 0.5194, 1e-4); assert (cv, 0.7470, 1e-4); ***** test load examgrades x = grades(:,1); [h, pval, adstat, cv] = adtest (x, "Distribution", "ev"); assert (h, false); assert (pval, 0.071363, 1e-6); ***** test load examgrades x = grades(:,1); [h, pval, adstat, cv] = adtest (x, "Distribution", {"norm", 75, 10}); assert (h, false); assert (pval, 0.4687, 1e-4); 25 tests, 25 passed, 0 known failure, 0 skipped [inst/dendrogram.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/dendrogram.m ***** demo ## simple dendrogram y = [4, 5; 2, 6; 3, 7; 8, 9; 1, 10]; y(:,3) = 1:5; dendrogram (y); title ("simple dendrogram"); ***** demo ## another simple dendrogram v = 2 * rand (30, 1) - 1; d = abs (bsxfun (@minus, v(:, 1), v(:, 1)')); y = linkage (squareform (d, "tovector")); dendrogram (y); title ("another simple dendrogram"); ***** demo ## collapsed tree, find all the leaves of node 5 X = randn (60, 2); D = pdist (X); y = linkage (D, "average"); subplot (2, 1, 1); title ("original tree"); dendrogram (y, 0); subplot (2, 1, 2); title ("collapsed tree"); [~, t] = dendrogram (y, 20); find(t == 5) ***** demo ## optimal leaf order X = randn (30, 2); D = pdist (X); y = linkage (D, "average"); order = optimalleaforder (y, D); subplot (2, 1, 1); title ("original leaf order"); dendrogram (y); subplot (2, 1, 2); title ("optimal leaf order"); dendrogram (y, "Reorder", order); ***** demo ## horizontal orientation and labels X = randn (8, 2); D = pdist (X); L = ["Snow White"; "Doc"; "Grumpy"; "Happy"; "Sleepy"; "Bashful"; ... "Sneezy"; "Dopey"]; y = linkage (D, "average"); dendrogram (y, "Orientation", "left", "Labels", L); title ("horizontal orientation and labels"); ***** shared visibility_setting visibility_setting = get (0, "DefaultFigureVisible"); ***** test hf = figure ("visible", "off"); unwind_protect y = [4, 5; 2, 6; 3, 7; 8, 9; 1, 10]; y(:,3) = 1:5; dendrogram (y); unwind_protect_cleanup close (hf); end_unwind_protect ***** test hf = figure ("visible", "off"); unwind_protect y = [4, 5; 2, 6; 3, 7; 8, 9; 1, 10]; y(:,3) = 1:5; dendrogram (y); unwind_protect_cleanup close (hf); end_unwind_protect ***** test hf = figure ("visible", "off"); unwind_protect v = 2 * rand (30, 1) - 1; d = abs (bsxfun (@minus, v(:, 1), v(:, 1)')); y = linkage (squareform (d, "tovector")); dendrogram (y); unwind_protect_cleanup close (hf); end_unwind_protect ***** test hf = figure ("visible", "off"); unwind_protect X = randn (30, 2); D = pdist (X); y = linkage (D, "average"); order = optimalleaforder (y, D); subplot (2, 1, 1); title ("original leaf order"); dendrogram (y); subplot (2, 1, 2); title ("optimal leaf order"); dendrogram (y, "Reorder", order); unwind_protect_cleanup close (hf); end_unwind_protect ***** error dendrogram (); ***** error dendrogram (ones (2, 2), 1); ***** error dendrogram ([1 2 1], 1, "xxx", "xxx"); ***** error dendrogram ([1 2 1], "Reorder", "xxx"); ***** error dendrogram ([1 2 1], "Reorder", [1 2 3 4]); fail ('dendrogram ([1 2 1], "Orientation", "north")', "invalid orientation .*") 9 tests, 9 passed, 0 known failure, 0 skipped [inst/sampsizepwr.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/sampsizepwr.m ***** demo ## Compute the mean closest to 100 that can be determined to be ## significantly different from 100 using a t-test with a sample size ## of 60 and a power of 0.8. mu1 = sampsizepwr ("t", [100, 10], [], 0.8, 60); disp (mu1); ***** demo ## Compute the sample sizes required to distinguish mu0 = 100 from ## mu1 = 110 by a two-sample t-test with a ratio of the larger and the ## smaller sample sizes of 1.5 and a power of 0.6. [N1,N2] = sampsizepwr ("t2", [100, 10], 110, 0.6, [], "ratio", 1.5) ***** demo ## Compute the sample size N required to distinguish p=.26 from p=.2 ## with a binomial test. The result is approximate, so make a plot to ## see if any smaller N values also have the required power of 0.6. Napprox = sampsizepwr ("p", 0.2, 0.26, 0.6); nn = 1:250; pwr = sampsizepwr ("p", 0.2, 0.26, [], nn); Nexact = min (nn(pwr >= 0.6)); plot(nn,pwr,'b-', [Napprox Nexact],pwr([Napprox Nexact]),'ro'); grid on ***** demo ## The company must test 52 bottles to detect the difference between a mean ## volume of 100 mL and 102 mL with a power of 0.80. Generate a power curve ## to visualize how the sample size affects the power of the test. nout = sampsizepwr('t',[100 5],102,0.80); nn = 1:100; pwrout = sampsizepwr('t',[100 5],102,[],nn); figure; plot (nn, pwrout, "b-", nout, 0.8, "ro") title ("Power versus Sample Size") xlabel ("Sample Size") ylabel ("Power") ***** error ... out = sampsizepwr ([], [100, 10], [], 0.8, 60); ***** error ... out = sampsizepwr (3, [100, 10], [], 0.8, 60); ***** error ... out = sampsizepwr ({"t", "t2"}, [100, 10], [], 0.8, 60); ***** error ... out = sampsizepwr ("reg", [100, 10], [], 0.8, 60); ***** error ... out = sampsizepwr ("t", ["a", "e"], [], 0.8, 60); ***** error ... out = sampsizepwr ("z", 100, [], 0.8, 60); ***** error ... out = sampsizepwr ("t", 100, [], 0.8, 60); ***** error ... out = sampsizepwr ("t2", 60, [], 0.8, 60); ***** error ... out = sampsizepwr ("var", [100, 10], [], 0.8, 60); ***** error ... out = sampsizepwr ("p", [100, 10], [], 0.8, 60); ***** error ... out = sampsizepwr ("r", [100, 10], [], 0.8, 60); ***** error ... [out, N1] = sampsizepwr ("z", [100, 10], [], 0.8, 60); ***** error ... [out, N1] = sampsizepwr ("t", [100, 10], [], 0.8, 60); ***** error ... [out, N1] = sampsizepwr ("var", 2, [], 0.8, 60); ***** error ... [out, N1] = sampsizepwr ("p", 0.1, [], 0.8, 60); ***** error ... [out, N1] = sampsizepwr ("r", 0.5, [], 0.8, 60); ***** error ... out = sampsizepwr ("z", [100, 0], [], 0.8, 60); ***** error ... out = sampsizepwr ("z", [100, -5], [], 0.8, 60); ***** error ... out = sampsizepwr ("t", [100, 0], [], 0.8, 60); ***** error ... out = sampsizepwr ("t", [100, -5], [], 0.8, 60); ***** error ... [out, N1] = sampsizepwr ("t2", [100, 0], [], 0.8, 60); ***** error ... [out, N1] = sampsizepwr ("t2", [100, -5], [], 0.8, 60); ***** error ... out = sampsizepwr ("var", 0, [], 0.8, 60); ***** error ... out = sampsizepwr ("var", -5, [], 0.8, 60); ***** error ... out = sampsizepwr ("p", 0, [], 0.8, 60); ***** error ... out = sampsizepwr ("p", 1.2, [], 0.8, 60); ***** error ... out = sampsizepwr ("r", -1.5, [], 0.8, 60); ***** error ... out = sampsizepwr ("r", -1, [], 0.8, 60); ***** error ... out = sampsizepwr ("r", 1.2, [], 0.8, 60); ***** error ... out = sampsizepwr ("r", 0, [], 0.8, 60); ***** error ... out = sampsizepwr ("r", 0.2, [], 0.8, 60, "alpha", -0.2); ***** error ... out = sampsizepwr ("r", 0.2, [], 0.8, 60, "alpha", 0); ***** error ... out = sampsizepwr ("r", 0.2, [], 0.8, 60, "alpha", 1.5); ***** error ... out = sampsizepwr ("r", 0.2, [], 0.8, 60, "alpha", "zero"); ***** error ... out = sampsizepwr ("r", 0.2, [], 0.8, 60, "tail", 1.5); ***** error ... out = sampsizepwr ("r", 0.2, [], 0.8, 60, "tail", {"both", "left"}); ***** error ... out = sampsizepwr ("r", 0.2, [], 0.8, 60, "tail", "other"); ***** error ... out = sampsizepwr ("r", 0.2, [], 0.8, 60, "ratio", "some"); ***** error ... out = sampsizepwr ("r", 0.2, [], 0.8, 60, "ratio", 0.5); ***** error ... out = sampsizepwr ("r", 0.2, [], 0.8, 60, "ratio", [2, 1.3, 0.3]); ***** error ... out = sampsizepwr ("z", [100, 5], [], [], 60); ***** error ... out = sampsizepwr ("z", [100, 5], 110, [], []); ***** error ... out = sampsizepwr ("z", [100, 5], [], 0.8, []); ***** error ... out = sampsizepwr ("z", [100, 5], 110, 0.8, 60); ***** error ... out = sampsizepwr ("z", [100, 5], "mu", [], 60); ***** error ... out = sampsizepwr ("var", 5, -1, [], 60); ***** error ... out = sampsizepwr ("p", 0.8, 1.2, [], 60, "tail", "right"); ***** error ... out = sampsizepwr ("r", 0.8, 1.2, [], 60); ***** error ... out = sampsizepwr ("r", 0.8, -1.2, [], 60); ***** error ... out = sampsizepwr ("z", [100, 5], 110, 1.2); ***** error ... out = sampsizepwr ("z", [100, 5], 110, 0); ***** error ... out = sampsizepwr ("z", [100, 5], 110, 0.05, [], "alpha", 0.1); ***** error ... out = sampsizepwr ("z", [100, 5], [], [0.8, 0.7], [60, 80, 100]); ***** error ... out = sampsizepwr ("t", [100, 5], 100, 0.8, []); ***** error ... out = sampsizepwr ("t", [100, 5], 110, 0.8, [], "tail", "left"); ***** error ... out = sampsizepwr ("t", [100, 5], 90, 0.8, [], "tail", "right"); ***** warning ... Napprox = sampsizepwr ("p", 0.2, 0.26, 0.6); ***** warning ... Napprox = sampsizepwr ("p", 0.30, 0.36, 0.8); ***** test mu1 = sampsizepwr ("t", [100, 10], [], 0.8, 60); assert (mu1, 103.67704316, 1e-8); ***** test [N1,N2] = sampsizepwr ("t2", [100, 10], 110, 0.6, [], "ratio", 1.5); assert (N1, 9); assert (N2, 14); ***** test nn = 1:250; pwr = sampsizepwr ("p", 0.2, 0.26, [], nn); pwr_out = [0, 0.0676, 0.0176, 0.0566, 0.0181, 0.0431, 0.0802, 0.0322]; assert (pwr([1:8]), pwr_out, 1e-4 * ones (1,8)); pwr_out = [0.59275, 0.6073, 0.62166, 0.6358, 0.6497, 0.6087, 0.6229, 0.6369]; assert (pwr([243:end]), pwr_out, 1e-4 * ones (1,8)); ***** test nout = sampsizepwr ("t", [100, 5], 102, 0.80); assert (nout, 52); ***** test power = sampsizepwr ("t", [20, 5], 25, [], 5, "Tail", "right"); assert (power, 0.5797373588621888, 1e-14); ***** test nout = sampsizepwr ("t", [20, 5], 25, 0.99, [], "Tail", "right"); assert (nout, 18); ***** test p1out = sampsizepwr ("t", [20, 5], [], 0.95, 10, "Tail", "right"); assert (p1out, 25.65317979360237, 1e-14); ***** test pwr = sampsizepwr ("t2", [1.4, 0.2], 1.7, [], 5, "Ratio", 2); assert (pwr, 0.716504004686586, 1e-14); ***** test n = sampsizepwr ("t2", [1.4, 0.2], 1.7, 0.9, []); assert (n, 11); ***** test [n1, n2] = sampsizepwr ("t2", [1.4, 0.2], 1.7, 0.9, [], "Ratio", 2); assert ([n1, n2], [8, 16]); 68 tests, 68 passed, 0 known failure, 0 skipped [inst/runstest.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/runstest.m ***** test ## NIST beam deflection data ## http://www.itl.nist.gov/div898/handbook/eda/section4/eda425.htm data = [-213, -564, -35, -15, 141, 115, -420, -360, 203, -338, -431, ... 194, -220, -513, 154, -125, -559, 92, -21, -579, -52, 99, -543, ... -175, 162, -457, -346, 204, -300, -474, 164, -107, -572, -8, 83, ... -541, -224, 180, -420, -374, 201, -236, -531, 83, 27, -564, -112, ... 131, -507, -254, 199, -311, -495, 143, -46, -579, -90, 136, ... -472, -338, 202, -287, -477, 169, -124, -568, 17, 48, -568, -135, ... 162, -430, -422, 172, -74, -577, -13, 92, -534, -243, 194, -355, ... -465, 156, -81, -578, -64, 139, -449, -384, 193, -198, -538, 110, ... -44, -577, -6, 66, -552, -164, 161, -460, -344, 205, -281, -504, ... 134, -28, -576, -118, 156, -437, -381, 200, -220, -540, 83, 11, ... -568, -160, 172, -414, -408, 188, -125, -572, -32, 139, -492, ... -321, 205, -262, -504, 142, -83, -574, 0, 48, -571, -106, 137, ... -501, -266, 190, -391, -406, 194, -186, -553, 83, -13, -577, -49, ... 103, -515, -280, 201, 300, -506, 131, -45, -578, -80, 138, -462, ... -361, 201, -211, -554, 32, 74, -533, -235, 187, -372, -442, 182, ... -147, -566, 25, 68, -535, -244, 194, -351, -463, 174, -125, -570, ... 15, 72, -550, -190, 172, -424, -385, 198, -218, -536, 96]; [h, p, stats] = runstest (data, median (data)); expected_h = 1; expected_p = 0.008562; expected_z = 2.6229; assert (h, expected_h); assert (p, expected_p, 1E-6); assert (stats.z, expected_z, 1E-4); ***** shared x x = [45, -60, 1.225, 55.4, -9 27]; ***** test [h, p, stats] = runstest (x); assert (h, 0); assert (p, 0.6, 1e-14); assert (stats.nruns, 5); assert (stats.n1, 3); assert (stats.n0, 3); assert (stats.z, 0.456435464587638, 1e-14); ***** test [h, p, stats] = runstest (x, [], "method", "approximate"); assert (h, 0); assert (p, 0.6481, 1e-4); assert (stats.z, 0.456435464587638, 1e-14); ***** test [h, p, stats] = runstest (x, [], "tail", "left"); assert (h, 0); assert (p, 0.9, 1e-14); assert (stats.z, 1.369306393762915, 1e-14); ***** error runstest (ones (2,20)) ***** error runstest (["asdasda"]) ***** error ... runstest ([2 3 4 3 2 3 4], "updown") ***** error ... runstest ([2 3 4 3 2 3 4], [], "alpha", 0) ***** error ... runstest ([2 3 4 3 2 3 4], [], "alpha", [0.02 0.2]) ***** error ... runstest ([2 3 4 3 2 3 4], [], "alpha", 1.2) ***** error ... runstest ([2 3 4 3 2 3 4], [], "alpha", -0.05) ***** error ... runstest ([2 3 4 3 2 3 4], [], "method", "some") ***** error ... runstest ([2 3 4 3 2 3 4], [], "tail", "some") ***** error ... runstest ([2 3 4 3 2 3 4], [], "option", "some") 14 tests, 14 passed, 0 known failure, 0 skipped [inst/qrandn.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/qrandn.m ***** demo z = qrandn (-5, 5e6); [c x] = hist (z,linspace(-1.5,1.5,200),1); figure(1) plot(x,c,"r."); axis tight; axis([-1.5,1.5]); z = qrandn (-0.14286, 5e6); [c x] = hist (z,linspace(-2,2,200),1); figure(2) plot(x,c,"r."); axis tight; axis([-2,2]); z = qrandn (2.75, 5e6); [c x] = hist (z,linspace(-1e3,1e3,1e3),1); figure(3) semilogy(x,c,"r."); axis tight; axis([-100,100]); # --------- # Figures from the reference paper. ***** error qrandn ([1 2], 1) ***** error qrandn (4, 1) ***** error qrandn (3, 1) ***** error qrandn (2.5, 1, 2, 3) ***** error qrandn (2.5) ***** test q = 1.5; s = [2, 3]; z = qrandn (q, s); assert (isnumeric (z) && isequal (size (z), s)); 6 tests, 6 passed, 0 known failure, 0 skipped [inst/fitgmdist.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/fitgmdist.m ***** demo ## Generate a two-cluster problem C1 = randn (100, 2) + 2; C2 = randn (100, 2) - 2; data = [C1; C2]; ## Perform clustering GMModel = fitgmdist (data, 2); ## Plot the result figure [heights, bins] = hist3([C1; C2]); [xx, yy] = meshgrid(bins{1}, bins{2}); bbins = [xx(:), yy(:)]; contour (reshape (GMModel.pdf (bbins), size (heights))); ***** demo Angle_Theta = [ 30 + 10 * randn(1, 10), 60 + 10 * randn(1, 10) ]'; nbOrientations = 2; initial_orientations = [38.0; 18.0]; initial_weights = ones (1, nbOrientations) / nbOrientations; initial_Sigma = 10 * ones (1, 1, nbOrientations); start = struct ("mu", initial_orientations, "Sigma", initial_Sigma, ... "ComponentProportion", initial_weights); GMModel_Theta = fitgmdist (Angle_Theta, nbOrientations, "Start", start , ... "RegularizationValue", 0.0001) ***** test load fisheriris classes = unique (species); [~, score] = pca (meas, "NumComponents", 2); options.MaxIter = 1000; options.TolFun = 1e-6; options.Display = "off"; GMModel = fitgmdist (score, 2, "Options", options); assert (isa (GMModel, "gmdistribution"), true); assert (GMModel.mu, [1.3212, -0.0954; -2.6424, 0.1909], 1e-4); 1 test, 1 passed, 0 known failure, 0 skipped [inst/pca.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/pca.m ***** shared COEFF,SCORE,latent,tsquare,m,x,R,V,lambda,i,S,F ***** test x=[7 4 3 4 1 8 6 3 5 8 6 1 8 5 7 7 2 9 5 3 3 9 5 8 7 4 5 8 2 2]; R = corrcoef (x); [V, lambda] = eig (R); [~, i] = sort(diag(lambda), "descend"); #arrange largest PC first S = V(:, i) * diag(sqrt(diag(lambda)(i))); ***** assert(diag(S(:, 1:2)*S(:, 1:2)'), [0.8662; 0.8420; 0.9876], 1E-4); #contribution of first 2 PCs to each original variable B = V(:, i) * diag( 1./ sqrt(diag(lambda)(i))); F = zscore(x)*B; [COEFF,SCORE,latent,tsquare] = pca(zscore(x, 1)); ***** assert(tsquare,sumsq(F, 2),1E4*eps); ***** test x=[1,2,3;2,1,3]'; [COEFF,SCORE,latent,tsquare] = pca(x, "Economy", false); m=[sqrt(2),sqrt(2);sqrt(2),-sqrt(2);-2*sqrt(2),0]/2; m(:,1) = m(:,1)*sign(COEFF(1,1)); m(:,2) = m(:,2)*sign(COEFF(1,2)); ***** assert(COEFF,m(1:2,:),10*eps); ***** assert(SCORE,-m,10*eps); ***** assert(latent,[1.5;.5],10*eps); ***** assert(tsquare,[4;4;4]/3,10*eps); [COEFF,SCORE,latent,tsquare] = pca(x, "Economy", false, "weights", [1 2 1], "variableweights", "variance"); ***** assert(COEFF, [0.632455532033676 -0.632455532033676; 0.741619848709566 0.741619848709566], 10*eps); ***** assert(SCORE, [-0.622019449426284 0.959119380657905; -0.505649896847432 -0.505649896847431; 1.633319243121148 0.052180413036957], 10*eps); ***** assert(latent, [1.783001790889027; 0.716998209110974], 10*eps); ***** xtest assert(tsquare, [1.5; 0.5; 1.5], 10*eps); #currently, [4; 2; 4]/3 is actually returned; see comments above !!!!! known failure ASSERT errors for: assert (tsquare,[1.5; 0.5; 1.5],10 * eps) Location | Observed | Expected | Reason (1) 1.3333 1.5 Abs err 0.16667 exceeds tol 2.2204e-15 by 0.2 (2) 0.66667 0.5 Abs err 0.16667 exceeds tol 2.2204e-15 by 0.2 (3) 1.3333 1.5 Abs err 0.16667 exceeds tol 2.2204e-15 by 0.2 ***** test x=x'; [COEFF,SCORE,latent,tsquare] = pca(x, "Economy", false); m=[sqrt(2),sqrt(2),0;-sqrt(2),sqrt(2),0;0,0,2]/2; m(:,1) = m(:,1)*sign(COEFF(1,1)); m(:,2) = m(:,2)*sign(COEFF(1,2)); m(:,3) = m(:,3)*sign(COEFF(3,3)); ***** assert(COEFF,m,10*eps); ***** assert(SCORE(:,1),-m(1:2,1),10*eps); ***** assert(SCORE(:,2:3),zeros(2),10*eps); ***** assert(latent,[1;0;0],10*eps); ***** assert(tsquare,[0.5;0.5],10*eps) ***** test [COEFF,SCORE,latent,tsquare] = pca(x); ***** assert(COEFF,m(:, 1),10*eps); ***** assert(SCORE,-m(1:2,1),10*eps); ***** assert(latent,[1],10*eps); ***** assert(tsquare,[0.5;0.5],10*eps) ***** error pca([1 2; 3 4], "Algorithm", "xxx") ***** error <'centered' requires a boolean value> pca([1 2; 3 4], "Centered", "xxx") ***** error pca([1 2; 3 4], "NumComponents", -4) ***** error pca([1 2; 3 4], "Rows", 1) ***** error pca([1 2; 3 4], "Weights", [1 2 3]) ***** error pca([1 2; 3 4], "Weights", [-1 2]) ***** error pca([1 2; 3 4], "VariableWeights", [-1 2]) ***** error pca([1 2; 3 4], "VariableWeights", "xxx") ***** error pca([1 2; 3 4], "XXX", 1) 32 tests, 31 passed, 1 known failure, 0 skipped [inst/shadow9/mean.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/shadow9/mean.m ***** test x = -10:10; y = x'; z = [y, y+10]; assert (mean (x), 0); assert (mean (y), 0); assert (mean (z), [0, 10]); ***** assert (mean (magic (3), 1), [5, 5, 5]) ***** assert (mean (magic (3), 2), [5; 5; 5]) ***** assert (mean (logical ([1 0 1 1])), 0.75) ***** assert (mean (single ([1 0 1 1])), single (0.75)) ***** assert (mean ([1 2], 3), [1 2]) ***** test in = [1 2 3]; out = 2; assert (mean (in, "default"), mean (in)); assert (mean (in, "default"), out); assert (mean (in, "double"), out); assert (mean (in, "native"), out); ***** test in = single ([1 2 3]); out = 2; assert (mean (in, "default"), mean (in)); assert (mean (in, "default"), single (out)); assert (mean (in, "double"), out); assert (mean (in, "native"), single (out)); ***** test in = logical ([1 0 1]); out = 2/3; assert (mean (in, "default"), mean (in), eps); assert (mean (in, "default"), out, eps); assert (mean (in, "double"), out, eps); assert (mean (in, "native"), out, eps); ***** test in = char ("ab"); out = 97.5; assert (mean (in, "default"), mean (in), eps); assert (mean (in, "default"), out, eps); assert (mean (in, "double"), out, eps); ***** test in = uint8 ([1 2 3]); out = 2; assert (mean (in, "default"), mean (in)); assert (mean (in, "default"), out); assert (mean (in, "double"), out); assert (mean (in, "native"), uint8 (out)); ***** test in = uint8 ([0 1 2 3]); out = 1.5; out_u8 = 2; assert (mean (in, "default"), mean (in), eps); assert (mean (in, "default"), out, eps); assert (mean (in, "double"), out, eps); assert (mean (in, "native"), uint8 (out_u8)); assert (class (mean (in, "native")), "uint8"); ***** test # internal sum exceeding intmax in = uint8 ([3 141 141 255]); out = 135; assert (mean (in, "default"), mean (in)); assert (mean (in, "default"), out); assert (mean (in, "double"), out); assert (mean (in, "native"), uint8 (out)); assert (class (mean (in, "native")), "uint8"); ***** test # fractional answer with internal sum exceeding intmax in = uint8 ([1 141 141 255]); out = 134.5; out_u8 = 135; assert (mean (in, "default"), mean (in)); assert (mean (in, "default"), out); assert (mean (in, "double"), out); assert (mean (in, "native"), uint8 (out_u8)); assert (class (mean (in, "native")), "uint8"); ***** test <54567> # large int64 sum exceeding intmax and double precision limit in_same = uint64 ([intmax("uint64") intmax("uint64")-2]); out_same = intmax ("uint64")-1; in_opp = int64 ([intmin("int64"), intmax("int64")-1]); out_opp = -1; in_neg = int64 ([intmin("int64") intmin("int64")+2]); out_neg = intmin ("int64")+1; ## both positive assert (mean (in_same, "default"), mean (in_same)); assert (mean (in_same, "default"), double (out_same)); assert (mean (in_same, "double"), double (out_same)); assert (mean (in_same, "native"), uint64 (out_same)); assert (class (mean (in_same, "native")), "uint64"); ## opposite signs assert (mean (in_opp, "default"), mean (in_opp)); assert (mean (in_opp, "default"), double (out_opp)); assert (mean (in_opp, "double"), double (out_opp)); assert (mean (in_opp, "native"), int64 (out_opp)); assert (class (mean (in_opp, "native")), "int64"); ## both negative assert (mean (in_neg, "default"), mean (in_neg)); assert (mean (in_neg, "default"), double(out_neg)); assert (mean (in_neg, "double"), double(out_neg)); assert (mean (in_neg, "native"), int64(out_neg)); assert (class (mean (in_neg, "native")), "int64"); ***** test <54567> in = [(intmin('int64')+5), (intmax('int64'))-5]; assert (mean (in, "native"), int64(-1)); assert (class (mean (in, "native")), "int64"); assert (mean (double(in)), double(0) ); assert (mean (in), double(-0.5) ); assert (mean (in, "default"), double(-0.5) ); assert (mean (in, "double"), double(-0.5) ); assert (mean (in, "all", "native"), int64(-1)); assert (mean (in, 2, "native"), int64(-1)); assert (mean (in, [1 2], "native"), int64(-1)); assert (mean (in, [2 3], "native"), int64(-1)); assert (mean ([intmin("int64"), in, intmax("int64")]), double(-0.5)) assert (mean ([in; int64([1 3])], 2, "native"), int64([-1; 2])); ***** test x = [-10:10]; y = [x;x+5;x-5]; assert (mean (x), 0); assert (mean (y, 2), [0, 5, -5]'); assert (mean (y, "all"), 0); y(2,4) = NaN; assert (mean (y', "omitnan"), [0 5.35 -5]); z = y + 20; assert (mean (z, "all"), NaN); assert (mean (z, "all", "includenan"), NaN); assert (mean (z, "all", "omitnan"), 20.03225806451613, 4e-14); m = [20 NaN 15]; assert (mean (z'), m); assert (mean (z', "includenan"), m); m = [20 25.35 15]; assert (mean (z', "omitnan"), m); assert (mean (z, 2, "omitnan"), m'); assert (mean (z, 2, "native", "omitnan"), m'); assert (mean (z, 2, "omitnan", "native"), m'); ***** test assert (mean (true, "all"), 1); assert (mean (false), 0); assert (mean ([true false true]), 2/3, 4e-14); assert (mean ([true false true], 1), [1 0 1]); assert (mean ([true false NaN], 1), [1 0 NaN]); assert (mean ([true false NaN], 2), NaN); assert (mean ([true false NaN], 2, "omitnan"), 0.5); assert (mean ([true false NaN], 2, "omitnan", "native"), 0.5); ***** assert (mean ("abc"), double (98)) ***** assert (mean ("ab"), double (97.5), eps) ***** assert (mean ("abc", "double"), double (98)) ***** assert (mean ("abc", "default"), double (98)) ***** test x = magic (4); x([2, 9:12]) = NaN; assert (mean (x), [NaN 8.5, NaN, 8.5], eps); assert (mean (x,1), [NaN 8.5, NaN, 8.5], eps); assert (mean (x,2), NaN(4,1), eps); assert (mean (x,3), x, eps); assert (mean (x, 'omitnan'), [29/3, 8.5, NaN, 8.5], eps); assert (mean (x, 1, 'omitnan'), [29/3, 8.5, NaN, 8.5], eps); assert (mean (x, 2, 'omitnan'), [31/3; 9.5; 28/3; 19/3], eps); assert (mean (x, 3, 'omitnan'), x, eps); ***** assert (mean ([]), NaN(1,1)) ***** assert (mean (single([])), NaN(1,1,"single")) ***** assert (mean ([], 1), NaN(1,0)) ***** assert (mean ([], 2), NaN(0,1)) ***** assert (mean ([], 3), NaN(0,0)) ***** assert (mean (ones(1,0)), NaN(1,1)) ***** assert (mean (ones(1,0), 1), NaN(1,0)) ***** assert (mean (ones(1,0), 2), NaN(1,1)) ***** assert (mean (ones(1,0), 3), NaN(1,0)) ***** assert (mean (ones(0,1)), NaN(1,1)) ***** assert (mean (ones(0,1), 1), NaN(1,1)) ***** assert (mean (ones(0,1), 2), NaN(0,1)) ***** assert (mean (ones(0,1), 3), NaN(0,1)) ***** assert (mean (ones(0,1,0)), NaN(1,1,0)) ***** assert (mean (ones(0,1,0), 1), NaN(1,1,0)) ***** assert (mean (ones(0,1,0), 2), NaN(0,1,0)) ***** assert (mean (ones(0,1,0), 3), NaN(0,1,1)) ***** assert (mean (ones(0,0,1,0)), NaN(1,0,1,0)) ***** assert (mean (ones(0,0,1,0), 1), NaN(1,0,1,0)) ***** assert (mean (ones(0,0,1,0), 2), NaN(0,1,1,0)) ***** assert (mean (ones(0,0,1,0), 3), NaN(0,0,1,0)) ***** test x = repmat ([1:20;6:25], [5 2 6 3]); assert (size (mean (x, [3 2])), [10 1 1 3]); assert (size (mean (x, [1 2])), [1 1 6 3]); assert (size (mean (x, [1 2 4])), [1 1 6]); assert (size (mean (x, [1 4 3])), [1 40]); assert (size (mean (x, [1 2 3 4])), [1 1]); ***** assert (mean (ones (2,2), 3), ones (2,2)) ***** assert (mean (ones (2,2,2), 99), ones (2,2,2)) ***** assert (mean (magic (3), 3), magic (3)) ***** assert (mean (magic (3), [1 3]), [5, 5, 5]) ***** assert (mean (magic (3), [1 99]), [5, 5, 5]) ***** test x = repmat ([1:20;6:25], [5 2 6 3]); m = repmat ([10.5;15.5], [5 1 1 3]); assert (mean (x, [3 2]), m, 4e-14); x(2,5,6,3) = NaN; m(2,1,1,3) = NaN; assert (mean (x, [3 2]), m, 4e-14); m(2,1,1,3) = 15.52301255230125; assert (mean (x, [3 2], "omitnan"), m, 4e-14); ***** assert (mean ([1 2 3], "aLL"), 2) ***** assert (mean ([1 2 3], "OmitNan"), 2) ***** assert (mean ([1 2 3], "DOUBle"), 2) ***** assert <*63848> (mean (ones (80e6, 1, "single")), 1, eps) ***** assert <*63848> (mean (ones (80e6, 1, "single"), "all"), 1, eps) ***** assert <*63848> (mean (ones (80e6, 1, "single"), 1), 1, eps) ***** assert <*63848> (mean (ones (80e6, 1, "single"), [1 2]), 1, eps) ***** assert <*63848> (mean (ones (80e6, 1, "single"), [1 3]), 1, eps) ***** assert <63848> (mean ([flintmax("double"), ones(1, 2^8-1, "double")]), ... 35184372088833-1/(2^8), eps(35184372088833)) ***** error mean () ***** error mean (1, 2, 3) ***** error mean (1, 2, 3, 4) ***** error mean (1, "all", 3) ***** error mean (1, "b") ***** error mean (1, 1, "foo") ***** error mean ("abc", "native") ***** error mean ({1:5}) ***** error mean (1, ones (2,2)) ***** error mean (1, 1.5) ***** error mean (1, 0) ***** error mean (1, []) ***** error mean (1, -1) ***** error mean (1, -1.5) ***** error mean (1, NaN) ***** error mean (1, Inf) ***** error mean (repmat ([1:20;6:25], [5 2]), -1) ***** error mean (repmat ([1:5;5:9], [5 2]), [1 -1]) ***** error mean (1, ones(1,0)) ***** error mean (1, [2 2]) 80 tests, 80 passed, 0 known failure, 0 skipped [inst/shadow9/std.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/shadow9/std.m ***** assert (std (13), 0) ***** assert (std (single (13)), single (0)) ***** assert (std ([1,2,3]), 1) ***** assert (std ([1,2,3], 1), sqrt (2/3), eps) ***** assert (std ([1,2,3], [], 1), [0,0,0]) ***** assert (std ([1,2,3], [], 3), [0,0,0]) ***** assert (std (5, 99), 0) ***** assert (std (5, 99, 1), 0) ***** assert (std (5, 99, 2), 0) ***** assert (std ([5 3], [99 99], 2), 1) ***** assert (std ([1:7], [1:7]), sqrt (3)) ***** assert (std ([eye(3)], [1:3]), sqrt ([5/36, 2/9, 1/4]), eps) ***** assert (std (ones (2,2,2), [1:2], 3), [(zeros (2,2))]) ***** assert (std ([1 2; 3 4], 0, 'all'), std ([1:4])) ***** assert (std (reshape ([1:8], 2, 2, 2), 0, [1 3]), sqrt ([17/3 17/3]), eps) ***** assert (std ([1 2 3;1 2 3], [], [1 2]), sqrt (0.8), eps) ***** test x = [-10:10]; y = [x;x+5;x-5]; assert (std (x), sqrt (38.5), 1e-14); assert (std (y, [], 2), sqrt ([38.5; 38.5; 38.5]), 1e-14); assert (std (y, 0, 2), sqrt ([38.5; 38.5; 38.5]), 1e-14); assert (std (y, 1, 2), ones (3,1) * sqrt (36.66666666666666), 1e-14); assert (std (y, "all"), sqrt (54.19354838709678), 1e-14); y(2,4) = NaN; assert (std (y, "all"), NaN); assert (std (y, "all", "includenan"), NaN); assert (std (y, "all", "omitnan"), sqrt (55.01533580116342), 1e-14); assert (std (y, 0, 2, "includenan"), sqrt ([38.5; NaN; 38.5]), 1e-14); assert (std (y, [], 2), sqrt ([38.5; NaN; 38.5]), 1e-14); assert (std (y, [], 2, "omitnan"), ... sqrt ([38.5; 37.81842105263158; 38.5]), 1e-14); ***** assert (std ([4 NaN 6], [1 2 1], "omitnan"), 1, eps) ***** assert (std ([4 5 6], [1 NaN 1], "omitnan"), 1, eps) ***** assert (std (magic(3), [1 NaN 3], "omitnan"), sqrt(3)*[1 2 1], eps) ***** assert (std ([4 NaN 6], [1 2 1], "omitnan", "all"), 1, eps) ***** assert (std ([4 NaN 6], [1 2 1], "all", "omitnan"), 1, eps) ***** assert (std ([4 5 6], [1 NaN 1], "omitnan", "all"), 1, eps) ***** assert (std ([4 NaN 6], [1 2 1], 2, "omitnan"), 1, eps) ***** assert (std ([4 5 6], [1 NaN 1], 2, "omitnan"), 1, eps) ***** assert (std (magic(3), [1 NaN 3], 1, "omitnan"), sqrt(3)*[1 2 1], eps) ***** assert (std (magic(3), [1 NaN 3], 2, "omitnan"), sqrt(3)*[0.5;1;0.5], eps) ***** assert (std (4*[4 5; 6 7; 8 9], [1 3], 2, 'omitnan'), sqrt(3)*[1;1;1], eps) ***** assert (std ([4 NaN; 6 7; 8 9], [1 1 3], 1, 'omitnan'), [1.6 sqrt(3)/2], eps) ***** assert (std (4*[4 NaN; 6 7; 8 9], [1 3], 2, 'omitnan'), sqrt(3)*[0;1;1], eps) ***** assert (std (3*reshape(1:18, [3 3 2]), [1 2 3], 1, 'omitnan'), ... sqrt(5)*ones(1,3,2), eps) ***** assert (std (reshape(1:18, [3 3 2]), [1 2 3], 2, 'omitnan'), ... sqrt(5)*ones(3,1,2), eps) ***** assert (std (3*reshape(1:18, [3 3 2]), ones (3,3,2), [1 2], 'omitnan'), ... sqrt(60)*ones(1,1,2),eps) ***** assert (std (3*reshape(1:18, [3 3 2]), ones (3,3,2), [1 4], 'omitnan'), ... sqrt(6)*ones(1,3,2),eps) ***** assert (std (6*reshape(1:18, [3 3 2]), ones (3,3,2), [1:3], 'omitnan'), ... sqrt(969),eps) ***** test x = reshape(1:18, [3 3 2]); x([2, 14]) = NaN; w = ones (3,3,2); assert (std (16*x, w, [1:3], 'omitnan'), sqrt(6519), eps); ***** test x = reshape(1:18, [3 3 2]); w = ones (3,3,2); w([2, 14]) = NaN; assert (std (16*x, w, [1:3], 'omitnan'), sqrt(6519), eps); ***** assert (std ([1 2 3], "aLl"), 1); ***** assert (std ([1 2 3], "OmitNan"), 1); ***** assert (std ([1 2 3], "IncludeNan"), 1); ***** test x = repmat ([1:20;6:25], [5, 2, 6, 3]); assert (size (std (x, 0, [3 2])), [10, 1, 1, 3]); assert (size (std (x, 1, [1 2])), [1, 1, 6, 3]); assert (size (std (x, [], [1 2 4])), [1, 1, 6]); assert (size (std (x, 0, [1 4 3])), [1, 40]); assert (size (std (x, [], [1 2 3 4])), [1, 1]); ***** assert (std (3*magic(3)), sqrt([63 144 63]), eps) ***** assert (std (3*magic(3), 'omitnan'), sqrt([63 144 63]), eps) ***** assert (std (3*magic(3), 1), sqrt([42 96 42]), eps) ***** assert (std (3*magic(3), 1, 'omitnan'), sqrt([42 96 42]), eps) ***** assert (std (3*magic(3), ones(1,3), 1), sqrt([42 96 42]), eps) ***** assert (std (3*magic(3), ones(1,3), 1, 'omitnan'), sqrt([42 96 42]), eps) ***** assert (std (2*magic(3), [1 1 NaN], 1, 'omitnan'), [5 4 1], eps) ***** assert (std (3*magic(3), ones(3,3)), sqrt([42 96 42]), eps) ***** assert (std (3*magic(3), ones(3,3), 'omitnan'), sqrt([42 96 42]), eps) ***** assert (std (3*magic(3), [1 1 1; 1 1 1; 1 NaN 1], 'omitnan'), ... sqrt([42 36 42]), eps) ***** assert (std (3*magic(3), ones(3,3), 1), sqrt([42 96 42]), eps) ***** assert (std (3*magic(3), ones(3,3), 1, 'omitnan'), sqrt([42 96 42]), eps) ***** assert (std (3*magic(3), [1 1 1; 1 1 1; 1 NaN 1], 1, 'omitnan'), ... sqrt([42 36 42]), eps) ***** assert (std (3*magic(3), ones(3,3), [1 4]), sqrt([42 96 42]), eps) ***** assert (std (3*magic(3), ones(3,3), [1 4], 'omitnan'), sqrt([42 96 42]), eps) ***** assert (std (3*magic(3), [1 1 1; 1 1 1; 1 NaN 1],[1 4],'omitnan'), ... sqrt([42 36 42]), eps) ***** test x = repmat ([1:20;6:25], [5, 2, 6, 3]); v = repmat (sqrt (33.38912133891213), [10, 1, 1, 3]); assert (std (x, 0, [3, 2]), v, 1e-14); v = repmat (sqrt (33.250), [10, 1, 1, 3]); assert (std (x, 1, [3, 2]), v, 1e-14); x(2,5,6,3) = NaN; v(2,1,1,3) = NaN; assert (std (x, 1, [3, 2]), v, 1e-14); v = repmat (sqrt (33.38912133891213), [10 1 1 3]); v(2,1,1,3) = NaN; assert (std (x, [], [3, 2]), v, 1e-14); v(2,1,1,3) = sqrt (33.40177912169048); assert (std (x, [], [3, 2], "omitnan"), v, 1e-14); ***** assert (std (ones (2,2,2), [1:2], 3), [(zeros (2, 2))]) ***** assert (std (magic (3), [1:9], "all"), 2.581988897471611, 1e-14) ***** assert (std (ones (2,2), [], 3), zeros (2,2)) ***** assert (std (ones (2,2,2), [], 99), zeros (2,2,2)) ***** assert (std (magic (3), [], 3), zeros (3,3)) ***** assert (std (magic (3), [], 1), sqrt ([7, 16, 7])) ***** assert (std (magic (3), [], [1 3]), sqrt ([7, 16, 7])) ***** assert (std (magic (3), [], [1 99]), sqrt ([7, 16, 7])) ***** assert (std ([]), NaN) ***** assert (class (var (single ([]))), "single") ***** assert (std ([],[],1), NaN(1,0)) ***** assert (std ([],[],2), NaN(0,1)) ***** assert (std ([],[],3), []) ***** assert (class (var (single ([]), [], 1)), "single") ***** assert (std (ones (1,0)), NaN) ***** assert (std (ones (1,0), [], 1), NaN(1,0)) ***** assert (std (ones (1,0), [], 2), NaN) ***** assert (std (ones (1,0), [], 3), NaN(1,0)) ***** assert (class (var (ones (1, 0, "single"), [], 1)), "single") ***** assert (std (ones (0,1)), NaN) ***** assert (std (ones (0,1), [], 1), NaN) ***** assert (std (ones (0,1), [], 2), NaN(0,1)) ***** assert (std (ones (0,1), [], 3), NaN(0,1)) ***** assert (std (ones (1,3,0,2)), NaN(1,1,0,2)) ***** assert (std (ones (1,3,0,2), [], 1), NaN(1,3,0,2)) ***** assert (std (ones (1,3,0,2), [], 2), NaN(1,1,0,2)) ***** assert (std (ones (1,3,0,2), [], 3), NaN(1,3,1,2)) ***** assert (std (ones (1,3,0,2), [], 4), NaN(1,3,0)) ***** test [~, m] = std ([]); assert (m, NaN); ***** test <*62395> [~, m] = std (13); assert (m, 13); [~, m] = std (single(13)); assert (m, single(13)); [~, m] = std ([1, 2, 3; 3 2 1], []); assert (m, [2 2 2]); [~, m] = std ([1, 2, 3; 3 2 1], [], 1); assert (m, [2 2 2]); [~, m] = std ([1, 2, 3; 3 2 1], [], 2); assert (m, [2 2]'); [~, m] = std ([1, 2, 3; 3 2 1], [], 3); assert (m, [1 2 3; 3 2 1]); ***** test <*62395> [~, m] = std (5,99); assert (m, 5); [~, m] = std ([1:7], [1:7]); assert (m, 5); [~, m] = std ([eye(3)], [1:3]); assert (m, [1/6, 1/3, 0.5], eps); [~, m] = std (ones (2,2,2), [1:2], 3); assert (m, ones (2,2)); [~, m] = std ([1 2; 3 4], 0, 'all'); assert (m, 2.5, eps); [~, m] = std (reshape ([1:8], 2, 2, 2), 0, [1 3]); assert (m, [3.5, 5.5], eps); ***** test [v, m] = std (4 * eye (2), [1, 3]); assert (v, sqrt ([3, 3]), 1e-14); assert (m, [1, 3]); ***** test <*62395> [~, m] = std ([]); assert (m, NaN); ***** test x = repmat ([1:20;6:25], [5, 2, 6, 3]); [~, m] = std (x, 0, [3 2]); assert (m, mean (x, [3 2])); [~, m] = std (x, 0, [1 2]); assert (m, mean (x, [1 2])); [~, m] = std (x, 0, [1 3 4]); assert (m, mean (x, [1 3 4])); ***** test x = repmat ([1:20;6:25], [5, 2, 6, 3]); x(2,5,6,3) = NaN; [~, m] = std (x, 0, [3 2], "omitnan"); assert (m, mean (x, [3 2], "omitnan")); ***** test <*63203> [v, m] = std (Inf); assert (v, NaN); assert (m, Inf); ***** test <*63203> [v, m] = std (NaN); assert (v, NaN); assert (m, NaN); ***** test <*63203> [v, m] = std ([1, Inf, 3]); assert (v, NaN); assert (m, Inf); ***** test <*63203> [v, m] = std ([1, Inf, 3]'); assert (v, NaN); assert (m, Inf); ***** test <*63203> [v, m] = std ([1, NaN, 3]); assert (v, NaN); assert (m, NaN); ***** test <*63203> [v, m] = std ([1, NaN, 3]'); assert (v, NaN); assert (m, NaN); ***** test <*63203> [v, m] = std ([1, Inf, 3], [], 1); assert (v, [0, NaN, 0]); assert (m, [1, Inf, 3]); ***** test <*63203> [v, m] = std ([1, Inf, 3], [], 2); assert (v, NaN); assert (m, Inf); ***** test <*63203> [v, m] = std ([1, Inf, 3], [], 3); assert (v, [0, NaN, 0]); assert (m, [1, Inf, 3]); ***** test <*63203> [v, m] = std ([1, NaN, 3], [], 1); assert (v, [0, NaN, 0]); assert (m, [1, NaN, 3]); ***** test <*63203> [v, m] = std ([1, NaN, 3], [], 2); assert (v, NaN); assert (m, NaN); ***** test <*63203> [v, m] = std ([1, NaN, 3], [], 3); assert (v, [0, NaN, 0]); assert (m, [1, NaN, 3]); ***** test <*63203> [v, m] = std ([1, 2, 3; 3, Inf, 5]); assert (v, sqrt ([2, NaN, 2])); assert (m, [2, Inf, 4]); ***** test <*63203> [v, m] = std ([1, Inf, 3; 3, Inf, 5]); assert (v, sqrt ([2, NaN, 2])); assert (m, [2, Inf, 4]); ***** test <*63203> [v, m] = std ([1, 2, 3; 3, NaN, 5]); assert (v, sqrt ([2, NaN, 2])); assert (m, [2, NaN, 4]); ***** test <*63203> [v, m] = std ([1, NaN, 3; 3, NaN, 5]); assert (v, sqrt ([2, NaN, 2])); assert (m, [2, NaN, 4]); ***** test <*63203> [v, m] = std ([Inf, 2, NaN]); assert (v, NaN); assert (m, NaN); ***** test <*63203> [v, m] = std ([Inf, 2, NaN]'); assert (v, NaN); assert (m, NaN); ***** test <*63203> [v, m] = std ([NaN, 2, Inf]); assert (v, NaN); assert (m, NaN); ***** test <*63203> [v, m] = std ([NaN, 2, Inf]'); assert (v, NaN); assert (m, NaN); ***** test <*63203> [v, m] = std ([Inf, 2, NaN], [], 1); assert (v, [NaN, 0, NaN]); assert (m, [Inf, 2, NaN]); ***** test <*63203> [v, m] = std ([Inf, 2, NaN], [], 2); assert (v, NaN); assert (m, NaN); ***** test <*63203> [v, m] = std ([NaN, 2, Inf], [], 1); assert (v, [NaN, 0, NaN]); assert (m, [NaN, 2, Inf]); ***** test <*63203> [v, m] = std ([NaN, 2, Inf], [], 2); assert (v, NaN); assert (m, NaN); ***** test <*63203> [v, m] = std ([1, 3, NaN; 3, 5, Inf]); assert (v, sqrt ([2, 2, NaN])); assert (m, [2, 4, NaN]); ***** test <*63203> [v, m] = std ([1, 3, Inf; 3, 5, NaN]); assert (v, sqrt ([2, 2, NaN])); assert (m, [2, 4, NaN]); ***** test <*63291> [v, m] = std (2 * eye (2)); assert (v, sqrt ([2, 2])); assert (m, [1, 1]); ***** test <*63291> [v, m] = std (4 * eye (2), [1, 3]); assert (v, sqrt ([3, 3])); assert (m, [1, 3]); ***** test <*63291> [v, m] = std (sparse (2 * eye (2))); assert (full (v), sqrt ([2, 2])); assert (full (m), [1, 1]); ***** test <*63291> [v, m] = std (sparse (4 * eye (2)), [1, 3]); assert (full (v), sqrt ([3, 3])); assert (full (m), [1, 3]); ***** test <*63291> [v, m] = std (sparse (eye (2))); assert (issparse (v)); assert (issparse (m)); ***** test <*63291> [v, m] = std (sparse (eye (2)), [1, 3]); assert (issparse (v)); assert (issparse (m)); ***** error std () ***** error std (1, 2, "omitnan", 3) ***** error std (1, 2, 3, 4) ***** error std (1, 2, 3, 4, 5) ***** error std (1, "foo") ***** error std (1, [], "foo") ***** error std ([1 2 3], 2) ***** error std ([1 2], 2, "all") ***** error std ([1 2],0.5, "all") ***** error std (1, -1) ***** error std (1, [1 -1]) ***** error ... std ([1 2 3], [1 -1 0]) ***** error std ({1:5}) ***** error std ("char") ***** error std (['A'; 'B']) ***** error std (1, [], ones (2,2)) ***** error std (1, 0, 1.5) ***** error std (1, [], 0) ***** error std (1, [], 1.5) ***** error std ([1 2 3], [], [-1 1]) ***** error ... std (repmat ([1:20;6:25], [5 2 6 3]), 0, [1 2 2 2]) ***** error ... std ([1 2], eye (2)) ***** error ... std ([1 2 3 4], [1 2; 3 4]) ***** error ... std ([1 2 3 4], [1 2; 3 4], 1) ***** error ... std ([1 2 3 4], [1 2; 3 4], [2 3]) ***** error ... std (ones (2, 2), [1 2], [1 2]) ***** error ... std ([1 2 3 4; 5 6 7 8], [1 2 1 2 1; 1 2 1 2 1], 1) ***** error ... std (repmat ([1:20;6:25], [5 2 6 3]), repmat ([1:20;6:25], [5 2 3]), [2 3]) ***** error std ([1 2 3; 2 3 4], [1 3 4]) ***** error std ([1 2], [1 2 3]) ***** error std (1, [1 2]) ***** error std ([1 2 3; 2 3 4], [1 3 4], 1) ***** error std ([1 2 3; 2 3 4], [1 3], 2) ***** error std ([1 2], [1 2], 1) ***** error <'all' flag cannot be used with DIM or VECDIM options> ... std (1, [], 1, "all") ***** error ... std ([1 2 3; 2 3 4], [1 3], "all") ***** error ... std (repmat ([1:20;6:25], [5 2 6 3]), repmat ([1:20;6:25], [5 2 3]), "all") 162 tests, 162 passed, 0 known failure, 0 skipped [inst/shadow9/median.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/shadow9/median.m ***** assert (median (1), 1) ***** assert (median ([1,2,3]), 2) ***** assert (median ([1,2,3]'), 2) ***** assert (median (cat(3,3,1,2)), 2) ***** assert (median ([3,1,2]), 2) ***** assert (median ([2,4,6,8]), 5) ***** assert (median ([8,2,6,4]), 5) ***** assert (median (single ([1,2,3])), single (2)) ***** assert (median ([1,2], 3), [1,2]) ***** test x = [1, 2, 3, 4, 5, 6]; x2 = x'; y = [1, 2, 3, 4, 5, 6, 7]; y2 = y'; assert (median (x) == median (x2) && median (x) == 3.5); assert (median (y) == median (y2) && median (y) == 4); assert (median ([x2, 2 * x2]), [3.5, 7]); assert (median ([y2, 3 * y2]), [4, 12]); ***** test in = [1 2 3]; out = 2; assert (median (in, "default"), median (in)); assert (median (in, "default"), out); ***** test in = single ([1 2 3]); out = 2; assert (median (in, "default"), single (median (in))); assert (median (in, "default"), single (out)); assert (median (in, "double"), double (out)); assert (median (in, "native"), single (out)); ***** test in = uint8 ([1 2 3]); out = 2; assert (median (in, "default"), double (median (in))); assert (median (in, "default"), double (out)); assert (median (in, "double"), out); assert (median (in, "native"), uint8 (out)); ***** test in = logical ([1 0 1]); out = 1; assert (median (in, "default"), double (median (in))); assert (median (in, "default"), double (out)); assert (median (in, "double"), double (out)); assert (median (in, "native"), double (out)); ***** test x = repmat ([2 2.1 2.2 2 NaN; 3 1 2 NaN 5; 1 1.1 1.4 5 3], [1, 1, 4]); y = repmat ([2 1.1 2 NaN NaN], [1, 1, 4]); assert (median (x), y); assert (median (x, 1), y); y = repmat ([2 1.1 2 3.5 4], [1, 1, 4]); assert (median (x, "omitnan"), y); assert (median (x, 1, "omitnan"), y); y = repmat ([2.05; 2.5; 1.4], [1, 1, 4]); assert (median (x, 2, "omitnan"), y); y = repmat ([NaN; NaN; 1.4], [1, 1, 4]); assert (median (x, 2), y); assert (median (x, "all"), NaN); assert (median (x, "all", "omitnan"), 2); ***** assert (median (cat (3, 3, 1, NaN, 2), "omitnan"), 2) ***** assert (median (cat (3, 3, 1, NaN, 2), 3, "omitnan"), 2) ***** test assert (median (true, "all"), logical (1)); assert (median (false), logical (0)); assert (median ([true false true]), true); assert (median ([true false true], 2), true); assert (median ([true false true], 1), logical ([1 0 1])); assert (median ([true false NaN], 1), [1 0 NaN]); assert (median ([true false NaN], 2), NaN); assert (median ([true false NaN], 2, "omitnan"), 0.5); assert (median ([true false NaN], 2, "omitnan", "native"), double(0.5)); ***** test x = repmat ([1:20;6:25], [5 2 6 3]); assert (size (median (x, [3 2])), [10 1 1 3]); assert (size (median (x, [1 2])), [1 1 6 3]); assert (size (median (x, [1 2 4])), [1 1 6]); assert (size (median (x, [1 4 3])), [1 40]); assert (size (median (x, [1 2 3 4])), [1 1]); ***** assert (median (ones (2,2), 3), ones (2,2)) ***** assert (median (ones (2,2,2), 99), ones (2,2,2)) ***** assert (median (magic (3), 3), magic (3)) ***** assert (median (magic (3), [1 3]), [4, 5, 6]) ***** assert (median (magic (3), [1 99]), [4, 5, 6]) ***** test x = repmat ([2 2.1 2.2 2 NaN; 3 1 2 NaN 5; 1 1.1 1.4 5 3], [1, 1, 4]); assert (median (x, [3 2]), [NaN NaN 1.4]'); assert (median (x, [3 2], "omitnan"), [2.05 2.5 1.4]'); assert (median (x, [1 3]), [2 1.1 2 NaN NaN]); assert (median (x, [1 3], "omitnan"), [2 1.1 2 3.5 4]); ***** assert (median (NaN), NaN) ***** assert (median (NaN, "omitnan"), NaN) ***** assert (median (NaN (2)), [NaN NaN]) ***** assert (median (NaN (2), "omitnan"), [NaN NaN]) ***** assert (median ([1 NaN 3]), NaN) ***** assert (median ([1 NaN 3], 1), [1 NaN 3]) ***** assert (median ([1 NaN 3], 2), NaN) ***** assert (median ([1 NaN 3]'), NaN) ***** assert (median ([1 NaN 3]', 1), NaN) ***** assert (median ([1 NaN 3]', 2), [1; NaN; 3]) ***** assert (median ([1 NaN 3], "omitnan"), 2) ***** assert (median ([1 NaN 3]', "omitnan"), 2) ***** assert (median ([1 NaN 3], 1, "omitnan"), [1 NaN 3]) ***** assert (median ([1 NaN 3], 2, "omitnan"), 2) ***** assert (median ([1 NaN 3]', 1, "omitnan"), 2) ***** assert (median ([1 NaN 3]', 2, "omitnan"), [1; NaN; 3]) ***** assert (median ([1 2 NaN 3]), NaN) ***** assert (median ([1 2 NaN 3], "omitnan"), 2) ***** assert (median ([1,2,NaN;4,5,6;NaN,8,9]), [NaN, 5, NaN]) ***** assert <*64011> (median ([1,2,NaN;4,5,6;NaN,8,9], "omitnan"), [2.5, 5, 7.5], eps) ***** assert (median ([1 2 ; NaN 4]), [NaN 3]) ***** assert (median ([1 2 ; NaN 4], "omitnan"), [1 3]) ***** assert (median ([1 2 ; NaN 4], 1, "omitnan"), [1 3]) ***** assert (median ([1 2 ; NaN 4], 2, "omitnan"), [1.5; 4], eps) ***** assert (median ([1 2 ; NaN 4], 3, "omitnan"), [1 2 ; NaN 4]) ***** assert (median ([NaN 2 ; NaN 4]), [NaN 3]) ***** assert (median ([NaN 2 ; NaN 4], "omitnan"), [NaN 3]) ***** assert (median (ones (1, 0, 3)), NaN (1, 1, 3)) ***** assert <*65405> (median ([NaN NaN], 1, "omitnan"), [NaN NaN]) ***** assert <*65405> (median ([NaN NaN], 2, "omitnan"), NaN) ***** assert <*65405> (median ([NaN NaN]', 1, "omitnan"), NaN) ***** assert <*65405> (median ([NaN NaN]', 2, "omitnan"), [NaN; NaN]) ***** assert <*65405> (median ([NaN NaN], "omitnan"), NaN) ***** assert <*65405> (median ([NaN NaN]', "omitnan"), NaN) ***** assert <*65405> (median (NaN(1,9), 1, "omitnan"), NaN(1,9)) ***** assert <*65405> (median (NaN(1,9), 2, "omitnan"), NaN) ***** assert <*65405> (median (NaN(1,9), 3, "omitnan"), NaN(1,9)) ***** assert <*65405> (median (NaN(9,1), 1, "omitnan"), NaN) ***** assert <*65405> (median (NaN(9,1), 2, "omitnan"), NaN(9,1)) ***** assert <*65405> (median (NaN(9,1), 3, "omitnan"), NaN(9,1)) ***** assert <*65405> (median (NaN(9,2), 1, "omitnan"), NaN(1,2)) ***** assert <*65405> (median (NaN(9,2), 2, "omitnan"), NaN(9,1)) ***** assert <*65405> (median (NaN(9,2), "omitnan"), NaN(1,2)) ***** assert (median (NaN("single")), NaN("single")) ***** assert (median (NaN("single"), "omitnan"), NaN("single")) ***** assert (median (NaN("single"), "double"), NaN("double")) ***** assert (median (single([1 2 ; NaN 4])), single([NaN 3])) ***** assert (median (single([1 2 ; NaN 4]), "double"), double([NaN 3])) ***** assert (median (single([1 2 ; NaN 4]), "omitnan"), single([1 3])) ***** assert (median (single([1 2 ; NaN 4]), "omitnan", "double"), double([1 3])) ***** assert (median (single([NaN 2 ; NaN 4]), "double"), double([NaN 3])) ***** assert (median (single([NaN 2 ; NaN 4]), "omitnan"), single([NaN 3])) ***** assert (median (single([NaN 2 ; NaN 4]), "omitnan", "double"), double([NaN 3])) ***** test <*64011> x = [magic(3), magic(3)]; x([3, 7, 11, 12, 16, 17]) = NaN; ynan = [NaN, 5, NaN, NaN, 5, NaN]; yomitnan = [5.5, 5, 4.5, 8, 5, 2]; assert (median (x), ynan); assert (median (x, "omitnan"), yomitnan, eps); assert (median (cat (3, x, x)), cat (3, ynan, ynan)); assert (median (cat (3, x, x), "omitnan"), cat (3, yomitnan, yomitnan), eps); ***** assert (median (Inf), Inf) ***** assert (median (-Inf), -Inf) ***** assert (median ([-Inf Inf]), NaN) ***** assert (median ([3 Inf]), Inf) ***** assert (median ([3 4 Inf]), 4) ***** assert (median ([Inf 3 4]), 4) ***** assert (median ([Inf 3 Inf]), Inf) ***** assert (median ([1, 2, Inf]), 2) ***** assert (median ([1, 2, Inf, Inf]), Inf) ***** assert (median ([1, -Inf, Inf, Inf]), Inf) ***** assert (median ([-Inf, -Inf, Inf, Inf]), NaN) ***** assert (median([-Inf, Inf, Inf, Inf]), Inf) ***** assert (median([-Inf, -Inf, -Inf, Inf]), -Inf) ***** assert (median([-Inf, -Inf, -Inf, 2]), -Inf) ***** assert (median([-Inf, -Inf, 1, 2]), -Inf) ***** assert (median ([]), NaN) ***** assert (median (ones(1,0)), NaN) ***** assert (median (ones(0,1)), NaN) ***** assert (median ([], 1), NaN(1,0)) ***** assert (median ([], 2), NaN(0,1)) ***** assert (median ([], 3), NaN(0,0)) ***** assert (median (ones(1,0), 1), NaN(1,0)) ***** assert (median (ones(1,0), 2), NaN(1,1)) ***** assert (median (ones(1,0), 3), NaN(1,0)) ***** assert (median (ones(0,1), 1), NaN(1,1)) ***** assert (median (ones(0,1), 2), NaN(0,1)) ***** assert (median (ones(0,1), 3), NaN(0,1)) ***** assert (median (ones(0,1,0,1), 1), NaN(1,1,0)) ***** assert (median (ones(0,1,0,1), 2), NaN(0,1,0)) ***** assert (median (ones(0,1,0,1), 3), NaN(0,1,1)) ***** assert (median (ones(0,1,0,1), 4), NaN(0,1,0)) ***** assert (median([1 3 3i 2 1i]), 2) ***** assert (median([1 2 4i; 3 2i 4]), [2, 1+1i, 2+2i]) ***** shared a, b, x, y old_state = rand ("state"); restore_state = onCleanup (@() rand ("state", old_state)); rand ("state", 2); a = rand (2,3,4,5); b = rand (3,4,6,5); x = sort (a, 4); y = sort (b, 3); ***** assert <*35679> (median (a, 4), x(:, :, :, 3)) ***** assert <*35679> (median (b, 3), (y(:, :, 3, :) + y(:, :, 4, :))/2) ***** shared ## Clear shared to prevent variable echo for any later test failures ***** test x = ones(15,1,4); x([13,15],1,:) = NaN; assert (median (x, 1, "omitnan"), ones (1,1,4)) ***** assert (median ([true, false]), true) ***** assert (median (logical ([])), false) ***** assert (median (uint8 ([1, 3])), uint8 (2)) ***** assert (median (uint8 ([])), uint8 (NaN)) ***** assert (median (uint8 ([NaN 10])), uint8 (5)) ***** assert (median (int8 ([1, 3, 4])), int8 (3)) ***** assert (median (int8 ([])), int8 (NaN)) ***** assert (median (single ([1, 3, 4])), single (3)) ***** assert (median (single ([1, 3, NaN])), single (NaN)) ***** assert <54567> (median (uint8 ([253, 255])), uint8 (254)) ***** assert <54567> (median (uint8 ([253, 254])), uint8 (254)) ***** assert <54567> (median (int8 ([127, 126, 125, 124; 1 3 5 9])), ... int8 ([64 65 65 67])) ***** assert <54567> (median (int8 ([127, 126, 125, 124; 1 3 5 9]), 2), ... int8 ([126; 4])) ***** assert <54567> (median (int64 ([intmax("int64"), intmax("int64")-2])), ... intmax ("int64") - 1) ***** assert <54567> (median ( ... int64 ([intmax("int64"), intmax("int64")-2; 1 2]), 2), ... int64([intmax("int64") - 1; 2])) ***** assert <54567> (median (uint64 ([intmax("uint64"), intmax("uint64")-2])), ... intmax ("uint64") - 1) ***** assert <54567> (median ( ... uint64 ([intmax("uint64"), intmax("uint64")-2; 1 2]), 2), ... uint64([intmax("uint64") - 1; 2])) ***** assert <54567> (median (... [intmin('int8') intmin('int8')+5 intmax('int8')-5 intmax('int8')]), ... int8(-1)) ***** assert <54567> (median ([int8([1 2 3 4]); ... intmin('int8') intmin('int8')+5 intmax('int8')-5 intmax('int8')], 2), ... int8([3;-1])) ***** assert <54567> (median (... [intmin('int64') intmin('int64')+5 intmax('int64')-5 intmax('int64')]), ... int64(-1)) ***** assert <54567> (median ([int64([1 2 3 4]); ... intmin('int64') intmin('int64')+5 intmax('int64')-5 intmax('int64')], 2), ... int64([3;-1])) ***** assert <54567> (median ([intmax("uint64"), intmax("uint64")-2]), ... intmax("uint64")-1) ***** assert <54567> (median ([intmax("uint64"), intmax("uint64")-2], "default"), ... double(intmax("uint64")-1)) ***** assert <54567> (median ([intmax("uint64"), intmax("uint64")-2], "double"), ... double(intmax("uint64")-1)) ***** assert <54567> (median ([intmax("uint64"), intmax("uint64")-2], "native"), ... intmax("uint64")-1) ***** assert (median ([1 2 3], "aLL"), 2) ***** assert (median ([1 2 3], "OmitNan"), 2) ***** assert (median ([1 2 3], "DOUBle"), 2) ***** error median () ***** error median (1, 2, 3) ***** error median (1, 2, 3, 4) ***** error median (1, "all", 3) ***** error median (1, "b") ***** error median (1, 1, "foo") ***** error <'all' cannot be used with> median (1, 3, "all") ***** error <'all' cannot be used with> median (1, [2 3], "all") ***** error median ({1:5}) ***** error median ("char") ***** error median(1, "double", "native") ***** error median (1, ones (2,2)) ***** error median (1, 1.5) ***** error median (1, 0) ***** error median ([1 2 3], [-1 1]) ***** error median(1, [1 2 2]) 159 tests, 159 passed, 0 known failure, 0 skipped [inst/shadow9/mad.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/shadow9/mad.m ***** assert (mad (1), 0) ***** assert (mad (1,1), 0) ***** assert (mad (1,0,3), 0) ***** assert (mad (1,1,3), 0) ***** assert (mad (1,[],5), 0) ***** assert (mad ([1,2,3]), 2/3) ***** assert (mad ([1,2,3],[]), 2/3) ***** assert (mad ([1,2,3],0), 2/3) ***** assert (mad ([1,2,3],1), 1) ***** assert (mad ([1,2,3],0,2), 2/3) ***** assert (mad ([1,2,3],[],2), 2/3) ***** assert (mad ([1,2,3],1,2), 1) ***** assert (mad ([1,2,3],0,1), zeros (1,3)) ***** assert (mad ([1,2,3],1,1), zeros (1,3)) ***** assert (mad ([1,2,3]',0,2), zeros (3,1)) ***** assert (mad ([1,2,3]',1,2), zeros (3,1)) ***** assert (mad ([1,2,3]',0,1), 2/3) ***** assert (mad ([1,2,3]',1,1), 1) ***** test A = [57, 59, 60, 100, 59, 58, 57, 58, 300, 61, 62, 60, 62, 58, 57]; AA = [A;2*A;3*A]; m0 = [38.000, 39.333, 40.000, 66.667, 39.333, 38.667, 38.000, 38.667, ... 200.000, 40.667, 41.333, 40.000, 41.333, 38.667, 38.000]; m1 = [32.569;65.138; 97.707]; assert (mad (AA), m0, 1e-3); assert (mad (AA,1), A); assert (mad (AA,1,1), A); assert (mad (AA,0,2), m1, 1e-3); assert (mad (AA,1,2), [2;4;6]); assert (mad (A,0,1), zeros (size (A))); assert (mad (A,1,1), zeros (size (A))); ***** test x = repmat ([2 2.1 2.2 2 NaN; 3 1 2 NaN 5; 1 1.1 1.4 5 3], [1, 1, 4]); m0 = repmat ([0.6667, 0.4667, 0.3111, 1.5, 1], [1, 1, 4]); m1 = repmat ([1, 0.1, 0.2, 1.5, 1], [1, 1, 4]); assert (mad (x), m0, 1e-4); assert (mad (x, 1), m1, 1e-14); assert (mad (x, [], [1, 2]), 1.0036 * ones(1,1,4), 1e-4) assert (mad (x, 1, [1, 2]), 0.9 * ones(1,1,4), 1e-14) assert (mad (x, 0, [1, 3]), m0(1,:,1), 1e-4) assert (mad (x, 1, [1, 3]), m1(1,:,1), 1e-14) assert (mad (x, 0, [2, 3]), [0.075; 1.25; 1.36], 1e-14) assert (mad (x, 1, [2, 3]), [0.05; 1; 0.4], 1e-14) assert (mad (x, 0, [1, 2, 3]) == mad (x, 0, "All")) assert (mad (x, 1, [1, 2, 3]) == mad (x, 1, "All")) ***** test x = repmat ([1:20;6:25], [5 2 6 3]); assert (size (mad (x, [], [3 2])), [10 1 1 3]); assert (size (mad (x, 0, [1 2])), [1 1 6 3]); assert (size (mad (x, 1, [1 2 4])), [1 1 6]); assert (size (mad (x, [], [1 4 3])), [1 40]); assert (size (mad (x, 1, [1 2 3 4])), [1 1]); ***** assert (mad (ones (2,2), 0, 3), zeros (2,2)) ***** assert (mad (ones (2,2,2), 1, 99), zeros (2,2,2)) ***** assert (mad (magic (3), 1, 3), zeros (3)) ***** assert (mad (magic (3), 1, [1 3]), [1, 4, 1]) ***** assert (mad (magic (3), 1, [1 99]), [1, 4, 1]) ***** assert (mad ([]), NaN) ***** assert (mad ([], 1), NaN) ***** assert (mad (NaN), NaN) ***** assert (mad (NaN, 1), NaN) ***** assert (mad (Inf), NaN) ***** assert (mad (Inf, 1), NaN) ***** assert (mad (-Inf), NaN) ***** assert (mad (-Inf, 1), NaN) ***** assert (mad ([-Inf Inf]), NaN) ***** assert (mad ([-Inf Inf], 1), NaN) ***** assert (mad ([3 Inf]), Inf) ***** assert (mad ([3 4 Inf]), Inf) ***** assert (mad ([Inf 3 4]), Inf) ***** assert (mad ([Inf 3 Inf]), Inf) ***** assert (mad ([Inf 3 Inf], 1), Inf) ***** assert (mad ([1 2; 3 Inf]), [1 Inf]) ***** assert (mad ([1 2; 3 Inf], 1), [1 Inf]) ***** assert (mad ([3, 4, Inf]), Inf) ***** assert (mad ([Inf, 3, 4]), Inf) ***** assert (mad ([3, 4, Inf], 0), Inf) ***** assert (mad ([3, 4, Inf], 0, 1), [0, 0, NaN]) ***** assert (mad ([3, 4, Inf], 0, 2), Inf) ***** assert (mad ([3, 4, Inf], 0, 3), [0, 0, NaN]) ***** assert (mad ([3, 4, Inf]', 0), Inf) ***** assert (mad ([3, 4, Inf]', 0, 1), Inf) ***** assert (mad ([3, 4, Inf]', 0, 2), [0; 0; NaN]) ***** assert (mad ([3, 4, Inf]', 0, 3), [0; 0; NaN]) ***** assert (mad ([Inf, 3, 4], 1), 1) ***** assert (mad ([3, 4, Inf], 1), 1) ***** assert (mad ([3, 4, Inf], 1, 1), [0, 0, NaN]) ***** assert (mad ([3, 4, Inf], 1, 2), 1) ***** assert (mad ([3, 4, Inf], 1, 3), [0, 0, NaN]) ***** assert (mad ([3, 4, Inf]', 1), 1) ***** assert (mad ([3, 4, Inf]', 1, 1), 1) ***** assert (mad ([3, 4, Inf]', 1, 2), [0; 0; NaN]) ***** assert (mad ([3, 4, Inf]', 1, 3), [0; 0; NaN]) ***** assert (mad ([3, Inf, Inf], 1), Inf) ***** assert (mad ([3, 4, 5, Inf], 1), 1) ***** assert (mad ([3, 4, Inf, Inf], 1), Inf) ***** assert (mad ([3, Inf, Inf, Inf], 1), Inf) ***** assert (mad ([1, 2; 3, 4; Inf, Inf], 0), [Inf, Inf]) ***** assert (mad ([1, 2; 3, 4; Inf, Inf], 1), [2, 2]) ***** assert (mad ([1, 2; 3, Inf; Inf, Inf], 1), [2, Inf]) ***** assert (mad ([1, 2; 3, 4; 5, 6; Inf, Inf], 1), [2, 2]) ***** assert (mad ([1, 2; 3, 4; 5, Inf; Inf, Inf], 1), [2, Inf]) ***** assert (mad ([Inf, 2; Inf, 4; Inf, Inf], 0), [NaN, Inf]) ***** assert (mad ([Inf, 2; Inf, 4; Inf, Inf], 1), [NaN, 2]) ***** assert (mad ([]), NaN) ***** assert (mad (ones(1,0)), NaN) ***** assert (mad (ones(0,1)), NaN) ***** assert (mad ([], 0, 1), NaN(1,0)) ***** assert (mad ([], 0, 2), NaN(0,1)) ***** assert (mad ([], 0, 3), NaN(0,0)) ***** assert (mad (ones(1,0), 0, 1), NaN(1,0)) ***** assert (mad (ones(1,0), 0, 2), NaN(1,1)) ***** assert (mad (ones(1,0), 0, 3), NaN(1,0)) ***** assert (mad (ones(0,1), 0, 1), NaN(1,1)) ***** assert (mad (ones(0,1), 0, 2), NaN(0,1)) ***** assert (mad (ones(0,1), 0, 3), NaN(0,1)) ***** assert (mad (ones(0,1,0,1), 0, 1), NaN(1,1,0)) ***** assert (mad (ones(0,1,0,1), 0, 2), NaN(0,1,0)) ***** assert (mad (ones(0,1,0,1), 0, 3), NaN(0,1,1)) ***** assert (mad (ones(0,1,0,1), 0, 4), NaN(0,1,0)) ***** assert (mad([1 3 3i 2 1i]), 1.5297, 1e-4) ***** assert (mad([1 3 3i 2 1i], 1), 1) ***** assert (mad([1 2 4i; 3 2i 4]), [1, 1.4142, 2.8284], 1e-4) ***** assert (mad([1 2 4i; 3 2i 4], 1), [1, 1.4142, 2.8284], 1e-4) ***** assert (mad([1 2 4i; 3 2i 4], 1, 2), [1; 1]) ***** assert (mad([1 2 4i; 3 2i 4], 0, 2), [1.9493; 1.8084], 1e-4) ***** assert <*65405> (mad ([-Inf Inf]), NaN) ***** assert <*65405> (mad ([-Inf Inf], 0), NaN) ***** assert <*65405> (mad ([-Inf Inf], 1), NaN) ***** assert <*65405> (mad ([-Inf Inf]', 0), NaN) ***** assert <*65405> (mad ([-Inf Inf]', 1), NaN) ***** assert <*65405> (mad ([-Inf Inf]', 0, 1), NaN) ***** assert <*65405> (mad ([-Inf Inf]', 0, 2), [NaN; NaN]) ***** assert <*65405> (mad ([-Inf Inf]', 0, 3), [NaN; NaN]) ***** assert <*65405> (mad ([-Inf Inf]', 1, 1), NaN) ***** assert <*65405> (mad ([-Inf Inf]', 1, 2), [NaN; NaN]) ***** assert <*65405> (mad ([-Inf Inf]', 1, 3), [NaN; NaN]) ***** assert <*65405> (mad (Inf(2), 0), [NaN, NaN]) ***** assert <*65405> (mad (Inf(2), 1), [NaN, NaN]) ***** assert <*65405> (mad (Inf(2), 0, 1), [NaN, NaN]) ***** assert <*65405> (mad (Inf(2), 0, 2), [NaN; NaN]) ***** assert <*65405> (mad (Inf(2), 0, 3), NaN(2)) ***** assert <*65405> (mad (Inf(2), 1, 1), [NaN, NaN]) ***** assert <*65405> (mad (Inf(2), 1, 2), [NaN; NaN]) ***** assert <*65405> (mad (Inf(2), 1, 3), NaN(2)) ***** assert (mad ([1 2 3], 0, "aLL"), 2/3) ***** assert (mad ([1 2 3], 1, "aLL"), 1) ***** error mad () ***** error mad (1, 2, 3, 4) ***** error mad ("text") ***** error mad ({2 3 4}) ***** error mad (1, "all", 3) ***** error mad (1, "b") ***** error mad (1, 1, "foo") ***** error mad (1, [] ,ones (2,2)) ***** error mad (1, [], 1.5) ***** error mad (1, [], 0) ***** error mad ([1 2 3], [], [-1 1]) ***** error mad(1, [], [1 2 2]) 128 tests, 128 passed, 0 known failure, 0 skipped [inst/shadow9/var.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/shadow9/var.m ***** assert (var (13), 0) ***** assert (var (single (13)), single (0)) ***** assert (var ([1,2,3]), 1) ***** assert (var ([1,2,3], 1), 2/3, eps) ***** assert (var ([1,2,3], [], 1), [0,0,0]) ***** assert (var ([1,2,3], [], 3), [0,0,0]) ***** assert (var (5, 99), 0) ***** assert (var (5, 99, 1), 0) ***** assert (var (5, 99, 2), 0) ***** assert (var ([5 3], [99 99], 2), 1) ***** assert (var ([1:7], [1:7]), 3) ***** assert (var ([eye(3)], [1:3]), [5/36, 2/9, 1/4], eps) ***** assert (var (ones (2,2,2), [1:2], 3), [(zeros (2,2))]) ***** assert (var ([1 2; 3 4], 0, 'all'), var ([1:4])) ***** assert (var (reshape ([1:8], 2, 2, 2), 0, [1 3]), [17/3 17/3], eps) ***** assert (var ([1 2 3;1 2 3], [], [1 2]), 0.8, eps) ***** test x = [-10:10]; y = [x;x+5;x-5]; assert (var (x), 38.5); assert (var (y, [], 2), [38.5; 38.5; 38.5]); assert (var (y, 0, 2), [38.5; 38.5; 38.5]); assert (var (y, 1, 2), ones (3,1) * 36.66666666666666, 1e-14); assert (var (y, "all"), 54.19354838709678, 1e-14); y(2,4) = NaN; assert (var (y, "all"), NaN); assert (var (y, "all", "includenan"), NaN); assert (var (y, "all", "omitnan"), 55.01533580116342, 1e-14); assert (var (y, 0, 2, "includenan"), [38.5; NaN; 38.5]); assert (var (y, [], 2), [38.5; NaN; 38.5]); assert (var (y, [], 2, "omitnan"), [38.5; 37.81842105263158; 38.5], 1e-14); ***** assert (var ([1 NaN 3], [1 2 3], "omitnan"), 0.75, eps) ***** assert (var ([1 2 3], [1 NaN 3], "omitnan"), 0.75, eps) ***** assert (var (magic(3), [1 NaN 3], "omitnan"), [3 12 3], eps) ***** assert (var ([1 NaN 3], [1 2 3], "omitnan", "all"), 0.75, eps) ***** assert (var ([1 NaN 3], [1 2 3], "all", "omitnan"), 0.75, eps) ***** assert (var ([1 2 3], [1 NaN 3], "omitnan", "all"), 0.75, eps) ***** assert (var ([1 NaN 3], [1 2 3], 2, "omitnan"), 0.75, eps) ***** assert (var ([1 2 3], [1 NaN 3], 2, "omitnan"), 0.75, eps) ***** assert (var (magic(3), [1 NaN 3], 1, "omitnan"), [3 12 3], eps) ***** assert (var (magic(3), [1 NaN 3], 2, "omitnan"), [0.75;3;0.75], eps) ***** assert (var ([4 4; 4 6; 6 6], [1 3], 2, 'omitnan'), [0;0.75;0], eps) ***** assert (var ([4 NaN; 4 6; 6 6], [1 2 3], 1, 'omitnan'), [1 0]) ***** assert (var ([4 NaN; 4 6; 6 6], [1 3], 2, 'omitnan'), [0;0.75;0], eps) ***** assert (var (3*reshape(1:18, [3 3 2]), [1 2 3], 1, 'omitnan'), ones(1,3,2)*5) ***** assert (var (reshape(1:18, [3 3 2]), [1 2 3], 2, 'omitnan'), 5*ones(3,1,2)) ***** assert (var (3*reshape(1:18, [3 3 2]), ones (3,3,2), [1 2], 'omitnan'), ... 60 * ones(1,1,2)) ***** assert (var (3*reshape(1:18, [3 3 2]), ones (3,3,2), [1 4], 'omitnan'), ... 6 * ones(1,3,2)) ***** assert (var (6*reshape(1:18, [3 3 2]), ones (3,3,2), [1:3], 'omitnan'), 969) ***** test x = reshape(1:18, [3 3 2]); x([2, 14]) = NaN; w = ones (3,3,2); assert (var (16*x, w, [1:3], 'omitnan'), 6519); ***** test x = reshape(1:18, [3 3 2]); w = ones (3,3,2); w([2, 14]) = NaN; assert (var (16*x, w, [1:3], 'omitnan'), 6519); ***** assert (var ([1 2 3], "aLl"), 1); ***** assert (var ([1 2 3], "OmitNan"), 1); ***** assert (var ([1 2 3], "IncludeNan"), 1); ***** test x = repmat ([1:20;6:25], [5, 2, 6, 3]); assert (size (var (x, 0, [3 2])), [10, 1, 1, 3]); assert (size (var (x, 1, [1 2])), [1, 1, 6, 3]); assert (size (var (x, [], [1 2 4])), [1, 1, 6]); assert (size (var (x, 0, [1 4 3])), [1, 40]); assert (size (var (x, [], [1 2 3 4])), [1, 1]); ***** assert (var (3*magic(3)), [63 144 63]) ***** assert (var (3*magic(3), 'omitnan'), [63 144 63]) ***** assert (var (3*magic(3), 1), [42 96 42]) ***** assert (var (3*magic(3), 1, 'omitnan'), [42 96 42]) ***** assert (var (3*magic(3), ones(1,3), 1), [42 96 42]) ***** assert (var (3*magic(3), ones(1,3), 1, 'omitnan'), [42 96 42]) ***** assert (var (2*magic(3), [1 1 NaN], 1, 'omitnan'), [25 16 1]) ***** assert (var (3*magic(3), ones(3,3)), [42 96 42]) ***** assert (var (3*magic(3), ones(3,3), 'omitnan'), [42 96 42]) ***** assert (var (3*magic(3), [1 1 1; 1 1 1; 1 NaN 1], 'omitnan'), [42 36 42]) ***** assert (var (3*magic(3), ones(3,3), 1), [42 96 42]) ***** assert (var (3*magic(3), ones(3,3), 1, 'omitnan'), [42 96 42]) ***** assert (var (3*magic(3), [1 1 1; 1 1 1; 1 NaN 1], 1, 'omitnan'), [42 36 42]) ***** assert (var (3*magic(3), ones(3,3), [1 4]), [42 96 42]) ***** assert (var (3*magic(3), ones(3,3), [1 4], 'omitnan'), [42 96 42]) ***** assert (var (3*magic(3), [1 1 1; 1 1 1; 1 NaN 1],[1 4],'omitnan'), [42 36 42]) ***** test x = repmat ([1:20;6:25], [5, 2, 6, 3]); v = repmat (33.38912133891213, [10, 1, 1, 3]); assert (var (x, 0, [3, 2]), v, 1e-14); v = repmat (33.250, [10, 1, 1, 3]); assert (var (x, 1, [3, 2]), v, 1e-14); x(2,5,6,3) = NaN; v(2,1,1,3) = NaN; assert (var (x, 1, [3, 2]), v, 4e-14); v = repmat (33.38912133891213, [10 1 1 3]); v(2,1,1,3) = NaN; assert (var (x, [], [3, 2]), v, 4e-14); v(2,1,1,3) = 33.40177912169048; assert (var (x, [], [3, 2], "omitnan"), v, 4e-14); ***** assert (var (ones (2,2,2), [1:2], 3), [(zeros (2, 2))]) ***** assert (var (magic (3), [1:9], "all"), 6.666666666666667, 1e-14) ***** assert (var (ones (2,2), [], 3), zeros (2,2)) ***** assert (var (ones (2,2,2), [], 99), zeros (2,2,2)) ***** assert (var (magic (3), [], 3), zeros (3,3)) ***** assert (var (magic (3), [], 1), [7, 16, 7]) ***** assert (var (magic (3), [], [1 3]), [7, 16, 7]) ***** assert (var (magic (3), [], [1 99]), [7, 16, 7]) ***** assert (var ([]), NaN) ***** assert (class (var (single ([]))), "single") ***** assert (var ([],[],1), NaN(1,0)) ***** assert (var ([],[],2), NaN(0,1)) ***** assert (var ([],[],3), []) ***** assert (class (var (single ([]), [], 1)), "single") ***** assert (var (ones (1,0)), NaN) ***** assert (var (ones (1,0), [], 1), NaN(1,0)) ***** assert (var (ones (1,0), [], 2), NaN) ***** assert (var (ones (1,0), [], 3), NaN(1,0)) ***** assert (class (var (ones (1, 0, "single"), [], 1)), "single") ***** assert (var (ones (0,1)), NaN) ***** assert (var (ones (0,1), [], 1), NaN) ***** assert (var (ones (0,1), [], 2), NaN(0,1)) ***** assert (var (ones (0,1), [], 3), NaN(0,1)) ***** assert (var (ones (1,3,0,2)), NaN(1,1,0,2)) ***** assert (var (ones (1,3,0,2), [], 1), NaN(1,3,0,2)) ***** assert (var (ones (1,3,0,2), [], 2), NaN(1,1,0,2)) ***** assert (var (ones (1,3,0,2), [], 3), NaN(1,3,1,2)) ***** assert (var (ones (1,3,0,2), [], 4), NaN(1,3,0)) ***** test [~, m] = var ([]); assert (m, NaN); ***** test <*62395> [~, m] = var (13); assert (m, 13); [~, m] = var (single(13)); assert (m, single(13)); [~, m] = var ([1, 2, 3; 3 2 1], []); assert (m, [2 2 2]); [~, m] = var ([1, 2, 3; 3 2 1], [], 1); assert (m, [2 2 2]); [~, m] = var ([1, 2, 3; 3 2 1], [], 2); assert (m, [2 2]'); [~, m] = var ([1, 2, 3; 3 2 1], [], 3); assert (m, [1 2 3; 3 2 1]); ***** test <*62395> [~, m] = var (5,99); assert (m, 5); [~, m] = var ([1:7], [1:7]); assert (m, 5); [~, m] = var ([eye(3)], [1:3]); assert (m, [1/6, 1/3, 0.5], eps); [~, m] = var (ones (2,2,2), [1:2], 3); assert (m, ones (2,2)); [~, m] = var ([1 2; 3 4], 0, 'all'); assert (m, 2.5, eps); [~, m] = var (reshape ([1:8], 2, 2, 2), 0, [1 3]); assert (m, [3.5, 5.5], eps); ***** test [v, m] = var (4 * eye (2), [1, 3]); assert (v, [3, 3]); assert (m, [1, 3]); ***** test <*62395> [~, m] = var ([]); assert (m, NaN); ***** test <*62395> x = repmat ([1:20;6:25], [5, 2, 6, 3]); [~, m] = var (x, 0, [3 2]); assert (m, mean (x, [3 2])); [~, m] = var (x, 0, [1 2]); assert (m, mean (x, [1 2])); [~, m] = var (x, 0, [1 3 4]); assert (m, mean (x, [1 3 4])); ***** test x = repmat ([1:20;6:25], [5, 2, 6, 3]); x(2,5,6,3) = NaN; [~, m] = var (x, 0, [3 2], "omitnan"); assert (m, mean (x, [3 2], "omitnan")); ***** test <*63203> [v, m] = var (Inf); assert (v, NaN); assert (m, Inf); ***** test <*63203> [v, m] = var (NaN); assert (v, NaN); assert (m, NaN); ***** test <*63203> [v, m] = var ([1, Inf, 3]); assert (v, NaN); assert (m, Inf); ***** test <*63203> [v, m] = var ([1, Inf, 3]'); assert (v, NaN); assert (m, Inf); ***** test <*63203> [v, m] = var ([1, NaN, 3]); assert (v, NaN); assert (m, NaN); ***** test <*63203> [v, m] = var ([1, NaN, 3]'); assert (v, NaN); assert (m, NaN); ***** test <*63203> [v, m] = var ([1, Inf, 3], [], 1); assert (v, [0, NaN, 0]); assert (m, [1, Inf, 3]); ***** test <*63203> [v, m] = var ([1, Inf, 3], [], 2); assert (v, NaN); assert (m, Inf); ***** test <*63203> [v, m] = var ([1, Inf, 3], [], 3); assert (v, [0, NaN, 0]); assert (m, [1, Inf, 3]); ***** test <*63203> [v, m] = var ([1, NaN, 3], [], 1); assert (v, [0, NaN, 0]); assert (m, [1, NaN, 3]); ***** test <*63203> [v, m] = var ([1, NaN, 3], [], 2); assert (v, NaN); assert (m, NaN); ***** test <*63203> [v, m] = var ([1, NaN, 3], [], 3); assert (v, [0, NaN, 0]); assert (m, [1, NaN, 3]); ***** test <*63203> [v, m] = var ([1, 2, 3; 3, Inf, 5]); assert (v, [2, NaN, 2]); assert (m, [2, Inf, 4]); ***** test <*63203> [v, m] = var ([1, Inf, 3; 3, Inf, 5]); assert (v, [2, NaN, 2]); assert (m, [2, Inf, 4]); ***** test <*63203> [v, m] = var ([1, 2, 3; 3, NaN, 5]); assert (v, [2, NaN, 2]); assert (m, [2, NaN, 4]); ***** test <*63203> [v, m] = var ([1, NaN, 3; 3, NaN, 5]); assert (v, [2, NaN, 2]); assert (m, [2, NaN, 4]); ***** test <*63203> [v, m] = var ([Inf, 2, NaN]); assert (v, NaN); assert (m, NaN); ***** test <*63203> [v, m] = var ([Inf, 2, NaN]'); assert (v, NaN); assert (m, NaN); ***** test <*63203> [v, m] = var ([NaN, 2, Inf]); assert (v, NaN); assert (m, NaN); ***** test <*63203> [v, m] = var ([NaN, 2, Inf]'); assert (v, NaN); assert (m, NaN); ***** test <*63203> [v, m] = var ([Inf, 2, NaN], [], 1); assert (v, [NaN, 0, NaN]); assert (m, [Inf, 2, NaN]); ***** test <*63203> [v, m] = var ([Inf, 2, NaN], [], 2); assert (v, NaN); assert (m, NaN); ***** test <*63203> [v, m] = var ([NaN, 2, Inf], [], 1); assert (v, [NaN, 0, NaN]); assert (m, [NaN, 2, Inf]); ***** test <*63203> [v, m] = var ([NaN, 2, Inf], [], 2); assert (v, NaN); assert (m, NaN); ***** test <*63203> [v, m] = var ([1, 3, NaN; 3, 5, Inf]); assert (v, [2, 2, NaN]); assert (m, [2, 4, NaN]); ***** test <*63203> [v, m] = var ([1, 3, Inf; 3, 5, NaN]); assert (v, [2, 2, NaN]); assert (m, [2, 4, NaN]); ***** test <*63291> [v, m] = var (2 * eye (2)); assert (v, [2, 2]); assert (m, [1, 1]); ***** test <*63291> [v, m] = var (4 * eye (2), [1, 3]); assert (v, [3, 3]); assert (m, [1, 3]); ***** test <*63291> [v, m] = var (sparse (2 * eye (2))); assert (full (v), [2, 2]); assert (full (m), [1, 1]); ***** test <*63291> [v, m] = var (sparse (4 * eye (2)), [1, 3]); assert (full (v), [3, 3]); assert (full (m), [1, 3]); ***** test<*63291> [v, m] = var (sparse (eye (2))); assert (issparse (v)); assert (issparse (m)); ***** test<*63291> [v, m] = var (sparse (eye (2)), [1, 3]); assert (issparse (v)); assert (issparse (m)); ***** error var () ***** error var (1, 2, "omitnan", 3) ***** error var (1, 2, 3, 4) ***** error var (1, 2, 3, 4, 5) ***** error var (1, "foo") ***** error var (1, [], "foo") ***** error var ([1 2 3], 2) ***** error var ([1 2], 2, "all") ***** error var ([1 2],0.5, "all") ***** error var (1, -1) ***** error var (1, [1 -1]) ***** error ... var ([1 2 3], [1 -1 0]) ***** error var ({1:5}) ***** error var ("char") ***** error var (['A'; 'B']) ***** error var (1, [], ones (2,2)) ***** error var (1, 0, 1.5) ***** error var (1, [], 0) ***** error var (1, [], 1.5) ***** error var ([1 2 3], [], [-1 1]) ***** error ... var (repmat ([1:20;6:25], [5 2 6 3]), 0, [1 2 2 2]) ***** error ... var ([1 2], eye (2)) ***** error ... var ([1 2 3 4], [1 2; 3 4]) ***** error ... var ([1 2 3 4], [1 2; 3 4], 1) ***** error ... var ([1 2 3 4], [1 2; 3 4], [2 3]) ***** error ... var (ones (2, 2), [1 2], [1 2]) ***** error ... var ([1 2 3 4; 5 6 7 8], [1 2 1 2 1; 1 2 1 2 1], 1) ***** error ... var (repmat ([1:20;6:25], [5 2 6 3]), repmat ([1:20;6:25], [5 2 3]), [2 3]) ***** error var ([1 2 3; 2 3 4], [1 3 4]) ***** error var ([1 2], [1 2 3]) ***** error var (1, [1 2]) ***** error var ([1 2 3; 2 3 4], [1 3 4], 1) ***** error var ([1 2 3; 2 3 4], [1 3], 2) ***** error var ([1 2], [1 2], 1) ***** error <'all' flag cannot be used with DIM or VECDIM options> ... var (1, [], 1, "all") ***** error ... var ([1 2 3; 2 3 4], [1 3], "all") ***** error ... var (repmat ([1:20;6:25], [5 2 6 3]), repmat ([1:20;6:25], [5 2 3]), "all") 162 tests, 162 passed, 0 known failure, 0 skipped [inst/dcov.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/dcov.m ***** demo base=@(x) (x- min(x))./(max(x)-min(x)); N = 5e2; x = randn (N,1); x = base (x); z = randn (N,1); z = base (z); # Linear relations cy = [1 0.55 0.3 0 -0.3 -0.55 -1]; ly = x .* cy; ly(:,[1:3 5:end]) = base (ly(:,[1:3 5:end])); # Correlated Gaussian cz = 1 - abs (cy); gy = base ( ly + cz.*z); # Shapes sx = repmat (x,1,7); sy = zeros (size (ly)); v = 2 * rand (size(x,1),2) - 1; sx(:,1) = v(:,1); sy(:,1) = cos(2*pi*sx(:,1)) + 0.5*v(:,2).*exp(-sx(:,1).^2/0.5); R =@(d) [cosd(d) sind(d); -sind(d) cosd(d)]; tmp = R(35) * v.'; sx(:,2) = tmp(1,:); sy(:,2) = tmp(2,:); tmp = R(45) * v.'; sx(:,3) = tmp(1,:); sy(:,3) = tmp(2,:); sx(:,4) = v(:,1); sy(:,4) = sx(:,4).^2 + 0.5*v(:,2); sx(:,5) = v(:,1); sy(:,5) = 3*sign(v(:,2)).*(sx(:,5)).^2 + v(:,2); sx(:,6) = cos (2*pi*v(:,1)) + 0.5*(x-0.5); sy(:,6) = sin (2*pi*v(:,1)) + 0.5*(z-0.5); sx(:,7) = x + sign(v(:,1)); sy(:,7) = z + sign(v(:,2)); sy = base (sy); sx = base (sx); # scaled shape sc = 1/3; ssy = (sy-0.5) * sc + 0.5; n = size (ly,2); ym = 1.2; xm = 0.5; fmt={'horizontalalignment','center'}; ff = "% .2f"; figure (1) for i=1:n subplot(4,n,i); plot (x, gy(:,i), '.b'); axis tight axis off text (xm,ym,sprintf (ff, dcov (x,gy(:,i))),fmt{:}) subplot(4,n,i+n); plot (x, ly(:,i), '.b'); axis tight axis off text (xm,ym,sprintf (ff, dcov (x,ly(:,i))),fmt{:}) subplot(4,n,i+2*n); plot (sx(:,i), sy(:,i), '.b'); axis tight axis off text (xm,ym,sprintf (ff, dcov (sx(:,i),sy(:,i))),fmt{:}) v = axis (); subplot(4,n,i+3*n); plot (sx(:,i), ssy(:,i), '.b'); axis (v) axis off text (xm,ym,sprintf (ff, dcov (sx(:,i),ssy(:,i))),fmt{:}) endfor ***** error dcov (randn (30, 5), randn (25,5)) 1 test, 1 passed, 0 known failure, 0 skipped [inst/cdfcalc.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/cdfcalc.m ***** test x = [2, 4, 3, 2, 4, 3, 2, 5, 6, 4]; [yCDF, xCDF, n, emsg, eid] = cdfcalc (x); assert (yCDF, [0, 0.3, 0.5, 0.8, 0.9, 1]'); assert (xCDF, [2, 3, 4, 5, 6]'); assert (n, 10); ***** shared x x = [2, 4, 3, 2, 4, 3, 2, 5, 6, 4]; ***** error yCDF = cdfcalc (x); ***** error [yCDF, xCDF] = cdfcalc (); ***** error [yCDF, xCDF] = cdfcalc (x, x); ***** warning [yCDF, xCDF] = cdfcalc (ones(10,2)); 5 tests, 5 passed, 0 known failure, 0 skipped [inst/nansum.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/nansum.m ***** assert (nansum ([2 4 NaN 7]), 13) ***** assert (nansum ([2 4 NaN Inf]), Inf) ***** assert (nansum ([1 NaN 3; NaN 5 6; 7 8 NaN]), [8 13 9]) ***** assert (nansum ([1 NaN 3; NaN 5 6; 7 8 NaN], 2), [4; 11; 15]) ***** assert (nansum (single ([1 NaN 3; NaN 5 6; 7 8 NaN])), single ([8 13 9])) ***** assert (nansum (single ([1 NaN 3; NaN 5 6; 7 8 NaN]), "double"), [8 13 9]) ***** assert (nansum (uint8 ([2 4 1 7])), 14) ***** assert (nansum (uint8 ([2 4 1 7]), "native"), uint8 (14)) ***** assert (nansum (uint8 ([2 4 1 7])), 14) 9 tests, 9 passed, 0 known failure, 0 skipped [inst/nanmin.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/nanmin.m ***** assert (nanmin ([2 4 NaN 7]), 2) ***** assert (nanmin ([2 4 NaN Inf]), 2) ***** assert (nanmin ([1 NaN 3; NaN 5 6; 7 8 NaN]), [1, 5, 3]) ***** assert (nanmin ([1 NaN 3; NaN 5 6; 7 8 NaN]'), [1, 5, 7]) ***** assert (nanmin (single ([1 NaN 3; NaN 5 6; 7 8 NaN])), single ([1 5 3])) 5 tests, 5 passed, 0 known failure, 0 skipped [inst/monotone_smooth.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/monotone_smooth.m ***** error ... monotone_smooth (1) ***** error ... monotone_smooth ("char", 1) ***** error ... monotone_smooth ({1,2,3}, 1) ***** error ... monotone_smooth (ones(20,3), 1) ***** error ... monotone_smooth (1, "char") ***** error ... monotone_smooth (1, {1,2,3}) ***** error ... monotone_smooth (1, ones(20,3)) ***** error monotone_smooth (ones (10,1), ones(10,1), [1, 2]) ***** error monotone_smooth (ones (10,1), ones(10,1), {2}) ***** error monotone_smooth (ones (10,1), ones(10,1), "char") 10 tests, 10 passed, 0 known failure, 0 skipped [inst/fullfact.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/fullfact.m ***** demo ## Full factorial design with 3 binary variables fullfact (3) ***** demo ## Full factorial design with 3 ordinal variables fullfact ([2, 3, 4]) ***** error fullfact (); ***** error fullfact (2, 5); ***** error fullfact (2.5); ***** error fullfact (0); ***** error fullfact (-3); ***** error fullfact (3+2i); ***** error fullfact (Inf); ***** error fullfact (NaN); ***** error fullfact ([1, 2, -3]); ***** error fullfact ([0, 1, 2]); ***** error fullfact ([1, 2, NaN]); ***** error fullfact ([1, 2, Inf]); ***** test A = fullfact (2); assert (A, [0, 0; 0, 1; 1, 0; 1, 1]); ***** test A = fullfact ([1, 2]); assert (A, [1, 1; 1, 2]); ***** test A = fullfact ([1, 2, 4]); A_out = [1, 1, 1; 1, 1, 2; 1, 1, 3; 1, 1, 4; ... 1, 2, 1; 1, 2, 2; 1, 2, 3; 1, 2, 4]; assert (A, A_out); 15 tests, 15 passed, 0 known failure, 0 skipped [inst/regression_ftest.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/regression_ftest.m ***** error regression_ftest (); ***** error ... regression_ftest ([1 2 3]', [2 3 4; 3 4 5]'); ***** error ... regression_ftest ([1 2 NaN]', [2 3 4; 3 4 5]', [1 0.5]); ***** error ... regression_ftest ([1 2 Inf]', [2 3 4; 3 4 5]', [1 0.5]); ***** error ... regression_ftest ([1 2 3+i]', [2 3 4; 3 4 5]', [1 0.5]); ***** error ... regression_ftest ([1 2 3]', [2 3 NaN; 3 4 5]', [1 0.5]); ***** error ... regression_ftest ([1 2 3]', [2 3 Inf; 3 4 5]', [1 0.5]); ***** error ... regression_ftest ([1 2 3]', [2 3 4; 3 4 3+i]', [1 0.5]); ***** error ... regression_ftest ([1 2 3]', [2 3 4; 3 4 5]', [1 0.5], [], "alpha", 0); ***** error ... regression_ftest ([1 2 3]', [2 3 4; 3 4 5]', [1 0.5], [], "alpha", 1.2); ***** error ... regression_ftest ([1 2 3]', [2 3 4; 3 4 5]', [1 0.5], [], "alpha", [.02 .1]); ***** error ... regression_ftest ([1 2 3]', [2 3 4; 3 4 5]', [1 0.5], [], "alpha", "a"); ***** error ... regression_ftest ([1 2 3]', [2 3 4; 3 4 5]', [1 0.5], [], "some", 0.05); ***** error ... regression_ftest ([1 2 3]', [2 3; 3 4]', [1 0.5]); ***** error ... regression_ftest ([1 2; 3 4]', [2 3; 3 4]', [1 0.5]); ***** error ... regression_ftest ([1 2 3]', [2 3 4; 3 4 5]', [1 0.5], ones (2)); ***** error ... regression_ftest ([1 2 3]', [2 3 4; 3 4 5]', [1 0.5], "alpha"); ***** error ... regression_ftest ([1 2 3]', [2 3 4; 3 4 5]', [1 0.5], [1 2]); 18 tests, 18 passed, 0 known failure, 0 skipped [inst/pdist.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/pdist.m ***** shared xy, t, eucl, x xy = [0 1; 0 2; 7 6; 5 6]; t = 1e-3; eucl = @(v,m) sqrt(sumsq(repmat(v,rows(m),1)-m,2)); x = [1 2 3; 4 5 6; 7 8 9; 3 2 1]; ***** assert (pdist (xy), [1.000 8.602 7.071 8.062 6.403 2.000], t); ***** assert (pdist (xy, eucl), [1.000 8.602 7.071 8.062 6.403 2.000], t); ***** assert (pdist (xy, "euclidean"), [1.000 8.602 7.071 8.062 6.403 2.000], t); ***** assert (pdist (xy, "seuclidean"), [0.380 2.735 2.363 2.486 2.070 0.561], t); ***** assert (pdist (xy, "mahalanobis"), [1.384 1.967 2.446 2.384 1.535 2.045], t); ***** assert (pdist (xy, "cityblock"), [1.000 12.00 10.00 11.00 9.000 2.000], t); ***** assert (pdist (xy, "minkowski"), [1.000 8.602 7.071 8.062 6.403 2.000], t); ***** assert (pdist (xy, "minkowski", 3), [1.000 7.763 6.299 7.410 5.738 2.000], t); ***** assert (pdist (xy, "cosine"), [0.000 0.349 0.231 0.349 0.231 0.013], t); ***** assert (pdist (xy, "correlation"), [0.000 2.000 0.000 2.000 0.000 2.000], t); ***** assert (pdist (xy, "spearman"), [0.000 2.000 0.000 2.000 0.000 2.000], t); ***** assert (pdist (xy, "hamming"), [0.500 1.000 1.000 1.000 1.000 0.500], t); ***** assert (pdist (xy, "jaccard"), [1.000 1.000 1.000 1.000 1.000 0.500], t); ***** assert (pdist (xy, "chebychev"), [1.000 7.000 5.000 7.000 5.000 2.000], t); ***** assert (pdist (x), [5.1962, 10.3923, 2.8284, 5.1962, 5.9161, 10.7703], 1e-4); ***** assert (pdist (x, "euclidean"), ... [5.1962, 10.3923, 2.8284, 5.1962, 5.9161, 10.7703], 1e-4); ***** assert (pdist (x, eucl), ... [5.1962, 10.3923, 2.8284, 5.1962, 5.9161, 10.7703], 1e-4); ***** assert (pdist (x, "squaredeuclidean"), [27, 108, 8, 27, 35, 116]); ***** assert (pdist (x, "seuclidean"), ... [1.8071, 3.6142, 0.9831, 1.8071, 1.8143, 3.4854], 1e-4); ***** warning ... pdist (x, "mahalanobis"); ***** assert (pdist (x, "cityblock"), [9, 18, 4, 9, 9, 18]); ***** assert (pdist (x, "minkowski"), ... [5.1962, 10.3923, 2.8284, 5.1962, 5.9161, 10.7703], 1e-4); ***** assert (pdist (x, "minkowski", 3), ... [4.3267, 8.6535, 2.5198, 4.3267, 5.3485, 9.2521], 1e-4); ***** assert (pdist (x, "cosine"), ... [0.0254, 0.0406, 0.2857, 0.0018, 0.1472, 0.1173], 1e-4); ***** assert (pdist (x, "correlation"), [0, 0, 2, 0, 2, 2], 1e-14); ***** assert (pdist (x, "spearman"), [0, 0, 2, 0, 2, 2], 1e-14); ***** assert (pdist (x, "hamming"), [1, 1, 2/3, 1, 1, 1]); ***** assert (pdist (x, "jaccard"), [1, 1, 2/3, 1, 1, 1]); ***** assert (pdist (x, "chebychev"), [3, 6, 2, 3, 5, 8]); 29 tests, 29 passed, 0 known failure, 0 skipped [inst/kruskalwallis.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/kruskalwallis.m ***** demo x = meshgrid (1:6); x = x + normrnd (0, 1, 6, 6); kruskalwallis (x, [], 'off'); ***** demo x = meshgrid (1:6); x = x + normrnd (0, 1, 6, 6); [p, atab] = kruskalwallis(x); ***** demo x = ones (30, 4) .* [-2, 0, 1, 5]; x = x + normrnd (0, 2, 30, 4); group = {"A", "B", "C", "D"}; kruskalwallis (x, group); ***** test data = [1.006, 0.996, 0.998, 1.000, 0.992, 0.993, 1.002, 0.999, 0.994, 1.000, ... 0.998, 1.006, 1.000, 1.002, 0.997, 0.998, 0.996, 1.000, 1.006, 0.988, ... 0.991, 0.987, 0.997, 0.999, 0.995, 0.994, 1.000, 0.999, 0.996, 0.996, ... 1.005, 1.002, 0.994, 1.000, 0.995, 0.994, 0.998, 0.996, 1.002, 0.996, ... 0.998, 0.998, 0.982, 0.990, 1.002, 0.984, 0.996, 0.993, 0.980, 0.996, ... 1.009, 1.013, 1.009, 0.997, 0.988, 1.002, 0.995, 0.998, 0.981, 0.996, ... 0.990, 1.004, 0.996, 1.001, 0.998, 1.000, 1.018, 1.010, 0.996, 1.002, ... 0.998, 1.000, 1.006, 1.000, 1.002, 0.996, 0.998, 0.996, 1.002, 1.006, ... 1.002, 0.998, 0.996, 0.995, 0.996, 1.004, 1.004, 0.998, 0.999, 0.991, ... 0.991, 0.995, 0.984, 0.994, 0.997, 0.997, 0.991, 0.998, 1.004, 0.997]; group = [1:10] .* ones (10,10); group = group(:); [p, tbl] = kruskalwallis (data, group, "off"); assert (p, 0.048229, 1e-6); assert (tbl{2,5}, 17.03124, 1e-5); assert (tbl{2,3}, 9, 0); assert (tbl{4,2}, 82655.5, 1e-16); data = reshape (data, 10, 10); [p, tbl, stats] = kruskalwallis (data, [], "off"); assert (p, 0.048229, 1e-6); assert (tbl{2,5}, 17.03124, 1e-5); assert (tbl{2,3}, 9, 0); assert (tbl{4,2}, 82655.5, 1e-16); means = [51.85, 60.45, 37.6, 51.1, 29.5, 54.25, 64.55, 66.7, 53.65, 35.35]; N = 10 * ones (1, 10); assert (stats.meanranks, means, 1e-6); assert (length (stats.gnames), 10, 0); assert (stats.n, N, 0); 1 test, 1 passed, 0 known failure, 0 skipped [inst/nanmax.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/nanmax.m ***** assert (nanmax ([2 4 NaN 7]), 7) ***** assert (nanmax ([2 4 NaN Inf]), Inf) ***** assert (nanmax ([1 NaN 3; NaN 5 6; 7 8 NaN]), [7, 8, 6]) ***** assert (nanmax ([1 NaN 3; NaN 5 6; 7 8 NaN]'), [3, 6, 8]) ***** assert (nanmax (single ([1 NaN 3; NaN 5 6; 7 8 NaN])), single ([7 8 6])) 5 tests, 5 passed, 0 known failure, 0 skipped [inst/friedman.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/friedman.m ***** demo load popcorn; friedman (popcorn, 3); ***** demo load popcorn; [p, atab] = friedman (popcorn, 3, "off"); disp (p); ***** test popcorn = [5.5, 4.5, 3.5; 5.5, 4.5, 4.0; 6.0, 4.0, 3.0; ... 6.5, 5.0, 4.0; 7.0, 5.5, 5.0; 7.0, 5.0, 4.5]; [p, atab] = friedman (popcorn, 3, "off"); assert (p, 0.001028853354594794, 1e-14); assert (atab{2,2}, 99.75, 1e-14); assert (atab{2,3}, 2, 0); assert (atab{2,4}, 49.875, 1e-14); assert (atab{2,5}, 13.75862068965517, 1e-14); assert (atab{2,6}, 0.001028853354594794, 1e-14); assert (atab{3,2}, 0.08333333333333215, 1e-14); assert (atab{3,4}, 0.04166666666666607, 1e-14); assert (atab{4,3}, 12, 0); ***** test popcorn = [5.5, 4.5, 3.5; 5.5, 4.5, 4.0; 6.0, 4.0, 3.0; ... 6.5, 5.0, 4.0; 7.0, 5.5, 5.0; 7.0, 5.0, 4.5]; [p, atab, stats] = friedman (popcorn, 3, "off"); assert (atab{5,2}, 116, 0); assert (atab{5,3}, 17, 0); assert (stats.source, "friedman"); assert (stats.n, 2); assert (stats.meanranks, [8, 4.75, 2.25], 0); assert (stats.sigma, 2.692582403567252, 1e-14); 2 tests, 2 passed, 0 known failure, 0 skipped [inst/hist3.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/hist3.m ***** demo X = [ 1 1 1 1 1 10 1 10 5 5 5 5 5 5 5 5 5 5 7 3 7 3 7 3 10 10 10 10]; hist3 (X) ***** test N_exp = [ 0 0 0 5 20 0 0 10 15 0 0 15 10 0 0 20 5 0 0 0]; n = 100; x = [1:n]'; y = [n:-1:1]'; D = [x y]; N = hist3 (D, [4 5]); assert (N, N_exp); ***** test N_exp = [0 0 0 0 1 0 0 0 0 1 0 0 0 0 1 1 1 1 1 93]; n = 100; x = [1:n]'; y = [n:-1:1]'; D = [x y]; C{1} = [1 1.7 3 4]; C{2} = [1:5]; N = hist3 (D, C); assert (N, N_exp); ***** test D = [1 1; 3 1; 3 3; 3 1]; [c, nn] = hist3 (D, {0:4, 0:4}); exp_c = zeros (5); exp_c([7 9 19]) = [1 2 1]; assert (c, exp_c); assert (nn, {0:4, 0:4}); ***** test for i = 10 assert (size (hist3 (rand (9, 2), "Edges", {[0:.2:1]; [0:.2:1]})), [6 6]) endfor ***** test edge_1 = linspace (0, 10, 10); edge_2 = linspace (0, 50, 10); [c, nn] = hist3 ([1:10; 1:5:50]', "Edges", {edge_1, edge_2}); exp_c = zeros (10, 10); exp_c([1 12 13 24 35 46 57 68 79 90]) = 1; assert (c, exp_c); assert (nn{1}, edge_1 + edge_1(2)/2, eps*10^4) assert (nn{2}, edge_2 + edge_2(2)/2, eps*10^4) ***** shared X X = [ 5 2 5 3 1 4 5 3 4 4 1 2 2 3 3 3 5 4 5 3]; ***** test N = zeros (10); N([1 10 53 56 60 91 98 100]) = [1 1 1 1 3 1 1 1]; C = {(1.2:0.4:4.8), (2.1:0.2:3.9)}; assert (nthargout ([1 2], @hist3, X), {N C}, eps*10^3) ***** test N = zeros (5, 7); N([1 5 17 18 20 31 34 35]) = [1 1 1 1 3 1 1 1]; C = {(1.4:0.8:4.6), ((2+(1/7)):(2/7):(4-(1/7)))}; assert (nthargout ([1 2], @hist3, X, [5 7]), {N C}, eps*10^3) assert (nthargout ([1 2], @hist3, X, "Nbins", [5 7]), {N C}, eps*10^3) ***** test N = [0 1 0; 0 1 0; 0 0 1; 0 0 0]; C = {(2:5), (2.5:1:4.5)}; assert (nthargout ([1 2], @hist3, X, "Edges", {(1.5:4.5), (2:4)}), {N C}) ***** test N = [0 0 1 0 1 0; 0 0 0 1 0 0; 0 0 1 4 2 0]; C = {(1.2:3.2), (0:5)}; assert (nthargout ([1 2], @hist3, X, "Ctrs", C), {N C}) assert (nthargout ([1 2], @hist3, X, C), {N C}) ***** test [~, C] = hist3 (rand (10, 2), "Edges", {[0 .05 .15 .35 .55 .95], [-1 .05 .07 .2 .3 .5 .89 1.2]}); C_exp = {[ 0.025 0.1 0.25 0.45 0.75 1.15], ... [-0.475 0.06 0.135 0.25 0.4 0.695 1.045 1.355]}; assert (C, C_exp, eps*10^2) ***** test Xv = repmat ([1:10]', [1 2]); ## Test Centers assert (hist3 (Xv, "Ctrs", {1:10, 1:10}), eye (10)) N_exp = eye (6); N_exp([1 end]) = 3; assert (hist3 (Xv, "Ctrs", {3:8, 3:8}), N_exp) N_exp = zeros (8, 6); N_exp([1 2 11 20 29 38 47 48]) = [2 1 1 1 1 1 1 2]; assert (hist3 (Xv, "Ctrs", {2:9, 3:8}), N_exp) ## Test Edges assert (hist3 (Xv, "Edges", {1:10, 1:10}), eye (10)) assert (hist3 (Xv, "Edges", {3:8, 3:8}), eye (6)) assert (hist3 (Xv, "Edges", {2:9, 3:8}), [zeros(1, 6); eye(6); zeros(1, 6)]) N_exp = zeros (14); N_exp(3:12, 3:12) = eye (10); assert (hist3 (Xv, "Edges", {-1:12, -1:12}), N_exp) ## Test for Nbins assert (hist3 (Xv), eye (10)) assert (hist3 (Xv, [10 10]), eye (10)) assert (hist3 (Xv, "nbins", [10 10]), eye (10)) assert (hist3 (Xv, [5 5]), eye (5) * 2) N_exp = zeros (7, 5); N_exp([1 9 10 18 26 27 35]) = [2 1 1 2 1 1 2]; assert (hist3 (Xv, [7 5]), N_exp) ***** test # bug #51059 D = [1 1; NaN 2; 3 1; 3 3; 1 NaN; 3 1]; [c, nn] = hist3 (D, {0:4, 0:4}); exp_c = zeros (5); exp_c([7 9 19]) = [1 2 1]; assert (c, exp_c) assert (nn, {0:4, 0:4}) ***** test [c, nn] = hist3 ([1 8]); exp_c = zeros (10, 10); exp_c(6, 6) = 1; exp_nn = {-4:5, 3:12}; assert (c, exp_c) assert (nn, exp_nn, eps) [c, nn] = hist3 ([1 8], [10 11]); exp_c = zeros (10, 11); exp_c(6, 6) = 1; exp_nn = {-4:5, 3:13}; assert (c, exp_c) assert (nn, exp_nn, eps) ***** test [c, nn] = hist3 ([1 NaN; 2 3; 6 9; 8 NaN]); exp_c = zeros (10, 10); exp_c(2, 1) = 1; exp_c(8, 10) = 1; exp_nn = {linspace(1.35, 7.65, 10) linspace(3.3, 8.7, 10)}; assert (c, exp_c) assert (nn, exp_nn, eps*100) ***** test [c, nn] = hist3 ([1 NaN; 2 NaN; 6 NaN; 8 NaN]); exp_c = zeros (10, 10); exp_nn = {linspace(1.35, 7.65, 10) NaN(1, 10)}; assert (c, exp_c) assert (nn, exp_nn, eps*100) ***** test [c, nn] = hist3 ([1 NaN; NaN 3; NaN 9; 8 NaN]); exp_c = zeros (10, 10); exp_nn = {linspace(1.35, 7.65, 10) linspace(3.3, 8.7, 10)}; assert (c, exp_c) assert (nn, exp_nn, eps*100) 16 tests, 16 passed, 0 known failure, 0 skipped [inst/x2fx.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/x2fx.m ***** test X = [1, 10; 2, 20; 3, 10; 4, 20; 5, 15; 6, 15]; D = x2fx(X,'quadratic'); assert (D(1,:) , [1, 1, 10, 10, 1, 100]); assert (D(2,:) , [1, 2, 20, 40, 4, 400]); ***** test X = [1, 10; 2, 20; 3, 10; 4, 20; 5, 15; 6, 15]; model = [0, 0; 1, 0; 0, 1; 1, 1; 2, 0]; D = x2fx(X,model); assert (D(1,:) , [1, 1, 10, 10, 1]); assert (D(2,:) , [1, 2, 20, 40, 4]); assert (D(4,:) , [1, 4, 20, 80, 16]); ***** error x2fx ([1, 10; 2, 20; 3, 10], [0; 1]); ***** error x2fx ([1, 10, 15; 2, 20, 40; 3, 10, 25], [0, 0; 1, 0; 0, 1; 1, 1; 2, 0]); ***** error x2fx ([1, 10; 2, 20; 3, 10], "whatever"); 5 tests, 5 passed, 0 known failure, 0 skipped [inst/trimmean.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/trimmean.m ***** test x = reshape (1:40, [5, 4, 2]); x([3, 37]) = -100; assert (trimmean (x, 10, "all"), 19.4722, 1e-4); ***** test x = reshape (1:40, [5, 4, 2]); x([3, 37]) = -100; out = trimmean (x, 10, [1, 2]); assert (out(1,1,1), 10.3889, 1e-4); assert (out(1,1,2), 29.6111, 1e-4); ***** test x = reshape (1:40, [5, 4, 2]); x([3, 37]) = -100; x([4, 38]) = NaN; assert (trimmean (x, 10, "all"), 19.3824, 1e-4); ***** test x = reshape (1:40, [5, 4, 2]); x([3, 37]) = -100; out = trimmean (x, 10, 1); assert (out(:,:,1), [-17.6, 8, 13, 18]); assert (out(:,:,2), [23, 28, 33, 10.6]); ***** test x = reshape (1:40, [5, 4, 2]); x([3, 37]) = -100; x([4, 38]) = NaN; out = trimmean (x, 10, 1); assert (out(:,:,1), [-23, 8, 13, 18]); assert (out(:,:,2), [23, 28, 33, 3.75]); ***** test x = reshape (1:40, [5, 4, 2]); x([3, 37]) = -100; out = trimmean (x, 10, 2); assert (out(:,:,1), [8.5; 9.5; -15.25; 11.5; 12.5]); assert (out(:,:,2), [28.5; -4.75; 30.5; 31.5; 32.5]); ***** test x = reshape (1:40, [5, 4, 2]); x([3, 37]) = -100; x([4, 38]) = NaN; out = trimmean (x, 10, 2); assert (out(:,:,1), [8.5; 9.5; -15.25; 14; 12.5]); assert (out(:,:,2), [28.5; -4.75; 28; 31.5; 32.5]); ***** test x = reshape (1:40, [5, 4, 2]); x([3, 37]) = -100; out = trimmean (x, 10, [1, 2, 3]); assert (out, trimmean (x, 10, "all")); ***** test x = reshape (1:40, [5, 4, 2]); x([3, 37]) = -100; x([4, 38]) = NaN; out = trimmean (x, 10, [1, 2]); assert (out(1,1,1), 10.7647, 1e-4); assert (out(1,1,2), 29.1176, 1e-4); ***** test x = reshape (1:40, [5, 4, 2]); x([3, 37]) = -100; x([4, 38]) = NaN; out = trimmean (x, 10, [1, 3]); assert (out, [2.5556, 18, 23, 11.6667], 1e-4); ***** test x = reshape (1:40, [5, 4, 2]); x([3, 37]) = -100; x([4, 38]) = NaN; out = trimmean (x, 10, [2, 3]); assert (out, [18.5; 2.3750; 3.2857; 24; 22.5], 1e-4); ***** test x = reshape (1:40, [5, 4, 2]); x([3, 37]) = -100; x([4, 38]) = NaN; out = trimmean (x, 10, [1, 2, 3]); assert (out, trimmean (x, 10, "all")); ***** test x = reshape (1:40, [5, 4, 2]); x([3, 37]) = -100; x([4, 38]) = NaN; out = trimmean (x, 10, [2, 3, 5]); assert (out, [18.5; 2.3750; 3.2857; 24; 22.5], 1e-4); ***** assert (trimmean (reshape (1:40, [5, 4, 2]), 10, 4), reshape(1:40, [5, 4, 2])) ***** assert (trimmean ([], 10), NaN) ***** assert (trimmean ([1;2;3;4;5], 10, 2), [1;2;3;4;5]) ***** error trimmean (1) ***** error trimmean (1,2,3,4,5) ***** error trimmean ([1 2 3 4], -10) ***** error trimmean ([1 2 3 4], 100) ***** error trimmean ([1 2 3 4], 10, "flag") ***** error trimmean ([1 2 3 4], 10, "flag", 1) ***** error ... trimmean ([1 2 3 4], 10, -1) ***** error ... trimmean ([1 2 3 4], 10, "floor", -1) ***** error ... trimmean (reshape (1:40, [5, 4, 2]), 10, [-1, 2]) ***** error ... trimmean (reshape (1:40, [5, 4, 2]), 10, [1, 2, 2]) 26 tests, 26 passed, 0 known failure, 0 skipped [inst/multcompare.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/multcompare.m ***** demo ## Demonstration using balanced one-way ANOVA from anova1 x = ones (50, 4) .* [-2, 0, 1, 5]; randn ("seed", 1); # for reproducibility x = x + normrnd (0, 2, 50, 4); groups = {"A", "B", "C", "D"}; [p, tbl, stats] = anova1 (x, groups, "off"); multcompare (stats); ***** demo ## Demonstration using unbalanced one-way ANOVA example from anovan dv = [ 8.706 10.362 11.552 6.941 10.983 10.092 6.421 14.943 15.931 ... 22.968 18.590 16.567 15.944 21.637 14.492 17.965 18.851 22.891 ... 22.028 16.884 17.252 18.325 25.435 19.141 21.238 22.196 18.038 ... 22.628 31.163 26.053 24.419 32.145 28.966 30.207 29.142 33.212 ... 25.694 ]'; g = [1 1 1 1 1 1 1 1 2 2 2 2 2 3 3 3 3 3 3 3 3 ... 4 4 4 4 4 4 4 5 5 5 5 5 5 5 5 5]'; [P,ATAB, STATS] = anovan (dv, g, "varnames", "score", "display", "off"); [C, M, H, GNAMES] = multcompare (STATS, "dim", 1, "ctype", "holm", ... "ControlGroup", 1, "display", "on") ***** demo ## Demonstration using factorial ANCOVA example from anovan score = [95.6 82.2 97.2 96.4 81.4 83.6 89.4 83.8 83.3 85.7 ... 97.2 78.2 78.9 91.8 86.9 84.1 88.6 89.8 87.3 85.4 ... 81.8 65.8 68.1 70.0 69.9 75.1 72.3 70.9 71.5 72.5 ... 84.9 96.1 94.6 82.5 90.7 87.0 86.8 93.3 87.6 92.4 ... 100. 80.5 92.9 84.0 88.4 91.1 85.7 91.3 92.3 87.9 ... 91.7 88.6 75.8 75.7 75.3 82.4 80.1 86.0 81.8 82.5]'; treatment = {"yes" "yes" "yes" "yes" "yes" "yes" "yes" "yes" "yes" "yes" ... "yes" "yes" "yes" "yes" "yes" "yes" "yes" "yes" "yes" "yes" ... "yes" "yes" "yes" "yes" "yes" "yes" "yes" "yes" "yes" "yes" ... "no" "no" "no" "no" "no" "no" "no" "no" "no" "no" ... "no" "no" "no" "no" "no" "no" "no" "no" "no" "no" ... "no" "no" "no" "no" "no" "no" "no" "no" "no" "no"}'; exercise = {"lo" "lo" "lo" "lo" "lo" "lo" "lo" "lo" "lo" "lo" ... "mid" "mid" "mid" "mid" "mid" "mid" "mid" "mid" "mid" "mid" ... "hi" "hi" "hi" "hi" "hi" "hi" "hi" "hi" "hi" "hi" ... "lo" "lo" "lo" "lo" "lo" "lo" "lo" "lo" "lo" "lo" ... "mid" "mid" "mid" "mid" "mid" "mid" "mid" "mid" "mid" "mid" ... "hi" "hi" "hi" "hi" "hi" "hi" "hi" "hi" "hi" "hi"}'; age = [59 65 70 66 61 65 57 61 58 55 62 61 60 59 55 57 60 63 62 57 ... 58 56 57 59 59 60 55 53 55 58 68 62 61 54 59 63 60 67 60 67 ... 75 54 57 62 65 60 58 61 65 57 56 58 58 58 52 53 60 62 61 61]'; [P, ATAB, STATS] = anovan (score, {treatment, exercise, age}, "model", ... [1 0 0; 0 1 0; 0 0 1; 1 1 0], "continuous", 3, ... "sstype", "h", "display", "off", "contrasts", ... {"simple","poly",""}); [C, M, H, GNAMES] = multcompare (STATS, "dim", [1 2], "ctype", "holm", ... "display", "on") ***** demo ## Demonstration using one-way ANOVA from anovan, with fit by weighted least ## squares to account for heteroskedasticity. g = [1, 1, 1, 1, 1, 1, 1, 1, ... 2, 2, 2, 2, 2, 2, 2, 2, ... 3, 3, 3, 3, 3, 3, 3, 3]'; y = [13, 16, 16, 7, 11, 5, 1, 9, ... 10, 25, 66, 43, 47, 56, 6, 39, ... 11, 39, 26, 35, 25, 14, 24, 17]'; [P,ATAB,STATS] = anovan(y, g, "display", "off"); fitted = STATS.X * STATS.coeffs(:,1); # fitted values b = polyfit (fitted, abs (STATS.resid), 1); v = polyval (b, fitted); # Variance as a function of the fitted values [P,ATAB,STATS] = anovan (y, g, "weights", v.^-1, "display", "off"); [C, M] = multcompare (STATS, "display", "on", "ctype", "mvt") ***** demo ## Demonstration of p-value adjustments to control the false discovery rate ## Data from Westfall (1997) JASA. 92(437):299-306 p = [.005708; .023544; .024193; .044895; ... .048805; .221227; .395867; .693051; .775755]; padj = multcompare(p,'ctype','fdr') ***** test ## Tests using unbalanced one-way ANOVA example from anovan and anova1 ## Test for anovan - compare pairwise comparisons with matlab for CTYPE "lsd" dv = [ 8.706 10.362 11.552 6.941 10.983 10.092 6.421 14.943 15.931 ... 22.968 18.590 16.567 15.944 21.637 14.492 17.965 18.851 22.891 ... 22.028 16.884 17.252 18.325 25.435 19.141 21.238 22.196 18.038 ... 22.628 31.163 26.053 24.419 32.145 28.966 30.207 29.142 33.212 ... 25.694 ]'; g = [1 1 1 1 1 1 1 1 2 2 2 2 2 3 3 3 3 3 3 3 3 ... 4 4 4 4 4 4 4 5 5 5 5 5 5 5 5 5]'; [P, ATAB, STATS] = anovan (dv, g, "varnames", "score", "display", "off"); [C, M, H, GNAMES] = multcompare (STATS, "dim", 1, "ctype", "lsd", ... "display", "off"); assert (C(1,6), 2.85812420217898e-05, 1e-09); assert (C(2,6), 5.22936741204085e-07, 1e-09); assert (C(3,6), 2.12794763209146e-08, 1e-09); assert (C(4,6), 7.82091664406946e-15, 1e-09); assert (C(5,6), 0.546591417210693, 1e-09); assert (C(6,6), 0.0845897945254446, 1e-09); assert (C(7,6), 9.47436557975328e-08, 1e-09); assert (C(8,6), 0.188873478781067, 1e-09); assert (C(9,6), 4.08974010364197e-08, 1e-09); assert (C(10,6), 4.44427348175241e-06, 1e-09); assert (M(1,1), 10, 1e-09); assert (M(2,1), 18, 1e-09); assert (M(3,1), 19, 1e-09); assert (M(4,1), 21.0001428571429, 1e-09); assert (M(5,1), 29.0001111111111, 1e-09); assert (M(1,2), 1.0177537954095, 1e-09); assert (M(2,2), 1.28736803631001, 1e-09); assert (M(3,2), 1.0177537954095, 1e-09); assert (M(4,2), 1.0880245732889, 1e-09); assert (M(5,2), 0.959547480416536, 1e-09); ## Compare "fdr" adjusted p-values to those obtained using p.adjust in R [C, M, H, GNAMES] = multcompare (STATS, "dim", 1, "ctype", "fdr", ... "display", "off"); assert (C(1,6), 4.08303457454140e-05, 1e-09); assert (C(2,6), 1.04587348240817e-06, 1e-09); assert (C(3,6), 1.06397381604573e-07, 1e-09); assert (C(4,6), 7.82091664406946e-14, 1e-09); assert (C(5,6), 5.46591417210693e-01, 1e-09); assert (C(6,6), 1.05737243156806e-01, 1e-09); assert (C(7,6), 2.36859139493832e-07, 1e-09); assert (C(8,6), 2.09859420867852e-01, 1e-09); assert (C(9,6), 1.36324670121399e-07, 1e-09); assert (C(10,6), 7.40712246958735e-06, 1e-09); ## Compare "hochberg" adjusted p-values to those obtained using p.adjust in R [C, M, H, GNAMES] = multcompare (STATS, "dim", 1, "ctype", "hochberg", ... "display", "off"); assert (C(1,6), 1.14324968087159e-04, 1e-09); assert (C(2,6), 3.13762044722451e-06, 1e-09); assert (C(3,6), 1.91515286888231e-07, 1e-09); assert (C(4,6), 7.82091664406946e-14, 1e-09); assert (C(5,6), 5.46591417210693e-01, 1e-09); assert (C(6,6), 2.53769383576334e-01, 1e-09); assert (C(7,6), 6.63205590582730e-07, 1e-09); assert (C(8,6), 3.77746957562134e-01, 1e-09); assert (C(9,6), 3.27179208291358e-07, 1e-09); assert (C(10,6), 2.22213674087620e-05, 1e-09); ## Compare "holm" adjusted p-values to those obtained using p.adjust in R [C, M, H, GNAMES] = multcompare (STATS, "dim", 1, "ctype", "holm", ... "display", "off"); assert (C(1,6), 1.14324968087159e-04, 1e-09); assert (C(2,6), 3.13762044722451e-06, 1e-09); assert (C(3,6), 1.91515286888231e-07, 1e-09); assert (C(4,6), 7.82091664406946e-14, 1e-09); assert (C(5,6), 5.46591417210693e-01, 1e-09); assert (C(6,6), 2.53769383576334e-01, 1e-09); assert (C(7,6), 6.63205590582730e-07, 1e-09); assert (C(8,6), 3.77746957562134e-01, 1e-09); assert (C(9,6), 3.27179208291358e-07, 1e-09); assert (C(10,6), 2.22213674087620e-05, 1e-09); ## Compare "scheffe" adjusted p-values to those obtained using 'scheffe' in Matlab [C, M, H, GNAMES] = multcompare (STATS, "dim", 1, "ctype", "scheffe", ... "display", "off"); assert (C(1,6), 0.00108105386141085, 1e-09); assert (C(2,6), 2.7779386789517e-05, 1e-09); assert (C(3,6), 1.3599854038198e-06, 1e-09); assert (C(4,6), 7.58830197867751e-13, 1e-09); assert (C(5,6), 0.984039948220281, 1e-09); assert (C(6,6), 0.539077018557706, 1e-09); assert (C(7,6), 5.59475764460574e-06, 1e-09); assert (C(8,6), 0.771173490574105, 1e-09); assert (C(9,6), 2.52838425729905e-06, 1e-09); assert (C(10,6), 0.000200719143889168, 1e-09); ## Compare "bonferroni" adjusted p-values to those obtained using p.adjust in R [C, M, H, GNAMES] = multcompare (STATS, "dim", 1, "ctype", "bonferroni", ... "display", "off"); assert (C(1,6), 2.85812420217898e-04, 1e-09); assert (C(2,6), 5.22936741204085e-06, 1e-09); assert (C(3,6), 2.12794763209146e-07, 1e-09); assert (C(4,6), 7.82091664406946e-14, 1e-09); assert (C(5,6), 1.00000000000000e+00, 1e-09); assert (C(6,6), 8.45897945254446e-01, 1e-09); assert (C(7,6), 9.47436557975328e-07, 1e-09); assert (C(8,6), 1.00000000000000e+00, 1e-09); assert (C(9,6), 4.08974010364197e-07, 1e-09); assert (C(10,6), 4.44427348175241e-05, 1e-09); ## Test for anova1 ("equal")- comparison of results from Matlab [P, ATAB, STATS] = anova1 (dv, g, "off", "equal"); [C, M, H, GNAMES] = multcompare (STATS, "ctype", "lsd", "display", "off"); assert (C(1,6), 2.85812420217898e-05, 1e-09); assert (C(2,6), 5.22936741204085e-07, 1e-09); assert (C(3,6), 2.12794763209146e-08, 1e-09); assert (C(4,6), 7.82091664406946e-15, 1e-09); assert (C(5,6), 0.546591417210693, 1e-09); assert (C(6,6), 0.0845897945254446, 1e-09); assert (C(7,6), 9.47436557975328e-08, 1e-09); assert (C(8,6), 0.188873478781067, 1e-09); assert (C(9,6), 4.08974010364197e-08, 1e-09); assert (C(10,6), 4.44427348175241e-06, 1e-09); assert (M(1,1), 10, 1e-09); assert (M(2,1), 18, 1e-09); assert (M(3,1), 19, 1e-09); assert (M(4,1), 21.0001428571429, 1e-09); assert (M(5,1), 29.0001111111111, 1e-09); assert (M(1,2), 1.0177537954095, 1e-09); assert (M(2,2), 1.28736803631001, 1e-09); assert (M(3,2), 1.0177537954095, 1e-09); assert (M(4,2), 1.0880245732889, 1e-09); assert (M(5,2), 0.959547480416536, 1e-09); ## Test for anova1 ("unequal") - comparison with results from GraphPad Prism 8 [P, ATAB, STATS] = anova1 (dv, g, "off", "unequal"); [C, M, H, GNAMES] = multcompare (STATS, "ctype", "lsd", "display", "off"); assert (C(1,6), 0.001247025266382, 1e-09); assert (C(2,6), 0.000018037115146, 1e-09); assert (C(3,6), 0.000002974595187, 1e-09); assert (C(4,6), 0.000000000786046, 1e-09); assert (C(5,6), 0.5693192886650109, 1e-09); assert (C(6,6), 0.110501699029776, 1e-09); assert (C(7,6), 0.000131226488700, 1e-09); assert (C(8,6), 0.1912101409715992, 1e-09); assert (C(9,6), 0.000005385256394, 1e-09); assert (C(10,6), 0.000074089106171, 1e-09); ***** test ## Test for anova2 ("interaction") - comparison with results from Matlab for column effect popcorn = [5.5, 4.5, 3.5; 5.5, 4.5, 4.0; 6.0, 4.0, 3.0; ... 6.5, 5.0, 4.0; 7.0, 5.5, 5.0; 7.0, 5.0, 4.5]; [P, ATAB, STATS] = anova2 (popcorn, 3, "off"); [C, M, H, GNAMES] = multcompare (STATS, "estimate", "column",... "ctype", "lsd", "display", "off"); assert (C(1,6), 1.49311100811177e-05, 1e-09); assert (C(2,6), 2.20506904243535e-07, 1e-09); assert (C(3,6), 0.00449897860490058, 1e-09); assert (M(1,1), 6.25, 1e-09); assert (M(2,1), 4.75, 1e-09); assert (M(3,1), 4, 1e-09); assert (M(1,2), 0.152145154862547, 1e-09); assert (M(2,2), 0.152145154862547, 1e-09); assert (M(3,2), 0.152145154862547, 1e-09); ***** test ## Test for anova2 ("linear") - comparison with results from GraphPad Prism 8 words = [10 13 13; 6 8 8; 11 14 14; 22 23 25; 16 18 20; ... 15 17 17; 1 1 4; 12 15 17; 9 12 12; 8 9 12]; [P, ATAB, STATS] = anova2 (words, 1, "off", "linear"); [C, M, H, GNAMES] = multcompare (STATS, "estimate", "column",... "ctype", "lsd", "display", "off"); assert (C(1,6), 0.000020799832702, 1e-09); assert (C(2,6), 0.000000035812410, 1e-09); assert (C(3,6), 0.003038942449215, 1e-09); ***** test ## Test for anova2 ("nested") - comparison with results from GraphPad Prism 8 data = [4.5924 7.3809 21.322; -0.5488 9.2085 25.0426; ... 6.1605 13.1147 22.66; 2.3374 15.2654 24.1283; ... 5.1873 12.4188 16.5927; 3.3579 14.3951 10.2129; ... 6.3092 8.5986 9.8934; 3.2831 3.4945 10.0203]; [P, ATAB, STATS] = anova2 (data, 4, "off", "nested"); [C, M, H, GNAMES] = multcompare (STATS, "estimate", "column",... "ctype", "lsd", "display", "off"); assert (C(1,6), 0.261031111511073, 1e-09); assert (C(2,6), 0.065879755907745, 1e-09); assert (C(3,6), 0.241874613529270, 1e-09); ***** shared visibility_setting visibility_setting = get (0, "DefaultFigureVisible"); ***** test set (0, "DefaultFigureVisible", "off"); ## Test for kruskalwallis - comparison with results from MATLAB data = [3,2,4; 5,4,4; 4,2,4; 4,2,4; 4,1,5; ... 4,2,3; 4,3,5; 4,2,4; 5,2,4; 5,3,3]; group = [1:3] .* ones (10,3); [P, ATAB, STATS] = kruskalwallis (data(:), group(:), "off"); C = multcompare (STATS, "ctype", "lsd", "display", "off"); assert (C(1,6), 0.000163089828959986, 1e-09); assert (C(2,6), 0.630298044801257, 1e-09); assert (C(3,6), 0.00100567660695682, 1e-09); C = multcompare (STATS, "ctype", "bonferroni", "display", "off"); assert (C(1,6), 0.000489269486879958, 1e-09); assert (C(2,6), 1, 1e-09); assert (C(3,6), 0.00301702982087047, 1e-09); C = multcompare(STATS, "ctype", "scheffe", "display", "off"); assert (C(1,6), 0.000819054880289573, 1e-09); assert (C(2,6), 0.890628039849261, 1e-09); assert (C(3,6), 0.00447816059021654, 1e-09); set (0, "DefaultFigureVisible", visibility_setting); ***** test set (0, "DefaultFigureVisible", "off"); ## Test for friedman - comparison with results from MATLAB popcorn = [5.5, 4.5, 3.5; 5.5, 4.5, 4.0; 6.0, 4.0, 3.0; ... 6.5, 5.0, 4.0; 7.0, 5.5, 5.0; 7.0, 5.0, 4.5]; [P, ATAB, STATS] = friedman (popcorn, 3, "off"); C = multcompare(STATS, "ctype", "lsd", "display", "off"); assert (C(1,6), 0.227424558028569, 1e-09); assert (C(2,6), 0.0327204848315735, 1e-09); assert (C(3,6), 0.353160353315988, 1e-09); C = multcompare(STATS, "ctype", "bonferroni", "display", "off"); assert (C(1,6), 0.682273674085708, 1e-09); assert (C(2,6), 0.0981614544947206, 1e-09); assert (C(3,6), 1, 1e-09); C = multcompare(STATS, "ctype", "scheffe", "display", "off"); assert (C(1,6), 0.482657360384373, 1e-09); assert (C(2,6), 0.102266573027672, 1e-09); assert (C(3,6), 0.649836502233148, 1e-09); set (0, "DefaultFigureVisible", visibility_setting); ***** test set (0, "DefaultFigureVisible", "off"); ## Test for fitlm - same comparisons as for first anovan example y = [ 8.706 10.362 11.552 6.941 10.983 10.092 6.421 14.943 15.931 ... 22.968 18.590 16.567 15.944 21.637 14.492 17.965 18.851 22.891 ... 22.028 16.884 17.252 18.325 25.435 19.141 21.238 22.196 18.038 ... 22.628 31.163 26.053 24.419 32.145 28.966 30.207 29.142 33.212 ... 25.694 ]'; X = [1 1 1 1 1 1 1 1 2 2 2 2 2 3 3 3 3 3 3 3 3 4 4 4 4 4 4 4 5 5 5 5 5 5 5 5 5]'; [TAB,STATS] = fitlm (X,y,"linear","categorical",1,"display","off",... "contrasts","simple"); [C, M] = multcompare(STATS, "ctype", "lsd", "display", "off"); assert (C(1,6), 2.85812420217898e-05, 1e-09); assert (C(2,6), 5.22936741204085e-07, 1e-09); assert (C(3,6), 2.12794763209146e-08, 1e-09); assert (C(4,6), 7.82091664406946e-15, 1e-09); assert (C(5,6), 0.546591417210693, 1e-09); assert (C(6,6), 0.0845897945254446, 1e-09); assert (C(7,6), 9.47436557975328e-08, 1e-09); assert (C(8,6), 0.188873478781067, 1e-09); assert (C(9,6), 4.08974010364197e-08, 1e-09); assert (C(10,6), 4.44427348175241e-06, 1e-09); assert (M(1,1), 10, 1e-09); assert (M(2,1), 18, 1e-09); assert (M(3,1), 19, 1e-09); assert (M(4,1), 21.0001428571429, 1e-09); assert (M(5,1), 29.0001111111111, 1e-09); assert (M(1,2), 1.0177537954095, 1e-09); assert (M(2,2), 1.28736803631001, 1e-09); assert (M(3,2), 1.0177537954095, 1e-09); assert (M(4,2), 1.0880245732889, 1e-09); assert (M(5,2), 0.959547480416536, 1e-09); set (0, "DefaultFigureVisible", visibility_setting); ***** test ## Test p-value adjustments compared to R stats package function p.adjust ## Data from Westfall (1997) JASA. 92(437):299-306 p = [.005708; .023544; .024193; .044895; ... .048805; .221227; .395867; .693051; .775755]; padj = multcompare (p); assert (padj(1), 0.051372, 1e-06); assert (padj(2), 0.188352, 1e-06); assert (padj(3), 0.188352, 1e-06); assert (padj(4), 0.269370, 1e-06); assert (padj(5), 0.269370, 1e-06); assert (padj(6), 0.884908, 1e-06); assert (padj(7), 1.000000, 1e-06); assert (padj(8), 1.000000, 1e-06); assert (padj(9), 1.000000, 1e-06); padj = multcompare(p,'ctype','holm'); assert (padj(1), 0.051372, 1e-06); assert (padj(2), 0.188352, 1e-06); assert (padj(3), 0.188352, 1e-06); assert (padj(4), 0.269370, 1e-06); assert (padj(5), 0.269370, 1e-06); assert (padj(6), 0.884908, 1e-06); assert (padj(7), 1.000000, 1e-06); assert (padj(8), 1.000000, 1e-06); assert (padj(9), 1.000000, 1e-06); padj = multcompare(p,'ctype','hochberg'); assert (padj(1), 0.051372, 1e-06); assert (padj(2), 0.169351, 1e-06); assert (padj(3), 0.169351, 1e-06); assert (padj(4), 0.244025, 1e-06); assert (padj(5), 0.244025, 1e-06); assert (padj(6), 0.775755, 1e-06); assert (padj(7), 0.775755, 1e-06); assert (padj(8), 0.775755, 1e-06); assert (padj(9), 0.775755, 1e-06); padj = multcompare(p,'ctype','fdr'); assert (padj(1), 0.0513720, 1e-07); assert (padj(2), 0.0725790, 1e-07); assert (padj(3), 0.0725790, 1e-07); assert (padj(4), 0.0878490, 1e-07); assert (padj(5), 0.0878490, 1e-07); assert (padj(6), 0.3318405, 1e-07); assert (padj(7), 0.5089719, 1e-07); assert (padj(8), 0.7757550, 1e-07); assert (padj(9), 0.7757550, 1e-07); 8 tests, 8 passed, 0 known failure, 0 skipped [inst/regression_ttest.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/regression_ttest.m ***** error regression_ttest (); ***** error regression_ttest (1); ***** error ... regression_ttest ([1 2 NaN]', [2 3 4]'); ***** error ... regression_ttest ([1 2 Inf]', [2 3 4]'); ***** error ... regression_ttest ([1 2 3+i]', [2 3 4]'); ***** error ... regression_ttest ([1 2 3]', [2 3 NaN]'); ***** error ... regression_ttest ([1 2 3]', [2 3 Inf]'); ***** error ... regression_ttest ([1 2 3]', [3 4 3+i]'); ***** error ... regression_ttest ([1 2 3]', [3 4 4 5]'); ***** error ... regression_ttest ([1 2 3]', [2 3 4]', "alpha", 0); ***** error ... regression_ttest ([1 2 3]', [2 3 4]', "alpha", 1.2); ***** error ... regression_ttest ([1 2 3]', [2 3 4]', "alpha", [.02 .1]); ***** error ... regression_ttest ([1 2 3]', [2 3 4]', "alpha", "a"); ***** error ... regression_ttest ([1 2 3]', [2 3 4]', "some", 0.05); ***** error ... regression_ttest ([1 2 3]', [2 3 4]', "tail", "val"); ***** error ... regression_ttest ([1 2 3]', [2 3 4]', "alpha", 0.01, "tail", "val"); 16 tests, 16 passed, 0 known failure, 0 skipped [inst/rangesearch.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/rangesearch.m ***** demo ## Generate 1000 random 2D points from each of five distinct multivariate ## normal distributions that form five separate classes N = 1000; d = 10; randn ("seed", 5); X1 = mvnrnd (d * [0, 0], eye (2), 1000); randn ("seed", 6); X2 = mvnrnd (d * [1, 1], eye (2), 1000); randn ("seed", 7); X3 = mvnrnd (d * [-1, -1], eye (2), 1000); randn ("seed", 8); X4 = mvnrnd (d * [1, -1], eye (2), 1000); randn ("seed", 8); X5 = mvnrnd (d * [-1, 1], eye (2), 1000); X = [X1; X2; X3; X4; X5]; ## For each point in X, find the points in X that are within a radius d ## away from the points in X. Idx = rangesearch (X, X, d, "NSMethod", "exhaustive"); ## Select the first point in X (corresponding to the first class) and find ## its nearest neighbors within the radius d. Display these points in ## one color and the remaining points in a different color. x = X(1,:); nearestPoints = X (Idx{1},:); nonNearestIdx = true (size (X, 1), 1); nonNearestIdx(Idx{1}) = false; scatter (X(nonNearestIdx,1), X(nonNearestIdx,2)) hold on scatter (nearestPoints(:,1),nearestPoints(:,2)) scatter (x(1), x(2), "black", "filled") hold off ## Select the last point in X (corresponding to the fifth class) and find ## its nearest neighbors within the radius d. Display these points in ## one color and the remaining points in a different color. x = X(end,:); nearestPoints = X (Idx{1},:); nonNearestIdx = true (size (X, 1), 1); nonNearestIdx(Idx{1}) = false; figure scatter (X(nonNearestIdx,1), X(nonNearestIdx,2)) hold on scatter (nearestPoints(:,1),nearestPoints(:,2)) scatter (x(1), x(2), "black", "filled") hold off ***** shared x, y, X, Y x = [1, 2, 3; 4, 5, 6; 7, 8, 9; 3, 2, 1]; y = [2, 3, 4; 1, 4, 3]; X = [1, 2, 3, 4; 2, 3, 4, 5; 3, 4, 5, 6]; Y = [1, 2, 2, 3; 2, 3, 3, 4]; ***** test [idx, D] = rangesearch (x, y, 4); assert (idx, {[1, 4, 2]; [1, 4]}); assert (D, {[1.7321, 3.3166, 3.4641]; [2, 3.4641]}, 1e-4); ***** test [idx, D] = rangesearch (x, y, 4, "NSMethod", "exhaustive"); assert (idx, {[1, 4, 2]; [1, 4]}); assert (D, {[1.7321, 3.3166, 3.4641]; [2, 3.4641]}, 1e-4); ***** test [idx, D] = rangesearch (x, y, 4, "NSMethod", "kdtree"); assert (idx, {[1, 4, 2]; [1, 4]}); assert (D, {[1.7321, 3.3166, 3.4641]; [2, 3.4641]}, 1e-4); ***** test [idx, D] = rangesearch (x, y, 4, "SortIndices", true); assert (idx, {[1, 4, 2]; [1, 4]}); assert (D, {[1.7321, 3.3166, 3.4641]; [2, 3.4641]}, 1e-4); ***** test [idx, D] = rangesearch (x, y, 4, "SortIndices", false); assert (idx, {[1, 2, 4]; [1, 4]}); assert (D, {[1.7321, 3.4641, 3.3166]; [2, 3.4641]}, 1e-4); ***** test [idx, D] = rangesearch (x, y, 4, "NSMethod", "exhaustive", ... "SortIndices", false); assert (idx, {[1, 2, 4]; [1, 4]}); assert (D, {[1.7321, 3.4641, 3.3166]; [2, 3.4641]}, 1e-4); ***** test eucldist = @(v,m) sqrt(sumsq(repmat(v,rows(m),1)-m,2)); [idx, D] = rangesearch (x, y, 4, "Distance", eucldist); assert (idx, {[1, 4, 2]; [1, 4]}); assert (D, {[1.7321, 3.3166, 3.4641]; [2, 3.4641]}, 1e-4); ***** test eucldist = @(v,m) sqrt(sumsq(repmat(v,rows(m),1)-m,2)); [idx, D] = rangesearch (x, y, 4, "Distance", eucldist, ... "NSMethod", "exhaustive"); assert (idx, {[1, 4, 2]; [1, 4]}); assert (D, {[1.7321, 3.3166, 3.4641]; [2, 3.4641]}, 1e-4); ***** test [idx, D] = rangesearch (x, y, 1.5, "Distance", "seuclidean", ... "NSMethod", "exhaustive"); assert (idx, {[1, 4, 2]; [1, 4]}); assert (D, {[0.6024, 1.0079, 1.2047]; [0.6963, 1.2047]}, 1e-4); ***** test [idx, D] = rangesearch (x, y, 1.5, "Distance", "seuclidean", ... "NSMethod", "exhaustive", "SortIndices", false); assert (idx, {[1, 2, 4]; [1, 4]}); assert (D, {[0.6024, 1.2047, 1.0079]; [0.6963, 1.2047]}, 1e-4); ***** test [idx, D] = rangesearch (X, Y, 4); assert (idx, {[1, 2]; [1, 2, 3]}); assert (D, {[1.4142, 3.1623]; [1.4142, 1.4142, 3.1623]}, 1e-4); ***** test [idx, D] = rangesearch (X, Y, 2); assert (idx, {[1]; [1, 2]}); assert (D, {[1.4142]; [1.4142, 1.4142]}, 1e-4); ***** test eucldist = @(v,m) sqrt(sumsq(repmat(v,rows(m),1)-m,2)); [idx, D] = rangesearch (X, Y, 4, "Distance", eucldist); assert (idx, {[1, 2]; [1, 2, 3]}); assert (D, {[1.4142, 3.1623]; [1.4142, 1.4142, 3.1623]}, 1e-4); ***** test [idx, D] = rangesearch (X, Y, 4, "SortIndices", false); assert (idx, {[1, 2]; [1, 2, 3]}); assert (D, {[1.4142, 3.1623]; [1.4142, 1.4142, 3.1623]}, 1e-4); ***** test [idx, D] = rangesearch (X, Y, 4, "Distance", "seuclidean", ... "NSMethod", "exhaustive"); assert (idx, {[1, 2]; [1, 2, 3]}); assert (D, {[1.4142, 3.1623]; [1.4142, 1.4142, 3.1623]}, 1e-4); ***** error rangesearch (1) ***** error ... rangesearch (ones (4, 5), ones (4)) ***** error ... rangesearch (ones (4, 2), ones (3, 2), 1, "Distance", "euclidean", "some", "some") ***** error ... rangesearch (ones (4, 5), ones (1, 5), 1, "scale", ones (1, 5), "P", 3) ***** error ... rangesearch (ones (4, 5), ones (1, 5), 1, "P",-2) ***** error ... rangesearch (ones (4, 5), ones (1, 5), 1, "scale", ones(4,5), "distance", "euclidean") ***** error ... rangesearch (ones (4, 5), ones (1, 5), 1, "cov", ["some" "some"]) ***** error ... rangesearch (ones (4, 5), ones (1, 5), 1, "cov", ones(4,5), "distance", "euclidean") ***** error ... rangesearch (ones (4, 5), ones (1, 5), 1, "bucketsize", -1) ***** error ... rangesearch (ones (4, 5), ones (1, 5), 1, "NSmethod", "kdtree", "distance", "cosine") ***** error ... rangesearch (ones (4, 5), ones (1, 5), 1, "NSmethod", "kdtree", "distance", "mahalanobis") ***** error ... rangesearch (ones (4, 5), ones (1, 5), 1, "NSmethod", "kdtree", "distance", "correlation") ***** error ... rangesearch (ones (4, 5), ones (1, 5), 1, "NSmethod", "kdtree", "distance", "seuclidean") ***** error ... rangesearch (ones (4, 5), ones (1, 5), 1, "NSmethod", "kdtree", "distance", "spearman") ***** error ... rangesearch (ones (4, 5), ones (1, 5), 1, "NSmethod", "kdtree", "distance", "hamming") ***** error ... rangesearch (ones (4, 5), ones (1, 5), 1, "NSmethod", "kdtree", "distance", "jaccard") 31 tests, 31 passed, 0 known failure, 0 skipped [inst/ppplot.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/ppplot.m ***** test hf = figure ("visible", "off"); unwind_protect ppplot ([2 3 3 4 4 5 6 5 6 7 8 9 8 7 8 9 0 8 7 6 5 4 6 13 8 15 9 9]); unwind_protect_cleanup close (hf); end_unwind_protect ***** error ppplot () ***** error ppplot (ones (2,2)) ***** error ppplot (1, 2) ***** error ppplot ([1 2 3 4], 2) 5 tests, 5 passed, 0 known failure, 0 skipped [inst/dist_obj/MultinomialDistribution.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/dist_obj/MultinomialDistribution.m ***** shared pd, t pd = MultinomialDistribution ([0.1, 0.2, 0.3, 0.2, 0.1, 0.1]); t = truncate (pd, 2, 4); ***** assert (cdf (pd, [2, 3, 4]), [0.3, 0.6, 0.8], eps); ***** assert (cdf (t, [2, 3, 4]), [0.2857, 0.7143, 1], 1e-4); ***** assert (cdf (pd, [1.5, 2, 3, 4]), [0.1, 0.3, 0.6, 0.8], eps); ***** assert (cdf (pd, [1.5, 2-eps, 3, 4]), [0.1, 0.1, 0.6, 0.8], eps); ***** assert (cdf (t, [1.5, 2, 3, 4]), [0, 0.2857, 0.7143, 1], 1e-4); ***** assert (cdf (t, [1.5, 2-eps, 3, 4]), [0, 0, 0.7143, 1], 1e-4); ***** assert (cdf (pd, [1, 2.5, 4, 6]), [0.1, 0.3, 0.8, 1], eps); ***** assert (icdf (pd, [0, 0.2857, 0.7143, 1]), [1, 2, 4, 6]); ***** assert (icdf (t, [0, 0.2857, 0.7143, 1]), [2, 2, 4, 4]); ***** assert (icdf (t, [0, 0.35, 0.7143, 1]), [2, 3, 4, 4]); ***** assert (icdf (t, [0, 0.35, 0.7143, 1, NaN]), [2, 3, 4, 4, NaN]); ***** assert (icdf (t, [-0.5, 0, 0.35, 0.7143, 1, NaN]), [NaN, 2, 3, 4, 4, NaN]); ***** assert (icdf (pd, [-0.5, 0, 0.35, 0.7143, 1, NaN]), [NaN, 1, 3, 4, 6, NaN]); ***** assert (iqr (pd), 2); ***** assert (iqr (t), 2); ***** assert (mean (pd), 3.3, 1e-14); ***** assert (mean (t), 3, eps); ***** assert (median (pd), 3); ***** assert (median (t), 3); ***** assert (pdf (pd, [-5, 1, 2.5, 4, 6, NaN, 9]), [0, 0.1, 0, 0.2, 0.1, NaN, 0]); ***** assert (pdf (pd, [-5, 1, 2, 3, 4, 6, NaN, 9]), ... [0, 0.1, 0.2, 0.3, 0.2, 0.1, NaN, 0]); ***** assert (pdf (t, [-5, 1, 2, 3, 4, 6, NaN, 0]), ... [0, 0, 0.2857, 0.4286, 0.2857, 0, NaN, 0], 1e-4); ***** assert (pdf (t, [-5, 1, 2, 4, 6, NaN, 0]), ... [0, 0, 0.2857, 0.2857, 0, NaN, 0], 1e-4); ***** assert (unique (random (pd, 1000, 5)), [1, 2, 3, 4, 5, 6]'); ***** assert (unique (random (t, 1000, 5)), [2, 3, 4]'); ***** assert (std (pd), 1.4177, 1e-4); ***** assert (std (t), 0.7559, 1e-4); ***** assert (var (pd), 2.0100, 1e-4); ***** assert (var (t), 0.5714, 1e-4); ***** error ... MultinomialDistribution(0) ***** error ... MultinomialDistribution(-1) ***** error ... MultinomialDistribution(Inf) ***** error ... MultinomialDistribution(i) ***** error ... MultinomialDistribution("a") ***** error ... MultinomialDistribution([1, 2]) ***** error ... MultinomialDistribution(NaN) ***** error ... cdf (MultinomialDistribution, 2, "uper") ***** error ... cdf (MultinomialDistribution, 2, 3) ***** error ... cdf (MultinomialDistribution, i) ***** error ... plot (MultinomialDistribution, "Parent") ***** error ... plot (MultinomialDistribution, "PlotType", 12) ***** error ... plot (MultinomialDistribution, "PlotType", {"pdf", "cdf"}) ***** error ... plot (MultinomialDistribution, "PlotType", "pdfcdf") ***** error ... plot (MultinomialDistribution, "Discrete", "pdfcdf") ***** error ... plot (MultinomialDistribution, "Discrete", [1, 0]) ***** error ... plot (MultinomialDistribution, "Discrete", {true}) ***** error ... plot (MultinomialDistribution, "Parent", 12) ***** error ... plot (MultinomialDistribution, "Parent", "hax") ***** error ... truncate (MultinomialDistribution) ***** error ... truncate (MultinomialDistribution, 2) ***** error ... truncate (MultinomialDistribution, 4, 2) ***** shared pd pd = MultinomialDistribution([0.1, 0.2, 0.3, 0.4]); pd(2) = MultinomialDistribution([0.1, 0.2, 0.3, 0.4]); ***** error cdf (pd, 1) ***** error icdf (pd, 0.5) ***** error iqr (pd) ***** error mean (pd) ***** error median (pd) ***** error pdf (pd, 1) ***** error plot (pd) ***** error random (pd) ***** error std (pd) ***** error ... truncate (pd, 2, 4) ***** error var (pd) 62 tests, 62 passed, 0 known failure, 0 skipped [inst/dist_obj/NakagamiDistribution.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/dist_obj/NakagamiDistribution.m ***** shared pd, t pd = NakagamiDistribution; t = truncate (pd, 2, 4); ***** assert (cdf (pd, [0:5]), [0, 0.6321, 0.9817, 0.9999, 1, 1], 1e-4); ***** assert (cdf (t, [0:5]), [0, 0, 0, 0.9933, 1, 1], 1e-4); ***** assert (cdf (pd, [1.5, 2, 3, 4]), [0.8946, 0.9817, 0.9999, 1], 1e-4); ***** assert (cdf (t, [1.5, 2, 3, 4]), [0, 0, 0.9933, 1], 1e-4); ***** assert (icdf (pd, [0:0.2:1]), [0, 0.4724, 0.7147, 0.9572, 1.2686, Inf], 1e-4); ***** assert (icdf (t, [0:0.2:1]), [2, 2.0550, 2.1239, 2.2173, 2.3684, 4], 1e-4); ***** assert (icdf (pd, [-1, 0.4:0.2:1, NaN]), [NaN, 0.7147, 0.9572, 1.2686, Inf, NaN], 1e-4); ***** assert (icdf (t, [-1, 0.4:0.2:1, NaN]), [NaN, 2.1239, 2.2173, 2.3684, 4, NaN], 1e-4); ***** assert (iqr (pd), 0.6411, 1e-4); ***** assert (iqr (t), 0.2502, 1e-4); ***** assert (mean (pd), 0.8862, 1e-4); ***** assert (mean (t), 2.2263, 1e-4); ***** assert (median (pd), 0.8326, 1e-4); ***** assert (median (t), 2.1664, 1e-4); ***** assert (pdf (pd, [0:5]), [0, 0.7358, 0.0733, 0.0007, 0, 0], 1e-4); ***** assert (pdf (t, [0:5]), [0, 0, 4, 0.0404, 0, 0], 1e-4); ***** assert (pdf (pd, [-1, 1:4, NaN]), [0, 0.7358, 0.0733, 0.0007, 0, NaN], 1e-4); ***** assert (pdf (t, [-1, 1:4, NaN]), [0, 0, 4, 0.0404, 0, NaN], 1e-4); ***** assert (isequal (size (random (pd, 100, 50)), [100, 50])) ***** assert (any (random (t, 1000, 1) < 2), false); ***** assert (any (random (t, 1000, 1) > 4), false); ***** assert (std (pd), 0.4633, 1e-4); ***** assert (std (t), 0.2083, 1e-4); ***** assert (var (pd), 0.2146, 1e-4); ***** assert (var (t), 0.0434, 1e-4); ***** error ... NakagamiDistribution(Inf, 1) ***** error ... NakagamiDistribution(i, 1) ***** error ... NakagamiDistribution("a", 1) ***** error ... NakagamiDistribution([1, 2], 1) ***** error ... NakagamiDistribution(NaN, 1) ***** error ... NakagamiDistribution(1, 0) ***** error ... NakagamiDistribution(1, -1) ***** error ... NakagamiDistribution(1, Inf) ***** error ... NakagamiDistribution(1, i) ***** error ... NakagamiDistribution(1, "a") ***** error ... NakagamiDistribution(1, [1, 2]) ***** error ... NakagamiDistribution(1, NaN) ***** error ... cdf (NakagamiDistribution, 2, "uper") ***** error ... cdf (NakagamiDistribution, 2, 3) ***** shared x x = nakarnd (1, 0.5, [1, 100]); ***** error ... paramci (NakagamiDistribution.fit (x), "alpha") ***** error ... paramci (NakagamiDistribution.fit (x), "alpha", 0) ***** error ... paramci (NakagamiDistribution.fit (x), "alpha", 1) ***** error ... paramci (NakagamiDistribution.fit (x), "alpha", [0.5 2]) ***** error ... paramci (NakagamiDistribution.fit (x), "alpha", "") ***** error ... paramci (NakagamiDistribution.fit (x), "alpha", {0.05}) ***** error ... paramci (NakagamiDistribution.fit (x), "parameter", "mu", "alpha", {0.05}) ***** error ... paramci (NakagamiDistribution.fit (x), "parameter", {"mu", "omega", "param"}) ***** error ... paramci (NakagamiDistribution.fit (x), "alpha", 0.01, ... "parameter", {"mu", "omega", "param"}) ***** error ... paramci (NakagamiDistribution.fit (x), "parameter", "param") ***** error ... paramci (NakagamiDistribution.fit (x), "alpha", 0.01, "parameter", "param") ***** error ... paramci (NakagamiDistribution.fit (x), "NAME", "value") ***** error ... paramci (NakagamiDistribution.fit (x), "alpha", 0.01, "NAME", "value") ***** error ... paramci (NakagamiDistribution.fit (x), "alpha", 0.01, "parameter", "mu", ... "NAME", "value") ***** error ... plot (NakagamiDistribution, "Parent") ***** error ... plot (NakagamiDistribution, "PlotType", 12) ***** error ... plot (NakagamiDistribution, "PlotType", {"pdf", "cdf"}) ***** error ... plot (NakagamiDistribution, "PlotType", "pdfcdf") ***** error ... plot (NakagamiDistribution, "Discrete", "pdfcdf") ***** error ... plot (NakagamiDistribution, "Discrete", [1, 0]) ***** error ... plot (NakagamiDistribution, "Discrete", {true}) ***** error ... plot (NakagamiDistribution, "Parent", 12) ***** error ... plot (NakagamiDistribution, "Parent", "hax") ***** error ... proflik (NakagamiDistribution, 2) ***** error ... proflik (NakagamiDistribution.fit (x), 3) ***** error ... proflik (NakagamiDistribution.fit (x), [1, 2]) ***** error ... proflik (NakagamiDistribution.fit (x), {1}) ***** error ... proflik (NakagamiDistribution.fit (x), 1, ones (2)) ***** error ... proflik (NakagamiDistribution.fit (x), 1, "Display") ***** error ... proflik (NakagamiDistribution.fit (x), 1, "Display", 1) ***** error ... proflik (NakagamiDistribution.fit (x), 1, "Display", {1}) ***** error ... proflik (NakagamiDistribution.fit (x), 1, "Display", {"on"}) ***** error ... proflik (NakagamiDistribution.fit (x), 1, "Display", ["on"; "on"]) ***** error ... proflik (NakagamiDistribution.fit (x), 1, "Display", "onnn") ***** error ... proflik (NakagamiDistribution.fit (x), 1, "NAME", "on") ***** error ... proflik (NakagamiDistribution.fit (x), 1, {"NAME"}, "on") ***** error ... proflik (NakagamiDistribution.fit (x), 1, {[1 2 3 4]}, "Display", "on") ***** error ... truncate (NakagamiDistribution) ***** error ... truncate (NakagamiDistribution, 2) ***** error ... truncate (NakagamiDistribution, 4, 2) ***** shared pd pd = NakagamiDistribution(1, 0.5); pd(2) = NakagamiDistribution(1, 0.6); ***** error cdf (pd, 1) ***** error icdf (pd, 0.5) ***** error iqr (pd) ***** error mean (pd) ***** error median (pd) ***** error negloglik (pd) ***** error paramci (pd) ***** error pdf (pd, 1) ***** error plot (pd) ***** error proflik (pd, 2) ***** error random (pd) ***** error std (pd) ***** error ... truncate (pd, 2, 4) ***** error var (pd) 93 tests, 93 passed, 0 known failure, 0 skipped [inst/dist_obj/LoglogisticDistribution.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/dist_obj/LoglogisticDistribution.m ***** shared pd, t pd = LoglogisticDistribution; t = truncate (pd, 2, 4); ***** assert (cdf (pd, [0:5]), [0, 0.5, 0.6667, 0.75, 0.8, 0.8333], 1e-4); ***** assert (cdf (t, [0:5]), [0, 0, 0, 0.625, 1, 1], 1e-4); ***** assert (cdf (pd, [1.5, 2, 3, 4]), [0.6, 0.6667, 0.75, 0.8], 1e-4); ***** assert (cdf (t, [1.5, 2, 3, 4]), [0, 0, 0.625, 1], 1e-4); ***** assert (icdf (pd, [0:0.2:1]), [0, 0.25, 0.6667, 1.5, 4, Inf], 1e-4); ***** assert (icdf (t, [0:0.2:1]), [2, 2.2609, 2.5714, 2.9474, 3.4118, 4], 1e-4); ***** assert (icdf (pd, [-1, 0.4:0.2:1, NaN]), [NaN, 0.6667, 1.5, 4, Inf, NaN], 1e-4); ***** assert (icdf (t, [-1, 0.4:0.2:1, NaN]), [NaN, 2.5714, 2.9474, 3.4118, 4, NaN], 1e-4); ***** assert (iqr (pd), 2.6667, 1e-4); ***** assert (iqr (t), 0.9524, 1e-4); ***** assert (mean (pd), Inf); ***** assert (mean (t), 2.8312, 1e-4); ***** assert (median (pd), 1, 1e-4); ***** assert (median (t), 2.75, 1e-4); ***** assert (pdf (pd, [0:5]), [0, 0.25, 0.1111, 0.0625, 0.04, 0.0278], 1e-4); ***** assert (pdf (t, [0:5]), [0, 0, 0.8333, 0.4687, 0.3, 0], 1e-4); ***** assert (pdf (pd, [-1, 1:4, NaN]), [0, 0.25, 0.1111, 0.0625, 0.04, NaN], 1e-4); ***** assert (pdf (t, [-1, 1:4, NaN]), [0, 0, 0.8333, 0.4687, 0.3, NaN], 1e-4); ***** assert (isequal (size (random (pd, 100, 50)), [100, 50])) ***** assert (any (random (t, 1000, 1) < 2), false); ***** assert (any (random (t, 1000, 1) > 4), false); ***** assert (std (pd), Inf); ***** assert (std (t), 0.5674, 1e-4); ***** assert (var (pd), Inf); ***** assert (var (t), 0.3220, 1e-4); ***** error ... LoglogisticDistribution(Inf, 1) ***** error ... LoglogisticDistribution(i, 1) ***** error ... LoglogisticDistribution("a", 1) ***** error ... LoglogisticDistribution([1, 2], 1) ***** error ... LoglogisticDistribution(NaN, 1) ***** error ... LoglogisticDistribution(1, 0) ***** error ... LoglogisticDistribution(1, -1) ***** error ... LoglogisticDistribution(1, Inf) ***** error ... LoglogisticDistribution(1, i) ***** error ... LoglogisticDistribution(1, "a") ***** error ... LoglogisticDistribution(1, [1, 2]) ***** error ... LoglogisticDistribution(1, NaN) ***** error ... cdf (LoglogisticDistribution, 2, "uper") ***** error ... cdf (LoglogisticDistribution, 2, 3) ***** shared x x = loglrnd (1, 1, [1, 100]); ***** error ... paramci (LoglogisticDistribution.fit (x), "alpha") ***** error ... paramci (LoglogisticDistribution.fit (x), "alpha", 0) ***** error ... paramci (LoglogisticDistribution.fit (x), "alpha", 1) ***** error ... paramci (LoglogisticDistribution.fit (x), "alpha", [0.5 2]) ***** error ... paramci (LoglogisticDistribution.fit (x), "alpha", "") ***** error ... paramci (LoglogisticDistribution.fit (x), "alpha", {0.05}) ***** error ... paramci (LoglogisticDistribution.fit (x), "parameter", "mu", "alpha", {0.05}) ***** error ... paramci (LoglogisticDistribution.fit (x), "parameter", {"mu", "sigma", "pa"}) ***** error ... paramci (LoglogisticDistribution.fit (x), "alpha", 0.01, ... "parameter", {"mu", "sigma", "param"}) ***** error ... paramci (LoglogisticDistribution.fit (x), "parameter", "param") ***** error ... paramci (LoglogisticDistribution.fit (x), "alpha", 0.01, "parameter", "parm") ***** error ... paramci (LoglogisticDistribution.fit (x), "NAME", "value") ***** error ... paramci (LoglogisticDistribution.fit (x), "alpha", 0.01, "NAME", "value") ***** error ... paramci (LoglogisticDistribution.fit (x), "alpha", 0.01, ... "parameter", "mu", "NAME", "value") ***** error ... plot (LoglogisticDistribution, "Parent") ***** error ... plot (LoglogisticDistribution, "PlotType", 12) ***** error ... plot (LoglogisticDistribution, "PlotType", {"pdf", "cdf"}) ***** error ... plot (LoglogisticDistribution, "PlotType", "pdfcdf") ***** error ... plot (LoglogisticDistribution, "Discrete", "pdfcdf") ***** error ... plot (LoglogisticDistribution, "Discrete", [1, 0]) ***** error ... plot (LoglogisticDistribution, "Discrete", {true}) ***** error ... plot (LoglogisticDistribution, "Parent", 12) ***** error ... plot (LoglogisticDistribution, "Parent", "hax") ***** error ... proflik (LoglogisticDistribution, 2) ***** error ... proflik (LoglogisticDistribution.fit (x), 3) ***** error ... proflik (LoglogisticDistribution.fit (x), [1, 2]) ***** error ... proflik (LoglogisticDistribution.fit (x), {1}) ***** error ... proflik (LoglogisticDistribution.fit (x), 1, ones (2)) ***** error ... proflik (LoglogisticDistribution.fit (x), 1, "Display") ***** error ... proflik (LoglogisticDistribution.fit (x), 1, "Display", 1) ***** error ... proflik (LoglogisticDistribution.fit (x), 1, "Display", {1}) ***** error ... proflik (LoglogisticDistribution.fit (x), 1, "Display", {"on"}) ***** error ... proflik (LoglogisticDistribution.fit (x), 1, "Display", ["on"; "on"]) ***** error ... proflik (LoglogisticDistribution.fit (x), 1, "Display", "onnn") ***** error ... proflik (LoglogisticDistribution.fit (x), 1, "NAME", "on") ***** error ... proflik (LoglogisticDistribution.fit (x), 1, {"NAME"}, "on") ***** error ... proflik (LoglogisticDistribution.fit (x), 1, {[1 2 3 4]}, "Display", "on") ***** error ... truncate (LoglogisticDistribution) ***** error ... truncate (LoglogisticDistribution, 2) ***** error ... truncate (LoglogisticDistribution, 4, 2) ***** shared pd pd = LoglogisticDistribution(1, 1); pd(2) = LoglogisticDistribution(1, 3); ***** error cdf (pd, 1) ***** error icdf (pd, 0.5) ***** error iqr (pd) ***** error mean (pd) ***** error median (pd) ***** error negloglik (pd) ***** error paramci (pd) ***** error pdf (pd, 1) ***** error plot (pd) ***** error proflik (pd, 2) ***** error random (pd) ***** error std (pd) ***** error ... truncate (pd, 2, 4) ***** error var (pd) 93 tests, 93 passed, 0 known failure, 0 skipped [inst/dist_obj/WeibullDistribution.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/dist_obj/WeibullDistribution.m ***** shared pd, t pd = WeibullDistribution; t = truncate (pd, 2, 4); ***** assert (cdf (pd, [0:5]), [0, 0.6321, 0.8647, 0.9502, 0.9817, 0.9933], 1e-4); ***** assert (cdf (t, [0:5]), [0, 0, 0, 0.7311, 1, 1], 1e-4); ***** assert (cdf (pd, [1.5, 2, 3, 4, NaN]), [0.7769, 0.8647, 0.9502, 0.9817, NaN], 1e-4); ***** assert (cdf (t, [1.5, 2, 3, 4, NaN]), [0, 0, 0.7311, 1, NaN], 1e-4); ***** assert (icdf (pd, [0:0.2:1]), [0, 0.2231, 0.5108, 0.9163, 1.6094, Inf], 1e-4); ***** assert (icdf (t, [0:0.2:1]), [2, 2.1899, 2.4244, 2.7315, 3.1768, 4], 1e-4); ***** assert (icdf (pd, [-1, 0.4:0.2:1, NaN]), [NaN, 0.5108, 0.9163, 1.6094, Inf, NaN], 1e-4); ***** assert (icdf (t, [-1, 0.4:0.2:1, NaN]), [NaN, 2.4244, 2.7315, 3.1768, 4, NaN], 1e-4); ***** assert (iqr (pd), 1.0986, 1e-4); ***** assert (iqr (t), 0.8020, 1e-4); ***** assert (mean (pd), 1, 1e-14); ***** assert (mean (t), 2.6870, 1e-4); ***** assert (median (pd), 0.6931, 1e-4); ***** assert (median (t), 2.5662, 1e-4); ***** assert (pdf (pd, [0:5]), [1, 0.3679, 0.1353, 0.0498, 0.0183, 0.0067], 1e-4); ***** assert (pdf (t, [0:5]), [0, 0, 1.1565, 0.4255, 0.1565, 0], 1e-4); ***** assert (pdf (pd, [-1, 1.5, NaN]), [0, 0.2231, NaN], 1e-4); ***** assert (pdf (t, [-1, 1.5, NaN]), [0, 0, NaN], 1e-4); ***** assert (isequal (size (random (pd, 100, 50)), [100, 50])) ***** assert (any (random (t, 1000, 1) < 2), false); ***** assert (any (random (t, 1000, 1) > 4), false); ***** assert (std (pd), 1, 1e-14); ***** assert (std (t), 0.5253, 1e-4); ***** assert (var (pd), 1, 1e-14); ***** assert (var (t), 0.2759, 1e-4); ***** error ... WeibullDistribution(0, 1) ***** error ... WeibullDistribution(-1, 1) ***** error ... WeibullDistribution(Inf, 1) ***** error ... WeibullDistribution(i, 1) ***** error ... WeibullDistribution("a", 1) ***** error ... WeibullDistribution([1, 2], 1) ***** error ... WeibullDistribution(NaN, 1) ***** error ... WeibullDistribution(1, 0) ***** error ... WeibullDistribution(1, -1) ***** error ... WeibullDistribution(1, Inf) ***** error ... WeibullDistribution(1, i) ***** error ... WeibullDistribution(1, "a") ***** error ... WeibullDistribution(1, [1, 2]) ***** error ... WeibullDistribution(1, NaN) ***** error ... cdf (WeibullDistribution, 2, "uper") ***** error ... cdf (WeibullDistribution, 2, 3) ***** shared x x = wblrnd (1, 1, [1, 100]); ***** error ... paramci (WeibullDistribution.fit (x), "alpha") ***** error ... paramci (WeibullDistribution.fit (x), "alpha", 0) ***** error ... paramci (WeibullDistribution.fit (x), "alpha", 1) ***** error ... paramci (WeibullDistribution.fit (x), "alpha", [0.5 2]) ***** error ... paramci (WeibullDistribution.fit (x), "alpha", "") ***** error ... paramci (WeibullDistribution.fit (x), "alpha", {0.05}) ***** error ... paramci (WeibullDistribution.fit (x), "parameter", "k", "alpha", {0.05}) ***** error ... paramci (WeibullDistribution.fit (x), "parameter", {"lambda", "k", "param"}) ***** error ... paramci (WeibullDistribution.fit (x), "alpha", 0.01, ... "parameter", {"lambda", "k", "param"}) ***** error ... paramci (WeibullDistribution.fit (x), "parameter", "param") ***** error ... paramci (WeibullDistribution.fit (x), "alpha", 0.01, "parameter", "param") ***** error ... paramci (WeibullDistribution.fit (x), "NAME", "value") ***** error ... paramci (WeibullDistribution.fit (x), "alpha", 0.01, "NAME", "value") ***** error ... paramci (WeibullDistribution.fit (x), "alpha", 0.01, "parameter", "k", ... "NAME", "value") ***** error ... plot (WeibullDistribution, "Parent") ***** error ... plot (WeibullDistribution, "PlotType", 12) ***** error ... plot (WeibullDistribution, "PlotType", {"pdf", "cdf"}) ***** error ... plot (WeibullDistribution, "PlotType", "pdfcdf") ***** error ... plot (WeibullDistribution, "Discrete", "pdfcdf") ***** error ... plot (WeibullDistribution, "Discrete", [1, 0]) ***** error ... plot (WeibullDistribution, "Discrete", {true}) ***** error ... plot (WeibullDistribution, "Parent", 12) ***** error ... plot (WeibullDistribution, "Parent", "hax") ***** error ... proflik (WeibullDistribution, 2) ***** error ... proflik (WeibullDistribution.fit (x), 3) ***** error ... proflik (WeibullDistribution.fit (x), [1, 2]) ***** error ... proflik (WeibullDistribution.fit (x), {1}) ***** error ... proflik (WeibullDistribution.fit (x), 1, ones (2)) ***** error ... proflik (WeibullDistribution.fit (x), 1, "Display") ***** error ... proflik (WeibullDistribution.fit (x), 1, "Display", 1) ***** error ... proflik (WeibullDistribution.fit (x), 1, "Display", {1}) ***** error ... proflik (WeibullDistribution.fit (x), 1, "Display", {"on"}) ***** error ... proflik (WeibullDistribution.fit (x), 1, "Display", ["on"; "on"]) ***** error ... proflik (WeibullDistribution.fit (x), 1, "Display", "onnn") ***** error ... proflik (WeibullDistribution.fit (x), 1, "NAME", "on") ***** error ... proflik (WeibullDistribution.fit (x), 1, {"NAME"}, "on") ***** error ... proflik (WeibullDistribution.fit (x), 1, {[1 2 3 4]}, "Display", "on") ***** error ... truncate (WeibullDistribution) ***** error ... truncate (WeibullDistribution, 2) ***** error ... truncate (WeibullDistribution, 4, 2) ***** shared pd pd = WeibullDistribution(1, 1); pd(2) = WeibullDistribution(1, 3); ***** error cdf (pd, 1) ***** error icdf (pd, 0.5) ***** error iqr (pd) ***** error mean (pd) ***** error median (pd) ***** error negloglik (pd) ***** error paramci (pd) ***** error pdf (pd, 1) ***** error plot (pd) ***** error proflik (pd, 2) ***** error random (pd) ***** error std (pd) ***** error ... truncate (pd, 2, 4) ***** error var (pd) 95 tests, 95 passed, 0 known failure, 0 skipped [inst/dist_obj/NegativeBinomialDistribution.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/dist_obj/NegativeBinomialDistribution.m ***** shared pd, t pd = NegativeBinomialDistribution; t = truncate (pd, 2, 4); ***** assert (cdf (pd, [0:5]), [0.5, 0.75, 0.875, 0.9375, 0.9688, 0.9844], 1e-4); ***** assert (cdf (pd, [1.5, 2, 3, 4]), [0.75, 0.875, 0.9375, 0.9688], 1e-4); ***** assert (icdf (pd, [0:0.2:1]), [0, 0, 0, 1, 2, Inf], 1e-4); ***** assert (icdf (pd, [-1, 0.4:0.2:1, NaN]), [NaN, 0, 1, 2, Inf, NaN], 1e-4); ***** assert (iqr (pd), 1); ***** assert (mean (pd), 1); ***** assert (median (pd), 0); ***** assert (pdf (pd, [0:5]), [0.5, 0.25, 0.125, 0.0625, 0.0312, 0.0156], 1e-4); ***** assert (pdf (pd, [-1, 1:4, NaN]), [0, 0.25, 0.125, 0.0625, 0.0312, NaN], 1e-4); ***** assert (isequal (size (random (pd, 100, 50)), [100, 50])) ***** assert (std (pd), 1.4142, 1e-4); ***** assert (var (pd), 2); ***** error ... NegativeBinomialDistribution(Inf, 1) ***** error ... NegativeBinomialDistribution(i, 1) ***** error ... NegativeBinomialDistribution("a", 1) ***** error ... NegativeBinomialDistribution([1, 2], 1) ***** error ... NegativeBinomialDistribution(NaN, 1) ***** error ... NegativeBinomialDistribution(1, 0) ***** error ... NegativeBinomialDistribution(1, -1) ***** error ... NegativeBinomialDistribution(1, Inf) ***** error ... NegativeBinomialDistribution(1, i) ***** error ... NegativeBinomialDistribution(1, "a") ***** error ... NegativeBinomialDistribution(1, [1, 2]) ***** error ... NegativeBinomialDistribution(1, NaN) ***** error ... NegativeBinomialDistribution(1, 1.2) ***** error ... cdf (NegativeBinomialDistribution, 2, "uper") ***** error ... cdf (NegativeBinomialDistribution, 2, 3) ***** shared x x = nbinrnd (1, 0.5, [1, 100]); ***** error ... paramci (NegativeBinomialDistribution.fit (x), "alpha") ***** error ... paramci (NegativeBinomialDistribution.fit (x), "alpha", 0) ***** error ... paramci (NegativeBinomialDistribution.fit (x), "alpha", 1) ***** error ... paramci (NegativeBinomialDistribution.fit (x), "alpha", [0.5 2]) ***** error ... paramci (NegativeBinomialDistribution.fit (x), "alpha", "") ***** error ... paramci (NegativeBinomialDistribution.fit (x), "alpha", {0.05}) ***** error ... paramci (NegativeBinomialDistribution.fit (x), "parameter", "R", ... "alpha", {0.05}) ***** error ... paramci (NegativeBinomialDistribution.fit (x), ... "parameter", {"R", "P", "param"}) ***** error ... paramci (NegativeBinomialDistribution.fit (x), "alpha", 0.01, ... "parameter", {"R", "P", "param"}) ***** error ... paramci (NegativeBinomialDistribution.fit (x), "parameter", "param") ***** error ... paramci (NegativeBinomialDistribution.fit (x), "alpha", 0.01, ... "parameter", "param") ***** error ... paramci (NegativeBinomialDistribution.fit (x), "NAME", "value") ***** error ... paramci (NegativeBinomialDistribution.fit (x), "alpha", 0.01, ... "NAME", "value") ***** error ... paramci (NegativeBinomialDistribution.fit (x), "alpha", 0.01, ... "parameter", "R", "NAME", "value") ***** error ... plot (NegativeBinomialDistribution, "Parent") ***** error ... plot (NegativeBinomialDistribution, "PlotType", 12) ***** error ... plot (NegativeBinomialDistribution, "PlotType", {"pdf", "cdf"}) ***** error ... plot (NegativeBinomialDistribution, "PlotType", "pdfcdf") ***** error ... plot (NegativeBinomialDistribution, "Discrete", "pdfcdf") ***** error ... plot (NegativeBinomialDistribution, "Discrete", [1, 0]) ***** error ... plot (NegativeBinomialDistribution, "Discrete", {true}) ***** error ... plot (NegativeBinomialDistribution, "Parent", 12) ***** error ... plot (NegativeBinomialDistribution, "Parent", "hax") ***** error ... proflik (NegativeBinomialDistribution, 2) ***** error ... proflik (NegativeBinomialDistribution.fit (x), 3) ***** error ... proflik (NegativeBinomialDistribution.fit (x), [1, 2]) ***** error ... proflik (NegativeBinomialDistribution.fit (x), {1}) ***** error ... proflik (NegativeBinomialDistribution.fit (x), 1, ones (2)) ***** error ... proflik (NegativeBinomialDistribution.fit (x), 1, "Display") ***** error ... proflik (NegativeBinomialDistribution.fit (x), 1, "Display", 1) ***** error ... proflik (NegativeBinomialDistribution.fit (x), 1, "Display", {1}) ***** error ... proflik (NegativeBinomialDistribution.fit (x), 1, "Display", {"on"}) ***** error ... proflik (NegativeBinomialDistribution.fit (x), 1, "Display", ["on"; "on"]) ***** error ... proflik (NegativeBinomialDistribution.fit (x), 1, "Display", "onnn") ***** error ... proflik (NegativeBinomialDistribution.fit (x), 1, "NAME", "on") ***** error ... proflik (NegativeBinomialDistribution.fit (x), 1, {"NAME"}, "on") ***** error ... proflik (NegativeBinomialDistribution.fit (x), 1, {[1 2 3]}, "Display", "on") ***** error ... truncate (NegativeBinomialDistribution) ***** error ... truncate (NegativeBinomialDistribution, 2) ***** error ... truncate (NegativeBinomialDistribution, 4, 2) ***** shared pd pd = NegativeBinomialDistribution(1, 0.5); pd(2) = NegativeBinomialDistribution(1, 0.6); ***** error cdf (pd, 1) ***** error icdf (pd, 0.5) ***** error iqr (pd) ***** error mean (pd) ***** error median (pd) ***** error negloglik (pd) ***** error paramci (pd) ***** error pdf (pd, 1) ***** error plot (pd) ***** error proflik (pd, 2) ***** error random (pd) ***** error std (pd) ***** error ... truncate (pd, 2, 4) ***** error var (pd) 81 tests, 81 passed, 0 known failure, 0 skipped [inst/dist_obj/GammaDistribution.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/dist_obj/GammaDistribution.m ***** shared pd, t pd = GammaDistribution (1, 1); t = truncate (pd, 2, 4); ***** assert (cdf (pd, [0:5]), [0, 0.6321, 0.8647, 0.9502, 0.9817, 0.9933], 1e-4); ***** assert (cdf (t, [0:5]), [0, 0, 0, 0.7311, 1, 1], 1e-4); ***** assert (cdf (pd, [1.5, 2, 3, 4]), [0.7769, 0.8647, 0.9502, 0.9817], 1e-4); ***** assert (cdf (t, [1.5, 2, 3, 4]), [0, 0, 0.7311, 1], 1e-4); ***** assert (icdf (pd, [0:0.2:1]), [0, 0.2231, 0.5108, 0.9163, 1.6094, Inf], 1e-4); ***** assert (icdf (t, [0:0.2:1]), [2, 2.1899, 2.4244, 2.7315, 3.1768, 4], 1e-4); ***** assert (icdf (pd, [-1, 0.4:0.2:1, NaN]), [NaN, 0.5108, 0.9163, 1.6094, Inf, NaN], 1e-4); ***** assert (icdf (t, [-1, 0.4:0.2:1, NaN]), [NaN, 2.4244, 2.7315, 3.1768, 4, NaN], 1e-4); ***** assert (iqr (pd), 1.0986, 1e-4); ***** assert (iqr (t), 0.8020, 1e-4); ***** assert (mean (pd), 1); ***** assert (mean (t), 2.6870, 1e-4); ***** assert (median (pd), 0.6931, 1e-4); ***** assert (median (t), 2.5662, 1e-4); ***** assert (pdf (pd, [0:5]), [1, 0.3679, 0.1353, 0.0498, 0.0183, 0.0067], 1e-4); ***** assert (pdf (t, [0:5]), [0, 0, 1.1565, 0.4255, 0.1565, 0], 1e-4); ***** assert (pdf (pd, [-1, 1:4, NaN]), [0, 0.3679, 0.1353, 0.0498, 0.0183, NaN], 1e-4); ***** assert (pdf (t, [-1, 1:4, NaN]), [0, 0, 1.1565, 0.4255, 0.1565, NaN], 1e-4); ***** assert (isequal (size (random (pd, 100, 50)), [100, 50])) ***** assert (any (random (t, 1000, 1) < 2), false); ***** assert (any (random (t, 1000, 1) > 4), false); ***** assert (std (pd), 1); ***** assert (std (t), 0.5253, 1e-4); ***** assert (var (pd), 1); ***** assert (var (t), 0.2759, 1e-4); ***** error ... GammaDistribution(0, 1) ***** error ... GammaDistribution(Inf, 1) ***** error ... GammaDistribution(i, 1) ***** error ... GammaDistribution("a", 1) ***** error ... GammaDistribution([1, 2], 1) ***** error ... GammaDistribution(NaN, 1) ***** error ... GammaDistribution(1, 0) ***** error ... GammaDistribution(1, -1) ***** error ... GammaDistribution(1, Inf) ***** error ... GammaDistribution(1, i) ***** error ... GammaDistribution(1, "a") ***** error ... GammaDistribution(1, [1, 2]) ***** error ... GammaDistribution(1, NaN) ***** error ... cdf (GammaDistribution, 2, "uper") ***** error ... cdf (GammaDistribution, 2, 3) ***** shared x x = gamrnd (1, 1, [100, 1]); ***** error ... paramci (GammaDistribution.fit (x), "alpha") ***** error ... paramci (GammaDistribution.fit (x), "alpha", 0) ***** error ... paramci (GammaDistribution.fit (x), "alpha", 1) ***** error ... paramci (GammaDistribution.fit (x), "alpha", [0.5 2]) ***** error ... paramci (GammaDistribution.fit (x), "alpha", "") ***** error ... paramci (GammaDistribution.fit (x), "alpha", {0.05}) ***** error ... paramci (GammaDistribution.fit (x), "parameter", "a", "alpha", {0.05}) ***** error ... paramci (GammaDistribution.fit (x), "parameter", {"a", "b", "param"}) ***** error ... paramci (GammaDistribution.fit (x), "alpha", 0.01, ... "parameter", {"a", "b", "param"}) ***** error ... paramci (GammaDistribution.fit (x), "parameter", "param") ***** error ... paramci (GammaDistribution.fit (x), "alpha", 0.01, "parameter", "param") ***** error ... paramci (GammaDistribution.fit (x), "NAME", "value") ***** error ... paramci (GammaDistribution.fit (x), "alpha", 0.01, "NAME", "value") ***** error ... paramci (GammaDistribution.fit (x), "alpha", 0.01, "parameter", "a", ... "NAME", "value") ***** error ... plot (GammaDistribution, "Parent") ***** error ... plot (GammaDistribution, "PlotType", 12) ***** error ... plot (GammaDistribution, "PlotType", {"pdf", "cdf"}) ***** error ... plot (GammaDistribution, "PlotType", "pdfcdf") ***** error ... plot (GammaDistribution, "Discrete", "pdfcdf") ***** error ... plot (GammaDistribution, "Discrete", [1, 0]) ***** error ... plot (GammaDistribution, "Discrete", {true}) ***** error ... plot (GammaDistribution, "Parent", 12) ***** error ... plot (GammaDistribution, "Parent", "hax") ***** error ... proflik (GammaDistribution, 2) ***** error ... proflik (GammaDistribution.fit (x), 3) ***** error ... proflik (GammaDistribution.fit (x), [1, 2]) ***** error ... proflik (GammaDistribution.fit (x), {1}) ***** error ... proflik (GammaDistribution.fit (x), 1, ones (2)) ***** error ... proflik (GammaDistribution.fit (x), 1, "Display") ***** error ... proflik (GammaDistribution.fit (x), 1, "Display", 1) ***** error ... proflik (GammaDistribution.fit (x), 1, "Display", {1}) ***** error ... proflik (GammaDistribution.fit (x), 1, "Display", {"on"}) ***** error ... proflik (GammaDistribution.fit (x), 1, "Display", ["on"; "on"]) ***** error ... proflik (GammaDistribution.fit (x), 1, "Display", "onnn") ***** error ... proflik (GammaDistribution.fit (x), 1, "NAME", "on") ***** error ... proflik (GammaDistribution.fit (x), 1, {"NAME"}, "on") ***** error ... proflik (GammaDistribution.fit (x), 1, {[1 2 3 4]}, "Display", "on") ***** error ... truncate (GammaDistribution) ***** error ... truncate (GammaDistribution, 2) ***** error ... truncate (GammaDistribution, 4, 2) ***** shared pd pd = GammaDistribution(1, 1); pd(2) = GammaDistribution(1, 3); ***** error cdf (pd, 1) ***** error icdf (pd, 0.5) ***** error iqr (pd) ***** error mean (pd) ***** error median (pd) ***** error negloglik (pd) ***** error paramci (pd) ***** error pdf (pd, 1) ***** error plot (pd) ***** error proflik (pd, 2) ***** error random (pd) ***** error std (pd) ***** error ... truncate (pd, 2, 4) ***** error var (pd) 94 tests, 94 passed, 0 known failure, 0 skipped [inst/dist_obj/UniformDistribution.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/dist_obj/UniformDistribution.m ***** shared pd, t pd = UniformDistribution (0, 5); t = truncate (pd, 2, 4); ***** assert (cdf (pd, [0:5]), [0, 0.2, 0.4, 0.6, 0.8, 1], 1e-4); ***** assert (cdf (t, [0:5]), [0, 0, 0, 0.5, 1, 1], 1e-4); ***** assert (cdf (pd, [1.5, 2, 3, 4, NaN]), [0.3, 0.4, 0.6, 0.8, NaN], 1e-4); ***** assert (cdf (t, [1.5, 2, 3, 4, NaN]), [0, 0, 0.5, 1, NaN], 1e-4); ***** assert (icdf (pd, [0:0.2:1]), [0, 1, 2, 3, 4, 5], 1e-4); ***** assert (icdf (t, [0:0.2:1]), [2, 2.4, 2.8, 3.2, 3.6, 4], 1e-4); ***** assert (icdf (pd, [-1, 0.4:0.2:1, NaN]), [NaN, 2, 3, 4, 5, NaN], 1e-4); ***** assert (icdf (t, [-1, 0.4:0.2:1, NaN]), [NaN, 2.8, 3.2, 3.6, 4, NaN], 1e-4); ***** assert (iqr (pd), 2.5, 1e-14); ***** assert (iqr (t), 1, 1e-14); ***** assert (mean (pd), 2.5, 1e-14); ***** assert (mean (t), 3, 1e-14); ***** assert (median (pd), 2.5, 1e-14); ***** assert (median (t), 3, 1e-14); ***** assert (pdf (pd, [0:5]), [0.2, 0.2, 0.2, 0.2, 0.2, 0.2], 1e-4); ***** assert (pdf (t, [0:5]), [0, 0, 0.5, 0.5, 0.5, 0], 1e-4); ***** assert (pdf (pd, [-1, 1.5, NaN]), [0, 0.2, NaN], 1e-4); ***** assert (pdf (t, [-1, 1.5, NaN]), [0, 0, NaN], 1e-4); ***** assert (isequal (size (random (pd, 100, 50)), [100, 50])) ***** assert (any (random (t, 1000, 1) < 2), false); ***** assert (any (random (t, 1000, 1) > 4), false); ***** assert (std (pd), 1.4434, 1e-4); ***** assert (std (t), 0.5774, 1e-4); ***** assert (var (pd), 2.0833, 1e-4); ***** assert (var (t), 0.3333, 1e-4); ***** error ... UniformDistribution (i, 1) ***** error ... UniformDistribution (Inf, 1) ***** error ... UniformDistribution ([1, 2], 1) ***** error ... UniformDistribution ("a", 1) ***** error ... UniformDistribution (NaN, 1) ***** error ... UniformDistribution (1, i) ***** error ... UniformDistribution (1, Inf) ***** error ... UniformDistribution (1, [1, 2]) ***** error ... UniformDistribution (1, "a") ***** error ... UniformDistribution (1, NaN) ***** error ... UniformDistribution (2, 1) ***** error ... cdf (UniformDistribution, 2, "uper") ***** error ... cdf (UniformDistribution, 2, 3) ***** error ... plot (UniformDistribution, "Parent") ***** error ... plot (UniformDistribution, "PlotType", 12) ***** error ... plot (UniformDistribution, "PlotType", {"pdf", "cdf"}) ***** error ... plot (UniformDistribution, "PlotType", "pdfcdf") ***** error ... plot (UniformDistribution, "Discrete", "pdfcdf") ***** error ... plot (UniformDistribution, "Discrete", [1, 0]) ***** error ... plot (UniformDistribution, "Discrete", {true}) ***** error ... plot (UniformDistribution, "Parent", 12) ***** error ... plot (UniformDistribution, "Parent", "hax") ***** error ... truncate (UniformDistribution) ***** error ... truncate (UniformDistribution, 2) ***** error ... truncate (UniformDistribution, 4, 2) ***** shared pd pd = UniformDistribution (0, 1); pd(2) = UniformDistribution (0, 2); ***** error cdf (pd, 1) ***** error icdf (pd, 0.5) ***** error iqr (pd) ***** error mean (pd) ***** error median (pd) ***** error pdf (pd, 1) ***** error plot (pd) ***** error random (pd) ***** error std (pd) ***** error ... truncate (pd, 2, 4) ***** error var (pd) 61 tests, 61 passed, 0 known failure, 0 skipped [inst/dist_obj/TriangularDistribution.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/dist_obj/TriangularDistribution.m ***** shared pd, t pd = TriangularDistribution (0, 3, 5); t = truncate (pd, 2, 4); ***** assert (cdf (pd, [0:5]), [0, 0.0667, 0.2667, 0.6000, 0.9000, 1], 1e-4); ***** assert (cdf (t, [0:5]), [0, 0, 0, 0.5263, 1, 1], 1e-4); ***** assert (cdf (pd, [1.5, 2, 3, 4, NaN]), [0.1500, 0.2667, 0.6, 0.9, NaN], 1e-4); ***** assert (cdf (t, [1.5, 2, 3, 4, NaN]), [0, 0, 0.5263, 1, NaN], 1e-4); ***** assert (icdf (pd, [0:0.2:1]), [0, 1.7321, 2.4495, 3, 3.5858, 5], 1e-4); ***** assert (icdf (t, [0:0.2:1]), [2, 2.4290, 2.7928, 3.1203, 3.4945, 4], 1e-4); ***** assert (icdf (pd, [-1, 0.4:0.2:1, NaN]), [NaN, 2.4495, 3, 3.5858, 5, NaN], 1e-4); ***** assert (icdf (t, [-1, 0.4:0.2:1, NaN]), [NaN, 2.7928, 3.1203, 3.4945, 4, NaN], 1e-4); ***** assert (iqr (pd), 1.4824, 1e-4); ***** assert (iqr (t), 0.8678, 1e-4); ***** assert (mean (pd), 2.6667, 1e-4); ***** assert (mean (t), 2.9649, 1e-4); ***** assert (median (pd), 2.7386, 1e-4); ***** assert (median (t), 2.9580, 1e-4); ***** assert (pdf (pd, [0:5]), [0, 0.1333, 0.2667, 0.4, 0.2, 0], 1e-4); ***** assert (pdf (t, [0:5]), [0, 0, 0.4211, 0.6316, 0.3158, 0], 1e-4); ***** assert (pdf (pd, [-1, 1.5, NaN]), [0, 0.2, NaN], 1e-4); ***** assert (pdf (t, [-1, 1.5, NaN]), [0, 0, NaN], 1e-4); ***** assert (isequal (size (random (pd, 100, 50)), [100, 50])) ***** assert (any (random (t, 1000, 1) < 2), false); ***** assert (any (random (t, 1000, 1) > 4), false); ***** assert (std (pd), 1.0274, 1e-4); ***** assert (std (t), 0.5369, 1e-4); ***** assert (var (pd), 1.0556, 1e-4); ***** assert (var (t), 0.2882, 1e-4); ***** error ... TriangularDistribution (i, 1, 2) ***** error ... TriangularDistribution (Inf, 1, 2) ***** error ... TriangularDistribution ([1, 2], 1, 2) ***** error ... TriangularDistribution ("a", 1, 2) ***** error ... TriangularDistribution (NaN, 1, 2) ***** error ... TriangularDistribution (1, i, 2) ***** error ... TriangularDistribution (1, Inf, 2) ***** error ... TriangularDistribution (1, [1, 2], 2) ***** error ... TriangularDistribution (1, "a", 2) ***** error ... TriangularDistribution (1, NaN, 2) ***** error ... TriangularDistribution (1, 2, i) ***** error ... TriangularDistribution (1, 2, Inf) ***** error ... TriangularDistribution (1, 2, [1, 2]) ***** error ... TriangularDistribution (1, 2, "a") ***** error ... TriangularDistribution (1, 2, NaN) ***** error ... TriangularDistribution (1, 1, 1) ***** error ... TriangularDistribution (1, 0.5, 2) ***** error ... cdf (TriangularDistribution, 2, "uper") ***** error ... cdf (TriangularDistribution, 2, 3) ***** error ... plot (TriangularDistribution, "Parent") ***** error ... plot (TriangularDistribution, "PlotType", 12) ***** error ... plot (TriangularDistribution, "PlotType", {"pdf", "cdf"}) ***** error ... plot (TriangularDistribution, "PlotType", "pdfcdf") ***** error ... plot (TriangularDistribution, "Discrete", "pdfcdf") ***** error ... plot (TriangularDistribution, "Discrete", [1, 0]) ***** error ... plot (TriangularDistribution, "Discrete", {true}) ***** error ... plot (TriangularDistribution, "Parent", 12) ***** error ... plot (TriangularDistribution, "Parent", "hax") ***** error ... truncate (TriangularDistribution) ***** error ... truncate (TriangularDistribution, 2) ***** error ... truncate (TriangularDistribution, 4, 2) ***** shared pd pd = TriangularDistribution (0, 1, 2); pd(2) = TriangularDistribution (0, 1, 2); ***** error cdf (pd, 1) ***** error icdf (pd, 0.5) ***** error iqr (pd) ***** error mean (pd) ***** error median (pd) ***** error pdf (pd, 1) ***** error plot (pd) ***** error random (pd) ***** error std (pd) ***** error ... truncate (pd, 2, 4) ***** error var (pd) 67 tests, 67 passed, 0 known failure, 0 skipped [inst/dist_obj/InverseGaussianDistribution.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/dist_obj/InverseGaussianDistribution.m ***** shared pd, t pd = InverseGaussianDistribution (1, 1); t = truncate (pd, 2, 4); ***** assert (cdf (pd, [0:5]), [0, 0.6681, 0.8855, 0.9532, 0.9791, 0.9901], 1e-4); ***** assert (cdf (t, [0:5]), [0, 0, 0, 0.7234, 1, 1], 1e-4); ***** assert (cdf (pd, [1.5, 2, 3, 4]), [0.8108, 0.8855, 0.9532, 0.9791], 1e-4); ***** assert (cdf (t, [1.5, 2, 3, 4]), [0, 0, 0.7234, 1], 1e-4); ***** assert (icdf (pd, [0:0.2:1]), [0, 0.3320, 0.5411, 0.8483, 1.4479, Inf], 1e-4); ***** assert (icdf (t, [0:0.2:1]), [2, 2.1889, 2.4264, 2.7417, 3.1993, 4], 1e-4); ***** assert (icdf (pd, [-1, 0.4:0.2:1, NaN]), [NaN, 0.5411, 0.8483, 1.4479, Inf, NaN], 1e-4); ***** assert (icdf (t, [-1, 0.4:0.2:1, NaN]), [NaN, 2.4264, 2.7417, 3.1993, 4, NaN], 1e-4); ***** assert (iqr (pd), 0.8643, 1e-4); ***** assert (iqr (t), 0.8222, 1e-4); ***** assert (mean (pd), 1); ***** assert (mean (t), 2.6953, 1e-4); ***** assert (median (pd), 0.6758, 1e-4); ***** assert (median (t), 2.5716, 1e-4); ***** assert (pdf (pd, [0:5]), [0, 0.3989, 0.1098, 0.0394, 0.0162, 0.0072], 1e-4); ***** assert (pdf (t, [0:5]), [0, 0, 1.1736, 0.4211, 0.1730, 0], 1e-4); ***** assert (pdf (pd, [-1, 1:4, NaN]), [0, 0.3989, 0.1098, 0.0394, 0.0162, NaN], 1e-4); ***** assert (pdf (t, [-1, 1:4, NaN]), [0, 0, 1.1736, 0.4211, 0.1730, NaN], 1e-4); ***** assert (isequal (size (random (pd, 100, 50)), [100, 50])) ***** assert (any (random (t, 1000, 1) < 2), false); ***** assert (any (random (t, 1000, 1) > 4), false); ***** assert (std (pd), 1); ***** assert (std (t), 0.5332, 1e-4); ***** assert (var (pd), 1); ***** assert (var (t), 0.2843, 1e-4); ***** error ... InverseGaussianDistribution(0, 1) ***** error ... InverseGaussianDistribution(Inf, 1) ***** error ... InverseGaussianDistribution(i, 1) ***** error ... InverseGaussianDistribution("a", 1) ***** error ... InverseGaussianDistribution([1, 2], 1) ***** error ... InverseGaussianDistribution(NaN, 1) ***** error ... InverseGaussianDistribution(1, 0) ***** error ... InverseGaussianDistribution(1, -1) ***** error ... InverseGaussianDistribution(1, Inf) ***** error ... InverseGaussianDistribution(1, i) ***** error ... InverseGaussianDistribution(1, "a") ***** error ... InverseGaussianDistribution(1, [1, 2]) ***** error ... InverseGaussianDistribution(1, NaN) ***** error ... cdf (InverseGaussianDistribution, 2, "uper") ***** error ... cdf (InverseGaussianDistribution, 2, 3) ***** shared x x = invgrnd (1, 1, [1, 100]); ***** error ... paramci (InverseGaussianDistribution.fit (x), "alpha") ***** error ... paramci (InverseGaussianDistribution.fit (x), "alpha", 0) ***** error ... paramci (InverseGaussianDistribution.fit (x), "alpha", 1) ***** error ... paramci (InverseGaussianDistribution.fit (x), "alpha", [0.5 2]) ***** error ... paramci (InverseGaussianDistribution.fit (x), "alpha", "") ***** error ... paramci (InverseGaussianDistribution.fit (x), "alpha", {0.05}) ***** error ... paramci (InverseGaussianDistribution.fit (x), "parameter", "mu", ... "alpha", {0.05}) ***** error ... paramci (InverseGaussianDistribution.fit (x), ... "parameter", {"mu", "lambda", "param"}) ***** error ... paramci (InverseGaussianDistribution.fit (x), "alpha", 0.01, ... "parameter", {"mu", "lambda", "param"}) ***** error ... paramci (InverseGaussianDistribution.fit (x), "parameter", "param") ***** error ... paramci (InverseGaussianDistribution.fit (x), "alpha", 0.01, ... "parameter", "param") ***** error ... paramci (InverseGaussianDistribution.fit (x), "NAME", "value") ***** error ... paramci (InverseGaussianDistribution.fit (x), "alpha", 0.01, "NAME", "value") ***** error ... paramci (InverseGaussianDistribution.fit (x), "alpha", 0.01, ... "parameter", "mu", "NAME", "value") ***** error ... plot (InverseGaussianDistribution, "Parent") ***** error ... plot (InverseGaussianDistribution, "PlotType", 12) ***** error ... plot (InverseGaussianDistribution, "PlotType", {"pdf", "cdf"}) ***** error ... plot (InverseGaussianDistribution, "PlotType", "pdfcdf") ***** error ... plot (InverseGaussianDistribution, "Discrete", "pdfcdf") ***** error ... plot (InverseGaussianDistribution, "Discrete", [1, 0]) ***** error ... plot (InverseGaussianDistribution, "Discrete", {true}) ***** error ... plot (InverseGaussianDistribution, "Parent", 12) ***** error ... plot (InverseGaussianDistribution, "Parent", "hax") ***** error ... proflik (InverseGaussianDistribution, 2) ***** error ... proflik (InverseGaussianDistribution.fit (x), 3) ***** error ... proflik (InverseGaussianDistribution.fit (x), [1, 2]) ***** error ... proflik (InverseGaussianDistribution.fit (x), {1}) ***** error ... proflik (InverseGaussianDistribution.fit (x), 1, ones (2)) ***** error ... proflik (InverseGaussianDistribution.fit (x), 1, "Display") ***** error ... proflik (InverseGaussianDistribution.fit (x), 1, "Display", 1) ***** error ... proflik (InverseGaussianDistribution.fit (x), 1, "Display", {1}) ***** error ... proflik (InverseGaussianDistribution.fit (x), 1, "Display", {"on"}) ***** error ... proflik (InverseGaussianDistribution.fit (x), 1, "Display", ["on"; "on"]) ***** error ... proflik (InverseGaussianDistribution.fit (x), 1, "Display", "onnn") ***** error ... proflik (InverseGaussianDistribution.fit (x), 1, "NAME", "on") ***** error ... proflik (InverseGaussianDistribution.fit (x), 1, {"NAME"}, "on") ***** error ... proflik (InverseGaussianDistribution.fit (x), 1, {[1 2 3]}, "Display", "on") ***** error ... truncate (InverseGaussianDistribution) ***** error ... truncate (InverseGaussianDistribution, 2) ***** error ... truncate (InverseGaussianDistribution, 4, 2) ***** shared pd pd = InverseGaussianDistribution(1, 1); pd(2) = InverseGaussianDistribution(1, 3); ***** error cdf (pd, 1) ***** error icdf (pd, 0.5) ***** error iqr (pd) ***** error mean (pd) ***** error median (pd) ***** error negloglik (pd) ***** error paramci (pd) ***** error pdf (pd, 1) ***** error plot (pd) ***** error proflik (pd, 2) ***** error random (pd) ***** error std (pd) ***** error ... truncate (pd, 2, 4) ***** error var (pd) 94 tests, 94 passed, 0 known failure, 0 skipped [inst/dist_obj/PoissonDistribution.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/dist_obj/PoissonDistribution.m ***** shared pd, t pd = PoissonDistribution; t = truncate (pd, 2, 4); ***** assert (cdf (pd, [0:5]), [0.3679, 0.7358, 0.9197, 0.9810, 0.9963, 0.9994], 1e-4); ***** assert (cdf (pd, [1.5, 2, 3, 4]), [0.7358, 0.9197, 0.9810, 0.9963], 1e-4); ***** assert (icdf (pd, [0:0.2:1]), [0, 0, 1, 1, 2, Inf], 1e-4); ***** assert (icdf (pd, [-1, 0.4:0.2:1, NaN]), [NaN, 1, 1, 2, Inf, NaN], 1e-4); ***** assert (iqr (pd), 2); ***** assert (mean (pd), 1); ***** assert (median (pd), 1); ***** assert (pdf (pd, [0:5]), [0.3679, 0.3679, 0.1839, 0.0613, 0.0153, 0.0031], 1e-4); ***** assert (pdf (pd, [-1, 1:4, NaN]), [0, 0.3679, 0.1839, 0.0613, 0.0153, NaN], 1e-4); ***** assert (isequal (size (random (pd, 100, 50)), [100, 50])) ***** assert (any (random (t, 1000, 1) < 2), false); ***** assert (any (random (t, 1000, 1) > 4), false); ***** assert (std (pd), 1); ***** assert (var (pd), 1); ***** error ... PoissonDistribution(0) ***** error ... PoissonDistribution(-1) ***** error ... PoissonDistribution(Inf) ***** error ... PoissonDistribution(i) ***** error ... PoissonDistribution("a") ***** error ... PoissonDistribution([1, 2]) ***** error ... PoissonDistribution(NaN) ***** error ... cdf (PoissonDistribution, 2, "uper") ***** error ... cdf (PoissonDistribution, 2, 3) ***** shared x x = poissrnd (1, [1, 100]); ***** error ... paramci (PoissonDistribution.fit (x), "alpha") ***** error ... paramci (PoissonDistribution.fit (x), "alpha", 0) ***** error ... paramci (PoissonDistribution.fit (x), "alpha", 1) ***** error ... paramci (PoissonDistribution.fit (x), "alpha", [0.5 2]) ***** error ... paramci (PoissonDistribution.fit (x), "alpha", "") ***** error ... paramci (PoissonDistribution.fit (x), "alpha", {0.05}) ***** error ... paramci (PoissonDistribution.fit (x), "parameter", "lambda", "alpha", {0.05}) ***** error ... paramci (PoissonDistribution.fit (x), "parameter", {"lambda", "param"}) ***** error ... paramci (PoissonDistribution.fit (x), "alpha", 0.01, ... "parameter", {"lambda", "param"}) ***** error ... paramci (PoissonDistribution.fit (x), "parameter", "param") ***** error ... paramci (PoissonDistribution.fit (x), "alpha", 0.01, "parameter", "param") ***** error ... paramci (PoissonDistribution.fit (x), "NAME", "value") ***** error ... paramci (PoissonDistribution.fit (x), "alpha", 0.01, "NAME", "value") ***** error ... paramci (PoissonDistribution.fit (x), "alpha", 0.01, ... "parameter", "lambda", "NAME", "value") ***** error ... plot (PoissonDistribution, "Parent") ***** error ... plot (PoissonDistribution, "PlotType", 12) ***** error ... plot (PoissonDistribution, "PlotType", {"pdf", "cdf"}) ***** error ... plot (PoissonDistribution, "PlotType", "pdfcdf") ***** error ... plot (PoissonDistribution, "Discrete", "pdfcdf") ***** error ... plot (PoissonDistribution, "Discrete", [1, 0]) ***** error ... plot (PoissonDistribution, "Discrete", {true}) ***** error ... plot (PoissonDistribution, "Parent", 12) ***** error ... plot (PoissonDistribution, "Parent", "hax") ***** error ... proflik (PoissonDistribution, 2) ***** error ... proflik (PoissonDistribution.fit (x), 3) ***** error ... proflik (PoissonDistribution.fit (x), [1, 2]) ***** error ... proflik (PoissonDistribution.fit (x), {1}) ***** error ... proflik (PoissonDistribution.fit (x), 1, ones (2)) ***** error ... proflik (PoissonDistribution.fit (x), 1, "Display") ***** error ... proflik (PoissonDistribution.fit (x), 1, "Display", 1) ***** error ... proflik (PoissonDistribution.fit (x), 1, "Display", {1}) ***** error ... proflik (PoissonDistribution.fit (x), 1, "Display", {"on"}) ***** error ... proflik (PoissonDistribution.fit (x), 1, "Display", ["on"; "on"]) ***** error ... proflik (PoissonDistribution.fit (x), 1, "Display", "onnn") ***** error ... proflik (PoissonDistribution.fit (x), 1, "NAME", "on") ***** error ... proflik (PoissonDistribution.fit (x), 1, {"NAME"}, "on") ***** error ... proflik (PoissonDistribution.fit (x), 1, {[1 2 3 4]}, "Display", "on") ***** error ... truncate (PoissonDistribution) ***** error ... truncate (PoissonDistribution, 2) ***** error ... truncate (PoissonDistribution, 4, 2) ***** shared pd pd = PoissonDistribution(1); pd(2) = PoissonDistribution(3); ***** error cdf (pd, 1) ***** error icdf (pd, 0.5) ***** error iqr (pd) ***** error mean (pd) ***** error median (pd) ***** error negloglik (pd) ***** error paramci (pd) ***** error pdf (pd, 1) ***** error plot (pd) ***** error proflik (pd, 2) ***** error random (pd) ***** error std (pd) ***** error ... truncate (pd, 2, 4) ***** error var (pd) 77 tests, 77 passed, 0 known failure, 0 skipped [inst/dist_obj/NormalDistribution.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/dist_obj/NormalDistribution.m ***** shared pd, t pd = NormalDistribution; t = truncate (pd, -2, 2); ***** assert (cdf (pd, [0:5]), [0.5, 0.8413, 0.9772, 0.9987, 1, 1], 1e-4); ***** assert (cdf (t, [0:5]), [0.5, 0.8576, 1, 1, 1, 1], 1e-4); ***** assert (cdf (pd, [1.5, 2, 3, 4]), [0.9332, 0.9772, 0.9987, 1], 1e-4); ***** assert (cdf (t, [1.5, 2, 3, 4]), [0.9538, 1, 1, 1], 1e-4); ***** assert (icdf (pd, [0:0.2:1]), [-Inf, -0.8416, -0.2533, 0.2533, 0.8416, Inf], 1e-4); ***** assert (icdf (t, [0:0.2:1]), [-2, -0.7938, -0.2416, 0.2416, 0.7938, 2], 1e-4); ***** assert (icdf (pd, [-1, 0.4:0.2:1, NaN]), [NaN, -0.2533, 0.2533, 0.8416, Inf, NaN], 1e-4); ***** assert (icdf (t, [-1, 0.4:0.2:1, NaN]), [NaN, -0.2416, 0.2416, 0.7938, 2, NaN], 1e-4); ***** assert (iqr (pd), 1.3490, 1e-4); ***** assert (iqr (t), 1.2782, 1e-4); ***** assert (mean (pd), 0); ***** assert (mean (t), 0, eps); ***** assert (median (pd), 0); ***** assert (median (t), 0); ***** assert (pdf (pd, [0:5]), [0.3989, 0.2420, 0.0540, 0.0044, 0.0001, 0], 1e-4); ***** assert (pdf (t, [0:5]), [0.4180, 0.2535, 0.0566, 0, 0, 0], 1e-4); ***** assert (pdf (pd, [-1, 1:4, NaN]), [0.2420, 0.2420, 0.0540, 0.0044, 0.0001, NaN], 1e-4); ***** assert (pdf (t, [-1, 1:4, NaN]), [0.2535, 0.2535, 0.0566, 0, 0, NaN], 1e-4); ***** assert (isequal (size (random (pd, 100, 50)), [100, 50])) ***** assert (any (random (t, 1000, 1) < -2), false); ***** assert (any (random (t, 1000, 1) > 2), false); ***** assert (std (pd), 1); ***** assert (std (t), 0.8796, 1e-4); ***** assert (var (pd), 1); ***** assert (var (t), 0.7737, 1e-4); ***** error ... NormalDistribution(Inf, 1) ***** error ... NormalDistribution(i, 1) ***** error ... NormalDistribution("a", 1) ***** error ... NormalDistribution([1, 2], 1) ***** error ... NormalDistribution(NaN, 1) ***** error ... NormalDistribution(1, 0) ***** error ... NormalDistribution(1, -1) ***** error ... NormalDistribution(1, Inf) ***** error ... NormalDistribution(1, i) ***** error ... NormalDistribution(1, "a") ***** error ... NormalDistribution(1, [1, 2]) ***** error ... NormalDistribution(1, NaN) ***** error ... cdf (NormalDistribution, 2, "uper") ***** error ... cdf (NormalDistribution, 2, 3) ***** shared x x = normrnd (1, 1, [1, 100]); ***** error ... paramci (NormalDistribution.fit (x), "alpha") ***** error ... paramci (NormalDistribution.fit (x), "alpha", 0) ***** error ... paramci (NormalDistribution.fit (x), "alpha", 1) ***** error ... paramci (NormalDistribution.fit (x), "alpha", [0.5 2]) ***** error ... paramci (NormalDistribution.fit (x), "alpha", "") ***** error ... paramci (NormalDistribution.fit (x), "alpha", {0.05}) ***** error ... paramci (NormalDistribution.fit (x), "parameter", "mu", "alpha", {0.05}) ***** error ... paramci (NormalDistribution.fit (x), "parameter", {"mu", "sigma", "param"}) ***** error ... paramci (NormalDistribution.fit (x), "alpha", 0.01, ... "parameter", {"mu", "sigma", "param"}) ***** error ... paramci (NormalDistribution.fit (x), "parameter", "param") ***** error ... paramci (NormalDistribution.fit (x), "alpha", 0.01, "parameter", "param") ***** error ... paramci (NormalDistribution.fit (x), "NAME", "value") ***** error ... paramci (NormalDistribution.fit (x), "alpha", 0.01, "NAME", "value") ***** error ... paramci (NormalDistribution.fit (x), "alpha", 0.01, "parameter", "mu", ... "NAME", "value") ***** error ... plot (NormalDistribution, "Parent") ***** error ... plot (NormalDistribution, "PlotType", 12) ***** error ... plot (NormalDistribution, "PlotType", {"pdf", "cdf"}) ***** error ... plot (NormalDistribution, "PlotType", "pdfcdf") ***** error ... plot (NormalDistribution, "Discrete", "pdfcdf") ***** error ... plot (NormalDistribution, "Discrete", [1, 0]) ***** error ... plot (NormalDistribution, "Discrete", {true}) ***** error ... plot (NormalDistribution, "Parent", 12) ***** error ... plot (NormalDistribution, "Parent", "hax") ***** error ... proflik (NormalDistribution, 2) ***** error ... proflik (NormalDistribution.fit (x), 3) ***** error ... proflik (NormalDistribution.fit (x), [1, 2]) ***** error ... proflik (NormalDistribution.fit (x), {1}) ***** error ... proflik (NormalDistribution.fit (x), 1, ones (2)) ***** error ... proflik (NormalDistribution.fit (x), 1, "Display") ***** error ... proflik (NormalDistribution.fit (x), 1, "Display", 1) ***** error ... proflik (NormalDistribution.fit (x), 1, "Display", {1}) ***** error ... proflik (NormalDistribution.fit (x), 1, "Display", {"on"}) ***** error ... proflik (NormalDistribution.fit (x), 1, "Display", ["on"; "on"]) ***** error ... proflik (NormalDistribution.fit (x), 1, "Display", "onnn") ***** error ... proflik (NormalDistribution.fit (x), 1, "NAME", "on") ***** error ... proflik (NormalDistribution.fit (x), 1, {"NAME"}, "on") ***** error ... proflik (NormalDistribution.fit (x), 1, {[1 2 3 4]}, "Display", "on") ***** error ... truncate (NormalDistribution) ***** error ... truncate (NormalDistribution, 2) ***** error ... truncate (NormalDistribution, 4, 2) ***** shared pd pd = NormalDistribution(1, 1); pd(2) = NormalDistribution(1, 3); ***** error cdf (pd, 1) ***** error icdf (pd, 0.5) ***** error iqr (pd) ***** error mean (pd) ***** error median (pd) ***** error negloglik (pd) ***** error paramci (pd) ***** error pdf (pd, 1) ***** error plot (pd) ***** error proflik (pd, 2) ***** error random (pd) ***** error std (pd) ***** error ... truncate (pd, 2, 4) ***** error var (pd) 93 tests, 93 passed, 0 known failure, 0 skipped [inst/dist_obj/tLocationScaleDistribution.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/dist_obj/tLocationScaleDistribution.m ***** shared pd, t pd = tLocationScaleDistribution; t = truncate (pd, 2, 4); ***** assert (cdf (pd, [0:5]), [0.5, 0.8184, 0.9490, 0.9850, 0.9948, 0.9979], 1e-4); ***** assert (cdf (t, [0:5]), [0, 0, 0, 0.7841, 1, 1], 1e-4); ***** assert (cdf (pd, [1.5, 2, 3, 4, NaN]), [0.9030, 0.9490, 0.9850, 0.9948, NaN], 1e-4); ***** assert (cdf (t, [1.5, 2, 3, 4, NaN]), [0, 0, 0.7841, 1, NaN], 1e-4); ***** assert (icdf (pd, [0:0.2:1]), [-Inf, -0.9195, -0.2672, 0.2672, 0.9195, Inf], 1e-4); ***** assert (icdf (t, [0:0.2:1]), [2, 2.1559, 2.3533, 2.6223, 3.0432, 4], 1e-4); ***** assert (icdf (pd, [-1, 0.4:0.2:1, NaN]), [NaN, -0.2672, 0.2672, 0.9195, Inf, NaN], 1e-4); ***** assert (icdf (t, [-1, 0.4:0.2:1, NaN]), [NaN, 2.3533, 2.6223, 3.0432, 4, NaN], 1e-4); ***** assert (iqr (pd), 1.4534, 1e-4); ***** assert (iqr (t), 0.7139, 1e-4); ***** assert (mean (pd), 0, eps); ***** assert (mean (t), 2.6099, 1e-4); ***** assert (median (pd), 0, eps); ***** assert (median (t), 2.4758, 1e-4); ***** assert (pdf (pd, [0:5]), [0.3796, 0.2197, 0.0651, 0.0173, 0.0051, 0.0018], 1e-4); ***** assert (pdf (t, [0:5]), [0, 0, 1.4209, 0.3775, 0.1119, 0], 1e-4); ***** assert (pdf (pd, [-1, 1.5, NaN]), [0.2197, 0.1245, NaN], 1e-4); ***** assert (pdf (t, [-1, 1.5, NaN]), [0, 0, NaN], 1e-4); ***** assert (isequal (size (random (pd, 100, 50)), [100, 50])) ***** assert (any (random (t, 1000, 1) < 2), false); ***** assert (any (random (t, 1000, 1) > 4), false); ***** assert (std (pd), 1.2910, 1e-4); ***** assert (std (t), 0.4989, 1e-4); ***** assert (var (pd), 1.6667, 1e-4); ***** assert (var (t), 0.2489, 1e-4); ***** error ... tLocationScaleDistribution(i, 1, 1) ***** error ... tLocationScaleDistribution(Inf, 1, 1) ***** error ... tLocationScaleDistribution([1, 2], 1, 1) ***** error ... tLocationScaleDistribution("a", 1, 1) ***** error ... tLocationScaleDistribution(NaN, 1, 1) ***** error ... tLocationScaleDistribution(0, 0, 1) ***** error ... tLocationScaleDistribution(0, -1, 1) ***** error ... tLocationScaleDistribution(0, Inf, 1) ***** error ... tLocationScaleDistribution(0, i, 1) ***** error ... tLocationScaleDistribution(0, "a", 1) ***** error ... tLocationScaleDistribution(0, [1, 2], 1) ***** error ... tLocationScaleDistribution(0, NaN, 1) ***** error ... tLocationScaleDistribution(0, 1, 0) ***** error ... tLocationScaleDistribution(0, 1, -1) ***** error ... tLocationScaleDistribution(0, 1, Inf) ***** error ... tLocationScaleDistribution(0, 1, i) ***** error ... tLocationScaleDistribution(0, 1, "a") ***** error ... tLocationScaleDistribution(0, 1, [1, 2]) ***** error ... tLocationScaleDistribution(0, 1, NaN) ***** error ... cdf (tLocationScaleDistribution, 2, "uper") ***** error ... cdf (tLocationScaleDistribution, 2, 3) ***** shared x x = tlsrnd (0, 1, 1, [1, 100]); ***** error ... paramci (tLocationScaleDistribution.fit (x), "alpha") ***** error ... paramci (tLocationScaleDistribution.fit (x), "alpha", 0) ***** error ... paramci (tLocationScaleDistribution.fit (x), "alpha", 1) ***** error ... paramci (tLocationScaleDistribution.fit (x), "alpha", [0.5 2]) ***** error ... paramci (tLocationScaleDistribution.fit (x), "alpha", "") ***** error ... paramci (tLocationScaleDistribution.fit (x), "alpha", {0.05}) ***** error ... paramci (tLocationScaleDistribution.fit (x), "parameter", "mu", ... "alpha", {0.05}) ***** error ... paramci (tLocationScaleDistribution.fit (x), ... "parameter", {"mu", "sigma", "nu", "param"}) ***** error ... paramci (tLocationScaleDistribution.fit (x), "alpha", 0.01, ... "parameter", {"mu", "sigma", "nu", "param"}) ***** error ... paramci (tLocationScaleDistribution.fit (x), "parameter", "param") ***** error ... paramci (tLocationScaleDistribution.fit (x), "alpha", 0.01, ... "parameter", "param") ***** error ... paramci (tLocationScaleDistribution.fit (x), "NAME", "value") ***** error ... paramci (tLocationScaleDistribution.fit (x), "alpha", 0.01, "NAME", "value") ***** error ... paramci (tLocationScaleDistribution.fit (x), "alpha", 0.01, ... "parameter", "mu", "NAME", "value") ***** error ... plot (tLocationScaleDistribution, "Parent") ***** error ... plot (tLocationScaleDistribution, "PlotType", 12) ***** error ... plot (tLocationScaleDistribution, "PlotType", {"pdf", "cdf"}) ***** error ... plot (tLocationScaleDistribution, "PlotType", "pdfcdf") ***** error ... plot (tLocationScaleDistribution, "Discrete", "pdfcdf") ***** error ... plot (tLocationScaleDistribution, "Discrete", [1, 0]) ***** error ... plot (tLocationScaleDistribution, "Discrete", {true}) ***** error ... plot (tLocationScaleDistribution, "Parent", 12) ***** error ... plot (tLocationScaleDistribution, "Parent", "hax") ***** error ... proflik (tLocationScaleDistribution, 2) ***** error ... proflik (tLocationScaleDistribution.fit (x), 4) ***** error ... proflik (tLocationScaleDistribution.fit (x), [1, 2]) ***** error ... proflik (tLocationScaleDistribution.fit (x), {1}) ***** error ... proflik (tLocationScaleDistribution.fit (x), 1, ones (2)) ***** error ... proflik (tLocationScaleDistribution.fit (x), 1, "Display") ***** error ... proflik (tLocationScaleDistribution.fit (x), 1, "Display", 1) ***** error ... proflik (tLocationScaleDistribution.fit (x), 1, "Display", {1}) ***** error ... proflik (tLocationScaleDistribution.fit (x), 1, "Display", {"on"}) ***** error ... proflik (tLocationScaleDistribution.fit (x), 1, "Display", ["on"; "on"]) ***** error ... proflik (tLocationScaleDistribution.fit (x), 1, "Display", "onnn") ***** error ... proflik (tLocationScaleDistribution.fit (x), 1, "NAME", "on") ***** error ... proflik (tLocationScaleDistribution.fit (x), 1, {"NAME"}, "on") ***** error ... proflik (tLocationScaleDistribution.fit (x), 1, {[1 2 3 4]}, "Display", "on") ***** error ... truncate (tLocationScaleDistribution) ***** error ... truncate (tLocationScaleDistribution, 2) ***** error ... truncate (tLocationScaleDistribution, 4, 2) ***** shared pd pd = tLocationScaleDistribution (0, 1, 1); pd(2) = tLocationScaleDistribution (0, 1, 3); ***** error cdf (pd, 1) ***** error icdf (pd, 0.5) ***** error iqr (pd) ***** error mean (pd) ***** error median (pd) ***** error negloglik (pd) ***** error paramci (pd) ***** error pdf (pd, 1) ***** error plot (pd) ***** error proflik (pd, 2) ***** error random (pd) ***** error std (pd) ***** error ... truncate (pd, 2, 4) ***** error var (pd) 100 tests, 100 passed, 0 known failure, 0 skipped [inst/dist_obj/LoguniformDistribution.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/dist_obj/LoguniformDistribution.m ***** shared pd, t pd = LoguniformDistribution (1, 4); t = truncate (pd, 2, 4); ***** assert (cdf (pd, [0, 1, 2, 3, 4, 5]), [0, 0, 0.5, 0.7925, 1, 1], 1e-4); ***** assert (cdf (t, [0, 1, 2, 3, 4, 5]), [0, 0, 0, 0.5850, 1, 1], 1e-4); ***** assert (cdf (pd, [1.5, 2, 3, 4]), [0.2925, 0.5, 0.7925, 1], 1e-4); ***** assert (cdf (t, [1.5, 2, 3, 4]), [0, 0, 0.5850, 1], 1e-4); ***** assert (icdf (pd, [0:0.2:1]), [1, 1.3195, 1.7411, 2.2974, 3.0314, 4], 1e-4); ***** assert (icdf (t, [0:0.2:1]), [2, 2.2974, 2.6390, 3.0314, 3.4822, 4], 1e-4); ***** assert (icdf (pd, [-1, 0.4:0.2:1, NaN]), [NaN, 1.7411, 2.2974, 3.0314, 4, NaN], 1e-4); ***** assert (icdf (t, [-1, 0.4:0.2:1, NaN]), [NaN, 2.6390, 3.0314, 3.4822, 4, NaN], 1e-4); ***** assert (iqr (pd), 1.4142, 1e-4); ***** assert (iqr (t), 0.9852, 1e-4); ***** assert (mean (pd), 2.1640, 1e-4); ***** assert (mean (t), 2.8854, 1e-4); ***** assert (median (pd), 2); ***** assert (median (t), 2.8284, 1e-4); ***** assert (pdf (pd, [0, 1, 2, 3, 4, 5]), [0, 0.7213, 0.3607, 0.2404, 0.1803, 0], 1e-4); ***** assert (pdf (t, [0, 1, 2, 3, 4, 5]), [0, 0, 0.7213, 0.4809, 0.3607, 0], 1e-4); ***** assert (pdf (pd, [-1, 1, 2, 3, 4, NaN]), [0, 0.7213, 0.3607, 0.2404, 0.1803, NaN], 1e-4); ***** assert (pdf (t, [-1, 1, 2, 3, 4, NaN]), [0, 0, 0.7213, 0.4809, 0.3607, NaN], 1e-4); ***** assert (isequal (size (random (pd, 100, 50)), [100, 50])) ***** assert (any (random (pd, 1000, 1) < 1), false); ***** assert (any (random (pd, 1000, 1) > 4), false); ***** assert (any (random (t, 1000, 1) < 2), false); ***** assert (any (random (t, 1000, 1) > 4), false); ***** assert (std (pd), 0.8527, 1e-4); ***** assert (std (t), 0.5751, 1e-4); ***** assert (var (pd), 0.7270, 1e-4); ***** assert (var (t), 0.3307, 1e-4); ***** error ... LoguniformDistribution (i, 1) ***** error ... LoguniformDistribution (Inf, 1) ***** error ... LoguniformDistribution ([1, 2], 1) ***** error ... LoguniformDistribution ("a", 1) ***** error ... LoguniformDistribution (NaN, 1) ***** error ... LoguniformDistribution (1, i) ***** error ... LoguniformDistribution (1, Inf) ***** error ... LoguniformDistribution (1, [1, 2]) ***** error ... LoguniformDistribution (1, "a") ***** error ... LoguniformDistribution (1, NaN) ***** error ... LoguniformDistribution (2, 1) ***** error ... cdf (LoguniformDistribution, 2, "uper") ***** error ... cdf (LoguniformDistribution, 2, 3) ***** error ... plot (LoguniformDistribution, "Parent") ***** error ... plot (LoguniformDistribution, "PlotType", 12) ***** error ... plot (LoguniformDistribution, "PlotType", {"pdf", "cdf"}) ***** error ... plot (LoguniformDistribution, "PlotType", "pdfcdf") ***** error ... plot (LoguniformDistribution, "Discrete", "pdfcdf") ***** error ... plot (LoguniformDistribution, "Discrete", [1, 0]) ***** error ... plot (LoguniformDistribution, "Discrete", {true}) ***** error ... plot (LoguniformDistribution, "Parent", 12) ***** error ... plot (LoguniformDistribution, "Parent", "hax") ***** error ... truncate (LoguniformDistribution) ***** error ... truncate (LoguniformDistribution, 2) ***** error ... truncate (LoguniformDistribution, 4, 2) ***** shared pd pd = LoguniformDistribution(1, 4); pd(2) = LoguniformDistribution(2, 5); ***** error cdf (pd, 1) ***** error icdf (pd, 0.5) ***** error iqr (pd) ***** error mean (pd) ***** error median (pd) ***** error pdf (pd, 1) ***** error plot (pd) ***** error random (pd) ***** error std (pd) ***** error ... truncate (pd, 2, 4) ***** error var (pd) 63 tests, 63 passed, 0 known failure, 0 skipped [inst/dist_obj/GeneralizedParetoDistribution.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/dist_obj/GeneralizedParetoDistribution.m ***** shared pd, t pd = GeneralizedParetoDistribution (1, 1, 1); t = truncate (pd, 2, 4); ***** assert (cdf (pd, [0:5]), [0, 0, 0.5, 0.6667, 0.75, 0.8], 1e-4); ***** assert (cdf (t, [0:5]), [0, 0, 0, 0.6667, 1, 1], 1e-4); ***** assert (cdf (pd, [1.5, 2, 3, 4]), [0.3333, 0.5, 0.6667, 0.75], 1e-4); ***** assert (cdf (t, [1.5, 2, 3, 4]), [0, 0, 0.6667, 1], 1e-4); ***** assert (icdf (pd, [0:0.2:1]), [1, 1.25, 1.6667, 2.5, 5, Inf], 1e-4); ***** assert (icdf (t, [0:0.2:1]), [2, 2.2222, 2.5, 2.8571, 3.3333, 4], 1e-4); ***** assert (icdf (pd, [-1, 0.4:0.2:1, NaN]), [NaN, 1.6667, 2.5, 5, Inf, NaN], 1e-4); ***** assert (icdf (t, [-1, 0.4:0.2:1, NaN]), [NaN, 2.5, 2.8571, 3.3333, 4, NaN], 1e-4); ***** assert (iqr (pd), 2.6667, 1e-4); ***** assert (iqr (t), 0.9143, 1e-4); ***** assert (mean (pd), Inf); ***** assert (mean (t), 2.7726, 1e-4); ***** assert (median (pd), 2); ***** assert (median (t), 2.6667, 1e-4); ***** assert (pdf (pd, [0:5]), [0, 1, 0.25, 0.1111, 0.0625, 0.04], 1e-4); ***** assert (pdf (t, [0:5]), [0, 0, 1, 0.4444, 0.25, 0], 1e-4); ***** assert (pdf (pd, [-1, 1:4, NaN]), [0, 1, 0.25, 0.1111, 0.0625, NaN], 1e-4); ***** assert (pdf (t, [-1, 1:4, NaN]), [0, 0, 1, 0.4444, 0.25, NaN], 1e-4); ***** assert (isequal (size (random (pd, 100, 50)), [100, 50])) ***** assert (any (random (t, 1000, 1) < 2), false); ***** assert (any (random (t, 1000, 1) > 4), false); ***** assert (std (pd), Inf); ***** assert (std (t), 0.5592, 1e-4); ***** assert (var (pd), Inf); ***** assert (var (t), 0.3128, 1e-4); ***** error ... GeneralizedParetoDistribution(Inf, 1, 1) ***** error ... GeneralizedParetoDistribution(i, 1, 1) ***** error ... GeneralizedParetoDistribution("a", 1, 1) ***** error ... GeneralizedParetoDistribution([1, 2], 1, 1) ***** error ... GeneralizedParetoDistribution(NaN, 1, 1) ***** error ... GeneralizedParetoDistribution(1, 0, 1) ***** error ... GeneralizedParetoDistribution(1, -1, 1) ***** error ... GeneralizedParetoDistribution(1, Inf, 1) ***** error ... GeneralizedParetoDistribution(1, i, 1) ***** error ... GeneralizedParetoDistribution(1, "a", 1) ***** error ... GeneralizedParetoDistribution(1, [1, 2], 1) ***** error ... GeneralizedParetoDistribution(1, NaN, 1) ***** error ... GeneralizedParetoDistribution(1, 1, Inf) ***** error ... GeneralizedParetoDistribution(1, 1, i) ***** error ... GeneralizedParetoDistribution(1, 1, "a") ***** error ... GeneralizedParetoDistribution(1, 1, [1, 2]) ***** error ... GeneralizedParetoDistribution(1, 1, NaN) ***** error ... cdf (GeneralizedParetoDistribution, 2, "uper") ***** error ... cdf (GeneralizedParetoDistribution, 2, 3) ***** shared x x = gprnd (1, 1, 1, [1, 100]); ***** error ... paramci (GeneralizedParetoDistribution.fit (x, 1), "alpha") ***** error ... paramci (GeneralizedParetoDistribution.fit (x, 1), "alpha", 0) ***** error ... paramci (GeneralizedParetoDistribution.fit (x, 1), "alpha", 1) ***** error ... paramci (GeneralizedParetoDistribution.fit (x, 1), "alpha", [0.5 2]) ***** error ... paramci (GeneralizedParetoDistribution.fit (x, 1), "alpha", "") ***** error ... paramci (GeneralizedParetoDistribution.fit (x, 1), "alpha", {0.05}) ***** error ... paramci (GeneralizedParetoDistribution.fit (x, 1), ... "parameter", "sigma", "alpha", {0.05}) ***** error ... paramci (GeneralizedParetoDistribution.fit (x, 1), ... "parameter", {"k", "sigma", "param"}) ***** error ... paramci (GeneralizedParetoDistribution.fit (x, 1), "alpha", 0.01, ... "parameter", {"k", "sigma", "param"}) ***** error ... paramci (GeneralizedParetoDistribution.fit (x, 1), "parameter", "param") ***** error ... paramci (GeneralizedParetoDistribution.fit (x, 1), "alpha", 0.01, ... "parameter", "param") ***** error ... paramci (GeneralizedParetoDistribution.fit (x, 1), "NAME", "value") ***** error ... paramci (GeneralizedParetoDistribution.fit (x, 1), "alpha", 0.01, ... "NAME", "value") ***** error ... paramci (GeneralizedParetoDistribution.fit (x, 1), "alpha", 0.01, ... "parameter", "sigma", "NAME", "value") ***** error ... plot (GeneralizedParetoDistribution, "Parent") ***** error ... plot (GeneralizedParetoDistribution, "PlotType", 12) ***** error ... plot (GeneralizedParetoDistribution, "PlotType", {"pdf", "cdf"}) ***** error ... plot (GeneralizedParetoDistribution, "PlotType", "pdfcdf") ***** error ... plot (GeneralizedParetoDistribution, "Discrete", "pdfcdf") ***** error ... plot (GeneralizedParetoDistribution, "Discrete", [1, 0]) ***** error ... plot (GeneralizedParetoDistribution, "Discrete", {true}) ***** error ... plot (GeneralizedParetoDistribution, "Parent", 12) ***** error ... plot (GeneralizedParetoDistribution, "Parent", "hax") ***** error ... proflik (GeneralizedParetoDistribution, 2) ***** error ... proflik (GeneralizedParetoDistribution.fit (x, 1), 3) ***** error ... proflik (GeneralizedParetoDistribution.fit (x, 1), [1, 2]) ***** error ... proflik (GeneralizedParetoDistribution.fit (x, 1), {1}) ***** error ... proflik (GeneralizedParetoDistribution.fit (x, 1), 1, ones (2)) ***** error ... proflik (GeneralizedParetoDistribution.fit (x, 1), 1, "Display") ***** error ... proflik (GeneralizedParetoDistribution.fit (x, 1), 1, "Display", 1) ***** error ... proflik (GeneralizedParetoDistribution.fit (x, 1), 1, "Display", {1}) ***** error ... proflik (GeneralizedParetoDistribution.fit (x, 1), 1, "Display", {"on"}) ***** error ... proflik (GeneralizedParetoDistribution.fit (x, 1), 1, ... "Display", ["on"; "on"]) ***** error ... proflik (GeneralizedParetoDistribution.fit (x, 1), 1, "Display", "onnn") ***** error ... proflik (GeneralizedParetoDistribution.fit (x, 1), 1, "NAME", "on") ***** error ... proflik (GeneralizedParetoDistribution.fit (x, 1), 1, {"NAME"}, "on") ***** error ... proflik (GeneralizedParetoDistribution.fit (x, 1), 1, {[1 2 3 4]}, ... "Display", "on") ***** error ... truncate (GeneralizedParetoDistribution) ***** error ... truncate (GeneralizedParetoDistribution, 2) ***** error ... truncate (GeneralizedParetoDistribution, 4, 2) ***** shared pd pd = GeneralizedParetoDistribution(1, 1, 1); pd(2) = GeneralizedParetoDistribution(1, 3, 1); ***** error cdf (pd, 1) ***** error icdf (pd, 0.5) ***** error iqr (pd) ***** error mean (pd) ***** error median (pd) ***** error negloglik (pd) ***** error paramci (pd) ***** error pdf (pd, 1) ***** error plot (pd) ***** error proflik (pd, 2) ***** error random (pd) ***** error std (pd) ***** error ... truncate (pd, 2, 4) ***** error var (pd) 98 tests, 98 passed, 0 known failure, 0 skipped [inst/dist_obj/BurrDistribution.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/dist_obj/BurrDistribution.m ***** shared pd, t pd = BurrDistribution; t = truncate (pd, 2, 4); ***** assert (cdf (pd, [0:5]), [0, 0.5, 0.6667, 0.75, 0.8, 0.8333], 1e-4); ***** assert (cdf (t, [0:5]), [0, 0, 0, 0.625, 1, 1], 1e-4); ***** assert (cdf (pd, [1.5, 2, 3, 4]), [0.6, 0.6667, 0.75, 0.8], 1e-4); ***** assert (cdf (t, [1.5, 2, 3, 4]), [0, 0, 0.625, 1], 1e-4); ***** assert (icdf (pd, [0:0.2:1]), [0, 0.25, 0.6667, 1.5, 4, Inf], 1e-4); ***** assert (icdf (t, [0:0.2:1]), [2, 2.2609, 2.5714, 2.9474, 3.4118, 4], 1e-4); ***** assert (icdf (pd, [-1, 0.4:0.2:1, NaN]), [NaN, 0.6667, 1.5, 4, Inf, NaN], 1e-4); ***** assert (icdf (t, [-1, 0.4:0.2:1, NaN]), [NaN, 2.5714, 2.9474, 3.4118, 4, NaN], 1e-4); ***** assert (iqr (pd), 2.6667, 1e-4); ***** assert (iqr (t), 0.9524, 1e-4); ***** assert (mean (pd), Inf); ***** assert (mean (t), 2.8312, 1e-4); ***** assert (median (pd), 1, 1e-4); ***** assert (median (t), 2.75, 1e-4); ***** assert (pdf (pd, [0:5]), [1, 0.25, 0.1111, 0.0625, 0.04, 0.0278], 1e-4); ***** assert (pdf (t, [0:5]), [0, 0, 0.8333, 0.4687, 0.3, 0], 1e-4); ***** assert (pdf (pd, [-1, 1:4, NaN]), [0, 0.25, 0.1111, 0.0625, 0.04, NaN], 1e-4); ***** assert (pdf (t, [-1, 1:4, NaN]), [0, 0, 0.8333, 0.4687, 0.3, NaN], 1e-4); ***** assert (isequal (size (random (pd, 100, 50)), [100, 50])) ***** assert (any (random (t, 1000, 1) < 2), false); ***** assert (any (random (t, 1000, 1) > 4), false); ***** assert (std (pd), Inf); ***** assert (std (t), 0.5674, 1e-4); ***** assert (var (pd), Inf); ***** assert (var (t), 0.3220, 1e-4); ***** error ... BurrDistribution(0, 1, 1) ***** error ... BurrDistribution(-1, 1, 1) ***** error ... BurrDistribution(Inf, 1, 1) ***** error ... BurrDistribution(i, 1, 1) ***** error ... BurrDistribution("a", 1, 1) ***** error ... BurrDistribution([1, 2], 1, 1) ***** error ... BurrDistribution(NaN, 1, 1) ***** error ... BurrDistribution(1, 0, 1) ***** error ... BurrDistribution(1, -1, 1) ***** error ... BurrDistribution(1, Inf, 1) ***** error ... BurrDistribution(1, i, 1) ***** error ... BurrDistribution(1, "a", 1) ***** error ... BurrDistribution(1, [1, 2], 1) ***** error ... BurrDistribution(1, NaN, 1) ***** error ... BurrDistribution(1, 1, 0) ***** error ... BurrDistribution(1, 1, -1) ***** error ... BurrDistribution(1, 1, Inf) ***** error ... BurrDistribution(1, 1, i) ***** error ... BurrDistribution(1, 1, "a") ***** error ... BurrDistribution(1, 1, [1, 2]) ***** error ... BurrDistribution(1, 1, NaN) ***** error ... cdf (BurrDistribution, 2, "uper") ***** error ... cdf (BurrDistribution, 2, 3) ***** shared x rand ("seed", 4); x = burrrnd (1, 1, 1, [1, 100]); ***** error ... paramci (BurrDistribution.fit (x), "alpha") ***** error ... paramci (BurrDistribution.fit (x), "alpha", 0) ***** error ... paramci (BurrDistribution.fit (x), "alpha", 1) ***** error ... paramci (BurrDistribution.fit (x), "alpha", [0.5 2]) ***** error ... paramci (BurrDistribution.fit (x), "alpha", "") ***** error ... paramci (BurrDistribution.fit (x), "alpha", {0.05}) ***** error ... paramci (BurrDistribution.fit (x), "parameter", "c", "alpha", {0.05}) ***** error ... paramci (BurrDistribution.fit (x), "parameter", {"alpha", "c", "k", "param"}) ***** error ... paramci (BurrDistribution.fit (x), "alpha", 0.01, ... "parameter", {"alpha", "c", "k", "param"}) ***** error ... paramci (BurrDistribution.fit (x), "parameter", "param") ***** error ... paramci (BurrDistribution.fit (x), "alpha", 0.01, "parameter", "param") ***** error ... paramci (BurrDistribution.fit (x), "NAME", "value") ***** error ... paramci (BurrDistribution.fit (x), "alpha", 0.01, "NAME", "value") ***** error ... paramci (BurrDistribution.fit (x), "alpha", 0.01, "parameter", "c", ... "NAME", "value") ***** error ... plot (BurrDistribution, "Parent") ***** error ... plot (BurrDistribution, "PlotType", 12) ***** error ... plot (BurrDistribution, "PlotType", {"pdf", "cdf"}) ***** error ... plot (BurrDistribution, "PlotType", "pdfcdf") ***** error ... plot (BurrDistribution, "Discrete", "pdfcdf") ***** error ... plot (BurrDistribution, "Discrete", [1, 0]) ***** error ... plot (BurrDistribution, "Discrete", {true}) ***** error ... plot (BurrDistribution, "Parent", 12) ***** error ... plot (BurrDistribution, "Parent", "hax") ***** error ... proflik (BurrDistribution, 2) ***** error ... proflik (BurrDistribution.fit (x), 4) ***** error ... proflik (BurrDistribution.fit (x), [1, 2]) ***** error ... proflik (BurrDistribution.fit (x), {1}) ***** error ... proflik (BurrDistribution.fit (x), 1, ones (2)) ***** error ... proflik (BurrDistribution.fit (x), 1, "Display") ***** error ... proflik (BurrDistribution.fit (x), 1, "Display", 1) ***** error ... proflik (BurrDistribution.fit (x), 1, "Display", {1}) ***** error ... proflik (BurrDistribution.fit (x), 1, "Display", {"on"}) ***** error ... proflik (BurrDistribution.fit (x), 1, "Display", ["on"; "on"]) ***** error ... proflik (BurrDistribution.fit (x), 1, "Display", "onnn") ***** error ... proflik (BurrDistribution.fit (x), 1, "NAME", "on") ***** error ... proflik (BurrDistribution.fit (x), 1, {"NAME"}, "on") ***** error ... proflik (BurrDistribution.fit (x), 1, {[1 2 3 4]}, "Display", "on") ***** error ... truncate (BurrDistribution) ***** error ... truncate (BurrDistribution, 2) ***** error ... truncate (BurrDistribution, 4, 2) ***** shared pd pd = BurrDistribution(1, 1, 1); pd(2) = BurrDistribution(1, 3, 1); ***** error cdf (pd, 1) ***** error icdf (pd, 0.5) ***** error iqr (pd) ***** error mean (pd) ***** error median (pd) ***** error negloglik (pd) ***** error paramci (pd) ***** error pdf (pd, 1) ***** error plot (pd) ***** error proflik (pd, 2) ***** error random (pd) ***** error std (pd) ***** error ... truncate (pd, 2, 4) ***** error var (pd) 102 tests, 102 passed, 0 known failure, 0 skipped [inst/dist_obj/HalfNormalDistribution.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/dist_obj/HalfNormalDistribution.m ***** shared pd, t pd = HalfNormalDistribution (0, 1); t = truncate (pd, 2, 4); ***** assert (cdf (pd, [0:5]), [0, 0.6827, 0.9545, 0.9973, 0.9999, 1], 1e-4); ***** assert (cdf (t, [0:5]), [0, 0, 0, 0.9420, 1, 1], 1e-4); ***** assert (cdf (pd, [1.5, 2, 3, 4]), [0.8664, 0.9545, 0.9973, 0.9999], 1e-4); ***** assert (cdf (t, [1.5, 2, 3, 4]), [0, 0, 0.9420, 1], 1e-4); ***** assert (icdf (pd, [0:0.2:1]), [0, 0.2533, 0.5244, 0.8416, 1.2816, Inf], 1e-4); ***** assert (icdf (t, [0:0.2:1]), [2, 2.0923, 2.2068, 2.3607, 2.6064, 4], 1e-4); ***** assert (icdf (pd, [-1, 0.4:0.2:1, NaN]), [NaN, 0.5244, 0.8416, 1.2816, Inf, NaN], 1e-4); ***** assert (icdf (t, [-1, 0.4:0.2:1, NaN]), [NaN, 2.2068, 2.3607, 2.6064, 4, NaN], 1e-4); ***** assert (iqr (pd), 0.8317, 1e-4); ***** assert (iqr (t), 0.4111, 1e-4); ***** assert (mean (pd), 0.7979, 1e-4); ***** assert (mean (t), 2.3706, 1e-4); ***** assert (median (pd), 0.6745, 1e-4); ***** assert (median (t), 2.2771, 1e-4); ***** assert (pdf (pd, [0:5]), [0.7979, 0.4839, 0.1080, 0.0089, 0.0003, 0], 1e-4); ***** assert (pdf (t, [0:5]), [0, 0, 2.3765, 0.1951, 0.0059, 0], 1e-4); ***** assert (pdf (pd, [-1, 1:4, NaN]), [0, 0.4839, 0.1080, 0.0089, 0.0003, NaN], 1e-4); ***** assert (pdf (t, [-1, 1:4, NaN]), [0, 0, 2.3765, 0.1951, 0.0059, NaN], 1e-4); ***** assert (isequal (size (random (pd, 100, 50)), [100, 50])) ***** assert (any (random (t, 1000, 1) < 2), false); ***** assert (any (random (t, 1000, 1) > 4), false); ***** assert (std (pd), 0.6028, 1e-4); ***** assert (std (t), 0.3310, 1e-4); ***** assert (var (pd), 0.3634, 1e-4); ***** assert (var (t), 0.1096, 1e-4); ***** error ... HalfNormalDistribution(Inf, 1) ***** error ... HalfNormalDistribution(i, 1) ***** error ... HalfNormalDistribution("a", 1) ***** error ... HalfNormalDistribution([1, 2], 1) ***** error ... HalfNormalDistribution(NaN, 1) ***** error ... HalfNormalDistribution(1, 0) ***** error ... HalfNormalDistribution(1, -1) ***** error ... HalfNormalDistribution(1, Inf) ***** error ... HalfNormalDistribution(1, i) ***** error ... HalfNormalDistribution(1, "a") ***** error ... HalfNormalDistribution(1, [1, 2]) ***** error ... HalfNormalDistribution(1, NaN) ***** error ... cdf (HalfNormalDistribution, 2, "uper") ***** error ... cdf (HalfNormalDistribution, 2, 3) ***** shared x x = hnrnd (1, 1, [1, 100]); ***** error ... paramci (HalfNormalDistribution.fit (x, 1), "alpha") ***** error ... paramci (HalfNormalDistribution.fit (x, 1), "alpha", 0) ***** error ... paramci (HalfNormalDistribution.fit (x, 1), "alpha", 1) ***** error ... paramci (HalfNormalDistribution.fit (x, 1), "alpha", [0.5 2]) ***** error ... paramci (HalfNormalDistribution.fit (x, 1), "alpha", "") ***** error ... paramci (HalfNormalDistribution.fit (x, 1), "alpha", {0.05}) ***** error ... paramci (HalfNormalDistribution.fit (x, 1), "parameter", "sigma", ... "alpha", {0.05}) ***** error ... paramci (HalfNormalDistribution.fit (x, 1), ... "parameter", {"mu", "sigma", "param"}) ***** error ... paramci (HalfNormalDistribution.fit (x, 1), "alpha", 0.01, ... "parameter", {"mu", "sigma", "param"}) ***** error ... paramci (HalfNormalDistribution.fit (x, 1), "parameter", "param") ***** error ... paramci (HalfNormalDistribution.fit (x, 1), "alpha", 0.01, ... "parameter", "param") ***** error ... paramci (HalfNormalDistribution.fit (x, 1),"NAME", "value") ***** error ... paramci (HalfNormalDistribution.fit (x, 1), "alpha", 0.01, ... "NAME", "value") ***** error ... paramci (HalfNormalDistribution.fit (x, 1), "alpha", 0.01, ... "parameter", "sigma", "NAME", "value") ***** error ... plot (HalfNormalDistribution, "Parent") ***** error ... plot (HalfNormalDistribution, "PlotType", 12) ***** error ... plot (HalfNormalDistribution, "PlotType", {"pdf", "cdf"}) ***** error ... plot (HalfNormalDistribution, "PlotType", "pdfcdf") ***** error ... plot (HalfNormalDistribution, "Discrete", "pdfcdf") ***** error ... plot (HalfNormalDistribution, "Discrete", [1, 0]) ***** error ... plot (HalfNormalDistribution, "Discrete", {true}) ***** error ... plot (HalfNormalDistribution, "Parent", 12) ***** error ... plot (HalfNormalDistribution, "Parent", "hax") ***** error ... proflik (HalfNormalDistribution, 2) ***** error ... proflik (HalfNormalDistribution.fit (x, 1), 3) ***** error ... proflik (HalfNormalDistribution.fit (x, 1), [1, 2]) ***** error ... proflik (HalfNormalDistribution.fit (x, 1), {1}) ***** error ... proflik (HalfNormalDistribution.fit (x, 1), 1) ***** error ... proflik (HalfNormalDistribution.fit (x, 1), 2, ones (2)) ***** error ... proflik (HalfNormalDistribution.fit (x, 1), 2, "Display") ***** error ... proflik (HalfNormalDistribution.fit (x, 1), 2, "Display", 1) ***** error ... proflik (HalfNormalDistribution.fit (x, 1), 2, "Display", {1}) ***** error ... proflik (HalfNormalDistribution.fit (x, 1), 2, "Display", {"on"}) ***** error ... proflik (HalfNormalDistribution.fit (x, 1), 2, "Display", ["on"; "on"]) ***** error ... proflik (HalfNormalDistribution.fit (x, 1), 2, "Display", "onnn") ***** error ... proflik (HalfNormalDistribution.fit (x, 1), 2, "NAME", "on") ***** error ... proflik (HalfNormalDistribution.fit (x, 1), 2, {"NAME"}, "on") ***** error ... proflik (HalfNormalDistribution.fit (x, 1), 2, {[1 2 3 4]}, ... "Display", "on") ***** error ... truncate (HalfNormalDistribution) ***** error ... truncate (HalfNormalDistribution, 2) ***** error ... truncate (HalfNormalDistribution, 4, 2) ***** shared pd pd = HalfNormalDistribution(1, 1); pd(2) = HalfNormalDistribution(1, 3); ***** error cdf (pd, 1) ***** error icdf (pd, 0.5) ***** error iqr (pd) ***** error mean (pd) ***** error median (pd) ***** error negloglik (pd) ***** error paramci (pd) ***** error pdf (pd, 1) ***** error plot (pd) ***** error proflik (pd, 2) ***** error random (pd) ***** error std (pd) ***** error ... truncate (pd, 2, 4) ***** error var (pd) 94 tests, 94 passed, 0 known failure, 0 skipped [inst/dist_obj/LognormalDistribution.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/dist_obj/LognormalDistribution.m ***** shared pd, t pd = LognormalDistribution; t = truncate (pd, 2, 4); ***** assert (cdf (pd, [0:5]), [0, 0.5, 0.7559, 0.8640, 0.9172, 0.9462], 1e-4); ***** assert (cdf (t, [0:5]), [0, 0, 0, 0.6705, 1, 1], 1e-4); ***** assert (cdf (pd, [1.5, 2, 3, 4]), [0.6574, 0.7559, 0.8640, 0.9172], 1e-4); ***** assert (cdf (t, [1.5, 2, 3, 4]), [0, 0, 0.6705, 1], 1e-4); ***** assert (icdf (pd, [0:0.2:1]), [0, 0.4310, 0.7762, 1.2883, 2.3201, Inf], 1e-4); ***** assert (icdf (t, [0:0.2:1]), [2, 2.2256, 2.5015, 2.8517, 3.3199, 4], 1e-4); ***** assert (icdf (pd, [-1, 0.4:0.2:1, NaN]), [NaN, 0.7762, 1.2883, 2.3201, Inf, NaN], 1e-4); ***** assert (icdf (t, [-1, 0.4:0.2:1, NaN]), [NaN, 2.5015, 2.8517, 3.3199, 4, NaN], 1e-4); ***** assert (iqr (pd), 1.4536, 1e-4); ***** assert (iqr (t), 0.8989, 1e-4); ***** assert (mean (pd), 1.6487, 1e-4); ***** assert (mean (t), 2.7692, 1e-4); ***** assert (median (pd), 1, 1e-4); ***** assert (median (t), 2.6653, 1e-4); ***** assert (pdf (pd, [0:5]), [0, 0.3989, 0.1569, 0.0727, 0.0382, 0.0219], 1e-4); ***** assert (pdf (t, [0:5]), [0, 0, 0.9727, 0.4509, 0.2366, 0], 1e-4); ***** assert (pdf (pd, [-1, 1:4, NaN]), [0, 0.3989, 0.1569, 0.0727, 0.0382, NaN], 1e-4); ***** assert (pdf (t, [-1, 1:4, NaN]), [0, 0, 0.9727, 0.4509, 0.2366, NaN], 1e-4); ***** assert (isequal (size (random (pd, 100, 50)), [100, 50])) ***** assert (any (random (t, 1000, 1) < 2), false); ***** assert (any (random (t, 1000, 1) > 4), false); ***** assert (std (pd), 2.1612, 1e-4); ***** assert (std (t), 0.5540, 1e-4); ***** assert (var (pd), 4.6708, 1e-4); ***** assert (var (t), 0.3069, 1e-4); ***** error ... LognormalDistribution(Inf, 1) ***** error ... LognormalDistribution(i, 1) ***** error ... LognormalDistribution("a", 1) ***** error ... LognormalDistribution([1, 2], 1) ***** error ... LognormalDistribution(NaN, 1) ***** error ... LognormalDistribution(1, 0) ***** error ... LognormalDistribution(1, -1) ***** error ... LognormalDistribution(1, Inf) ***** error ... LognormalDistribution(1, i) ***** error ... LognormalDistribution(1, "a") ***** error ... LognormalDistribution(1, [1, 2]) ***** error ... LognormalDistribution(1, NaN) ***** error ... cdf (LognormalDistribution, 2, "uper") ***** error ... cdf (LognormalDistribution, 2, 3) ***** shared x randn ("seed", 1); x = lognrnd (1, 1, [1, 100]); ***** error ... paramci (LognormalDistribution.fit (x), "alpha") ***** error ... paramci (LognormalDistribution.fit (x), "alpha", 0) ***** error ... paramci (LognormalDistribution.fit (x), "alpha", 1) ***** error ... paramci (LognormalDistribution.fit (x), "alpha", [0.5 2]) ***** error ... paramci (LognormalDistribution.fit (x), "alpha", "") ***** error ... paramci (LognormalDistribution.fit (x), "alpha", {0.05}) ***** error ... paramci (LognormalDistribution.fit (x), "parameter", "mu", "alpha", {0.05}) ***** error ... paramci (LognormalDistribution.fit (x), "parameter", {"mu", "sigma", "parm"}) ***** error ... paramci (LognormalDistribution.fit (x), "alpha", 0.01, ... "parameter", {"mu", "sigma", "param"}) ***** error ... paramci (LognormalDistribution.fit (x), "parameter", "param") ***** error ... paramci (LognormalDistribution.fit (x), "alpha", 0.01, "parameter", "param") ***** error ... paramci (LognormalDistribution.fit (x), "NAME", "value") ***** error ... paramci (LognormalDistribution.fit (x), "alpha", 0.01, "NAME", "value") ***** error ... paramci (LognormalDistribution.fit (x), "alpha", 0.01, "parameter", "mu", ... "NAME", "value") ***** error ... plot (LognormalDistribution, "Parent") ***** error ... plot (LognormalDistribution, "PlotType", 12) ***** error ... plot (LognormalDistribution, "PlotType", {"pdf", "cdf"}) ***** error ... plot (LognormalDistribution, "PlotType", "pdfcdf") ***** error ... plot (LognormalDistribution, "Discrete", "pdfcdf") ***** error ... plot (LognormalDistribution, "Discrete", [1, 0]) ***** error ... plot (LognormalDistribution, "Discrete", {true}) ***** error ... plot (LognormalDistribution, "Parent", 12) ***** error ... plot (LognormalDistribution, "Parent", "hax") ***** error ... proflik (LognormalDistribution, 2) ***** error ... proflik (LognormalDistribution.fit (x), 3) ***** error ... proflik (LognormalDistribution.fit (x), [1, 2]) ***** error ... proflik (LognormalDistribution.fit (x), {1}) ***** error ... proflik (LognormalDistribution.fit (x), 1, ones (2)) ***** error ... proflik (LognormalDistribution.fit (x), 1, "Display") ***** error ... proflik (LognormalDistribution.fit (x), 1, "Display", 1) ***** error ... proflik (LognormalDistribution.fit (x), 1, "Display", {1}) ***** error ... proflik (LognormalDistribution.fit (x), 1, "Display", {"on"}) ***** error ... proflik (LognormalDistribution.fit (x), 1, "Display", ["on"; "on"]) ***** error ... proflik (LognormalDistribution.fit (x), 1, "Display", "onnn") ***** error ... proflik (LognormalDistribution.fit (x), 1, "NAME", "on") ***** error ... proflik (LognormalDistribution.fit (x), 1, {"NAME"}, "on") ***** error ... proflik (LognormalDistribution.fit (x), 1, {[1 2 3 4]}, "Display", "on") ***** error ... truncate (LognormalDistribution) ***** error ... truncate (LognormalDistribution, 2) ***** error ... truncate (LognormalDistribution, 4, 2) ***** shared pd pd = LognormalDistribution(1, 1); pd(2) = LognormalDistribution(1, 3); ***** error cdf (pd, 1) ***** error icdf (pd, 0.5) ***** error iqr (pd) ***** error mean (pd) ***** error median (pd) ***** error negloglik (pd) ***** error paramci (pd) ***** error pdf (pd, 1) ***** error plot (pd) ***** error proflik (pd, 2) ***** error random (pd) ***** error std (pd) ***** error ... truncate (pd, 2, 4) ***** error var (pd) 93 tests, 93 passed, 0 known failure, 0 skipped [inst/dist_obj/BinomialDistribution.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/dist_obj/BinomialDistribution.m ***** shared pd, t pd = BinomialDistribution (5, 0.5); t = truncate (pd, 2, 4); ***** assert (cdf (pd, [0:5]), [0.0312, 0.1875, 0.5, 0.8125, 0.9688, 1], 1e-4); ***** assert (cdf (pd, [1.5, 2, 3, 4, NaN]), [0.1875, 0.5, 0.8125, 0.9688, NaN], 1e-4); ***** assert (icdf (pd, [0:0.2:1]), [0, 2, 2, 3, 3, 5], 1e-4); ***** assert (icdf (pd, [-1, 0.4:0.2:1, NaN]), [NaN, 2, 3, 3, 5, NaN], 1e-4); ***** assert (iqr (pd), 1); ***** assert (mean (pd), 2.5, 1e-10); ***** assert (median (pd), 2.5); ***** assert (pdf (pd, [0:5]), [0.0312, 0.1562, 0.3125, 0.3125, 0.1562, 0.0312], 1e-4); ***** assert (pdf (pd, [-1, 1.5, NaN]), [0, 0, NaN], 1e-4); ***** assert (isequal (size (random (pd, 100, 50)), [100, 50])) ***** assert (std (pd), 1.1180, 1e-4); ***** assert (var (pd), 1.2500, 1e-4); ***** error ... BinomialDistribution(Inf, 0.5) ***** error ... BinomialDistribution(i, 0.5) ***** error ... BinomialDistribution("a", 0.5) ***** error ... BinomialDistribution([1, 2], 0.5) ***** error ... BinomialDistribution(NaN, 0.5) ***** error ... BinomialDistribution(1, 1.01) ***** error ... BinomialDistribution(1, -0.01) ***** error ... BinomialDistribution(1, Inf) ***** error ... BinomialDistribution(1, i) ***** error ... BinomialDistribution(1, "a") ***** error ... BinomialDistribution(1, [1, 2]) ***** error ... BinomialDistribution(1, NaN) ***** error ... cdf (BinomialDistribution, 2, "uper") ***** error ... cdf (BinomialDistribution, 2, 3) ***** shared x rand ("seed", 2); x = binornd (5, 0.5, [1, 100]); ***** error ... paramci (BinomialDistribution.fit (x, 6), "alpha") ***** error ... paramci (BinomialDistribution.fit (x, 6), "alpha", 0) ***** error ... paramci (BinomialDistribution.fit (x, 6), "alpha", 1) ***** error ... paramci (BinomialDistribution.fit (x, 6), "alpha", [0.5 2]) ***** error ... paramci (BinomialDistribution.fit (x, 6), "alpha", "") ***** error ... paramci (BinomialDistribution.fit (x, 6), "alpha", {0.05}) ***** error ... paramci (BinomialDistribution.fit (x, 6), "parameter", "p", ... "alpha", {0.05}) ***** error ... paramci (BinomialDistribution.fit (x, 6), ... "parameter", {"N", "p", "param"}) ***** error ... paramci (BinomialDistribution.fit (x, 6), "alpha", 0.01, ... "parameter", {"N", "p", "param"}) ***** error ... paramci (BinomialDistribution.fit (x, 6), "parameter", "param") ***** error ... paramci (BinomialDistribution.fit (x, 6), "parameter", "N") ***** error ... paramci (BinomialDistribution.fit (x, 6), "alpha", 0.01, ... "parameter", "param") ***** error ... paramci (BinomialDistribution.fit (x, 6), "NAME", "value") ***** error ... paramci (BinomialDistribution.fit (x, 6), "alpha", 0.01, ... "NAME", "value") ***** error ... paramci (BinomialDistribution.fit (x, 6), "alpha", 0.01, ... "parameter", "p", "NAME", "value") ***** error ... plot (BinomialDistribution, "Parent") ***** error ... plot (BinomialDistribution, "PlotType", 12) ***** error ... plot (BinomialDistribution, "PlotType", {"pdf", "cdf"}) ***** error ... plot (BinomialDistribution, "PlotType", "pdfcdf") ***** error ... plot (BinomialDistribution, "Discrete", "pdfcdf") ***** error ... plot (BinomialDistribution, "Discrete", [1, 0]) ***** error ... plot (BinomialDistribution, "Discrete", {true}) ***** error ... plot (BinomialDistribution, "Parent", 12) ***** error ... plot (BinomialDistribution, "Parent", "hax") ***** error ... proflik (BinomialDistribution, 2) ***** error ... proflik (BinomialDistribution.fit (x, 6), 3) ***** error ... proflik (BinomialDistribution.fit (x, 6), [1, 2]) ***** error ... proflik (BinomialDistribution.fit (x, 6), {1}) ***** error ... proflik (BinomialDistribution.fit (x, 6), 2, ones (2)) ***** error ... proflik (BinomialDistribution.fit (x, 6), 2, "Display") ***** error ... proflik (BinomialDistribution.fit (x, 6), 2, "Display", 1) ***** error ... proflik (BinomialDistribution.fit (x, 6), 2, "Display", {1}) ***** error ... proflik (BinomialDistribution.fit (x, 6), 2, "Display", {"on"}) ***** error ... proflik (BinomialDistribution.fit (x, 6), 2, "Display", ["on"; "on"]) ***** error ... proflik (BinomialDistribution.fit (x, 6), 2, "Display", "onnn") ***** error ... proflik (BinomialDistribution.fit (x, 6), 2, "NAME", "on") ***** error ... proflik (BinomialDistribution.fit (x, 6), 2, {"NAME"}, "on") ***** error ... proflik (BinomialDistribution.fit (x, 6), 2, {[1 2 3]}, "Display", "on") ***** error ... truncate (BinomialDistribution) ***** error ... truncate (BinomialDistribution, 2) ***** error ... truncate (BinomialDistribution, 4, 2) ***** shared pd pd = BinomialDistribution(1, 0.5); pd(2) = BinomialDistribution(1, 0.6); ***** error cdf (pd, 1) ***** error icdf (pd, 0.5) ***** error iqr (pd) ***** error mean (pd) ***** error median (pd) ***** error negloglik (pd) ***** error paramci (pd) ***** error pdf (pd, 1) ***** error plot (pd) ***** error proflik (pd, 2) ***** error random (pd) ***** error std (pd) ***** error ... truncate (pd, 2, 4) ***** error var (pd) 81 tests, 81 passed, 0 known failure, 0 skipped [inst/dist_obj/ExtremeValueDistribution.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/dist_obj/ExtremeValueDistribution.m ***** shared pd, t pd = ExtremeValueDistribution (0, 1); t = truncate (pd, 2, 4); ***** assert (cdf (pd, [0:5]), [0.6321, 0.9340, 0.9994, 1, 1, 1], 1e-4); ***** assert (cdf (t, [0:5]), [0, 0, 0, 1, 1, 1], 1e-4); ***** assert (cdf (pd, [1.5, 2, 3, 4]), [0.9887, 0.9994, 1, 1], 1e-4); ***** assert (cdf (t, [1.5, 2, 3, 4]), [0, 0, 1, 1], 1e-4); ***** assert (icdf (pd, [0:0.2:1]), [-Inf, -1.4999, -0.6717, -0.0874, 0.4759, Inf], 1e-4); ***** assert (icdf (t, [0:0.2:1]), [2, 2.0298, 2.0668, 2.1169, 2.1971, 4], 1e-4); ***** assert (icdf (pd, [-1, 0.4:0.2:1, NaN]), [NaN, -0.6717, -0.0874, 0.4759, Inf, NaN], 1e-4); ***** assert (icdf (t, [-1, 0.4:0.2:1, NaN]), [NaN, 2.0668, 2.1169, 2.1971, 4, NaN], 1e-4); ***** assert (iqr (pd), 1.5725, 1e-4); ***** assert (iqr (t), 0.1338, 1e-4); ***** assert (mean (pd), -0.5772, 1e-4); ***** assert (mean (t), 2.1206, 1e-4); ***** assert (median (pd), -0.3665, 1e-4); ***** assert (median (t), 2.0897, 1e-4); ***** assert (pdf (pd, [0:5]), [0.3679, 0.1794, 0.0046, 0, 0, 0], 1e-4); ***** assert (pdf (t, [0:5]), [0, 0, 7.3891, 0.0001, 0, 0], 1e-4); ***** assert (pdf (pd, [-1, 1:4, NaN]), [0.2546, 0.1794, 0.0046, 0, 0, NaN], 1e-4); ***** assert (pdf (t, [-1, 1:4, NaN]), [0, 0, 7.3891, 0.0001, 0, NaN], 1e-4); ***** assert (isequal (size (random (pd, 100, 50)), [100, 50])) ***** assert (any (random (t, 1000, 1) < 2), false); ***** assert (any (random (t, 1000, 1) > 4), false); ***** assert (std (pd), 1.2825, 1e-4); ***** assert (std (t), 0.1091, 1e-4); ***** assert (var (pd), 1.6449, 1e-4); ***** assert (var (t), 0.0119, 1e-4); ***** error ... ExtremeValueDistribution(Inf, 1) ***** error ... ExtremeValueDistribution(i, 1) ***** error ... ExtremeValueDistribution("a", 1) ***** error ... ExtremeValueDistribution([1, 2], 1) ***** error ... ExtremeValueDistribution(NaN, 1) ***** error ... ExtremeValueDistribution(1, 0) ***** error ... ExtremeValueDistribution(1, -1) ***** error ... ExtremeValueDistribution(1, Inf) ***** error ... ExtremeValueDistribution(1, i) ***** error ... ExtremeValueDistribution(1, "a") ***** error ... ExtremeValueDistribution(1, [1, 2]) ***** error ... ExtremeValueDistribution(1, NaN) ***** error ... cdf (ExtremeValueDistribution, 2, "uper") ***** error ... cdf (ExtremeValueDistribution, 2, 3) ***** shared x rand ("seed", 1); x = evrnd (1, 1, [1000, 1]); ***** error ... paramci (ExtremeValueDistribution.fit (x), "alpha") ***** error ... paramci (ExtremeValueDistribution.fit (x), "alpha", 0) ***** error ... paramci (ExtremeValueDistribution.fit (x), "alpha", 1) ***** error ... paramci (ExtremeValueDistribution.fit (x), "alpha", [0.5 2]) ***** error ... paramci (ExtremeValueDistribution.fit (x), "alpha", "") ***** error ... paramci (ExtremeValueDistribution.fit (x), "alpha", {0.05}) ***** error ... paramci (ExtremeValueDistribution.fit (x), ... "parameter", "mu", "alpha", {0.05}) ***** error ... paramci (ExtremeValueDistribution.fit (x), ... "parameter", {"mu", "sigma", "param"}) ***** error ... paramci (ExtremeValueDistribution.fit (x), "alpha", 0.01, ... "parameter", {"mu", "sigma", "param"}) ***** error ... paramci (ExtremeValueDistribution.fit (x), "parameter", "param") ***** error ... paramci (ExtremeValueDistribution.fit (x), "alpha", 0.01, ... "parameter", "param") ***** error ... paramci (ExtremeValueDistribution.fit (x), "NAME", "value") ***** error ... paramci (ExtremeValueDistribution.fit (x), "alpha", 0.01, "NAME", "value") ***** error ... paramci (ExtremeValueDistribution.fit (x), "alpha", 0.01, ... "parameter", "mu", "NAME", "value") ***** error ... plot (ExtremeValueDistribution, "Parent") ***** error ... plot (ExtremeValueDistribution, "PlotType", 12) ***** error ... plot (ExtremeValueDistribution, "PlotType", {"pdf", "cdf"}) ***** error ... plot (ExtremeValueDistribution, "PlotType", "pdfcdf") ***** error ... plot (ExtremeValueDistribution, "Discrete", "pdfcdf") ***** error ... plot (ExtremeValueDistribution, "Discrete", [1, 0]) ***** error ... plot (ExtremeValueDistribution, "Discrete", {true}) ***** error ... plot (ExtremeValueDistribution, "Parent", 12) ***** error ... plot (ExtremeValueDistribution, "Parent", "hax") ***** error ... proflik (ExtremeValueDistribution, 2) ***** error ... proflik (ExtremeValueDistribution.fit (x), 3) ***** error ... proflik (ExtremeValueDistribution.fit (x), [1, 2]) ***** error ... proflik (ExtremeValueDistribution.fit (x), {1}) ***** error ... proflik (ExtremeValueDistribution.fit (x), 1, ones (2)) ***** error ... proflik (ExtremeValueDistribution.fit (x), 1, "Display") ***** error ... proflik (ExtremeValueDistribution.fit (x), 1, "Display", 1) ***** error ... proflik (ExtremeValueDistribution.fit (x), 1, "Display", {1}) ***** error ... proflik (ExtremeValueDistribution.fit (x), 1, "Display", {"on"}) ***** error ... proflik (ExtremeValueDistribution.fit (x), 1, "Display", ["on"; "on"]) ***** error ... proflik (ExtremeValueDistribution.fit (x), 1, "Display", "onnn") ***** error ... proflik (ExtremeValueDistribution.fit (x), 1, "NAME", "on") ***** error ... proflik (ExtremeValueDistribution.fit (x), 1, {"NAME"}, "on") ***** error ... proflik (ExtremeValueDistribution.fit (x), 1, {[1 2 3 4]}, "Display", "on") ***** error ... truncate (ExtremeValueDistribution) ***** error ... truncate (ExtremeValueDistribution, 2) ***** error ... truncate (ExtremeValueDistribution, 4, 2) ***** shared pd pd = ExtremeValueDistribution(1, 1); pd(2) = ExtremeValueDistribution(1, 3); ***** error cdf (pd, 1) ***** error icdf (pd, 0.5) ***** error iqr (pd) ***** error mean (pd) ***** error median (pd) ***** error negloglik (pd) ***** error paramci (pd) ***** error pdf (pd, 1) ***** error plot (pd) ***** error proflik (pd, 2) ***** error random (pd) ***** error std (pd) ***** error ... truncate (pd, 2, 4) ***** error var (pd) 93 tests, 93 passed, 0 known failure, 0 skipped [inst/dist_obj/BirnbaumSaundersDistribution.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/dist_obj/BirnbaumSaundersDistribution.m ***** shared pd, t pd = BirnbaumSaundersDistribution; t = truncate (pd, 2, 4); ***** assert (cdf (pd, [0:5]), [0, 0.5, 0.7602, 0.8759, 0.9332, 0.9632], 1e-4); ***** assert (cdf (t, [0:5]), [0, 0, 0, 0.6687, 1, 1], 1e-4); ***** assert (cdf (pd, [1.5, 2, 3, 4, NaN]), [0.6585, 0.7602, 0.8759, 0.9332, NaN], 1e-4); ***** assert (cdf (t, [1.5, 2, 3, 4, NaN]), [0, 0, 0.6687, 1, NaN], 1e-4); ***** assert (icdf (pd, [0:0.2:1]), [0, 0.4411, 0.7767, 1.2875, 2.2673, Inf], 1e-4); ***** assert (icdf (t, [0:0.2:1]), [2, 2.2293, 2.5073, 2.8567, 3.3210, 4], 1e-4); ***** assert (icdf (pd, [-1, 0.4:0.2:1, NaN]), [NaN, 0.7767, 1.2875, 2.2673, Inf, NaN], 1e-4); ***** assert (icdf (t, [-1, 0.4:0.2:1, NaN]), [NaN, 2.5073, 2.8567, 3.3210, 4, NaN], 1e-4); ***** assert (iqr (pd), 1.4236, 1e-4); ***** assert (iqr (t), 0.8968, 1e-4); ***** assert (mean (pd), 1.5, eps); ***** assert (mean (t), 2.7723, 1e-4); ***** assert (median (pd), 1, 1e-4); ***** assert (median (t), 2.6711, 1e-4); ***** assert (pdf (pd, [0:5]), [0, 0.3989, 0.1648, 0.0788, 0.0405, 0.0216], 1e-4); ***** assert (pdf (t, [0:5]), [0, 0, 0.9528, 0.4559, 0.2340, 0], 1e-4); ***** assert (pdf (pd, [-1, 1.5, NaN]), [0, 0.2497, NaN], 1e-4); ***** assert (pdf (t, [-1, 1.5, NaN]), [0, 0, NaN], 1e-4); ***** assert (isequal (size (random (pd, 100, 50)), [100, 50])) ***** assert (any (random (t, 1000, 1) < 2), false); ***** assert (any (random (t, 1000, 1) > 4), false); ***** assert (std (pd), 1.5, eps); ***** assert (std (t), 0.5528, 1e-4); ***** assert (var (pd), 2.25, eps); ***** assert (var (t), 0.3056, 1e-4); ***** error ... BirnbaumSaundersDistribution(0, 1) ***** error ... BirnbaumSaundersDistribution(Inf, 1) ***** error ... BirnbaumSaundersDistribution(i, 1) ***** error ... BirnbaumSaundersDistribution("beta", 1) ***** error ... BirnbaumSaundersDistribution([1, 2], 1) ***** error ... BirnbaumSaundersDistribution(NaN, 1) ***** error ... BirnbaumSaundersDistribution(1, 0) ***** error ... BirnbaumSaundersDistribution(1, -1) ***** error ... BirnbaumSaundersDistribution(1, Inf) ***** error ... BirnbaumSaundersDistribution(1, i) ***** error ... BirnbaumSaundersDistribution(1, "beta") ***** error ... BirnbaumSaundersDistribution(1, [1, 2]) ***** error ... BirnbaumSaundersDistribution(1, NaN) ***** error ... cdf (BirnbaumSaundersDistribution, 2, "uper") ***** error ... cdf (BirnbaumSaundersDistribution, 2, 3) ***** shared x rand ("seed", 5); x = bisarnd (1, 1, [100, 1]); ***** error ... paramci (BirnbaumSaundersDistribution.fit (x), "alpha") ***** error ... paramci (BirnbaumSaundersDistribution.fit (x), "alpha", 0) ***** error ... paramci (BirnbaumSaundersDistribution.fit (x), "alpha", 1) ***** error ... paramci (BirnbaumSaundersDistribution.fit (x), "alpha", [0.5 2]) ***** error ... paramci (BirnbaumSaundersDistribution.fit (x), "alpha", "") ***** error ... paramci (BirnbaumSaundersDistribution.fit (x), "alpha", {0.05}) ***** error ... paramci (BirnbaumSaundersDistribution.fit (x), "parameter", ... "beta", "alpha", {0.05}) ***** error ... paramci (BirnbaumSaundersDistribution.fit (x), ... "parameter", {"beta", "gamma", "param"}) ***** error ... paramci (BirnbaumSaundersDistribution.fit (x), "alpha", 0.01, ... "parameter", {"beta", "gamma", "param"}) ***** error ... paramci (BirnbaumSaundersDistribution.fit (x), "parameter", "param") ***** error ... paramci (BirnbaumSaundersDistribution.fit (x), "alpha", 0.01, ... "parameter", "param") ***** error ... paramci (BirnbaumSaundersDistribution.fit (x), "NAME", "value") ***** error ... paramci (BirnbaumSaundersDistribution.fit (x), "alpha", 0.01, ... "NAME", "value") ***** error ... paramci (BirnbaumSaundersDistribution.fit (x), "alpha", 0.01, ... "parameter", "beta", "NAME", "value") ***** error ... plot (BirnbaumSaundersDistribution, "Parent") ***** error ... plot (BirnbaumSaundersDistribution, "PlotType", 12) ***** error ... plot (BirnbaumSaundersDistribution, "PlotType", {"pdf", "cdf"}) ***** error ... plot (BirnbaumSaundersDistribution, "PlotType", "pdfcdf") ***** error ... plot (BirnbaumSaundersDistribution, "Discrete", "pdfcdf") ***** error ... plot (BirnbaumSaundersDistribution, "Discrete", [1, 0]) ***** error ... plot (BirnbaumSaundersDistribution, "Discrete", {true}) ***** error ... plot (BirnbaumSaundersDistribution, "Parent", 12) ***** error ... plot (BirnbaumSaundersDistribution, "Parent", "hax") ***** error ... proflik (BirnbaumSaundersDistribution, 2) ***** error ... proflik (BirnbaumSaundersDistribution.fit (x), 3) ***** error ... proflik (BirnbaumSaundersDistribution.fit (x), [1, 2]) ***** error ... proflik (BirnbaumSaundersDistribution.fit (x), {1}) ***** error ... proflik (BirnbaumSaundersDistribution.fit (x), 1, ones (2)) ***** error ... proflik (BirnbaumSaundersDistribution.fit (x), 1, "Display") ***** error ... proflik (BirnbaumSaundersDistribution.fit (x), 1, "Display", 1) ***** error ... proflik (BirnbaumSaundersDistribution.fit (x), 1, "Display", {1}) ***** error ... proflik (BirnbaumSaundersDistribution.fit (x), 1, "Display", {"on"}) ***** error ... proflik (BirnbaumSaundersDistribution.fit (x), 1, "Display", ["on"; "on"]) ***** error ... proflik (BirnbaumSaundersDistribution.fit (x), 1, "Display", "onnn") ***** error ... proflik (BirnbaumSaundersDistribution.fit (x), 1, "NAME", "on") ***** error ... proflik (BirnbaumSaundersDistribution.fit (x), 1, {"NAME"}, "on") ***** error ... proflik (BirnbaumSaundersDistribution.fit (x), 1, {[1 2 3 4]}, "Display", "on") ***** error ... truncate (BirnbaumSaundersDistribution) ***** error ... truncate (BirnbaumSaundersDistribution, 2) ***** error ... truncate (BirnbaumSaundersDistribution, 4, 2) ***** shared pd pd = BirnbaumSaundersDistribution(1, 1); pd(2) = BirnbaumSaundersDistribution(1, 3); ***** error cdf (pd, 1) ***** error icdf (pd, 0.5) ***** error iqr (pd) ***** error mean (pd) ***** error median (pd) ***** error negloglik (pd) ***** error paramci (pd) ***** error pdf (pd, 1) ***** error plot (pd) ***** error proflik (pd, 2) ***** error random (pd) ***** error std (pd) ***** error ... truncate (pd, 2, 4) ***** error var (pd) 94 tests, 94 passed, 0 known failure, 0 skipped [inst/dist_obj/PiecewiseLinearDistribution.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/dist_obj/PiecewiseLinearDistribution.m ***** shared pd, t load patients [f, x] = ecdf (Weight); f = f(1:5:end); x = x(1:5:end); pd = PiecewiseLinearDistribution (x, f); t = truncate (pd, 130, 180); ***** assert (cdf (pd, [120, 130, 140, 150, 200]), [0.0767, 0.25, 0.4629, 0.5190, 0.9908], 1e-4); ***** assert (cdf (t, [120, 130, 140, 150, 200]), [0, 0, 0.4274, 0.5403, 1], 1e-4); ***** assert (cdf (pd, [100, 250, NaN]), [0, 1, NaN], 1e-4); ***** assert (cdf (t, [115, 290, NaN]), [0, 1, NaN], 1e-4); ***** assert (icdf (pd, [0:0.2:1]), [111, 127.5, 136.62, 169.67, 182.17, 202], 1e-2); ***** assert (icdf (t, [0:0.2:1]), [130, 134.15, 139.26, 162.5, 173.99, 180], 1e-2); ***** assert (icdf (pd, [-1, 0.4:0.2:1, NaN]), [NA, 136.62, 169.67, 182.17, 202, NA], 1e-2); ***** assert (icdf (t, [-1, 0.4:0.2:1, NaN]), [NA, 139.26, 162.5, 173.99, 180, NA], 1e-2); ***** assert (iqr (pd), 50.0833, 1e-4); ***** assert (iqr (t), 36.8077, 1e-4); ***** assert (mean (pd), 153.61, 1e-10); ***** assert (mean (t), 152.311, 1e-4); ***** assert (median (pd), 142, 1e-10); ***** assert (median (t), 141.9462, 1e-4); ***** assert (pdf (pd, [120, 130, 140, 150, 200]), [0.0133, 0.0240, 0.0186, 0.0024, 0.0046], 1e-4); ***** assert (pdf (t, [120, 130, 140, 150, 200]), [0, 0.0482, 0.0373, 0.0048, 0], 1e-4); ***** assert (pdf (pd, [100, 250, NaN]), [0, 0, NaN], 1e-4); ***** assert (pdf (t, [100, 250, NaN]), [0, 0, NaN], 1e-4); ***** assert (isequal (size (random (pd, 100, 50)), [100, 50])) ***** assert (any (random (t, 1000, 1) < 130), false); ***** assert (any (random (t, 1000, 1) > 180), false); ***** assert (std (pd), 26.5196, 1e-4); ***** assert (std (t), 18.2941, 1e-4); ***** assert (var (pd), 703.2879, 1e-4); ***** assert (var (t), 334.6757, 1e-4); ***** error ... PiecewiseLinearDistribution ([0, i], [0, 1]) ***** error ... PiecewiseLinearDistribution ([0, Inf], [0, 1]) ***** error ... PiecewiseLinearDistribution (["a", "c"], [0, 1]) ***** error ... PiecewiseLinearDistribution ([NaN, 1], [0, 1]) ***** error ... PiecewiseLinearDistribution ([0, 1], [0, i]) ***** error ... PiecewiseLinearDistribution ([0, 1], [0, Inf]) ***** error ... PiecewiseLinearDistribution ([0, 1], ["a", "c"]) ***** error ... PiecewiseLinearDistribution ([0, 1], [NaN, 1]) ***** error ... PiecewiseLinearDistribution ([0, 1], [0, 0.5, 1]) ***** error ... PiecewiseLinearDistribution ([0], [1]) ***** error ... PiecewiseLinearDistribution ([0, 0.5, 1], [0, 1, 1.5]) ***** error ... cdf (PiecewiseLinearDistribution, 2, "uper") ***** error ... cdf (PiecewiseLinearDistribution, 2, 3) ***** error ... plot (PiecewiseLinearDistribution, "Parent") ***** error ... plot (PiecewiseLinearDistribution, "PlotType", 12) ***** error ... plot (PiecewiseLinearDistribution, "PlotType", {"pdf", "cdf"}) ***** error ... plot (PiecewiseLinearDistribution, "PlotType", "pdfcdf") ***** error ... plot (PiecewiseLinearDistribution, "Discrete", "pdfcdf") ***** error ... plot (PiecewiseLinearDistribution, "Discrete", [1, 0]) ***** error ... plot (PiecewiseLinearDistribution, "Discrete", {true}) ***** error ... plot (PiecewiseLinearDistribution, "Parent", 12) ***** error ... plot (PiecewiseLinearDistribution, "Parent", "hax") ***** error ... truncate (PiecewiseLinearDistribution) ***** error ... truncate (PiecewiseLinearDistribution, 2) ***** error ... truncate (PiecewiseLinearDistribution, 4, 2) ***** shared pd pd = PiecewiseLinearDistribution (); pd(2) = PiecewiseLinearDistribution (); ***** error cdf (pd, 1) ***** error icdf (pd, 0.5) ***** error iqr (pd) ***** error mean (pd) ***** error median (pd) ***** error pdf (pd, 1) ***** error plot (pd) ***** error random (pd) ***** error std (pd) ***** error ... truncate (pd, 2, 4) ***** error var (pd) 61 tests, 61 passed, 0 known failure, 0 skipped [inst/dist_obj/RayleighDistribution.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/dist_obj/RayleighDistribution.m ***** shared pd, t pd = RayleighDistribution; t = truncate (pd, 2, 4); ***** assert (cdf (pd, [0:5]), [0, 0.3935, 0.8647, 0.9889, 0.9997, 1], 1e-4); ***** assert (cdf (t, [0:5]), [0, 0, 0, 0.9202, 1, 1], 1e-4); ***** assert (cdf (pd, [1.5, 2, 3, 4, NaN]), [0.6753, 0.8647, 0.9889, 0.9997, NaN], 1e-4); ***** assert (cdf (t, [1.5, 2, 3, 4, NaN]), [0, 0, 0.9202, 1, NaN], 1e-4); ***** assert (icdf (pd, [0:0.2:1]), [0, 0.6680, 1.0108, 1.3537, 1.7941, Inf], 1e-4); ***** assert (icdf (t, [0:0.2:1]), [2, 2.1083, 2.2402, 2.4135, 2.6831, 4], 1e-4); ***** assert (icdf (pd, [-1, 0.4:0.2:1, NaN]), [NaN, 1.0108, 1.3537, 1.7941, Inf, NaN], 1e-4); ***** assert (icdf (t, [-1, 0.4:0.2:1, NaN]), [NaN, 2.2402, 2.4135, 2.6831, 4, NaN], 1e-4); ***** assert (iqr (pd), 0.9066, 1e-4); ***** assert (iqr (t), 0.4609, 1e-4); ***** assert (mean (pd), 1.2533, 1e-4); ***** assert (mean (t), 2.4169, 1e-4); ***** assert (median (pd), 1.1774, 1e-4); ***** assert (median (t), 2.3198, 1e-4); ***** assert (pdf (pd, [0:5]), [0, 0.6065, 0.2707, 0.0333, 0.0013, 0], 1e-4); ***** assert (pdf (t, [0:5]), [0, 0, 2.0050, 0.2469, 0.0099, 0], 1e-4); ***** assert (pdf (pd, [-1, 1.5, NaN]), [0, 0.4870, NaN], 1e-4); ***** assert (pdf (t, [-1, 1.5, NaN]), [0, 0, NaN], 1e-4); ***** assert (isequal (size (random (pd, 100, 50)), [100, 50])) ***** assert (any (random (t, 1000, 1) < 2), false); ***** assert (any (random (t, 1000, 1) > 4), false); ***** assert (std (pd), 0.6551, 1e-4); ***** assert (std (t), 0.3591, 1e-4); ***** assert (var (pd), 0.4292, 1e-4); ***** assert (var (t), 0.1290, 1e-4); ***** error ... RayleighDistribution(0) ***** error ... RayleighDistribution(-1) ***** error ... RayleighDistribution(Inf) ***** error ... RayleighDistribution(i) ***** error ... RayleighDistribution("a") ***** error ... RayleighDistribution([1, 2]) ***** error ... RayleighDistribution(NaN) ***** error ... cdf (RayleighDistribution, 2, "uper") ***** error ... cdf (RayleighDistribution, 2, 3) ***** shared x x = raylrnd (1, [1, 100]); ***** error ... paramci (RayleighDistribution.fit (x), "alpha") ***** error ... paramci (RayleighDistribution.fit (x), "alpha", 0) ***** error ... paramci (RayleighDistribution.fit (x), "alpha", 1) ***** error ... paramci (RayleighDistribution.fit (x), "alpha", [0.5 2]) ***** error ... paramci (RayleighDistribution.fit (x), "alpha", "") ***** error ... paramci (RayleighDistribution.fit (x), "alpha", {0.05}) ***** error ... paramci (RayleighDistribution.fit (x), "parameter", "sigma", "alpha", {0.05}) ***** error ... paramci (RayleighDistribution.fit (x), "parameter", {"sigma", "param"}) ***** error ... paramci (RayleighDistribution.fit (x), "alpha", 0.01, ... "parameter", {"sigma", "param"}) ***** error ... paramci (RayleighDistribution.fit (x), "parameter", "param") ***** error ... paramci (RayleighDistribution.fit (x), "alpha", 0.01, "parameter", "param") ***** error ... paramci (RayleighDistribution.fit (x), "NAME", "value") ***** error ... paramci (RayleighDistribution.fit (x), "alpha", 0.01, "NAME", "value") ***** error ... paramci (RayleighDistribution.fit (x), "alpha", 0.01, ... "parameter", "sigma", "NAME", "value") ***** error ... plot (RayleighDistribution, "Parent") ***** error ... plot (RayleighDistribution, "PlotType", 12) ***** error ... plot (RayleighDistribution, "PlotType", {"pdf", "cdf"}) ***** error ... plot (RayleighDistribution, "PlotType", "pdfcdf") ***** error ... plot (RayleighDistribution, "Discrete", "pdfcdf") ***** error ... plot (RayleighDistribution, "Discrete", [1, 0]) ***** error ... plot (RayleighDistribution, "Discrete", {true}) ***** error ... plot (RayleighDistribution, "Parent", 12) ***** error ... plot (RayleighDistribution, "Parent", "hax") ***** error ... proflik (RayleighDistribution, 2) ***** error ... proflik (RayleighDistribution.fit (x), 3) ***** error ... proflik (RayleighDistribution.fit (x), [1, 2]) ***** error ... proflik (RayleighDistribution.fit (x), {1}) ***** error ... proflik (RayleighDistribution.fit (x), 1, ones (2)) ***** error ... proflik (RayleighDistribution.fit (x), 1, "Display") ***** error ... proflik (RayleighDistribution.fit (x), 1, "Display", 1) ***** error ... proflik (RayleighDistribution.fit (x), 1, "Display", {1}) ***** error ... proflik (RayleighDistribution.fit (x), 1, "Display", {"on"}) ***** error ... proflik (RayleighDistribution.fit (x), 1, "Display", ["on"; "on"]) ***** error ... proflik (RayleighDistribution.fit (x), 1, "Display", "onnn") ***** error ... proflik (RayleighDistribution.fit (x), 1, "NAME", "on") ***** error ... proflik (RayleighDistribution.fit (x), 1, {"NAME"}, "on") ***** error ... proflik (RayleighDistribution.fit (x), 1, {[1 2 3 4]}, "Display", "on") ***** error ... truncate (RayleighDistribution) ***** error ... truncate (RayleighDistribution, 2) ***** error ... truncate (RayleighDistribution, 4, 2) ***** shared pd pd = RayleighDistribution(1); pd(2) = RayleighDistribution(3); ***** error cdf (pd, 1) ***** error icdf (pd, 0.5) ***** error iqr (pd) ***** error mean (pd) ***** error median (pd) ***** error negloglik (pd) ***** error paramci (pd) ***** error pdf (pd, 1) ***** error plot (pd) ***** error proflik (pd, 2) ***** error random (pd) ***** error std (pd) ***** error ... truncate (pd, 2, 4) ***** error var (pd) 88 tests, 88 passed, 0 known failure, 0 skipped [inst/dist_obj/RicianDistribution.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/dist_obj/RicianDistribution.m ***** shared pd, t pd = RicianDistribution; t = truncate (pd, 2, 4); ***** assert (cdf (pd, [0:5]), [0, 0.2671, 0.7310, 0.9563, 0.9971, 0.9999], 1e-4); ***** assert (cdf (t, [0:5]), [0, 0, 0, 0.8466, 1, 1], 1e-4); ***** assert (cdf (pd, [1.5, 2, 3, 4, NaN]), [0.5120, 0.7310, 0.9563, 0.9971, NaN], 1e-4); ***** assert (cdf (t, [1.5, 2, 3, 4, NaN]), [0, 0, 0.8466, 1, NaN], 1e-4); ***** assert (icdf (pd, [0:0.2:1]), [0, 0.8501, 1.2736, 1.6863, 2.2011, Inf], 1e-4); ***** assert (icdf (t, [0:0.2:1]), [2, 2.1517, 2.3296, 2.5545, 2.8868, 4], 1e-4); ***** assert (icdf (pd, [-1, 0.4:0.2:1, NaN]), [NaN, 1.2736, 1.6863, 2.2011, Inf, NaN], 1e-4); ***** assert (icdf (t, [-1, 0.4:0.2:1, NaN]), [NaN, 2.3296, 2.5545, 2.8868, 4, NaN], 1e-4); ***** assert (iqr (pd), 1.0890, 1e-4); ***** assert (iqr (t), 0.5928, 1e-4); ***** assert (mean (pd), 1.5486, 1e-4); ***** assert (mean (t), 2.5380, 1e-4); ***** assert (median (pd), 1.4755, 1e-4); ***** assert (median (t), 2.4341, 1e-4); ***** assert (pdf (pd, [0:5]), [0, 0.4658, 0.3742, 0.0987, 0.0092, 0.0003], 1e-4); ***** assert (pdf (t, [0:5]), [0, 0, 1.4063, 0.3707, 0.0346, 0], 1e-4); ***** assert (pdf (pd, [-1, 1.5, NaN]), [0, 0.4864, NaN], 1e-4); ***** assert (pdf (t, [-1, 1.5, NaN]), [0, 0, NaN], 1e-4); ***** assert (isequal (size (random (pd, 100, 50)), [100, 50])) ***** assert (any (random (t, 1000, 1) < 2), false); ***** assert (any (random (t, 1000, 1) > 4), false); ***** assert (std (pd), 0.7758, 1e-4); ***** assert (std (t), 0.4294, 1e-4); ***** assert (var (pd), 0.6019, 1e-4); ***** assert (var (t), 0.1844, 1e-4); ***** error ... RicianDistribution(-eps, 1) ***** error ... RicianDistribution(-1, 1) ***** error ... RicianDistribution(Inf, 1) ***** error ... RicianDistribution(i, 1) ***** error ... RicianDistribution("a", 1) ***** error ... RicianDistribution([1, 2], 1) ***** error ... RicianDistribution(NaN, 1) ***** error ... RicianDistribution(1, 0) ***** error ... RicianDistribution(1, -1) ***** error ... RicianDistribution(1, Inf) ***** error ... RicianDistribution(1, i) ***** error ... RicianDistribution(1, "a") ***** error ... RicianDistribution(1, [1, 2]) ***** error ... RicianDistribution(1, NaN) ***** error ... cdf (RicianDistribution, 2, "uper") ***** error ... cdf (RicianDistribution, 2, 3) ***** shared x x = gevrnd (1, 1, 1, [1, 100]); ***** error ... paramci (RicianDistribution.fit (x), "alpha") ***** error ... paramci (RicianDistribution.fit (x), "alpha", 0) ***** error ... paramci (RicianDistribution.fit (x), "alpha", 1) ***** error ... paramci (RicianDistribution.fit (x), "alpha", [0.5 2]) ***** error ... paramci (RicianDistribution.fit (x), "alpha", "") ***** error ... paramci (RicianDistribution.fit (x), "alpha", {0.05}) ***** error ... paramci (RicianDistribution.fit (x), "parameter", "s", "alpha", {0.05}) ***** error ... paramci (RicianDistribution.fit (x), "parameter", {"s", "sigma", "param"}) ***** error ... paramci (RicianDistribution.fit (x), "alpha", 0.01, ... "parameter", {"s", "sigma", "param"}) ***** error ... paramci (RicianDistribution.fit (x), "parameter", "param") ***** error ... paramci (RicianDistribution.fit (x), "alpha", 0.01, "parameter", "param") ***** error ... paramci (RicianDistribution.fit (x), "NAME", "value") ***** error ... paramci (RicianDistribution.fit (x), "alpha", 0.01, "NAME", "value") ***** error ... paramci (RicianDistribution.fit (x), "alpha", 0.01, "parameter", "s", ... "NAME", "value") ***** error ... plot (RicianDistribution, "Parent") ***** error ... plot (RicianDistribution, "PlotType", 12) ***** error ... plot (RicianDistribution, "PlotType", {"pdf", "cdf"}) ***** error ... plot (RicianDistribution, "PlotType", "pdfcdf") ***** error ... plot (RicianDistribution, "Discrete", "pdfcdf") ***** error ... plot (RicianDistribution, "Discrete", [1, 0]) ***** error ... plot (RicianDistribution, "Discrete", {true}) ***** error ... plot (RicianDistribution, "Parent", 12) ***** error ... plot (RicianDistribution, "Parent", "hax") ***** error ... proflik (RicianDistribution, 2) ***** error ... proflik (RicianDistribution.fit (x), 3) ***** error ... proflik (RicianDistribution.fit (x), [1, 2]) ***** error ... proflik (RicianDistribution.fit (x), {1}) ***** error ... proflik (RicianDistribution.fit (x), 1, ones (2)) ***** error ... proflik (RicianDistribution.fit (x), 1, "Display") ***** error ... proflik (RicianDistribution.fit (x), 1, "Display", 1) ***** error ... proflik (RicianDistribution.fit (x), 1, "Display", {1}) ***** error ... proflik (RicianDistribution.fit (x), 1, "Display", {"on"}) ***** error ... proflik (RicianDistribution.fit (x), 1, "Display", ["on"; "on"]) ***** error ... proflik (RicianDistribution.fit (x), 1, "Display", "onnn") ***** error ... proflik (RicianDistribution.fit (x), 1, "NAME", "on") ***** error ... proflik (RicianDistribution.fit (x), 1, {"NAME"}, "on") ***** error ... proflik (RicianDistribution.fit (x), 1, {[1 2 3 4]}, "Display", "on") ***** error ... truncate (RicianDistribution) ***** error ... truncate (RicianDistribution, 2) ***** error ... truncate (RicianDistribution, 4, 2) ***** shared pd pd = RicianDistribution(1, 1); pd(2) = RicianDistribution(1, 3); ***** error cdf (pd, 1) ***** error icdf (pd, 0.5) ***** error iqr (pd) ***** error mean (pd) ***** error median (pd) ***** error negloglik (pd) ***** error paramci (pd) ***** error pdf (pd, 1) ***** error plot (pd) ***** error proflik (pd, 2) ***** error random (pd) ***** error std (pd) ***** error ... truncate (pd, 2, 4) ***** error var (pd) 95 tests, 95 passed, 0 known failure, 0 skipped [inst/dist_obj/LogisticDistribution.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/dist_obj/LogisticDistribution.m ***** shared pd, t pd = LogisticDistribution (0, 1); t = truncate (pd, 2, 4); ***** assert (cdf (pd, [0:5]), [0.5, 0.7311, 0.8808, 0.9526, 0.9820, 0.9933], 1e-4); ***** assert (cdf (t, [0:5]), [0, 0, 0, 0.7091, 1, 1], 1e-4); ***** assert (cdf (pd, [1.5, 2, 3, 4]), [0.8176, 0.8808, 0.9526, 0.9820], 1e-4); ***** assert (cdf (t, [1.5, 2, 3, 4]), [0, 0, 0.7091, 1], 1e-4); ***** assert (icdf (pd, [0:0.2:1]), [-Inf, -1.3863, -0.4055, 0.4055, 1.3863, Inf], 1e-4); ***** assert (icdf (t, [0:0.2:1]), [2, 2.2088, 2.4599, 2.7789, 3.2252, 4], 1e-4); ***** assert (icdf (pd, [-1, 0.4:0.2:1, NaN]), [NaN, -0.4055, 0.4055, 1.3863, Inf, NaN], 1e-4); ***** assert (icdf (t, [-1, 0.4:0.2:1, NaN]), [NaN, 2.4599, 2.7789, 3.2252, 4, NaN], 1e-4); ***** assert (iqr (pd), 2.1972, 1e-4); ***** assert (iqr (t), 0.8286, 1e-4); ***** assert (mean (pd), 0, 1e-4); ***** assert (mean (t), 2.7193, 1e-4); ***** assert (median (pd), 0); ***** assert (median (t), 2.6085, 1e-4); ***** assert (pdf (pd, [0:5]), [0.25, 0.1966, 0.1050, 0.0452, 0.0177, 0.0066], 1e-4); ***** assert (pdf (t, [0:5]), [0, 0, 1.0373, 0.4463, 0.1745, 0], 1e-4); ***** assert (pdf (pd, [-1, 1:4, NaN]), [0.1966, 0.1966, 0.1050, 0.0452, 0.0177, NaN], 1e-4); ***** assert (pdf (t, [-1, 1:4, NaN]), [0, 0, 1.0373, 0.4463, 0.1745, NaN], 1e-4); ***** assert (isequal (size (random (pd, 100, 50)), [100, 50])) ***** assert (any (random (t, 1000, 1) < 2), false); ***** assert (any (random (t, 1000, 1) > 4), false); ***** assert (std (pd), 1.8138, 1e-4); ***** assert (std (t), 0.5320, 1e-4); ***** assert (var (pd), 3.2899, 1e-4); ***** assert (var (t), 0.2830, 1e-4); ***** error ... LogisticDistribution(Inf, 1) ***** error ... LogisticDistribution(i, 1) ***** error ... LogisticDistribution("a", 1) ***** error ... LogisticDistribution([1, 2], 1) ***** error ... LogisticDistribution(NaN, 1) ***** error ... LogisticDistribution(1, 0) ***** error ... LogisticDistribution(1, -1) ***** error ... LogisticDistribution(1, Inf) ***** error ... LogisticDistribution(1, i) ***** error ... LogisticDistribution(1, "a") ***** error ... LogisticDistribution(1, [1, 2]) ***** error ... LogisticDistribution(1, NaN) ***** error ... cdf (LogisticDistribution, 2, "uper") ***** error ... cdf (LogisticDistribution, 2, 3) ***** shared x x = logirnd (1, 1, [1, 100]); ***** error ... paramci (LogisticDistribution.fit (x), "alpha") ***** error ... paramci (LogisticDistribution.fit (x), "alpha", 0) ***** error ... paramci (LogisticDistribution.fit (x), "alpha", 1) ***** error ... paramci (LogisticDistribution.fit (x), "alpha", [0.5 2]) ***** error ... paramci (LogisticDistribution.fit (x), "alpha", "") ***** error ... paramci (LogisticDistribution.fit (x), "alpha", {0.05}) ***** error ... paramci (LogisticDistribution.fit (x), "parameter", "mu", "alpha", {0.05}) ***** error ... paramci (LogisticDistribution.fit (x), "parameter", {"mu", "sigma", "param"}) ***** error ... paramci (LogisticDistribution.fit (x), "alpha", 0.01, ... "parameter", {"mu", "sigma", "param"}) ***** error ... paramci (LogisticDistribution.fit (x), "parameter", "param") ***** error ... paramci (LogisticDistribution.fit (x), "alpha", 0.01, "parameter", "param") ***** error ... paramci (LogisticDistribution.fit (x), "NAME", "value") ***** error ... paramci (LogisticDistribution.fit (x), "alpha", 0.01, "NAME", "value") ***** error ... paramci (LogisticDistribution.fit (x), "alpha", 0.01, "parameter", "mu", ... "NAME", "value") ***** error ... plot (LogisticDistribution, "Parent") ***** error ... plot (LogisticDistribution, "PlotType", 12) ***** error ... plot (LogisticDistribution, "PlotType", {"pdf", "cdf"}) ***** error ... plot (LogisticDistribution, "PlotType", "pdfcdf") ***** error ... plot (LogisticDistribution, "Discrete", "pdfcdf") ***** error ... plot (LogisticDistribution, "Discrete", [1, 0]) ***** error ... plot (LogisticDistribution, "Discrete", {true}) ***** error ... plot (LogisticDistribution, "Parent", 12) ***** error ... plot (LogisticDistribution, "Parent", "hax") ***** error ... proflik (LogisticDistribution, 2) ***** error ... proflik (LogisticDistribution.fit (x), 3) ***** error ... proflik (LogisticDistribution.fit (x), [1, 2]) ***** error ... proflik (LogisticDistribution.fit (x), {1}) ***** error ... proflik (LogisticDistribution.fit (x), 1, ones (2)) ***** error ... proflik (LogisticDistribution.fit (x), 1, "Display") ***** error ... proflik (LogisticDistribution.fit (x), 1, "Display", 1) ***** error ... proflik (LogisticDistribution.fit (x), 1, "Display", {1}) ***** error ... proflik (LogisticDistribution.fit (x), 1, "Display", {"on"}) ***** error ... proflik (LogisticDistribution.fit (x), 1, "Display", ["on"; "on"]) ***** error ... proflik (LogisticDistribution.fit (x), 1, "Display", "onnn") ***** error ... proflik (LogisticDistribution.fit (x), 1, "NAME", "on") ***** error ... proflik (LogisticDistribution.fit (x), 1, {"NAME"}, "on") ***** error ... proflik (LogisticDistribution.fit (x), 1, {[1 2 3 4]}, "Display", "on") ***** error ... truncate (LogisticDistribution) ***** error ... truncate (LogisticDistribution, 2) ***** error ... truncate (LogisticDistribution, 4, 2) ***** shared pd pd = LogisticDistribution(1, 1); pd(2) = LogisticDistribution(1, 3); ***** error cdf (pd, 1) ***** error icdf (pd, 0.5) ***** error iqr (pd) ***** error mean (pd) ***** error median (pd) ***** error negloglik (pd) ***** error paramci (pd) ***** error pdf (pd, 1) ***** error plot (pd) ***** error proflik (pd, 2) ***** error random (pd) ***** error std (pd) ***** error ... truncate (pd, 2, 4) ***** error var (pd) 93 tests, 93 passed, 0 known failure, 0 skipped [inst/dist_obj/BetaDistribution.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/dist_obj/BetaDistribution.m ***** shared pd, t pd = BetaDistribution; t = truncate (pd, 0.2, 0.8); ***** assert (cdf (pd, [0:0.2:1]), [0, 0.2, 0.4, 0.6, 0.8, 1], 1e-4); ***** assert (cdf (t, [0:0.2:1]), [0, 0, 0.3333, 0.6667, 1, 1], 1e-4); ***** assert (cdf (pd, [-1, 1, NaN]), [0, 1, NaN], 1e-4); ***** assert (cdf (t, [-1, 1, NaN]), [0, 1, NaN], 1e-4); ***** assert (icdf (pd, [0:0.2:1]), [0, 0.2, 0.4, 0.6, 0.8, 1], 1e-4); ***** assert (icdf (t, [0:0.2:1]), [0.2, 0.32, 0.44, 0.56, 0.68, 0.8], 1e-4); ***** assert (icdf (pd, [-1, 0.4:0.2:1, NaN]), [NaN, 0.4, 0.6, 0.8, 1, NaN], 1e-4); ***** assert (icdf (t, [-1, 0.4:0.2:1, NaN]), [NaN, 0.44, 0.56, 0.68, 0.8, NaN], 1e-4); ***** assert (iqr (pd), 0.5, 1e-4); ***** assert (iqr (t), 0.3, 1e-4); ***** assert (mean (pd), 0.5); ***** assert (mean (t), 0.5, 1e-6); ***** assert (median (pd), 0.5); ***** assert (median (t), 0.5, 1e-6); ***** assert (pdf (pd, [0:0.2:1]), [1, 1, 1, 1, 1, 1], 1e-4); ***** assert (pdf (t, [0:0.2:1]), [0, 1.6667, 1.6667, 1.6667, 1.6667, 0], 1e-4); ***** assert (pdf (pd, [-1, 1, NaN]), [0, 1, NaN], 1e-4); ***** assert (pdf (t, [-1, 1, NaN]), [0, 0, NaN], 1e-4); ***** assert (isequal (size (random (pd, 100, 50)), [100, 50])) ***** assert (any (random (t, 1000, 1) < 0.2), false); ***** assert (any (random (t, 1000, 1) > 0.8), false); ***** assert (std (pd), 0.2887, 1e-4); ***** assert (std (t), 0.1732, 1e-4); ***** assert (var (pd), 0.0833, 1e-4); ***** assert (var (t), 0.0300, 1e-4); ***** error ... BetaDistribution(0, 1) ***** error ... BetaDistribution(Inf, 1) ***** error ... BetaDistribution(i, 1) ***** error ... BetaDistribution("a", 1) ***** error ... BetaDistribution([1, 2], 1) ***** error ... BetaDistribution(NaN, 1) ***** error ... BetaDistribution(1, 0) ***** error ... BetaDistribution(1, -1) ***** error ... BetaDistribution(1, Inf) ***** error ... BetaDistribution(1, i) ***** error ... BetaDistribution(1, "a") ***** error ... BetaDistribution(1, [1, 2]) ***** error ... BetaDistribution(1, NaN) ***** error ... cdf (BetaDistribution, 2, "uper") ***** error ... cdf (BetaDistribution, 2, 3) ***** shared x randg ("seed", 1); x = betarnd (1, 1, [100, 1]); ***** error ... paramci (BetaDistribution.fit (x), "alpha") ***** error ... paramci (BetaDistribution.fit (x), "alpha", 0) ***** error ... paramci (BetaDistribution.fit (x), "alpha", 1) ***** error ... paramci (BetaDistribution.fit (x), "alpha", [0.5 2]) ***** error ... paramci (BetaDistribution.fit (x), "alpha", "") ***** error ... paramci (BetaDistribution.fit (x), "alpha", {0.05}) ***** error ... paramci (BetaDistribution.fit (x), "parameter", "a", "alpha", {0.05}) ***** error ... paramci (BetaDistribution.fit (x), "parameter", {"a", "b", "param"}) ***** error ... paramci (BetaDistribution.fit (x), "alpha", 0.01, ... "parameter", {"a", "b", "param"}) ***** error ... paramci (BetaDistribution.fit (x), "parameter", "param") ***** error ... paramci (BetaDistribution.fit (x), "alpha", 0.01, "parameter", "param") ***** error ... paramci (BetaDistribution.fit (x), "NAME", "value") ***** error ... paramci (BetaDistribution.fit (x), "alpha", 0.01, "NAME", "value") ***** error ... paramci (BetaDistribution.fit (x), "alpha", 0.01, "parameter", "a", ... "NAME", "value") ***** error ... plot (BetaDistribution, "Parent") ***** error ... plot (BetaDistribution, "PlotType", 12) ***** error ... plot (BetaDistribution, "PlotType", {"pdf", "cdf"}) ***** error ... plot (BetaDistribution, "PlotType", "pdfcdf") ***** error ... plot (BetaDistribution, "Discrete", "pdfcdf") ***** error ... plot (BetaDistribution, "Discrete", [1, 0]) ***** error ... plot (BetaDistribution, "Discrete", {true}) ***** error ... plot (BetaDistribution, "Parent", 12) ***** error ... plot (BetaDistribution, "Parent", "hax") ***** error ... proflik (BetaDistribution, 2) ***** error ... proflik (BetaDistribution.fit (x), 3) ***** error ... proflik (BetaDistribution.fit (x), [1, 2]) ***** error ... proflik (BetaDistribution.fit (x), {1}) ***** error ... proflik (BetaDistribution.fit (x), 1, ones (2)) ***** error ... proflik (BetaDistribution.fit (x), 1, "Display") ***** error ... proflik (BetaDistribution.fit (x), 1, "Display", 1) ***** error ... proflik (BetaDistribution.fit (x), 1, "Display", {1}) ***** error ... proflik (BetaDistribution.fit (x), 1, "Display", {"on"}) ***** error ... proflik (BetaDistribution.fit (x), 1, "Display", ["on"; "on"]) ***** error ... proflik (BetaDistribution.fit (x), 1, "Display", "onnn") ***** error ... proflik (BetaDistribution.fit (x), 1, "NAME", "on") ***** error ... proflik (BetaDistribution.fit (x), 1, {"NAME"}, "on") ***** error ... proflik (BetaDistribution.fit (x), 1, {[1 2 3 4]}, "Display", "on") ***** error ... truncate (BetaDistribution) ***** error ... truncate (BetaDistribution, 2) ***** error ... truncate (BetaDistribution, 4, 2) ***** shared pd pd = BetaDistribution(1, 1); pd(2) = BetaDistribution(1, 3); ***** error cdf (pd, 1) ***** error icdf (pd, 0.5) ***** error iqr (pd) ***** error mean (pd) ***** error median (pd) ***** error negloglik (pd) ***** error paramci (pd) ***** error pdf (pd, 1) ***** error plot (pd) ***** error proflik (pd, 2) ***** error random (pd) ***** error std (pd) ***** error ... truncate (pd, 2, 4) ***** error var (pd) 94 tests, 94 passed, 0 known failure, 0 skipped [inst/dist_obj/ExponentialDistribution.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/dist_obj/ExponentialDistribution.m ***** shared pd, t pd = ExponentialDistribution (1); t = truncate (pd, 2, 4); ***** assert (cdf (pd, [0:5]), [0, 0.6321, 0.8647, 0.9502, 0.9817, 0.9933], 1e-4); ***** assert (cdf (t, [0:5]), [0, 0, 0, 0.7311, 1, 1], 1e-4); ***** assert (cdf (pd, [1.5, 2, 3, 4]), [0.7769, 0.8647, 0.9502, 0.9817], 1e-4); ***** assert (cdf (t, [1.5, 2, 3, 4]), [0, 0, 0.7311, 1], 1e-4); ***** assert (icdf (pd, [0:0.2:1]), [0, 0.2231, 0.5108, 0.9163, 1.6094, Inf], 1e-4); ***** assert (icdf (t, [0:0.2:1]), [2, 2.1899, 2.4244, 2.7315, 3.1768, 4], 1e-4); ***** assert (icdf (pd, [-1, 0.4:0.2:1, NaN]), [NaN, 0.5108, 0.9163, 1.6094, Inf, NaN], 1e-4); ***** assert (icdf (t, [-1, 0.4:0.2:1, NaN]), [NaN, 2.4244, 2.7315, 3.1768, 4, NaN], 1e-4); ***** assert (iqr (pd), 1.0986, 1e-4); ***** assert (iqr (t), 0.8020, 1e-4); ***** assert (mean (pd), 1); ***** assert (mean (t), 2.6870, 1e-4); ***** assert (median (pd), 0.6931, 1e-4); ***** assert (median (t), 2.5662, 1e-4); ***** assert (pdf (pd, [0:5]), [1, 0.3679, 0.1353, 0.0498, 0.0183, 0.0067], 1e-4); ***** assert (pdf (t, [0:5]), [0, 0, 1.1565, 0.4255, 0.1565, 0], 1e-4); ***** assert (pdf (pd, [-1, 1:4, NaN]), [0, 0.3679, 0.1353, 0.0498, 0.0183, NaN], 1e-4); ***** assert (pdf (t, [-1, 1:4, NaN]), [0, 0, 1.1565, 0.4255, 0.1565, NaN], 1e-4); ***** assert (isequal (size (random (pd, 100, 50)), [100, 50])) ***** assert (any (random (t, 1000, 1) < 2), false); ***** assert (any (random (t, 1000, 1) > 4), false); ***** assert (std (pd), 1); ***** assert (std (t), 0.5253, 1e-4); ***** assert (var (pd), 1); ***** assert (var (t), 0.2759, 1e-4); ***** error ... ExponentialDistribution(0) ***** error ... ExponentialDistribution(-1) ***** error ... ExponentialDistribution(Inf) ***** error ... ExponentialDistribution(i) ***** error ... ExponentialDistribution("a") ***** error ... ExponentialDistribution([1, 2]) ***** error ... ExponentialDistribution(NaN) ***** error ... cdf (ExponentialDistribution, 2, "uper") ***** error ... cdf (ExponentialDistribution, 2, 3) ***** shared x x = exprnd (1, [100, 1]); ***** error ... paramci (ExponentialDistribution.fit (x), "alpha") ***** error ... paramci (ExponentialDistribution.fit (x), "alpha", 0) ***** error ... paramci (ExponentialDistribution.fit (x), "alpha", 1) ***** error ... paramci (ExponentialDistribution.fit (x), "alpha", [0.5 2]) ***** error ... paramci (ExponentialDistribution.fit (x), "alpha", "") ***** error ... paramci (ExponentialDistribution.fit (x), "alpha", {0.05}) ***** error ... paramci (ExponentialDistribution.fit (x), "parameter", "mu", ... "alpha", {0.05}) ***** error ... paramci (ExponentialDistribution.fit (x), "parameter", {"mu", "param"}) ***** error ... paramci (ExponentialDistribution.fit (x), "alpha", 0.01, ... "parameter", {"mu", "param"}) ***** error ... paramci (ExponentialDistribution.fit (x), "parameter", "param") ***** error ... paramci (ExponentialDistribution.fit (x), "alpha", 0.01, "parameter", "parm") ***** error ... paramci (ExponentialDistribution.fit (x), "NAME", "value") ***** error ... paramci (ExponentialDistribution.fit (x), "alpha", 0.01, "NAME", "value") ***** error ... paramci (ExponentialDistribution.fit (x), "alpha", 0.01, ... "parameter", "mu", "NAME", "value") ***** error ... plot (ExponentialDistribution, "Parent") ***** error ... plot (ExponentialDistribution, "PlotType", 12) ***** error ... plot (ExponentialDistribution, "PlotType", {"pdf", "cdf"}) ***** error ... plot (ExponentialDistribution, "PlotType", "pdfcdf") ***** error ... plot (ExponentialDistribution, "Discrete", "pdfcdf") ***** error ... plot (ExponentialDistribution, "Discrete", [1, 0]) ***** error ... plot (ExponentialDistribution, "Discrete", {true}) ***** error ... plot (ExponentialDistribution, "Parent", 12) ***** error ... plot (ExponentialDistribution, "Parent", "hax") ***** error ... proflik (ExponentialDistribution, 2) ***** error ... proflik (ExponentialDistribution.fit (x), 3) ***** error ... proflik (ExponentialDistribution.fit (x), [1, 2]) ***** error ... proflik (ExponentialDistribution.fit (x), {1}) ***** error ... proflik (ExponentialDistribution.fit (x), 1, ones (2)) ***** error ... proflik (ExponentialDistribution.fit (x), 1, "Display") ***** error ... proflik (ExponentialDistribution.fit (x), 1, "Display", 1) ***** error ... proflik (ExponentialDistribution.fit (x), 1, "Display", {1}) ***** error ... proflik (ExponentialDistribution.fit (x), 1, "Display", {"on"}) ***** error ... proflik (ExponentialDistribution.fit (x), 1, "Display", ["on"; "on"]) ***** error ... proflik (ExponentialDistribution.fit (x), 1, "Display", "onnn") ***** error ... proflik (ExponentialDistribution.fit (x), 1, "NAME", "on") ***** error ... proflik (ExponentialDistribution.fit (x), 1, {"NAME"}, "on") ***** error ... proflik (ExponentialDistribution.fit (x), 1, {[1 2 3 4]}, "Display", "on") ***** error ... truncate (ExponentialDistribution) ***** error ... truncate (ExponentialDistribution, 2) ***** error ... truncate (ExponentialDistribution, 4, 2) ***** shared pd pd = ExponentialDistribution(1); pd(2) = ExponentialDistribution(3); ***** error cdf (pd, 1) ***** error icdf (pd, 0.5) ***** error iqr (pd) ***** error mean (pd) ***** error median (pd) ***** error negloglik (pd) ***** error paramci (pd) ***** error pdf (pd, 1) ***** error plot (pd) ***** error proflik (pd, 2) ***** error random (pd) ***** error std (pd) ***** error ... truncate (pd, 2, 4) ***** error var (pd) 88 tests, 88 passed, 0 known failure, 0 skipped [inst/dist_obj/GeneralizedExtremeValueDistribution.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/dist_obj/GeneralizedExtremeValueDistribution.m ***** shared pd, t pd = GeneralizedExtremeValueDistribution; t = truncate (pd, 2, 4); ***** assert (cdf (pd, [0:5]), [0.3679, 0.6922, 0.8734, 0.9514, 0.9819, 0.9933], 1e-4); ***** assert (cdf (t, [0:5]), [0, 0, 0, 0.7195, 1, 1], 1e-4); ***** assert (cdf (pd, [1.5, 2, 3, 4]), [0.8, 0.8734, 0.9514, 0.9819], 1e-4); ***** assert (cdf (t, [1.5, 2, 3, 4]), [0, 0, 0.7195, 1], 1e-4); ***** assert (icdf (pd, [0:0.2:1]), [-Inf, -0.4759, 0.0874, 0.6717, 1.4999, Inf], 1e-4); ***** assert (icdf (t, [0:0.2:1]), [2, 2.1999, 2.4433, 2.7568, 3.2028, 4], 1e-4); ***** assert (icdf (pd, [-1, 0.4:0.2:1, NaN]), [NaN, 0.0874, 0.6717, 1.4999, Inf, NaN], 1e-4); ***** assert (icdf (t, [-1, 0.4:0.2:1, NaN]), [NaN, 2.4433, 2.7568, 3.2028, 4, NaN], 1e-4); ***** assert (iqr (pd), 1.5725, 1e-4); ***** assert (iqr (t), 0.8164, 1e-4); ***** assert (mean (pd), 0.5772, 1e-4); ***** assert (mean (t), 2.7043, 1e-4); ***** assert (median (pd), 0.3665, 1e-4); ***** assert (median (t), 2.5887, 1e-4); ***** assert (pdf (pd, [0:5]), [0.3679, 0.2546, 0.1182, 0.0474, 0.0180, 0.0067], 1e-4); ***** assert (pdf (t, [0:5]), [0, 0, 1.0902, 0.4369, 0.1659, 0], 1e-4); ***** assert (pdf (pd, [-1, 1:4, NaN]), [0.1794, 0.2546, 0.1182, 0.0474, 0.0180, NaN], 1e-4); ***** assert (pdf (t, [-1, 1:4, NaN]), [0, 0, 1.0902, 0.4369, 0.1659, NaN], 1e-4); ***** assert (isequal (size (random (pd, 100, 50)), [100, 50])) ***** assert (any (random (t, 1000, 1) < 2), false); ***** assert (any (random (t, 1000, 1) > 4), false); ***** assert (std (pd), 1.2825, 1e-4); ***** assert (std (t), 0.5289, 1e-4); ***** assert (var (pd), 1.6449, 1e-4); ***** assert (var (t), 0.2798, 1e-4); ***** error ... GeneralizedExtremeValueDistribution(Inf, 1, 1) ***** error ... GeneralizedExtremeValueDistribution(i, 1, 1) ***** error ... GeneralizedExtremeValueDistribution("a", 1, 1) ***** error ... GeneralizedExtremeValueDistribution([1, 2], 1, 1) ***** error ... GeneralizedExtremeValueDistribution(NaN, 1, 1) ***** error ... GeneralizedExtremeValueDistribution(1, 0, 1) ***** error ... GeneralizedExtremeValueDistribution(1, -1, 1) ***** error ... GeneralizedExtremeValueDistribution(1, Inf, 1) ***** error ... GeneralizedExtremeValueDistribution(1, i, 1) ***** error ... GeneralizedExtremeValueDistribution(1, "a", 1) ***** error ... GeneralizedExtremeValueDistribution(1, [1, 2], 1) ***** error ... GeneralizedExtremeValueDistribution(1, NaN, 1) ***** error ... GeneralizedExtremeValueDistribution(1, 1, Inf) ***** error ... GeneralizedExtremeValueDistribution(1, 1, i) ***** error ... GeneralizedExtremeValueDistribution(1, 1, "a") ***** error ... GeneralizedExtremeValueDistribution(1, 1, [1, 2]) ***** error ... GeneralizedExtremeValueDistribution(1, 1, NaN) ***** error ... cdf (GeneralizedExtremeValueDistribution, 2, "uper") ***** error ... cdf (GeneralizedExtremeValueDistribution, 2, 3) ***** shared x x = gevrnd (1, 1, 1, [1, 100]); ***** error ... paramci (GeneralizedExtremeValueDistribution.fit (x), "alpha") ***** error ... paramci (GeneralizedExtremeValueDistribution.fit (x), "alpha", 0) ***** error ... paramci (GeneralizedExtremeValueDistribution.fit (x), "alpha", 1) ***** error ... paramci (GeneralizedExtremeValueDistribution.fit (x), "alpha", [0.5 2]) ***** error ... paramci (GeneralizedExtremeValueDistribution.fit (x), "alpha", "") ***** error ... paramci (GeneralizedExtremeValueDistribution.fit (x), "alpha", {0.05}) ***** error ... paramci (GeneralizedExtremeValueDistribution.fit (x), ... "parameter", "sigma", "alpha", {0.05}) ***** error ... paramci (GeneralizedExtremeValueDistribution.fit (x), ... "parameter", {"k", "sigma", "mu", "param"}) ***** error ... paramci (GeneralizedExtremeValueDistribution.fit (x), "alpha", 0.01, ... "parameter", {"k", "sigma", "mu", "param"}) ***** error ... paramci (GeneralizedExtremeValueDistribution.fit (x), "parameter", "param") ***** error ... paramci (GeneralizedExtremeValueDistribution.fit (x), "alpha", 0.01, ... "parameter", "param") ***** error ... paramci (GeneralizedExtremeValueDistribution.fit (x), "NAME", "value") ***** error ... paramci (GeneralizedExtremeValueDistribution.fit (x), "alpha", 0.01, ... "NAME", "value") ***** error ... paramci (GeneralizedExtremeValueDistribution.fit (x), "alpha", 0.01, ... "parameter", "sigma", "NAME", "value") ***** error ... plot (GeneralizedExtremeValueDistribution, "Parent") ***** error ... plot (GeneralizedExtremeValueDistribution, "PlotType", 12) ***** error ... plot (GeneralizedExtremeValueDistribution, "PlotType", {"pdf", "cdf"}) ***** error ... plot (GeneralizedExtremeValueDistribution, "PlotType", "pdfcdf") ***** error ... plot (GeneralizedExtremeValueDistribution, "Discrete", "pdfcdf") ***** error ... plot (GeneralizedExtremeValueDistribution, "Discrete", [1, 0]) ***** error ... plot (GeneralizedExtremeValueDistribution, "Discrete", {true}) ***** error ... plot (GeneralizedExtremeValueDistribution, "Parent", 12) ***** error ... plot (GeneralizedExtremeValueDistribution, "Parent", "hax") ***** error ... proflik (GeneralizedExtremeValueDistribution, 2) ***** error ... proflik (GeneralizedExtremeValueDistribution.fit (x), 4) ***** error ... proflik (GeneralizedExtremeValueDistribution.fit (x), [1, 2]) ***** error ... proflik (GeneralizedExtremeValueDistribution.fit (x), {1}) ***** error ... proflik (GeneralizedExtremeValueDistribution.fit (x), 1, ones (2)) ***** error ... proflik (GeneralizedExtremeValueDistribution.fit (x), 1, "Display") ***** error ... proflik (GeneralizedExtremeValueDistribution.fit (x), 1, "Display", 1) ***** error ... proflik (GeneralizedExtremeValueDistribution.fit (x), 1, "Display", {1}) ***** error ... proflik (GeneralizedExtremeValueDistribution.fit (x), 1, "Display", {"on"}) ***** error ... proflik (GeneralizedExtremeValueDistribution.fit (x), 1, ... "Display", ["on"; "on"]) ***** error ... proflik (GeneralizedExtremeValueDistribution.fit (x), 1, "Display", "onnn") ***** error ... proflik (GeneralizedExtremeValueDistribution.fit (x), 1, "NAME", "on") ***** error ... proflik (GeneralizedExtremeValueDistribution.fit (x), 1, {"NAME"}, "on") ***** error ... proflik (GeneralizedExtremeValueDistribution.fit (x), 1, {[1 2 3 4]}, ... "Display", "on") ***** error ... truncate (GeneralizedExtremeValueDistribution) ***** error ... truncate (GeneralizedExtremeValueDistribution, 2) ***** error ... truncate (GeneralizedExtremeValueDistribution, 4, 2) ***** shared pd pd = GeneralizedExtremeValueDistribution(1, 1, 1); pd(2) = GeneralizedExtremeValueDistribution(1, 3, 1); ***** error cdf (pd, 1) ***** error icdf (pd, 0.5) ***** error iqr (pd) ***** error mean (pd) ***** error median (pd) ***** error negloglik (pd) ***** error paramci (pd) ***** error pdf (pd, 1) ***** error plot (pd) ***** error proflik (pd, 2) ***** error random (pd) ***** error std (pd) ***** error ... truncate (pd, 2, 4) ***** error var (pd) 98 tests, 98 passed, 0 known failure, 0 skipped [inst/fishertest.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/fishertest.m ***** demo ## A Fisher's exact test example x = [3, 1; 1, 3] [h, p, stats] = fishertest(x) ***** assert (fishertest ([3, 4; 5, 7]), false); ***** assert (isa (fishertest ([3, 4; 5, 7]), "logical"), true); ***** test [h, pval, stats] = fishertest ([3, 4; 5, 7]); assert (pval, 1, 1e-14); assert (stats.OddsRatio, 1.05); CI = [0.159222057151289, 6.92429189601808]; assert (stats.ConfidenceInterval, CI, 1e-14) ***** test [h, pval, stats] = fishertest ([3, 4; 5, 0]); assert (pval, 0.08080808080808080, 1e-14); assert (stats.OddsRatio, 0); assert (stats.ConfidenceInterval, [-Inf, Inf]) ***** error fishertest (); ***** error fishertest (1, 2, 3, 4, 5, 6); ***** error ... fishertest (ones (2, 2, 2)); ***** error ... fishertest ([1, 2; -3, 4]); ***** error ... fishertest ([1, 2; 3, 4+i]); ***** error ... fishertest ([1, 2; 3, 4.2]); ***** error ... fishertest ([NaN, 2; 3, 4]); ***** error ... fishertest ([1, Inf; 3, 4]); ***** error ... fishertest (ones (2) * 1e8); ***** error ... fishertest ([1, 2; 3, 4], "alpha", 0); ***** error ... fishertest ([1, 2; 3, 4], "alpha", 1.2); ***** error ... fishertest ([1, 2; 3, 4], "alpha", "val"); ***** error ... fishertest ([1, 2; 3, 4], "tail", "val"); ***** error ... fishertest ([1, 2; 3, 4], "alpha", 0.01, "tail", "val"); ***** error ... fishertest ([1, 2; 3, 4], "alpha", 0.01, "badoption", 3); 19 tests, 19 passed, 0 known failure, 0 skipped [inst/bartlett_test.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/bartlett_test.m ***** error bartlett_test () ***** error ... bartlett_test (1, 2, 3, 4); ***** error bartlett_test (randn (50, 2), 0); ***** error ... bartlett_test (randn (50, 2), [1, 2, 3]); ***** error ... bartlett_test (randn (50, 1), ones (55, 1)); ***** error ... bartlett_test (randn (50, 1), ones (50, 2)); ***** error ... bartlett_test (randn (50, 2), [], 1.2); ***** error ... bartlett_test (randn (50, 2), [], "alpha"); ***** error ... bartlett_test (randn (50, 1), [ones(25, 1); 2*ones(25, 1)], 1.2); ***** error ... bartlett_test (randn (50, 1), [ones(25, 1); 2*ones(25, 1)], "err"); ***** warning ... bartlett_test (randn (50, 1), [ones(24, 1); 2*ones(25, 1); 3]); ***** test load examgrades [h, pval, chisq, df] = bartlett_test (grades); assert (h, 1); assert (pval, 7.908647337018238e-08, 1e-14); assert (chisq, 38.73324, 1e-5); assert (df, 4); ***** test load examgrades [h, pval, chisq, df] = bartlett_test (grades(:,[2:4])); assert (h, 1); assert (pval, 0.01172, 1e-5); assert (chisq, 8.89274, 1e-5); assert (df, 2); ***** test load examgrades [h, pval, chisq, df] = bartlett_test (grades(:,[1,4])); assert (h, 0); assert (pval, 0.88118, 1e-5); assert (chisq, 0.02234, 1e-5); assert (df, 1); ***** test load examgrades grades = [grades; nan(10, 5)]; [h, pval, chisq, df] = bartlett_test (grades(:,[1,4])); assert (h, 0); assert (pval, 0.88118, 1e-5); assert (chisq, 0.02234, 1e-5); assert (df, 1); ***** test load examgrades [h, pval, chisq, df] = bartlett_test (grades(:,[2,5]), 0.01); assert (h, 0); assert (pval, 0.01791, 1e-5); assert (chisq, 5.60486, 1e-5); assert (df, 1); 16 tests, 16 passed, 0 known failure, 0 skipped [inst/ttest2.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/ttest2.m ***** test a = 1:5; b = 6:10; b(5) = NaN; [h,p,ci,stats] = ttest2 (a,b); assert (h, 1); assert (p, 0.002535996080258229, 1e-14); assert (ci, [-6.822014919225481, -2.17798508077452], 1e-14); assert (stats.tstat, -4.582575694955839, 1e-14); assert (stats.df, 7); assert (stats.sd, 1.4638501094228, 1e-13); ***** error ttest2 ([8:0.1:12], [8:0.1:12], "tail", "invalid"); ***** error ttest2 ([8:0.1:12], [8:0.1:12], "tail", 25); 3 tests, 3 passed, 0 known failure, 0 skipped [inst/gscatter.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/gscatter.m ***** demo load fisheriris; X = meas(:,3:4); cidcs = kmeans (X, 3, "Replicates", 5); gscatter (X(:,1), X(:,2), cidcs, [.75 .75 0; 0 .75 .75; .75 0 .75], "os^"); title ("Fisher's iris data"); ***** shared visibility_setting visibility_setting = get (0, "DefaultFigureVisible"); ***** test hf = figure ("visible", "off"); unwind_protect load fisheriris; X = meas(:,3:4); cidcs = kmeans (X, 3, "Replicates", 5); gscatter (X(:,1), X(:,2), cidcs, [.75 .75 0; 0 .75 .75; .75 0 .75], "os^"); title ("Fisher's iris data"); unwind_protect_cleanup close (hf); end_unwind_protect warning: legend: 'best' not yet implemented for location specifier, using 'northeast' instead ***** error gscatter (); ***** error gscatter ([1]); ***** error gscatter ([1], [2]); ***** error gscatter ('abc', [1 2 3], [1]); ***** error gscatter ([1 2 3], [1 2], [1]); ***** error gscatter ([1 2 3], 'abc', [1]); ***** error gscatter ([1 2], [1 2], [1]); ***** error gscatter ([1 2], [1 2], [1 2], 'rb', 'so', 12, 'xxx'); 9 tests, 9 passed, 0 known failure, 0 skipped [inst/hotelling_t2test2.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/hotelling_t2test2.m ***** error hotelling_t2test2 (); ***** error ... hotelling_t2test2 ([2, 3, 4, 5, 6]); ***** error ... hotelling_t2test2 (1, [2, 3, 4, 5, 6]); ***** error ... hotelling_t2test2 (ones (2,2,2), [2, 3, 4, 5, 6]); ***** error ... hotelling_t2test2 ([2, 3, 4, 5, 6], 2); ***** error ... hotelling_t2test2 ([2, 3, 4, 5, 6], ones (2,2,2)); ***** error ... hotelling_t2test2 (ones (20,2), ones (20,2), "alpha", 1); ***** error ... hotelling_t2test2 (ones (20,2), ones (20,2), "alpha", -0.2); ***** error ... hotelling_t2test2 (ones (20,2), ones (20,2), "alpha", "a"); ***** error ... hotelling_t2test2 (ones (20,2), ones (20,2), "alpha", [0.01, 0.05]); ***** error ... hotelling_t2test2 (ones (20,2), ones (20,2), "name", 0.01); ***** error ... hotelling_t2test2 (ones (20,1), ones (20,2)); ***** error ... hotelling_t2test2 (ones (20,2), ones (25,3)); ***** test randn ("seed", 1); x1 = randn (60000, 5); randn ("seed", 5); x2 = randn (30000, 5); [h, pval, stats] = hotelling_t2test2 (x1, x2); assert (h, 0); assert (stats.df1, 5); assert (stats.df2, 89994); 14 tests, 14 passed, 0 known failure, 0 skipped [inst/@cvpartition/display.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/@cvpartition/display.m ***** test C = cvpartition (ones (10, 1), "KFold", 5); s = evalc ("display (C)"); sout = "K-fold cross validation partition"; assert (strcmpi (s(1:length (sout)), sout), true); ***** test C = cvpartition (ones (10, 1), "HoldOut", 5); s = evalc ("display (C)"); sout = "HoldOut cross validation partition"; assert (strcmpi (s(1:length (sout)), sout), true); ***** test C = cvpartition (ones (10, 1), "LeaveOut", 5); s = evalc ("display (C)"); sout = "Leave-One-Out cross validation partition"; assert (strcmpi (s(1:length (sout)), sout), true); ***** test C = cvpartition (ones (10, 1), "resubstitution", 5); s = evalc ("display (C)"); sout = "Resubstitution cross validation partition"; assert (strcmpi (s(1:length (sout)), sout), true); ***** test C = cvpartition (ones (10, 1), "Given", 5); s = evalc ("display (C)"); sout = "Given cross validation partition"; assert (strcmpi (s(1:length (sout)), sout), true); ***** error display () 6 tests, 6 passed, 0 known failure, 0 skipped [inst/@cvpartition/get.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/@cvpartition/get.m ***** shared C C = cvpartition (ones (10, 1), "KFold", 5); ***** assert (get (C, "NumObservations"), 10); ***** assert (get (C, "NumTestSets"), 5); ***** assert (get (C, "TrainSize"), ones(5,1) * 8); ***** assert (get (C, "TestSize"), ones (5,1) * 2); ***** assert (get (C, "inds"), [1 1 2 2 3 3 4 4 5 5]'); ***** assert (get (C, "Type"), "kfold"); ***** error get (C, "some") ***** error get (C, 25) ***** error get (C, {25}) 9 tests, 9 passed, 0 known failure, 0 skipped [inst/@cvpartition/training.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/@cvpartition/training.m ***** shared C C = cvpartition (ones (10, 1), "KFold", 5); ***** assert (training (C, 1), logical ([0 0 1 1 1 1 1 1 1 1]')) ***** assert (training (C, 2), logical ([1 1 0 0 1 1 1 1 1 1]')) ***** assert (training (C, 3), logical ([1 1 1 1 0 0 1 1 1 1]')) ***** assert (training (C, 4), logical ([1 1 1 1 1 1 0 0 1 1]')) ***** assert (training (C, 5), logical ([1 1 1 1 1 1 1 1 0 0]')) ***** test C = set (C, "inds", [1 2 2 2 3 4 3 4 5 5]'); ***** assert (training (C), logical ([0 1 1 1 1 1 1 1 1 1]')) ***** assert (training (C, 2), logical ([1 0 0 0 1 1 1 1 1 1]')) ***** assert (training (C, 3), logical ([1 1 1 1 0 1 0 1 1 1]')) 9 tests, 9 passed, 0 known failure, 0 skipped [inst/@cvpartition/set.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/@cvpartition/set.m ***** shared C C = cvpartition (ones (10, 1), "KFold", 5); ***** test Cnew = set (C, "inds", [1 2 2 2 3 4 3 4 5 5]'); assert (get (Cnew, "inds"), [1 2 2 2 3 4 3 4 5 5]'); ***** error set (C) ***** error set (C, "NumObservations") ***** error set (C, "some", 15) ***** error set (C, 15, 15) 5 tests, 5 passed, 0 known failure, 0 skipped [inst/@cvpartition/cvpartition.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/@cvpartition/cvpartition.m ***** demo ## Partition with Fisher iris dataset (n = 150) ## Stratified by species load fisheriris y = species; ## 10-fold cross-validation partition c = cvpartition (species, 'KFold', 10) ## leave-10-out partition c1 = cvpartition (species, 'HoldOut', 10) idx1 = test (c, 2); idx2 = training (c, 2); ## another leave-10-out partition c2 = repartition (c1) ***** test C = cvpartition (ones (10, 1)); assert (isa (C, "cvpartition"), true); ***** test C = cvpartition (ones (10, 1), "KFold", 5); assert (get (C, "NumObservations"), 10); assert (get (C, "NumTestSets"), 5); assert (get (C, "TrainSize"), ones(5,1) * 8); assert (get (C, "TestSize"), ones (5,1) * 2); assert (get (C, "inds"), [1 1 2 2 3 3 4 4 5 5]'); assert (get (C, "Type"), "kfold"); ***** test C = cvpartition (ones (10, 1), "KFold", 2); assert (get (C, "NumObservations"), 10); assert (get (C, "NumTestSets"), 2); assert (get (C, "TrainSize"), [5; 5]); assert (get (C, "TestSize"), [5; 5]); assert (get (C, "inds"), [1 1 1 1 1 2 2 2 2 2]'); assert (get (C, "Type"), "kfold"); ***** test C = cvpartition (ones (10, 1), "HoldOut", 5); assert (get (C, "NumObservations"), 10); assert (get (C, "NumTestSets"), 1); assert (get (C, "TrainSize"), 5); assert (get (C, "TestSize"), 5); assert (class (get (C, "inds")), "logical"); assert (length (get (C, "inds")), 10); assert (get (C, "Type"), "holdout"); ***** test C = cvpartition ([1 2 3 4 5 6 7 8 9 10], "LeaveOut", 5); assert (get (C, "NumObservations"), 10); assert (get (C, "NumTestSets"), 10); assert (get (C, "TrainSize"), ones (10, 1)); assert (get (C, "TestSize"), ones (10, 1) * 9); assert (get (C, "inds"), []); assert (get (C, "Type"), "leaveout"); ***** test C = cvpartition ([1 2 3 4 5 6 7 8 9 10], "resubstitution", 5); assert (get (C, "NumObservations"), 10); assert (get (C, "NumTestSets"), 1); assert (get (C, "TrainSize"), 10); assert (get (C, "TestSize"), 10); assert (get (C, "inds"), []); assert (get (C, "Type"), "resubstitution"); ***** test C = cvpartition ([1 2 3 4 5 6 7 8 9 10], "Given", 2); assert (get (C, "NumObservations"), 10); assert (get (C, "NumTestSets"), 10); assert (get (C, "TrainSize"), ones (10, 1) * 9); assert (get (C, "TestSize"), ones (10, 1)); assert (get (C, "inds"), [1:10]'); assert (get (C, "Type"), "given"); ***** warning ... C = cvpartition ([1 2 3 4 5 6 7 8 9 10], "some", 2); 8 tests, 8 passed, 0 known failure, 0 skipped [inst/@cvpartition/repartition.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/@cvpartition/repartition.m ***** test C = cvpartition (ones (10, 1), "KFold", 5); Cnew = repartition (C); assert (isa (Cnew, "cvpartition"), true); ***** test C = cvpartition (ones (100, 1), "HoldOut", 5); Cnew = repartition (C); indC = get (C, "inds"); indCnew = get (Cnew, "inds"); assert (isequal (indC, indCnew), false); 2 tests, 2 passed, 0 known failure, 0 skipped [inst/@cvpartition/test.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/@cvpartition/test.m ***** shared C C = cvpartition (ones (10, 1), "KFold", 5); ***** assert (test (C, 1), logical ([1 1 0 0 0 0 0 0 0 0]')) ***** assert (test (C, 2), logical ([0 0 1 1 0 0 0 0 0 0]')) ***** assert (test (C, 3), logical ([0 0 0 0 1 1 0 0 0 0]')) ***** assert (test (C, 4), logical ([0 0 0 0 0 0 1 1 0 0]')) ***** assert (test (C, 5), logical ([0 0 0 0 0 0 0 0 1 1]')) ***** test C = set (C, "inds", [1 2 2 2 3 4 3 4 5 5]'); ***** assert (test (C), logical ([1 0 0 0 0 0 0 0 0 0]')) ***** assert (test (C, 2), logical ([0 1 1 1 0 0 0 0 0 0]')) ***** assert (test (C, 3), logical ([0 0 0 0 1 0 1 0 0 0]')) 9 tests, 9 passed, 0 known failure, 0 skipped [inst/isoutlier.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/isoutlier.m ***** demo A = [57 59 60 100 59 58 57 58 300 61 62 60 62 58 57]; TF = isoutlier (A, "mean") ***** demo ## Use a moving detection method to detect local outliers in a sine wave x = -2*pi:0.1:2*pi; A = sin(x); A(47) = 0; time = datenum (2023,1,1,0,0,0) + (1/24)*[0:length(x)-1] - 730485; TF = isoutlier (A, "movmedian", 5*(1/24), "SamplePoints", time); plot (time, A) hold on plot (time(TF), A(TF), "x") datetick ('x', 20, 'keepticks') legend ("Original Data", "Outlier Data") ***** demo ## Locate an outlier in a vector of data and visualize the outlier x = 1:10; A = [60 59 49 49 58 100 61 57 48 58]; [TF, L, U, C] = isoutlier (A); plot (x, A); hold on plot (x(TF), A(TF), "x"); xlim ([1,10]); line ([1,10], [L, L], "Linestyle", ":"); text (1.1, L-2, "Lower Threshold"); line ([1,10], [U, U], "Linestyle", ":"); text (1.1, U-2, "Upper Threshold"); line ([1,10], [C, C], "Linestyle", ":"); text (1.1, C-3, "Center Value"); legend ("Original Data", "Outlier Data"); ***** test A = [57 59 60 100 59 58 57 58 300 61 62 60 62 58 57]; assert (isoutlier (A, "mean"), logical([zeros(1,8) 1 zeros(1,6)])) assert (isoutlier (A, "median"), ... logical([zeros(1,3) 1 zeros(1,4) 1 zeros(1,6)])) ***** test A = [57 59 60 100 59 58 57 58 300 61 62 60 62 58 57]; [TF, L, U, C] = isoutlier (A, "mean"); assert (L, -109.2459044922864, 1e-12) assert (U, 264.9792378256198, 1e-12) assert (C, 77.8666666666666, 1e-12) ***** test A = [57 59 60 100 59 58 57 58 300 61 62 60 62 58 57]; [TF, L, U, C] = isoutlier (A, "median"); assert (L, 50.104386688966386, 1e-12) assert (U, 67.895613311033610, 1e-12) assert (C, 59) ***** test A = magic(5) + diag(200*ones(1,5)); T = logical (eye (5)); assert (isoutlier (A, 2), T) ***** test A = [57 59 60 100 59 58 57 58 300 61 62 60 62 58 57]; [TF, L, U, C] = isoutlier (A, "movmedian", 5); l = [54.5522, 52.8283, 54.5522, 54.5522, 54.5522, 53.5522, 53.5522, ... 53.5522, 47.6566, 56.5522, 57.5522, 56.5522, 51.1044, 52.3283, 53.5522]; u = [63.4478, 66.1717, 63.4478, 63.4478, 63.4478, 62.4478, 62.4478, ... 62.4478, 74.3434, 65.4478, 66.4478, 65.4478, 68.8956, 65.6717, 62.4478]; c = [59, 59.5, 59, 59, 59, 58, 58, 58, 61, 61, 62, 61, 60, 59, 58]; assert (L, l, 1e-4) assert (U, u, 1e-4) assert (C, c) ***** test A = [57 59 60 100 59 58 57 58 300 61 62 60 62 58 57]; [TF, L, U, C] = isoutlier (A, "movmedian", 5, "SamplePoints", [1:15]); l = [54.5522, 52.8283, 54.5522, 54.5522, 54.5522, 53.5522, 53.5522, ... 53.5522, 47.6566, 56.5522, 57.5522, 56.5522, 51.1044, 52.3283, 53.5522]; u = [63.4478, 66.1717, 63.4478, 63.4478, 63.4478, 62.4478, 62.4478, ... 62.4478, 74.3434, 65.4478, 66.4478, 65.4478, 68.8956, 65.6717, 62.4478]; c = [59, 59.5, 59, 59, 59, 58, 58, 58, 61, 61, 62, 61, 60, 59, 58]; assert (L, l, 1e-4) assert (U, u, 1e-4) assert (C, c) ***** test A = [57 59 60 100 59 58 57 58 300 61 62 60 62 58 57]; [TF, L, U, C] = isoutlier (A, "movmean", 5); l = [54.0841, 6.8872, 11.5608, 12.1518, 11.0210, 10.0112, -218.2840, ... -217.2375, -215.1239, -213.4890, -211.3264, 55.5800, 52.9589, ... 52.5979, 51.0627]; u = [63.2492, 131.1128, 122.4392, 122.2482, 122.5790, 122.7888, 431.0840, ... 430.8375, 430.3239, 429.8890, 429.3264, 65.6200, 66.6411, 65.9021, ... 66.9373]; c = [58.6667, 69, 67, 67.2, 66.8, 66.4, 106.4, 106.8, 107.6, 108.2, 109, ... 60.6, 59.8, 59.25, 59]; assert (L, l, 1e-4) assert (U, u, 1e-4) assert (C, c, 1e-4) ***** test A = [57 59 60 100 59 58 57 58 300 61 62 60 62 58 57]; [TF, L, U, C] = isoutlier (A, "movmean", 5, "SamplePoints", [1:15]); l = [54.0841, 6.8872, 11.5608, 12.1518, 11.0210, 10.0112, -218.2840, ... -217.2375, -215.1239, -213.4890, -211.3264, 55.5800, 52.9589, ... 52.5979, 51.0627]; u = [63.2492, 131.1128, 122.4392, 122.2482, 122.5790, 122.7888, 431.0840, ... 430.8375, 430.3239, 429.8890, 429.3264, 65.6200, 66.6411, 65.9021, ... 66.9373]; c = [58.6667, 69, 67, 67.2, 66.8, 66.4, 106.4, 106.8, 107.6, 108.2, 109, ... 60.6, 59.8, 59.25, 59]; assert (L, l, 1e-4) assert (U, u, 1e-4) assert (C, c, 1e-4) ***** test A = [57 59 60 100 59 58 57 58 300 61 62 60 62 58 57]; [TF, L, U, C] = isoutlier (A, "gesd"); assert (TF, logical ([0 0 0 1 0 0 0 0 1 0 0 0 0 0 0])) assert (L, 34.235977035439944, 1e-12) assert (U, 89.764022964560060, 1e-12) assert (C, 62) ***** test A = [57 59 60 100 59 58 57 58 300 61 62 60 62 58 57]; [TF, L, U, C] = isoutlier (A, "gesd", "ThresholdFactor", 0.01); assert (TF, logical ([0 0 0 1 0 0 0 0 1 0 0 0 0 0 0])) assert (L, 31.489256770616173, 1e-12) assert (U, 92.510743229383820, 1e-12) assert (C, 62) ***** test A = [57 59 60 100 59 58 57 58 300 61 62 60 62 58 57]; [TF, L, U, C] = isoutlier (A, "gesd", "ThresholdFactor", 5e-10); assert (TF, logical ([0 0 0 0 0 0 0 0 1 0 0 0 0 0 0])) assert (L, 23.976664158788935, 1e-12) assert (U, 100.02333584121110, 1e-12) assert (C, 62) ***** test A = [57 59 60 100 59 58 57 58 300 61 62 60 62 58 57]; [TF, L, U, C] = isoutlier (A, "grubbs"); assert (TF, logical ([0 0 0 1 0 0 0 0 1 0 0 0 0 0 0])) assert (L, 54.642809574646606, 1e-12) assert (U, 63.511036579199555, 1e-12) assert (C, 59.076923076923080, 1e-12) ***** test A = [57 59 60 100 59 58 57 58 300 61 62 60 62 58 57]; [TF, L, U, C] = isoutlier (A, "grubbs", "ThresholdFactor", 0.01); assert (TF, logical ([0 0 0 1 0 0 0 0 1 0 0 0 0 0 0])) assert (L, 54.216083184201850, 1e-12) assert (U, 63.937762969644310, 1e-12) assert (C, 59.076923076923080, 1e-12) ***** test A = [57 59 60 100 59 58 57 58 300 61 62 60 62 58 57]; [TF, L, U, C] = isoutlier (A, "percentiles", [10 90]); assert (TF, logical ([0 0 0 0 0 0 0 0 1 0 0 0 0 0 0])) assert (L, 57) assert (U, 100) assert (C, 78.5) ***** test A = [57 59 60 100 59 58 57 58 300 61 62 60 62 58 57]; [TF, L, U, C] = isoutlier (A, "percentiles", [20 80]); assert (TF, logical ([1 0 0 1 0 0 1 0 1 0 0 0 0 0 1])) assert (L, 57.5) assert (U, 62) assert (C, 59.75) ***** shared A A = [57 59 60 100 59 58 57 58 300 61 62 60 62 58 57]; ***** error ... isoutlier (A, "movmedian", 0); ***** error ... isoutlier (A, "movmedian", []); ***** error ... isoutlier (A, "movmedian", [2 3 4]); ***** error ... isoutlier (A, "movmedian", 1.4); ***** error ... isoutlier (A, "movmedian", [0 1]); ***** error ... isoutlier (A, "movmedian", [2 -1]); ***** error ... isoutlier (A, "movmedian", {2 3}); ***** error ... isoutlier (A, "movmedian", "char"); ***** error ... isoutlier (A, "movmean", 0); ***** error ... isoutlier (A, "movmean", []); ***** error ... isoutlier (A, "movmean", [2 3 4]); ***** error ... isoutlier (A, "movmean", 1.4); ***** error ... isoutlier (A, "movmean", [0 1]); ***** error ... isoutlier (A, "movmean", [2 -1]); ***** error ... isoutlier (A, "movmean", {2 3}); ***** error ... isoutlier (A, "movmean", "char"); ***** error ... isoutlier (A, "percentiles", [-1 90]); ***** error ... isoutlier (A, "percentiles", [10 -90]); ***** error ... isoutlier (A, "percentiles", [90]); ***** error ... isoutlier (A, "percentiles", [90 20]); ***** error ... isoutlier (A, "percentiles", [90 20]); ***** error ... isoutlier (A, "percentiles", [10 20 90]); ***** error ... isoutlier (A, "percentiles", {10 90}); ***** error ... isoutlier (A, "percentiles", "char"); ***** error ... isoutlier (A, "movmean", 5, "SamplePoints", ones(3,15)); ***** error ... isoutlier (A, "movmean", 5, "SamplePoints", 15); ***** error ... isoutlier (A, "movmean", 5, "SamplePoints", [1,1:14]); ***** error ... isoutlier (A, "movmean", 5, "SamplePoints", [2,1,3:15]); ***** error ... isoutlier (A, "movmean", 5, "SamplePoints", [1:14]); ***** error ... isoutlier (A, "movmean", 5, "ThresholdFactor", [1:14]); ***** error ... isoutlier (A, "movmean", 5, "ThresholdFactor", -1); ***** error ... isoutlier (A, "gesd", "ThresholdFactor", 3); ***** error ... isoutlier (A, "grubbs", "ThresholdFactor", 3); ***** error ... isoutlier (A, "movmean", 5, "MaxNumOutliers", [1:14]); ***** error ... isoutlier (A, "movmean", 5, "MaxNumOutliers", -1); ***** error ... isoutlier (A, "movmean", 5, "MaxNumOutliers", 0); ***** error ... isoutlier (A, "movmean", 5, "MaxNumOutliers", 1.5); ***** error ... isoutlier (A, {"movmean"}, 5, "SamplePoints", [1:15]); ***** error isoutlier (A, {1}); ***** error isoutlier (A, true); ***** error isoutlier (A, false); ***** error isoutlier (A, 0); ***** error isoutlier (A, [1 2]); ***** error isoutlier (A, -2); 59 tests, 59 passed, 0 known failure, 0 skipped [inst/Classification/ConfusionMatrixChart.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/Classification/ConfusionMatrixChart.m ***** demo ## Create a simple ConfusionMatrixChart Object cm = ConfusionMatrixChart (gca, [1 2; 1 2], {"A","B"}, {"XLabel","LABEL A"}) NormalizedValues = cm.NormalizedValues ClassLabels = cm.ClassLabels ***** test hf = figure ("visible", "off"); unwind_protect cm = ConfusionMatrixChart (gca, [1 2; 1 2], {"A","B"}, {"XLabel","LABEL A"}); assert (isa (cm, "ConfusionMatrixChart"), true); unwind_protect_cleanup close (hf); end_unwind_protect 1 test, 1 passed, 0 known failure, 0 skipped [inst/Classification/ClassificationKNN.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/Classification/ClassificationKNN.m ***** demo ## Create a k-nearest neighbor classifier for Fisher's iris data with k = 5. ## Evaluate some model predictions on new data. load fisheriris x = meas; y = species; xc = [min(x); mean(x); max(x)]; obj = fitcknn (x, y, "NumNeighbors", 5, "Standardize", 1); [label, score, cost] = predict (obj, xc) ***** demo ## Train a k-nearest neighbor classifier for k = 10 ## and plot the decision boundaries. load fisheriris idx = ! strcmp (species, "setosa"); X = meas(idx,3:4); Y = cast (strcmpi (species(idx), "virginica"), "double"); obj = fitcknn (X, Y, "Standardize", 1, "NumNeighbors", 10, "NSMethod", "exhaustive") x1 = [min(X(:,1)):0.03:max(X(:,1))]; x2 = [min(X(:,2)):0.02:max(X(:,2))]; [x1G, x2G] = meshgrid (x1, x2); XGrid = [x1G(:), x2G(:)]; pred = predict (obj, XGrid); gidx = logical (str2num (cell2mat (pred))); figure scatter (XGrid(gidx,1), XGrid(gidx,2), "markerfacecolor", "magenta"); hold on scatter (XGrid(!gidx,1), XGrid(!gidx,2), "markerfacecolor", "red"); plot (X(Y == 0, 1), X(Y == 0, 2), "ko", X(Y == 1, 1), X(Y == 1, 2), "kx"); xlabel ("Petal length (cm)"); ylabel ("Petal width (cm)"); title ("5-Nearest Neighbor Classifier Decision Boundary"); legend ({"Versicolor Region", "Virginica Region", ... "Sampled Versicolor", "Sampled Virginica"}, ... "location", "northwest") axis tight hold off ***** test x = [1, 2, 3; 4, 5, 6; 7, 8, 9; 3, 2, 1]; y = ["a"; "a"; "b"; "b"]; a = ClassificationKNN (x, y); assert (class (a), "ClassificationKNN"); assert ({a.X, a.Y, a.NumNeighbors}, {x, y, 1}) assert ({a.NSMethod, a.Distance}, {"kdtree", "euclidean"}) assert ({a.BucketSize}, {50}) ***** test x = [1, 2, 3; 4, 5, 6; 7, 8, 9; 3, 2, 1]; y = ["a"; "a"; "b"; "b"]; a = ClassificationKNN (x, y, "NSMethod", "exhaustive"); assert (class (a), "ClassificationKNN"); assert ({a.X, a.Y, a.NumNeighbors}, {x, y, 1}) assert ({a.NSMethod, a.Distance}, {"exhaustive", "euclidean"}) assert ({a.BucketSize}, {50}) ***** test x = [1, 2, 3; 4, 5, 6; 7, 8, 9; 3, 2, 1]; y = ["a"; "a"; "b"; "b"]; k = 10; a = ClassificationKNN (x, y, "NumNeighbors" ,k); assert (class (a), "ClassificationKNN"); assert ({a.X, a.Y, a.NumNeighbors}, {x, y, 10}) assert ({a.NSMethod, a.Distance}, {"kdtree", "euclidean"}) assert ({a.BucketSize}, {50}) ***** test x = ones (4, 11); y = ["a"; "a"; "b"; "b"]; k = 10; a = ClassificationKNN (x, y, "NumNeighbors" ,k); assert (class (a), "ClassificationKNN"); assert ({a.X, a.Y, a.NumNeighbors}, {x, y, 10}) assert ({a.NSMethod, a.Distance}, {"exhaustive", "euclidean"}) assert ({a.BucketSize}, {50}) ***** test x = [1, 2, 3; 4, 5, 6; 7, 8, 9; 3, 2, 1]; y = ["a"; "a"; "b"; "b"]; k = 10; a = ClassificationKNN (x, y, "NumNeighbors" ,k, "NSMethod", "exhaustive"); assert (class (a), "ClassificationKNN"); assert ({a.X, a.Y, a.NumNeighbors}, {x, y, 10}) assert ({a.NSMethod, a.Distance}, {"exhaustive", "euclidean"}) assert ({a.BucketSize}, {50}) ***** test x = [1, 2, 3; 4, 5, 6; 7, 8, 9; 3, 2, 1]; y = ["a"; "a"; "b"; "b"]; k = 10; a = ClassificationKNN (x, y, "NumNeighbors" ,k, "Distance", "hamming"); assert (class (a), "ClassificationKNN"); assert ({a.X, a.Y, a.NumNeighbors}, {x, y, 10}) assert ({a.NSMethod, a.Distance}, {"exhaustive", "hamming"}) assert ({a.BucketSize}, {50}) ***** test x = [1, 2, 3; 4, 5, 6; 7, 8, 9; 3, 2, 1]; y = ["a"; "a"; "b"; "b"]; weights = ones (4,1); a = ClassificationKNN (x, y, "Standardize", 1); assert (class (a), "ClassificationKNN"); assert ({a.X, a.Y, a.NumNeighbors}, {x, y, 1}) assert ({a.NSMethod, a.Distance}, {"kdtree", "euclidean"}) assert ({a.Standardize}, {true}) assert ({a.Sigma}, {std(x, [], 1)}) assert ({a.Mu}, {[3.75, 4.25, 4.75]}) ***** test x = [1, 2, 3; 4, 5, 6; 7, 8, 9; 3, 2, 1]; y = ["a"; "a"; "b"; "b"]; weights = ones (4,1); a = ClassificationKNN (x, y, "Standardize", false); assert (class (a), "ClassificationKNN"); assert ({a.X, a.Y, a.NumNeighbors}, {x, y, 1}) assert ({a.NSMethod, a.Distance}, {"kdtree", "euclidean"}) assert ({a.Standardize}, {false}) assert ({a.Sigma}, {[]}) assert ({a.Mu}, {[]}) ***** test x = [1, 2, 3; 4, 5, 6; 7, 8, 9; 3, 2, 1]; y = ["a"; "a"; "b"; "b"]; s = ones (1, 3); a = ClassificationKNN (x, y, "Scale" , s, "Distance", "seuclidean"); assert (class (a), "ClassificationKNN"); assert ({a.DistParameter}, {s}) assert ({a.NSMethod, a.Distance}, {"exhaustive", "seuclidean"}) assert ({a.BucketSize}, {50}) ***** test x = [1, 2, 3; 4, 5, 6; 7, 8, 9; 3, 2, 1]; y = ["a"; "a"; "b"; "b"]; a = ClassificationKNN (x, y, "Exponent" , 5, "Distance", "minkowski"); assert (class (a), "ClassificationKNN"); assert (a.DistParameter, 5) assert ({a.NSMethod, a.Distance}, {"kdtree", "minkowski"}) ***** test x = [1, 2, 3; 4, 5, 6; 7, 8, 9; 3, 2, 1]; y = ["a"; "a"; "b"; "b"]; a = ClassificationKNN (x, y, "Exponent" , 5, "Distance", "minkowski", ... "NSMethod", "exhaustive"); assert (class (a), "ClassificationKNN"); assert (a.DistParameter, 5) assert ({a.NSMethod, a.Distance}, {"exhaustive", "minkowski"}) ***** test x = [1, 2, 3; 4, 5, 6; 7, 8, 9; 3, 2, 1]; y = ["a"; "a"; "b"; "b"]; a = ClassificationKNN (x, y, "BucketSize" , 20, "distance", "mahalanobis"); assert (class (a), "ClassificationKNN"); assert ({a.NSMethod, a.Distance}, {"exhaustive", "mahalanobis"}) assert ({a.BucketSize}, {20}) ***** test x = [1, 2, 3; 4, 5, 6; 7, 8, 9; 3, 2, 1]; y = ["a"; "a"; "b"; "b"]; a = ClassificationKNN (x, y, "IncludeTies", true); assert (class (a), "ClassificationKNN"); assert (a.IncludeTies, true); assert ({a.NSMethod, a.Distance}, {"kdtree", "euclidean"}) ***** test x = [1, 2, 3; 4, 5, 6; 7, 8, 9; 3, 2, 1]; y = ["a"; "a"; "b"; "b"]; a = ClassificationKNN (x, y); assert (class (a), "ClassificationKNN"); assert (a.IncludeTies, false); assert ({a.NSMethod, a.Distance}, {"kdtree", "euclidean"}) ***** test x = [1, 2, 3; 4, 5, 6; 7, 8, 9; 3, 2, 1]; y = ["a"; "a"; "b"; "b"]; a = ClassificationKNN (x, y); assert (class (a), "ClassificationKNN") assert (a.Prior, [0.5; 0.5]) assert ({a.NSMethod, a.Distance}, {"kdtree", "euclidean"}) assert ({a.BucketSize}, {50}) ***** test x = [1, 2, 3; 4, 5, 6; 7, 8, 9; 3, 2, 1]; y = ["a"; "a"; "b"; "b"]; prior = [0.5; 0.5]; a = ClassificationKNN (x, y, "Prior", "empirical"); assert (class (a), "ClassificationKNN") assert (a.Prior, prior) assert ({a.NSMethod, a.Distance}, {"kdtree", "euclidean"}) assert ({a.BucketSize}, {50}) ***** test x = [1, 2, 3; 4, 5, 6; 7, 8, 9; 3, 2, 1]; y = ["a"; "a"; "a"; "b"]; prior = [0.75; 0.25]; a = ClassificationKNN (x, y, "Prior", "empirical"); assert (class (a), "ClassificationKNN") assert (a.Prior, prior) assert ({a.NSMethod, a.Distance}, {"kdtree", "euclidean"}) assert ({a.BucketSize}, {50}) ***** test x = [1, 2, 3; 4, 5, 6; 7, 8, 9; 3, 2, 1]; y = ["a"; "a"; "a"; "b"]; prior = [0.5; 0.5]; a = ClassificationKNN (x, y, "Prior", "uniform"); assert (class (a), "ClassificationKNN") assert (a.Prior, prior) assert ({a.NSMethod, a.Distance}, {"kdtree", "euclidean"}) assert ({a.BucketSize}, {50}) ***** test x = [1, 2, 3; 4, 5, 6; 7, 8, 9; 3, 2, 1]; y = ["a"; "a"; "b"; "b"]; cost = eye (2); a = ClassificationKNN (x, y, "Cost", cost); assert (class (a), "ClassificationKNN") assert (a.Cost, [1, 0; 0, 1]) assert ({a.NSMethod, a.Distance}, {"kdtree", "euclidean"}) assert ({a.BucketSize}, {50}) ***** test x = [1, 2, 3; 4, 5, 6; 7, 8, 9; 3, 2, 1]; y = ["a"; "a"; "b"; "b"]; cost = eye (2); a = ClassificationKNN (x, y, "Cost", cost, "Distance", "hamming" ); assert (class (a), "ClassificationKNN") assert (a.Cost, [1, 0; 0, 1]) assert ({a.NSMethod, a.Distance}, {"exhaustive", "hamming"}) assert ({a.BucketSize}, {50}) ***** error ClassificationKNN () ***** error ... ClassificationKNN (ones(4, 1)) ***** error ... ClassificationKNN (ones (4,2), ones (1,4)) ***** error ... ClassificationKNN (ones (5,3), ones (5,1), "standardize", "a") ***** error ... ClassificationKNN (ones (5,2), ones (5,1), "scale", [1 1], "standardize", true) ***** error ... ClassificationKNN (ones (5,2), ones (5,1), "PredictorNames", ["A"]) ***** error ... ClassificationKNN (ones (5,2), ones (5,1), "PredictorNames", "A") ***** error ... ClassificationKNN (ones (5,2), ones (5,1), "PredictorNames", {"A", "B", "C"}) ***** error ... ClassificationKNN (ones (5,2), ones (5,1), "ResponseName", {"Y"}) ***** error ... ClassificationKNN (ones (5,2), ones (5,1), "ResponseName", 1) ***** error ... ClassificationKNN (ones (5,2), ones (5,1), "ClassNames", 1) ***** error ... ClassificationKNN (ones (5,2), ones (5,1), "ClassNames", ["1"]) ***** error ... ClassificationKNN (ones (5,2), ones (5,1), "ClassNames", {"1", "2"}) ***** error ... ClassificationKNN (ones (5,2), ones (5,1), "BreakTies", 1) ***** error ... ClassificationKNN (ones (5,2), ones (5,1), "BreakTies", {"1"}) ***** error ... ClassificationKNN (ones (5,2), ones (5,1), "BreakTies", "some") ***** error ... ClassificationKNN (ones (5,2), ones (5,1), "Prior", {"1", "2"}) ***** error ... ClassificationKNN (ones (5,2), ones (5,1), "Cost", [1, 2]) ***** error ... ClassificationKNN (ones (5,2), ones (5,1), "Cost", "string") ***** error ... ClassificationKNN (ones (5,2), ones (5,1), "Cost", {eye(2)}) ***** error ... ClassificationKNN (ones (5,2), ones (5,1), "NumNeighbors", 0) ***** error ... ClassificationKNN (ones (5,2), ones (5,1), "NumNeighbors", 15.2) ***** error ... ClassificationKNN (ones (5,2), ones (5,1), "NumNeighbors", "asd") ***** error ... ClassificationKNN (ones (5,2), ones (5,1), "Distance", "somemetric") ***** error ... ClassificationKNN (ones (5,2), ones (5,1), "Distance", ... @(v,m)sqrt(repmat(v,rows(m),1)-m,2)) ***** error ... ClassificationKNN (ones (5,2), ones (5,1), "Distance", ... @(v,m)sqrt(sum(sumsq(repmat(v,rows(m),1)-m,2)))) ***** error ... ClassificationKNN (ones (5,2), ones (5,1), "Distance", [1 2 3]) ***** error ... ClassificationKNN (ones (5,2), ones (5,1), "Distance", {"mahalanobis"}) ***** error ... ClassificationKNN (ones (5,2), ones (5,1), "Distance", logical (5)) ***** error ... ClassificationKNN (ones (5,2), ones (5,1), "DistanceWeight", @(x)sum(x)) ***** error ... ClassificationKNN (ones (5,2), ones (5,1), "DistanceWeight", "text") ***** error ... ClassificationKNN (ones (5,2), ones (5,1), "DistanceWeight", [1 2 3]) ***** error ... ClassificationKNN (ones (5,2), ones (5,1), "Scale", "scale") ***** error ... ClassificationKNN (ones (5,2), ones (5,1), "Scale", {[1 2 3]}) ***** error ... ClassificationKNN (ones (5,2), ones (5,1), "standardize", true, "scale", [1 1]) ***** error ... ClassificationKNN (ones (5,2), ones (5,1), "Cov", ones (2), "Distance", "mahalanobis") ***** error ... ClassificationKNN (ones (5,2), ones (5,1), "scale", [1 1], "Cov", ones (2)) ***** error ... ClassificationKNN (ones (5,2), ones (5,1), "Exponent", 12.5) ***** error ... ClassificationKNN (ones (5,2), ones (5,1), "Exponent", -3) ***** error ... ClassificationKNN (ones (5,2), ones (5,1), "Exponent", "three") ***** error ... ClassificationKNN (ones (5,2), ones (5,1), "Exponent", {3}) ***** error ... ClassificationKNN (ones (5,2), ones (5,1), "NSMethod", {"kdtree"}) ***** error ... ClassificationKNN (ones (5,2), ones (5,1), "NSMethod", 3) ***** error ... ClassificationKNN (ones (5,2), ones (5,1), "NSMethod", "some") ***** error ... ClassificationKNN (ones (5,2), ones (5,1), "IncludeTies", "some") ***** error ... ClassificationKNN (ones (5,2), ones (5,1), "BucketSize", 42.5) ***** error ... ClassificationKNN (ones (5,2), ones (5,1), "BucketSize", -50) ***** error ... ClassificationKNN (ones (5,2), ones (5,1), "BucketSize", "some") ***** error ... ClassificationKNN (ones (5,2), ones (5,1), "BucketSize", {50}) ***** error ... ClassificationKNN (ones (5,2), ones (5,1), "some", "some") ***** error ... ClassificationKNN ([1;2;3;'a';4], ones (5,1)) ***** error ... ClassificationKNN ([1;2;3;Inf;4], ones (5,1)) ***** error ... ClassificationKNN (ones (5,2), ones (5,1), "Prior", [1 2]) ***** error ... ClassificationKNN (ones (5,2), ones (5,1), "Cost", [1 2; 1 3]) ***** error ... ClassificationKNN (ones (5,2), ones (5,1), "Scale", [1 1]) ***** error ... ClassificationKNN (ones (5,2), ones (5,1), "Scale", [1 1 1], "Distance", "seuclidean") ***** error ... ClassificationKNN (ones (5,2), ones (5,1), "Scale", [1 -1], "Distance", "seuclidean") ***** error ... ClassificationKNN (ones (5,2), ones (5,1), "Cov", eye (2)) ***** error ... ClassificationKNN (ones (5,2), ones (5,1), "Cov", eye (3), "Distance", "mahalanobis") ***** error ... ClassificationKNN (ones (5,2), ones (5,1), "Exponent", 3) ***** error ... ClassificationKNN (ones (5,2), ones (5,1), "Distance", "hamming", "NSMethod", "kdtree") ***** shared x, y load fisheriris x = meas; y = species; ***** test xc = [min(x); mean(x); max(x)]; obj = fitcknn (x, y, "NumNeighbors", 5); [l, s, c] = predict (obj, xc); assert (l, {"setosa"; "versicolor"; "virginica"}) assert (s, [1, 0, 0; 0, 1, 0; 0, 0, 1]) assert (c, [0, 1, 1; 1, 0, 1; 1, 1, 0]) ***** test xc = [min(x); mean(x); max(x)]; obj = fitcknn (x, y, "NumNeighbors", 5, "Standardize", 1); [l, s, c] = predict (obj, xc); assert (l, {"versicolor"; "versicolor"; "virginica"}) assert (s, [0.4, 0.6, 0; 0, 1, 0; 0, 0, 1]) assert (c, [0.6, 0.4, 1; 1, 0, 1; 1, 1, 0]) ***** test xc = [min(x); mean(x); max(x)]; obj = fitcknn (x, y, "NumNeighbors", 10, "distance", "mahalanobis"); [l, s, c] = predict (obj, xc); assert (s, [0.3, 0.7, 0; 0, 0.9, 0.1; 0.2, 0.2, 0.6], 1e-4) assert (c, [0.7, 0.3, 1; 1, 0.1, 0.9; 0.8, 0.8, 0.4], 1e-4) ***** test xc = [min(x); mean(x); max(x)]; obj = fitcknn (x, y, "NumNeighbors", 10, "distance", "cosine"); [l, s, c] = predict (obj, xc); assert (l, {"setosa"; "versicolor"; "virginica"}) assert (s, [1, 0, 0; 0, 1, 0; 0, 0.3, 0.7], 1e-4) assert (c, [0, 1, 1; 1, 0, 1; 1, 0.7, 0.3], 1e-4) ***** test xc = [5.2, 4.1, 1.5, 0.1; 5.1, 3.8, 1.9, 0.4; ... 5.1, 3.8, 1.5, 0.3; 4.9, 3.6, 1.4, 0.1]; obj = fitcknn (x, y, "NumNeighbors", 5); [l, s, c] = predict (obj, xc); assert (l, {"setosa"; "setosa"; "setosa"; "setosa"}) assert (s, [1, 0, 0; 1, 0, 0; 1, 0, 0; 1, 0, 0]) assert (c, [0, 1, 1; 0, 1, 1; 0, 1, 1; 0, 1, 1]) ***** test xc = [5, 3, 5, 1.45]; obj = fitcknn (x, y, "NumNeighbors", 5); [l, s, c] = predict (obj, xc); assert (l, {"versicolor"}) assert (s, [0, 0.6, 0.4], 1e-4) assert (c, [1, 0.4, 0.6], 1e-4) ***** test xc = [5, 3, 5, 1.45]; obj = fitcknn (x, y, "NumNeighbors", 10, "distance", "minkowski", "Exponent", 5); [l, s, c] = predict (obj, xc); assert (l, {"versicolor"}) assert (s, [0, 0.5, 0.5], 1e-4) assert (c, [1, 0.5, 0.5], 1e-4) ***** test xc = [5, 3, 5, 1.45]; obj = fitcknn (x, y, "NumNeighbors", 10, "distance", "jaccard"); [l, s, c] = predict (obj, xc); assert (l, {"setosa"}) assert (s, [0.9, 0.1, 0], 1e-4) assert (c, [0.1, 0.9, 1], 1e-4) ***** test xc = [5, 3, 5, 1.45]; obj = fitcknn (x, y, "NumNeighbors", 10, "distance", "mahalanobis"); [l, s, c] = predict (obj, xc); assert (l, {"versicolor"}) assert (s, [0.1000, 0.5000, 0.4000], 1e-4) assert (c, [0.9000, 0.5000, 0.6000], 1e-4) ***** test xc = [5, 3, 5, 1.45]; obj = fitcknn (x, y, "NumNeighbors", 5, "distance", "jaccard"); [l, s, c] = predict (obj, xc); assert (l, {"setosa"}) assert (s, [0.8, 0.2, 0], 1e-4) assert (c, [0.2, 0.8, 1], 1e-4) ***** test xc = [5, 3, 5, 1.45]; obj = fitcknn (x, y, "NumNeighbors", 5, "distance", "seuclidean"); [l, s, c] = predict (obj, xc); assert (l, {"versicolor"}) assert (s, [0, 1, 0], 1e-4) assert (c, [1, 0, 1], 1e-4) ***** test xc = [5, 3, 5, 1.45]; obj = fitcknn (x, y, "NumNeighbors", 10, "distance", "chebychev"); [l, s, c] = predict (obj, xc); assert (l, {"versicolor"}) assert (s, [0, 0.7, 0.3], 1e-4) assert (c, [1, 0.3, 0.7], 1e-4) ***** test xc = [5, 3, 5, 1.45]; obj = fitcknn (x, y, "NumNeighbors", 10, "distance", "cityblock"); [l, s, c] = predict (obj, xc); assert (l, {"versicolor"}) assert (s, [0, 0.6, 0.4], 1e-4) assert (c, [1, 0.4, 0.6], 1e-4) ***** test xc = [5, 3, 5, 1.45]; obj = fitcknn (x, y, "NumNeighbors", 10, "distance", "cosine"); [l, s, c] = predict (obj, xc); assert (l, {"virginica"}) assert (s, [0, 0.1, 0.9], 1e-4) assert (c, [1, 0.9, 0.1], 1e-4) ***** test xc = [5, 3, 5, 1.45]; obj = fitcknn (x, y, "NumNeighbors", 10, "distance", "correlation"); [l, s, c] = predict (obj, xc); assert (l, {"virginica"}) assert (s, [0, 0.1, 0.9], 1e-4) assert (c, [1, 0.9, 0.1], 1e-4) ***** test xc = [5, 3, 5, 1.45]; obj = fitcknn (x, y, "NumNeighbors", 30, "distance", "spearman"); [l, s, c] = predict (obj, xc); assert (l, {"versicolor"}) assert (s, [0, 1, 0], 1e-4) assert (c, [1, 0, 1], 1e-4) ***** test xc = [5, 3, 5, 1.45]; obj = fitcknn (x, y, "NumNeighbors", 30, "distance", "hamming"); [l, s, c] = predict (obj, xc); assert (l, {"setosa"}) assert (s, [0.4333, 0.3333, 0.2333], 1e-4) assert (c, [0.5667, 0.6667, 0.7667], 1e-4) ***** test xc = [5, 3, 5, 1.45]; obj = fitcknn (x, y, "NumNeighbors", 5, "distance", "hamming"); [l, s, c] = predict (obj, xc); assert (l, {"setosa"}) assert (s, [0.8, 0.2, 0], 1e-4) assert (c, [0.2, 0.8, 1], 1e-4) ***** test xc = [min(x); mean(x); max(x)]; obj = fitcknn (x, y, "NumNeighbors", 10, "distance", "correlation"); [l, s, c] = predict (obj, xc); assert (l, {"setosa"; "versicolor"; "virginica"}) assert (s, [1, 0, 0; 0, 1, 0; 0, 0.4, 0.6], 1e-4) assert (c, [0, 1, 1; 1, 0, 1; 1, 0.6, 0.4], 1e-4) ***** test xc = [min(x); mean(x); max(x)]; obj = fitcknn (x, y, "NumNeighbors", 10, "distance", "hamming"); [l, s, c] = predict (obj, xc); assert (l, {"setosa";"setosa";"setosa"}) assert (s, [0.9, 0.1, 0; 1, 0, 0; 0.5, 0, 0.5], 1e-4) assert (c, [0.1, 0.9, 1; 0, 1, 1; 0.5, 1, 0.5], 1e-4) ***** error ... predict (ClassificationKNN (ones (4,2), ones (4,1))) ***** error ... predict (ClassificationKNN (ones (4,2), ones (4,1)), []) ***** error ... predict (ClassificationKNN (ones (4,2), ones (4,1)), 1) 104 tests, 104 passed, 0 known failure, 0 skipped [inst/hmmestimate.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/hmmestimate.m ***** test sequence = [1, 2, 1, 1, 1, 2, 2, 1, 2, 3, 3, ... 3, 3, 2, 3, 1, 1, 1, 1, 3, 3, 2, 3, 1, 3]; states = [1, 1, 2, 2, 2, 1, 1, 1, 1, 1, 1, ... 1, 1, 1, 1, 2, 2, 2, 2, 1, 1, 1, 1, 1, 1]; [transprobest, outprobest] = hmmestimate (sequence, states); expectedtransprob = [0.88889, 0.11111; 0.28571, 0.71429]; expectedoutprob = [0.16667, 0.33333, 0.50000; 1.00000, 0.00000, 0.00000]; assert (transprobest, expectedtransprob, 0.001); assert (outprobest, expectedoutprob, 0.001); ***** test sequence = {"A", "B", "A", "A", "A", "B", "B", "A", "B", "C", "C", "C", ... "C", "B", "C", "A", "A", "A", "A", "C", "C", "B", "C", "A", "C"}; states = {"One", "One", "Two", "Two", "Two", "One", "One", "One", "One", ... "One", "One", "One", "One", "One", "One", "Two", "Two", "Two", ... "Two", "One", "One", "One", "One", "One", "One"}; symbols = {"A", "B", "C"}; statenames = {"One", "Two"}; [transprobest, outprobest] = hmmestimate (sequence, states, "symbols", ... symbols, "statenames", statenames); expectedtransprob = [0.88889, 0.11111; 0.28571, 0.71429]; expectedoutprob = [0.16667, 0.33333, 0.50000; 1.00000, 0.00000, 0.00000]; assert (transprobest, expectedtransprob, 0.001); assert (outprobest, expectedoutprob, 0.001); ***** test sequence = [1, 2, 1, 1, 1, 2, 2, 1, 2, 3, 3, 3, ... 3, 2, 3, 1, 1, 1, 1, 3, 3, 2, 3, 1, 3]; states = [1, 1, 2, 2, 2, 1, 1, 1, 1, 1, 1, 1, ... 1, 1, 1, 2, 2, 2, 2, 1, 1, 1, 1, 1, 1]; pseudotransitions = [8, 2; 4, 6]; pseudoemissions = [2, 4, 4; 7, 2, 1]; [transprobest, outprobest] = hmmestimate (sequence, states, ... "pseudotransitions", pseudotransitions, "pseudoemissions", pseudoemissions); expectedtransprob = [0.85714, 0.14286; 0.35294, 0.64706]; expectedoutprob = [0.178571, 0.357143, 0.464286; ... 0.823529, 0.117647, 0.058824]; assert (transprobest, expectedtransprob, 0.001); assert (outprobest, expectedoutprob, 0.001); 3 tests, 3 passed, 0 known failure, 0 skipped [inst/grpstats.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/grpstats.m ***** demo load carsmall; [m,p,g] = grpstats (Weight, Model_Year, {"mean", "predci", "gname"}) n = length(m); errorbar((1:n)',m,p(:,2)-m); set (gca, "xtick", 1:n, "xticklabel", g); title ("95% prediction intervals for mean weight by year"); ***** demo load carsmall; [m,p,g] = grpstats ([Acceleration,Weight/1000],Cylinders, ... {"mean", "meanci", "gname"}, 0.05) [c,r] = size (m); errorbar((1:c)'.*ones(c,r),m,p(:,[(1:r)])-m); set (gca, "xtick", 1:c, "xticklabel", g); title ("95% prediction intervals for mean weight by year"); ***** test load carsmall means = grpstats (Acceleration, Origin); assert (means, [14.4377; 18.0500; 15.8867; 16.3778; 16.6000; 15.5000], 0.001); ***** test load carsmall [grpMin,grpMax,grp] = grpstats (Acceleration, Origin, {"min","max","gname"}); assert (grpMin, [8.0; 15.3; 13.9; 12.2; 15.7; 15.5]); assert (grpMax, [22.2; 21.9; 18.2; 24.6; 17.5; 15.5]); ***** test load carsmall [grpMin,grpMax,grp] = grpstats (Acceleration, Origin, {"min","max","gname"}); assert (grp', {"USA", "France", "Japan", "Germany", "Sweden", "Italy"}); ***** test load carsmall [m,p,g] = grpstats ([Acceleration,Weight/1000], Cylinders, ... {"mean", "meanci", "gname"}, 0.05); assert (p(:,1), [11.17621760075134, 16.13845847655224, 16.16222663683362]', ... [1e-14, 2e-14, 1e-14]'); 4 tests, 4 passed, 0 known failure, 0 skipped [inst/kstest.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/kstest.m ***** error kstest () ***** error kstest (ones(2,4)) ***** error kstest ([2,3,5,7,3+3i]) ***** error kstest ([2,3,4,5,6],"tail") ***** error kstest ([2,3,4,5,6],"tail", "whatever") ***** error kstest ([2,3,4,5,6],"badoption", 0.51) ***** error kstest ([2,3,4,5,6],"tail", 0) ***** error kstest ([2,3,4,5,6],"alpha", 0) ***** error kstest ([2,3,4,5,6],"alpha", NaN) ***** error kstest ([NaN,NaN,NaN,NaN,NaN],"tail", "unequal") ***** error kstest ([2,3,4,5,6],"alpha", 0.05, "CDF", [2,3,4;1,3,4;1,2,1]) ***** test load examgrades [h, p] = kstest (grades(:,1)); assert (h, true); assert (p, 7.58603305206105e-107, 1e-14); ***** test load stockreturns x = stocks(:,3); [h,p,k,c] = kstest (x, "Tail", "larger"); assert (h, true); assert (p, 5.085438806199252e-05, 1e-14); assert (k, 0.2197, 1e-4); assert (c, 0.1207, 1e-4); 13 tests, 13 passed, 0 known failure, 0 skipped [inst/Regression/RegressionGAM.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/Regression/RegressionGAM.m ***** demo ## Train a RegressionGAM Model for synthetic values f1 = @(x) cos (3 * x); f2 = @(x) x .^ 3; x1 = 2 * rand (50, 1) - 1; x2 = 2 * rand (50, 1) - 1; y = f1(x1) + f2(x2); y = y + y .* 0.2 .* rand (50,1); X = [x1, x2]; a = fitrgam (X, y, "tol", 1e-3) ***** demo ## Declare two different functions f1 = @(x) cos (3 * x); f2 = @(x) x .^ 3; ## Generate 80 samples for f1 and f2 x = [-4*pi:0.1*pi:4*pi-0.1*pi]'; X1 = f1 (x); X2 = f2 (x); ## Create a synthetic response by adding noise rand ("seed", 3); Ytrue = X1 + X2; Y = Ytrue + Ytrue .* 0.2 .* rand (80,1); ## Assemble predictor data X = [X1, X2]; ## Train the GAM and test on the same data a = fitrgam (X, Y, "order", [5, 5]); [ypred, ySDsd, yInt] = predict (a, X); ## Plot the results figure [sortedY, indY] = sort (Ytrue); plot (sortedY, "r-"); xlim ([0, 80]); hold on plot (ypred(indY), "g+") plot (yInt(indY,1), "k:") plot (yInt(indY,2), "k:") xlabel ("Predictor samples"); ylabel ("Response"); title ("actual vs predicted values for function f1(x) = cos (3x) "); legend ({"Theoretical Response", "Predicted Response", "Prediction Intervals"}); ## Use 30% Holdout partitioning for training and testing data C = cvpartition (80, "HoldOut", 0.3); [ypred, ySDsd, yInt] = predict (a, X(test(C),:)); ## Plot the results figure [sortedY, indY] = sort (Ytrue(test(C))); plot (sortedY, 'r-'); xlim ([0, sum(test(C))]); hold on plot (ypred(indY), "g+") plot (yInt(indY,1),'k:') plot (yInt(indY,2),'k:') xlabel ("Predictor samples"); ylabel ("Response"); title ("actual vs predicted values for function f1(x) = cos (3x) "); legend ({"Theoretical Response", "Predicted Response", "Prediction Intervals"}); ***** test x = [1, 2, 3; 4, 5, 6; 7, 8, 9; 3, 2, 1]; y = [1; 2; 3; 4]; a = RegressionGAM (x, y); assert ({a.X, a.Y}, {x, y}) assert ({a.BaseModel.Intercept}, {2.5000}) assert ({a.Knots, a.Order, a.DoF}, {[5, 5, 5], [3, 3, 3], [8, 8, 8]}) assert ({a.NumObservations, a.NumPredictors}, {4, 3}) assert ({a.ResponseName, a.PredictorNames}, {"Y", {"x1", "x2", "x3"}}) assert ({a.Formula}, {[]}) ***** test x = [1, 2, 3, 4; 4, 5, 6, 7; 7, 8, 9, 1; 3, 2, 1, 2]; y = [1; 2; 3; 4]; pnames = {"A", "B", "C", "D"}; formula = "Y ~ A + B + C + D + A:C"; intMat = logical ([1,0,0,0;0,1,0,0;0,0,1,0;0,0,0,1;1,0,1,0]); a = RegressionGAM (x, y, "predictors", pnames, "formula", formula); assert ({a.IntMatrix}, {intMat}) assert ({a.ResponseName, a.PredictorNames}, {"Y", pnames}) assert ({a.Formula}, {formula}) ***** error RegressionGAM () ***** error RegressionGAM (ones(10,2)) ***** error ... RegressionGAM (ones(10,2), ones (5,1)) ***** error ... RegressionGAM ([1;2;3;"a";4], ones (5,1)) ***** error ... RegressionGAM (ones(10,2), ones (10,1), "some", "some") ***** error RegressionGAM (ones(10,2), ones (10,1), "formula", {"y~x1+x2"}) ***** error RegressionGAM (ones(10,2), ones (10,1), "formula", [0, 1, 0]) ***** error ... RegressionGAM (ones(10,2), ones (10,1), "formula", "something") ***** error ... RegressionGAM (ones(10,2), ones (10,1), "formula", "something~") ***** error ... RegressionGAM (ones(10,2), ones (10,1), "formula", "something~") ***** error ... RegressionGAM (ones(10,2), ones (10,1), "formula", "something~x1:") ***** error ... RegressionGAM (ones(10,2), ones (10,1), "interactions", "some") ***** error ... RegressionGAM (ones(10,2), ones (10,1), "interactions", -1) ***** error ... RegressionGAM (ones(10,2), ones (10,1), "interactions", [1 2 3 4]) ***** error ... RegressionGAM (ones(10,2), ones (10,1), "interactions", 3) ***** error ... RegressionGAM (ones(10,2), ones (10,1), "formula", "y ~ x1 + x2", "interactions", 1) ***** error ... RegressionGAM (ones(10,2), ones (10,1), "interactions", 1, "formula", "y ~ x1 + x2") ***** error ... RegressionGAM (ones(10,2), ones (10,1), "knots", "a") ***** error ... RegressionGAM (ones(10,2), ones (10,1), "order", 3, "dof", 2, "knots", 5) ***** error ... RegressionGAM (ones(10,2), ones (10,1), "dof", 'a') ***** error ... RegressionGAM (ones(10,2), ones (10,1), "knots", 5, "order", 3, "dof", 2) ***** error ... RegressionGAM (ones(10,2), ones (10,1), "order", 'a') ***** error ... RegressionGAM (ones(10,2), ones (10,1), "knots", 5, "dof", 2, "order", 2) ***** error ... RegressionGAM (ones(10,2), ones (10,1), "tol", -1) ***** error ... RegressionGAM (ones(10,2), ones (10,1), "responsename", -1) ***** error ... RegressionGAM (ones(10,2), ones (10,1), "predictors", -1) ***** error ... RegressionGAM (ones(10,2), ones (10,1), "predictors", ['a','b','c']) ***** error ... RegressionGAM (ones(10,2), ones (10,1), "predictors", {'a','b','c'}) ***** error ... predict (RegressionGAM (ones(10,1), ones(10,1))) ***** error ... predict (RegressionGAM (ones(10,1), ones(10,1)), []) ***** error ... predict (RegressionGAM(ones(10,2), ones(10,1)), 2) ***** error ... predict (RegressionGAM(ones(10,2), ones(10,1)), ones (10,2), "some", "some") ***** error ... predict (RegressionGAM(ones(10,2), ones(10,1)), ones (10,2), "includeinteractions", "some") ***** error ... predict (RegressionGAM(ones(10,2), ones(10,1)), ones (10,2), "includeinteractions", 5) ***** error ... predict (RegressionGAM(ones(10,2), ones(10,1)), ones (10,2), "alpha", 5) ***** error ... predict (RegressionGAM(ones(10,2), ones(10,1)), ones (10,2), "alpha", -1) ***** error ... predict (RegressionGAM(ones(10,2), ones(10,1)), ones (10,2), "alpha", 'a') 39 tests, 39 passed, 0 known failure, 0 skipped [inst/anova2.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/anova2.m ***** demo # Factorial (Crossed) Two-way ANOVA with Interaction popcorn = [5.5, 4.5, 3.5; 5.5, 4.5, 4.0; 6.0, 4.0, 3.0; ... 6.5, 5.0, 4.0; 7.0, 5.5, 5.0; 7.0, 5.0, 4.5]; [p, atab, stats] = anova2(popcorn, 3, "on"); ***** demo # One-way Repeated Measures ANOVA (Rows are a crossed random factor) data = [54, 43, 78, 111; 23, 34, 37, 41; 45, 65, 99, 78; 31, 33, 36, 35; 15, 25, 30, 26]; [p, atab, stats] = anova2 (data, 1, "on", "linear"); ***** demo # Balanced Nested One-way ANOVA (Rows are a nested random factor) data = [4.5924 7.3809 21.322; -0.5488 9.2085 25.0426; ... 6.1605 13.1147 22.66; 2.3374 15.2654 24.1283; ... 5.1873 12.4188 16.5927; 3.3579 14.3951 10.2129; ... 6.3092 8.5986 9.8934; 3.2831 3.4945 10.0203]; [p, atab, stats] = anova2 (data, 4, "on", "nested"); ***** test ## Test for anova2 ("interaction") ## comparison with results from Matlab for column effect popcorn = [5.5, 4.5, 3.5; 5.5, 4.5, 4.0; 6.0, 4.0, 3.0; ... 6.5, 5.0, 4.0; 7.0, 5.5, 5.0; 7.0, 5.0, 4.5]; [p, atab, stats] = anova2 (popcorn, 3, "off"); assert (p(1), 7.678957383294716e-07, 1e-14); assert (p(2), 0.0001003738963050171, 1e-14); assert (p(3), 0.7462153966366274, 1e-14); assert (atab{2,5}, 56.700, 1e-14); assert (atab{2,3}, 2, 0); assert (atab{4,2}, 0.08333333333333348, 1e-14); assert (atab{5,4}, 0.1388888888888889, 1e-14); assert (atab{5,2}, 1.666666666666667, 1e-14); assert (atab{6,2}, 22); assert (stats.source, "anova2"); assert (stats.colmeans, [6.25, 4.75, 4]); assert (stats.inter, 1, 0); assert (stats.pval, 0.7462153966366274, 1e-14); assert (stats.df, 12); ***** test ## Test for anova2 ("linear") - comparison with results from GraphPad Prism 8 data = [54, 43, 78, 111; 23, 34, 37, 41; 45, 65, 99, 78; 31, 33, 36, 35; 15, 25, 30, 26]; [p, atab, stats] = anova2 (data, 1, "off", "linear"); assert (atab{2,2}, 2174.95, 1e-10); assert (atab{3,2}, 8371.7, 1e-10); assert (atab{4,2}, 2404.3, 1e-10); assert (atab{5,2}, 12950.95, 1e-10); assert (atab{2,4}, 724.983333333333, 1e-10); assert (atab{3,4}, 2092.925, 1e-10); assert (atab{4,4}, 200.358333333333, 1e-10); assert (atab{2,5}, 3.61843363972882, 1e-10); assert (atab{3,5}, 10.445909412303, 1e-10); assert (atab{2,6}, 0.087266112738617, 1e-10); assert (atab{3,6}, 0.000698397753556, 1e-10); ***** test ## Test for anova2 ("nested") - comparison with results from GraphPad Prism 8 data = [4.5924 7.3809 21.322; -0.5488 9.2085 25.0426; ... 6.1605 13.1147 22.66; 2.3374 15.2654 24.1283; ... 5.1873 12.4188 16.5927; 3.3579 14.3951 10.2129; ... 6.3092 8.5986 9.8934; 3.2831 3.4945 10.0203]; [p, atab, stats] = anova2 (data, 4, "off", "nested"); assert (atab{2,2}, 745.360306290833, 1e-10); assert (atab{3,2}, 278.01854140125, 1e-10); assert (atab{4,2}, 180.180377467501, 1e-10); assert (atab{5,2}, 1203.55922515958, 1e-10); assert (atab{2,4}, 372.680153145417, 1e-10); assert (atab{3,4}, 92.67284713375, 1e-10); assert (atab{4,4}, 10.0100209704167, 1e-10); assert (atab{2,5}, 4.02146005730833, 1e-10); assert (atab{3,5}, 9.25800729165627, 1e-10); assert (atab{2,6}, 0.141597630656771, 1e-10); assert (atab{3,6}, 0.000636643812875719, 1e-10); 3 tests, 3 passed, 0 known failure, 0 skipped [inst/linkage.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/linkage.m ***** shared x, t x = reshape (mod (magic (6),5), [], 3); t = 1e-6; ***** assert (cond (linkage (pdist (x))), 34.119045, t); ***** assert (cond (linkage (pdist (x), "complete")), 21.793345, t); ***** assert (cond (linkage (pdist (x), "average")), 27.045012, t); ***** assert (cond (linkage (pdist (x), "weighted")), 27.412889, t); lastwarn(); # Clear last warning before the test ***** warning linkage (pdist (x), "centroid"); ***** test warning off Octave:clustering assert (cond (linkage (pdist (x), "centroid")), 27.457477, t); warning on Octave:clustering ***** warning linkage (pdist (x), "median"); ***** test warning off Octave:clustering assert (cond (linkage (pdist (x), "median")), 27.683325, t); warning on Octave:clustering ***** assert (cond (linkage (pdist (x), "ward")), 17.195198, t); ***** assert (cond (linkage (x, "ward", "euclidean")), 17.195198, t); ***** assert (cond (linkage (x, "ward", {"euclidean"})), 17.195198, t); ***** assert (cond (linkage (x, "ward", {"minkowski", 2})), 17.195198, t); 12 tests, 12 passed, 0 known failure, 0 skipped [inst/ttest.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/ttest.m ***** test x = 8:0.1:12; [h, pval, ci] = ttest (x, 10); assert (h, 0) assert (pval, 1, 10*eps) assert (ci, [9.6219 10.3781], 1E-5) [h, pval, ci0] = ttest (x, 0); assert (h, 1) assert (pval, 0) assert (ci0, ci, 2e-15) [h, pval, ci] = ttest (x, 10, "tail", "right", "dim", 2, "alpha", 0.05); assert (h, 0) assert (pval, 0.5, 10*eps) assert (ci, [9.68498 Inf], 1E-5) ***** error ttest ([8:0.1:12], 10, "tail", "invalid"); ***** error ttest ([8:0.1:12], 10, "tail", 25); 3 tests, 3 passed, 0 known failure, 0 skipped [inst/ranksum.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/ranksum.m ***** test mileage = [33.3, 34.5, 37.4; 33.4, 34.8, 36.8; ... 32.9, 33.8, 37.6; 32.6, 33.4, 36.6; ... 32.5, 33.7, 37.0; 33.0, 33.9, 36.7]; [p,h,stats] = ranksum(mileage(:,1),mileage(:,2)); assert (p, 0.004329004329004329, 1e-14); assert (h, true); assert (stats.ranksum, 21.5); ***** test year1 = [51 52 62 62 52 52 51 53 59 63 59 56 63 74 68 86 82 70 69 75 73 ... 49 47 50 60 59 60 62 61 71]'; year2 = [54 53 64 66 57 53 54 54 62 66 59 59 67 76 75 86 82 67 74 80 75 ... 54 50 53 62 62 62 72 60 67]'; [p,h,stats] = ranksum(year1, year2, "alpha", 0.01, "tail", "left"); assert (p, 0.1270832752950605, 1e-14); assert (h, false); assert (stats.ranksum, 837.5); assert (stats.zval, -1.140287483634606, 1e-14); [p,h,stats] = ranksum(year1, year2, "alpha", 0.01, "tail", "left", ... "method", "exact"); assert (p, 0.127343916432862, 1e-14); assert (h, false); assert (stats.ranksum, 837.5); 2 tests, 2 passed, 0 known failure, 0 skipped [inst/normalise_distribution.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/normalise_distribution.m ***** test v = normalise_distribution ([1 2 3], [], 1); assert (v, [0 0 0]) ***** test v = normalise_distribution ([1 2 3], [], 2); assert (v, norminv ([1 3 5] / 6), 3 * eps) ***** test v = normalise_distribution ([1 2 3]', [], 2); assert (v, [0 0 0]') ***** test v = normalise_distribution ([1 2 3]', [], 1); assert (v, norminv ([1 3 5]' / 6), 3 * eps) ***** test v = normalise_distribution ([1 1 2 2 3 3], [], 2); assert (v, norminv ([3 3 7 7 11 11] / 12), 3 * eps) ***** test v = normalise_distribution ([1 1 2 2 3 3]', [], 1); assert (v, norminv ([3 3 7 7 11 11]' / 12), 3 * eps) ***** test A = randn ( 10 ); N = normalise_distribution (A, @normcdf); assert (A, N, 10000 * eps) ***** test A = exprnd (1, 100); N = normalise_distribution (A, @(x)(expcdf (x, 1))); assert (mean (vec (N)), 0, 0.1) assert (std (vec (N)), 1, 0.1) ***** test A = rand (1000,1); N = normalise_distribution (A, {@(x)(unifcdf (x, 0, 1))}); assert (mean (vec (N)), 0, 0.2) assert (std (vec (N)), 1, 0.1) ***** test A = [rand(1000,1), randn(1000, 1)]; N = normalise_distribution (A, {@(x)(unifcdf (x, 0, 1)), @normcdf}); assert (mean (N), [0, 0], 0.2) assert (std (N), [1, 1], 0.1) ***** test A = [rand(1000,1), randn(1000, 1), exprnd(1, 1000, 1)]'; N = normalise_distribution (A, {@(x)(unifcdf (x, 0, 1)); @normcdf; @(x)(expcdf (x, 1))}, 2); assert (mean (N, 2), [0, 0, 0]', 0.2); assert (std (N, [], 2), [1, 1, 1]', 0.1); ***** xtest A = exprnd (1, 1000, 9); A (300:500, 4:6) = 17; N = normalise_distribution (A); assert (mean (N), [0 0 0 0.38 0.38 0.38 0 0 0], 0.1); assert (var (N), [1 1 1 2.59 2.59 2.59 1 1 1], 0.1); ***** test ***** error normalise_distribution (zeros (3, 4), ... {@(x)(unifcdf (x, 0, 1)); @normcdf; @(x)(expcdf (x,1))}); 14 tests, 14 passed, 0 known failure, 0 skipped [inst/dist_wrap/mle.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/dist_wrap/mle.m ***** error mle (ones (2)) ***** error mle ("text") ***** error mle ([1, 2, 3, i, 5]) ***** error ... mle ([1:50], "distribution") ***** error ... mle ([1:50], "censoring", logical ([1,0,1,0])) ***** error ... mle ([1:50], "frequency", [1,0,1,0]) ***** error ... mle ([1 0 1 0], "frequency", [-1 1 0 0]) ***** error ... mle ([1 0 1 0], "distribution", "nbin", "frequency", [-1 1 0 0]) ***** error mle ([1:50], "alpha", [0.05, 0.01]) ***** error mle ([1:50], "alpha", 1) ***** error mle ([1:50], "alpha", -1) ***** error mle ([1:50], "alpha", i) ***** error ... mle ([1:50], "ntrials", -1) ***** error ... mle ([1:50], "ntrials", [20, 50]) ***** error ... mle ([1:50], "ntrials", [20.3]) ***** error ... mle ([1:50], "ntrials", 3i) ***** error ... mle ([1:50], "options", 4) ***** error ... mle ([1:50], "options", struct ("x", 3)) ***** error mle ([1:50], "NAME", "value") ***** error ... mle ([1 0 1 0], "distribution", "bernoulli", "censoring", [1 1 0 0]) ***** error ... mle ([1 2 1 0], "distribution", "bernoulli") ***** error ... mle ([1 0 1 0], "distribution", "beta", "censoring", [1 1 0 0]) ***** error ... mle ([1 0 1 0], "distribution", "bino", "censoring", [1 1 0 0]) ***** error ... mle ([1 0 1 0], "distribution", "bino") ***** error ... mle ([1 0 1 0], "distribution", "geo", "censoring", [1 1 0 0]) ***** error ... mle ([1 0 1 0], "distribution", "gev", "censoring", [1 1 0 0]) ***** error ... mle ([1 0 1 0], "distribution", "gp", "censoring", [1 1 0 0]) ***** error ... mle ([1 0 -1 0], "distribution", "gp") ***** error ... mle ([1 0 1 0], "distribution", "hn", "censoring", [1 1 0 0]) ***** error ... mle ([1 0 -1 0], "distribution", "hn") ***** error ... mle ([1 0 1 0], "distribution", "nbin", "censoring", [1 1 0 0]) ***** error ... mle ([1 0 1 0], "distribution", "poisson", "censoring", [1 1 0 0]) ***** error ... mle ([1 0 1 0], "distribution", "unid", "censoring", [1 1 0 0]) ***** error ... mle ([1 0 1 0], "distribution", "unif", "censoring", [1 1 0 0]) ***** error mle ([1:50], "distribution", "value") ***** error ... mle ([1 0 1 0], "distribution", "unif", "censoring", [1 1 0 0]) 36 tests, 36 passed, 0 known failure, 0 skipped [inst/dist_wrap/icdf.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/dist_wrap/icdf.m ***** shared p p = [0.05:0.05:0.5]; ***** assert (icdf ("Beta", p, 5, 2), betainv (p, 5, 2)) ***** assert (icdf ("beta", p, 5, 2), betainv (p, 5, 2)) ***** assert (icdf ("Binomial", p, 5, 2), binoinv (p, 5, 2)) ***** assert (icdf ("bino", p, 5, 2), binoinv (p, 5, 2)) ***** assert (icdf ("Birnbaum-Saunders", p, 5, 2), bisainv (p, 5, 2)) ***** assert (icdf ("bisa", p, 5, 2), bisainv (p, 5, 2)) ***** assert (icdf ("Burr", p, 5, 2, 2), burrinv (p, 5, 2, 2)) ***** assert (icdf ("burr", p, 5, 2, 2), burrinv (p, 5, 2, 2)) ***** assert (icdf ("Cauchy", p, 5, 2), cauchyinv (p, 5, 2)) ***** assert (icdf ("cauchy", p, 5, 2), cauchyinv (p, 5, 2)) ***** assert (icdf ("Chi-squared", p, 5), chi2inv (p, 5)) ***** assert (icdf ("chi2", p, 5), chi2inv (p, 5)) ***** assert (icdf ("Extreme Value", p, 5, 2), evinv (p, 5, 2)) ***** assert (icdf ("ev", p, 5, 2), evinv (p, 5, 2)) ***** assert (icdf ("Exponential", p, 5), expinv (p, 5)) ***** assert (icdf ("exp", p, 5), expinv (p, 5)) ***** assert (icdf ("F-Distribution", p, 5, 2), finv (p, 5, 2)) ***** assert (icdf ("f", p, 5, 2), finv (p, 5, 2)) ***** assert (icdf ("Gamma", p, 5, 2), gaminv (p, 5, 2)) ***** assert (icdf ("gam", p, 5, 2), gaminv (p, 5, 2)) ***** assert (icdf ("Geometric", p, 5), geoinv (p, 5)) ***** assert (icdf ("geo", p, 5), geoinv (p, 5)) ***** assert (icdf ("Generalized Extreme Value", p, 5, 2, 2), gevinv (p, 5, 2, 2)) ***** assert (icdf ("gev", p, 5, 2, 2), gevinv (p, 5, 2, 2)) ***** assert (icdf ("Generalized Pareto", p, 5, 2, 2), gpinv (p, 5, 2, 2)) ***** assert (icdf ("gp", p, 5, 2, 2), gpinv (p, 5, 2, 2)) ***** assert (icdf ("Gumbel", p, 5, 2), gumbelinv (p, 5, 2)) ***** assert (icdf ("gumbel", p, 5, 2), gumbelinv (p, 5, 2)) ***** assert (icdf ("Half-normal", p, 5, 2), hninv (p, 5, 2)) ***** assert (icdf ("hn", p, 5, 2), hninv (p, 5, 2)) ***** assert (icdf ("Hypergeometric", p, 5, 2, 2), hygeinv (p, 5, 2, 2)) ***** assert (icdf ("hyge", p, 5, 2, 2), hygeinv (p, 5, 2, 2)) ***** assert (icdf ("Inverse Gaussian", p, 5, 2), invginv (p, 5, 2)) ***** assert (icdf ("invg", p, 5, 2), invginv (p, 5, 2)) ***** assert (icdf ("Laplace", p, 5, 2), laplaceinv (p, 5, 2)) ***** assert (icdf ("laplace", p, 5, 2), laplaceinv (p, 5, 2)) ***** assert (icdf ("Logistic", p, 5, 2), logiinv (p, 5, 2)) ***** assert (icdf ("logi", p, 5, 2), logiinv (p, 5, 2)) ***** assert (icdf ("Log-Logistic", p, 5, 2), loglinv (p, 5, 2)) ***** assert (icdf ("logl", p, 5, 2), loglinv (p, 5, 2)) ***** assert (icdf ("Lognormal", p, 5, 2), logninv (p, 5, 2)) ***** assert (icdf ("logn", p, 5, 2), logninv (p, 5, 2)) ***** assert (icdf ("Nakagami", p, 5, 2), nakainv (p, 5, 2)) ***** assert (icdf ("naka", p, 5, 2), nakainv (p, 5, 2)) ***** assert (icdf ("Negative Binomial", p, 5, 2), nbininv (p, 5, 2)) ***** assert (icdf ("nbin", p, 5, 2), nbininv (p, 5, 2)) ***** assert (icdf ("Noncentral F-Distribution", p, 5, 2, 2), ncfinv (p, 5, 2, 2)) ***** assert (icdf ("ncf", p, 5, 2, 2), ncfinv (p, 5, 2, 2)) ***** assert (icdf ("Noncentral Student T", p, 5, 2), nctinv (p, 5, 2)) ***** assert (icdf ("nct", p, 5, 2), nctinv (p, 5, 2)) ***** assert (icdf ("Noncentral Chi-Squared", p, 5, 2), ncx2inv (p, 5, 2)) ***** assert (icdf ("ncx2", p, 5, 2), ncx2inv (p, 5, 2)) ***** assert (icdf ("Normal", p, 5, 2), norminv (p, 5, 2)) ***** assert (icdf ("norm", p, 5, 2), norminv (p, 5, 2)) ***** assert (icdf ("Poisson", p, 5), poissinv (p, 5)) ***** assert (icdf ("poiss", p, 5), poissinv (p, 5)) ***** assert (icdf ("Rayleigh", p, 5), raylinv (p, 5)) ***** assert (icdf ("rayl", p, 5), raylinv (p, 5)) ***** assert (icdf ("Rician", p, 5, 1), riceinv (p, 5, 1)) ***** assert (icdf ("rice", p, 5, 1), riceinv (p, 5, 1)) ***** assert (icdf ("Student T", p, 5), tinv (p, 5)) ***** assert (icdf ("t", p, 5), tinv (p, 5)) ***** assert (icdf ("location-scale T", p, 5, 1, 2), tlsinv (p, 5, 1, 2)) ***** assert (icdf ("tls", p, 5, 1, 2), tlsinv (p, 5, 1, 2)) ***** assert (icdf ("Triangular", p, 5, 2, 2), triinv (p, 5, 2, 2)) ***** assert (icdf ("tri", p, 5, 2, 2), triinv (p, 5, 2, 2)) ***** assert (icdf ("Discrete Uniform", p, 5), unidinv (p, 5)) ***** assert (icdf ("unid", p, 5), unidinv (p, 5)) ***** assert (icdf ("Uniform", p, 5, 2), unifinv (p, 5, 2)) ***** assert (icdf ("unif", p, 5, 2), unifinv (p, 5, 2)) ***** assert (icdf ("Von Mises", p, 5, 2), vminv (p, 5, 2)) ***** assert (icdf ("vm", p, 5, 2), vminv (p, 5, 2)) ***** assert (icdf ("Weibull", p, 5, 2), wblinv (p, 5, 2)) ***** assert (icdf ("wbl", p, 5, 2), wblinv (p, 5, 2)) ***** error icdf (1) ***** error icdf ({"beta"}) ***** error icdf ("beta", {[1 2 3 4 5]}) ***** error icdf ("beta", "text") ***** error icdf ("beta", 1+i) ***** error ... icdf ("Beta", p, "a", 2) ***** error ... icdf ("Beta", p, 5, "") ***** error ... icdf ("Beta", p, 5, {2}) ***** error icdf ("chi2", p) ***** error icdf ("Beta", p, 5) ***** error icdf ("Burr", p, 5) ***** error icdf ("Burr", p, 5, 2) 86 tests, 86 passed, 0 known failure, 0 skipped [inst/dist_wrap/makedist.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/dist_wrap/makedist.m ***** test pd = makedist ("beta"); assert (class (pd), "BetaDistribution"); assert (pd.a, 1); assert (pd.b, 1); ***** test pd = makedist ("beta", "a", 5); assert (pd.a, 5); assert (pd.b, 1); ***** test pd = makedist ("beta", "b", 5); assert (pd.a, 1); assert (pd.b, 5); ***** test pd = makedist ("beta", "a", 3, "b", 5); assert (pd.a, 3); assert (pd.b, 5); ***** test pd = makedist ("binomial"); assert (class (pd), "BinomialDistribution"); assert (pd.N, 1); assert (pd.p, 0.5); ***** test pd = makedist ("binomial", "N", 5); assert (pd.N, 5); assert (pd.p, 0.5); ***** test pd = makedist ("binomial", "p", 0.2); assert (pd.N, 1); assert (pd.p, 0.2); ***** test pd = makedist ("binomial", "N", 3, "p", 0.3); assert (pd.N, 3); assert (pd.p, 0.3); ***** test pd = makedist ("birnbaumsaunders"); assert (class (pd), "BirnbaumSaundersDistribution"); assert (pd.beta, 1); assert (pd.gamma, 1); ***** test pd = makedist ("birnbaumsaunders", "beta", 5); assert (pd.beta, 5); assert (pd.gamma, 1); ***** test pd = makedist ("birnbaumsaunders", "gamma", 5); assert (pd.beta, 1); assert (pd.gamma, 5); ***** test pd = makedist ("birnbaumsaunders", "beta", 3, "gamma", 5); assert (pd.beta, 3); assert (pd.gamma, 5); ***** test pd = makedist ("burr"); assert (class (pd), "BurrDistribution"); assert (pd.alpha, 1); assert (pd.c, 1); assert (pd.k, 1); ***** test pd = makedist ("burr", "k", 5); assert (pd.alpha, 1); assert (pd.c, 1); assert (pd.k, 5); ***** test pd = makedist ("burr", "c", 5); assert (pd.alpha, 1); assert (pd.c, 5); assert (pd.k, 1); ***** test pd = makedist ("burr", "alpha", 3, "c", 5); assert (pd.alpha, 3); assert (pd.c, 5); assert (pd.k, 1); ***** test pd = makedist ("burr", "k", 3, "c", 5); assert (pd.alpha, 1); assert (pd.c, 5); assert (pd.k, 3); ***** test pd = makedist ("exponential"); assert (class (pd), "ExponentialDistribution"); assert (pd.mu, 1); ***** test pd = makedist ("exponential", "mu", 5); assert (pd.mu, 5); ***** test pd = makedist ("extremevalue"); assert (class (pd), "ExtremeValueDistribution"); assert (pd.mu, 0); assert (pd.sigma, 1); ***** test pd = makedist ("extremevalue", "mu", 5); assert (class (pd), "ExtremeValueDistribution"); assert (pd.mu, 5); assert (pd.sigma, 1); ***** test pd = makedist ("ev", "sigma", 5); assert (class (pd), "ExtremeValueDistribution"); assert (pd.mu, 0); assert (pd.sigma, 5); ***** test pd = makedist ("ev", "mu", -3, "sigma", 5); assert (class (pd), "ExtremeValueDistribution"); assert (pd.mu, -3); assert (pd.sigma, 5); ***** test pd = makedist ("gamma"); assert (class (pd), "GammaDistribution"); assert (pd.a, 1); assert (pd.b, 1); ***** test pd = makedist ("gamma", "a", 5); assert (pd.a, 5); assert (pd.b, 1); ***** test pd = makedist ("gamma", "b", 5); assert (pd.a, 1); assert (pd.b, 5); ***** test pd = makedist ("gamma", "a", 3, "b", 5); assert (pd.a, 3); assert (pd.b, 5); ***** test pd = makedist ("GeneralizedExtremeValue"); assert (class (pd), "GeneralizedExtremeValueDistribution"); assert (pd.k, 0); assert (pd.sigma, 1); assert (pd.mu, 0); ***** test pd = makedist ("GeneralizedExtremeValue", "k", 5); assert (pd.k, 5); assert (pd.sigma, 1); assert (pd.mu, 0); ***** test pd = makedist ("GeneralizedExtremeValue", "sigma", 5); assert (pd.k, 0); assert (pd.sigma, 5); assert (pd.mu, 0); ***** test pd = makedist ("GeneralizedExtremeValue", "k", 3, "sigma", 5); assert (pd.k, 3); assert (pd.sigma, 5); assert (pd.mu, 0); ***** test pd = makedist ("GeneralizedExtremeValue", "mu", 3, "sigma", 5); assert (pd.k, 0); assert (pd.sigma, 5); assert (pd.mu, 3); ***** test pd = makedist ("GeneralizedPareto"); assert (class (pd), "GeneralizedParetoDistribution"); assert (pd.k, 1); assert (pd.sigma, 1); assert (pd.theta, 1); ***** test pd = makedist ("GeneralizedPareto", "k", 5); assert (pd.k, 5); assert (pd.sigma, 1); assert (pd.theta, 1); ***** test pd = makedist ("GeneralizedPareto", "sigma", 5); assert (pd.k, 1); assert (pd.sigma, 5); assert (pd.theta, 1); ***** test pd = makedist ("GeneralizedPareto", "k", 3, "sigma", 5); assert (pd.k, 3); assert (pd.sigma, 5); assert (pd.theta, 1); ***** test pd = makedist ("GeneralizedPareto", "theta", 3, "sigma", 5); assert (pd.k, 1); assert (pd.sigma, 5); assert (pd.theta, 3); ***** test pd = makedist ("HalfNormal"); assert (class (pd), "HalfNormalDistribution"); assert (pd.mu, 0); assert (pd.sigma, 1); ***** test pd = makedist ("HalfNormal", "mu", 5); assert (pd.mu, 5); assert (pd.sigma, 1); ***** test pd = makedist ("HalfNormal", "sigma", 5); assert (pd.mu, 0); assert (pd.sigma, 5); ***** test pd = makedist ("HalfNormal", "mu", 3, "sigma", 5); assert (pd.mu, 3); assert (pd.sigma, 5); ***** test pd = makedist ("InverseGaussian"); assert (class (pd), "InverseGaussianDistribution"); assert (pd.mu, 1); assert (pd.lambda, 1); ***** test pd = makedist ("InverseGaussian", "mu", 5); assert (pd.mu, 5); assert (pd.lambda, 1); ***** test pd = makedist ("InverseGaussian", "lambda", 5); assert (pd.mu, 1); assert (pd.lambda, 5); ***** test pd = makedist ("InverseGaussian", "mu", 3, "lambda", 5); assert (pd.mu, 3); assert (pd.lambda, 5); ***** test pd = makedist ("logistic"); assert (class (pd), "LogisticDistribution"); assert (pd.mu, 0); assert (pd.sigma, 1); ***** test pd = makedist ("logistic", "mu", 5); assert (pd.mu, 5); assert (pd.sigma, 1); ***** test pd = makedist ("logistic", "sigma", 5); assert (pd.mu, 0); assert (pd.sigma, 5); ***** test pd = makedist ("logistic", "mu", 3, "sigma", 5); assert (pd.mu, 3); assert (pd.sigma, 5); ***** test pd = makedist ("loglogistic"); assert (class (pd), "LoglogisticDistribution"); assert (pd.mu, 0); assert (pd.sigma, 1); ***** test pd = makedist ("loglogistic", "mu", 5); assert (pd.mu, 5); assert (pd.sigma, 1); ***** test pd = makedist ("loglogistic", "sigma", 5); assert (pd.mu, 0); assert (pd.sigma, 5); ***** test pd = makedist ("loglogistic", "mu", 3, "sigma", 5); assert (pd.mu, 3); assert (pd.sigma, 5); ***** test pd = makedist ("Lognormal"); assert (class (pd), "LognormalDistribution"); assert (pd.mu, 0); assert (pd.sigma, 1); ***** test pd = makedist ("Lognormal", "mu", 5); assert (pd.mu, 5); assert (pd.sigma, 1); ***** test pd = makedist ("Lognormal", "sigma", 5); assert (pd.mu, 0); assert (pd.sigma, 5); ***** test pd = makedist ("Lognormal", "mu", -3, "sigma", 5); assert (pd.mu, -3); assert (pd.sigma, 5); ***** test pd = makedist ("Loguniform"); assert (class (pd), "LoguniformDistribution"); assert (pd.Lower, 1); assert (pd.Upper, 4); ***** test pd = makedist ("Loguniform", "Lower", 2); assert (pd.Lower, 2); assert (pd.Upper, 4); ***** test pd = makedist ("Loguniform", "Lower", 1, "Upper", 3); assert (pd.Lower, 1); assert (pd.Upper, 3); ***** test pd = makedist ("Multinomial"); assert (class (pd), "MultinomialDistribution"); assert (pd.Probabilities, [0.5, 0.5]); ***** test pd = makedist ("Multinomial", "Probabilities", [0.2, 0.3, 0.1, 0.4]); assert (class (pd), "MultinomialDistribution"); assert (pd.Probabilities, [0.2, 0.3, 0.1, 0.4]); ***** test pd = makedist ("Nakagami"); assert (class (pd), "NakagamiDistribution"); assert (pd.mu, 1); assert (pd.omega, 1); ***** test pd = makedist ("Nakagami", "mu", 5); assert (class (pd), "NakagamiDistribution"); assert (pd.mu, 5); assert (pd.omega, 1); ***** test pd = makedist ("Nakagami", "omega", 0.3); assert (class (pd), "NakagamiDistribution"); assert (pd.mu, 1); assert (pd.omega, 0.3); ***** test pd = makedist ("NegativeBinomial"); assert (class (pd), "NegativeBinomialDistribution"); assert (pd.R, 1); assert (pd.P, 0.5); ***** test pd = makedist ("NegativeBinomial", "R", 5); assert (class (pd), "NegativeBinomialDistribution"); assert (pd.R, 5); assert (pd.P, 0.5); ***** test pd = makedist ("NegativeBinomial", "p", 0.3); assert (class (pd), "NegativeBinomialDistribution"); assert (pd.R, 1); assert (pd.P, 0.3); ***** test pd = makedist ("Normal"); assert (class (pd), "NormalDistribution"); assert (pd.mu, 0); assert (pd.sigma, 1); ***** test pd = makedist ("Normal", "mu", 5); assert (class (pd), "NormalDistribution"); assert (pd.mu, 5); assert (pd.sigma, 1); ***** test pd = makedist ("Normal", "sigma", 5); assert (class (pd), "NormalDistribution"); assert (pd.mu, 0); assert (pd.sigma, 5); ***** test pd = makedist ("Normal", "mu", -3, "sigma", 5); assert (class (pd), "NormalDistribution"); assert (pd.mu, -3); assert (pd.sigma, 5); ***** test pd = makedist ("PiecewiseLinear"); assert (class (pd), "PiecewiseLinearDistribution"); assert (pd.x, [0; 1]); assert (pd.Fx, [0; 1]); ***** test pd = makedist ("PiecewiseLinear", "x", [0, 1, 2], "Fx", [0, 0.5, 1]); assert (pd.x, [0; 1; 2]); assert (pd.Fx, [0; 0.5; 1]); ***** test pd = makedist ("Poisson"); assert (class (pd), "PoissonDistribution"); assert (pd.lambda, 1); ***** test pd = makedist ("Poisson", "lambda", 5); assert (pd.lambda, 5); ***** test pd = makedist ("Rayleigh"); assert (class (pd), "RayleighDistribution"); assert (pd.sigma, 1); ***** test pd = makedist ("Rayleigh", "sigma", 5); assert (pd.sigma, 5); ***** test pd = makedist ("Rician"); assert (class (pd), "RicianDistribution"); assert (pd.s, 1); assert (pd.sigma, 1); ***** test pd = makedist ("Rician", "s", 3); assert (pd.s, 3); assert (pd.sigma, 1); ***** test pd = makedist ("Rician", "sigma", 3); assert (pd.s, 1); assert (pd.sigma, 3); ***** test pd = makedist ("Rician", "s", 2, "sigma", 3); assert (pd.s, 2); assert (pd.sigma, 3); ***** warning pd = makedist ("stable"); assert (class (pd), "double"); assert (isempty (pd), true); ***** test pd = makedist ("tlocationscale"); assert (class (pd), "tLocationScaleDistribution"); assert (pd.mu, 0); assert (pd.sigma, 1); assert (pd.nu, 5); ***** test pd = makedist ("tlocationscale", "mu", 5); assert (pd.mu, 5); assert (pd.sigma, 1); assert (pd.nu, 5); ***** test pd = makedist ("tlocationscale", "sigma", 2); assert (pd.mu, 0); assert (pd.sigma, 2); assert (pd.nu, 5); ***** test pd = makedist ("tlocationscale", "mu", 5, "sigma", 2); assert (pd.mu, 5); assert (pd.sigma, 2); assert (pd.nu, 5); ***** test pd = makedist ("tlocationscale", "nu", 1, "sigma", 2); assert (pd.mu, 0); assert (pd.sigma, 2); assert (pd.nu, 1); ***** test pd = makedist ("tlocationscale", "mu", -2, "sigma", 3, "nu", 1); assert (pd.mu, -2); assert (pd.sigma, 3); assert (pd.nu, 1); ***** test pd = makedist ("Triangular"); assert (class (pd), "TriangularDistribution"); assert (pd.A, 0); assert (pd.B, 0.5); assert (pd.C, 1); ***** test pd = makedist ("Triangular", "A", -2); assert (pd.A, -2); assert (pd.B, 0.5); assert (pd.C, 1); ***** test pd = makedist ("Triangular", "A", 0.5, "B", 0.9); assert (pd.A, 0.5); assert (pd.B, 0.9); assert (pd.C, 1); ***** test pd = makedist ("Triangular", "A", 1, "B", 2, "C", 5); assert (pd.A, 1); assert (pd.B, 2); assert (pd.C, 5); ***** test pd = makedist ("Uniform"); assert (class (pd), "UniformDistribution"); assert (pd.Lower, 0); assert (pd.Upper, 1); ***** test pd = makedist ("Uniform", "Lower", -2); assert (pd.Lower, -2); assert (pd.Upper, 1); ***** test pd = makedist ("Uniform", "Lower", 1, "Upper", 3); assert (pd.Lower, 1); assert (pd.Upper, 3); ***** test pd = makedist ("Weibull"); assert (class (pd), "WeibullDistribution"); assert (pd.lambda, 1); assert (pd.k, 1); ***** test pd = makedist ("Weibull", "lambda", 3); assert (pd.lambda, 3); assert (pd.k, 1); ***** test pd = makedist ("Weibull", "lambda", 3, "k", 2); assert (pd.lambda, 3); assert (pd.k, 2); ***** error makedist (1) ***** error makedist (["as";"sd"]) ***** error makedist ("some") ***** error ... makedist ("Beta", "a") ***** error ... makedist ("Beta", "a", 1, "Q", 23) ***** error ... makedist ("Binomial", "N", 1, "Q", 23) ***** error ... makedist ("BirnbaumSaunders", "N", 1) ***** error ... makedist ("Burr", "lambda", 1, "sdfs", 34) ***** error ... makedist ("extremevalue", "mu", 1, "sdfs", 34) ***** error ... makedist ("exponential", "mu", 1, "sdfs", 34) ***** error ... makedist ("Gamma", "k", 1, "sdfs", 34) ***** error ... makedist ("GeneralizedExtremeValue", "k", 1, "sdfs", 34) ***** error ... makedist ("GeneralizedPareto", "k", 1, "sdfs", 34) ***** error ... makedist ("HalfNormal", "k", 1, "sdfs", 34) ***** error ... makedist ("InverseGaussian", "k", 1, "sdfs", 34) ***** error ... makedist ("Logistic", "k", 1, "sdfs", 34) ***** error ... makedist ("Loglogistic", "k", 1, "sdfs", 34) ***** error ... makedist ("Lognormal", "k", 1, "sdfs", 34) ***** error ... makedist ("Loguniform", "k", 1, "sdfs", 34) ***** error ... makedist ("Multinomial", "k", 1, "sdfs", 34) ***** error ... makedist ("Nakagami", "mu", 1, "sdfs", 34) ***** error ... makedist ("NegativeBinomial", "mu", 1, "sdfs", 34) ***** error ... makedist ("Normal", "mu", 1, "sdfs", 34) ***** error ... makedist ("PiecewiseLinear", "mu", 1, "sdfs", 34) ***** error ... makedist ("Poisson", "mu", 1, "sdfs", 34) ***** error ... makedist ("Rayleigh", "mu", 1, "sdfs", 34) ***** error ... makedist ("Rician", "mu", 1, "sdfs", 34) ***** error ... makedist ("Stable", "mu", 1, "sdfs", 34) ***** error ... makedist ("tLocationScale", "mu", 1, "sdfs", 34) ***** error ... makedist ("Triangular", "mu", 1, "sdfs", 34) ***** error ... makedist ("Uniform", "mu", 1, "sdfs", 34) ***** error ... makedist ("Weibull", "mu", 1, "sdfs", 34) 131 tests, 131 passed, 0 known failure, 0 skipped [inst/dist_wrap/random.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/dist_wrap/random.m ***** assert (size (random ("Beta", 5, 2, 2, 10)), size (betarnd (5, 2, 2, 10))) ***** assert (size (random ("beta", 5, 2, 2, 10)), size (betarnd (5, 2, 2, 10))) ***** assert (size (random ("Binomial", 5, 2, [10, 20])), size (binornd (5, 2, 10, 20))) ***** assert (size (random ("bino", 5, 2, [10, 20])), size (binornd (5, 2, 10, 20))) ***** assert (size (random ("Birnbaum-Saunders", 5, 2, [10, 20])), size (bisarnd (5, 2, 10, 20))) ***** assert (size (random ("bisa", 5, 2, [10, 20])), size (bisarnd (5, 2, 10, 20))) ***** assert (size (random ("Burr", 5, 2, 2, [10, 20])), size (burrrnd (5, 2, 2, 10, 20))) ***** assert (size (random ("burr", 5, 2, 2, [10, 20])), size (burrrnd (5, 2, 2, 10, 20))) ***** assert (size (random ("Cauchy", 5, 2, [10, 20])), size (cauchyrnd (5, 2, 10, 20))) ***** assert (size (random ("cauchy", 5, 2, [10, 20])), size (cauchyrnd (5, 2, 10, 20))) ***** assert (size (random ("Chi-squared", 5, [10, 20])), size (chi2rnd (5, 10, 20))) ***** assert (size (random ("chi2", 5, [10, 20])), size (chi2rnd (5, 10, 20))) ***** assert (size (random ("Extreme Value", 5, 2, [10, 20])), size (evrnd (5, 2, 10, 20))) ***** assert (size (random ("ev", 5, 2, [10, 20])), size (evrnd (5, 2, 10, 20))) ***** assert (size (random ("Exponential", 5, [10, 20])), size (exprnd (5, 10, 20))) ***** assert (size (random ("exp", 5, [10, 20])), size (exprnd (5, 10, 20))) ***** assert (size (random ("F-Distribution", 5, 2, [10, 20])), size (frnd (5, 2, 10, 20))) ***** assert (size (random ("f", 5, 2, [10, 20])), size (frnd (5, 2, 10, 20))) ***** assert (size (random ("Gamma", 5, 2, [10, 20])), size (gamrnd (5, 2, 10, 20))) ***** assert (size (random ("gam", 5, 2, [10, 20])), size (gamrnd (5, 2, 10, 20))) ***** assert (size (random ("Geometric", 5, [10, 20])), size (geornd (5, 10, 20))) ***** assert (size (random ("geo", 5, [10, 20])), size (geornd (5, 10, 20))) ***** assert (size (random ("Generalized Extreme Value", 5, 2, 2, [10, 20])), size (gevrnd (5, 2, 2, 10, 20))) ***** assert (size (random ("gev", 5, 2, 2, [10, 20])), size (gevrnd (5, 2, 2, 10, 20))) ***** assert (size (random ("Generalized Pareto", 5, 2, 2, [10, 20])), size (gprnd (5, 2, 2, 10, 20))) ***** assert (size (random ("gp", 5, 2, 2, [10, 20])), size (gprnd (5, 2, 2, 10, 20))) ***** assert (size (random ("Gumbel", 5, 2, [10, 20])), size (gumbelrnd (5, 2, 10, 20))) ***** assert (size (random ("gumbel", 5, 2, [10, 20])), size (gumbelrnd (5, 2, 10, 20))) ***** assert (size (random ("Half-normal", 5, 2, [10, 20])), size (hnrnd (5, 2, 10, 20))) ***** assert (size (random ("hn", 5, 2, [10, 20])), size (hnrnd (5, 2, 10, 20))) ***** assert (size (random ("Hypergeometric", 5, 2, 2, [10, 20])), size (hygernd (5, 2, 2, 10, 20))) ***** assert (size (random ("hyge", 5, 2, 2, [10, 20])), size (hygernd (5, 2, 2, 10, 20))) ***** assert (size (random ("Inverse Gaussian", 5, 2, [10, 20])), size (invgrnd (5, 2, 10, 20))) ***** assert (size (random ("invg", 5, 2, [10, 20])), size (invgrnd (5, 2, 10, 20))) ***** assert (size (random ("Laplace", 5, 2, [10, 20])), size (laplacernd (5, 2, 10, 20))) ***** assert (size (random ("laplace", 5, 2, [10, 20])), size (laplacernd (5, 2, 10, 20))) ***** assert (size (random ("Logistic", 5, 2, [10, 20])), size (logirnd (5, 2, 10, 20))) ***** assert (size (random ("logi", 5, 2, [10, 20])), size (logirnd (5, 2, 10, 20))) ***** assert (size (random ("Log-Logistic", 5, 2, [10, 20])), size (loglrnd (5, 2, 10, 20))) ***** assert (size (random ("logl", 5, 2, [10, 20])), size (loglrnd (5, 2, 10, 20))) ***** assert (size (random ("Lognormal", 5, 2, [10, 20])), size (lognrnd (5, 2, 10, 20))) ***** assert (size (random ("logn", 5, 2, [10, 20])), size (lognrnd (5, 2, 10, 20))) ***** assert (size (random ("Nakagami", 5, 2, [10, 20])), size (nakarnd (5, 2, 10, 20))) ***** assert (size (random ("naka", 5, 2, [10, 20])), size (nakarnd (5, 2, 10, 20))) ***** assert (size (random ("Negative Binomial", 5, 2, [10, 20])), size (nbinrnd (5, 2, 10, 20))) ***** assert (size (random ("nbin", 5, 2, [10, 20])), size (nbinrnd (5, 2, 10, 20))) ***** assert (size (random ("Noncentral F-Distribution", 5, 2, 2, [10, 20])), size (ncfrnd (5, 2, 2, 10, 20))) ***** assert (size (random ("ncf", 5, 2, 2, [10, 20])), size (ncfrnd (5, 2, 2, 10, 20))) ***** assert (size (random ("Noncentral Student T", 5, 2, [10, 20])), size (nctrnd (5, 2, 10, 20))) ***** assert (size (random ("nct", 5, 2, [10, 20])), size (nctrnd (5, 2, 10, 20))) ***** assert (size (random ("Noncentral Chi-Squared", 5, 2, [10, 20])), size (ncx2rnd (5, 2, 10, 20))) ***** assert (size (random ("ncx2", 5, 2, [10, 20])), size (ncx2rnd (5, 2, 10, 20))) ***** assert (size (random ("Normal", 5, 2, [10, 20])), size (normrnd (5, 2, 10, 20))) ***** assert (size (random ("norm", 5, 2, [10, 20])), size (normrnd (5, 2, 10, 20))) ***** assert (size (random ("Poisson", 5, [10, 20])), size (poissrnd (5, 10, 20))) ***** assert (size (random ("poiss", 5, [10, 20])), size (poissrnd (5, 10, 20))) ***** assert (size (random ("Rayleigh", 5, [10, 20])), size (raylrnd (5, 10, 20))) ***** assert (size (random ("rayl", 5, [10, 20])), size (raylrnd (5, 10, 20))) ***** assert (size (random ("Rician", 5, 1, [10, 20])), size (ricernd (5, 1, 10, 20))) ***** assert (size (random ("rice", 5, 1, [10, 20])), size (ricernd (5, 1, 10, 20))) ***** assert (size (random ("Student T", 5, [10, 20])), size (trnd (5, 10, 20))) ***** assert (size (random ("t", 5, [10, 20])), size (trnd (5, 10, 20))) ***** assert (size (random ("location-scale T", 5, 1, 2, [10, 20])), size (tlsrnd (5, 1, 2, 10, 20))) ***** assert (size (random ("tls", 5, 1, 2, [10, 20])), size (tlsrnd (5, 1, 2, 10, 20))) ***** assert (size (random ("Triangular", 5, 2, 2, [10, 20])), size (trirnd (5, 2, 2, 10, 20))) ***** assert (size (random ("tri", 5, 2, 2, [10, 20])), size (trirnd (5, 2, 2, 10, 20))) ***** assert (size (random ("Discrete Uniform", 5, [10, 20])), size (unidrnd (5, 10, 20))) ***** assert (size (random ("unid", 5, [10, 20])), size (unidrnd (5, 10, 20))) ***** assert (size (random ("Uniform", 5, 2, [10, 20])), size (unifrnd (5, 2, 10, 20))) ***** assert (size (random ("unif", 5, 2, [10, 20])), size (unifrnd (5, 2, 10, 20))) ***** assert (size (random ("Von Mises", 5, 2, [10, 20])), size (vmrnd (5, 2, 10, 20))) ***** assert (size (random ("vm", 5, 2, [10, 20])), size (vmrnd (5, 2, 10, 20))) ***** assert (size (random ("Weibull", 5, 2, [10, 20])), size (wblrnd (5, 2, 10, 20))) ***** assert (size (random ("wbl", 5, 2, [10, 20])), size (wblrnd (5, 2, 10, 20))) ***** error random (1) ***** error random ({"beta"}) ***** error ... random ("Beta", "a", 2) ***** error ... random ("Beta", 5, "") ***** error ... random ("Beta", 5, {2}) ***** error ... random ("Beta", "a", 2, 2, 10) ***** error ... random ("Beta", 5, "", 2, 10) ***** error ... random ("Beta", 5, {2}, 2, 10) ***** error ... random ("Beta", 5, "", 2, 10) ***** error random ("chi2") ***** error random ("Beta", 5) ***** error random ("Burr", 5) ***** error random ("Burr", 5, 2) 87 tests, 87 passed, 0 known failure, 0 skipped [inst/dist_wrap/cdf.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/dist_wrap/cdf.m ***** shared x x = [1:5]; ***** assert (cdf ("Beta", x, 5, 2), betacdf (x, 5, 2)) ***** assert (cdf ("beta", x, 5, 2, "upper"), betacdf (x, 5, 2, "upper")) ***** assert (cdf ("Binomial", x, 5, 2), binocdf (x, 5, 2)) ***** assert (cdf ("bino", x, 5, 2, "upper"), binocdf (x, 5, 2, "upper")) ***** assert (cdf ("Birnbaum-Saunders", x, 5, 2), bisacdf (x, 5, 2)) ***** assert (cdf ("bisa", x, 5, 2, "upper"), bisacdf (x, 5, 2, "upper")) ***** assert (cdf ("Burr", x, 5, 2, 2), burrcdf (x, 5, 2, 2)) ***** assert (cdf ("burr", x, 5, 2, 2, "upper"), burrcdf (x, 5, 2, 2, "upper")) ***** assert (cdf ("Cauchy", x, 5, 2), cauchycdf (x, 5, 2)) ***** assert (cdf ("cauchy", x, 5, 2, "upper"), cauchycdf (x, 5, 2, "upper")) ***** assert (cdf ("Chi-squared", x, 5), chi2cdf (x, 5)) ***** assert (cdf ("chi2", x, 5, "upper"), chi2cdf (x, 5, "upper")) ***** assert (cdf ("Extreme Value", x, 5, 2), evcdf (x, 5, 2)) ***** assert (cdf ("ev", x, 5, 2, "upper"), evcdf (x, 5, 2, "upper")) ***** assert (cdf ("Exponential", x, 5), expcdf (x, 5)) ***** assert (cdf ("exp", x, 5, "upper"), expcdf (x, 5, "upper")) ***** assert (cdf ("F-Distribution", x, 5, 2), fcdf (x, 5, 2)) ***** assert (cdf ("f", x, 5, 2, "upper"), fcdf (x, 5, 2, "upper")) ***** assert (cdf ("Gamma", x, 5, 2), gamcdf (x, 5, 2)) ***** assert (cdf ("gam", x, 5, 2, "upper"), gamcdf (x, 5, 2, "upper")) ***** assert (cdf ("Geometric", x, 5), geocdf (x, 5)) ***** assert (cdf ("geo", x, 5, "upper"), geocdf (x, 5, "upper")) ***** assert (cdf ("Generalized Extreme Value", x, 5, 2, 2), gevcdf (x, 5, 2, 2)) ***** assert (cdf ("gev", x, 5, 2, 2, "upper"), gevcdf (x, 5, 2, 2, "upper")) ***** assert (cdf ("Generalized Pareto", x, 5, 2, 2), gpcdf (x, 5, 2, 2)) ***** assert (cdf ("gp", x, 5, 2, 2, "upper"), gpcdf (x, 5, 2, 2, "upper")) ***** assert (cdf ("Gumbel", x, 5, 2), gumbelcdf (x, 5, 2)) ***** assert (cdf ("gumbel", x, 5, 2, "upper"), gumbelcdf (x, 5, 2, "upper")) ***** assert (cdf ("Half-normal", x, 5, 2), hncdf (x, 5, 2)) ***** assert (cdf ("hn", x, 5, 2, "upper"), hncdf (x, 5, 2, "upper")) ***** assert (cdf ("Hypergeometric", x, 5, 2, 2), hygecdf (x, 5, 2, 2)) ***** assert (cdf ("hyge", x, 5, 2, 2, "upper"), hygecdf (x, 5, 2, 2, "upper")) ***** assert (cdf ("Inverse Gaussian", x, 5, 2), invgcdf (x, 5, 2)) ***** assert (cdf ("invg", x, 5, 2, "upper"), invgcdf (x, 5, 2, "upper")) ***** assert (cdf ("Laplace", x, 5, 2), laplacecdf (x, 5, 2)) ***** assert (cdf ("laplace", x, 5, 2, "upper"), laplacecdf (x, 5, 2, "upper")) ***** assert (cdf ("Logistic", x, 5, 2), logicdf (x, 5, 2)) ***** assert (cdf ("logi", x, 5, 2, "upper"), logicdf (x, 5, 2, "upper")) ***** assert (cdf ("Log-Logistic", x, 5, 2), loglcdf (x, 5, 2)) ***** assert (cdf ("logl", x, 5, 2, "upper"), loglcdf (x, 5, 2, "upper")) ***** assert (cdf ("Lognormal", x, 5, 2), logncdf (x, 5, 2)) ***** assert (cdf ("logn", x, 5, 2, "upper"), logncdf (x, 5, 2, "upper")) ***** assert (cdf ("Nakagami", x, 5, 2), nakacdf (x, 5, 2)) ***** assert (cdf ("naka", x, 5, 2, "upper"), nakacdf (x, 5, 2, "upper")) ***** assert (cdf ("Negative Binomial", x, 5, 2), nbincdf (x, 5, 2)) ***** assert (cdf ("nbin", x, 5, 2, "upper"), nbincdf (x, 5, 2, "upper")) ***** assert (cdf ("Noncentral F-Distribution", x, 5, 2, 2), ncfcdf (x, 5, 2, 2)) ***** assert (cdf ("ncf", x, 5, 2, 2, "upper"), ncfcdf (x, 5, 2, 2, "upper")) ***** assert (cdf ("Noncentral Student T", x, 5, 2), nctcdf (x, 5, 2)) ***** assert (cdf ("nct", x, 5, 2, "upper"), nctcdf (x, 5, 2, "upper")) ***** assert (cdf ("Noncentral Chi-Squared", x, 5, 2), ncx2cdf (x, 5, 2)) ***** assert (cdf ("ncx2", x, 5, 2, "upper"), ncx2cdf (x, 5, 2, "upper")) ***** assert (cdf ("Normal", x, 5, 2), normcdf (x, 5, 2)) ***** assert (cdf ("norm", x, 5, 2, "upper"), normcdf (x, 5, 2, "upper")) ***** assert (cdf ("Poisson", x, 5), poisscdf (x, 5)) ***** assert (cdf ("poiss", x, 5, "upper"), poisscdf (x, 5, "upper")) ***** assert (cdf ("Rayleigh", x, 5), raylcdf (x, 5)) ***** assert (cdf ("rayl", x, 5, "upper"), raylcdf (x, 5, "upper")) ***** assert (cdf ("Rician", x, 5, 1), ricecdf (x, 5, 1)) ***** assert (cdf ("rice", x, 5, 1, "upper"), ricecdf (x, 5, 1, "upper")) ***** assert (cdf ("Student T", x, 5), tcdf (x, 5)) ***** assert (cdf ("t", x, 5, "upper"), tcdf (x, 5, "upper")) ***** assert (cdf ("location-scale T", x, 5, 1, 2), tlscdf (x, 5, 1, 2)) ***** assert (cdf ("tls", x, 5, 1, 2, "upper"), tlscdf (x, 5, 1, 2, "upper")) ***** assert (cdf ("Triangular", x, 5, 2, 2), tricdf (x, 5, 2, 2)) ***** assert (cdf ("tri", x, 5, 2, 2, "upper"), tricdf (x, 5, 2, 2, "upper")) ***** assert (cdf ("Discrete Uniform", x, 5), unidcdf (x, 5)) ***** assert (cdf ("unid", x, 5, "upper"), unidcdf (x, 5, "upper")) ***** assert (cdf ("Uniform", x, 5, 2), unifcdf (x, 5, 2)) ***** assert (cdf ("unif", x, 5, 2, "upper"), unifcdf (x, 5, 2, "upper")) ***** assert (cdf ("Von Mises", x, 5, 2), vmcdf (x, 5, 2)) ***** assert (cdf ("vm", x, 5, 2, "upper"), vmcdf (x, 5, 2, "upper")) ***** assert (cdf ("Weibull", x, 5, 2), wblcdf (x, 5, 2)) ***** assert (cdf ("wbl", x, 5, 2, "upper"), wblcdf (x, 5, 2, "upper")) ***** error cdf (1) ***** error cdf ({"beta"}) ***** error cdf ("beta", {[1 2 3 4 5]}) ***** error cdf ("beta", "text") ***** error cdf ("beta", 1+i) ***** error ... cdf ("Beta", x, "a", 2) ***** error ... cdf ("Beta", x, 5, "") ***** error ... cdf ("Beta", x, 5, {2}) ***** error cdf ("chi2", x) ***** error cdf ("Beta", x, 5) ***** error cdf ("Burr", x, 5) ***** error cdf ("Burr", x, 5, 2) 86 tests, 86 passed, 0 known failure, 0 skipped [inst/dist_wrap/pdf.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/dist_wrap/pdf.m ***** shared x x = [1:5]; ***** assert (pdf ("Beta", x, 5, 2), betapdf (x, 5, 2)) ***** assert (pdf ("beta", x, 5, 2), betapdf (x, 5, 2)) ***** assert (pdf ("Binomial", x, 5, 2), binopdf (x, 5, 2)) ***** assert (pdf ("bino", x, 5, 2), binopdf (x, 5, 2)) ***** assert (pdf ("Birnbaum-Saunders", x, 5, 2), bisapdf (x, 5, 2)) ***** assert (pdf ("bisa", x, 5, 2), bisapdf (x, 5, 2)) ***** assert (pdf ("Burr", x, 5, 2, 2), burrpdf (x, 5, 2, 2)) ***** assert (pdf ("burr", x, 5, 2, 2), burrpdf (x, 5, 2, 2)) ***** assert (pdf ("Cauchy", x, 5, 2), cauchypdf (x, 5, 2)) ***** assert (pdf ("cauchy", x, 5, 2), cauchypdf (x, 5, 2)) ***** assert (pdf ("Chi-squared", x, 5), chi2pdf (x, 5)) ***** assert (pdf ("chi2", x, 5), chi2pdf (x, 5)) ***** assert (pdf ("Extreme Value", x, 5, 2), evpdf (x, 5, 2)) ***** assert (pdf ("ev", x, 5, 2), evpdf (x, 5, 2)) ***** assert (pdf ("Exponential", x, 5), exppdf (x, 5)) ***** assert (pdf ("exp", x, 5), exppdf (x, 5)) ***** assert (pdf ("F-Distribution", x, 5, 2), fpdf (x, 5, 2)) ***** assert (pdf ("f", x, 5, 2), fpdf (x, 5, 2)) ***** assert (pdf ("Gamma", x, 5, 2), gampdf (x, 5, 2)) ***** assert (pdf ("gam", x, 5, 2), gampdf (x, 5, 2)) ***** assert (pdf ("Geometric", x, 5), geopdf (x, 5)) ***** assert (pdf ("geo", x, 5), geopdf (x, 5)) ***** assert (pdf ("Generalized Extreme Value", x, 5, 2, 2), gevpdf (x, 5, 2, 2)) ***** assert (pdf ("gev", x, 5, 2, 2), gevpdf (x, 5, 2, 2)) ***** assert (pdf ("Generalized Pareto", x, 5, 2, 2), gppdf (x, 5, 2, 2)) ***** assert (pdf ("gp", x, 5, 2, 2), gppdf (x, 5, 2, 2)) ***** assert (pdf ("Gumbel", x, 5, 2), gumbelpdf (x, 5, 2)) ***** assert (pdf ("gumbel", x, 5, 2), gumbelpdf (x, 5, 2)) ***** assert (pdf ("Half-normal", x, 5, 2), hnpdf (x, 5, 2)) ***** assert (pdf ("hn", x, 5, 2), hnpdf (x, 5, 2)) ***** assert (pdf ("Hypergeometric", x, 5, 2, 2), hygepdf (x, 5, 2, 2)) ***** assert (pdf ("hyge", x, 5, 2, 2), hygepdf (x, 5, 2, 2)) ***** assert (pdf ("Inverse Gaussian", x, 5, 2), invgpdf (x, 5, 2)) ***** assert (pdf ("invg", x, 5, 2), invgpdf (x, 5, 2)) ***** assert (pdf ("Laplace", x, 5, 2), laplacepdf (x, 5, 2)) ***** assert (pdf ("laplace", x, 5, 2), laplacepdf (x, 5, 2)) ***** assert (pdf ("Logistic", x, 5, 2), logipdf (x, 5, 2)) ***** assert (pdf ("logi", x, 5, 2), logipdf (x, 5, 2)) ***** assert (pdf ("Log-Logistic", x, 5, 2), loglpdf (x, 5, 2)) ***** assert (pdf ("logl", x, 5, 2), loglpdf (x, 5, 2)) ***** assert (pdf ("Lognormal", x, 5, 2), lognpdf (x, 5, 2)) ***** assert (pdf ("logn", x, 5, 2), lognpdf (x, 5, 2)) ***** assert (pdf ("Nakagami", x, 5, 2), nakapdf (x, 5, 2)) ***** assert (pdf ("naka", x, 5, 2), nakapdf (x, 5, 2)) ***** assert (pdf ("Negative Binomial", x, 5, 2), nbinpdf (x, 5, 2)) ***** assert (pdf ("nbin", x, 5, 2), nbinpdf (x, 5, 2)) ***** assert (pdf ("Noncentral F-Distribution", x, 5, 2, 2), ncfpdf (x, 5, 2, 2)) ***** assert (pdf ("ncf", x, 5, 2, 2), ncfpdf (x, 5, 2, 2)) ***** assert (pdf ("Noncentral Student T", x, 5, 2), nctpdf (x, 5, 2)) ***** assert (pdf ("nct", x, 5, 2), nctpdf (x, 5, 2)) ***** assert (pdf ("Noncentral Chi-Squared", x, 5, 2), ncx2pdf (x, 5, 2)) ***** assert (pdf ("ncx2", x, 5, 2), ncx2pdf (x, 5, 2)) ***** assert (pdf ("Normal", x, 5, 2), normpdf (x, 5, 2)) ***** assert (pdf ("norm", x, 5, 2), normpdf (x, 5, 2)) ***** assert (pdf ("Poisson", x, 5), poisspdf (x, 5)) ***** assert (pdf ("poiss", x, 5), poisspdf (x, 5)) ***** assert (pdf ("Rayleigh", x, 5), raylpdf (x, 5)) ***** assert (pdf ("rayl", x, 5), raylpdf (x, 5)) ***** assert (pdf ("Rician", x, 5, 1), ricepdf (x, 5, 1)) ***** assert (pdf ("rice", x, 5, 1), ricepdf (x, 5, 1)) ***** assert (pdf ("Student T", x, 5), tpdf (x, 5)) ***** assert (pdf ("t", x, 5), tpdf (x, 5)) ***** assert (pdf ("location-scale T", x, 5, 1, 2), tlspdf (x, 5, 1, 2)) ***** assert (pdf ("tls", x, 5, 1, 2), tlspdf (x, 5, 1, 2)) ***** assert (pdf ("Triangular", x, 5, 2, 2), tripdf (x, 5, 2, 2)) ***** assert (pdf ("tri", x, 5, 2, 2), tripdf (x, 5, 2, 2)) ***** assert (pdf ("Discrete Uniform", x, 5), unidpdf (x, 5)) ***** assert (pdf ("unid", x, 5), unidpdf (x, 5)) ***** assert (pdf ("Uniform", x, 5, 2), unifpdf (x, 5, 2)) ***** assert (pdf ("unif", x, 5, 2), unifpdf (x, 5, 2)) ***** assert (pdf ("Von Mises", x, 5, 2), vmpdf (x, 5, 2)) ***** assert (pdf ("vm", x, 5, 2), vmpdf (x, 5, 2)) ***** assert (pdf ("Weibull", x, 5, 2), wblpdf (x, 5, 2)) ***** assert (pdf ("wbl", x, 5, 2), wblpdf (x, 5, 2)) ***** error pdf (1) ***** error pdf ({"beta"}) ***** error pdf ("beta", {[1 2 3 4 5]}) ***** error pdf ("beta", "text") ***** error pdf ("beta", 1+i) ***** error ... pdf ("Beta", x, "a", 2) ***** error ... pdf ("Beta", x, 5, "") ***** error ... pdf ("Beta", x, 5, {2}) ***** error pdf ("chi2", x) ***** error pdf ("Beta", x, 5) ***** error pdf ("Burr", x, 5) ***** error pdf ("Burr", x, 5, 2) 86 tests, 86 passed, 0 known failure, 0 skipped [inst/dist_wrap/fitdist.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/dist_wrap/fitdist.m ***** test x = betarnd (1, 1, 100, 1); pd = fitdist (x, "Beta"); [phat, pci] = betafit (x); assert ([pd.a, pd.b], phat); assert (paramci (pd), pci); ***** test x1 = betarnd (1, 1, 100, 1); x2 = betarnd (5, 2, 100, 1); pd = fitdist ([x1; x2], "Beta", "By", [ones(100,1); 2*ones(100,1)]); [phat, pci] = betafit (x1); assert ([pd(1).a, pd(1).b], phat); assert (paramci (pd(1)), pci); [phat, pci] = betafit (x2); assert ([pd(2).a, pd(2).b], phat); assert (paramci (pd(2)), pci); ***** test N = 1; x = binornd (N, 0.5, 100, 1); pd = fitdist (x, "binomial"); [phat, pci] = binofit (sum (x), numel (x)); assert ([pd.N, pd.p], [N, phat]); assert (paramci (pd), pci); ***** test N = 3; x = binornd (N, 0.4, 100, 1); pd = fitdist (x, "binomial", "ntrials", N); [phat, pci] = binofit (sum (x), numel (x) * N); assert ([pd.N, pd.p], [N, phat]); assert (paramci (pd), pci); ***** test N = 1; x1 = binornd (N, 0.5, 100, 1); x2 = binornd (N, 0.7, 100, 1); pd = fitdist ([x1; x2], "binomial", "By", [ones(100,1); 2*ones(100,1)]); [phat, pci] = binofit (sum (x1), numel (x1)); assert ([pd(1).N, pd(1).p], [N, phat]); assert (paramci (pd(1)), pci); [phat, pci] = binofit (sum (x2), numel (x2)); assert ([pd(2).N, pd(2).p], [N, phat]); assert (paramci (pd(2)), pci); ***** test N = 5; x1 = binornd (N, 0.5, 100, 1); x2 = binornd (N, 0.8, 100, 1); pd = fitdist ([x1; x2], "binomial", "ntrials", N, ... "By", [ones(100,1); 2*ones(100,1)]); [phat, pci] = binofit (sum (x1), numel (x1) * N); assert ([pd(1).N, pd(1).p], [N, phat]); assert (paramci (pd(1)), pci); [phat, pci] = binofit (sum (x2), numel (x2) * N); assert ([pd(2).N, pd(2).p], [N, phat]); assert (paramci (pd(2)), pci); ***** test x = bisarnd (1, 1, 100, 1); pd = fitdist (x, "BirnbaumSaunders"); [phat, pci] = bisafit (x); assert ([pd.beta, pd.gamma], phat); assert (paramci (pd), pci); ***** test x1 = bisarnd (1, 1, 100, 1); x2 = bisarnd (5, 2, 100, 1); pd = fitdist ([x1; x2], "bisa", "By", [ones(100,1); 2*ones(100,1)]); [phat, pci] = bisafit (x1); assert ([pd(1).beta, pd(1).gamma], phat); assert (paramci (pd(1)), pci); [phat, pci] = bisafit (x2); assert ([pd(2).beta, pd(2).gamma], phat); assert (paramci (pd(2)), pci); ***** test x = exprnd (1, 100, 1); pd = fitdist (x, "exponential"); [muhat, muci] = expfit (x); assert ([pd.mu], muhat); assert (paramci (pd), muci); ***** test x1 = exprnd (1, 100, 1); x2 = exprnd (5, 100, 1); pd = fitdist ([x1; x2], "exponential", "By", [ones(100,1); 2*ones(100,1)]); [muhat, muci] = expfit (x1); assert ([pd(1).mu], muhat); assert (paramci (pd(1)), muci); [muhat, muci] = expfit (x2); assert ([pd(2).mu], muhat); assert (paramci (pd(2)), muci); ***** test x = evrnd (1, 1, 100, 1); pd = fitdist (x, "ev"); [phat, pci] = evfit (x); assert ([pd.mu, pd.sigma], phat); assert (paramci (pd), pci); ***** test x1 = evrnd (1, 1, 100, 1); x2 = evrnd (5, 2, 100, 1); pd = fitdist ([x1; x2], "extremevalue", "By", [ones(100,1); 2*ones(100,1)]); [phat, pci] = evfit (x1); assert ([pd(1).mu, pd(1).sigma], phat); assert (paramci (pd(1)), pci); [phat, pci] = evfit (x2); assert ([pd(2).mu, pd(2).sigma], phat); assert (paramci (pd(2)), pci); ***** test x = gamrnd (1, 1, 100, 1); pd = fitdist (x, "Gamma"); [phat, pci] = gamfit (x); assert ([pd.a, pd.b], phat); assert (paramci (pd), pci); ***** test x1 = gamrnd (1, 1, 100, 1); x2 = gamrnd (5, 2, 100, 1); pd = fitdist ([x1; x2], "Gamma", "By", [ones(100,1); 2*ones(100,1)]); [phat, pci] = gamfit (x1); assert ([pd(1).a, pd(1).b], phat); assert (paramci (pd(1)), pci); [phat, pci] = gamfit (x2); assert ([pd(2).a, pd(2).b], phat); assert (paramci (pd(2)), pci); ***** test rand ("seed", 4); # for reproducibility x = gevrnd (-0.5, 1, 2, 1000, 1); pd = fitdist (x, "generalizedextremevalue"); [phat, pci] = gevfit (x); assert ([pd.k, pd.sigma, pd.mu], phat); assert (paramci (pd), pci); ***** test rand ("seed", 5); # for reproducibility x1 = gevrnd (-0.5, 1, 2, 1000, 1); rand ("seed", 9); # for reproducibility x2 = gevrnd (0, 1, -4, 1000, 1); pd = fitdist ([x1; x2], "gev", "By", [ones(1000,1); 2*ones(1000,1)]); [phat, pci] = gevfit (x1); assert ([pd(1).k, pd(1).sigma, pd(1).mu], phat); assert (paramci (pd(1)), pci); [phat, pci] = gevfit (x2); assert ([pd(2).k, pd(2).sigma, pd(2).mu], phat); assert (paramci (pd(2)), pci); ***** test x = gprnd (1, 1, 1, 100, 1); pd = fitdist (x, "GeneralizedPareto"); [phat, pci] = gpfit (x, 1); assert ([pd.k, pd.sigma, pd.theta], phat); assert (paramci (pd), pci); ***** test x = gprnd (1, 1, 2, 100, 1); pd = fitdist (x, "GeneralizedPareto", "theta", 2); [phat, pci] = gpfit (x, 2); assert ([pd.k, pd.sigma, pd.theta], phat); assert (paramci (pd), pci); ***** test x1 = gprnd (1, 1, 1, 100, 1); x2 = gprnd (0, 2, 1, 100, 1); pd = fitdist ([x1; x2], "gp", "By", [ones(100,1); 2*ones(100,1)]); [phat, pci] = gpfit (x1, 1); assert ([pd(1).k, pd(1).sigma, pd(1).theta], phat); assert (paramci (pd(1)), pci); [phat, pci] = gpfit (x2, 1); assert ([pd(2).k, pd(2).sigma, pd(2).theta], phat); assert (paramci (pd(2)), pci); ***** test x1 = gprnd (3, 2, 2, 100, 1); x2 = gprnd (2, 3, 2, 100, 1); pd = fitdist ([x1; x2], "GeneralizedPareto", "theta", 2, ... "By", [ones(100,1); 2*ones(100,1)]); [phat, pci] = gpfit (x1, 2); assert ([pd(1).k, pd(1).sigma, pd(1).theta], phat); assert (paramci (pd(1)), pci); [phat, pci] = gpfit (x2, 2); assert ([pd(2).k, pd(2).sigma, pd(2).theta], phat); assert (paramci (pd(2)), pci); ***** test x = hnrnd (0, 1, 100, 1); pd = fitdist (x, "HalfNormal"); [phat, pci] = hnfit (x, 0); assert ([pd.mu, pd.sigma], phat); assert (paramci (pd), pci); ***** test x = hnrnd (1, 1, 100, 1); pd = fitdist (x, "HalfNormal", "mu", 1); [phat, pci] = hnfit (x, 1); assert ([pd.mu, pd.sigma], phat); assert (paramci (pd), pci); ***** test x1 = hnrnd (0, 1, 100, 1); x2 = hnrnd (0, 2, 100, 1); pd = fitdist ([x1; x2], "HalfNormal", "By", [ones(100,1); 2*ones(100,1)]); [phat, pci] = hnfit (x1, 0); assert ([pd(1).mu, pd(1).sigma], phat); assert (paramci (pd(1)), pci); [phat, pci] = hnfit (x2, 0); assert ([pd(2).mu, pd(2).sigma], phat); assert (paramci (pd(2)), pci); ***** test x1 = hnrnd (2, 1, 100, 1); x2 = hnrnd (2, 2, 100, 1); pd = fitdist ([x1; x2], "HalfNormal", "mu", 2, ... "By", [ones(100,1); 2*ones(100,1)]); [phat, pci] = hnfit (x1, 2); assert ([pd(1).mu, pd(1).sigma], phat); assert (paramci (pd(1)), pci); [phat, pci] = hnfit (x2, 2); assert ([pd(2).mu, pd(2).sigma], phat); assert (paramci (pd(2)), pci); ***** test x = invgrnd (1, 1, 100, 1); pd = fitdist (x, "InverseGaussian"); [phat, pci] = invgfit (x); assert ([pd.mu, pd.lambda], phat); assert (paramci (pd), pci); ***** test x1 = invgrnd (1, 1, 100, 1); x2 = invgrnd (5, 2, 100, 1); pd = fitdist ([x1; x2], "InverseGaussian", "By", [ones(100,1); 2*ones(100,1)]); [phat, pci] = invgfit (x1); assert ([pd(1).mu, pd(1).lambda], phat); assert (paramci (pd(1)), pci); [phat, pci] = invgfit (x2); assert ([pd(2).mu, pd(2).lambda], phat); assert (paramci (pd(2)), pci); ***** test x = logirnd (1, 1, 100, 1); pd = fitdist (x, "logistic"); [phat, pci] = logifit (x); assert ([pd.mu, pd.sigma], phat); assert (paramci (pd), pci); ***** test x1 = logirnd (1, 1, 100, 1); x2 = logirnd (5, 2, 100, 1); pd = fitdist ([x1; x2], "logistic", "By", [ones(100,1); 2*ones(100,1)]); [phat, pci] = logifit (x1); assert ([pd(1).mu, pd(1).sigma], phat); assert (paramci (pd(1)), pci); [phat, pci] = logifit (x2); assert ([pd(2).mu, pd(2).sigma], phat); assert (paramci (pd(2)), pci); ***** test x = loglrnd (1, 1, 100, 1); pd = fitdist (x, "loglogistic"); [phat, pci] = loglfit (x); assert ([pd.mu, pd.sigma], phat); assert (paramci (pd), pci); ***** test x1 = loglrnd (1, 1, 100, 1); x2 = loglrnd (5, 2, 100, 1); pd = fitdist ([x1; x2], "loglogistic", "By", [ones(100,1); 2*ones(100,1)]); [phat, pci] = loglfit (x1); assert ([pd(1).mu, pd(1).sigma], phat); assert (paramci (pd(1)), pci); [phat, pci] = loglfit (x2); assert ([pd(2).mu, pd(2).sigma], phat); assert (paramci (pd(2)), pci); ***** test x = lognrnd (1, 1, 100, 1); pd = fitdist (x, "lognormal"); [phat, pci] = lognfit (x); assert ([pd.mu, pd.sigma], phat); assert (paramci (pd), pci); ***** test x1 = lognrnd (1, 1, 100, 1); x2 = lognrnd (5, 2, 100, 1); pd = fitdist ([x1; x2], "lognormal", "By", [ones(100,1); 2*ones(100,1)]); [phat, pci] = lognfit (x1); assert ([pd(1).mu, pd(1).sigma], phat); assert (paramci (pd(1)), pci); [phat, pci] = lognfit (x2); assert ([pd(2).mu, pd(2).sigma], phat); assert (paramci (pd(2)), pci); ***** test x = nakarnd (2, 0.5, 100, 1); pd = fitdist (x, "Nakagami"); [phat, pci] = nakafit (x); assert ([pd.mu, pd.omega], phat); assert (paramci (pd), pci); ***** test x1 = nakarnd (2, 0.5, 100, 1); x2 = nakarnd (5, 0.8, 100, 1); pd = fitdist ([x1; x2], "Nakagami", "By", [ones(100,1); 2*ones(100,1)]); [phat, pci] = nakafit (x1); assert ([pd(1).mu, pd(1).omega], phat); assert (paramci (pd(1)), pci); [phat, pci] = nakafit (x2); assert ([pd(2).mu, pd(2).omega], phat); assert (paramci (pd(2)), pci); ***** test randp ("seed", 123); randg ("seed", 321); x = nbinrnd (2, 0.5, 100, 1); pd = fitdist (x, "negativebinomial"); [phat, pci] = nbinfit (x); assert ([pd.R, pd.P], phat); assert (paramci (pd), pci); ***** test randp ("seed", 345); randg ("seed", 543); x1 = nbinrnd (2, 0.5, 100, 1); randp ("seed", 432); randg ("seed", 234); x2 = nbinrnd (5, 0.8, 100, 1); pd = fitdist ([x1; x2], "nbin", "By", [ones(100,1); 2*ones(100,1)]); [phat, pci] = nbinfit (x1); assert ([pd(1).R, pd(1).P], phat); assert (paramci (pd(1)), pci); [phat, pci] = nbinfit (x2); assert ([pd(2).R, pd(2).P], phat); assert (paramci (pd(2)), pci); ***** test x = normrnd (1, 1, 100, 1); pd = fitdist (x, "normal"); [muhat, sigmahat, muci, sigmaci] = normfit (x); assert ([pd.mu, pd.sigma], [muhat, sigmahat]); assert (paramci (pd), [muci, sigmaci]); ***** test x1 = normrnd (1, 1, 100, 1); x2 = normrnd (5, 2, 100, 1); pd = fitdist ([x1; x2], "normal", "By", [ones(100,1); 2*ones(100,1)]); [muhat, sigmahat, muci, sigmaci] = normfit (x1); assert ([pd(1).mu, pd(1).sigma], [muhat, sigmahat]); assert (paramci (pd(1)), [muci, sigmaci]); [muhat, sigmahat, muci, sigmaci] = normfit (x2); assert ([pd(2).mu, pd(2).sigma], [muhat, sigmahat]); assert (paramci (pd(2)), [muci, sigmaci]); ***** test x = poissrnd (1, 100, 1); pd = fitdist (x, "poisson"); [phat, pci] = poissfit (x); assert (pd.lambda, phat); assert (paramci (pd), pci); ***** test x1 = poissrnd (1, 100, 1); x2 = poissrnd (5, 100, 1); pd = fitdist ([x1; x2], "poisson", "By", [ones(100,1); 2*ones(100,1)]); [phat, pci] = poissfit (x1); assert (pd(1).lambda, phat); assert (paramci (pd(1)), pci); [phat, pci] = poissfit (x2); assert (pd(2).lambda, phat); assert (paramci (pd(2)), pci); ***** test x = raylrnd (1, 100, 1); pd = fitdist (x, "rayleigh"); [phat, pci] = raylfit (x); assert (pd.sigma, phat); assert (paramci (pd), pci); ***** test x1 = raylrnd (1, 100, 1); x2 = raylrnd (5, 100, 1); pd = fitdist ([x1; x2], "rayleigh", "By", [ones(100,1); 2*ones(100,1)]); [phat, pci] = raylfit (x1); assert ( pd(1).sigma, phat); assert (paramci (pd(1)), pci); [phat, pci] = raylfit (x2); assert (pd(2).sigma, phat); assert (paramci (pd(2)), pci); ***** test x = ricernd (1, 1, 100, 1); pd = fitdist (x, "rician"); [phat, pci] = ricefit (x); assert ([pd.s, pd.sigma], phat); assert (paramci (pd), pci); ***** test x1 = ricernd (1, 1, 100, 1); x2 = ricernd (5, 2, 100, 1); pd = fitdist ([x1; x2], "rician", "By", [ones(100,1); 2*ones(100,1)]); [phat, pci] = ricefit (x1); assert ([pd(1).s, pd(1).sigma], phat); assert (paramci (pd(1)), pci); [phat, pci] = ricefit (x2); assert ([pd(2).s, pd(2).sigma], phat); assert (paramci (pd(2)), pci); ***** warning ... fitdist ([1 2 3 4 5], "Stable"); ***** test x = tlsrnd (0, 1, 1, 100, 1); pd = fitdist (x, "tlocationscale"); [phat, pci] = tlsfit (x); assert ([pd.mu, pd.sigma, pd.nu], phat); assert (paramci (pd), pci); ***** test x1 = tlsrnd (0, 1, 1, 100, 1); x2 = tlsrnd (5, 2, 1, 100, 1); pd = fitdist ([x1; x2], "tlocationscale", "By", [ones(100,1); 2*ones(100,1)]); [phat, pci] = tlsfit (x1); assert ([pd(1).mu, pd(1).sigma, pd(1).nu], phat); assert (paramci (pd(1)), pci); [phat, pci] = tlsfit (x2); assert ([pd(2).mu, pd(2).sigma, pd(2).nu], phat); assert (paramci (pd(2)), pci); ***** test x = [1 2 3 4 5]; pd = fitdist (x, "weibull"); [phat, pci] = wblfit (x); assert ([pd.lambda, pd.k], phat); assert (paramci (pd), pci); ***** test x = [1 2 3 4 5 6 7 8 9 10]; pd = fitdist (x, "weibull", "By", [1 1 1 1 1 2 2 2 2 2]); [phat, pci] = wblfit (x(1:5)); assert ([pd(1).lambda, pd(1).k], phat); assert (paramci (pd(1)), pci); [phat, pci] = wblfit (x(6:10)); assert ([pd(2).lambda, pd(2).k], phat); assert (paramci (pd(2)), pci); ***** error fitdist (1) ***** error fitdist (1, ["as";"sd"]) ***** error fitdist (1, "some") ***** error ... fitdist (ones (2), "normal") ***** error ... fitdist ([i, 2, 3], "normal") ***** error ... fitdist (["a", "s", "d"], "normal") ***** error ... fitdist ([1, 2, 3], "normal", "By") ***** error ... fitdist ([1, 2, 3], "normal", "By", [1, 2]) ***** error ... fitdist ([1, 2, 3], "normal", "Censoring", [1, 2]) ***** error ... fitdist ([1, 2, 3], "normal", "frequency", [1, 2]) ***** error ... fitdist ([1, 2, 3], "negativebinomial", "frequency", [1, -2, 3]) ***** error ... fitdist ([1, 2, 3], "normal", "alpha", [1, 2]) ***** error ... fitdist ([1, 2, 3], "normal", "alpha", i) ***** error ... fitdist ([1, 2, 3], "normal", "alpha", -0.5) ***** error ... fitdist ([1, 2, 3], "normal", "alpha", 1.5) ***** error ... fitdist ([1, 2, 3], "normal", "ntrials", [1, 2]) ***** error ... fitdist ([1, 2, 3], "normal", "ntrials", 0) ***** error ... fitdist ([1, 2, 3], "normal", "options", 0) ***** error ... fitdist ([1, 2, 3], "normal", "options", struct ("options", 1)) ***** warning fitdist ([1, 2, 3], "kernel", "kernel", "normal"); ***** warning fitdist ([1, 2, 3], "kernel", "support", "positive"); ***** warning fitdist ([1, 2, 3], "kernel", "width", 1); ***** error ... fitdist ([1, 2, 3], "normal", "param", struct ("options", 1)) ***** error ... [pdca, gn, gl] = fitdist ([1, 2, 3], "normal"); ***** error ... fitdist ([1, 2, 3], "generalizedpareto", "theta", 2); ***** error ... fitdist ([1, 2, 3], "halfnormal", "mu", 2); 75 tests, 75 passed, 0 known failure, 0 skipped [inst/rmmissing.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/rmmissing.m ***** assert (rmmissing ([1,NaN,3]), [1,3]) ***** assert (rmmissing ('abcd f'), 'abcdf') ***** assert (rmmissing ({'xxx','','xyz'}), {'xxx','xyz'}) ***** assert (rmmissing ({'xxx','';'xyz','yyy'}), {'xyz','yyy'}) ***** assert (rmmissing ({'xxx','';'xyz','yyy'}, 2), {'xxx';'xyz'}) ***** assert (rmmissing ([1,2;NaN,2]), [1,2]) ***** assert (rmmissing ([1,2;NaN,2], 2), [2,2]') ***** assert (rmmissing ([1,2;NaN,4;NaN,NaN],"MinNumMissing", 2), [1,2;NaN,4]) ***** test x = [1:6]; x([2,4]) = NaN; [~, idx] = rmmissing (x); assert (idx, logical ([0, 1, 0, 1, 0, 0])); assert (class(idx), 'logical'); x = reshape (x, [2, 3]); [~, idx] = rmmissing (x); assert (idx, logical ([0; 1])); assert (class(idx), 'logical'); [~, idx] = rmmissing (x, 2); assert (idx, logical ([1, 1, 0])); assert (class(idx), 'logical'); [~, idx] = rmmissing (x, 1, "MinNumMissing", 2); assert (idx, logical ([0; 1])); assert (class(idx), 'logical'); [~, idx] = rmmissing (x, 2, "MinNumMissing", 2); assert (idx, logical ([0, 0, 0])); assert (class(idx), 'logical'); ***** assert (rmmissing (single ([1 2 NaN; 3 4 5])), single ([3 4 5])) ***** assert (rmmissing (logical (ones (3))), logical (ones (3))) ***** assert (rmmissing (int32 (ones (3))), int32 (ones (3))) ***** assert (rmmissing (uint32 (ones (3))), uint32 (ones (3))) ***** assert (rmmissing ({1, 2, 3}), {1, 2, 3}) ***** assert (rmmissing ([struct, struct, struct]), [struct, struct, struct]) ***** assert (rmmissing ([]), []) ***** assert (rmmissing (ones (1,0)), ones (1,0)) ***** assert (rmmissing (ones (1,0), 1), ones (1,0)) ***** assert (rmmissing (ones (1,0), 2), ones (1,0)) ***** assert (rmmissing (ones (0,1)), ones (0,1)) ***** assert (rmmissing (ones (0,1), 1), ones (0,1)) ***** assert (rmmissing (ones (0,1), 2), ones (0,1)) ***** error rmmissing (ones (0,1,2)) ***** error rmmissing () ***** error rmmissing (ones(2,2,2)) ***** error rmmissing ([1 2; 3 4], 5) ***** error rmmissing ([1 2; 3 4], "XXX", 1) ***** error <'MinNumMissing'> rmmissing ([1 2; 3 4], 2, "MinNumMissing", -2) ***** error <'MinNumMissing'> rmmissing ([1 2; 3 4], "MinNumMissing", 3.8) ***** error <'MinNumMissing'> rmmissing ([1 2; 3 4], "MinNumMissing", [1 2 3]) ***** error <'MinNumMissing'> rmmissing ([1 2; 3 4], "MinNumMissing", 'xxx') 31 tests, 31 passed, 0 known failure, 0 skipped [inst/pcacov.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/pcacov.m ***** demo x = [ 7 26 6 60; 1 29 15 52; 11 56 8 20; 11 31 8 47; 7 52 6 33; 11 55 9 22; 3 71 17 6; 1 31 22 44; 2 54 18 22; 21 47 4 26; 1 40 23 34; 11 66 9 12; 10 68 8 12 ]; Kxx = cov (x); [coeff, latent, explained] = pcacov (Kxx) ***** test load hald Kxx = cov (ingredients); [coeff,latent,explained] = pcacov(Kxx); c_out = [-0.0678, -0.6460, 0.5673, 0.5062; ... -0.6785, -0.0200, -0.5440, 0.4933; ... 0.0290, 0.7553, 0.4036, 0.5156; ... 0.7309, -0.1085, -0.4684, 0.4844]; l_out = [517.7969; 67.4964; 12.4054; 0.2372]; e_out = [ 86.5974; 11.2882; 2.0747; 0.0397]; assert (coeff, c_out, 1e-4); assert (latent, l_out, 1e-4); assert (explained, e_out, 1e-4); ***** error pcacov (ones (2,3)) ***** error pcacov (ones (3,3,3)) 3 tests, 3 passed, 0 known failure, 0 skipped [inst/confusionchart.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/confusionchart.m ***** demo ## Setting the chart properties Yt = [8 5 6 8 5 3 1 6 4 2 5 3 1 4]'; Yp = [8 5 6 8 5 2 3 4 4 5 5 7 2 6]'; confusionchart (Yt, Yp, "Title", ... "Demonstration with summaries","Normalization",... "absolute","ColumnSummary", "column-normalized","RowSummary",... "row-normalized") ***** demo ## Cellstr as inputs Yt = {"Positive", "Positive", "Positive", "Negative", "Negative"}; Yp = {"Positive", "Positive", "Negative", "Negative", "Negative"}; m = confusionmat (Yt, Yp); confusionchart (m, {"Positive", "Negative"}); ***** demo ## Editing the object properties Yt = {"Positive", "Positive", "Positive", "Negative", "Negative"}; Yp = {"Positive", "Positive", "Negative", "Negative", "Negative"}; cm = confusionchart (Yt, Yp); cm.Title = "This is an example with a green diagonal"; cm.DiagonalColor = [0.4660, 0.6740, 0.1880]; ***** demo ## Confusion chart in a uipanel h = uipanel (); Yt = {"Positive", "Positive", "Positive", "Negative", "Negative"}; Yp = {"Positive", "Positive", "Negative", "Negative", "Negative"}; cm = confusionchart (h, Yt, Yp); ***** demo ## Sorting classes Yt = [8 5 6 8 5 3 1 6 4 2 5 3 1 4]'; Yp = [8 5 6 8 5 2 3 4 4 5 5 7 2 6]'; cm = confusionchart (Yt, Yp, "Title", ... "Classes are sorted in ascending order"); cm = confusionchart (Yt, Yp, "Title", ... "Classes are sorted according to clusters"); sortClasses (cm, "cluster"); ***** shared visibility_setting visibility_setting = get (0, "DefaultFigureVisible"); ***** test set (0, "DefaultFigureVisible", "off"); fail ("confusionchart ()", "Invalid call"); set (0, "DefaultFigureVisible", visibility_setting); ***** test set (0, "DefaultFigureVisible", "off"); fail ("confusionchart ([1 1; 2 2; 3 3])", "invalid argument"); set (0, "DefaultFigureVisible", visibility_setting); ***** test set (0, "DefaultFigureVisible", "off"); fail ("confusionchart ([1 2], [0 1], 'xxx', 1)", "invalid property"); set (0, "DefaultFigureVisible", visibility_setting); ***** test set (0, "DefaultFigureVisible", "off"); fail ("confusionchart ([1 2], [0 1], 'XLabel', 1)", "XLabel .* string"); set (0, "DefaultFigureVisible", visibility_setting); ***** test set (0, "DefaultFigureVisible", "off"); fail ("confusionchart ([1 2], [0 1], 'YLabel', [1 0])", ... ".* YLabel .* string"); set (0, "DefaultFigureVisible", visibility_setting); ***** test set (0, "DefaultFigureVisible", "off"); fail ("confusionchart ([1 2], [0 1], 'Title', .5)", ".* Title .* string"); set (0, "DefaultFigureVisible", visibility_setting); ***** test set (0, "DefaultFigureVisible", "off"); fail ("confusionchart ([1 2], [0 1], 'FontName', [])", ... ".* FontName .* string"); set (0, "DefaultFigureVisible", visibility_setting); ***** test set (0, "DefaultFigureVisible", "off"); fail ("confusionchart ([1 2], [0 1], 'FontSize', 'b')", ... ".* FontSize .* numeric"); set (0, "DefaultFigureVisible", visibility_setting); ***** test set (0, "DefaultFigureVisible", "off"); fail ("confusionchart ([1 2], [0 1], 'DiagonalColor', 'h')", ... ".* DiagonalColor .* color"); set (0, "DefaultFigureVisible", visibility_setting); ***** test set (0, "DefaultFigureVisible", "off"); fail ("confusionchart ([1 2], [0 1], 'OffDiagonalColor', [])", ... ".* OffDiagonalColor .* color"); set (0, "DefaultFigureVisible", visibility_setting); ***** test set (0, "DefaultFigureVisible", "off"); fail ("confusionchart ([1 2], [0 1], 'Normalization', '')", ... ".* invalid .* Normalization"); set (0, "DefaultFigureVisible", visibility_setting); ***** test set (0, "DefaultFigureVisible", "off"); fail ("confusionchart ([1 2], [0 1], 'ColumnSummary', [])", ... ".* invalid .* ColumnSummary"); set (0, "DefaultFigureVisible", visibility_setting); ***** test set (0, "DefaultFigureVisible", "off"); fail ("confusionchart ([1 2], [0 1], 'RowSummary', 1)", ... ".* invalid .* RowSummary"); set (0, "DefaultFigureVisible", visibility_setting); ***** test set (0, "DefaultFigureVisible", "off"); fail ("confusionchart ([1 2], [0 1], 'GridVisible', .1)", ... ".* invalid .* GridVisible"); set (0, "DefaultFigureVisible", visibility_setting); ***** test set (0, "DefaultFigureVisible", "off"); fail ("confusionchart ([1 2], [0 1], 'HandleVisibility', .1)", ... ".* invalid .* HandleVisibility"); set (0, "DefaultFigureVisible", visibility_setting); ***** test set (0, "DefaultFigureVisible", "off"); fail ("confusionchart ([1 2], [0 1], 'OuterPosition', .1)", ... ".* invalid .* OuterPosition"); set (0, "DefaultFigureVisible", visibility_setting); ***** test set (0, "DefaultFigureVisible", "off"); fail ("confusionchart ([1 2], [0 1], 'Position', .1)", ... ".* invalid .* Position"); set (0, "DefaultFigureVisible", visibility_setting); ***** test set (0, "DefaultFigureVisible", "off"); fail ("confusionchart ([1 2], [0 1], 'Units', .1)", ".* invalid .* Units"); set (0, "DefaultFigureVisible", visibility_setting); 18 tests, 18 passed, 0 known failure, 0 skipped [inst/fillmissing.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/fillmissing.m ***** assert (fillmissing ([1 2 3], "constant", 99), [1 2 3]) ***** assert (fillmissing ([1 2 NaN], "constant", 99), [1 2 99]) ***** assert (fillmissing ([NaN 2 NaN], "constant", 99), [99 2 99]) ***** assert (fillmissing ([1 2 3]', "constant", 99), [1 2 3]') ***** assert (fillmissing ([1 2 NaN]', "constant", 99), [1 2 99]') ***** assert (fillmissing ([1 2 3; 4 5 6], "constant", 99), [1 2 3; 4 5 6]) ***** assert (fillmissing ([1 2 NaN; 4 NaN 6], "constant", 99), [1 2 99; 4 99 6]) ***** assert (fillmissing ([NaN 2 NaN; 4 NaN 6], "constant", [97, 98, 99]), [97 2 99; 4 98 6]) ***** test x = cat (3, [1, 2, NaN; 4, NaN, 6], [NaN, 2, 3; 4, 5, NaN]); y = cat (3, [1, 2, 99; 4, 99, 6], [99, 2, 3; 4, 5, 99]); assert (fillmissing (x, "constant", 99), y); y = cat (3, [1, 2, 96; 4, 95, 6], [97, 2, 3; 4, 5, 99]); assert (fillmissing (x, "constant", [94:99]), y); assert (fillmissing (x, "constant", [94:99]'), y); assert (fillmissing (x, "constant", permute ([94:99], [1 3 2])), y); assert (fillmissing (x, "constant", [94, 96, 98; 95, 97, 99]), y); assert (fillmissing (x, "constant", [94:99], 1), y); y = cat (3, [1, 2, 96; 4, 97, 6], [98, 2, 3; 4, 5, 99]); assert (fillmissing (x, "constant", [96:99], 2), y); y = cat (3, [1, 2, 98; 4, 97, 6], [94, 2, 3; 4, 5, 99]); assert (fillmissing (x, "constant", [94:99], 3), y); y = cat (3, [1, 2, 92; 4, 91, 6], [94, 2, 3; 4, 5, 99]); assert (fillmissing (x, "constant", [88:99], 99), y); ***** test x = reshape([1:24],4,3,2); x([1, 6, 7, 9, 12, 14, 16, 19, 22, 23]) = NaN; y = x; y([1,6,7,9 12, 14, 16, 19, 22, 23]) = [94 95 95 96 96 97 97 98 99 99]; assert (fillmissing (x, "constant", [94:99], 1), y); y([1,6,7,9 12, 14, 16, 19, 22, 23]) = [92 93 94 92 95 97 99 98 97 98]; assert (fillmissing (x, "constant", [92:99], 2), y); y([1,6,7,9 12, 14, 16, 19, 22, 23]) = [88 93 94 96 99 89 91 94 97 98]; assert (fillmissing (x, "constant", [88:99], 3), y); y([1,6,7,9 12, 14, 16, 19, 22, 23]) = [76 81 82 84 87 89 91 94 97 98]; assert (fillmissing (x, "constant", [76:99], 99), y); ***** assert (fillmissing ([1 2 3], "constant", 99, "endvalues", 88), [1 2 3]) ***** assert (fillmissing ([1 NaN 3], "constant", 99, "endvalues", 88), [1 99 3]) ***** assert (fillmissing ([1 2 NaN], "constant", 99, "endvalues", 88), [1 2 88]) ***** assert (fillmissing ([NaN 2 3], "constant", 99, "endvalues", 88), [88 2 3]) ***** assert (fillmissing ([NaN NaN 3], "constant", 99, "endvalues", 88), [88 88 3]) ***** assert (fillmissing ([1 NaN NaN], "constant", 99, "endvalues", 88), [1 88 88]) ***** assert (fillmissing ([NaN 2 NaN], "constant", 99, "endvalues", 88), [88 2 88]) ***** assert (fillmissing ([NaN 2 NaN]', "constant", 99, "endvalues", 88), [88 2 88]') ***** assert (fillmissing ([1 NaN 3 NaN 5], "constant", 99, "endvalues", 88), [1 99 3 99 5]) ***** assert (fillmissing ([1 NaN NaN NaN 5], "constant", 99, "endvalues", 88), [1 99 99 99 5]) ***** assert (fillmissing ([NaN NaN NaN NaN 5], "constant", 99, "endvalues", 88), [88 88 88 88 5]) ***** assert (fillmissing ([1 NaN 3 4 NaN], "constant", 99, "endvalues", 88), [1 99 3 4 88]) ***** assert (fillmissing ([1 NaN 3 4 NaN], "constant", 99, 1, "endvalues", 88), [1 88 3 4 88]) ***** assert (fillmissing ([1 NaN 3 4 NaN], "constant", 99, 1, "endvalues", "extrap"), [1 99 3 4 99]) ***** test x = reshape ([1:24], 3, 4, 2); y = x; x([1,2,5,6,8,10,13,16,18,19,20,21,22]) = NaN; y([1,2,5,6,10,13,16,18,19,20,21,22])= 88; y([8])=99; assert (fillmissing (x, "constant", 99, "endvalues", 88), y); assert (fillmissing (x, "constant", 99, 1, "endvalues", 88), y); y = x; y([1,2,5,8,10,13,16,19,22])= 88; y([6,18,20,21])=99; assert (fillmissing (x, "constant", 99, 2, "endvalues", 88), y); y(y==99) = 88; assert (fillmissing (x, "constant", 99, 3, "endvalues", 88), y); assert (fillmissing (x, "constant", 99, 4, "endvalues", 88), y); assert (fillmissing (x, "constant", 99, 99, "endvalues", 88), y); y([8]) = 94; assert (fillmissing (x, "constant", [92:99], 1, "endvalues", 88), y); y([6,8,18,20,21]) = [96,88,99,98,99]; assert (fillmissing (x, "constant", [94:99], 2, "endvalues", 88), y); y = x; y(isnan(y)) = 88; assert (fillmissing (x, "constant", [88:99], 3, "endvalues", 88), y); y = x; y(isnan(y)) = [82,82,83,83,94,85,86,87,87,88,88,88,89]; assert (fillmissing (x, "constant", [92:99], 1, "endvalues", [82:89]), y); y = x; y(isnan(y)) = [84,85,85,96,85,84,87,87,99,87,98,99,87]; assert (fillmissing (x, "constant", [94:99], 2, "endvalues", [84:89]), y); y = x; y(isnan(y)) = [68,69,72,73,75,77,68,71,73,74,75,76,77]; assert (fillmissing (x, "constant", [88:99], 3, "endvalues", [68:79]), y); assert (fillmissing (x, "constant", [88:93;94:99]', 3, "endvalues", [68:73;74:79]'), y) ***** test x = reshape([1:24],4,3,2); x([1, 6, 7, 9, 12, 14, 16, 19, 22, 23]) = NaN; y = x; y([1,6,7,9 12, 14, 16, 19, 22, 23]) = [94 95 95 96 96 97 97 98 99 99]; assert (fillmissing (x, "constant", [94:99], 1), y); y([1,6,7,9 12, 14, 16, 19, 22, 23]) = [92 93 94 92 95 97 99 98 97 98]; assert (fillmissing (x, "constant", [92:99], 2), y); y([1,6,7,9 12, 14, 16, 19, 22, 23]) = [88 93 94 96 99 89 91 94 97 98]; assert (fillmissing (x, "constant", [88:99], 3), y); y([1,6,7,9 12, 14, 16, 19, 22, 23]) = [76 81 82 84 87 89 91 94 97 98]; assert (fillmissing (x, "constant", [76:99], 99), y); ***** assert (fillmissing ([1 2 3], "previous"), [1 2 3]) ***** assert (fillmissing ([1 2 3], "next"), [1 2 3]) ***** assert (fillmissing ([1 2 3]', "previous"), [1 2 3]') ***** assert (fillmissing ([1 2 3]', "next"), [1 2 3]') ***** assert (fillmissing ([1 2 NaN], "previous"), [1 2 2]) ***** assert (fillmissing ([1 2 NaN], "next"), [1 2 NaN]) ***** assert (fillmissing ([NaN 2 NaN], "previous"), [NaN 2 2]) ***** assert (fillmissing ([NaN 2 NaN], "next"), [2 2 NaN]) ***** assert (fillmissing ([1 NaN 3], "previous"), [1 1 3]) ***** assert (fillmissing ([1 NaN 3], "next"), [1 3 3]) ***** assert (fillmissing ([1 2 NaN; 4 NaN 6], "previous", 1), [1 2 NaN; 4 2 6]) ***** assert (fillmissing ([1 2 NaN; 4 NaN 6], "previous", 2), [1 2 2; 4 4 6]) ***** assert (fillmissing ([1 2 NaN; 4 NaN 6], "previous", 3), [1 2 NaN; 4 NaN 6]) ***** assert (fillmissing ([1 2 NaN; 4 NaN 6], "next", 1), [1 2 6; 4 NaN 6]) ***** assert (fillmissing ([1 2 NaN; 4 NaN 6], "next", 2), [1 2 NaN; 4 6 6]) ***** assert (fillmissing ([1 2 NaN; 4 NaN 6], "next", 3), [1 2 NaN; 4 NaN 6]) ***** test x = reshape([1:24],4,3,2); x([1, 6, 7, 9, 12, 14, 16, 19, 22, 23]) = NaN; y = x; y([1, 6, 7, 9, 14, 19, 22, 23]) = [2 8 8 10 15 20 24 24]; assert (fillmissing (x, "next", 1), y); y = x; y([1, 6, 7, 14, 16]) = [5, 10, 11, 18, 20]; assert (fillmissing (x, "next", 2), y); y = x; y([1, 6, 9, 12]) = [13 18 21 24]; assert (fillmissing (x, "next", 3), y); assert (fillmissing (x, "next", 99), x); y = x; y([6, 7, 12, 14, 16, 19, 22, 23]) = [5 5 11 13 15 18 21 21]; assert (fillmissing (x, "previous", 1), y); y = x; y([6, 7, 9, 12, 19, 22, 23]) = [2 3 5 8 15 18 15]; assert (fillmissing (x, "previous", 2), y); y = x; y([14, 16, 22, 23]) = [2 4 10 11]; assert (fillmissing (x, "previous", 3), y); assert (fillmissing (x, "previous", 99), x); ***** assert (fillmissing ([1 2 3], "constant", 0, "endvalues", "previous"), [1 2 3]) ***** assert (fillmissing ([1 2 3], "constant", 0, "endvalues", "next"), [1 2 3]) ***** assert (fillmissing ([1 NaN 3], "constant", 0, "endvalues", "previous"), [1 0 3]) ***** assert (fillmissing ([1 NaN 3], "constant", 0, "endvalues", "next"), [1 0 3]) ***** assert (fillmissing ([1 2 NaN], "constant", 0, "endvalues", "previous"), [1 2 2]) ***** assert (fillmissing ([1 2 NaN], "constant", 0, "endvalues", "next"), [1 2 NaN]) ***** assert (fillmissing ([1 NaN NaN], "constant", 0, "endvalues", "previous"), [1 1 1]) ***** assert (fillmissing ([1 NaN NaN], "constant", 0, "endvalues", "next"), [1 NaN NaN]) ***** assert (fillmissing ([NaN 2 3], "constant", 0, "endvalues", "previous"), [NaN 2 3]) ***** assert (fillmissing ([NaN 2 3], "constant", 0, "endvalues", "next"), [2 2 3]) ***** assert (fillmissing ([NaN NaN 3], "constant", 0, "endvalues", "previous"), [NaN NaN 3]) ***** assert (fillmissing ([NaN NaN 3], "constant", 0, "endvalues", "next"), [3 3 3]) ***** assert (fillmissing ([NaN NaN NaN], "constant", 0, "endvalues", "previous"), [NaN NaN NaN]) ***** assert (fillmissing ([NaN NaN NaN], "constant", 0, "endvalues", "next"), [NaN NaN NaN]) ***** assert (fillmissing ([NaN 2 NaN 4 NaN], "constant", 0, "endvalues", "previous"), [NaN 2 0 4 4]) ***** assert (fillmissing ([NaN 2 NaN 4 NaN], "constant", 0, "endvalues", "next"), [2 2 0 4 NaN]) ***** assert (fillmissing ([NaN 2 NaN 4 NaN], "constant", 0, 1, "endvalues", "previous"), [NaN 2 NaN 4 NaN]) ***** assert (fillmissing ([NaN 2 NaN 4 NaN], "constant", 0, 1, "endvalues", "next"), [NaN 2 NaN 4 NaN]) ***** assert (fillmissing ([NaN 2 NaN 4 NaN], "constant", 0, 2, "endvalues", "previous"), [NaN 2 0 4 4]) ***** assert (fillmissing ([NaN 2 NaN 4 NaN], "constant", 0, 2, "endvalues", "next"), [2 2 0 4 NaN]) ***** assert (fillmissing ([NaN 2 NaN 4 NaN], "constant", 0, 3, "endvalues", "previous"), [NaN 2 NaN 4 NaN]) ***** assert (fillmissing ([NaN 2 NaN 4 NaN], "constant", 0, 3, "endvalues", "next"), [NaN 2 NaN 4 NaN]) ***** test x = reshape ([1:24], 3, 4, 2); x([1,2,5,6,8,10,13,16,18,19,20,21,22]) = NaN; y = x; y([5,6,8,18])=[4,4,0,17]; assert (fillmissing (x, "constant", 0, "endvalues", "previous"), y); assert (fillmissing (x, "constant", 0, 1, "endvalues", "previous"), y); y = x; y([6,10,18,20,21])=[0,7,0,0,0]; assert (fillmissing (x, "constant", 0, 2, "endvalues", "previous"), y); y = x; y([16,19,21])=[4,7,9]; assert (fillmissing (x, "constant", 0, 3, "endvalues", "previous"), y); assert (fillmissing (x, "constant", 0, 4, "endvalues", "previous"), x); assert (fillmissing (x, "constant", 0, 99, "endvalues", "previous"), x); y = x; y([1,2,8,10,13,16,22])=[3,3,0,11,14,17,23]; assert (fillmissing (x, "constant", 0, "endvalues", "next"), y); assert (fillmissing (x, "constant", 0, 1, "endvalues", "next"), y); y = x; y([1,2,5,6,8,18,20,21])=[4,11,11,0,11,0,0,0]; assert (fillmissing (x, "constant", 0, 2, "endvalues", "next"), y); y = x; y([2,5])=[14,17]; assert (fillmissing (x, "constant", 0, 3, "endvalues", "next"), y); assert (fillmissing (x, "constant", 0, 4, "endvalues", "next"), x); assert (fillmissing (x, "constant", 0, 99, "endvalues", "next"), x); ***** assert (fillmissing ([1 2 3], "nearest"), [1 2 3]) ***** assert (fillmissing ([1 2 3]', "nearest"), [1 2 3]') ***** assert (fillmissing ([1 2 NaN], "nearest"), [1 2 2]) ***** assert (fillmissing ([NaN 2 NaN], "nearest"), [2 2 2]) ***** assert (fillmissing ([1 NaN 3], "nearest"), [1 3 3]) ***** assert (fillmissing ([1 2 NaN; 4 NaN 6], "nearest", 1), [1 2 6; 4 2 6]) ***** assert (fillmissing ([1 2 NaN; 4 NaN 6], "nearest", 2), [1 2 2; 4 6 6]) ***** assert (fillmissing ([1 2 NaN; 4 NaN 6], "nearest", 3), [1 2 NaN; 4 NaN 6]) ***** assert (fillmissing ([1 NaN 3 NaN 5], "nearest"), [1 3 3 5 5]) ***** assert (fillmissing ([1 NaN 3 NaN 5], "nearest", "samplepoints", [0 1 2 3 4]), [1 3 3 5 5]) ***** assert (fillmissing ([1 NaN 3 NaN 5], "nearest", "samplepoints", [0.5 1 2 3 5]), [1 1 3 3 5]) ***** test x = reshape([1:24],4,3,2); x([1, 6, 7, 9, 12, 14, 16, 19, 22, 23]) = NaN; y = x; y([1, 6, 7, 9, 12, 14, 16, 19, 22, 23]) = [2 5 8 10 11 15 15 20 21 24]; assert (fillmissing (x, "nearest", 1), y); y = x; y([1, 6, 7, 9, 12, 14, 16, 19, 22, 23]) = [5 10 11 5 8 18 20 15 18 15]; assert (fillmissing (x, "nearest", 2), y); y = x; y([1, 6, 9, 12, 14, 16, 22, 23]) = [13 18 21 24 2 4 10 11]; assert (fillmissing (x, "nearest", 3), y); assert (fillmissing (x, "nearest", 99), x); ***** assert (fillmissing ([1 2 3], "constant", 0, "endvalues", "nearest"), [1 2 3]) ***** assert (fillmissing ([1 NaN 3], "constant", 0, "endvalues", "nearest"), [1 0 3]) ***** assert (fillmissing ([1 2 NaN], "constant", 0, "endvalues", "nearest"), [1 2 2]) ***** assert (fillmissing ([1 NaN NaN], "constant", 0, "endvalues", "nearest"), [1 1 1]) ***** assert (fillmissing ([NaN 2 3], "constant", 0, "endvalues", "nearest"), [2 2 3]) ***** assert (fillmissing ([NaN NaN 3], "constant", 0, "endvalues", "nearest"), [3 3 3]) ***** assert (fillmissing ([NaN NaN NaN], "constant", 0, "endvalues", "nearest"), [NaN NaN NaN]) ***** assert (fillmissing ([NaN 2 NaN 4 NaN], "constant", 0, "endvalues", "nearest"), [2 2 0 4 4]) ***** assert (fillmissing ([NaN 2 NaN 4 NaN], "constant", 0, 1, "endvalues", "nearest"), [NaN 2 NaN 4 NaN]) ***** assert (fillmissing ([NaN 2 NaN 4 NaN], "constant", 0, 2, "endvalues", "nearest"), [2 2 0 4 4]) ***** assert (fillmissing ([NaN 2 NaN 4 NaN], "constant", 0, 3, "endvalues", "nearest"), [NaN 2 NaN 4 NaN]) ***** test x = reshape ([1:24], 3, 4, 2); x([1,2,5,6,8,10,13,16,18,19,20,21,22]) = NaN; y = x; y([1,2,5,6,8,10,13,16,18,22])=[3 3 4 4 0 11 14 17 17 23]; assert (fillmissing (x, "constant", 0, "endvalues", "nearest"), y); assert (fillmissing (x, "constant", 0, 1, "endvalues", "nearest"), y); y = x; y([1,2,5,6,8,10,18,20,21])=[4 11 11 0 11 7 0 0 0]; assert (fillmissing (x, "constant", 0, 2, "endvalues", "nearest"), y); y = x; y([2,5,16,19,21])=[14 17 4 7 9]; assert (fillmissing (x, "constant", 0, 3, "endvalues", "nearest"), y); assert (fillmissing (x, "constant", 0, 99, "endvalues", "nearest"), x); ***** assert (fillmissing ([1 2 3], "linear"), [1 2 3]) ***** assert (fillmissing ([1 2 3]', "linear"), [1 2 3]') ***** assert (fillmissing ([1 2 NaN], "linear"), [1 2 3]) ***** assert (fillmissing ([NaN 2 NaN], "linear"), [NaN 2 NaN]) ***** assert (fillmissing ([1 NaN 3], "linear"), [1 2 3]) ***** assert (fillmissing ([1 2 NaN; 4 NaN 6], "linear", 1), [1 2 NaN; 4 NaN 6]) ***** assert (fillmissing ([1 2 NaN; 4 NaN 6], "linear", 2), [1 2 3; 4 5 6]) ***** assert (fillmissing ([1 2 NaN; 4 NaN 6], "linear", 3), [1 2 NaN; 4 NaN 6]) ***** assert (fillmissing ([1 NaN 3 NaN 5], "linear"), [1 2 3 4 5]) ***** assert (fillmissing ([1 NaN 3 NaN 5], "linear", "samplepoints", [0 1 2 3 4]), [1 2 3 4 5]) ***** assert (fillmissing ([1 NaN 3 NaN 5], "linear", "samplepoints", [0 1.5 2 5 14]), [1 2.5 3 3.5 5], eps) ***** test x = reshape([1:24],4,3,2); x([1, 6, 7, 9, 12, 14, 16, 19, 22, 23]) = NaN; assert (fillmissing (x, "linear", 1), reshape([1:24],4,3,2)); y = reshape([1:24],4,3,2); y([1 9 14 19 22 23]) = NaN; assert (fillmissing (x, "linear", 2), y); y = reshape([1:24],4,3,2); y([1, 6, 7, 9, 12, 14, 16, 19, 22, 23]) = NaN; assert (fillmissing (x, "linear", 3), y); assert (fillmissing (x, "linear", 99), x); ***** assert (fillmissing ([1 2 3], "linear", "endvalues", 0), [1 2 3]) ***** assert (fillmissing ([1 NaN 3], "linear", "endvalues", 0), [1 2 3]) ***** assert (fillmissing ([1 2 NaN], "linear", "endvalues", 0), [1 2 0]) ***** assert (fillmissing ([1 NaN NaN], "linear", "endvalues", 0), [1 0 0]) ***** assert (fillmissing ([NaN 2 3], "linear", "endvalues", 0), [0 2 3]) ***** assert (fillmissing ([NaN NaN 3], "linear", "endvalues", 0), [0 0 3]) ***** assert (fillmissing ([NaN NaN NaN], "linear", "endvalues", 0), [0 0 0]) ***** assert (fillmissing ([NaN 2 NaN 4 NaN], "linear", "endvalues", 0), [0 2 3 4 0]) ***** assert (fillmissing ([NaN 2 NaN 4 NaN], "linear", 1, "endvalues", 0), [0 2 0 4 0]) ***** assert (fillmissing ([NaN 2 NaN 4 NaN], "linear", 2, "endvalues", 0), [0 2 3 4 0]) ***** assert (fillmissing ([NaN 2 NaN 4 NaN], "linear", 3, "endvalues", 0), [0 2 0 4 0]) ***** test x = reshape ([1:24], 3, 4, 2); x([1,2,5,6,8,10,13,16,18,19,20,21,22]) = NaN; y = x; y([1,2,5,6,10,13,16,18,19,20,21,22])=0; y(8)=8; assert (fillmissing (x, "linear", "endvalues", 0), y); assert (fillmissing (x, "linear", 1, "endvalues", 0), y); y = x; y([1,2,5,8,10,13,16,19,22])=0; y([6,18,20,21])=[6,18,20,21]; assert (fillmissing (x, "linear", 2, "endvalues", 0), y); y = x; y(isnan(y))=0; assert (fillmissing (x, "linear", 3, "endvalues", 0), y); assert (fillmissing (x, "linear", 99, "endvalues", 0), y); ***** assert (fillmissing ([1 2 3], "constant", 99, "endvalues", "linear"), [1 2 3]) ***** assert (fillmissing ([1 NaN 3], "constant", 99, "endvalues", "linear"), [1 99 3]) ***** assert (fillmissing ([1 NaN 3 NaN], "constant", 99, "endvalues", "linear"), [1 99 3 4]) ***** assert (fillmissing ([NaN 2 NaN 4 NaN], "constant", 99, "endvalues", "linear"), [1 2 99 4 5]) ***** assert (fillmissing ([NaN 2 NaN NaN], "constant", 99, "endvalues", "linear"), [NaN 2 NaN NaN]) ***** assert (fillmissing ([NaN 2 NaN 4 NaN], "constant", 99, "endvalues", "linear", "samplepoints", [1 2 3 4 5]), [1 2 99 4 5]) ***** assert (fillmissing ([NaN 2 NaN 4 NaN], "constant", 99, "endvalues", "linear", "samplepoints", [0 2 3 4 10]), [0 2 99 4 10]) x = reshape ([1:24], 3, 4, 2); x([1,2,5,6,8,10,13,16,18,19,20,21,22]) = NaN; y = x; y([1,6,10,18,20,21]) = [2.5, 5, 8.5, 17.25, 21, 21.75]; assert (fillmissing (x, "linear", 2, "samplepoints", [2 4 8 10]), y, eps); y([1,6,10,18,20,21]) = [2.5, 4.5, 8.5, 17.25, 21.5, 21.75]; assert (fillmissing (x, "spline", 2, "samplepoints", [2 4 8 10]), y, eps); y([1,6,10,18,20,21]) = [2.5, 4.559386973180077, 8.5, 17.25, 21.440613026819925, 21.75]; assert (fillmissing (x, "pchip", 2, "samplepoints", [2 4 8 10]), y, 10*eps); ***** test <60965> x = reshape ([1:24], 3, 4, 2); x([1,2,5,6,8,10,13,16,18,19,20,21,22]) = NaN; y = x; y([1,6,10,18,20,21]) = [2.5, 4.609523809523809, 8.5, 17.25, 21.390476190476186, 21.75]; assert (fillmissing (x, "makima", 2, "samplepoints", [2 4 8 10]), y, 10*eps); !!!!! known bug: https://octave.org/testfailure/?60965 interp1: invalid METHOD 'makima' ***** assert (fillmissing ([1 2 3], "constant", 99, "endvalues", "spline"), [1 2 3]) ***** assert (fillmissing ([1 NaN 3], "constant", 99, "endvalues", "spline"), [1 99 3]) ***** assert (fillmissing ([1 NaN 3 NaN], "constant", 99, "endvalues", "spline"), [1 99 3 4]) ***** assert (fillmissing ([NaN 2 NaN 4 NaN], "constant", 99, "endvalues", "spline"), [1 2 99 4 5]) ***** assert (fillmissing ([NaN 2 NaN NaN], "constant", 99, "endvalues", "spline"), [NaN 2 NaN NaN]) ***** assert (fillmissing ([NaN 2 NaN 4 NaN], "constant", 99, "endvalues", "spline", "samplepoints", [1 2 3 4 5]), [1 2 99 4 5]) ***** assert (fillmissing ([NaN 2 NaN 4 NaN], "constant", 99, "endvalues", "spline", "samplepoints", [0 2 3 4 10]), [0 2 99 4 10]) ***** assert (fillmissing ([1 2 3], "movmean", 1), [1 2 3]) ***** assert (fillmissing ([1 2 NaN], "movmean", 1), [1 2 NaN]) ***** assert (fillmissing ([1 2 3], "movmean", 2), [1 2 3]) ***** assert (fillmissing ([1 2 3], "movmean", [1 0]), [1 2 3]) ***** assert (fillmissing ([1 2 3]', "movmean", 2), [1 2 3]') ***** assert (fillmissing ([1 2 NaN], "movmean", 2), [1 2 2]) ***** assert (fillmissing ([1 2 NaN], "movmean", [1 0]), [1 2 2]) ***** assert (fillmissing ([1 2 NaN], "movmean", [1 0]'), [1 2 2]) ***** assert (fillmissing ([NaN 2 NaN], "movmean", 2), [NaN 2 2]) ***** assert (fillmissing ([NaN 2 NaN], "movmean", [1 0]), [NaN 2 2]) ***** assert (fillmissing ([NaN 2 NaN], "movmean", [0 1]), [2 2 NaN]) ***** assert (fillmissing ([NaN 2 NaN], "movmean", [0 1.1]), [2 2 NaN]) ***** assert (fillmissing ([1 NaN 3 NaN 5], "movmean", [3 0]), [1 1 3 2 5]) ***** assert (fillmissing ([1 2 NaN; 4 NaN 6], "movmean", 3, 1), [1 2 6; 4 2 6]) ***** assert (fillmissing ([1 2 NaN; 4 NaN 6], "movmean", 3, 2), [1 2 2; 4 5 6]) ***** assert (fillmissing ([1 2 NaN; 4 NaN 6], "movmean", 3, 3), [1 2 NaN; 4 NaN 6]) ***** assert (fillmissing ([1 NaN 3 NaN 5], "movmean", 99), [1 3 3 3 5]) ***** assert (fillmissing ([1 NaN 3 NaN 5], "movmean", 99, 1), [1 NaN 3 NaN 5]) ***** assert (fillmissing ([1 NaN 3 NaN 5]', "movmean", 99, 1), [1 3 3 3 5]') ***** assert (fillmissing ([1 NaN 3 NaN 5], "movmean", 99, 2), [1 3 3 3 5]) ***** assert (fillmissing ([1 NaN 3 NaN 5]', "movmean", 99, 2), [1 NaN 3 NaN 5]') ***** assert (fillmissing ([1 NaN NaN NaN 5], "movmean", 3, "samplepoints", [1 2 3 4 5]), [1 1 NaN 5 5]) ***** assert (fillmissing ([1 NaN NaN NaN 5], "movmean", [1 1], "samplepoints", [1 2 3 4 5]), [1 1 NaN 5 5]) ***** assert (fillmissing ([1 NaN NaN NaN 5], "movmean", [1.5 1.5], "samplepoints", [1 2 3 4 5]), [1 1 NaN 5 5]) ***** assert (fillmissing ([1 NaN NaN NaN 5], "movmean", 4, "samplepoints", [1 2 3 4 5]), [1 1 1 5 5]) ***** assert (fillmissing ([1 NaN NaN NaN 5], "movmean", [2 2], "samplepoints", [1 2 3 4 5]), [1 1 3 5 5]) ***** assert (fillmissing ([1 NaN NaN NaN 5], "movmean", 4.0001, "samplepoints", [1 2 3 4 5]), [1 1 3 5 5]) ***** assert (fillmissing ([1 NaN NaN NaN 5], "movmean", 3, "samplepoints", [1.5 2 3 4 5]), [1 1 1 5 5]) ***** assert (fillmissing ([1 NaN NaN NaN 5], "movmean", 3, "samplepoints", [1 2 3 4 4.5]), [1 1 NaN 5 5]) ***** assert (fillmissing ([1 NaN NaN NaN 5], "movmean", 3, "samplepoints", [1.5 2 3 4 4.5]), [1 1 1 5 5]) ***** assert (fillmissing ([1 NaN NaN NaN 5], "movmean", [1.5 1.5], "samplepoints", [1.5 2 3 4 5]), [1 1 1 5 5]) ***** assert (fillmissing ([1 NaN NaN NaN 5], "movmean", [1.5 1.5], "samplepoints", [1 2 3 4 4.5]), [1 1 5 5 5]) ***** assert (fillmissing ([1 NaN NaN NaN 5], "movmean", [1.5 1.5], "samplepoints", [1.5 2 3 4 4.5]), [1 1 3 5 5]) ***** test x = reshape ([1:24], 3, 4, 2); x([1,2,5,6,8,10,13,16,18,19,20,21,22]) = NaN; y = x; y([2,5,8,10,13,16,18,22]) = [3,4,8,11,14,17,17,23]; assert (fillmissing (x, "movmean", 3), y); assert (fillmissing (x, "movmean", [1 1]), y); assert (fillmissing (x, "movmean", 3, "endvalues", "extrap"), y); assert (fillmissing (x, "movmean", 3, "samplepoints", [1 2 3]), y); y = x; y([1,6,8,10,18,20,21]) = [4,6,11,7,15,20,24]; assert (fillmissing (x, "movmean", 3, 2), y); assert (fillmissing (x, "movmean", [1 1], 2), y); assert (fillmissing (x, "movmean", 3, 2, "endvalues", "extrap"), y); assert (fillmissing (x, "movmean", 3, 2, "samplepoints", [1 2 3 4]), y); y([1,18]) = NaN; y(6) = 9; assert (fillmissing (x, "movmean", 3, 2, "samplepoints", [0 2 3 4]), y); y = x; y([1,2,5,6,10,13,16,18,19,20,21,22]) = 99; y(8) = 8; assert (fillmissing (x, "movmean", 3, "endvalues", 99), y); y = x; y([1,2,5,8,10,13,16,19,22]) = 99; y([6,18,20,21]) = [6,15,20,24]; assert (fillmissing (x, "movmean", 3, 2, "endvalues", 99), y); ***** assert (fillmissing ([1 2 3], "movmedian", 1), [1 2 3]) ***** assert (fillmissing ([1 2 NaN], "movmedian", 1), [1 2 NaN]) ***** assert (fillmissing ([1 2 3], "movmedian", 2), [1 2 3]) ***** assert (fillmissing ([1 2 3], "movmedian", [1 0]), [1 2 3]) ***** assert (fillmissing ([1 2 3]', "movmedian", 2), [1 2 3]') ***** assert (fillmissing ([1 2 NaN], "movmedian", 2), [1 2 2]) ***** assert (fillmissing ([1 2 NaN], "movmedian", [1 0]), [1 2 2]) ***** assert (fillmissing ([1 2 NaN], "movmedian", [1 0]'), [1 2 2]) ***** assert (fillmissing ([NaN 2 NaN], "movmedian", 2), [NaN 2 2]) ***** assert (fillmissing ([NaN 2 NaN], "movmedian", [1 0]), [NaN 2 2]) ***** assert (fillmissing ([NaN 2 NaN], "movmedian", [0 1]), [2 2 NaN]) ***** assert (fillmissing ([NaN 2 NaN], "movmedian", [0 1.1]), [2 2 NaN]) ***** assert (fillmissing ([1 NaN 3 NaN 5], "movmedian", [3 0]), [1 1 3 2 5]) ***** assert (fillmissing ([1 2 NaN; 4 NaN 6], "movmedian", 3, 1), [1 2 6; 4 2 6]) ***** assert (fillmissing ([1 2 NaN; 4 NaN 6], "movmedian", 3, 2), [1 2 2; 4 5 6]) ***** assert (fillmissing ([1 2 NaN; 4 NaN 6], "movmedian", 3, 3), [1 2 NaN; 4 NaN 6]) ***** assert (fillmissing ([1 NaN 3 NaN 5], "movmedian", 99), [1 3 3 3 5]) ***** assert (fillmissing ([1 NaN 3 NaN 5], "movmedian", 99, 1), [1 NaN 3 NaN 5]) ***** assert (fillmissing ([1 NaN 3 NaN 5]', "movmedian", 99, 1), [1 3 3 3 5]') ***** assert (fillmissing ([1 NaN 3 NaN 5], "movmedian", 99, 2), [1 3 3 3 5]) ***** assert (fillmissing ([1 NaN 3 NaN 5]', "movmedian", 99, 2), [1 NaN 3 NaN 5]') ***** assert (fillmissing ([1 NaN NaN NaN 5], "movmedian", 3, "samplepoints", [1 2 3 4 5]), [1 1 NaN 5 5]) ***** assert (fillmissing ([1 NaN NaN NaN 5], "movmedian", [1 1], "samplepoints", [1 2 3 4 5]), [1 1 NaN 5 5]) ***** assert (fillmissing ([1 NaN NaN NaN 5], "movmedian", [1.5 1.5], "samplepoints", [1 2 3 4 5]), [1 1 NaN 5 5]) ***** assert (fillmissing ([1 NaN NaN NaN 5], "movmedian", 4, "samplepoints", [1 2 3 4 5]), [1 1 1 5 5]) ***** assert (fillmissing ([1 NaN NaN NaN 5], "movmedian", [2 2], "samplepoints", [1 2 3 4 5]), [1 1 3 5 5]) ***** assert (fillmissing ([1 NaN NaN NaN 5], "movmedian", 4.0001, "samplepoints", [1 2 3 4 5]), [1 1 3 5 5]) ***** assert (fillmissing ([1 NaN NaN NaN 5], "movmedian", 3, "samplepoints", [1.5 2 3 4 5]), [1 1 1 5 5]) ***** assert (fillmissing ([1 NaN NaN NaN 5], "movmedian", 3, "samplepoints", [1 2 3 4 4.5]), [1 1 NaN 5 5]) ***** assert (fillmissing ([1 NaN NaN NaN 5], "movmedian", 3, "samplepoints", [1.5 2 3 4 4.5]), [1 1 1 5 5]) ***** assert (fillmissing ([1 NaN NaN NaN 5], "movmedian", [1.5 1.5], "samplepoints", [1.5 2 3 4 5]), [1 1 1 5 5]) ***** assert (fillmissing ([1 NaN NaN NaN 5], "movmedian", [1.5 1.5], "samplepoints", [1 2 3 4 4.5]), [1 1 5 5 5]) ***** assert (fillmissing ([1 NaN NaN NaN 5], "movmedian", [1.5 1.5], "samplepoints", [1.5 2 3 4 4.5]), [1 1 3 5 5]) ***** test x = reshape ([1:24], 3, 4, 2); x([1,2,5,6,8,10,13,16,18,19,20,21,22]) = NaN; y = x; y([2 5 8 10 13 16 18 22]) = [3 4 8 11 14 17 17 23]; assert (fillmissing (x, "movmedian", 3), y); assert (fillmissing (x, "movmedian", [1 1]), y); assert (fillmissing (x, "movmedian", 3, "endvalues", "extrap"), y); assert (fillmissing (x, "movmedian", 3, "samplepoints", [1 2 3]), y); y = x; y([1 6 8 10 18 20 21]) = [4 6 11 7 15 20 24]; assert (fillmissing (x, "movmedian", 3, 2), y); assert (fillmissing (x, "movmedian", [1 1], 2), y); assert (fillmissing (x, "movmedian", 3, 2, "endvalues", "extrap"), y); assert (fillmissing (x, "movmedian", 3, 2, "samplepoints", [1 2 3 4]), y); y([1,18]) = NaN; y(6) = 9; assert (fillmissing (x, "movmedian", 3, 2, "samplepoints", [0 2 3 4]), y); y = x; y([1,2,5,6,10,13,16,18,19,20,21,22]) = 99; y(8) = 8; assert (fillmissing (x, "movmedian", 3, "endvalues", 99), y); y = x; y([1,2,5,8,10,13,16,19,22]) = 99; y([6,18,20,21]) = [6,15,20,24]; assert (fillmissing (x, "movmedian", 3, 2, "endvalues", 99), y); ***** assert (fillmissing ([1 2 3], @(x,y,z) x+y+z, 2), [1 2 3]) ***** assert (fillmissing ([1 2 NaN], @(x,y,z) x+y+z, 1), [1 2 NaN]) ***** assert (fillmissing ([1 2 3], @(x,y,z) x+y+z, 2), [1 2 3]) ***** assert (fillmissing ([1 2 3], @(x,y,z) x+y+z, [1 0]), [1 2 3]) ***** assert (fillmissing ([1 2 3]', @(x,y,z) x+y+z, 2), [1 2 3]') ***** assert (fillmissing ([1 2 NaN], @(x,y,z) x+y+z, 2), [1 2 7]) ***** assert (fillmissing ([1 2 NaN], @(x,y,z) x+y+z, [1 0]), [1 2 7]) ***** assert (fillmissing ([1 2 NaN], @(x,y,z) x+y+z, [1 0]'), [1 2 7]) ***** assert (fillmissing ([NaN 2 NaN], @(x,y,z) x+y+z, 2), [5 2 7]) ***** assert (fillmissing ([NaN 2 NaN], @(x,y,z) x+y+z, [1 0]), [NaN 2 7]) ***** assert (fillmissing ([NaN 2 NaN], @(x,y,z) x+y+z, [0 1]), [5 2 NaN]) ***** assert (fillmissing ([NaN 2 NaN], @(x,y,z) x+y+z, [0 1.1]), [5 2 NaN]) ***** assert (fillmissing ([1 2 NaN NaN 3 4], @(x,y,z) x+y+z, 2),[1 2 7 12 3 4]) ***** assert (fillmissing ([1 2 NaN NaN 3 4], @(x,y,z) x+y+z, 0.5),[1 2 NaN NaN 3 4]) ***** function A = testfcn (x,y,z) if isempty (y) A = z; elseif (numel (y) == 1) A = repelem (x(1), numel(z)); else A = interp1 (y, x, z, "linear","extrap"); endif ***** endfunction ***** assert (fillmissing ([1 NaN 3 NaN 5], @testfcn, [3 0]), [1 1 3 NaN 5]) ***** assert (fillmissing ([1 2 NaN; 4 NaN 6], @testfcn, 3, 1), [1 2 6; 4 2 6]) ***** assert (fillmissing ([1 2 NaN; 4 NaN 6], @testfcn, 3, 2), [1 2 2; 4 5 6]) ***** assert (fillmissing ([1 2 NaN; 4 NaN 6], @testfcn, 3, 3), [1 2 NaN; 4 NaN 6]) ***** assert (fillmissing ([1 NaN 3 NaN 5], @testfcn, 99), [1 2 3 4 5]) ***** assert (fillmissing ([1 NaN 3 NaN 5], @testfcn, 99, 1), [1 NaN 3 NaN 5]) ##known not-compatible. matlab bug ML2022a: [1 1 3 1 5] ***** assert (fillmissing ([1 NaN 3 NaN 5]', @testfcn, 99, 1), [1 2 3 4 5]') ***** assert (fillmissing ([1 NaN 3 NaN 5], @testfcn, 99, 2), [1 2 3 4 5]) ***** assert (fillmissing ([1 NaN 3 NaN 5]', @testfcn, 99, 2), [1 NaN 3 NaN 5]') ##known not-compatible. matlab bug ML2022a: [1 1 3 1 5]' ***** assert (fillmissing ([1 NaN 3 NaN 5], @testfcn, 99, 3), [1 NaN 3 NaN 5]) ***** assert (fillmissing ([1 NaN 3 NaN 5]', @testfcn, 99, 3), [1 NaN 3 NaN 5]') ***** assert (fillmissing ([1 NaN NaN NaN 5], @testfcn, 3, "samplepoints", [1 2 3 4 5]), [1 2 3 4 5]) ***** assert (fillmissing ([1 NaN NaN NaN 5], @testfcn, [1 1], "samplepoints", [1 2 3 4 5]), [1 2 3 4 5]) ***** assert (fillmissing ([1 NaN NaN NaN 5], @testfcn, [1.5 1.5], "samplepoints", [1 2 3 4 5]), [1 2 3 4 5]) ***** assert (fillmissing ([1 NaN NaN NaN 5], @testfcn, 4, "samplepoints", [1 2 3 4 5]), [1 2 3 4 5]) ***** assert (fillmissing ([1 NaN NaN NaN 5], @testfcn, [2 2], "samplepoints", [1 2 3 4 5]), [1 2 3 4 5]) ***** assert (fillmissing ([1 NaN NaN NaN 5], @testfcn, 3, "samplepoints", [1 2 2.5 3 3.5]), [1 2.6 3.4 4.2 5], 10*eps) ***** assert (fillmissing ([NaN NaN 3 NaN 5], @testfcn, 99, 1), [NaN NaN 3 NaN 5]) ##known not-compatible. matlab bug ML2022a: [1 1 3 1 5] ***** test ***** function A = testfcn (x,y,z) if isempty (y) A = z; elseif (numel (y) == 1) A = repelem (x(1), numel(z)); else A = interp1 (y, x, z, "linear","extrap"); endif ***** endfunction x = reshape ([1:24], 3, 4, 2); x([1,2,5,6,8,10,13,16,18,19,20,21,22]) = NaN; y = x; y([1,2,5,6,8,10,13,16,18,22]) = [3,3,4,4,8,11,14,17,17,23]; assert (fillmissing (x, @testfcn, 3), y); assert (fillmissing (x, @testfcn, [1 1]), y); assert (fillmissing (x, @testfcn, 3, "endvalues", "extrap"), y); assert (fillmissing (x, @testfcn, 3, "samplepoints", [1 2 3]), y); y= x; y(isnan(x)) = 99; y(8) = 8; assert (fillmissing (x, @testfcn, 3, "endvalues", 99), y) y = x; y([1,2,5,6,8,10,18,20,21]) = [4,11,11,6,11,7,18,20,21]; assert (fillmissing (x, @testfcn, 3, 2), y); assert (fillmissing (x, @testfcn, [1 1], 2), y); assert (fillmissing (x, @testfcn, 3, 2, "endvalues", "extrap"), y); assert (fillmissing (x, @testfcn, 3, 2, "samplepoints", [1 2 3 4]), y); y(1) = NaN; y([6,18,21]) = [9,24,24]; assert (fillmissing (x, @testfcn, 3, 2, "samplepoints", [0 2 3 4]), y); y = x; y([1,2,5,6,10,13,16,18,19,20,21,22]) = 99; y(8) = [8]; assert (fillmissing (x, @testfcn, 3, "endvalues", 99), y); y([6,18,20,21]) = [6,18,20,21]; y(8)=99; assert (fillmissing (x, @testfcn, 3, 2, "endvalues", 99), y); y([6,18,20,21]) = 99; assert (fillmissing (x, @testfcn, 3, 3, "endvalues", 99), y); ***** assert (fillmissing ([1 2 3], "constant", 0, "maxgap", 1), [1 2 3]) ***** assert (fillmissing ([1 2 3], "constant", 0, "maxgap", 99), [1 2 3]) ***** assert (fillmissing ([1 NaN 3], "constant", 0, "maxgap", 1), [1 NaN 3]) ***** assert (fillmissing ([1 NaN 3], "constant", 0, "maxgap", 1.999), [1 NaN 3]) ***** assert (fillmissing ([1 NaN 3], "constant", 0, "maxgap", 2), [1 0 3]) ***** assert (fillmissing ([1 NaN NaN 4], "constant", 0, "maxgap", 2), [1 NaN NaN 4]) ***** assert (fillmissing ([1 NaN NaN 4], "constant", 0, "maxgap", 3), [1 0 0 4]) ***** assert (fillmissing ([1 NaN 3 NaN 5], "constant", 0, "maxgap", 2), [1 0 3 0 5]) ***** assert (fillmissing ([NaN 2 NaN], "constant", 0, "maxgap", 0.999), [NaN 2 NaN]) ***** assert (fillmissing ([NaN 2 NaN], "constant", 0, "maxgap", 1), [0 2 0]) ***** assert (fillmissing ([NaN 2 NaN NaN], "constant", 0, "maxgap", 1), [0 2 NaN NaN]) ***** assert (fillmissing ([NaN 2 NaN NaN], "constant", 0, "maxgap", 2), [0 2 0 0]) ***** assert (fillmissing ([NaN NaN NaN], "constant", 0, "maxgap", 1), [NaN NaN NaN]) ***** assert (fillmissing ([NaN NaN NaN], "constant", 0, "maxgap", 3), [NaN NaN NaN]) ***** assert (fillmissing ([NaN NaN NaN], "constant", 0, "maxgap", 999), [NaN NaN NaN]) ***** assert (fillmissing ([1 NaN 3 NaN 5], "constant", 0, "maxgap", 2, "samplepoints", [0 1 2 3 5]), [1 0 3 NaN 5]) ***** assert (fillmissing ([1 NaN 3 NaN 5]', "constant", 0, "maxgap", 2, "samplepoints", [0 1 2 3 5]), [1 0 3 NaN 5]') ***** assert (fillmissing ([1 NaN 3 NaN 5], "constant", 0, "maxgap", 2, "samplepoints", [0 2 3 4 5]), [1 NaN 3 0 5]) ***** assert (fillmissing ([1 NaN 3 NaN 5; 1 NaN 3 NaN 5], "constant", 0, 2, "maxgap", 2, "samplepoints", [0 2 3 4 5]), [1 NaN 3 0 5; 1 NaN 3 0 5]) ***** test x = cat (3, [1, 2, NaN; 4, NaN, NaN], [NaN, 2, 3; 4, 5, NaN]); assert (fillmissing (x, "constant", 0, "maxgap", 0.1), x); y = x; y([4,7,12]) = 0; assert (fillmissing (x, "constant", 0, "maxgap", 1), y); assert (fillmissing (x, "constant", 0, 1, "maxgap", 1), y); y = x; y([5,7,12]) = 0; assert (fillmissing (x, "constant", 0, 2, "maxgap", 1), y); y = x; y([4,5,7]) = 0; assert (fillmissing (x, "constant", 0, 3, "maxgap", 1), y); ***** test x = cat (3, [1, 2, NaN; 4, NaN, NaN], [NaN, 2, 3; 4, 5, NaN]); [~, idx] = fillmissing (x, "constant", 0, "maxgap", 1); assert (idx, logical (cat (3, [0 0 0; 0 1 0], [1 0 0; 0 0 1]))); [~, idx] = fillmissing (x, "constant", 0, 1, "maxgap", 1); assert (idx, logical (cat (3, [0 0 0; 0 1 0], [1 0 0; 0 0 1]))); [~, idx] = fillmissing (x, "constant", 0, 2, "maxgap", 1); assert (idx, logical (cat (3, [0 0 1; 0 0 0], [1 0 0; 0 0 1]))); [~, idx] = fillmissing (x, "constant", 0, 3, "maxgap", 1); assert (idx, logical (cat (3, [0 0 1; 0 1 0], [1 0 0; 0 0 0]))); ***** test x = [NaN, 2, 3]; [~,idx] = fillmissing (x, "previous"); assert (idx, logical ([0 0 0])); [~,idx] = fillmissing (x, "movmean", 1); assert (idx, logical ([0 0 0])); x = [1:3;4:6;7:9]; x([2,4,7,9]) = NaN; [~,idx] = fillmissing (x, "linear"); assert (idx, logical ([0 1 0;1 0 0;0 0 0])); [~,idx] = fillmissing (x, "movmean", 2); assert (idx, logical ([0 0 0;1 0 0;0 0 1])); [A, idx] = fillmissing ([1 2 3 NaN NaN], 'movmean',2); assert (A, [1 2 3 3 NaN]); assert (idx, logical([0 0 0 1 0])); [A, idx] = fillmissing ([1 2 3 NaN NaN], 'movmean',3); assert (A, [1 2 3 3 NaN]); assert (idx, logical([0 0 0 1 0])); [A, idx] = fillmissing ([1 2 NaN NaN NaN], 'movmedian', 2); assert (A, [1 2 2 NaN NaN]); assert (idx, logical([0 0 1 0 0])); [A, idx] = fillmissing ([1 2 3 NaN NaN], 'movmedian', 3); assert (A, [1 2 3 3 NaN]); assert (idx, logical([0 0 0 1 0])); [A, idx] = fillmissing ([1 NaN 1 NaN 1], @(x,y,z) z, 3); assert (A, [1 2 1 4 1]); assert (idx, logical([0 1 0 1 0])); [A, idx] = fillmissing ([1 NaN 1 NaN 1], @(x,y,z) NaN (size (z)), 3); assert (A, [1 NaN 1 NaN 1]); assert (idx, logical([0 0 0 0 0])); ***** assert (fillmissing ([1 2 3], "constant", 99, "missinglocations", logical([0 0 0])), [1 2 3]) ***** assert (fillmissing ([1 2 3], "constant", 99, "missinglocations", logical([1 1 1])), [99 99 99]) ***** assert (fillmissing ([1 NaN 2 3 NaN], "constant", 99, "missinglocations", logical([1 0 1 0 1])), [99 NaN 99 3 99]) ***** assert (fillmissing ([1 NaN 3 NaN 5], "constant", NaN, "missinglocations", logical([0 1 1 1 0])), [1 NaN NaN NaN 5]) ***** assert (fillmissing (["foo ";" bar"], "constant", 'X', "missinglocations", logical([0 0 0 0; 0 0 0 0])), ["foo ";" bar"]) ***** assert (fillmissing (["foo ";" bar"], "constant", 'X', "missinglocations", logical([1 0 1 0; 0 1 1 0])), ["XoX ";" XXr"]) ***** assert (fillmissing ({"foo","", "bar"}, "constant", 'X', "missinglocations", logical([0 0 0])), {"foo","", "bar"}) ***** assert (fillmissing ({"foo","", "bar"}, "constant", 'X', "missinglocations", logical([1 1 0])), {"X","X","bar"}) ***** test [~,idx] = fillmissing ([1 NaN 3 NaN 5], "constant", NaN); assert (idx, logical([0 0 0 0 0])); [~,idx] = fillmissing ([1 NaN 3 NaN 5], "constant", NaN, "missinglocations", logical([0 1 1 1 0])); assert (idx, logical([0 1 1 1 0])); [A, idx] = fillmissing ([1 2 NaN 1 NaN], 'movmean', 3.1, 'missinglocations', logical([0 0 1 1 0])); assert (A, [1 2 2 NaN NaN]); assert (idx, logical([0 0 1 0 0])); [A, idx] = fillmissing ([1 2 NaN NaN NaN], 'movmean', 2, 'missinglocations', logical([0 0 1 1 0])); assert (A, [1 2 2 NaN NaN]); assert (idx, logical([0 0 1 0 0])); [A, idx] = fillmissing ([1 2 NaN 1 NaN], 'movmean', 3, 'missinglocations', logical([0 0 1 1 0])); assert (A, [1 2 2 NaN NaN]); assert (idx, logical([0 0 1 0 0])); [A, idx] = fillmissing ([1 2 NaN NaN NaN], 'movmean', 3, 'missinglocations', logical([0 0 1 1 0])); assert (A, [1 2 2 NaN NaN]); assert (idx, logical([0 0 1 0 0])); [A, idx] = fillmissing ([1 2 NaN NaN NaN], 'movmedian', 2, 'missinglocations', logical([0 0 1 1 0])); assert (A, [1 2 2 NaN NaN]); assert (idx, logical([0 0 1 0 0])); [A, idx] = fillmissing ([1 2 NaN NaN NaN], 'movmedian', 3, 'missinglocations', logical([0 0 1 1 0])); assert (A, [1 2 2 NaN NaN]); assert (idx, logical([0 0 1 0 0])); [A, idx] = fillmissing ([1 2 NaN NaN NaN], 'movmedian', 3.1, 'missinglocations', logical([0 0 1 1 0])); assert (A, [1 2 2 NaN NaN]); assert (idx, logical([0 0 1 0 0])); [A, idx] = fillmissing ([1 NaN 1 NaN 1], @(x,y,z) ones (size (z)), 3, "missinglocations", logical([0 1 0 1 1])); assert (A, [1 1 1 1 1]); assert (idx, logical([0 1 0 1 1])); [A, idx] = fillmissing ([1 NaN 1 NaN 1], @(x,y,z) NaN (size (z)), 3, "missinglocations", logical([0 1 0 1 1])); assert (A, [1 NaN 1 NaN NaN]); assert (idx, logical([0 0 0 0 0])); ***** assert (fillmissing (' foo bar ', "constant", 'X'), 'XfooXbarX') ***** assert (fillmissing ([' foo';'bar '], "constant", 'X'), ['Xfoo';'barX']) ***** assert (fillmissing ([' foo';'bar '], "next"), ['bfoo';'bar ']) ***** assert (fillmissing ([' foo';'bar '], "next", 1), ['bfoo';'bar ']) ***** assert (fillmissing ([' foo';'bar '], "previous"), [' foo';'baro']) ***** assert (fillmissing ([' foo';'bar '], "previous", 1), [' foo';'baro']) ***** assert (fillmissing ([' foo';'bar '], "nearest"), ['bfoo';'baro']) ***** assert (fillmissing ([' foo';'bar '], "nearest", 1), ['bfoo';'baro']) ***** assert (fillmissing ([' foo';'bar '], "next", 2), ['ffoo';'bar ']) ***** assert (fillmissing ([' foo';'bar '], "previous", 2), [' foo';'barr']) ***** assert (fillmissing ([' foo';'bar '], "nearest", 2), ['ffoo';'barr']) ***** assert (fillmissing ([' foo';'bar '], "next", 3), [' foo';'bar ']) ***** assert (fillmissing ([' foo';'bar '], "previous", 3), [' foo';'bar ']) ***** assert (fillmissing ([' foo';'bar '], "nearest", 3), [' foo';'bar ']) ***** assert (fillmissing ({'foo','bar'}, "constant", 'a'), {'foo','bar'}) ***** assert (fillmissing ({'foo','bar'}, "constant", {'a'}), {'foo','bar'}) ***** assert (fillmissing ({'foo', '', 'bar'}, "constant", 'a'), {'foo', 'a', 'bar'}) ***** assert (fillmissing ({'foo', '', 'bar'}, "constant", {'a'}), {'foo', 'a', 'bar'}) ***** assert (fillmissing ({'foo', '', 'bar'}, "previous"), {'foo', 'foo', 'bar'}) ***** assert (fillmissing ({'foo', '', 'bar'}, "next"), {'foo', 'bar', 'bar'}) ***** assert (fillmissing ({'foo', '', 'bar'}, "nearest"), {'foo', 'bar', 'bar'}) ***** assert (fillmissing ({'foo', '', 'bar'}, "previous", 2), {'foo', 'foo', 'bar'}) ***** assert (fillmissing ({'foo', '', 'bar'}, "next", 2), {'foo', 'bar', 'bar'}) ***** assert (fillmissing ({'foo', '', 'bar'}, "nearest", 2), {'foo', 'bar', 'bar'}) ***** assert (fillmissing ({'foo', '', 'bar'}, "previous", 1), {'foo', '', 'bar'}) ***** assert (fillmissing ({'foo', '', 'bar'}, "previous", 1), {'foo', '', 'bar'}) ***** assert (fillmissing ({'foo', '', 'bar'}, "next", 1), {'foo', '', 'bar'}) ***** assert (fillmissing ({'foo', '', 'bar'}, "nearest", 1), {'foo', '', 'bar'}) ***** assert (fillmissing ("abc ", @(x,y,z) x+y+z, 2), "abcj") ***** assert (fillmissing ({'foo', '', 'bar'}, @(x,y,z) x(1), 3), {'foo','foo','bar'}) ***** test [A, idx] = fillmissing (" a b c", "constant", " "); assert (A, " a b c"); assert (idx, logical([0 0 0 0 0 0])); [A, idx] = fillmissing ({"foo", "", "bar", ""}, "constant", ""); assert (A, {"foo", "", "bar", ""}); assert (idx, logical([0 0 0 0])); [A, idx] = fillmissing ({"foo", "", "bar", ""}, "constant", {""}); assert (A, {"foo", "", "bar", ""}); assert (idx, logical([0 0 0 0])); [A,idx] = fillmissing (' f o o ', @(x,y,z) repelem ("a", numel (z)), 3); assert (A, "afaoaoa"); assert (idx, logical([1 0 1 0 1 0 1])); [A,idx] = fillmissing (' f o o ', @(x,y,z) repelem (" ", numel (z)), 3); assert (A, " f o o "); assert (idx, logical([0 0 0 0 0 0 0])); [A,idx] = fillmissing ({'','foo',''}, @(x,y,z) repelem ({'a'}, numel (z)), 3); assert (A, {'a','foo','a'}); assert (idx, logical([1 0 1])); [A,idx] = fillmissing ({'','foo',''}, @(x,y,z) repelem ({''}, numel (z)), 3); assert (A, {'','foo',''}); assert (idx, logical([0 0 0])); ***** assert (fillmissing (logical ([1 0 1 0 1]), "constant", true), logical ([1 0 1 0 1])) ***** assert (fillmissing (logical ([1 0 1 0 1]), "constant", false, 'missinglocations', logical([1 0 1 0 1])), logical ([0 0 0 0 0])) ***** assert (fillmissing (logical ([1 0 1 0 1]), "previous", 'missinglocations', logical([1 0 1 0 1])), logical ([1 0 0 0 0])) ***** assert (fillmissing (logical ([1 0 1 0 1]), "next", 'missinglocations', logical([1 0 1 0 1])), logical ([0 0 0 0 1])) ***** assert (fillmissing (logical ([1 0 1 0 1]), "nearest", 'missinglocations', logical([1 0 1 0 1])), logical ([0 0 0 0 0])) ***** assert (fillmissing (logical ([1 0 1 0 1]), @(x,y,z) false(size(z)), 3), logical ([1 0 1 0 1])) ***** assert (fillmissing (logical ([1 0 1 0 1]), @(x,y,z) false(size(z)), 3, 'missinglocations', logical([1 0 1 0 1])), logical ([0 0 0 0 0])) ***** assert (fillmissing (logical ([1 0 1 0 1]), @(x,y,z) false(size(z)), [2 0], 'missinglocations', logical([1 0 1 0 1])), logical ([1 0 0 0 0])) ***** test x = logical ([1 0 1 0 1]); [~,idx] = fillmissing (x, "constant", true); assert (idx, logical([0 0 0 0 0])); [~,idx] = fillmissing (x, "constant", false, 'missinglocations', logical([1 0 1 0 1])); assert (idx, logical([1 0 1 0 1])); [~,idx] = fillmissing (x, "constant", true, 'missinglocations', logical([1 0 1 0 1])); assert (idx, logical([1 0 1 0 1])); [~,idx] = fillmissing (x, "previous", 'missinglocations', logical([1 0 1 0 1])); assert (idx, logical([0 0 1 0 1])); [~,idx] = fillmissing (x, "next", 'missinglocations', logical([1 0 1 0 1])); assert (idx, logical([1 0 1 0 0])); [~,idx] = fillmissing (x, "nearest", 'missinglocations', logical([1 0 1 0 1])); assert (idx, logical([1 0 1 0 1])); [~,idx] = fillmissing (x, @(x,y,z) false(size(z)), 3); assert (idx, logical ([0 0 0 0 0])) [~,idx] = fillmissing (x, @(x,y,z) false(size(z)), 3, 'missinglocations', logical([1 0 1 0 1])); assert (idx, logical ([1 0 1 0 1])) [~,idx] = fillmissing (x, @(x,y,z) false(size(z)), [2 0], 'missinglocations', logical([1 0 1 0 1])); assert (idx, logical ([0 0 1 0 1])) ***** assert (fillmissing (int32 ([1 2 3 4 5]), "constant", 0), int32 ([1 2 3 4 5])) ***** assert (fillmissing (int32 ([1 2 3 4 5]), "constant", 0,'missinglocations', logical([1 0 1 0 1])), int32 ([0 2 0 4 0])) ***** assert (fillmissing (int32 ([1 2 3 4 5]), "previous", 'missinglocations', logical([1 0 1 0 1])), int32 ([1 2 2 4 4])) ***** assert (fillmissing (int32 ([1 2 3 4 5]), "next", 'missinglocations', logical([1 0 1 0 1])), int32 ([2 2 4 4 5])) ***** assert (fillmissing (int32 ([1 2 3 4 5]), "nearest", 'missinglocations', logical([1 0 1 0 1])), int32 ([2 2 4 4 4])) ***** assert (fillmissing (int32 ([1 2 3 4 5]), @(x,y,z) z+10, 3), int32 ([1 2 3 4 5])) ***** assert (fillmissing (int32 ([1 2 3 4 5]), @(x,y,z) z+10, 3, 'missinglocations', logical([1 0 1 0 1])), int32 ([11 2 13 4 15])) ***** assert (fillmissing (int32 ([1 2 3 4 5]), @(x,y,z) z+10, [2 0], 'missinglocations', logical([1 0 1 0 1])), int32 ([1 2 13 4 15])) ***** test x = int32 ([1 2 3 4 5]); [~,idx] = fillmissing (x, "constant", 0); assert (idx, logical([0 0 0 0 0])); [~,idx] = fillmissing (x, "constant", 0, 'missinglocations', logical([1 0 1 0 1])); assert (idx, logical([1 0 1 0 1])); [~,idx] = fillmissing (x, "constant", 3, 'missinglocations', logical([0 0 1 0 0])); assert (idx, logical([0 0 1 0 0])); [~,idx] = fillmissing (x, "previous", 'missinglocations', logical([1 0 1 0 1])); assert (idx, logical([0 0 1 0 1])); [~,idx] = fillmissing (x, "next", 'missinglocations', logical([1 0 1 0 1])); assert (idx, logical([1 0 1 0 0])); [~,idx] = fillmissing (x, "nearest", 'missinglocations', logical([1 0 1 0 1])); assert (idx, logical([1 0 1 0 1])); [~,idx] = fillmissing (x, @(x,y,z) z+10, 3); assert (idx, logical([0 0 0 0 0])); [~,idx] = fillmissing (x, @(x,y,z) z+10, 3, 'missinglocations', logical([1 0 1 0 1])); assert (idx, logical([1 0 1 0 1])); [~,idx] = fillmissing (x, @(x,y,z) z+10, [2 0], 'missinglocations', logical([1 0 1 0 1])); assert (idx, logical([0 0 1 0 1])); ***** test [A, idx] = fillmissing ([struct struct], "constant", 1); assert (A, [struct struct]) assert (idx, [false false]) ***** error fillmissing () ***** error fillmissing (1) ***** error fillmissing (1,2,3,4,5,6,7,8,9,10,11,12,13) ***** error fillmissing (1, 2) ***** error fillmissing (1, "foo") ***** error fillmissing (1, @(x) x, 1) ***** error fillmissing (1, @(x,y) x+y, 1) ***** error fillmissing ("a b c", "linear") ***** error fillmissing ({'a','b'}, "linear") ***** error <'movmean' and 'movmedian' methods only valid for numeric> fillmissing ("a b c", "movmean", 2) ***** error <'movmean' and 'movmedian' methods only valid for numeric> fillmissing ({'a','b'}, "movmean", 2) ***** error <'constant' method must be followed by> fillmissing (1, "constant") ***** error fillmissing (1, "constant", []) ***** error fillmissing (1, "constant", "a") ***** error fillmissing ("a", "constant", 1) ***** error fillmissing ("a", "constant", {"foo"}) ***** error fillmissing ({"foo"}, "constant", 1) ***** error fillmissing (1, "movmean") ***** error fillmissing (1, "movmedian") ***** error fillmissing (1, "constant", 1, 0) ***** error fillmissing (1, "constant", 1, -1) ***** error fillmissing (1, "constant", 1, [1 2]) ***** error fillmissing (1, "constant", 1, "samplepoints") ***** error fillmissing (1, "constant", 1, "foo") ***** error fillmissing (1, "constant", 1, 1, "foo") ***** error fillmissing (1, "constant", 1, 2, {1}, 4) ***** error fillmissing ([1 2 3], "constant", 1, 2, "samplepoints", [1 2]) ***** error fillmissing ([1 2 3], "constant", 1, 2, "samplepoints", [3 1 2]) ***** error fillmissing ([1 2 3], "constant", 1, 2, "samplepoints", [1 1 2]) ***** error fillmissing ([1 2 3], "constant", 1, 2, "samplepoints", "abc") ***** error fillmissing ([1 2 3], "constant", 1, 2, "samplepoints", logical([1 1 1])) ***** error fillmissing ([1 2 3], "constant", 1, 1, "samplepoints", [1 2 3]) ***** error fillmissing ('foo', "next", "endvalues", 1) ***** error fillmissing (1, "constant", 1, 1, "endvalues", "foo") ***** error fillmissing ([1 2 3], "constant", 1, 2, "endvalues", [1 2 3]) ***** error fillmissing ([1 2 3], "constant", 1, 1, "endvalues", [1 2]) ***** error fillmissing (randi(5,4,3,2), "constant", 1, 3, "endvalues", [1 2]) ***** error fillmissing (1, "constant", 1, 1, "endvalues", {1}) ***** error fillmissing (1, "constant", 1, 2, "foo", 4) ***** error fillmissing (struct, "constant", 1, "missinglocations", false) ***** error fillmissing (1, "constant", 1, 2, "maxgap", 1, "missinglocations", false) ***** error fillmissing (1, "constant", 1, 2, "missinglocations", false, "maxgap", 1) ***** error fillmissing (1, "constant", 1, "replacevalues", true) ***** error fillmissing (1, "constant", 1, "datavariables", 'Varname') ***** error fillmissing (1, "constant", 1, 2, "missinglocations", 1) ***** error fillmissing (1, "constant", 1, 2, "missinglocations", 'a') ***** error fillmissing (1, "constant", 1, 2, "missinglocations", [true false]) ***** error fillmissing (true, "linear", "missinglocations", true) ***** error fillmissing (int8(1), "linear", "missinglocations", true) ***** error fillmissing (true, "next", "missinglocations", true, "EndValues", "linear") ***** error fillmissing (true, "next", "EndValues", "linear", "missinglocations", true) ***** error fillmissing (int8(1), "next", "missinglocations", true, "EndValues", "linear") ***** error fillmissing (int8(1), "next", "EndValues", "linear", "missinglocations", true) ***** error fillmissing (1, "constant", 1, 2, "maxgap", true) ***** error fillmissing (1, "constant", 1, 2, "maxgap", 'a') ***** error fillmissing (1, "constant", 1, 2, "maxgap", [1 2]) ***** error fillmissing (1, "constant", 1, 2, "maxgap", 0) ***** error fillmissing (1, "constant", 1, 2, "maxgap", -1) ***** error fillmissing ([1 2 3], "constant", [1 2 3]) ***** error fillmissing ([1 2 3]', "constant", [1 2 3]) ***** error fillmissing ([1 2 3]', "constant", [1 2 3], 1) ***** error fillmissing ([1 2 3], "constant", [1 2 3], 2) ***** error fillmissing (randi(5,4,3,2), "constant", [1 2], 1) ***** error fillmissing (randi(5,4,3,2), "constant", [1 2], 2) ***** error fillmissing (randi(5,4,3,2), "constant", [1 2], 3) ***** error fillmissing (1, @(x,y,z) x+y+z) ***** error fillmissing ([1 NaN 2], @(x,y,z) [1 2], 2) 378 tests, 377 passed, 0 known failure, 1 skipped Checking C++ files ... [src/libsvmread.cc] >>>>> /build/reproducible-path/octave-statistics-1.6.5/src/libsvmread.cc ***** error [L, D] = libsvmread (24); ***** error ... D = libsvmread ("filename"); ***** test [L, D] = libsvmread (file_in_loadpath ("heart_scale.dat")); assert (size (L), [270, 1]); assert (size (D), [270, 13]); ***** test [L, D] = libsvmread (file_in_loadpath ("heart_scale.dat")); assert (issparse (L), false); assert (issparse (D), true); 4 tests, 4 passed, 0 known failure, 0 skipped [src/libsvmwrite.cc] >>>>> /build/reproducible-path/octave-statistics-1.6.5/src/libsvmwrite.cc ***** shared L, D [L, D] = libsvmread (file_in_loadpath ("heart_scale.dat")); ***** error libsvmwrite ("", L, D); ***** error ... libsvmwrite (tempname (), [L;L], D); ***** error ... OUT = libsvmwrite (tempname (), L, D); ***** error ... libsvmwrite (tempname (), single (L), D); ***** error libsvmwrite (13412, L, D); ***** error ... libsvmwrite (tempname (), L, full (D)); ***** error ... libsvmwrite (tempname (), L, D, D); 7 tests, 7 passed, 0 known failure, 0 skipped [src/svmpredict.cc] >>>>> /build/reproducible-path/octave-statistics-1.6.5/src/svmpredict.cc ***** test [L, D] = libsvmread (file_in_loadpath ("heart_scale.dat")); model = svmtrain (L, D, '-c 1 -g 0.07'); [predict_label, accuracy, dec_values] = svmpredict (L, D, model); assert (size (predict_label), size (dec_values)); assert (accuracy, [86.666, 0.533, 0.533]', [1e-3, 1e-3, 1e-3]'); assert (dec_values(1), 1.225836001973273, 1e-14); assert (dec_values(2), -0.3212992933043805, 1e-14); assert (predict_label(1), 1); ***** shared L, D, model [L, D] = libsvmread (file_in_loadpath ("heart_scale.dat")); model = svmtrain (L, D, '-c 1 -g 0.07'); ***** error ... [p, a] = svmpredict (L, D, model); ***** error p = svmpredict (L, D); ***** error ... p = svmpredict (single (L), D, model); ***** error p = svmpredict (L, D, 123); 5 tests, 5 passed, 0 known failure, 0 skipped [src/svmtrain.cc] >>>>> /build/reproducible-path/octave-statistics-1.6.5/src/svmtrain.cc ***** test [L, D] = libsvmread (file_in_loadpath ("heart_scale.dat")); model = svmtrain(L, D, '-c 1 -g 0.07'); [predict_label, accuracy, dec_values] = svmpredict(L, D, model); assert (isstruct (model), true); assert (isfield (model, "Parameters"), true); assert (model.totalSV, 130); assert (model.nr_class, 2); assert (size (model.Label), [2, 1]); ***** shared L, D [L, D] = libsvmread (file_in_loadpath ("heart_scale.dat")); ***** error [L, D] = svmtrain (L, D); ***** error ... model = svmtrain (single (L), D); ***** error ... model = svmtrain (L, D, "", ""); 4 tests, 4 passed, 0 known failure, 0 skipped Done running the unit tests. Summary: 10345 tests, 10343 passed, 1 known failures, 1 skipped dh_install -O--buildsystem=octave dh_installdocs -O--buildsystem=octave dh_installchangelogs -O--buildsystem=octave dh_octave_changelogs -O--buildsystem=octave dh_octave_examples -O--buildsystem=octave dh_installsystemduser -O--buildsystem=octave dh_perl -O--buildsystem=octave dh_link -O--buildsystem=octave dh_strip_nondeterminism -O--buildsystem=octave dh_compress -O--buildsystem=octave dh_fixperms -O--buildsystem=octave dh_missing -O--buildsystem=octave dh_dwz -a -O--buildsystem=octave dh_strip -a -O--buildsystem=octave dh_makeshlibs -a -O--buildsystem=octave dh_shlibdeps -a -O--buildsystem=octave dh_octave_substvar -O--buildsystem=octave dh_installdeb -O--buildsystem=octave debian/rules execute_after_dh_installdeb-indep make[1]: Entering directory '/build/reproducible-path/octave-statistics-1.6.5' # Use local JavaScript and CSS files debian/local-url # Remove empty directory rm -rf # See https://savannah.gnu.org/bugs/?65418 find debian/octave-statistics-common -name \*.m -a -perm /+x -exec chmod -x \{} \; make[1]: Leaving directory '/build/reproducible-path/octave-statistics-1.6.5' dh_gencontrol -O--buildsystem=octave dpkg-gencontrol: warning: package octave-statistics: substitution variable ${octave:Upstream-Description} unused, but is defined dpkg-gencontrol: warning: package octave-statistics-common: substitution variable ${octave:Upstream-Description} unused, but is defined dpkg-gencontrol: warning: package octave-statistics: substitution variable ${octave:Upstream-Description} unused, but is defined dh_md5sums -O--buildsystem=octave dh_builddeb -O--buildsystem=octave dpkg-deb: building package 'octave-statistics' in '../octave-statistics_1.6.5-3_i386.deb'. dpkg-deb: building package 'octave-statistics-common' in '../octave-statistics-common_1.6.5-3_all.deb'. dpkg-deb: building package 'octave-statistics-dbgsym' in '../octave-statistics-dbgsym_1.6.5-3_i386.deb'. dpkg-genbuildinfo --build=binary -O../octave-statistics_1.6.5-3_i386.buildinfo dpkg-genchanges --build=binary -O../octave-statistics_1.6.5-3_i386.changes dpkg-genchanges: info: binary-only upload (no source code included) dpkg-source --after-build . dpkg-buildpackage: info: binary-only upload (no source included) dpkg-genchanges: info: not including original source code in upload I: copying local configuration I: user script /srv/workspace/pbuilder/29027/tmp/hooks/B01_cleanup starting I: user script /srv/workspace/pbuilder/29027/tmp/hooks/B01_cleanup finished I: unmounting dev/ptmx filesystem I: unmounting dev/pts filesystem I: unmounting dev/shm filesystem I: unmounting proc filesystem I: unmounting sys filesystem I: cleaning the build env I: removing directory /srv/workspace/pbuilder/29027 and its subdirectories I: Current time: Tue May 6 10:23:20 +14 2025 I: pbuilder-time-stamp: 1746476600