Fri May 10 18:42:31 UTC 2024 I: starting to build octave-statistics/trixie/amd64 on jenkins on '2024-05-10 18:42' Fri May 10 18:42:31 UTC 2024 I: The jenkins build log is/was available at https://jenkins.debian.net/userContent/reproducible/debian/build_service/amd64_36/11473/console.log Fri May 10 18:42:31 UTC 2024 I: Downloading source for trixie/octave-statistics=1.6.5-3 --2024-05-10 18:42:31-- http://deb.debian.org/debian/pool/main/o/octave-statistics/octave-statistics_1.6.5-3.dsc Connecting to 46.16.76.132:3128... connected. Proxy request sent, awaiting response... 200 OK Length: 2445 (2.4K) [text/prs.lines.tag] Saving to: ‘octave-statistics_1.6.5-3.dsc’ 0K .. 100% 283M=0s 2024-05-10 18:42:31 (283 MB/s) - ‘octave-statistics_1.6.5-3.dsc’ saved [2445/2445] Fri May 10 18:42:32 UTC 2024 I: octave-statistics_1.6.5-3.dsc -----BEGIN PGP SIGNED MESSAGE----- Hash: SHA256 Format: 3.0 (quilt) Source: octave-statistics Binary: octave-statistics, octave-statistics-common Architecture: any all Version: 1.6.5-3 Maintainer: Debian Octave Group Uploaders: Sébastien Villemot , Rafael Laboissière Homepage: https://gnu-octave.github.io/packages/statistics/ Standards-Version: 4.6.2 Vcs-Browser: https://salsa.debian.org/pkg-octave-team/octave-statistics Vcs-Git: https://salsa.debian.org/pkg-octave-team/octave-statistics.git Testsuite: autopkgtest-pkg-octave Build-Depends: debhelper-compat (= 13), dh-octave (>= 1.2.3), dh-sequence-octave, octave, octave-io, python3 Build-Conflicts: octave-nan Package-List: octave-statistics deb math optional arch=any octave-statistics-common deb math optional arch=all Checksums-Sha1: eb897230bd69f9f4febed46c495973122f0746df 8513099 octave-statistics_1.6.5.orig.tar.gz a0bdfac67435a9d6c0c10d367e688424994e2f1b 10560 octave-statistics_1.6.5-3.debian.tar.xz Checksums-Sha256: 0ea8258c92ce67e1bb75a9813b7ceb56fff1dacf6c47236d3da776e27b684cee 8513099 octave-statistics_1.6.5.orig.tar.gz 99d61b4a7110e480f837d70a1ec6f88d45d5ba2d34d105ba69dd8a74ce3c7848 10560 octave-statistics_1.6.5-3.debian.tar.xz Files: a06f7e133cf44fb5827a9d8ee4071612 8513099 octave-statistics_1.6.5.orig.tar.gz a54b1eb1553c9ce2e7c278ec163aa4f6 10560 octave-statistics_1.6.5-3.debian.tar.xz Dgit: 7dfa9aa51b217ee54ddd56b0ef97ae0d039fc1dc debian archive/debian/1.6.5-3 https://git.dgit.debian.org/octave-statistics -----BEGIN PGP SIGNATURE----- iQJGBAEBCAAwFiEEP0ZDkUmP6HS9tdmPISSqGYN4XJAFAmX9bs4SHHJhZmFlbEBk ZWJpYW4ub3JnAAoJECEkqhmDeFyQdDYP/1FWzQxODPvkQvpIATzu7pCGqEm6e6W6 Y6yKFeF5RthMEW3z02TrOAxPXuIsu4Q+MwtYeNo6MErOG4p9ZC8n94+SlfkPNwqX NAayFSILRY0VV2HKK14ApEdtgPsrM70WYjA9799UBILqw1ZH9y3XSClvXU3K1LEB /FS2Jzg1Oc628ibfqET/JcP9h36aevFTP8petP8On2YDOvwaWycG9RiXsHqze1CE Dv2PWxTfoatxfo/zsCrCat03BOSklrkqmypu3+xcGdK4ukltmSs23N4enT8YikkX h0ukxwMNTPqXtPUmAALkwVQf7ttddjIgxzrN7+LhB4dKD4bn2w7gMgoLpVgQffYj 5JJjKkdmp2AmbDHHQVc3IDojkdEMuzoSQ/83bZfSaOqF7oqAR+0SanYJpO687WSg 2v7LN+MGyNGCeLwd1SI5eYSAY7+qd55t4NdtZLHfxyrIR2bFUBQYKBVccquggNpl TFgILJ0Nebp60sW0i9hNShj9N/RiKoq0uWrKbz9l/o/Essot5YCi3bArOvvqt+Q7 NOemJRYB1akDCkX3x52tBUK9s+42TPl+wypA7HQypH84iUfZHgngZMEAk/EwpusA hoTsyk2x71YlJBwB46MCuW/6YVb4Q77uzawK+daSd9Qp4JTdSLuianBbVED/v635 SOY56tDVXSN9 =Cizl -----END PGP SIGNATURE----- Fri May 10 18:42:32 UTC 2024 I: Checking whether the package is not for us Fri May 10 18:42:32 UTC 2024 I: Starting 1st build on remote node infom02-amd64.debian.net. Fri May 10 18:42:32 UTC 2024 I: Preparing to do remote build '1' on infom02-amd64.debian.net. Fri May 10 18:54:11 UTC 2024 I: Deleting $TMPDIR on infom02-amd64.debian.net. I: pbuilder: network access will be disabled during build I: Current time: Thu Jun 12 13:05:34 -12 2025 I: pbuilder-time-stamp: 1749776734 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: 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/1635889/tmp/hooks/D02_print_environment starting I: set BUILDDIR='/build/reproducible-path' BUILDUSERGECOS='first user,first room,first work-phone,first home-phone,first other' BUILDUSERNAME='pbuilder1' BUILD_ARCH='amd64' DEBIAN_FRONTEND='noninteractive' DEB_BUILD_OPTIONS='buildinfo=+all reproducible=+all parallel=12 ' DISTRIBUTION='trixie' HOME='/root' HOST_ARCH='amd64' IFS=' ' INVOCATION_ID='6f4c66610a1247f397e9591a95efb99f' LANG='C' LANGUAGE='en_US:en' LC_ALL='C' MAIL='/var/mail/root' OPTIND='1' PATH='/usr/sbin:/usr/bin:/sbin:/bin:/usr/games' PBCURRENTCOMMANDLINEOPERATION='build' PBUILDER_OPERATION='build' PBUILDER_PKGDATADIR='/usr/share/pbuilder' PBUILDER_PKGLIBDIR='/usr/lib/pbuilder' PBUILDER_SYSCONFDIR='/etc' PPID='1635889' PS1='# ' PS2='> ' PS4='+ ' PWD='/' SHELL='/bin/bash' SHLVL='2' SUDO_COMMAND='/usr/bin/timeout -k 18.1h 18h /usr/bin/ionice -c 3 /usr/bin/nice /usr/sbin/pbuilder --build --configfile /srv/reproducible-results/rbuild-debian/r-b-build.rwluX86S/pbuilderrc_hZUB --distribution trixie --hookdir /etc/pbuilder/first-build-hooks --debbuildopts -b --basetgz /var/cache/pbuilder/trixie-reproducible-base.tgz --buildresult /srv/reproducible-results/rbuild-debian/r-b-build.rwluX86S/b1 --logfile b1/build.log octave-statistics_1.6.5-3.dsc' SUDO_GID='109' SUDO_UID='104' SUDO_USER='jenkins' TERM='unknown' TZ='/usr/share/zoneinfo/Etc/GMT+12' USER='root' _='/usr/bin/systemd-run' I: uname -a Linux infom02-amd64 6.6.13+bpo-amd64 #1 SMP PREEMPT_DYNAMIC Debian 6.6.13-1~bpo12+1 (2024-02-15) x86_64 GNU/Linux I: ls -l /bin lrwxrwxrwx 1 root root 7 Jun 10 17:51 /bin -> usr/bin I: user script /srv/workspace/pbuilder/1635889/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: amd64 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 ... 19699 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-x86-64-linux-gnu{a} gfortran-x86-64-linux-gnu{a} gnuplot-data{a} gnuplot-nox{a} gpg{a} gpgconf{a} groff-base{a} hdf5-helpers{a} ibverbs-providers{a} intltool-debian{a} iso-codes{a} libabsl20230802{a} libaec-dev{a} libaec0{a} libalgorithm-c3-perl{a} libaliased-perl{a} libamd-comgr2{a} libamd3{a} libamdhip64-5{a} libaom3{a} libapp-cmd-perl{a} libapt-pkg-perl{a} libarchive-zip-perl{a} libarpack2t64{a} libarray-intspan-perl{a} libasound2-data{a} libasound2t64{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} libcom-err2{a} libcombblas2.0.0t64{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} libcups2t64{a} libcurl3t64-gnutls{a} libcurl4-openssl-dev{a} libcurl4t64{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} libelf1t64{a} libemail-address-xs-perl{a} libencode-locale-perl{a} liberror-perl{a} libevdev2{a} libevent-core-2.1-7t64{a} libevent-pthreads-2.1-7t64{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} libflac12t64{a} libfltk-gl1.3t64{a} libfltk1.3t64{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} libglib2.0-0t64{a} libglpk40{a} libglu1-mesa{a} libglvnd0{a} libglx-dev{a} libglx-mesa0{a} libglx0{a} libgraphicsmagick++-q16-12t64{a} libgraphicsmagick-q16-3t64{a} libgraphite2-3{a} libgssapi-krb5-2{a} libgudev-1.0-0{a} libharfbuzz0b{a} libhash-merge-perl{a} libhdf5-103-1t64{a} libhdf5-cpp-103-1t64{a} libhdf5-dev{a} libhdf5-fortran-102t64{a} libhdf5-hl-100t64{a} libhdf5-hl-cpp-100t64{a} libhdf5-hl-fortran-100t64{a} libhdf5-openmpi-103-1t64{a} libheif-plugin-dav1d{a} libheif-plugin-libde265{a} libheif1{a} libhsa-runtime64-1{a} libhsakmt1{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} libhwy1t64{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} libk5crypto3{a} libkeyutils1{a} libklu2{a} libkrb5-3{a} libkrb5support0{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} libllvm17t64{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} libmagic1t64{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} libmpg123-0t64{a} libmro-compat-perl{a} libmtdev1t64{a} libmumps-5.6t64{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} 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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} libsvtav1enc1d1{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} libtrilinos-amesos-13.2{a} libtrilinos-aztecoo-13.2{a} libtrilinos-epetra-13.2{a} libtrilinos-epetraext-13.2{a} libtrilinos-galeri-13.2{a} libtrilinos-ifpack-13.2{a} libtrilinos-kokkos-13.2{a} libtrilinos-ml-13.2{a} libtrilinos-teuchos-13.2{a} libtrilinos-trilinosss-13.2{a} libtrilinos-triutils-13.2{a} libtrilinos-zoltan-13.2{a} libtry-tiny-perl{a} libuchardet0{a} libucx0{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 gnupg groff krb5-locales 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, 546 newly installed, 0 to remove and 0 not upgraded. Need to get 241 MB of archives. After unpacking 941 MB will be used. Writing extended state information... Get: 1 http://deb.debian.org/debian trixie/main amd64 libpython3.11-minimal amd64 3.11.9-1 [817 kB] Get: 2 http://deb.debian.org/debian trixie/main amd64 libexpat1 amd64 2.6.2-1 [103 kB] Get: 3 http://deb.debian.org/debian trixie/main amd64 python3.11-minimal amd64 3.11.9-1 [1879 kB] Get: 4 http://deb.debian.org/debian trixie/main amd64 python3-minimal amd64 3.11.8-1 [26.3 kB] Get: 5 http://deb.debian.org/debian trixie/main amd64 media-types all 10.1.0 [26.9 kB] Get: 6 http://deb.debian.org/debian trixie/main amd64 netbase all 6.4 [12.8 kB] Get: 7 http://deb.debian.org/debian trixie/main amd64 tzdata all 2024a-4 [255 kB] Get: 8 http://deb.debian.org/debian trixie/main amd64 readline-common all 8.2-4 [69.3 kB] Get: 9 http://deb.debian.org/debian trixie/main amd64 libreadline8t64 amd64 8.2-4 [167 kB] Get: 10 http://deb.debian.org/debian trixie/main amd64 libpython3.11-stdlib amd64 3.11.9-1 [1792 kB] Get: 11 http://deb.debian.org/debian trixie/main amd64 python3.11 amd64 3.11.9-1 [602 kB] Get: 12 http://deb.debian.org/debian trixie/main amd64 libpython3-stdlib amd64 3.11.8-1 [9332 B] Get: 13 http://deb.debian.org/debian trixie/main amd64 python3 amd64 3.11.8-1 [27.4 kB] Get: 14 http://deb.debian.org/debian trixie/main amd64 sensible-utils all 0.0.22 [22.4 kB] Get: 15 http://deb.debian.org/debian trixie/main amd64 openssl amd64 3.2.1-3 [1360 kB] Get: 16 http://deb.debian.org/debian trixie/main amd64 ca-certificates all 20240203 [158 kB] Get: 17 http://deb.debian.org/debian trixie/main amd64 libmagic-mgc amd64 1:5.45-3 [314 kB] Get: 18 http://deb.debian.org/debian trixie/main amd64 libmagic1t64 amd64 1:5.45-3 [105 kB] Get: 19 http://deb.debian.org/debian trixie/main amd64 file amd64 1:5.45-3 [42.9 kB] Get: 20 http://deb.debian.org/debian trixie/main amd64 gettext-base amd64 0.21-14+b1 [161 kB] Get: 21 http://deb.debian.org/debian trixie/main amd64 libuchardet0 amd64 0.0.8-1+b1 [68.8 kB] Get: 22 http://deb.debian.org/debian trixie/main amd64 groff-base amd64 1.23.0-4 [1180 kB] Get: 23 http://deb.debian.org/debian trixie/main amd64 bsdextrautils amd64 2.40-8 [92.8 kB] Get: 24 http://deb.debian.org/debian trixie/main amd64 libpipeline1 amd64 1.5.7-2 [38.0 kB] Get: 25 http://deb.debian.org/debian trixie/main amd64 man-db amd64 2.12.1-1 [1411 kB] Get: 26 http://deb.debian.org/debian trixie/main amd64 libbsd0 amd64 0.12.2-1 [131 kB] Get: 27 http://deb.debian.org/debian trixie/main amd64 libedit2 amd64 3.1-20230828-1+b1 [93.5 kB] Get: 28 http://deb.debian.org/debian trixie/main amd64 libcbor0.10 amd64 0.10.2-1.1 [27.8 kB] Get: 29 http://deb.debian.org/debian trixie/main amd64 libfido2-1 amd64 1.14.0-1+b2 [77.7 kB] Get: 30 http://deb.debian.org/debian trixie/main amd64 libkrb5support0 amd64 1.20.1-6+b1 [33.3 kB] Get: 31 http://deb.debian.org/debian trixie/main amd64 libcom-err2 amd64 1.47.1~rc2-1 [22.6 kB] Get: 32 http://deb.debian.org/debian trixie/main amd64 libk5crypto3 amd64 1.20.1-6+b1 [79.8 kB] Get: 33 http://deb.debian.org/debian trixie/main amd64 libkeyutils1 amd64 1.6.3-3 [8952 B] Get: 34 http://deb.debian.org/debian trixie/main amd64 libkrb5-3 amd64 1.20.1-6+b1 [333 kB] Get: 35 http://deb.debian.org/debian trixie/main amd64 libgssapi-krb5-2 amd64 1.20.1-6+b1 [135 kB] Get: 36 http://deb.debian.org/debian trixie/main amd64 openssh-client amd64 1:9.7p1-4 [965 kB] Get: 37 http://deb.debian.org/debian trixie/main amd64 ucf all 3.0043+nmu1 [55.2 kB] Get: 38 http://deb.debian.org/debian trixie/main amd64 aglfn all 1.7+git20191031.4036a9c-2 [30.5 kB] Get: 39 http://deb.debian.org/debian trixie/main amd64 m4 amd64 1.4.19-4 [287 kB] Get: 40 http://deb.debian.org/debian trixie/main amd64 autoconf all 2.71-3 [332 kB] Get: 41 http://deb.debian.org/debian trixie/main amd64 autotools-dev all 20220109.1 [51.6 kB] Get: 42 http://deb.debian.org/debian trixie/main amd64 automake all 1:1.16.5-1.3 [823 kB] Get: 43 http://deb.debian.org/debian trixie/main amd64 autopoint all 0.21-14 [496 kB] Get: 44 http://deb.debian.org/debian trixie/main amd64 libcapture-tiny-perl all 0.48-2 [24.6 kB] Get: 45 http://deb.debian.org/debian trixie/main amd64 libparams-util-perl amd64 1.102-3 [24.0 kB] Get: 46 http://deb.debian.org/debian trixie/main amd64 libsub-install-perl all 0.929-1 [10.5 kB] Get: 47 http://deb.debian.org/debian trixie/main amd64 libdata-optlist-perl all 0.114-1 [10.6 kB] Get: 48 http://deb.debian.org/debian trixie/main amd64 libb-hooks-op-check-perl amd64 0.22-3+b1 [10.6 kB] Get: 49 http://deb.debian.org/debian trixie/main amd64 libdynaloader-functions-perl all 0.003-3 [12.7 kB] Get: 50 http://deb.debian.org/debian trixie/main amd64 libdevel-callchecker-perl amd64 0.009-1 [15.9 kB] Get: 51 http://deb.debian.org/debian trixie/main amd64 libparams-classify-perl amd64 0.015-2+b3 [22.4 kB] Get: 52 http://deb.debian.org/debian trixie/main amd64 libmodule-runtime-perl all 0.016-2 [19.6 kB] Get: 53 http://deb.debian.org/debian trixie/main amd64 libtry-tiny-perl all 0.31-2 [22.6 kB] Get: 54 http://deb.debian.org/debian trixie/main amd64 libmodule-implementation-perl all 0.09-2 [12.6 kB] Get: 55 http://deb.debian.org/debian trixie/main amd64 libpackage-stash-perl all 0.40-1 [22.0 kB] Get: 56 http://deb.debian.org/debian trixie/main amd64 libclass-load-perl all 0.25-2 [15.3 kB] Get: 57 http://deb.debian.org/debian trixie/main amd64 libio-stringy-perl all 2.111-3 [56.5 kB] Get: 58 http://deb.debian.org/debian trixie/main amd64 libparams-validate-perl amd64 1.31-2+b2 [63.7 kB] Get: 59 http://deb.debian.org/debian trixie/main amd64 libsub-exporter-perl all 0.990-1 [50.6 kB] Get: 60 http://deb.debian.org/debian trixie/main amd64 libgetopt-long-descriptive-perl all 0.111-1 [27.8 kB] Get: 61 http://deb.debian.org/debian trixie/main amd64 libio-tiecombine-perl all 1.005-3 [10.8 kB] Get: 62 http://deb.debian.org/debian trixie/main amd64 libmodule-pluggable-perl all 5.2-5 [23.0 kB] Get: 63 http://deb.debian.org/debian trixie/main amd64 libstring-rewriteprefix-perl all 0.009-1 [7140 B] Get: 64 http://deb.debian.org/debian trixie/main amd64 libapp-cmd-perl all 0.336-1 [65.8 kB] Get: 65 http://deb.debian.org/debian trixie/main amd64 libboolean-perl all 0.46-3 [9924 B] Get: 66 http://deb.debian.org/debian trixie/main amd64 libsub-uplevel-perl all 0.2800-3 [14.0 kB] Get: 67 http://deb.debian.org/debian trixie/main amd64 libtest-exception-perl all 0.43-3 [16.9 kB] Get: 68 http://deb.debian.org/debian trixie/main amd64 libcarp-assert-more-perl all 2.4.0-1 [20.2 kB] Get: 69 http://deb.debian.org/debian trixie/main amd64 libfile-which-perl all 1.27-2 [15.1 kB] Get: 70 http://deb.debian.org/debian trixie/main amd64 libfile-homedir-perl all 1.006-2 [42.4 kB] Get: 71 http://deb.debian.org/debian trixie/main amd64 libclone-choose-perl all 0.010-2 [8676 B] Get: 72 http://deb.debian.org/debian trixie/main amd64 libhash-merge-perl all 0.302-1 [14.7 kB] Get: 73 http://deb.debian.org/debian trixie/main amd64 libjson-perl all 4.10000-1 [87.5 kB] Get: 74 http://deb.debian.org/debian trixie/main amd64 libexporter-tiny-perl all 1.006002-1 [38.7 kB] Get: 75 http://deb.debian.org/debian trixie/main amd64 liblist-moreutils-xs-perl amd64 0.430-4+b1 [42.3 kB] Get: 76 http://deb.debian.org/debian trixie/main amd64 liblist-moreutils-perl all 0.430-2 [46.9 kB] Get: 77 http://deb.debian.org/debian trixie/main amd64 liblog-log4perl-perl all 1.57-1 [367 kB] Get: 78 http://deb.debian.org/debian trixie/main amd64 libmouse-perl amd64 2.5.10-1+b5 [143 kB] Get: 79 http://deb.debian.org/debian trixie/main amd64 libmousex-nativetraits-perl all 1.09-3 [53.5 kB] Get: 80 http://deb.debian.org/debian trixie/main amd64 libmousex-strictconstructor-perl all 0.02-3 [5304 B] Get: 81 http://deb.debian.org/debian trixie/main amd64 libparse-recdescent-perl all 1.967015+dfsg-4 [147 kB] Get: 82 http://deb.debian.org/debian trixie/main amd64 libpath-tiny-perl all 0.144-1 [56.4 kB] Get: 83 http://deb.debian.org/debian trixie/main amd64 libpod-pom-perl all 2.01-4 [65.0 kB] Get: 84 http://deb.debian.org/debian trixie/main amd64 libregexp-common-perl all 2017060201-3 [175 kB] Get: 85 http://deb.debian.org/debian trixie/main amd64 libyaml-tiny-perl all 1.74-1 [30.7 kB] Get: 86 http://deb.debian.org/debian trixie/main amd64 libconfig-model-perl all 2.153-3 [448 kB] Get: 87 http://deb.debian.org/debian trixie/main amd64 libyaml-pp-perl all 0.38.0-1 [109 kB] Get: 88 http://deb.debian.org/debian trixie/main amd64 cme all 1.040-1 [68.8 kB] Get: 89 http://deb.debian.org/debian trixie/main amd64 libdebhelper-perl all 13.15.3 [88.0 kB] Get: 90 http://deb.debian.org/debian trixie/main amd64 libtool all 2.4.7-7 [517 kB] Get: 91 http://deb.debian.org/debian trixie/main amd64 dh-autoreconf all 20 [17.1 kB] Get: 92 http://deb.debian.org/debian trixie/main amd64 libarchive-zip-perl all 1.68-1 [104 kB] Get: 93 http://deb.debian.org/debian trixie/main amd64 libsub-override-perl all 0.10-1 [10.6 kB] Get: 94 http://deb.debian.org/debian trixie/main amd64 libfile-stripnondeterminism-perl all 1.13.1-1 [19.4 kB] Get: 95 http://deb.debian.org/debian trixie/main amd64 dh-strip-nondeterminism all 1.13.1-1 [8620 B] Get: 96 http://deb.debian.org/debian trixie/main amd64 libelf1t64 amd64 0.191-1+b1 [189 kB] Get: 97 http://deb.debian.org/debian trixie/main amd64 dwz amd64 0.15-1+b1 [110 kB] Get: 98 http://deb.debian.org/debian trixie/main amd64 libicu72 amd64 72.1-4+b1 [9395 kB] Get: 99 http://deb.debian.org/debian trixie/main amd64 libxml2 amd64 2.9.14+dfsg-1.3+b3 [692 kB] Get: 100 http://deb.debian.org/debian trixie/main amd64 gettext amd64 0.21-14+b1 [1301 kB] Get: 101 http://deb.debian.org/debian trixie/main amd64 intltool-debian all 0.35.0+20060710.6 [22.9 kB] Get: 102 http://deb.debian.org/debian trixie/main amd64 po-debconf all 1.0.21+nmu1 [248 kB] Get: 103 http://deb.debian.org/debian trixie/main amd64 debhelper all 13.15.3 [901 kB] Get: 104 http://deb.debian.org/debian trixie/main amd64 gnuplot-data all 6.0.0+dfsg1-3 [72.3 kB] Get: 105 http://deb.debian.org/debian trixie/main amd64 libbrotli1 amd64 1.1.0-2+b3 [305 kB] Get: 106 http://deb.debian.org/debian trixie/main amd64 libpng16-16t64 amd64 1.6.43-5 [278 kB] Get: 107 http://deb.debian.org/debian trixie/main amd64 libfreetype6 amd64 2.13.2+dfsg-1+b4 [439 kB] Get: 108 http://deb.debian.org/debian trixie/main amd64 fonts-dejavu-mono all 2.37-8 [489 kB] Get: 109 http://deb.debian.org/debian trixie/main amd64 fonts-dejavu-core all 2.37-8 [840 kB] Get: 110 http://deb.debian.org/debian trixie/main amd64 fonts-freefont-otf all 20211204+svn4273-2 [4328 kB] Get: 111 http://deb.debian.org/debian trixie/main amd64 fontconfig-config amd64 2.15.0-1.1 [317 kB] Get: 112 http://deb.debian.org/debian trixie/main amd64 libfontconfig1 amd64 2.15.0-1.1 [388 kB] Get: 113 http://deb.debian.org/debian trixie/main amd64 libpixman-1-0 amd64 0.42.2-1+b1 [556 kB] Get: 114 http://deb.debian.org/debian trixie/main amd64 libxau6 amd64 1:1.0.9-1+b1 [18.1 kB] Get: 115 http://deb.debian.org/debian trixie/main amd64 libxdmcp6 amd64 1:1.1.2-3+b1 [24.3 kB] Get: 116 http://deb.debian.org/debian trixie/main amd64 libxcb1 amd64 1.15-1 [144 kB] Get: 117 http://deb.debian.org/debian trixie/main amd64 libx11-data all 2:1.8.7-1 [328 kB] Get: 118 http://deb.debian.org/debian trixie/main amd64 libx11-6 amd64 2:1.8.7-1+b1 [799 kB] Get: 119 http://deb.debian.org/debian trixie/main amd64 libxcb-render0 amd64 1.15-1 [115 kB] Get: 120 http://deb.debian.org/debian trixie/main amd64 libxcb-shm0 amd64 1.15-1 [105 kB] Get: 121 http://deb.debian.org/debian trixie/main amd64 libxext6 amd64 2:1.3.4-1+b1 [52.9 kB] Get: 122 http://deb.debian.org/debian trixie/main amd64 libxrender1 amd64 1:0.9.10-1.1+b1 [27.9 kB] Get: 123 http://deb.debian.org/debian trixie/main amd64 libcairo2 amd64 1.18.0-3+b1 [531 kB] Get: 124 http://deb.debian.org/debian trixie/main amd64 libaom3 amd64 3.8.2-2 [1869 kB] Get: 125 http://deb.debian.org/debian trixie/main amd64 libdav1d7 amd64 1.4.1-1 [547 kB] Get: 126 http://deb.debian.org/debian trixie/main amd64 libabsl20230802 amd64 20230802.1-4 [464 kB] Get: 127 http://deb.debian.org/debian trixie/main amd64 libgav1-1 amd64 0.19.0-2+b1 [351 kB] Get: 128 http://deb.debian.org/debian trixie/main amd64 librav1e0 amd64 0.7.1-2 [900 kB] Get: 129 http://deb.debian.org/debian trixie/main amd64 libsharpyuv0 amd64 1.3.2-0.4+b1 [108 kB] Get: 130 http://deb.debian.org/debian trixie/main amd64 libsvtav1enc1d1 amd64 1.7.0+dfsg-2+b1 [2169 kB] Get: 131 http://deb.debian.org/debian trixie/main amd64 libjpeg62-turbo amd64 1:2.1.5-3 [167 kB] Get: 132 http://deb.debian.org/debian trixie/main amd64 libyuv0 amd64 0.0~git202401110.af6ac82-1 [169 kB] Get: 133 http://deb.debian.org/debian trixie/main amd64 libavif16 amd64 1.0.4-2 [106 kB] Get: 134 http://deb.debian.org/debian trixie/main amd64 libheif-plugin-dav1d amd64 1.17.6-1+b2 [9856 B] Get: 135 http://deb.debian.org/debian trixie/main amd64 libde265-0 amd64 1.0.15-1+b1 [187 kB] Get: 136 http://deb.debian.org/debian trixie/main amd64 libheif-plugin-libde265 amd64 1.17.6-1+b2 [13.1 kB] Get: 137 http://deb.debian.org/debian trixie/main amd64 libheif1 amd64 1.17.6-1+b2 [284 kB] Get: 138 http://deb.debian.org/debian trixie/main amd64 libdeflate0 amd64 1.20-1 [46.0 kB] Get: 139 http://deb.debian.org/debian trixie/main amd64 libjbig0 amd64 2.1-6.1+b1 [32.0 kB] Get: 140 http://deb.debian.org/debian trixie/main amd64 liblerc4 amd64 4.0.0+ds-4+b1 [171 kB] Get: 141 http://deb.debian.org/debian trixie/main amd64 libwebp7 amd64 1.3.2-0.4+b1 [308 kB] Get: 142 http://deb.debian.org/debian trixie/main amd64 libtiff6 amd64 4.5.1+git230720-4 [322 kB] Get: 143 http://deb.debian.org/debian trixie/main amd64 libxpm4 amd64 1:3.5.17-1+b1 [56.1 kB] Get: 144 http://deb.debian.org/debian trixie/main amd64 libgd3 amd64 2.3.3-9+b3 [125 kB] Get: 145 http://deb.debian.org/debian trixie/main amd64 libglib2.0-0t64 amd64 2.80.1-1 [1485 kB] Get: 146 http://deb.debian.org/debian trixie/main amd64 liblua5.4-0 amd64 5.4.6-3+b1 [147 kB] Get: 147 http://deb.debian.org/debian trixie/main amd64 fontconfig amd64 2.15.0-1.1 [463 kB] Get: 148 http://deb.debian.org/debian trixie/main amd64 libfribidi0 amd64 1.0.13-3+b1 [71.4 kB] Get: 149 http://deb.debian.org/debian trixie/main amd64 libgraphite2-3 amd64 1.3.14-2 [74.9 kB] Get: 150 http://deb.debian.org/debian trixie/main amd64 libharfbuzz0b amd64 8.3.0-2+b1 [2214 kB] Get: 151 http://deb.debian.org/debian trixie/main amd64 libthai-data all 0.1.29-2 [168 kB] Get: 152 http://deb.debian.org/debian trixie/main amd64 libdatrie1 amd64 0.2.13-3 [37.7 kB] Get: 153 http://deb.debian.org/debian trixie/main amd64 libthai0 amd64 0.1.29-2 [49.1 kB] Get: 154 http://deb.debian.org/debian trixie/main amd64 libpango-1.0-0 amd64 1.52.2+ds-1 [218 kB] Get: 155 http://deb.debian.org/debian trixie/main amd64 libpangoft2-1.0-0 amd64 1.52.2+ds-1 [48.1 kB] Get: 156 http://deb.debian.org/debian trixie/main amd64 libpangocairo-1.0-0 amd64 1.52.2+ds-1 [35.0 kB] Get: 157 http://deb.debian.org/debian trixie/main amd64 libwebpmux3 amd64 1.3.2-0.4+b1 [120 kB] Get: 158 http://deb.debian.org/debian trixie/main amd64 gnuplot-nox amd64 6.0.0+dfsg1-3 [916 kB] Get: 159 http://deb.debian.org/debian trixie/main amd64 dh-octave-autopkgtest all 1.8.0 [10.0 kB] Get: 160 http://deb.debian.org/debian trixie/main amd64 libapt-pkg-perl amd64 0.1.40+b5 [66.9 kB] Get: 161 http://deb.debian.org/debian trixie/main amd64 libarray-intspan-perl all 2.004-2 [25.7 kB] Get: 162 http://deb.debian.org/debian trixie/main amd64 libyaml-0-2 amd64 0.2.5-1+b1 [52.6 kB] Get: 163 http://deb.debian.org/debian trixie/main amd64 libyaml-libyaml-perl amd64 0.89+ds-1+b1 [35.0 kB] Get: 164 http://deb.debian.org/debian trixie/main amd64 libconfig-model-backend-yaml-perl all 2.134-2 [10.8 kB] Get: 165 http://deb.debian.org/debian trixie/main amd64 libexporter-lite-perl all 0.09-2 [10.7 kB] Get: 166 http://deb.debian.org/debian trixie/main amd64 libencode-locale-perl all 1.05-3 [12.9 kB] Get: 167 http://deb.debian.org/debian trixie/main amd64 libtimedate-perl all 2.3300-2 [39.3 kB] Get: 168 http://deb.debian.org/debian trixie/main amd64 libhttp-date-perl all 6.06-1 [10.7 kB] Get: 169 http://deb.debian.org/debian trixie/main amd64 libfile-listing-perl all 6.16-1 [12.4 kB] Get: 170 http://deb.debian.org/debian trixie/main amd64 libhtml-tagset-perl all 3.24-1 [14.7 kB] Get: 171 http://deb.debian.org/debian trixie/main amd64 liburi-perl all 5.28-1 [98.6 kB] Get: 172 http://deb.debian.org/debian trixie/main amd64 libhtml-parser-perl amd64 3.82-1 [98.9 kB] Get: 173 http://deb.debian.org/debian trixie/main amd64 libhtml-tree-perl all 5.07-3 [211 kB] Get: 174 http://deb.debian.org/debian trixie/main amd64 libclone-perl amd64 0.46-1+b2 [13.7 kB] Get: 175 http://deb.debian.org/debian trixie/main amd64 libio-html-perl all 1.004-3 [16.2 kB] Get: 176 http://deb.debian.org/debian trixie/main amd64 liblwp-mediatypes-perl all 6.04-2 [20.2 kB] Get: 177 http://deb.debian.org/debian trixie/main amd64 libhttp-message-perl all 6.45-1 [82.0 kB] Get: 178 http://deb.debian.org/debian trixie/main amd64 libhttp-cookies-perl all 6.11-1 [19.1 kB] Get: 179 http://deb.debian.org/debian trixie/main amd64 libhttp-negotiate-perl all 6.01-2 [13.1 kB] Get: 180 http://deb.debian.org/debian trixie/main amd64 perl-openssl-defaults amd64 7+b2 [6724 B] Get: 181 http://deb.debian.org/debian trixie/main amd64 libnet-ssleay-perl amd64 1.94-1+b1 [339 kB] Get: 182 http://deb.debian.org/debian trixie/main amd64 libio-socket-ssl-perl all 2.085-1 [218 kB] Get: 183 http://deb.debian.org/debian trixie/main amd64 libnet-http-perl all 6.23-1 [23.9 kB] Get: 184 http://deb.debian.org/debian trixie/main amd64 liblwp-protocol-https-perl all 6.14-1 [10.8 kB] Get: 185 http://deb.debian.org/debian trixie/main amd64 libwww-robotrules-perl all 6.02-1 [12.9 kB] Get: 186 http://deb.debian.org/debian trixie/main amd64 libwww-perl all 6.77-1 [183 kB] Get: 187 http://deb.debian.org/debian trixie/main amd64 liberror-perl all 0.17029-2 [29.0 kB] Get: 188 http://deb.debian.org/debian trixie/main amd64 libparse-debcontrol-perl all 2.005-6 [21.6 kB] Get: 189 http://deb.debian.org/debian trixie/main amd64 libsoftware-copyright-perl all 0.012-2 [18.0 kB] Get: 190 http://deb.debian.org/debian trixie/main amd64 libalgorithm-c3-perl all 0.11-2 [10.8 kB] Get: 191 http://deb.debian.org/debian trixie/main amd64 libclass-c3-perl all 0.35-2 [21.0 kB] Get: 192 http://deb.debian.org/debian trixie/main amd64 libmro-compat-perl all 0.15-2 [11.8 kB] Get: 193 http://deb.debian.org/debian trixie/main amd64 libdata-section-perl all 0.200008-1 [13.1 kB] Get: 194 http://deb.debian.org/debian trixie/main amd64 libtext-template-perl all 1.61-1 [54.4 kB] Get: 195 http://deb.debian.org/debian trixie/main amd64 libsoftware-license-perl all 0.104006-1 [116 kB] Get: 196 http://deb.debian.org/debian trixie/main amd64 libsoftware-licensemoreutils-perl all 1.009-1 [22.0 kB] Get: 197 http://deb.debian.org/debian trixie/main amd64 libsort-versions-perl all 1.62-3 [8928 B] Get: 198 http://deb.debian.org/debian trixie/main amd64 libtext-reform-perl all 1.20-5 [36.0 kB] Get: 199 http://deb.debian.org/debian trixie/main amd64 libtext-autoformat-perl all 1.750000-2 [35.2 kB] Get: 200 http://deb.debian.org/debian trixie/main amd64 libtext-levenshtein-damerau-perl all 0.41-3 [12.3 kB] Get: 201 http://deb.debian.org/debian trixie/main amd64 libtoml-tiny-perl all 0.16-1 [23.4 kB] Get: 202 http://deb.debian.org/debian trixie/main amd64 libindirect-perl amd64 0.39-2+b3 [27.1 kB] Get: 203 http://deb.debian.org/debian trixie/main amd64 libxs-parse-keyword-perl amd64 0.41-1 [60.0 kB] Get: 204 http://deb.debian.org/debian trixie/main amd64 libxs-parse-sublike-perl amd64 0.21-2+b2 [40.3 kB] Get: 205 http://deb.debian.org/debian trixie/main amd64 libobject-pad-perl amd64 0.808-1+b2 [119 kB] Get: 206 http://deb.debian.org/debian trixie/main amd64 libfeature-compat-class-perl all 0.06-1 [10.7 kB] Get: 207 http://deb.debian.org/debian trixie/main amd64 libsyntax-keyword-try-perl amd64 0.29-2 [26.9 kB] Get: 208 http://deb.debian.org/debian trixie/main amd64 libfeature-compat-try-perl all 0.05-1 [10.4 kB] Get: 209 http://deb.debian.org/debian trixie/main amd64 libio-interactive-perl all 1.025-1 [11.4 kB] Get: 210 http://deb.debian.org/debian trixie/main amd64 liblog-any-perl all 1.717-1 [78.9 kB] Get: 211 http://deb.debian.org/debian trixie/main amd64 liblog-any-adapter-screen-perl all 0.140-2 [13.3 kB] Get: 212 http://deb.debian.org/debian trixie/main amd64 libsub-exporter-progressive-perl all 0.001013-3 [7496 B] Get: 213 http://deb.debian.org/debian trixie/main amd64 libvariable-magic-perl amd64 0.64-1 [44.7 kB] Get: 214 http://deb.debian.org/debian trixie/main amd64 libb-hooks-endofscope-perl all 0.28-1 [17.5 kB] Get: 215 http://deb.debian.org/debian trixie/main amd64 libsub-identify-perl amd64 0.14-3+b2 [11.2 kB] Get: 216 http://deb.debian.org/debian trixie/main amd64 libsub-name-perl amd64 0.27-1+b2 [12.5 kB] Get: 217 http://deb.debian.org/debian trixie/main amd64 libnamespace-clean-perl all 0.27-2 [17.8 kB] Get: 218 http://deb.debian.org/debian trixie/main amd64 libnumber-compare-perl all 0.03-3 [6332 B] Get: 219 http://deb.debian.org/debian trixie/main amd64 libtext-glob-perl all 0.11-3 [7676 B] Get: 220 http://deb.debian.org/debian trixie/main amd64 libpath-iterator-rule-perl all 1.015-2 [41.7 kB] Get: 221 http://deb.debian.org/debian trixie/main amd64 libpod-parser-perl all 1.67-1 [94.1 kB] Get: 222 http://deb.debian.org/debian trixie/main amd64 libpod-constants-perl all 0.19-2 [17.3 kB] Get: 223 http://deb.debian.org/debian trixie/main amd64 libset-intspan-perl all 1.19-3 [25.3 kB] Get: 224 http://deb.debian.org/debian trixie/main amd64 libstring-copyright-perl all 0.003014-1 [23.4 kB] Get: 225 http://deb.debian.org/debian trixie/main amd64 libstring-escape-perl all 2010.002-3 [18.7 kB] Get: 226 http://deb.debian.org/debian trixie/main amd64 libregexp-pattern-license-perl all 3.11.0-1 [94.8 kB] Get: 227 http://deb.debian.org/debian trixie/main amd64 libregexp-pattern-perl all 0.2.14-2 [18.7 kB] Get: 228 http://deb.debian.org/debian trixie/main amd64 libstring-license-perl all 0.0.9-2 [35.5 kB] Get: 229 http://deb.debian.org/debian trixie/main amd64 licensecheck all 3.3.9-1 [50.1 kB] Get: 230 http://deb.debian.org/debian trixie/main amd64 diffstat amd64 1.66-1 [34.0 kB] Get: 231 http://deb.debian.org/debian trixie/main amd64 libassuan0 amd64 2.5.6-1+b1 [50.4 kB] Get: 232 http://deb.debian.org/debian trixie/main amd64 gpgconf amd64 2.2.40-3 [565 kB] Get: 233 http://deb.debian.org/debian trixie/main amd64 gpg amd64 2.2.40-3 [950 kB] Get: 234 http://deb.debian.org/debian trixie/main amd64 iso-codes all 4.16.0-1 [2936 kB] Get: 235 http://deb.debian.org/debian trixie/main amd64 libberkeleydb-perl amd64 0.64-2+b3 [121 kB] Get: 236 http://deb.debian.org/debian trixie/main amd64 libclass-xsaccessor-perl amd64 1.19-4+b3 [36.2 kB] Get: 237 http://deb.debian.org/debian trixie/main amd64 libconfig-tiny-perl all 2.30-1 [18.9 kB] Get: 238 http://deb.debian.org/debian trixie/main amd64 libconst-fast-perl all 0.014-2 [8792 B] Get: 239 http://deb.debian.org/debian trixie/main amd64 libcpanel-json-xs-perl amd64 4.37-1+b2 [128 kB] Get: 240 http://deb.debian.org/debian trixie/main amd64 libaliased-perl all 0.34-3 [13.5 kB] Get: 241 http://deb.debian.org/debian trixie/main amd64 libclass-data-inheritable-perl all 0.08-3 [8588 B] Get: 242 http://deb.debian.org/debian trixie/main amd64 libdevel-stacktrace-perl all 2.0500-1 [26.4 kB] Get: 243 http://deb.debian.org/debian trixie/main amd64 libexception-class-perl all 1.45-1 [34.6 kB] Get: 244 http://deb.debian.org/debian trixie/main amd64 libiterator-perl all 0.03+ds1-2 [18.8 kB] Get: 245 http://deb.debian.org/debian trixie/main amd64 libiterator-util-perl all 0.02+ds1-2 [14.0 kB] Get: 246 http://deb.debian.org/debian trixie/main amd64 libdata-dpath-perl all 0.59-1 [43.6 kB] Get: 247 http://deb.debian.org/debian trixie/main amd64 libnet-domain-tld-perl all 1.75-3 [31.9 kB] Get: 248 http://deb.debian.org/debian trixie/main amd64 libdata-validate-domain-perl all 0.10-1.1 [11.1 kB] Get: 249 http://deb.debian.org/debian trixie/main amd64 libnet-ipv6addr-perl all 1.02-1 [21.7 kB] Get: 250 http://deb.debian.org/debian trixie/main amd64 libnet-netmask-perl all 2.0002-2 [28.6 kB] Get: 251 http://deb.debian.org/debian trixie/main amd64 libnetaddr-ip-perl amd64 4.079+dfsg-2+b3 [98.1 kB] Get: 252 http://deb.debian.org/debian trixie/main amd64 libdata-validate-ip-perl all 0.31-1 [20.6 kB] Get: 253 http://deb.debian.org/debian trixie/main amd64 libdata-validate-uri-perl all 0.07-3 [11.0 kB] Get: 254 http://deb.debian.org/debian trixie/main amd64 libdevel-size-perl amd64 0.84-1 [23.9 kB] Get: 255 http://deb.debian.org/debian trixie/main amd64 libemail-address-xs-perl amd64 1.05-1+b3 [29.3 kB] Get: 256 http://deb.debian.org/debian trixie/main amd64 libipc-system-simple-perl all 1.30-2 [26.8 kB] Get: 257 http://deb.debian.org/debian trixie/main amd64 libfile-basedir-perl all 0.09-2 [15.1 kB] Get: 258 http://deb.debian.org/debian trixie/main amd64 libfile-find-rule-perl all 0.34-3 [26.6 kB] Get: 259 http://deb.debian.org/debian trixie/main amd64 libio-string-perl all 1.08-4 [12.1 kB] Get: 260 http://deb.debian.org/debian trixie/main amd64 libfont-ttf-perl all 1.06-2 [318 kB] Get: 261 http://deb.debian.org/debian trixie/main amd64 libhtml-html5-entities-perl all 0.004-3 [21.0 kB] Get: 262 http://deb.debian.org/debian trixie/main amd64 libhtml-tokeparser-simple-perl all 3.16-4 [39.1 kB] Get: 263 http://deb.debian.org/debian trixie/main amd64 libipc-run3-perl all 0.049-1 [31.5 kB] Get: 264 http://deb.debian.org/debian trixie/main amd64 libjson-maybexs-perl all 1.004005-1 [12.9 kB] Get: 265 http://deb.debian.org/debian trixie/main amd64 liblist-compare-perl all 0.55-2 [65.7 kB] Get: 266 http://deb.debian.org/debian trixie/main amd64 liblist-someutils-perl all 0.59-1 [37.1 kB] Get: 267 http://deb.debian.org/debian trixie/main amd64 liblist-utilsby-perl all 0.12-2 [15.5 kB] Get: 268 http://deb.debian.org/debian trixie/main amd64 libmldbm-perl all 2.05-4 [16.8 kB] Get: 269 http://deb.debian.org/debian trixie/main amd64 libclass-method-modifiers-perl all 2.15-1 [18.0 kB] Get: 270 http://deb.debian.org/debian trixie/main amd64 libimport-into-perl all 1.002005-2 [11.3 kB] Get: 271 http://deb.debian.org/debian trixie/main amd64 librole-tiny-perl all 2.002004-1 [21.4 kB] Get: 272 http://deb.debian.org/debian trixie/main amd64 libsub-quote-perl all 2.006008-1 [21.8 kB] Get: 273 http://deb.debian.org/debian trixie/main amd64 libmoo-perl all 2.005005-1 [58.0 kB] Get: 274 http://deb.debian.org/debian trixie/main amd64 libstrictures-perl all 2.000006-1 [18.6 kB] Get: 275 http://deb.debian.org/debian trixie/main amd64 libmoox-aliases-perl all 0.001006-2 [7156 B] Get: 276 http://deb.debian.org/debian trixie/main amd64 libperlio-gzip-perl amd64 0.20-1+b3 [17.5 kB] Get: 277 http://deb.debian.org/debian trixie/main amd64 libperlio-utf8-strict-perl amd64 0.010-1+b2 [11.4 kB] Get: 278 http://deb.debian.org/debian trixie/main amd64 libproc-processtable-perl amd64 0.636-1+b2 [42.2 kB] Get: 279 http://deb.debian.org/debian trixie/main amd64 libregexp-wildcards-perl all 1.05-3 [14.1 kB] Get: 280 http://deb.debian.org/debian trixie/main amd64 libsereal-decoder-perl amd64 5.004+ds-1+b2 [99.3 kB] Get: 281 http://deb.debian.org/debian trixie/main amd64 libsereal-encoder-perl amd64 5.004+ds-1+b2 [102 kB] Get: 282 http://deb.debian.org/debian trixie/main amd64 libterm-readkey-perl amd64 2.38-2+b3 [24.7 kB] Get: 283 http://deb.debian.org/debian trixie/main amd64 libtext-levenshteinxs-perl amd64 0.03-5+b3 [8700 B] Get: 284 http://deb.debian.org/debian trixie/main amd64 libmarkdown2 amd64 2.2.7-2+b1 [35.6 kB] Get: 285 http://deb.debian.org/debian trixie/main amd64 libtext-markdown-discount-perl amd64 0.16-1+b2 [13.0 kB] Get: 286 http://deb.debian.org/debian trixie/main amd64 libdata-messagepack-perl amd64 1.02-1+b3 [32.5 kB] Get: 287 http://deb.debian.org/debian trixie/main amd64 libtext-xslate-perl amd64 3.5.9-2 [173 kB] Get: 288 http://deb.debian.org/debian trixie/main amd64 libtime-duration-perl all 1.21-2 [13.1 kB] Get: 289 http://deb.debian.org/debian trixie/main amd64 libtime-moment-perl amd64 0.44-2+b3 [72.8 kB] Get: 290 http://deb.debian.org/debian trixie/main amd64 libunicode-utf8-perl amd64 0.62-2+b2 [20.2 kB] Get: 291 http://deb.debian.org/debian trixie/main amd64 libcgi-pm-perl all 4.64-1 [217 kB] Get: 292 http://deb.debian.org/debian trixie/main amd64 libhtml-form-perl all 6.11-1 [33.1 kB] Get: 293 http://deb.debian.org/debian trixie/main amd64 libwww-mechanize-perl all 2.18-1 [114 kB] Get: 294 http://deb.debian.org/debian trixie/main amd64 libxml-namespacesupport-perl all 1.12-2 [15.1 kB] Get: 295 http://deb.debian.org/debian trixie/main amd64 libxml-sax-base-perl all 1.09-3 [20.6 kB] Get: 296 http://deb.debian.org/debian trixie/main amd64 libxml-sax-perl all 1.02+dfsg-3 [59.4 kB] Get: 297 http://deb.debian.org/debian trixie/main amd64 libxml-libxml-perl amd64 2.0207+dfsg+really+2.0134-1+b3 [313 kB] Get: 298 http://deb.debian.org/debian trixie/main amd64 liblz1 amd64 1.15~pre1-1 [38.5 kB] Get: 299 http://deb.debian.org/debian trixie/main amd64 plzip amd64 1.11-1 [63.9 kB] Get: 300 http://deb.debian.org/debian trixie/main amd64 liblzo2-2 amd64 2.10-2+b1 [54.8 kB] Get: 301 http://deb.debian.org/debian trixie/main amd64 lzop amd64 1.04-2 [84.2 kB] Get: 302 http://deb.debian.org/debian trixie/main amd64 patchutils amd64 0.4.2-1 [77.5 kB] Get: 303 http://deb.debian.org/debian trixie/main amd64 t1utils amd64 1.41-4 [62.1 kB] Get: 304 http://deb.debian.org/debian trixie/main amd64 unzip amd64 6.0-28 [166 kB] Get: 305 http://deb.debian.org/debian trixie/main amd64 lintian all 2.117.0 [1052 kB] Get: 306 http://deb.debian.org/debian trixie/main amd64 libconfig-model-dpkg-perl all 3.004 [173 kB] Get: 307 http://deb.debian.org/debian trixie/main amd64 libconvert-binhex-perl all 1.125-3 [27.4 kB] Get: 308 http://deb.debian.org/debian trixie/main amd64 libnet-smtp-ssl-perl all 1.04-2 [6548 B] Get: 309 http://deb.debian.org/debian trixie/main amd64 libmailtools-perl all 2.21-3 [88.6 kB] Get: 310 http://deb.debian.org/debian trixie/main amd64 libmime-tools-perl all 5.515-1 [203 kB] Get: 311 http://deb.debian.org/debian trixie/main amd64 libsuitesparseconfig7 amd64 1:7.7.0+dfsg-2 [22.4 kB] Get: 312 http://deb.debian.org/debian trixie/main amd64 libamd3 amd64 1:7.7.0+dfsg-2 [39.0 kB] Get: 313 http://deb.debian.org/debian trixie/main amd64 libblas3 amd64 3.12.0-3 [148 kB] Get: 314 http://deb.debian.org/debian trixie/main amd64 libgfortran5 amd64 14-20240330-1 [836 kB] Get: 315 http://deb.debian.org/debian trixie/main amd64 liblapack3 amd64 3.12.0-3 [2407 kB] Get: 316 http://deb.debian.org/debian trixie/main amd64 libarpack2t64 amd64 3.9.1-1.1+b1 [104 kB] Get: 317 http://deb.debian.org/debian trixie/main amd64 libccolamd3 amd64 1:7.7.0+dfsg-2 [37.9 kB] Get: 318 http://deb.debian.org/debian trixie/main amd64 libcamd3 amd64 1:7.7.0+dfsg-2 [36.0 kB] Get: 319 http://deb.debian.org/debian trixie/main amd64 libcolamd3 amd64 1:7.7.0+dfsg-2 [31.3 kB] Get: 320 http://deb.debian.org/debian trixie/main amd64 libcholmod5 amd64 1:7.7.0+dfsg-2 [623 kB] Get: 321 http://deb.debian.org/debian trixie/main amd64 libsasl2-modules-db amd64 2.1.28+dfsg1-6 [19.5 kB] Get: 322 http://deb.debian.org/debian trixie/main amd64 libsasl2-2 amd64 2.1.28+dfsg1-6 [56.9 kB] Get: 323 http://deb.debian.org/debian trixie/main amd64 libldap-2.5-0 amd64 2.5.17+dfsg-1 [186 kB] Get: 324 http://deb.debian.org/debian trixie/main amd64 libnghttp2-14 amd64 1.61.0-1+b1 [75.6 kB] Get: 325 http://deb.debian.org/debian trixie/main amd64 libpsl5t64 amd64 0.21.2-1.1 [56.8 kB] Get: 326 http://deb.debian.org/debian trixie/main amd64 librtmp1 amd64 2.4+20151223.gitfa8646d.1-2+b4 [58.5 kB] Get: 327 http://deb.debian.org/debian trixie/main amd64 libssh2-1t64 amd64 1.11.0-4.1+b2 [215 kB] Get: 328 http://deb.debian.org/debian trixie/main amd64 libcurl3t64-gnutls amd64 8.7.1-3 [432 kB] Get: 329 http://deb.debian.org/debian trixie/main amd64 libcxsparse4 amd64 1:7.7.0+dfsg-2 [82.3 kB] Get: 330 http://deb.debian.org/debian trixie/main amd64 libfftw3-double3 amd64 3.3.10-1+b2 [779 kB] Get: 331 http://deb.debian.org/debian trixie/main amd64 libfftw3-single3 amd64 3.3.10-1+b2 [806 kB] Get: 332 http://deb.debian.org/debian trixie/main amd64 libxfixes3 amd64 1:6.0.0-2+b1 [20.3 kB] Get: 333 http://deb.debian.org/debian trixie/main amd64 libxcursor1 amd64 1:1.2.1-1+b1 [36.2 kB] Get: 334 http://deb.debian.org/debian trixie/main amd64 libxft2 amd64 2.3.6-1+b1 [54.2 kB] Get: 335 http://deb.debian.org/debian trixie/main amd64 libxinerama1 amd64 2:1.1.4-3+b1 [16.0 kB] Get: 336 http://deb.debian.org/debian trixie/main amd64 libfltk1.3t64 amd64 1.3.8-6.1 [553 kB] Get: 337 http://deb.debian.org/debian trixie/main amd64 libglvnd0 amd64 1.7.0-1+b1 [56.3 kB] Get: 338 http://deb.debian.org/debian trixie/main amd64 libdrm-common all 2.4.120-2 [7688 B] Get: 339 http://deb.debian.org/debian trixie/main amd64 libdrm2 amd64 2.4.120-2 [38.1 kB] Get: 340 http://deb.debian.org/debian trixie/main amd64 libglapi-mesa amd64 24.0.6-1+b1 [36.6 kB] Get: 341 http://deb.debian.org/debian trixie/main amd64 libx11-xcb1 amd64 2:1.8.7-1+b1 [232 kB] Get: 342 http://deb.debian.org/debian trixie/main amd64 libxcb-dri2-0 amd64 1.15-1 [107 kB] Get: 343 http://deb.debian.org/debian trixie/main amd64 libxcb-dri3-0 amd64 1.15-1 [107 kB] Get: 344 http://deb.debian.org/debian trixie/main amd64 libxcb-glx0 amd64 1.15-1 [122 kB] Get: 345 http://deb.debian.org/debian trixie/main amd64 libxcb-present0 amd64 1.15-1 [105 kB] Get: 346 http://deb.debian.org/debian trixie/main amd64 libxcb-randr0 amd64 1.15-1 [117 kB] Get: 347 http://deb.debian.org/debian trixie/main amd64 libxcb-sync1 amd64 1.15-1 [109 kB] Get: 348 http://deb.debian.org/debian trixie/main amd64 libxcb-xfixes0 amd64 1.15-1 [109 kB] Get: 349 http://deb.debian.org/debian trixie/main amd64 libxshmfence1 amd64 1.3-1+b1 [8852 B] Get: 350 http://deb.debian.org/debian trixie/main amd64 libxxf86vm1 amd64 1:1.1.4-1+b2 [20.8 kB] Get: 351 http://deb.debian.org/debian trixie/main amd64 libvulkan1 amd64 1.3.280.0-1 [123 kB] Get: 352 http://deb.debian.org/debian trixie/main amd64 libdrm-amdgpu1 amd64 2.4.120-2 [21.4 kB] Get: 353 http://deb.debian.org/debian trixie/main amd64 libpciaccess0 amd64 0.17-3+b1 [51.9 kB] Get: 354 http://deb.debian.org/debian trixie/main amd64 libdrm-intel1 amd64 2.4.120-2 [62.7 kB] Get: 355 http://deb.debian.org/debian trixie/main amd64 libdrm-nouveau2 amd64 2.4.120-2 [19.3 kB] Get: 356 http://deb.debian.org/debian trixie/main amd64 libdrm-radeon1 amd64 2.4.120-2 [22.2 kB] Get: 357 http://deb.debian.org/debian trixie/main amd64 libz3-4 amd64 4.8.12-3.1+b2 [7346 kB] Get: 358 http://deb.debian.org/debian trixie/main amd64 libllvm17t64 amd64 1:17.0.6-12 [23.7 MB] Get: 359 http://deb.debian.org/debian trixie/main amd64 libsensors-config all 1:3.6.0-9 [14.6 kB] Get: 360 http://deb.debian.org/debian trixie/main amd64 libsensors5 amd64 1:3.6.0-9 [34.6 kB] Get: 361 http://deb.debian.org/debian trixie/main amd64 libgl1-mesa-dri amd64 24.0.6-1+b1 [8279 kB] Get: 362 http://deb.debian.org/debian trixie/main amd64 libglx-mesa0 amd64 24.0.6-1+b1 [151 kB] Get: 363 http://deb.debian.org/debian trixie/main amd64 libglx0 amd64 1.7.0-1+b1 [35.0 kB] Get: 364 http://deb.debian.org/debian trixie/main amd64 libgl1 amd64 1.7.0-1+b1 [89.8 kB] Get: 365 http://deb.debian.org/debian trixie/main amd64 libfltk-gl1.3t64 amd64 1.3.8-6.1 [62.4 kB] Get: 366 http://deb.debian.org/debian trixie/main amd64 libgl2ps1.4 amd64 1.4.2+dfsg1-2 [41.3 kB] Get: 367 http://deb.debian.org/debian trixie/main amd64 libltdl7 amd64 2.4.7-7+b1 [393 kB] Get: 368 http://deb.debian.org/debian trixie/main amd64 libglpk40 amd64 5.0-1+b1 [397 kB] Get: 369 http://deb.debian.org/debian trixie/main amd64 libopengl0 amd64 1.7.0-1+b1 [31.1 kB] Get: 370 http://deb.debian.org/debian trixie/main amd64 libglu1-mesa amd64 9.0.2-1.1+b1 [180 kB] Get: 371 http://deb.debian.org/debian trixie/main amd64 libhwy1t64 amd64 1.0.7-8.1 [526 kB] Get: 372 http://deb.debian.org/debian trixie/main amd64 liblcms2-2 amd64 2.14-2+b1 [154 kB] Get: 373 http://deb.debian.org/debian trixie/main amd64 libjxl0.7 amd64 0.7.0-10.2+b3 [1068 kB] Get: 374 http://deb.debian.org/debian trixie/main amd64 libwmflite-0.2-7 amd64 0.2.13-1.1+b2 [75.4 kB] Get: 375 http://deb.debian.org/debian trixie/main amd64 libgraphicsmagick-q16-3t64 amd64 1.4+really1.3.43-1 [1200 kB] Get: 376 http://deb.debian.org/debian trixie/main amd64 libgraphicsmagick++-q16-12t64 amd64 1.4+really1.3.43-1 [118 kB] Get: 377 http://deb.debian.org/debian trixie/main amd64 libcurl4t64 amd64 8.7.1-3 [441 kB] Get: 378 http://deb.debian.org/debian trixie/main amd64 libaec0 amd64 1.1.3-1 [23.4 kB] Get: 379 http://deb.debian.org/debian trixie/main amd64 libsz2 amd64 1.1.3-1 [7740 B] Get: 380 http://deb.debian.org/debian trixie/main amd64 libhdf5-103-1t64 amd64 1.10.10+repack-3.3 [1241 kB] Get: 381 http://deb.debian.org/debian trixie/main amd64 libasound2-data all 1.2.11-1 [20.9 kB] Get: 382 http://deb.debian.org/debian trixie/main amd64 libasound2t64 amd64 1.2.11-1+b1 [369 kB] Get: 383 http://deb.debian.org/debian trixie/main amd64 libopus0 amd64 1.4-1+b1 [198 kB] Get: 384 http://deb.debian.org/debian trixie/main amd64 libsamplerate0 amd64 0.2.2-4+b1 [951 kB] Get: 385 http://deb.debian.org/debian trixie/main amd64 libjack-jackd2-0 amd64 1.9.21~dfsg-3+b3 [284 kB] Get: 386 http://deb.debian.org/debian trixie/main amd64 libportaudio2 amd64 19.6.0-1.2+b2 [64.8 kB] Get: 387 http://deb.debian.org/debian trixie/main amd64 libqhull-r8.0 amd64 2020.2-6+b1 [245 kB] Get: 388 http://deb.debian.org/debian trixie/main amd64 libqrupdate1 amd64 1.1.2-4+b1 [38.4 kB] Get: 389 http://deb.debian.org/debian trixie/main amd64 libqscintilla2-qt5-l10n all 2.14.1+dfsg-1 [105 kB] Get: 390 http://deb.debian.org/debian trixie/main amd64 shared-mime-info amd64 2.4-4 [759 kB] Get: 391 http://deb.debian.org/debian trixie/main amd64 libdouble-conversion3 amd64 3.3.0-1+b1 [41.0 kB] Get: 392 http://deb.debian.org/debian trixie/main amd64 libpcre2-16-0 amd64 10.42-4+b1 [246 kB] Get: 393 http://deb.debian.org/debian trixie/main amd64 libqt5core5t64 amd64 5.15.10+dfsg-7.2+b1 [1835 kB] Get: 394 http://deb.debian.org/debian trixie/main amd64 libwayland-server0 amd64 1.22.0-2.1+b1 [33.0 kB] Get: 395 http://deb.debian.org/debian trixie/main amd64 libgbm1 amd64 24.0.6-1+b1 [41.0 kB] Get: 396 http://deb.debian.org/debian trixie/main amd64 libwayland-client0 amd64 1.22.0-2.1+b1 [25.7 kB] Get: 397 http://deb.debian.org/debian trixie/main amd64 libegl-mesa0 amd64 24.0.6-1+b1 [119 kB] Get: 398 http://deb.debian.org/debian trixie/main amd64 libegl1 amd64 1.7.0-1+b1 [34.3 kB] Get: 399 http://deb.debian.org/debian trixie/main amd64 x11-common all 1:7.7+23 [252 kB] Get: 400 http://deb.debian.org/debian trixie/main amd64 libice6 amd64 2:1.0.10-1+b1 [56.7 kB] Get: 401 http://deb.debian.org/debian trixie/main amd64 libevdev2 amd64 1.13.1+dfsg-1+b1 [32.6 kB] Get: 402 http://deb.debian.org/debian trixie/main amd64 libmtdev1t64 amd64 1.1.6-1.2 [22.2 kB] Get: 403 http://deb.debian.org/debian trixie/main amd64 libgudev-1.0-0 amd64 238-5 [14.4 kB] Get: 404 http://deb.debian.org/debian trixie/main amd64 libwacom-common all 2.10.0-2 [62.5 kB] Get: 405 http://deb.debian.org/debian trixie/main amd64 libwacom9 amd64 2.10.0-2 [22.4 kB] Get: 406 http://deb.debian.org/debian trixie/main amd64 libinput-bin amd64 1.25.0-1+b2 [24.8 kB] Get: 407 http://deb.debian.org/debian trixie/main amd64 libinput10 amd64 1.25.0-1+b2 [128 kB] Get: 408 http://deb.debian.org/debian trixie/main amd64 libmd4c0 amd64 0.4.8-1+b1 [45.1 kB] Get: 409 http://deb.debian.org/debian trixie/main amd64 libdbus-1-3 amd64 1.14.10-4+b1 [203 kB] Get: 410 http://deb.debian.org/debian trixie/main amd64 libqt5dbus5t64 amd64 5.15.10+dfsg-7.2+b1 [213 kB] Get: 411 http://deb.debian.org/debian trixie/main amd64 libqt5network5t64 amd64 5.15.10+dfsg-7.2+b1 [677 kB] Get: 412 http://deb.debian.org/debian trixie/main amd64 libsm6 amd64 2:1.2.3-1+b1 [33.6 kB] Get: 413 http://deb.debian.org/debian trixie/main amd64 libxcb-icccm4 amd64 0.4.1-1.1+b1 [26.8 kB] Get: 414 http://deb.debian.org/debian trixie/main amd64 libxcb-util1 amd64 0.4.0-1+b1 [23.2 kB] Get: 415 http://deb.debian.org/debian trixie/main amd64 libxcb-image0 amd64 0.4.0-2+b1 [22.2 kB] Get: 416 http://deb.debian.org/debian trixie/main amd64 libxcb-keysyms1 amd64 0.4.0-1+b2 [16.4 kB] Get: 417 http://deb.debian.org/debian trixie/main amd64 libxcb-render-util0 amd64 0.3.9-1+b1 [18.3 kB] Get: 418 http://deb.debian.org/debian trixie/main amd64 libxcb-shape0 amd64 1.15-1 [106 kB] Get: 419 http://deb.debian.org/debian trixie/main amd64 libxcb-xinerama0 amd64 1.15-1 [105 kB] Get: 420 http://deb.debian.org/debian trixie/main amd64 libxcb-xinput0 amd64 1.15-1 [130 kB] Get: 421 http://deb.debian.org/debian trixie/main amd64 libxcb-xkb1 amd64 1.15-1 [129 kB] Get: 422 http://deb.debian.org/debian trixie/main amd64 xkb-data all 2.41-2 [795 kB] Get: 423 http://deb.debian.org/debian trixie/main amd64 libxkbcommon0 amd64 1.6.0-1+b1 [109 kB] Get: 424 http://deb.debian.org/debian trixie/main amd64 libxkbcommon-x11-0 amd64 1.6.0-1+b1 [16.2 kB] Get: 425 http://deb.debian.org/debian trixie/main amd64 libqt5gui5t64 amd64 5.15.10+dfsg-7.2+b1 [3444 kB] Get: 426 http://deb.debian.org/debian trixie/main amd64 libavahi-common-data amd64 0.8-13+b2 [112 kB] Get: 427 http://deb.debian.org/debian trixie/main amd64 libavahi-common3 amd64 0.8-13+b2 [43.3 kB] Get: 428 http://deb.debian.org/debian trixie/main amd64 libavahi-client3 amd64 0.8-13+b2 [47.0 kB] Get: 429 http://deb.debian.org/debian trixie/main amd64 libcups2t64 amd64 2.4.7-1.2+b1 [247 kB] Get: 430 http://deb.debian.org/debian trixie/main amd64 libqt5widgets5t64 amd64 5.15.10+dfsg-7.2+b1 [2385 kB] Get: 431 http://deb.debian.org/debian trixie/main amd64 libqt5printsupport5t64 amd64 5.15.10+dfsg-7.2+b1 [204 kB] Get: 432 http://deb.debian.org/debian trixie/main amd64 libqscintilla2-qt5-15 amd64 2.14.1+dfsg-1+b2 [1118 kB] Get: 433 http://deb.debian.org/debian trixie/main amd64 libqt5sql5t64 amd64 5.15.10+dfsg-7.2+b1 [123 kB] Get: 434 http://deb.debian.org/debian trixie/main amd64 libqt5help5 amd64 5.15.10-7 [149 kB] Get: 435 http://deb.debian.org/debian trixie/main amd64 libqt5xml5t64 amd64 5.15.10+dfsg-7.2+b1 [123 kB] Get: 436 http://deb.debian.org/debian trixie/main amd64 libogg0 amd64 1.3.5-3+b1 [23.7 kB] Get: 437 http://deb.debian.org/debian trixie/main amd64 libflac12t64 amd64 1.4.3+ds-2.1 [200 kB] Get: 438 http://deb.debian.org/debian trixie/main amd64 libmp3lame0 amd64 3.100-6+b2 [361 kB] Get: 439 http://deb.debian.org/debian trixie/main amd64 libmpg123-0t64 amd64 1.32.6-3 [148 kB] Get: 440 http://deb.debian.org/debian trixie/main amd64 libvorbis0a amd64 1.3.7-2 [89.7 kB] Get: 441 http://deb.debian.org/debian trixie/main amd64 libvorbisenc2 amd64 1.3.7-2 [75.9 kB] Get: 442 http://deb.debian.org/debian trixie/main amd64 libsndfile1 amd64 1.2.2-1+b2 [197 kB] Get: 443 http://deb.debian.org/debian trixie/main amd64 libspqr4 amd64 1:7.7.0+dfsg-2 [140 kB] Get: 444 http://deb.debian.org/debian trixie/main amd64 libsundials-ida6 amd64 6.4.1+dfsg1-3+b5 [145 kB] Get: 445 http://deb.debian.org/debian trixie/main amd64 libbtf2 amd64 1:7.7.0+dfsg-2 [23.3 kB] Get: 446 http://deb.debian.org/debian trixie/main amd64 libklu2 amd64 1:7.7.0+dfsg-2 [87.1 kB] Get: 447 http://deb.debian.org/debian trixie/main amd64 libfftw3-long3 amd64 3.3.10-1+b2 [344 kB] Get: 448 http://deb.debian.org/debian trixie/main amd64 libevent-core-2.1-7t64 amd64 2.1.12-stable-8.1+b3 [132 kB] Get: 449 http://deb.debian.org/debian trixie/main amd64 libevent-pthreads-2.1-7t64 amd64 2.1.12-stable-8.1+b3 [54.1 kB] Get: 450 http://deb.debian.org/debian trixie/main amd64 libnl-3-200 amd64 3.7.0-0.3 [59.0 kB] Get: 451 http://deb.debian.org/debian trixie/main amd64 libnl-route-3-200 amd64 3.7.0-0.3 [181 kB] Get: 452 http://deb.debian.org/debian trixie/main amd64 libibverbs1 amd64 50.0-2+b1 [61.7 kB] Get: 453 http://deb.debian.org/debian trixie/main amd64 ibverbs-providers amd64 50.0-2+b1 [342 kB] Get: 454 http://deb.debian.org/debian trixie/main amd64 libpsm-infinipath1 amd64 3.3+20.604758e7-6.3 [170 kB] Get: 455 http://deb.debian.org/debian trixie/main amd64 libnuma1 amd64 2.0.18-1 [21.9 kB] Get: 456 http://deb.debian.org/debian trixie/main amd64 libpsm2-2 amd64 11.2.185-2 [180 kB] Get: 457 http://deb.debian.org/debian trixie/main amd64 librdmacm1t64 amd64 50.0-2+b1 [70.2 kB] Get: 458 http://deb.debian.org/debian trixie/main amd64 libfabric1 amd64 1.17.0-3+b1 [628 kB] Get: 459 http://deb.debian.org/debian trixie/main amd64 libhwloc15 amd64 2.10.0-1+b1 [161 kB] Get: 460 http://deb.debian.org/debian trixie/main amd64 libmunge2 amd64 0.5.15-4 [19.8 kB] Get: 461 http://deb.debian.org/debian trixie/main amd64 libxnvctrl0 amd64 535.171.04-1 [13.8 kB] Get: 462 http://deb.debian.org/debian trixie/main amd64 ocl-icd-libopencl1 amd64 2.3.2-1+b1 [40.3 kB] Get: 463 http://deb.debian.org/debian trixie/main amd64 libhwloc-plugins amd64 2.10.0-1+b1 [18.0 kB] Get: 464 http://deb.debian.org/debian trixie/main amd64 libpmix2t64 amd64 5.0.2-3 [652 kB] Get: 465 http://deb.debian.org/debian trixie/main amd64 libamd-comgr2 amd64 6.0+git20231212.4510c28+dfsg-3+b1 [13.0 MB] Get: 466 http://deb.debian.org/debian trixie/main amd64 libhsakmt1 amd64 5.7.0-1 [60.7 kB] Get: 467 http://deb.debian.org/debian trixie/main amd64 libhsa-runtime64-1 amd64 5.7.1-2 [504 kB] Get: 468 http://deb.debian.org/debian trixie/main amd64 libamdhip64-5 amd64 5.7.1-3 [8760 kB] Get: 469 http://deb.debian.org/debian trixie/main amd64 libucx0 amd64 1.16.0+ds-5 [1109 kB] Get: 470 http://deb.debian.org/debian trixie/main amd64 libopenmpi3t64 amd64 4.1.6-13.2 [2428 kB] Get: 471 http://deb.debian.org/debian trixie/main amd64 libfftw3-mpi3 amd64 3.3.10-1+b2 [64.2 kB] Get: 472 http://deb.debian.org/debian trixie/main amd64 libhdf5-openmpi-103-1t64 amd64 1.10.10+repack-3.3 [1301 kB] Get: 473 http://deb.debian.org/debian trixie/main amd64 libcombblas2.0.0t64 amd64 2.0.0-3.1+b1 [285 kB] Get: 474 http://deb.debian.org/debian trixie/main amd64 libmetis5 amd64 5.1.0.dfsg-7+b1 [175 kB] Get: 475 http://deb.debian.org/debian trixie/main amd64 libptscotch-7.0 amd64 7.0.4-2 [681 kB] Get: 476 http://deb.debian.org/debian trixie/main amd64 libsuperlu-dist8 amd64 8.2.1+dfsg1-1+b2 [605 kB] Get: 477 http://deb.debian.org/debian trixie/main amd64 libhypre-2.28.0 amd64 2.28.0-8+b2 [1640 kB] Get: 478 http://deb.debian.org/debian trixie/main amd64 openmpi-common all 4.1.6-13.2 [169 kB] Get: 479 http://deb.debian.org/debian trixie/main amd64 openmpi-bin amd64 4.1.6-13.2 [226 kB] Get: 480 http://deb.debian.org/debian trixie/main amd64 mpi-default-bin amd64 1.15 [2408 B] Get: 481 http://deb.debian.org/debian trixie/main amd64 libscalapack-openmpi2.2 amd64 2.2.1-3.1 [1567 kB] Get: 482 http://deb.debian.org/debian trixie/main amd64 libmumps-5.6t64 amd64 5.6.2-2.1+b1 [1895 kB] Get: 483 http://deb.debian.org/debian trixie/main amd64 libsuperlu6 amd64 6.0.1+dfsg1-1+b1 [170 kB] Get: 484 http://deb.debian.org/debian trixie/main amd64 libscotch-7.0 amd64 7.0.4-2 [410 kB] Get: 485 http://deb.debian.org/debian trixie/main amd64 libtrilinos-kokkos-13.2 amd64 13.2.0-5+b3 [107 kB] Get: 486 http://deb.debian.org/debian trixie/main amd64 libtrilinos-teuchos-13.2 amd64 13.2.0-5+b3 [1278 kB] Get: 487 http://deb.debian.org/debian trixie/main amd64 libtrilinos-epetra-13.2 amd64 13.2.0-5+b3 [441 kB] Get: 488 http://deb.debian.org/debian trixie/main amd64 libtrilinos-triutils-13.2 amd64 13.2.0-5+b3 [125 kB] Get: 489 http://deb.debian.org/debian trixie/main amd64 libtrilinos-epetraext-13.2 amd64 13.2.0-5+b3 [451 kB] Get: 490 http://deb.debian.org/debian trixie/main amd64 libtrilinos-trilinosss-13.2 amd64 13.2.0-5+b3 [88.0 kB] Get: 491 http://deb.debian.org/debian trixie/main amd64 libtrilinos-amesos-13.2 amd64 13.2.0-5+b3 [120 kB] Get: 492 http://deb.debian.org/debian trixie/main amd64 libtrilinos-aztecoo-13.2 amd64 13.2.0-5+b3 [210 kB] Get: 493 http://deb.debian.org/debian trixie/main amd64 libtrilinos-galeri-13.2 amd64 13.2.0-5+b3 [94.3 kB] Get: 494 http://deb.debian.org/debian trixie/main amd64 libtrilinos-ifpack-13.2 amd64 13.2.0-5+b3 [493 kB] Get: 495 http://deb.debian.org/debian trixie/main amd64 libtrilinos-zoltan-13.2 amd64 13.2.0-5+b3 [386 kB] Get: 496 http://deb.debian.org/debian trixie/main amd64 libtrilinos-ml-13.2 amd64 13.2.0-5+b3 [1009 kB] Get: 497 http://deb.debian.org/debian trixie/main amd64 libumfpack6 amd64 1:7.7.0+dfsg-2 [267 kB] Get: 498 http://deb.debian.org/debian trixie/main amd64 libpetsc-real3.19t64 amd64 3.19.6+dfsg1-2.2 [6847 kB] Get: 499 http://deb.debian.org/debian trixie/main amd64 libsundials-nvecparallel-petsc6 amd64 6.4.1+dfsg1-3+b5 [58.7 kB] Get: 500 http://deb.debian.org/debian trixie/main amd64 libsundials-sunmatrix4 amd64 6.4.1+dfsg1-3+b5 [105 kB] Get: 501 http://deb.debian.org/debian trixie/main amd64 libsundials-sunlinsol3 amd64 6.4.1+dfsg1-3+b5 [202 kB] Get: 502 http://deb.debian.org/debian trixie/main amd64 libtext-unidecode-perl all 1.30-3 [101 kB] Get: 503 http://deb.debian.org/debian trixie/main amd64 texinfo-lib amd64 7.1-3+b1 [224 kB] Get: 504 http://deb.debian.org/debian trixie/main amd64 tex-common all 6.18 [32.5 kB] Get: 505 http://deb.debian.org/debian trixie/main amd64 texinfo all 7.1-3 [1748 kB] Get: 506 http://deb.debian.org/debian trixie/main amd64 octave-common all 8.4.0-1 [6368 kB] Get: 507 http://deb.debian.org/debian trixie/main amd64 octave amd64 8.4.0-1+b3 [9724 kB] Get: 508 http://deb.debian.org/debian trixie/main amd64 libncurses6 amd64 6.4+20240414-1 [104 kB] Get: 509 http://deb.debian.org/debian trixie/main amd64 libncurses-dev amd64 6.4+20240414-1 [349 kB] Get: 510 http://deb.debian.org/debian trixie/main amd64 libreadline-dev amd64 8.2-4 [152 kB] Get: 511 http://deb.debian.org/debian trixie/main amd64 libhdf5-fortran-102t64 amd64 1.10.10+repack-3.3 [89.3 kB] Get: 512 http://deb.debian.org/debian trixie/main amd64 libhdf5-hl-100t64 amd64 1.10.10+repack-3.3 [63.3 kB] Get: 513 http://deb.debian.org/debian trixie/main amd64 libhdf5-hl-fortran-100t64 amd64 1.10.10+repack-3.3 [40.4 kB] Get: 514 http://deb.debian.org/debian trixie/main amd64 libhdf5-cpp-103-1t64 amd64 1.10.10+repack-3.3 [131 kB] Get: 515 http://deb.debian.org/debian trixie/main amd64 libhdf5-hl-cpp-100t64 amd64 1.10.10+repack-3.3 [21.3 kB] Get: 516 http://deb.debian.org/debian trixie/main amd64 zlib1g-dev amd64 1:1.3.dfsg-3.1 [918 kB] Get: 517 http://deb.debian.org/debian trixie/main amd64 libjpeg62-turbo-dev amd64 1:2.1.5-3 [290 kB] Get: 518 http://deb.debian.org/debian trixie/main amd64 libjpeg-dev amd64 1:2.1.5-3 [71.9 kB] Get: 519 http://deb.debian.org/debian trixie/main amd64 libaec-dev amd64 1.1.3-1 [21.0 kB] Get: 520 http://deb.debian.org/debian trixie/main amd64 libcurl4-openssl-dev amd64 8.7.1-3 [547 kB] Get: 521 http://deb.debian.org/debian trixie/main amd64 libssl-dev amd64 3.2.1-3 [2699 kB] Get: 522 http://deb.debian.org/debian trixie/main amd64 hdf5-helpers amd64 1.10.10+repack-3.3 [23.4 kB] Get: 523 http://deb.debian.org/debian trixie/main amd64 libhdf5-dev amd64 1.10.10+repack-3.3 [2639 kB] Get: 524 http://deb.debian.org/debian trixie/main amd64 xorg-sgml-doctools all 1:1.11-1.1 [22.1 kB] Get: 525 http://deb.debian.org/debian trixie/main amd64 x11proto-dev all 2024.1-1 [603 kB] Get: 526 http://deb.debian.org/debian trixie/main amd64 libxau-dev amd64 1:1.0.9-1+b1 [21.3 kB] Get: 527 http://deb.debian.org/debian trixie/main amd64 libxdmcp-dev amd64 1:1.1.2-3+b1 [40.8 kB] Get: 528 http://deb.debian.org/debian trixie/main amd64 xtrans-dev all 1.4.0-1 [98.7 kB] Get: 529 http://deb.debian.org/debian trixie/main amd64 libpthread-stubs0-dev amd64 0.4-1+b1 [5348 B] Get: 530 http://deb.debian.org/debian trixie/main amd64 libxcb1-dev amd64 1.15-1 [181 kB] Get: 531 http://deb.debian.org/debian trixie/main amd64 libx11-dev amd64 2:1.8.7-1+b1 [875 kB] Get: 532 http://deb.debian.org/debian trixie/main amd64 libglx-dev amd64 1.7.0-1+b1 [15.8 kB] Get: 533 http://deb.debian.org/debian trixie/main amd64 libgl-dev amd64 1.7.0-1+b1 [101 kB] Get: 534 http://deb.debian.org/debian trixie/main amd64 libblas-dev amd64 3.12.0-3 [159 kB] Get: 535 http://deb.debian.org/debian trixie/main amd64 liblapack-dev amd64 3.12.0-3 [4880 kB] Get: 536 http://deb.debian.org/debian trixie/main amd64 libfftw3-quad3 amd64 3.3.10-1+b2 [608 kB] Get: 537 http://deb.debian.org/debian trixie/main amd64 libfftw3-bin amd64 3.3.10-1+b2 [52.3 kB] Get: 538 http://deb.debian.org/debian trixie/main amd64 libfftw3-dev amd64 3.3.10-1+b2 [2125 kB] Get: 539 http://deb.debian.org/debian trixie/main amd64 libgfortran-13-dev amd64 13.2.0-24 [847 kB] Get: 540 http://deb.debian.org/debian trixie/main amd64 gfortran-13-x86-64-linux-gnu amd64 13.2.0-24 [10.7 MB] Get: 541 http://deb.debian.org/debian trixie/main amd64 gfortran-13 amd64 13.2.0-24 [12.2 kB] Get: 542 http://deb.debian.org/debian trixie/main amd64 gfortran-x86-64-linux-gnu amd64 4:13.2.0-7 [1280 B] Get: 543 http://deb.debian.org/debian trixie/main amd64 gfortran amd64 4:13.2.0-7 [1440 B] Get: 544 http://deb.debian.org/debian trixie/main amd64 octave-dev amd64 8.4.0-1+b3 [957 kB] Get: 545 http://deb.debian.org/debian trixie/main amd64 dh-octave all 1.8.0 [22.7 kB] Get: 546 http://deb.debian.org/debian trixie/main amd64 octave-io amd64 2.6.4-3+b1 [201 kB] Fetched 241 MB in 6s (37.5 MB/s) debconf: delaying package configuration, since apt-utils is not installed Selecting previously unselected package libpython3.11-minimal:amd64. (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 ... 19699 files and directories currently installed.) Preparing to unpack .../libpython3.11-minimal_3.11.9-1_amd64.deb ... Unpacking libpython3.11-minimal:amd64 (3.11.9-1) ... Selecting previously unselected package libexpat1:amd64. Preparing to unpack .../libexpat1_2.6.2-1_amd64.deb ... Unpacking libexpat1:amd64 (2.6.2-1) ... Selecting previously unselected package python3.11-minimal. Preparing to unpack .../python3.11-minimal_3.11.9-1_amd64.deb ... Unpacking python3.11-minimal (3.11.9-1) ... Setting up libpython3.11-minimal:amd64 (3.11.9-1) ... Setting up libexpat1:amd64 (2.6.2-1) ... Setting up python3.11-minimal (3.11.9-1) ... 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 ... 20015 files and directories currently installed.) Preparing to unpack .../0-python3-minimal_3.11.8-1_amd64.deb ... Unpacking python3-minimal (3.11.8-1) ... 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-4_all.deb ... Unpacking tzdata (2024a-4) ... Selecting previously unselected package readline-common. Preparing to unpack .../4-readline-common_8.2-4_all.deb ... Unpacking readline-common (8.2-4) ... Selecting previously unselected package libreadline8t64:amd64. Preparing to unpack .../5-libreadline8t64_8.2-4_amd64.deb ... Adding 'diversion of /lib/x86_64-linux-gnu/libhistory.so.8 to /lib/x86_64-linux-gnu/libhistory.so.8.usr-is-merged by libreadline8t64' Adding 'diversion of /lib/x86_64-linux-gnu/libhistory.so.8.2 to /lib/x86_64-linux-gnu/libhistory.so.8.2.usr-is-merged by libreadline8t64' Adding 'diversion of /lib/x86_64-linux-gnu/libreadline.so.8 to /lib/x86_64-linux-gnu/libreadline.so.8.usr-is-merged by libreadline8t64' Adding 'diversion of /lib/x86_64-linux-gnu/libreadline.so.8.2 to /lib/x86_64-linux-gnu/libreadline.so.8.2.usr-is-merged by libreadline8t64' Unpacking libreadline8t64:amd64 (8.2-4) ... Selecting previously unselected package libpython3.11-stdlib:amd64. Preparing to unpack .../6-libpython3.11-stdlib_3.11.9-1_amd64.deb ... Unpacking libpython3.11-stdlib:amd64 (3.11.9-1) ... Selecting previously unselected package python3.11. Preparing to unpack .../7-python3.11_3.11.9-1_amd64.deb ... Unpacking python3.11 (3.11.9-1) ... Selecting previously unselected package libpython3-stdlib:amd64. Preparing to unpack .../8-libpython3-stdlib_3.11.8-1_amd64.deb ... Unpacking libpython3-stdlib:amd64 (3.11.8-1) ... Setting up python3-minimal (3.11.8-1) ... 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 ... 21007 files and directories currently installed.) Preparing to unpack .../000-python3_3.11.8-1_amd64.deb ... Unpacking python3 (3.11.8-1) ... 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_3.2.1-3_amd64.deb ... Unpacking openssl (3.2.1-3) ... 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%3a5.45-3_amd64.deb ... Unpacking libmagic-mgc (1:5.45-3) ... Selecting previously unselected package libmagic1t64:amd64. Preparing to unpack .../005-libmagic1t64_1%3a5.45-3_amd64.deb ... Unpacking libmagic1t64:amd64 (1:5.45-3) ... Selecting previously unselected package file. Preparing to unpack .../006-file_1%3a5.45-3_amd64.deb ... Unpacking file (1:5.45-3) ... Selecting previously unselected package gettext-base. Preparing to unpack .../007-gettext-base_0.21-14+b1_amd64.deb ... Unpacking gettext-base (0.21-14+b1) ... Selecting previously unselected package libuchardet0:amd64. Preparing to unpack .../008-libuchardet0_0.0.8-1+b1_amd64.deb ... Unpacking libuchardet0:amd64 (0.0.8-1+b1) ... Selecting previously unselected package groff-base. Preparing to unpack .../009-groff-base_1.23.0-4_amd64.deb ... Unpacking groff-base (1.23.0-4) ... Selecting previously unselected package bsdextrautils. Preparing to unpack .../010-bsdextrautils_2.40-8_amd64.deb ... Unpacking bsdextrautils (2.40-8) ... Selecting previously unselected package libpipeline1:amd64. Preparing to unpack .../011-libpipeline1_1.5.7-2_amd64.deb ... Unpacking libpipeline1:amd64 (1.5.7-2) ... Selecting previously unselected package man-db. Preparing to unpack .../012-man-db_2.12.1-1_amd64.deb ... Unpacking man-db (2.12.1-1) ... Selecting previously unselected package libbsd0:amd64. Preparing to unpack .../013-libbsd0_0.12.2-1_amd64.deb ... Unpacking libbsd0:amd64 (0.12.2-1) ... Selecting previously unselected package libedit2:amd64. Preparing to unpack .../014-libedit2_3.1-20230828-1+b1_amd64.deb ... Unpacking libedit2:amd64 (3.1-20230828-1+b1) ... Selecting previously unselected package libcbor0.10:amd64. Preparing to unpack .../015-libcbor0.10_0.10.2-1.1_amd64.deb ... Unpacking libcbor0.10:amd64 (0.10.2-1.1) ... Selecting previously unselected package libfido2-1:amd64. Preparing to unpack .../016-libfido2-1_1.14.0-1+b2_amd64.deb ... Unpacking libfido2-1:amd64 (1.14.0-1+b2) ... Selecting previously unselected package libkrb5support0:amd64. Preparing to unpack .../017-libkrb5support0_1.20.1-6+b1_amd64.deb ... Unpacking libkrb5support0:amd64 (1.20.1-6+b1) ... Selecting previously unselected package libcom-err2:amd64. Preparing to unpack .../018-libcom-err2_1.47.1~rc2-1_amd64.deb ... Unpacking libcom-err2:amd64 (1.47.1~rc2-1) ... Selecting previously unselected package libk5crypto3:amd64. Preparing to unpack .../019-libk5crypto3_1.20.1-6+b1_amd64.deb ... Unpacking libk5crypto3:amd64 (1.20.1-6+b1) ... Selecting previously unselected package libkeyutils1:amd64. Preparing to unpack .../020-libkeyutils1_1.6.3-3_amd64.deb ... Unpacking libkeyutils1:amd64 (1.6.3-3) ... Selecting previously unselected package libkrb5-3:amd64. Preparing to unpack .../021-libkrb5-3_1.20.1-6+b1_amd64.deb ... Unpacking libkrb5-3:amd64 (1.20.1-6+b1) ... Selecting previously unselected package libgssapi-krb5-2:amd64. Preparing to unpack .../022-libgssapi-krb5-2_1.20.1-6+b1_amd64.deb ... Unpacking libgssapi-krb5-2:amd64 (1.20.1-6+b1) ... Selecting previously unselected package openssh-client. Preparing to unpack .../023-openssh-client_1%3a9.7p1-4_amd64.deb ... Unpacking openssh-client (1:9.7p1-4) ... Selecting previously unselected package ucf. Preparing to unpack .../024-ucf_3.0043+nmu1_all.deb ... Moving old data out of the way Unpacking ucf (3.0043+nmu1) ... Selecting previously unselected package aglfn. 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Preparing to unpack .../203-libsub-name-perl_0.27-1+b2_amd64.deb ... Unpacking libsub-name-perl:amd64 (0.27-1+b2) ... Selecting previously unselected package libnamespace-clean-perl. Preparing to unpack .../204-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 .../205-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 .../206-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 .../207-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 .../208-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 .../209-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 .../210-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 .../211-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 .../212-libstring-escape-perl_2010.002-3_all.deb ... Unpacking libstring-escape-perl (2010.002-3) ... 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Unpacking libassuan0:amd64 (2.5.6-1+b1) ... Selecting previously unselected package gpgconf. Preparing to unpack .../219-gpgconf_2.2.40-3_amd64.deb ... Unpacking gpgconf (2.2.40-3) ... Selecting previously unselected package gpg. Preparing to unpack .../220-gpg_2.2.40-3_amd64.deb ... Unpacking gpg (2.2.40-3) ... Selecting previously unselected package iso-codes. Preparing to unpack .../221-iso-codes_4.16.0-1_all.deb ... Unpacking iso-codes (4.16.0-1) ... Selecting previously unselected package libberkeleydb-perl:amd64. Preparing to unpack .../222-libberkeleydb-perl_0.64-2+b3_amd64.deb ... Unpacking libberkeleydb-perl:amd64 (0.64-2+b3) ... Selecting previously unselected package libclass-xsaccessor-perl. Preparing to unpack .../223-libclass-xsaccessor-perl_1.19-4+b3_amd64.deb ... Unpacking libclass-xsaccessor-perl (1.19-4+b3) ... Selecting previously unselected package libconfig-tiny-perl. Preparing to unpack .../224-libconfig-tiny-perl_2.30-1_all.deb ... 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Selecting previously unselected package libio-string-perl. Preparing to unpack .../246-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 .../247-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 .../248-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 .../249-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 .../250-libipc-run3-perl_0.049-1_all.deb ... Unpacking libipc-run3-perl (0.049-1) ... Selecting previously unselected package libjson-maybexs-perl. 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Setting up libunicode-utf8-perl (0.62-2+b2) ... Setting up libfftw3-single3:amd64 (3.3.10-1+b2) ... Setting up libset-intspan-perl (1.19-3) ... Setting up libicu72:amd64 (72.1-4+b1) ... Setting up libogg0:amd64 (1.3.5-3+b1) ... Setting up libmouse-perl (2.5.10-1+b5) ... Setting up liblerc4:amd64 (4.0.0+ds-4+b1) ... Setting up libpod-pom-perl (2.01-4) ... Setting up bsdextrautils (2.40-8) ... Setting up hdf5-helpers (1.10.10+repack-3.3) ... Setting up libwmflite-0.2-7:amd64 (0.2.13-1.1+b2) ... Setting up libregexp-pattern-perl (0.2.14-2) ... Setting up libdata-messagepack-perl (1.02-1+b3) ... Setting up libdynaloader-functions-perl (0.003-3) ... Setting up libdatrie1:amd64 (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 (1:5.45-3) ... Setting up libcbor0.10:amd64 (0.10.2-1.1) ... Setting up libclone-perl:amd64 (0.46-1+b2) ... 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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 libpsl5t64:amd64 (0.21.2-1.1) ... Setting up libnghttp2-14:amd64 (1.61.0-1+b1) ... Setting up libdeflate0:amd64 (1.20-1) ... Setting up perl-openssl-defaults:amd64 (7+b2) ... Setting up libmldbm-perl (2.05-4) ... Setting up libxml-namespacesupport-perl (1.12-2) ... Setting up libfftw3-long3:amd64 (3.3.10-1+b2) ... 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:amd64 (2020.2-6+b1) ... Setting up xkb-data (2.41-2) ... Setting up liblzo2-2:amd64 (2.10-2+b1) ... Setting up libtime-moment-perl (0.44-2+b3) ... Setting up libencode-locale-perl (1.05-3) ... Setting up libtrilinos-kokkos-13.2:amd64 (13.2.0-5+b3) ... Setting up libmetis5:amd64 (5.1.0.dfsg-7+b1) ... Setting up libsvtav1enc1d1:amd64 (1.7.0+dfsg-2+b1) ... Setting up libcom-err2:amd64 (1.47.1~rc2-1) ... Setting up file (1:5.45-3) ... Setting up texinfo-lib (7.1-3+b1) ... Setting up libassuan0:amd64 (2.5.6-1+b1) ... Setting up libmpg123-0t64:amd64 (1.32.6-3) ... Setting up libconfig-tiny-perl (2.30-1) ... Setting up libsereal-encoder-perl (5.004+ds-1+b2) ... Setting up liblist-utilsby-perl (0.12-2) ... Setting up libyaml-tiny-perl (1.74-1) ... Setting up libpthread-stubs0-dev:amd64 (0.4-1+b1) ... Setting up libjbig0:amd64 (2.1-6.1+b1) ... Setting up octave-common (8.4.0-1) ... Setting up libregexp-common-perl (2017060201-3) ... Setting up librav1e0:amd64 (0.7.1-2) ... Setting up libpcre2-16-0:amd64 (10.42-4+b1) ... Setting up libaec0:amd64 (1.1.3-1) ... Setting up libnet-netmask-perl (2.0002-2) ... Setting up libopengl0:amd64 (1.7.0-1+b1) ... Setting up libsub-install-perl (0.929-1) ... Setting up libelf1t64:amd64 (0.191-1+b1) ... Setting up libindirect-perl (0.39-2+b3) ... Setting up libxs-parse-sublike-perl:amd64 (0.21-2+b2) ... Setting up libkrb5support0:amd64 (1.20.1-6+b1) ... Setting up libnumber-compare-perl (0.03-3) ... Setting up libsasl2-modules-db:amd64 (2.1.28+dfsg1-6) ... Setting up tzdata (2024a-4) ... Current default time zone: 'Etc/UTC' Local time is now: Fri Jun 13 01:09:52 UTC 2025. Universal Time is now: Fri Jun 13 01:09:52 UTC 2025. Run 'dpkg-reconfigure tzdata' if you wish to change it. Setting up liberror-perl (0.17029-2) ... Setting up libtrilinos-trilinosss-13.2:amd64 (13.2.0-5+b3) ... Setting up libasound2-data (1.2.11-1) ... Setting up libbtf2:amd64 (1:7.7.0+dfsg-2) ... 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+b3) ... Setting up xtrans-dev (1.4.0-1) ... Setting up autotools-dev (20220109.1) ... Setting up libz3-4:amd64 (4.8.12-3.1+b2) ... Setting up libglib2.0-0t64:amd64 (2.80.1-1) ... No schema files found: doing nothing. Setting up libblas3:amd64 (3.12.0-3) ... update-alternatives: using /usr/lib/x86_64-linux-gnu/blas/libblas.so.3 to provide /usr/lib/x86_64-linux-gnu/libblas.so.3 (libblas.so.3-x86_64-linux-gnu) in auto mode Setting up libclass-data-inheritable-perl (0.08-3) ... Setting up libxs-parse-keyword-perl (0.41-1) ... Setting up libalgorithm-c3-perl (0.11-2) ... Setting up libasound2t64:amd64 (1.2.11-1+b1) ... Setting up libmunge2:amd64 (0.5.15-4) ... Setting up liblog-log4perl-perl (1.57-1) ... Setting up libtext-reform-perl (1.20-5) ... Setting up libjpeg62-turbo:amd64 (1:2.1.5-3) ... Setting up libx11-data (2:1.8.7-1) ... Setting up libjpeg62-turbo-dev:amd64 (1:2.1.5-3) ... Setting up libfile-find-rule-perl (0.34-3) ... Setting up librtmp1:amd64 (2.4+20151223.gitfa8646d.1-2+b4) ... 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+b2) ... Setting up aglfn (1.7+git20191031.4036a9c-2) ... Setting up libavahi-common-data:amd64 (0.8-13+b2) ... Setting up libncurses6:amd64 (6.4+20240414-1) ... Setting up libdbus-1-3:amd64 (1.14.10-4+b1) ... Setting up libfftw3-quad3:amd64 (3.3.10-1+b2) ... Setting up libfribidi0:amd64 (1.0.13-3+b1) ... Setting up libopus0:amd64 (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:amd64 (3.2.1-3) ... Setting up libpng16-16t64:amd64 (1.6.43-5) ... Setting up libhwloc15:amd64 (2.10.0-1+b1) ... Setting up libvorbis0a:amd64 (1.3.7-2) ... Setting up libvariable-magic-perl (0.64-1) ... 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:amd64 (0.22-3+b1) ... Setting up fonts-dejavu-core (2.37-8) ... Setting up liblist-moreutils-xs-perl (0.430-4+b1) ... Setting up libsensors5:amd64 (1:3.6.0-9) ... Setting up libjxl0.7:amd64 (0.7.0-10.2+b3) ... Setting up libk5crypto3:amd64 (1.20.1-6+b1) ... Setting up libltdl7:amd64 (2.4.7-7+b1) ... Setting up libfftw3-double3:amd64 (3.3.10-1+b2) ... Setting up libglapi-mesa:amd64 (24.0.6-1+b1) ... Setting up libparams-util-perl (1.102-3) ... Setting up libsasl2-2:amd64 (2.1.28+dfsg1-6) ... Setting up libgfortran5:amd64 (14-20240330-1) ... Setting up libvulkan1:amd64 (1.3.280.0-1) ... Setting up libtime-duration-perl (1.21-2) ... Setting up autoconf (2.71-3) ... Setting up libtext-xslate-perl:amd64 (3.5.9-2) ... Setting up libsub-exporter-progressive-perl (0.001013-3) ... Setting up libwebp7:amd64 (1.3.2-0.4+b1) ... 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:amd64 (0.27-1+b2) ... Setting up zlib1g-dev:amd64 (1:1.3.dfsg-3.1) ... Setting up libsyntax-keyword-try-perl (0.29-2) ... Setting up libnuma1:amd64 (2.0.18-1) ... Setting up dwz (0.15-1+b1) ... Setting up libdata-validate-domain-perl (0.10-1.1) ... Setting up libproc-processtable-perl:amd64 (0.636-1+b2) ... Setting up libparse-recdescent-perl (1.967015+dfsg-4) ... Setting up libdav1d7:amd64 (1.4.1-1) ... Setting up libmtdev1t64:amd64 (1.1.6-1.2) ... Setting up sensible-utils (0.0.22) ... Setting up ocl-icd-libopencl1:amd64 (2.3.2-1+b1) ... Setting up libxshmfence1:amd64 (1.3-1+b1) ... Setting up libtiff6:amd64 (4.5.1+git230720-4) ... Setting up libpath-tiny-perl (0.144-1) ... Setting up libuchardet0:amd64 (0.0.8-1+b1) ... Setting up lzop (1.04-2) ... Setting up libjson-perl (4.10000-1) ... Setting up liblog-any-adapter-screen-perl (0.140-2) ... Setting up libnl-3-200:amd64 (3.7.0-0.3) ... Setting up librole-tiny-perl (2.002004-1) ... Setting up libpsm2-2 (11.2.185-2) ... Setting up openmpi-common (4.1.6-13.2) ... Setting up libipc-run3-perl (0.049-1) ... Setting up libmd4c0:amd64 (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:amd64 (1:7.7.0+dfsg-2) ... Setting up liblua5.4-0:amd64 (5.4.6-3+b1) ... 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 xorg-sgml-doctools (1:1.11-1.1) ... Setting up netbase (6.4) ... Setting up libabsl20230802:amd64 (20230802.1-4) ... 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+b3) ... Setting up libtext-autoformat-perl (1.750000-2) ... Setting up libkrb5-3:amd64 (1.20.1-6+b1) ... Setting up libevent-core-2.1-7t64:amd64 (2.1.12-stable-8.1+b3) ... Setting up libglu1-mesa:amd64 (9.0.2-1.1+b1) ... Setting up libflac12t64:amd64 (1.4.3+ds-2.1) ... 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/x86_64-linux-gnu/libpsm_infinipath.so.1 (libpsm_infinipath.so.1) in auto mode Setting up libsort-versions-perl (1.62-3) ... Setting up libssh2-1t64:amd64 (1.11.0-4.1+b2) ... Setting up libexporter-tiny-perl (1.006002-1) ... Setting up libterm-readkey-perl (2.38-2+b3) ... Setting up libfido2-1:amd64 (1.14.0-1+b2) ... Setting up libtext-unidecode-perl (1.30-3) ... Setting up libde265-0:amd64 (1.0.15-1+b1) ... Setting up libfont-ttf-perl (1.06-2) ... Setting up libfile-homedir-perl (1.006-2) ... Setting up libgfortran-13-dev:amd64 (13.2.0-24) ... Setting up libsamplerate0:amd64 (0.2.2-4+b1) ... Setting up openssl (3.2.1-3) ... Setting up libwebpmux3:amd64 (1.3.2-0.4+b1) ... Setting up libbsd0:amd64 (0.12.2-1) ... Setting up libtext-levenshteinxs-perl (0.03-5+b3) ... Setting up libperlio-gzip-perl (0.20-1+b3) ... Setting up libdrm-common (2.4.120-2) ... Setting up libyuv0:amd64 (0.0~git202401110.af6ac82-1) ... Setting up libevdev2:amd64 (1.13.1+dfsg-1+b1) ... Setting up readline-common (8.2-4) ... Setting up libxml2:amd64 (2.9.14+dfsg-1.3+b3) ... 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+b2) ... Setting up libmarkdown2:amd64 (2.2.7-2+b1) ... Setting up liburi-perl (5.28-1) ... Setting up iso-codes (4.16.0-1) ... Setting up libnet-ipv6addr-perl (1.02-1) ... Setting up libgudev-1.0-0:amd64 (238-5) ... Setting up libmp3lame0:amd64 (3.100-6+b2) ... Setting up libblas-dev:amd64 (3.12.0-3) ... update-alternatives: using /usr/lib/x86_64-linux-gnu/blas/libblas.so to provide /usr/lib/x86_64-linux-gnu/libblas.so (libblas.so-x86_64-linux-gnu) in auto mode Setting up libsz2:amd64 (1.1.3-1) ... Setting up libvorbisenc2:amd64 (1.3.7-2) ... Setting up libdata-validate-ip-perl (0.31-1) ... Setting up libwacom-common (2.10.0-2) ... Setting up libmousex-nativetraits-perl (1.09-3) ... Setting up libemail-address-xs-perl (1.05-1+b3) ... Setting up libxkbcommon0:amd64 (1.6.0-1+b1) ... Setting up libwayland-client0:amd64 (1.22.0-2.1+b1) ... Setting up libnet-ssleay-perl:amd64 (1.94-1+b1) ... 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 (2024.1-1) ... Setting up libfile-stripnondeterminism-perl (1.13.1-1) ... Setting up gnuplot-data (6.0.0+dfsg1-3) ... Setting up libice6:amd64 (2:1.0.10-1+b1) ... Setting up libhttp-date-perl (6.06-1) ... Setting up libxdmcp6:amd64 (1:1.1.2-3+b1) ... Setting up liblapack3:amd64 (3.12.0-3) ... update-alternatives: using /usr/lib/x86_64-linux-gnu/lapack/liblapack.so.3 to provide /usr/lib/x86_64-linux-gnu/liblapack.so.3 (liblapack.so.3-x86_64-linux-gnu) in auto mode Setting up libncurses-dev:amd64 (6.4+20240414-1) ... Setting up libxcb1:amd64 (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 libarpack2t64:amd64 (3.9.1-1.1+b1) ... Setting up libxcb-xfixes0:amd64 (1.15-1) ... Setting up libamd3:amd64 (1:7.7.0+dfsg-2) ... Setting up libfile-listing-perl (6.16-1) ... Setting up libxau-dev:amd64 (1:1.0.9-1+b1) ... Setting up libxcb-xinput0:amd64 (1.15-1) ... Setting up libtool (2.4.7-7) ... Setting up libcolamd3:amd64 (1:7.7.0+dfsg-2) ... Setting up libxcb-render0:amd64 (1.15-1) ... Setting up libfftw3-bin (3.3.10-1+b2) ... Setting up libwacom9:amd64 (2.10.0-2) ... Setting up libevent-pthreads-2.1-7t64:amd64 (2.1.12-stable-8.1+b3) ... Setting up fontconfig-config (2.15.0-1.1) ... Setting up liblist-moreutils-perl (0.430-2) ... Setting up libxcb-glx0:amd64 (1.15-1) ... Setting up libpod-constants-perl (0.19-2) ... Setting up libedit2:amd64 (3.1-20230828-1+b1) ... Setting up libhash-merge-perl (0.302-1) ... Setting up libxcb-keysyms1:amd64 (0.4.0-1+b2) ... Setting up libsoftware-copyright-perl (0.012-2) ... Setting up libaec-dev:amd64 (1.1.3-1) ... Setting up libxcb-shape0:amd64 (1.15-1) ... Setting up libavahi-common3:amd64 (0.8-13+b2) ... Setting up libcxsparse4:amd64 (1:7.7.0+dfsg-2) ... Setting up libjpeg-dev:amd64 (1:2.1.5-3) ... 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+b2) ... Setting up libxcb-render-util0:amd64 (0.3.9-1+b1) ... Setting up libxcb-shm0:amd64 (1.15-1) ... Setting up libexception-class-perl (1.45-1) ... Setting up libxcb-icccm4:amd64 (0.4.1-1.1+b1) ... Setting up libsundials-sunmatrix4:amd64 (6.4.1+dfsg1-3+b5) ... Setting up libclass-c3-perl (0.35-2) ... Setting up libsuperlu6:amd64 (6.0.1+dfsg1-1+b1) ... Setting up libqrupdate1:amd64 (1.1.2-4+b1) ... Setting up libdevel-callchecker-perl:amd64 (0.009-1) ... Setting up gfortran-13-x86-64-linux-gnu (13.2.0-24) ... Setting up libldap-2.5-0:amd64 (2.5.17+dfsg-1) ... Setting up libsundials-ida6:amd64 (6.4.1+dfsg1-3+b5) ... Setting up libcamd3:amd64 (1:7.7.0+dfsg-2) ... Setting up libxcb-util1:amd64 (0.4.0-1+b1) ... Setting up libinput-bin (1.25.0-1+b2) ... Setting up libxcb-xkb1:amd64 (1.15-1) ... Setting up libxcb-image0:amd64 (0.4.0-2+b1) ... Setting up intltool-debian (0.35.0+20060710.6) ... Setting up libnl-route-3-200:amd64 (3.7.0-0.3) ... Setting up libobject-pad-perl (0.808-1+b2) ... Setting up libxcb-present0:amd64 (1.15-1) ... Setting up dh-autoreconf (20) ... Setting up patchutils (0.4.2-1) ... Setting up libthai0:amd64 (0.1.29-2) ... Setting up ca-certificates (20240203) ... Updating certificates in /etc/ssl/certs... 146 added, 0 removed; done. Setting up libxdmcp-dev:amd64 (1:1.1.2-3+b1) ... Setting up libdata-validate-uri-perl (0.07-3) ... Setting up libxcb-xinerama0:amd64 (1.15-1) ... Setting up libllvm17t64:amd64 (1:17.0.6-12) ... Setting up libtest-exception-perl (0.43-3) ... Setting up libfreetype6:amd64 (2.13.2+dfsg-1+b4) ... Setting up libglpk40:amd64 (5.0-1+b1) ... Setting up libstring-copyright-perl (0.003014-1) ... Setting up libxcb-sync1:amd64 (1.15-1) ... Setting up gfortran-13 (13.2.0-24) ... Setting up shared-mime-info (2.4-4) ... Setting up libxkbcommon-x11-0:amd64 (1.6.0-1+b1) ... Setting up liblapack-dev:amd64 (3.12.0-3) ... update-alternatives: using /usr/lib/x86_64-linux-gnu/lapack/liblapack.so to provide /usr/lib/x86_64-linux-gnu/liblapack.so (liblapack.so-x86_64-linux-gnu) in auto mode Setting up libgssapi-krb5-2:amd64 (1.20.1-6+b1) ... Setting up libdata-optlist-perl (0.114-1) ... Setting up libgav1-1:amd64 (0.19.0-2+b1) ... Setting up ucf (3.0043+nmu1) ... Setting up libccolamd3:amd64 (1:7.7.0+dfsg-2) ... Setting up libreadline8t64:amd64 (8.2-4) ... Setting up libxcb-dri2-0:amd64 (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:amd64 (1.9.21~dfsg-3+b3) ... Setting up libdrm2:amd64 (2.4.120-2) ... Setting up groff-base (1.23.0-4) ... Setting up libxcb-randr0:amd64 (1.15-1) ... Setting up libhtml-parser-perl:amd64 (3.82-1) ... Setting up gpgconf (2.2.40-3) ... Setting up libx11-6:amd64 (2:1.8.7-1+b1) ... Setting up libharfbuzz0b:amd64 (8.3.0-2+b1) ... Setting up libamd-comgr2:amd64 (6.0+git20231212.4510c28+dfsg-3+b1) ... Setting up libfontconfig1:amd64 (2.15.0-1.1) ... Setting up libsndfile1:amd64 (1.2.2-1+b2) ... Setting up libmro-compat-perl (0.15-2) ... Setting up libsm6:amd64 (2:1.2.3-1+b1) ... Setting up libfftw3-dev:amd64 (3.3.10-1+b2) ... Setting up libavahi-client3:amd64 (0.8-13+b2) ... Setting up libio-socket-ssl-perl (2.085-1) ... Setting up gpg (2.2.40-3) ... Setting up libsub-exporter-perl (0.990-1) ... Setting up libhttp-message-perl (6.45-1) ... Setting up libdrm-amdgpu1:amd64 (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:amd64 (1.15-1) ... Setting up libinput10:amd64 (1.25.0-1+b2) ... Setting up libportaudio2:amd64 (19.6.0-1.2+b2) ... Setting up libx11-xcb1:amd64 (2:1.8.7-1+b1) ... Setting up libhttp-negotiate-perl (6.01-2) ... Setting up libibverbs1:amd64 (50.0-2+b1) ... Setting up fontconfig (2.15.0-1.1) ... Regenerating fonts cache... done. Setting up libavif16:amd64 (1.0.4-2) ... Setting up libcarp-assert-more-perl (2.4.0-1) ... Setting up libcholmod5:amd64 (1:7.7.0+dfsg-2) ... Setting up libdrm-nouveau2:amd64 (2.4.120-2) ... Setting up libxcb1-dev:amd64 (1.15-1) ... Setting up libxpm4:amd64 (1:3.5.17-1+b1) ... Setting up libiterator-util-perl (0.02+ds1-2) ... Setting up libxrender1:amd64 (1:0.9.10-1.1+b1) ... Setting up libcurl4t64:amd64 (8.7.1-3) ... Setting up libgbm1:amd64 (24.0.6-1+b1) ... Setting up ibverbs-providers:amd64 (50.0-2+b1) ... Setting up libhttp-cookies-perl (6.11-1) ... Setting up libspqr4:amd64 (1:7.7.0+dfsg-2) ... Setting up libdrm-radeon1:amd64 (2.4.120-2) ... Setting up openssh-client (1:9.7p1-4) ... Setting up po-debconf (1.0.21+nmu1) ... Setting up libhtml-tree-perl (5.07-3) ... Setting up libpython3.11-stdlib:amd64 (3.11.9-1) ... Setting up libparams-classify-perl:amd64 (0.015-2+b3) ... Setting up libpango-1.0-0:amd64 (1.52.2+ds-1) ... Setting up libdrm-intel1:amd64 (2.4.120-2) ... Setting up libcgi-pm-perl (4.64-1) ... Setting up libgl1-mesa-dri:amd64 (24.0.6-1+b1) ... Setting up libx11-dev:amd64 (2:1.8.7-1+b1) ... Setting up libcurl3t64-gnutls:amd64 (8.7.1-3) ... Setting up libxext6:amd64 (2:1.3.4-1+b1) ... Setting up libreadline-dev:amd64 (8.2-4) ... Setting up man-db (2.12.1-1) ... Not building database; man-db/auto-update is not 'true'. Setting up gfortran-x86-64-linux-gnu (4:13.2.0-7) ... 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:amd64 (1.18.0-3+b1) ... Setting up libxxf86vm1:amd64 (1:1.1.4-1+b2) ... Setting up libxnvctrl0:amd64 (535.171.04-1) ... Setting up libfeature-compat-class-perl (0.06-1) ... Setting up tex-common (6.18) ... update-language: texlive-base not installed and configured, doing nothing! Setting up libqt5core5t64:amd64 (5.15.10+dfsg-7.2+b1) ... Setting up libegl-mesa0:amd64 (24.0.6-1+b1) ... 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:amd64 (1:6.0.0-2+b1) ... Setting up libcurl4-openssl-dev:amd64 (8.7.1-3) ... Setting up libklu2:amd64 (1:7.7.0+dfsg-2) ... Setting up libconfig-model-perl (2.153-3) ... Setting up libxinerama1:amd64 (2:1.1.4-3+b1) ... Setting up libxml-libxml-perl (2.0207+dfsg+really+2.0134-1+b3) ... 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 libumfpack6:amd64 (1:7.7.0+dfsg-2) ... Setting up libconst-fast-perl (0.014-2) ... Setting up libdata-section-perl (0.200008-1) ... Setting up libegl1:amd64 (1.7.0-1+b1) ... Setting up libqt5sql5t64:amd64 (5.15.10+dfsg-7.2+b1) ... Setting up librdmacm1t64:amd64 (50.0-2+b1) ... Setting up libpangoft2-1.0-0:amd64 (1.52.2+ds-1) ... Setting up libhdf5-103-1t64:amd64 (1.10.10+repack-3.3) ... Setting up libdata-dpath-perl (0.59-1) ... Setting up libcups2t64:amd64 (2.4.7-1.2+b1) ... Setting up libhsakmt1:amd64 (5.7.0-1) ... Setting up libstring-rewriteprefix-perl (0.009-1) ... Setting up libpangocairo-1.0-0:amd64 (1.52.2+ds-1) ... Setting up libpython3-stdlib:amd64 (3.11.8-1) ... Setting up libfabric1:amd64 (1.17.0-3+b1) ... Setting up libconfig-model-backend-yaml-perl (2.134-2) ... Setting up libhdf5-hl-100t64:amd64 (1.10.10+repack-3.3) ... Setting up python3.11 (3.11.9-1) ... Setting up libxft2:amd64 (2.3.6-1+b1) ... Setting up libqt5dbus5t64:amd64 (5.15.10+dfsg-7.2+b1) ... Setting up libglx-mesa0:amd64 (24.0.6-1+b1) ... Setting up libglx0:amd64 (1.7.0-1+b1) ... 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:amd64 (1:1.2.1-1+b1) ... Setting up libhdf5-cpp-103-1t64:amd64 (1.10.10+repack-3.3) ... Setting up libqt5network5t64:amd64 (5.15.10+dfsg-7.2+b1) ... Setting up liblist-someutils-perl (0.59-1) ... Setting up libhdf5-fortran-102t64:amd64 (1.10.10+repack-3.3) ... Setting up libqt5xml5t64:amd64 (5.15.10+dfsg-7.2+b1) ... Setting up debhelper (13.15.3) ... Setting up python3 (3.11.8-1) ... Setting up libhwloc-plugins:amd64 (2.10.0-1+b1) ... Setting up libmime-tools-perl (5.515-1) ... Setting up libsoftware-license-perl (0.104006-1) ... Setting up libclass-load-perl (0.25-2) ... Setting up libgl1:amd64 (1.7.0-1+b1) ... Setting up libpmix2t64:amd64 (5.0.2-3) ... Setting up texinfo (7.1-3) ... Setting up libhsa-runtime64-1 (5.7.1-2) ... Setting up libglx-dev:amd64 (1.7.0-1+b1) ... Setting up libmoox-aliases-perl (0.001006-2) ... Setting up libhdf5-hl-cpp-100t64:amd64 (1.10.10+repack-3.3) ... Setting up libparams-validate-perl:amd64 (1.31-2+b2) ... Setting up libb-hooks-endofscope-perl (0.28-1) ... Setting up libfltk1.3t64:amd64 (1.3.8-6.1) ... Setting up libgl-dev:amd64 (1.7.0-1+b1) ... Setting up libsoftware-licensemoreutils-perl (1.009-1) ... Setting up libhdf5-hl-fortran-100t64:amd64 (1.10.10+repack-3.3) ... Setting up libgl2ps1.4 (1.4.2+dfsg1-2) ... Setting up libfltk-gl1.3t64:amd64 (1.3.8-6.1) ... Setting up libqt5gui5t64:amd64 (5.15.10+dfsg-7.2+b1) ... Setting up libamdhip64-5 (5.7.1-3) ... Setting up libhdf5-dev (1.10.10+repack-3.3) ... update-alternatives: using /usr/lib/x86_64-linux-gnu/pkgconfig/hdf5-serial.pc to provide /usr/lib/x86_64-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 licensecheck (3.3.9-1) ... Setting up libucx0:amd64 (1.16.0+ds-5) ... Setting up libqt5widgets5t64:amd64 (5.15.10+dfsg-7.2+b1) ... Setting up libapp-cmd-perl (0.336-1) ... Setting up libqt5help5:amd64 (5.15.10-7) ... Setting up libopenmpi3t64:amd64 (4.1.6-13.2) ... Setting up cme (1.040-1) ... Setting up openmpi-bin (4.1.6-13.2) ... 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 libqt5printsupport5t64:amd64 (5.15.10+dfsg-7.2+b1) ... Setting up libptscotch-7.0:amd64 (7.0.4-2) ... Setting up mpi-default-bin (1.15) ... Setting up libcombblas2.0.0t64:amd64 (2.0.0-3.1+b1) ... Setting up libfftw3-mpi3:amd64 (3.3.10-1+b2) ... Setting up libqscintilla2-qt5-15:amd64 (2.14.1+dfsg-1+b2) ... Setting up libtrilinos-zoltan-13.2:amd64 (13.2.0-5+b3) ... Setting up libhdf5-openmpi-103-1t64:amd64 (1.10.10+repack-3.3) ... Setting up libtrilinos-teuchos-13.2:amd64 (13.2.0-5+b3) ... Setting up libtrilinos-epetra-13.2:amd64 (13.2.0-5+b3) ... Setting up libtrilinos-aztecoo-13.2:amd64 (13.2.0-5+b3) ... Setting up libtrilinos-triutils-13.2:amd64 (13.2.0-5+b3) ... Setting up libscalapack-openmpi2.2:amd64 (2.2.1-3.1) ... Setting up libsuperlu-dist8:amd64 (8.2.1+dfsg1-1+b2) ... Setting up libmumps-5.6t64:amd64 (5.6.2-2.1+b1) ... Setting up libhypre-2.28.0:amd64 (2.28.0-8+b2) ... Setting up libtrilinos-epetraext-13.2:amd64 (13.2.0-5+b3) ... Setting up libtrilinos-galeri-13.2:amd64 (13.2.0-5+b3) ... Setting up libtrilinos-amesos-13.2:amd64 (13.2.0-5+b3) ... Setting up libtrilinos-ifpack-13.2:amd64 (13.2.0-5+b3) ... Setting up libtrilinos-ml-13.2:amd64 (13.2.0-5+b3) ... Setting up libpetsc-real3.19t64:amd64 (3.19.6+dfsg1-2.2) ... update-alternatives: using /usr/lib/x86_64-linux-gnu/libpetsc_real.so.3.19.6 to provide /usr/lib/x86_64-linux-gnu/libpetsc.so.3.19 (libpetsc.so.3.19) in auto mode Setting up libsundials-nvecparallel-petsc6:amd64 (6.4.1+dfsg1-3+b5) ... Setting up libsundials-sunlinsol3:amd64 (6.4.1+dfsg1-3+b5) ... Setting up libheif-plugin-dav1d:amd64 (1.17.6-1+b2) ... Setting up liblwp-protocol-https-perl (6.14-1) ... Setting up libheif-plugin-libde265:amd64 (1.17.6-1+b2) ... Setting up libwww-perl (6.77-1) ... Setting up libheif1:amd64 (1.17.6-1+b2) ... 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:amd64 (2.3.3-9+b3) ... Setting up gnuplot-nox (6.0.0+dfsg1-3) ... update-alternatives: using /usr/bin/gnuplot-nox to provide /usr/bin/gnuplot (gnuplot) in auto mode Setting up libgraphicsmagick-q16-3t64 (1.4+really1.3.43-1) ... Setting up lintian (2.117.0) ... Setting up libgraphicsmagick++-q16-12t64 (1.4+really1.3.43-1) ... Setting up libconfig-model-dpkg-perl (3.004) ... Setting up dh-octave-autopkgtest (1.8.0) ... Setting up octave (8.4.0-1+b3) ... Setting up octave-dev (8.4.0-1+b3) ... Setting up octave-io (2.6.4-3+b1) ... Setting up dh-octave (1.8.0) ... Processing triggers for libc-bin (2.38-7) ... 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: Running cd /build/reproducible-path/octave-statistics-1.6.5/ && env PATH="/usr/sbin:/usr/bin:/sbin:/bin:/usr/games" HOME="/nonexistent/first-build" dpkg-buildpackage -us -uc -b && env PATH="/usr/sbin:/usr/bin:/sbin:/bin:/usr/games" HOME="/nonexistent/first-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 amd64 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/x86_64-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 -g -O2 -ffile-prefix-map=/build/reproducible-path/octave-statistics-1.6.5=. -fstack-protector-strong -fstack-clash-protection -Wformat -Werror=format-security -fcf-protection libsvmread.cc -o /tmp/oct-AusomP.o g++ -I/usr/include/octave-8.4.0/octave/.. -I/usr/include/octave-8.4.0/octave -pthread -fopenmp -g -O2 -ffile-prefix-map=/build/reproducible-path/octave-statistics-1.6.5=. -fstack-protector-strong -fstack-clash-protection -Wformat -Werror=format-security -fcf-protection -o libsvmread.oct /tmp/oct-AusomP.o -shared -Wl,-Bsymbolic -Wl,-z,relro -L/usr/lib/x86_64-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 -g -O2 -ffile-prefix-map=/build/reproducible-path/octave-statistics-1.6.5=. -fstack-protector-strong -fstack-clash-protection -Wformat -Werror=format-security -fcf-protection libsvmwrite.cc -o /tmp/oct-FOAbmY.o g++ -I/usr/include/octave-8.4.0/octave/.. -I/usr/include/octave-8.4.0/octave -pthread -fopenmp -g -O2 -ffile-prefix-map=/build/reproducible-path/octave-statistics-1.6.5=. -fstack-protector-strong -fstack-clash-protection -Wformat -Werror=format-security -fcf-protection -o libsvmwrite.oct /tmp/oct-FOAbmY.o -shared -Wl,-Bsymbolic -Wl,-z,relro -L/usr/lib/x86_64-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 -g -O2 -ffile-prefix-map=/build/reproducible-path/octave-statistics-1.6.5=. -fstack-protector-strong -fstack-clash-protection -Wformat -Werror=format-security -fcf-protection svmpredict.cc -o /tmp/oct-CgkNXw.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 -g -O2 -ffile-prefix-map=/build/reproducible-path/octave-statistics-1.6.5=. -fstack-protector-strong -fstack-clash-protection -Wformat -Werror=format-security -fcf-protection svm.cpp -o /tmp/oct-DEjZJx.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 -g -O2 -ffile-prefix-map=/build/reproducible-path/octave-statistics-1.6.5=. -fstack-protector-strong -fstack-clash-protection -Wformat -Werror=format-security -fcf-protection svm_model_octave.cc -o /tmp/oct-G77KeT.o g++ -I/usr/include/octave-8.4.0/octave/.. -I/usr/include/octave-8.4.0/octave -pthread -fopenmp -g -O2 -ffile-prefix-map=/build/reproducible-path/octave-statistics-1.6.5=. -fstack-protector-strong -fstack-clash-protection -Wformat -Werror=format-security -fcf-protection -o svmpredict.oct /tmp/oct-CgkNXw.o /tmp/oct-DEjZJx.o /tmp/oct-G77KeT.o -shared -Wl,-Bsymbolic -Wl,-z,relro -L/usr/lib/x86_64-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 -g -O2 -ffile-prefix-map=/build/reproducible-path/octave-statistics-1.6.5=. -fstack-protector-strong -fstack-clash-protection -Wformat -Werror=format-security -fcf-protection svmtrain.cc -o /tmp/oct-Rz6Lcu.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 -g -O2 -ffile-prefix-map=/build/reproducible-path/octave-statistics-1.6.5=. -fstack-protector-strong -fstack-clash-protection -Wformat -Werror=format-security -fcf-protection svm.cpp -o /tmp/oct-Vkj60r.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 -g -O2 -ffile-prefix-map=/build/reproducible-path/octave-statistics-1.6.5=. -fstack-protector-strong -fstack-clash-protection -Wformat -Werror=format-security -fcf-protection svm_model_octave.cc -o /tmp/oct-FcszPx.o g++ -I/usr/include/octave-8.4.0/octave/.. -I/usr/include/octave-8.4.0/octave -pthread -fopenmp -g -O2 -ffile-prefix-map=/build/reproducible-path/octave-statistics-1.6.5=. -fstack-protector-strong -fstack-clash-protection -Wformat -Werror=format-security -fcf-protection -o svmtrain.oct /tmp/oct-Rz6Lcu.o /tmp/oct-Vkj60r.o /tmp/oct-FcszPx.o -shared -Wl,-Bsymbolic -Wl,-z,relro -L/usr/lib/x86_64-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/x86_64-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/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/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/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/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 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/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 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/mad.m shadows a core library function warning: called from /tmp/tmp.ukec1gI1Qj 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.ukec1gI1Qj 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.ukec1gI1Qj 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.ukec1gI1Qj 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/mean.m shadows a core library function warning: called from /tmp/tmp.ukec1gI1Qj at line 12 column 1 [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/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/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/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/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/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 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. ***** 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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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_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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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 ***** 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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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)) !!!!! known bug: https://octave.org/testfailure/?63848 ASSERT errors for: assert (mean ([flintmax("double"), ones(1, 2 ^ 8 - 1, "double")]),35184372088833 - 1 / (2 ^ 8),eps (35184372088833)) Location | Observed | Expected | Reason () 35184372088832 35184372088833 Abs err 1 exceeds tol 0.0078125 by 1 ***** 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, 79 passed, 0 known failure, 1 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/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/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/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/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/@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/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/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/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/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/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/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/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/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/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/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/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/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/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/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 [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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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.ukec1gI1Qj at line 3198 column 31 1 test, 1 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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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 Checking C++ files ... [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/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/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/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, 10342 passed, 1 known failures, 2 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-dbgsym' in '../octave-statistics-dbgsym_1.6.5-3_amd64.deb'. dpkg-deb: building package 'octave-statistics' in '../octave-statistics_1.6.5-3_amd64.deb'. dpkg-deb: building package 'octave-statistics-common' in '../octave-statistics-common_1.6.5-3_all.deb'. dpkg-genbuildinfo --build=binary -O../octave-statistics_1.6.5-3_amd64.buildinfo dpkg-genchanges --build=binary -O../octave-statistics_1.6.5-3_amd64.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: 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/1635889 and its subdirectories I: Current time: Thu Jun 12 13:17:10 -12 2025 I: pbuilder-time-stamp: 1749777430 Fri May 10 18:54:12 UTC 2024 I: 1st build successful. Starting 2nd build on remote node infom01-amd64.debian.net. Fri May 10 18:54:12 UTC 2024 I: Preparing to do remote build '2' on infom01-amd64.debian.net. Fri May 10 19:03:40 UTC 2024 I: Deleting $TMPDIR on infom01-amd64.debian.net. Fri May 10 19:03:40 UTC 2024 I: octave-statistics_1.6.5-3_amd64.changes: Format: 1.8 Date: Fri, 22 Mar 2024 07:33:29 -0300 Source: octave-statistics Binary: octave-statistics octave-statistics-common octave-statistics-dbgsym Architecture: all amd64 Version: 1.6.5-3 Distribution: unstable Urgency: medium Maintainer: Debian Octave Group Changed-By: Rafael Laboissière Description: octave-statistics - additional statistical functions for Octave octave-statistics-common - additional statistical functions for Octave (arch-indep files) Closes: 1067327 Changes: octave-statistics (1.6.5-3) unstable; urgency=medium . * d/p/glmfit-reproducible-bist.patch: Add Applied-Upstream field * d/p/fpdf-reproducile-bist.patch: New patch (Closes: #1067327) * d/p/binomial-dist-median.patch: Update with upstream commit Checksums-Sha1: 8b24769640dd389ccc69862ed11a9c315eba9323 7024004 octave-statistics-common_1.6.5-3_all.deb 3481e60f75201f0ccbb582bc1ae92cb284cbf6af 1353620 octave-statistics-dbgsym_1.6.5-3_amd64.deb 856a22b170d9f524308f5bfaa20c56264530e4ba 23196 octave-statistics_1.6.5-3_amd64.buildinfo 23801d901254a8ab7e38b4a63bc7554432ae98a6 79884 octave-statistics_1.6.5-3_amd64.deb Checksums-Sha256: b1a82de3c817da8122706b53386734f730fdd458bb5e2983919f53316a7d300b 7024004 octave-statistics-common_1.6.5-3_all.deb 8d2db095de8d665922495e01c74c81416f057b4e76ceeb6525432193f0ed6402 1353620 octave-statistics-dbgsym_1.6.5-3_amd64.deb 7ef846992125a4bd8ec31d5a6c8f0313093dd4abd33d82f72fe6f601776ab6d7 23196 octave-statistics_1.6.5-3_amd64.buildinfo d9c8bb10f3589858d7c925b8ea9d90488708f83fbcdaf2c05d9854c0b20e25f0 79884 octave-statistics_1.6.5-3_amd64.deb Files: 6a73a35751bc15cf23ca6d156080c82b 7024004 math optional octave-statistics-common_1.6.5-3_all.deb 25a83a55007bef97eec06b347399d1ca 1353620 debug optional octave-statistics-dbgsym_1.6.5-3_amd64.deb 5128748879557f79f1f4fdd34229f15c 23196 math optional octave-statistics_1.6.5-3_amd64.buildinfo e18a13977851e88610e78d2c4f60799b 79884 math optional octave-statistics_1.6.5-3_amd64.deb Fri May 10 19:03:43 UTC 2024 I: diffoscope 265 will be used to compare the two builds: Running as unit: rb-diffoscope-amd64_36-11473.service # Profiling output for: /usr/bin/diffoscope --timeout 7200 --html /srv/reproducible-results/rbuild-debian/r-b-build.rwluX86S/octave-statistics_1.6.5-3.diffoscope.html --text /srv/reproducible-results/rbuild-debian/r-b-build.rwluX86S/octave-statistics_1.6.5-3.diffoscope.txt --json /srv/reproducible-results/rbuild-debian/r-b-build.rwluX86S/octave-statistics_1.6.5-3.diffoscope.json --profile=- /srv/reproducible-results/rbuild-debian/r-b-build.rwluX86S/b1/octave-statistics_1.6.5-3_amd64.changes /srv/reproducible-results/rbuild-debian/r-b-build.rwluX86S/b2/octave-statistics_1.6.5-3_amd64.changes ## command (total time: 0.000s) 0.000s 1 call cmp (internal) ## has_same_content_as (total time: 0.000s) 0.000s 1 call abc.DotChangesFile ## main (total time: 0.455s) 0.455s 2 calls outputs 0.000s 1 call cleanup ## recognizes (total time: 0.105s) 0.105s 12 calls diffoscope.comparators.binary.FilesystemFile ## specialize (total time: 0.000s) 0.000s 1 call specialize Finished with result: success Main processes terminated with: code=exited/status=0 Service runtime: 861ms CPU time consumed: 799ms Fri May 10 19:03:45 UTC 2024 I: diffoscope 265 found no differences in the changes files, and a .buildinfo file also exists. Fri May 10 19:03:45 UTC 2024 I: octave-statistics from trixie built successfully and reproducibly on amd64. Fri May 10 19:03:46 UTC 2024 I: Submitting .buildinfo files to external archives: Fri May 10 19:03:46 UTC 2024 I: Submitting 24K b1/octave-statistics_1.6.5-3_amd64.buildinfo.asc Fri May 10 19:03:48 UTC 2024 I: Submitting 24K b2/octave-statistics_1.6.5-3_amd64.buildinfo.asc Fri May 10 19:03:49 UTC 2024 I: Done submitting .buildinfo files to http://buildinfo.debian.net/api/submit. Fri May 10 19:03:49 UTC 2024 I: Done submitting .buildinfo files. Fri May 10 19:03:49 UTC 2024 I: Removing signed octave-statistics_1.6.5-3_amd64.buildinfo.asc files: removed './b1/octave-statistics_1.6.5-3_amd64.buildinfo.asc' removed './b2/octave-statistics_1.6.5-3_amd64.buildinfo.asc'