Thu Apr 4 00:18:20 UTC 2024 I: starting to build octave-statistics/trixie/armhf on jenkins on '2024-04-04 00:18' Thu Apr 4 00:18:20 UTC 2024 I: The jenkins build log is/was available at https://jenkins.debian.net/userContent/reproducible/debian/build_service/armhf_32/12348/console.log Thu Apr 4 00:18:20 UTC 2024 I: Downloading source for trixie/octave-statistics=1.6.5-3 --2024-04-04 00:18:20-- http://deb.debian.org/debian/pool/main/o/octave-statistics/octave-statistics_1.6.5-3.dsc Connecting to 78.137.99.97:3128... 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% 374M=0s 2024-04-04 00:18:20 (374 MB/s) - ‘octave-statistics_1.6.5-3.dsc’ saved [2445/2445] Thu Apr 4 00:18:20 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----- Thu Apr 4 00:18:20 UTC 2024 I: Checking whether the package is not for us Thu Apr 4 00:18:20 UTC 2024 I: Starting 1st build on remote node virt64c-armhf-rb.debian.net. Thu Apr 4 00:18:20 UTC 2024 I: Preparing to do remote build '1' on virt64c-armhf-rb.debian.net. Thu Apr 4 00:47:50 UTC 2024 I: Deleting $TMPDIR on virt64c-armhf-rb.debian.net. I: pbuilder: network access will be disabled during build I: Current time: Wed Apr 3 12:18:26 -12 2024 I: pbuilder-time-stamp: 1712189906 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/24856/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='armhf' DEBIAN_FRONTEND='noninteractive' DEB_BUILD_OPTIONS='buildinfo=+all reproducible=+all parallel=3 ' DISTRIBUTION='trixie' HOME='/root' HOST_ARCH='armhf' IFS=' ' INVOCATION_ID='c85b4af756b24719b9da8710d871fbe0' 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='24856' 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.NgTE4E7g/pbuilderrc_cCQN --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.NgTE4E7g/b1 --logfile b1/build.log octave-statistics_1.6.5-3.dsc' SUDO_GID='113' SUDO_UID='107' SUDO_USER='jenkins' TERM='unknown' TZ='/usr/share/zoneinfo/Etc/GMT+12' USER='root' _='/usr/bin/systemd-run' http_proxy='http://10.0.0.15:3142/' I: uname -a Linux virt64c 6.1.0-18-arm64 #1 SMP Debian 6.1.76-1 (2024-02-01) aarch64 GNU/Linux I: ls -l /bin lrwxrwxrwx 1 root root 7 Apr 1 11:24 /bin -> usr/bin I: user script /srv/workspace/pbuilder/24856/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: armhf 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 ... 19637 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-arm-linux-gnueabihf{a} gfortran-arm-linux-gnueabihf{a} gnuplot-data{a} gnuplot-nox{a} gpg{a} gpgconf{a} groff-base{a} hdf5-helpers{a} intltool-debian{a} iso-codes{a} libabsl20220623{a} libaec-dev{a} libaec0{a} libalgorithm-c3-perl{a} libaliased-perl{a} libamd3{a} libaom3{a} libapp-cmd-perl{a} libapt-pkg-perl{a} libarchive-zip-perl{a} libarpack2{a} 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libtext-autoformat-perl{a} libtext-glob-perl{a} libtext-levenshtein-damerau-perl{a} libtext-levenshteinxs-perl{a} libtext-markdown-discount-perl{a} libtext-reform-perl{a} libtext-template-perl{a} libtext-unidecode-perl{a} libtext-xslate-perl{a} libthai-data{a} libthai0{a} libtiff6{a} libtime-duration-perl{a} libtime-moment-perl{a} libtimedate-perl{a} libtoml-tiny-perl{a} libtool{a} libtry-tiny-perl{a} libuchardet0{a} libumfpack6{a} libunicode-utf8-perl{a} liburi-perl{a} libvariable-magic-perl{a} libvorbis0a{a} libvorbisenc2{a} libvulkan1{a} libwacom-common{a} libwacom9{a} libwayland-client0{a} libwayland-server0{a} libwebp7{a} libwebpmux3{a} libwmflite-0.2-7{a} libwww-mechanize-perl{a} libwww-perl{a} libwww-robotrules-perl{a} libx11-6{a} libx11-data{a} libx11-dev{a} libx11-xcb1{a} libxau-dev{a} libxau6{a} libxcb-dri2-0{a} libxcb-dri3-0{a} libxcb-glx0{a} libxcb-icccm4{a} libxcb-image0{a} libxcb-keysyms1{a} libxcb-present0{a} libxcb-randr0{a} libxcb-render-util0{a} libxcb-render0{a} libxcb-shape0{a} libxcb-shm0{a} libxcb-sync1{a} libxcb-util1{a} libxcb-xfixes0{a} libxcb-xinerama0{a} libxcb-xinput0{a} libxcb-xkb1{a} libxcb1{a} libxcb1-dev{a} libxcursor1{a} libxdmcp-dev{a} libxdmcp6{a} libxext6{a} libxfixes3{a} libxft2{a} libxinerama1{a} libxkbcommon-x11-0{a} libxkbcommon0{a} libxml-libxml-perl{a} libxml-namespacesupport-perl{a} libxml-sax-base-perl{a} libxml-sax-perl{a} libxml2{a} libxnvctrl0{a} libxpm4{a} libxrender1{a} libxs-parse-keyword-perl{a} libxs-parse-sublike-perl{a} libxshmfence1{a} libxxf86vm1{a} libyaml-0-2{a} libyaml-libyaml-perl{a} libyaml-pp-perl{a} libyaml-tiny-perl{a} libyuv0{a} libz3-4{a} licensecheck{a} lintian{a} lzop{a} m4{a} man-db{a} media-types{a} mpi-default-bin{a} netbase{a} ocl-icd-libopencl1{a} octave{a} octave-common{a} octave-dev{a} octave-io{a} openmpi-bin{a} openmpi-common{a} openssh-client{a} openssl{a} patchutils{a} perl-openssl-defaults{a} plzip{a} po-debconf{a} python3{a} python3-minimal{a} python3.11{a} python3.11-minimal{a} readline-common{a} sensible-utils{a} shared-mime-info{a} t1utils{a} tex-common{a} texinfo{a} texinfo-lib{a} tzdata{a} ucf{a} unzip{a} x11-common{a} x11proto-dev{a} xkb-data{a} xorg-sgml-doctools{a} xtrans-dev{a} zlib1g-dev{a} The following packages are RECOMMENDED but will NOT be installed: alsa-topology-conf alsa-ucm-conf bash-completion curl dbus default-jre-headless epstool fonts-liberation fonts-urw-base35 ghostscript groff ibverbs-providers libapache-poi-java libarchive-cpio-perl libauthen-sasl-perl libblis4 libcgi-fast-perl libclass-c3-xs-perl libconfig-model-approx-perl libconfig-model-lcdproc-perl libconfig-model-openssh-perl libconfig-model-systemd-perl libconfig-model-tkui-perl libdata-dump-perl libfreezethaw-perl libfuse-perl libglib2.0-data libgpm2 libheif-plugin-aomenc libheif-plugin-x265 libhtml-format-perl libhttp-daemon-perl libio-compress-brotli-perl libipc-shareable-perl libjexcelapi-java libjopendocument-java libjson-xs-perl libldap-common liblist-someutils-xs-perl liblog-dispatch-perl libltdl-dev libmail-sendmail-perl libmath-base85-perl libopenblas0 libpackage-stash-xs-perl libqt5sql5-ibase libqt5sql5-mysql libqt5sql5-odbc libqt5sql5-psql libqt5sql5-sqlite libqt5sql5-tds libqt5svg5 libre-engine-re2-perl libreoffice-core libreoffice-java-common libsasl2-modules libsocket6-perl libtie-ixhash-perl libtypes-serialiser-perl libxerces2-java libxml-sax-expat-perl libxstring-perl lynx mesa-vulkan-drivers octave-doc pstoedit publicsuffix qt5-gtk-platformtheme qttranslations5-l10n qtwayland5 wget xauth xdg-user-dirs 0 packages upgraded, 516 newly installed, 0 to remove and 0 not upgraded. Need to get 181 MB of archives. After unpacking 617 MB will be used. Writing extended state information... Get: 1 http://deb.debian.org/debian trixie/main armhf libpython3.11-minimal armhf 3.11.8-1 [802 kB] Get: 2 http://deb.debian.org/debian trixie/main armhf libexpat1 armhf 2.5.0-2+b2 [80.2 kB] Get: 3 http://deb.debian.org/debian trixie/main armhf python3.11-minimal armhf 3.11.8-1 [1707 kB] Get: 4 http://deb.debian.org/debian trixie/main armhf python3-minimal armhf 3.11.6-1 [26.2 kB] Get: 5 http://deb.debian.org/debian trixie/main armhf media-types all 10.1.0 [26.9 kB] Get: 6 http://deb.debian.org/debian trixie/main armhf netbase all 6.4 [12.8 kB] Get: 7 http://deb.debian.org/debian trixie/main armhf tzdata all 2024a-1 [255 kB] Get: 8 http://deb.debian.org/debian trixie/main armhf readline-common all 8.2-3 [69.1 kB] Get: 9 http://deb.debian.org/debian trixie/main armhf libreadline8 armhf 8.2-3+b1 [144 kB] Get: 10 http://deb.debian.org/debian trixie/main armhf libpython3.11-stdlib armhf 3.11.8-1 [1709 kB] Get: 11 http://deb.debian.org/debian trixie/main armhf python3.11 armhf 3.11.8-1 [597 kB] Get: 12 http://deb.debian.org/debian trixie/main armhf libpython3-stdlib armhf 3.11.6-1 [9224 B] Get: 13 http://deb.debian.org/debian trixie/main armhf python3 armhf 3.11.6-1 [26.2 kB] Get: 14 http://deb.debian.org/debian trixie/main armhf sensible-utils all 0.0.22 [22.4 kB] Get: 15 http://deb.debian.org/debian trixie/main armhf openssl armhf 3.1.5-1 [1208 kB] Get: 16 http://deb.debian.org/debian trixie/main armhf ca-certificates all 20240203 [158 kB] Get: 17 http://deb.debian.org/debian trixie/main armhf libmagic-mgc armhf 1:5.45-2+b1 [314 kB] Get: 18 http://deb.debian.org/debian trixie/main armhf libmagic1 armhf 1:5.45-2+b1 [97.9 kB] Get: 19 http://deb.debian.org/debian trixie/main armhf file armhf 1:5.45-2+b1 [42.2 kB] Get: 20 http://deb.debian.org/debian trixie/main armhf gettext-base armhf 0.21-14+b1 [157 kB] Get: 21 http://deb.debian.org/debian trixie/main armhf libuchardet0 armhf 0.0.8-1+b1 [65.7 kB] Get: 22 http://deb.debian.org/debian trixie/main armhf groff-base armhf 1.23.0-3 [1088 kB] Get: 23 http://deb.debian.org/debian trixie/main armhf bsdextrautils armhf 2.39.3-6 [81.2 kB] Get: 24 http://deb.debian.org/debian trixie/main armhf libpipeline1 armhf 1.5.7-1+b2 [33.4 kB] Get: 25 http://deb.debian.org/debian trixie/main armhf man-db armhf 2.12.0-3 [1367 kB] Get: 26 http://deb.debian.org/debian trixie/main armhf libbsd0 armhf 0.12.2-1 [127 kB] Get: 27 http://deb.debian.org/debian trixie/main armhf libedit2 armhf 3.1-20230828-1 [76.8 kB] Get: 28 http://deb.debian.org/debian trixie/main armhf libcbor0.10 armhf 0.10.2-1.1 [23.9 kB] Get: 29 http://deb.debian.org/debian trixie/main armhf libfido2-1 armhf 1.14.0-1 [69.9 kB] Get: 30 http://deb.debian.org/debian trixie/main armhf openssh-client armhf 1:9.6p1-4 [880 kB] Get: 31 http://deb.debian.org/debian trixie/main armhf ucf all 3.0043+nmu1 [55.2 kB] Get: 32 http://deb.debian.org/debian trixie/main armhf aglfn all 1.7+git20191031.4036a9c-2 [30.5 kB] Get: 33 http://deb.debian.org/debian trixie/main armhf m4 armhf 1.4.19-4 [264 kB] Get: 34 http://deb.debian.org/debian trixie/main armhf autoconf all 2.71-3 [332 kB] Get: 35 http://deb.debian.org/debian trixie/main armhf autotools-dev all 20220109.1 [51.6 kB] Get: 36 http://deb.debian.org/debian trixie/main armhf automake all 1:1.16.5-1.3 [823 kB] Get: 37 http://deb.debian.org/debian trixie/main armhf autopoint all 0.21-14 [496 kB] Get: 38 http://deb.debian.org/debian trixie/main armhf libcapture-tiny-perl all 0.48-2 [24.6 kB] Get: 39 http://deb.debian.org/debian trixie/main armhf libparams-util-perl armhf 1.102-2+b2 [23.3 kB] Get: 40 http://deb.debian.org/debian trixie/main armhf libsub-install-perl all 0.929-1 [10.5 kB] Get: 41 http://deb.debian.org/debian trixie/main armhf libdata-optlist-perl all 0.114-1 [10.6 kB] Get: 42 http://deb.debian.org/debian trixie/main armhf libb-hooks-op-check-perl armhf 0.22-2+b2 [10.3 kB] Get: 43 http://deb.debian.org/debian trixie/main armhf libdynaloader-functions-perl all 0.003-3 [12.7 kB] Get: 44 http://deb.debian.org/debian trixie/main armhf libdevel-callchecker-perl armhf 0.008-2+b1 [14.9 kB] Get: 45 http://deb.debian.org/debian trixie/main armhf libparams-classify-perl armhf 0.015-2+b2 [21.3 kB] Get: 46 http://deb.debian.org/debian trixie/main armhf libmodule-runtime-perl all 0.016-2 [19.6 kB] Get: 47 http://deb.debian.org/debian trixie/main armhf libtry-tiny-perl all 0.31-2 [22.6 kB] Get: 48 http://deb.debian.org/debian trixie/main armhf libmodule-implementation-perl all 0.09-2 [12.6 kB] Get: 49 http://deb.debian.org/debian trixie/main armhf libpackage-stash-perl all 0.40-1 [22.0 kB] Get: 50 http://deb.debian.org/debian trixie/main armhf libclass-load-perl all 0.25-2 [15.3 kB] Get: 51 http://deb.debian.org/debian trixie/main armhf libio-stringy-perl all 2.111-3 [56.5 kB] Get: 52 http://deb.debian.org/debian trixie/main armhf libparams-validate-perl armhf 1.31-2+b1 [62.2 kB] Get: 53 http://deb.debian.org/debian trixie/main armhf libsub-exporter-perl all 0.990-1 [50.6 kB] Get: 54 http://deb.debian.org/debian trixie/main armhf libgetopt-long-descriptive-perl all 0.111-1 [27.8 kB] Get: 55 http://deb.debian.org/debian trixie/main armhf libio-tiecombine-perl all 1.005-3 [10.8 kB] Get: 56 http://deb.debian.org/debian trixie/main armhf libmodule-pluggable-perl all 5.2-5 [23.0 kB] Get: 57 http://deb.debian.org/debian trixie/main armhf libstring-rewriteprefix-perl all 0.009-1 [7140 B] Get: 58 http://deb.debian.org/debian trixie/main armhf libapp-cmd-perl all 0.336-1 [65.8 kB] Get: 59 http://deb.debian.org/debian trixie/main armhf libboolean-perl all 0.46-3 [9924 B] Get: 60 http://deb.debian.org/debian trixie/main armhf libsub-uplevel-perl all 0.2800-3 [14.0 kB] Get: 61 http://deb.debian.org/debian trixie/main armhf libtest-exception-perl all 0.43-3 [16.9 kB] Get: 62 http://deb.debian.org/debian trixie/main armhf libcarp-assert-more-perl all 2.4.0-1 [20.2 kB] Get: 63 http://deb.debian.org/debian trixie/main armhf libfile-which-perl all 1.27-2 [15.1 kB] Get: 64 http://deb.debian.org/debian trixie/main armhf libfile-homedir-perl all 1.006-2 [42.4 kB] Get: 65 http://deb.debian.org/debian trixie/main armhf libclone-choose-perl all 0.010-2 [8676 B] Get: 66 http://deb.debian.org/debian trixie/main armhf libhash-merge-perl all 0.302-1 [14.7 kB] Get: 67 http://deb.debian.org/debian trixie/main armhf libjson-perl all 4.10000-1 [87.5 kB] Get: 68 http://deb.debian.org/debian trixie/main armhf libexporter-tiny-perl all 1.006002-1 [38.7 kB] Get: 69 http://deb.debian.org/debian trixie/main armhf liblist-moreutils-xs-perl armhf 0.430-3+b2 [36.7 kB] Get: 70 http://deb.debian.org/debian trixie/main armhf liblist-moreutils-perl all 0.430-2 [46.9 kB] Get: 71 http://deb.debian.org/debian trixie/main armhf liblog-log4perl-perl all 1.57-1 [367 kB] Get: 72 http://deb.debian.org/debian trixie/main armhf libmouse-perl armhf 2.5.10-1+b4 [139 kB] Get: 73 http://deb.debian.org/debian trixie/main armhf libmousex-nativetraits-perl all 1.09-3 [53.5 kB] Get: 74 http://deb.debian.org/debian trixie/main armhf libmousex-strictconstructor-perl all 0.02-3 [5304 B] Get: 75 http://deb.debian.org/debian trixie/main armhf libparse-recdescent-perl all 1.967015+dfsg-4 [147 kB] Get: 76 http://deb.debian.org/debian trixie/main armhf libpath-tiny-perl all 0.144-1 [56.4 kB] Get: 77 http://deb.debian.org/debian trixie/main armhf libpod-pom-perl all 2.01-4 [65.0 kB] Get: 78 http://deb.debian.org/debian trixie/main armhf libregexp-common-perl all 2017060201-3 [175 kB] Get: 79 http://deb.debian.org/debian trixie/main armhf libyaml-tiny-perl all 1.74-1 [30.7 kB] Get: 80 http://deb.debian.org/debian trixie/main armhf libconfig-model-perl all 2.153-3 [448 kB] Get: 81 http://deb.debian.org/debian trixie/main armhf libyaml-pp-perl all 0.38.0-1 [109 kB] Get: 82 http://deb.debian.org/debian trixie/main armhf cme all 1.040-1 [68.8 kB] Get: 83 http://deb.debian.org/debian trixie/main armhf libdebhelper-perl all 13.15.3 [88.0 kB] Get: 84 http://deb.debian.org/debian trixie/main armhf libtool all 2.4.7-7 [517 kB] Get: 85 http://deb.debian.org/debian trixie/main armhf dh-autoreconf all 20 [17.1 kB] Get: 86 http://deb.debian.org/debian trixie/main armhf libarchive-zip-perl all 1.68-1 [104 kB] Get: 87 http://deb.debian.org/debian trixie/main armhf libsub-override-perl all 0.10-1 [10.6 kB] Get: 88 http://deb.debian.org/debian trixie/main armhf libfile-stripnondeterminism-perl all 1.13.1-1 [19.4 kB] Get: 89 http://deb.debian.org/debian trixie/main armhf dh-strip-nondeterminism all 1.13.1-1 [8620 B] Get: 90 http://deb.debian.org/debian trixie/main armhf libelf1 armhf 0.190-1+b1 [171 kB] Get: 91 http://deb.debian.org/debian trixie/main armhf dwz armhf 0.15-1 [101 kB] Get: 92 http://deb.debian.org/debian trixie/main armhf libicu72 armhf 72.1-4+b1 [9070 kB] Get: 93 http://deb.debian.org/debian trixie/main armhf libxml2 armhf 2.9.14+dfsg-1.3+b2 [599 kB] Get: 94 http://deb.debian.org/debian trixie/main armhf gettext armhf 0.21-14+b1 [1230 kB] Get: 95 http://deb.debian.org/debian trixie/main armhf intltool-debian all 0.35.0+20060710.6 [22.9 kB] Get: 96 http://deb.debian.org/debian trixie/main armhf po-debconf all 1.0.21+nmu1 [248 kB] Get: 97 http://deb.debian.org/debian trixie/main armhf debhelper all 13.15.3 [901 kB] Get: 98 http://deb.debian.org/debian trixie/main armhf gnuplot-data all 6.0.0+dfsg1-1 [72.1 kB] Get: 99 http://deb.debian.org/debian trixie/main armhf libbrotli1 armhf 1.1.0-2+b3 [284 kB] Get: 100 http://deb.debian.org/debian trixie/main armhf libpng16-16 armhf 1.6.43-1 [262 kB] Get: 101 http://deb.debian.org/debian trixie/main armhf libfreetype6 armhf 2.13.2+dfsg-1+b1 [371 kB] Get: 102 http://deb.debian.org/debian trixie/main armhf fonts-dejavu-mono all 2.37-8 [489 kB] Get: 103 http://deb.debian.org/debian trixie/main armhf fonts-dejavu-core all 2.37-8 [840 kB] Get: 104 http://deb.debian.org/debian trixie/main armhf fonts-freefont-otf all 20211204+svn4273-2 [4328 kB] Get: 105 http://deb.debian.org/debian trixie/main armhf fontconfig-config armhf 2.15.0-1.1 [317 kB] Get: 106 http://deb.debian.org/debian trixie/main armhf libfontconfig1 armhf 2.15.0-1.1 [370 kB] Get: 107 http://deb.debian.org/debian trixie/main armhf libpixman-1-0 armhf 0.42.2-1+b1 [476 kB] Get: 108 http://deb.debian.org/debian trixie/main armhf libxau6 armhf 1:1.0.9-1 [19.0 kB] Get: 109 http://deb.debian.org/debian trixie/main armhf libxdmcp6 armhf 1:1.1.2-3 [24.9 kB] Get: 110 http://deb.debian.org/debian trixie/main armhf libxcb1 armhf 1.15-1 [140 kB] Get: 111 http://deb.debian.org/debian trixie/main armhf libx11-data all 2:1.8.7-1 [328 kB] Get: 112 http://deb.debian.org/debian trixie/main armhf libx11-6 armhf 2:1.8.7-1 [735 kB] Get: 113 http://deb.debian.org/debian trixie/main armhf libxcb-render0 armhf 1.15-1 [114 kB] Get: 114 http://deb.debian.org/debian trixie/main armhf libxcb-shm0 armhf 1.15-1 [106 kB] Get: 115 http://deb.debian.org/debian trixie/main armhf libxext6 armhf 2:1.3.4-1+b1 [47.8 kB] Get: 116 http://deb.debian.org/debian trixie/main armhf libxrender1 armhf 1:0.9.10-1.1 [30.1 kB] Get: 117 http://deb.debian.org/debian trixie/main armhf libcairo2 armhf 1.18.0-1+b1 [441 kB] Get: 118 http://deb.debian.org/debian trixie/main armhf libaom3 armhf 3.8.2-2 [1526 kB] Get: 119 http://deb.debian.org/debian trixie/main armhf libdav1d7 armhf 1.4.1-1 [262 kB] Get: 120 http://deb.debian.org/debian trixie/main armhf libabsl20220623 armhf 20220623.1-3 [361 kB] Get: 121 http://deb.debian.org/debian trixie/main armhf libgav1-1 armhf 0.18.0-1+b1 [284 kB] Get: 122 http://deb.debian.org/debian trixie/main armhf librav1e0 armhf 0.7.1-2 [546 kB] Get: 123 http://deb.debian.org/debian trixie/main armhf libsharpyuv0 armhf 1.3.2-0.4 [105 kB] Get: 124 http://deb.debian.org/debian trixie/main armhf libsvtav1enc1d1 armhf 1.7.0+dfsg-2+b1 [936 kB] Get: 125 http://deb.debian.org/debian trixie/main armhf libjpeg62-turbo armhf 1:2.1.5-2+b2 [143 kB] Get: 126 http://deb.debian.org/debian trixie/main armhf libyuv0 armhf 0.0~git202401110.af6ac82-1 [85.1 kB] Get: 127 http://deb.debian.org/debian trixie/main armhf libavif16 armhf 1.0.4-1 [95.0 kB] Get: 128 http://deb.debian.org/debian trixie/main armhf libheif-plugin-dav1d armhf 1.17.6-1 [9252 B] Get: 129 http://deb.debian.org/debian trixie/main armhf libde265-0 armhf 1.0.15-1 [145 kB] Get: 130 http://deb.debian.org/debian trixie/main armhf libheif-plugin-libde265 armhf 1.17.6-1 [12.0 kB] Get: 131 http://deb.debian.org/debian trixie/main armhf libheif1 armhf 1.17.6-1 [242 kB] Get: 132 http://deb.debian.org/debian trixie/main armhf libdeflate0 armhf 1.20-1 [35.9 kB] Get: 133 http://deb.debian.org/debian trixie/main armhf libjbig0 armhf 2.1-6.1+b1 [27.3 kB] Get: 134 http://deb.debian.org/debian trixie/main armhf liblerc4 armhf 4.0.0+ds-4+b1 [137 kB] Get: 135 http://deb.debian.org/debian trixie/main armhf libwebp7 armhf 1.3.2-0.4 [261 kB] Get: 136 http://deb.debian.org/debian trixie/main armhf libtiff6 armhf 4.5.1+git230720-4 [301 kB] Get: 137 http://deb.debian.org/debian trixie/main armhf libxpm4 armhf 1:3.5.17-1 [49.5 kB] Get: 138 http://deb.debian.org/debian trixie/main armhf libgd3 armhf 2.3.3-9+b1 [103 kB] Get: 139 http://deb.debian.org/debian trixie/main armhf libglib2.0-0 armhf 2.78.4-1 [1281 kB] Get: 140 http://deb.debian.org/debian trixie/main armhf liblua5.4-0 armhf 5.4.6-3 [122 kB] Get: 141 http://deb.debian.org/debian trixie/main armhf fontconfig armhf 2.15.0-1.1 [461 kB] Get: 142 http://deb.debian.org/debian trixie/main armhf libfribidi0 armhf 1.0.13-3+b1 [69.4 kB] Get: 143 http://deb.debian.org/debian trixie/main armhf libgraphite2-3 armhf 1.3.14-2 [63.2 kB] Get: 144 http://deb.debian.org/debian trixie/main armhf libharfbuzz0b armhf 8.3.0-2 [2155 kB] Get: 145 http://deb.debian.org/debian trixie/main armhf libthai-data all 0.1.29-2 [168 kB] Get: 146 http://deb.debian.org/debian trixie/main armhf libdatrie1 armhf 0.2.13-3 [34.4 kB] Get: 147 http://deb.debian.org/debian trixie/main armhf libthai0 armhf 0.1.29-2 [45.8 kB] Get: 148 http://deb.debian.org/debian trixie/main armhf libpango-1.0-0 armhf 1.52.0+ds-1 [192 kB] Get: 149 http://deb.debian.org/debian trixie/main armhf libpangoft2-1.0-0 armhf 1.52.0+ds-1 [41.8 kB] Get: 150 http://deb.debian.org/debian trixie/main armhf libpangocairo-1.0-0 armhf 1.52.0+ds-1 [31.2 kB] Get: 151 http://deb.debian.org/debian trixie/main armhf libwebpmux3 armhf 1.3.2-0.4 [116 kB] Get: 152 http://deb.debian.org/debian trixie/main armhf gnuplot-nox armhf 6.0.0+dfsg1-1 [837 kB] Get: 153 http://deb.debian.org/debian trixie/main armhf dh-octave-autopkgtest all 1.8.0 [10.0 kB] Get: 154 http://deb.debian.org/debian trixie/main armhf libapt-pkg-perl armhf 0.1.40+b3 [62.4 kB] Get: 155 http://deb.debian.org/debian trixie/main armhf libarray-intspan-perl all 2.004-2 [25.7 kB] Get: 156 http://deb.debian.org/debian trixie/main armhf libyaml-0-2 armhf 0.2.5-1 [46.8 kB] Get: 157 http://deb.debian.org/debian trixie/main armhf libyaml-libyaml-perl armhf 0.89+ds-1 [32.5 kB] Get: 158 http://deb.debian.org/debian trixie/main armhf libconfig-model-backend-yaml-perl all 2.134-2 [10.8 kB] Get: 159 http://deb.debian.org/debian trixie/main armhf libexporter-lite-perl all 0.09-2 [10.7 kB] Get: 160 http://deb.debian.org/debian trixie/main armhf libencode-locale-perl all 1.05-3 [12.9 kB] Get: 161 http://deb.debian.org/debian trixie/main armhf libtimedate-perl all 2.3300-2 [39.3 kB] Get: 162 http://deb.debian.org/debian trixie/main armhf libhttp-date-perl all 6.06-1 [10.7 kB] Get: 163 http://deb.debian.org/debian trixie/main armhf libfile-listing-perl all 6.16-1 [12.4 kB] Get: 164 http://deb.debian.org/debian trixie/main armhf libhtml-tagset-perl all 3.24-1 [14.7 kB] Get: 165 http://deb.debian.org/debian trixie/main armhf liburi-perl all 5.27-1 [98.4 kB] Get: 166 http://deb.debian.org/debian trixie/main armhf libhtml-parser-perl armhf 3.81-1+b1 [95.8 kB] Get: 167 http://deb.debian.org/debian trixie/main armhf libhtml-tree-perl all 5.07-3 [211 kB] Get: 168 http://deb.debian.org/debian trixie/main armhf libclone-perl armhf 0.46-1+b1 [13.2 kB] Get: 169 http://deb.debian.org/debian trixie/main armhf libio-html-perl all 1.004-3 [16.2 kB] Get: 170 http://deb.debian.org/debian trixie/main armhf liblwp-mediatypes-perl all 6.04-2 [20.2 kB] Get: 171 http://deb.debian.org/debian trixie/main armhf libhttp-message-perl all 6.45-1 [82.0 kB] Get: 172 http://deb.debian.org/debian trixie/main armhf libhttp-cookies-perl all 6.11-1 [19.1 kB] Get: 173 http://deb.debian.org/debian trixie/main armhf libhttp-negotiate-perl all 6.01-2 [13.1 kB] Get: 174 http://deb.debian.org/debian trixie/main armhf perl-openssl-defaults armhf 7+b1 [7916 B] Get: 175 http://deb.debian.org/debian trixie/main armhf libnet-ssleay-perl armhf 1.94-1 [318 kB] Get: 176 http://deb.debian.org/debian trixie/main armhf libio-socket-ssl-perl all 2.085-1 [218 kB] Get: 177 http://deb.debian.org/debian trixie/main armhf libnet-http-perl all 6.23-1 [23.9 kB] Get: 178 http://deb.debian.org/debian trixie/main armhf liblwp-protocol-https-perl all 6.14-1 [10.8 kB] Get: 179 http://deb.debian.org/debian trixie/main armhf libwww-robotrules-perl all 6.02-1 [12.9 kB] Get: 180 http://deb.debian.org/debian trixie/main armhf libwww-perl all 6.77-1 [183 kB] Get: 181 http://deb.debian.org/debian trixie/main armhf liberror-perl all 0.17029-2 [29.0 kB] Get: 182 http://deb.debian.org/debian trixie/main armhf libparse-debcontrol-perl all 2.005-6 [21.6 kB] Get: 183 http://deb.debian.org/debian trixie/main armhf libsoftware-copyright-perl all 0.012-2 [18.0 kB] Get: 184 http://deb.debian.org/debian trixie/main armhf libalgorithm-c3-perl all 0.11-2 [10.8 kB] Get: 185 http://deb.debian.org/debian trixie/main armhf libclass-c3-perl all 0.35-2 [21.0 kB] Get: 186 http://deb.debian.org/debian trixie/main armhf libmro-compat-perl all 0.15-2 [11.8 kB] Get: 187 http://deb.debian.org/debian trixie/main armhf libdata-section-perl all 0.200008-1 [13.1 kB] Get: 188 http://deb.debian.org/debian trixie/main armhf libtext-template-perl all 1.61-1 [54.4 kB] Get: 189 http://deb.debian.org/debian trixie/main armhf libsoftware-license-perl all 0.104006-1 [116 kB] Get: 190 http://deb.debian.org/debian trixie/main armhf libsoftware-licensemoreutils-perl all 1.009-1 [22.0 kB] Get: 191 http://deb.debian.org/debian trixie/main armhf libsort-versions-perl all 1.62-3 [8928 B] Get: 192 http://deb.debian.org/debian trixie/main armhf libtext-reform-perl all 1.20-5 [36.0 kB] Get: 193 http://deb.debian.org/debian trixie/main armhf libtext-autoformat-perl all 1.750000-2 [35.2 kB] Get: 194 http://deb.debian.org/debian trixie/main armhf libtext-levenshtein-damerau-perl all 0.41-3 [12.3 kB] Get: 195 http://deb.debian.org/debian trixie/main armhf libtoml-tiny-perl all 0.16-1 [23.4 kB] Get: 196 http://deb.debian.org/debian trixie/main armhf libindirect-perl armhf 0.39-2+b2 [25.8 kB] Get: 197 http://deb.debian.org/debian trixie/main armhf libxs-parse-keyword-perl armhf 0.39-1+b1 [55.1 kB] Get: 198 http://deb.debian.org/debian trixie/main armhf libxs-parse-sublike-perl armhf 0.21-2+b1 [38.6 kB] Get: 199 http://deb.debian.org/debian trixie/main armhf libobject-pad-perl armhf 0.808-1+b1 [111 kB] Get: 200 http://deb.debian.org/debian trixie/main armhf libfeature-compat-class-perl all 0.06-1 [10.7 kB] Get: 201 http://deb.debian.org/debian trixie/main armhf libsyntax-keyword-try-perl armhf 0.29-1+b1 [26.2 kB] Get: 202 http://deb.debian.org/debian trixie/main armhf libfeature-compat-try-perl all 0.05-1 [10.4 kB] Get: 203 http://deb.debian.org/debian trixie/main armhf libio-interactive-perl all 1.025-1 [11.4 kB] Get: 204 http://deb.debian.org/debian trixie/main armhf liblog-any-perl all 1.717-1 [78.9 kB] Get: 205 http://deb.debian.org/debian trixie/main armhf liblog-any-adapter-screen-perl all 0.140-2 [13.3 kB] Get: 206 http://deb.debian.org/debian trixie/main armhf libsub-exporter-progressive-perl all 0.001013-3 [7496 B] Get: 207 http://deb.debian.org/debian trixie/main armhf libvariable-magic-perl armhf 0.63-1+b2 [41.4 kB] Get: 208 http://deb.debian.org/debian trixie/main armhf libb-hooks-endofscope-perl all 0.28-1 [17.5 kB] Get: 209 http://deb.debian.org/debian trixie/main armhf libsub-identify-perl armhf 0.14-3+b1 [10.8 kB] Get: 210 http://deb.debian.org/debian trixie/main armhf libsub-name-perl armhf 0.27-1+b1 [12.0 kB] Get: 211 http://deb.debian.org/debian trixie/main armhf libnamespace-clean-perl all 0.27-2 [17.8 kB] Get: 212 http://deb.debian.org/debian trixie/main armhf libnumber-compare-perl all 0.03-3 [6332 B] Get: 213 http://deb.debian.org/debian trixie/main armhf libtext-glob-perl all 0.11-3 [7676 B] Get: 214 http://deb.debian.org/debian trixie/main armhf libpath-iterator-rule-perl all 1.015-2 [41.7 kB] Get: 215 http://deb.debian.org/debian trixie/main armhf libpod-parser-perl all 1.67-1 [94.1 kB] Get: 216 http://deb.debian.org/debian trixie/main armhf libpod-constants-perl all 0.19-2 [17.3 kB] Get: 217 http://deb.debian.org/debian trixie/main armhf libset-intspan-perl all 1.19-3 [25.3 kB] Get: 218 http://deb.debian.org/debian trixie/main armhf libstring-copyright-perl all 0.003014-1 [23.4 kB] Get: 219 http://deb.debian.org/debian trixie/main armhf libstring-escape-perl all 2010.002-3 [18.7 kB] Get: 220 http://deb.debian.org/debian trixie/main armhf libregexp-pattern-license-perl all 3.11.0-1 [94.8 kB] Get: 221 http://deb.debian.org/debian trixie/main armhf libregexp-pattern-perl all 0.2.14-2 [18.7 kB] Get: 222 http://deb.debian.org/debian trixie/main armhf libstring-license-perl all 0.0.9-2 [35.5 kB] Get: 223 http://deb.debian.org/debian trixie/main armhf licensecheck all 3.3.9-1 [50.1 kB] Get: 224 http://deb.debian.org/debian trixie/main armhf diffstat armhf 1.66-1 [32.0 kB] Get: 225 http://deb.debian.org/debian trixie/main armhf libassuan0 armhf 2.5.6-1 [43.3 kB] Get: 226 http://deb.debian.org/debian trixie/main armhf gpgconf armhf 2.2.40-1.1+b1 [547 kB] Get: 227 http://deb.debian.org/debian trixie/main armhf gpg armhf 2.2.40-1.1+b1 [886 kB] Get: 228 http://deb.debian.org/debian trixie/main armhf iso-codes all 4.16.0-1 [2936 kB] Get: 229 http://deb.debian.org/debian trixie/main armhf libberkeleydb-perl armhf 0.64-2+b2 [109 kB] Get: 230 http://deb.debian.org/debian trixie/main armhf libclass-xsaccessor-perl armhf 1.19-4+b2 [35.3 kB] Get: 231 http://deb.debian.org/debian trixie/main armhf libconfig-tiny-perl all 2.30-1 [18.9 kB] Get: 232 http://deb.debian.org/debian trixie/main armhf libconst-fast-perl all 0.014-2 [8792 B] Get: 233 http://deb.debian.org/debian trixie/main armhf libcpanel-json-xs-perl armhf 4.37-1+b1 [127 kB] Get: 234 http://deb.debian.org/debian trixie/main armhf libaliased-perl all 0.34-3 [13.5 kB] Get: 235 http://deb.debian.org/debian trixie/main armhf libclass-data-inheritable-perl all 0.08-3 [8588 B] Get: 236 http://deb.debian.org/debian trixie/main armhf libdevel-stacktrace-perl all 2.0500-1 [26.4 kB] Get: 237 http://deb.debian.org/debian trixie/main armhf libexception-class-perl all 1.45-1 [34.6 kB] Get: 238 http://deb.debian.org/debian trixie/main armhf libiterator-perl all 0.03+ds1-2 [18.8 kB] Get: 239 http://deb.debian.org/debian trixie/main armhf libiterator-util-perl all 0.02+ds1-2 [14.0 kB] Get: 240 http://deb.debian.org/debian trixie/main armhf libdata-dpath-perl all 0.59-1 [43.6 kB] Get: 241 http://deb.debian.org/debian trixie/main armhf libnet-domain-tld-perl all 1.75-3 [31.9 kB] Get: 242 http://deb.debian.org/debian trixie/main armhf libdata-validate-domain-perl all 0.10-1.1 [11.1 kB] Get: 243 http://deb.debian.org/debian trixie/main armhf libnet-ipv6addr-perl all 1.02-1 [21.7 kB] Get: 244 http://deb.debian.org/debian trixie/main armhf libnet-netmask-perl all 2.0002-2 [28.6 kB] Get: 245 http://deb.debian.org/debian trixie/main armhf libnetaddr-ip-perl armhf 4.079+dfsg-2+b2 [97.0 kB] Get: 246 http://deb.debian.org/debian trixie/main armhf libdata-validate-ip-perl all 0.31-1 [20.6 kB] Get: 247 http://deb.debian.org/debian trixie/main armhf libdata-validate-uri-perl all 0.07-3 [11.0 kB] Get: 248 http://deb.debian.org/debian trixie/main armhf libdevel-size-perl armhf 0.83-2+b2 [23.6 kB] Get: 249 http://deb.debian.org/debian trixie/main armhf libemail-address-xs-perl armhf 1.05-1+b2 [26.6 kB] Get: 250 http://deb.debian.org/debian trixie/main armhf libipc-system-simple-perl all 1.30-2 [26.8 kB] Get: 251 http://deb.debian.org/debian trixie/main armhf libfile-basedir-perl all 0.09-2 [15.1 kB] Get: 252 http://deb.debian.org/debian trixie/main armhf libfile-find-rule-perl all 0.34-3 [26.6 kB] Get: 253 http://deb.debian.org/debian trixie/main armhf libio-string-perl all 1.08-4 [12.1 kB] Get: 254 http://deb.debian.org/debian trixie/main armhf libfont-ttf-perl all 1.06-2 [318 kB] Get: 255 http://deb.debian.org/debian trixie/main armhf libhtml-html5-entities-perl all 0.004-3 [21.0 kB] Get: 256 http://deb.debian.org/debian trixie/main armhf libhtml-tokeparser-simple-perl all 3.16-4 [39.1 kB] Get: 257 http://deb.debian.org/debian trixie/main armhf libipc-run3-perl all 0.049-1 [31.5 kB] Get: 258 http://deb.debian.org/debian trixie/main armhf libjson-maybexs-perl all 1.004005-1 [12.9 kB] Get: 259 http://deb.debian.org/debian trixie/main armhf liblist-compare-perl all 0.55-2 [65.7 kB] Get: 260 http://deb.debian.org/debian trixie/main armhf liblist-someutils-perl all 0.59-1 [37.1 kB] Get: 261 http://deb.debian.org/debian trixie/main armhf liblist-utilsby-perl all 0.12-2 [15.5 kB] Get: 262 http://deb.debian.org/debian trixie/main armhf libmldbm-perl all 2.05-4 [16.8 kB] Get: 263 http://deb.debian.org/debian trixie/main armhf libclass-method-modifiers-perl all 2.15-1 [18.0 kB] Get: 264 http://deb.debian.org/debian trixie/main armhf libimport-into-perl all 1.002005-2 [11.3 kB] Get: 265 http://deb.debian.org/debian trixie/main armhf librole-tiny-perl all 2.002004-1 [21.4 kB] Get: 266 http://deb.debian.org/debian trixie/main armhf libsub-quote-perl all 2.006008-1 [21.8 kB] Get: 267 http://deb.debian.org/debian trixie/main armhf libmoo-perl all 2.005005-1 [58.0 kB] Get: 268 http://deb.debian.org/debian trixie/main armhf libstrictures-perl all 2.000006-1 [18.6 kB] Get: 269 http://deb.debian.org/debian trixie/main armhf libmoox-aliases-perl all 0.001006-2 [7156 B] Get: 270 http://deb.debian.org/debian trixie/main armhf libperlio-gzip-perl armhf 0.20-1+b2 [16.4 kB] Get: 271 http://deb.debian.org/debian trixie/main armhf libperlio-utf8-strict-perl armhf 0.010-1+b1 [10.9 kB] Get: 272 http://deb.debian.org/debian trixie/main armhf libproc-processtable-perl armhf 0.636-1+b1 [42.0 kB] Get: 273 http://deb.debian.org/debian trixie/main armhf libregexp-wildcards-perl all 1.05-3 [14.1 kB] Get: 274 http://deb.debian.org/debian trixie/main armhf libsereal-decoder-perl armhf 5.004+ds-1+b1 [92.5 kB] Get: 275 http://deb.debian.org/debian trixie/main armhf libsereal-encoder-perl armhf 5.004+ds-1+b1 [95.0 kB] Get: 276 http://deb.debian.org/debian trixie/main armhf libterm-readkey-perl armhf 2.38-2+b2 [23.7 kB] Get: 277 http://deb.debian.org/debian trixie/main armhf libtext-levenshteinxs-perl armhf 0.03-5+b2 [8116 B] Get: 278 http://deb.debian.org/debian trixie/main armhf libmarkdown2 armhf 2.2.7-2+b1 [28.8 kB] Get: 279 http://deb.debian.org/debian trixie/main armhf libtext-markdown-discount-perl armhf 0.16-1+b1 [12.7 kB] Get: 280 http://deb.debian.org/debian trixie/main armhf libdata-messagepack-perl armhf 1.02-1+b2 [30.6 kB] Get: 281 http://deb.debian.org/debian trixie/main armhf libtext-xslate-perl armhf 3.5.9-1+b3 [170 kB] Get: 282 http://deb.debian.org/debian trixie/main armhf libtime-duration-perl all 1.21-2 [13.1 kB] Get: 283 http://deb.debian.org/debian trixie/main armhf libtime-moment-perl armhf 0.44-2+b2 [72.0 kB] Get: 284 http://deb.debian.org/debian trixie/main armhf libunicode-utf8-perl armhf 0.62-2+b1 [19.2 kB] Get: 285 http://deb.debian.org/debian trixie/main armhf libcgi-pm-perl all 4.64-1 [217 kB] Get: 286 http://deb.debian.org/debian trixie/main armhf libhtml-form-perl all 6.11-1 [33.1 kB] Get: 287 http://deb.debian.org/debian trixie/main armhf libwww-mechanize-perl all 2.18-1 [114 kB] Get: 288 http://deb.debian.org/debian trixie/main armhf libxml-namespacesupport-perl all 1.12-2 [15.1 kB] Get: 289 http://deb.debian.org/debian trixie/main armhf libxml-sax-base-perl all 1.09-3 [20.6 kB] Get: 290 http://deb.debian.org/debian trixie/main armhf libxml-sax-perl all 1.02+dfsg-3 [59.4 kB] Get: 291 http://deb.debian.org/debian trixie/main armhf libxml-libxml-perl armhf 2.0207+dfsg+really+2.0134-1+b2 [298 kB] Get: 292 http://deb.debian.org/debian trixie/main armhf liblz1 armhf 1.14-1 [36.5 kB] Get: 293 http://deb.debian.org/debian trixie/main armhf plzip armhf 1.11-1 [58.0 kB] Get: 294 http://deb.debian.org/debian trixie/main armhf liblzo2-2 armhf 2.10-2+b1 [48.0 kB] Get: 295 http://deb.debian.org/debian trixie/main armhf lzop armhf 1.04-2 [82.2 kB] Get: 296 http://deb.debian.org/debian trixie/main armhf patchutils armhf 0.4.2-1 [72.5 kB] Get: 297 http://deb.debian.org/debian trixie/main armhf t1utils armhf 1.41-4 [54.7 kB] Get: 298 http://deb.debian.org/debian trixie/main armhf unzip armhf 6.0-28 [152 kB] Get: 299 http://deb.debian.org/debian trixie/main armhf lintian all 2.117.0 [1052 kB] Get: 300 http://deb.debian.org/debian trixie/main armhf libconfig-model-dpkg-perl all 3.004 [173 kB] Get: 301 http://deb.debian.org/debian trixie/main armhf libconvert-binhex-perl all 1.125-3 [27.4 kB] Get: 302 http://deb.debian.org/debian trixie/main armhf libnet-smtp-ssl-perl all 1.04-2 [6548 B] Get: 303 http://deb.debian.org/debian trixie/main armhf libmailtools-perl all 2.21-3 [88.6 kB] Get: 304 http://deb.debian.org/debian trixie/main armhf libmime-tools-perl all 5.514-1 [203 kB] Get: 305 http://deb.debian.org/debian trixie/main armhf libsuitesparseconfig7 armhf 1:7.6.1+dfsg-1 [21.6 kB] Get: 306 http://deb.debian.org/debian trixie/main armhf libamd3 armhf 1:7.6.1+dfsg-1 [39.1 kB] Get: 307 http://deb.debian.org/debian trixie/main armhf libblas3 armhf 3.12.0-3 [108 kB] Get: 308 http://deb.debian.org/debian trixie/main armhf libgfortran5 armhf 14-20240201-3 [263 kB] Get: 309 http://deb.debian.org/debian trixie/main armhf liblapack3 armhf 3.12.0-3 [1803 kB] Get: 310 http://deb.debian.org/debian trixie/main armhf libarpack2 armhf 3.9.1-1+b1 [84.7 kB] Get: 311 http://deb.debian.org/debian trixie/main armhf libccolamd3 armhf 1:7.6.1+dfsg-1 [39.4 kB] Get: 312 http://deb.debian.org/debian trixie/main armhf libcamd3 armhf 1:7.6.1+dfsg-1 [37.3 kB] Get: 313 http://deb.debian.org/debian trixie/main armhf libcolamd3 armhf 1:7.6.1+dfsg-1 [31.8 kB] Get: 314 http://deb.debian.org/debian trixie/main armhf libcholmod5 armhf 1:7.6.1+dfsg-1 [607 kB] Get: 315 http://deb.debian.org/debian trixie/main armhf libsasl2-modules-db armhf 2.1.28+dfsg1-4+b1 [18.2 kB] Get: 316 http://deb.debian.org/debian trixie/main armhf libsasl2-2 armhf 2.1.28+dfsg1-4+b1 [50.1 kB] Get: 317 http://deb.debian.org/debian trixie/main armhf libldap-2.5-0 armhf 2.5.13+dfsg-5+b3 [158 kB] Get: 318 http://deb.debian.org/debian trixie/main armhf libnghttp2-14 armhf 1.59.0-1 [62.0 kB] Get: 319 http://deb.debian.org/debian trixie/main armhf libpsl5 armhf 0.21.2-1+b1 [57.8 kB] Get: 320 http://deb.debian.org/debian trixie/main armhf librtmp1 armhf 2.4+20151223.gitfa8646d.1-2+b2 [55.2 kB] Get: 321 http://deb.debian.org/debian trixie/main armhf libssh2-1 armhf 1.11.0-4 [197 kB] Get: 322 http://deb.debian.org/debian trixie/main armhf libcurl3-gnutls armhf 8.5.0-2 [378 kB] Get: 323 http://deb.debian.org/debian trixie/main armhf libcxsparse4 armhf 1:7.6.1+dfsg-1 [78.8 kB] Get: 324 http://deb.debian.org/debian trixie/main armhf libfftw3-double3 armhf 3.3.10-1+b1 [328 kB] Get: 325 http://deb.debian.org/debian trixie/main armhf libfftw3-single3 armhf 3.3.10-1+b1 [519 kB] Get: 326 http://deb.debian.org/debian trixie/main armhf libxfixes3 armhf 1:6.0.0-2 [21.1 kB] Get: 327 http://deb.debian.org/debian trixie/main armhf libxcursor1 armhf 1:1.2.1-1 [37.9 kB] Get: 328 http://deb.debian.org/debian trixie/main armhf libxft2 armhf 2.3.6-1+b1 [46.4 kB] Get: 329 http://deb.debian.org/debian trixie/main armhf libxinerama1 armhf 2:1.1.4-3 [17.4 kB] Get: 330 http://deb.debian.org/debian trixie/main armhf libfltk1.3 armhf 1.3.8-6+b1 [492 kB] Get: 331 http://deb.debian.org/debian trixie/main armhf libglvnd0 armhf 1.7.0-1 [52.3 kB] Get: 332 http://deb.debian.org/debian trixie/main armhf libdrm-common all 2.4.120-2 [7688 B] Get: 333 http://deb.debian.org/debian trixie/main armhf libdrm2 armhf 2.4.120-2 [33.8 kB] Get: 334 http://deb.debian.org/debian trixie/main armhf libglapi-mesa armhf 23.3.5-1 [42.5 kB] Get: 335 http://deb.debian.org/debian trixie/main armhf libx11-xcb1 armhf 2:1.8.7-1 [231 kB] Get: 336 http://deb.debian.org/debian trixie/main armhf libxcb-dri2-0 armhf 1.15-1 [107 kB] Get: 337 http://deb.debian.org/debian trixie/main armhf libxcb-dri3-0 armhf 1.15-1 [107 kB] Get: 338 http://deb.debian.org/debian trixie/main armhf libxcb-glx0 armhf 1.15-1 [120 kB] Get: 339 http://deb.debian.org/debian trixie/main armhf libxcb-present0 armhf 1.15-1 [105 kB] Get: 340 http://deb.debian.org/debian trixie/main armhf libxcb-randr0 armhf 1.15-1 [116 kB] Get: 341 http://deb.debian.org/debian trixie/main armhf libxcb-sync1 armhf 1.15-1 [108 kB] Get: 342 http://deb.debian.org/debian trixie/main armhf libxcb-xfixes0 armhf 1.15-1 [110 kB] Get: 343 http://deb.debian.org/debian trixie/main armhf libxshmfence1 armhf 1.3-1 [8592 B] Get: 344 http://deb.debian.org/debian trixie/main armhf libxxf86vm1 armhf 1:1.1.4-1+b2 [20.2 kB] Get: 345 http://deb.debian.org/debian trixie/main armhf libvulkan1 armhf 1.3.275.0-1 [109 kB] Get: 346 http://deb.debian.org/debian trixie/main armhf libdrm-amdgpu1 armhf 2.4.120-2 [20.0 kB] Get: 347 http://deb.debian.org/debian trixie/main armhf libdrm-nouveau2 armhf 2.4.120-2 [16.9 kB] Get: 348 http://deb.debian.org/debian trixie/main armhf libdrm-radeon1 armhf 2.4.120-2 [19.5 kB] Get: 349 http://deb.debian.org/debian trixie/main armhf libz3-4 armhf 4.8.12-3.1+b2 [6324 kB] Get: 350 http://deb.debian.org/debian trixie/main armhf libllvm17 armhf 1:17.0.6-5 [21.6 MB] Get: 351 http://deb.debian.org/debian trixie/main armhf libsensors-config all 1:3.6.0-9 [14.6 kB] Get: 352 http://deb.debian.org/debian trixie/main armhf libsensors5 armhf 1:3.6.0-9 [31.9 kB] Get: 353 http://deb.debian.org/debian trixie/main armhf libgl1-mesa-dri armhf 23.3.5-1 [6405 kB] Get: 354 http://deb.debian.org/debian trixie/main armhf libglx-mesa0 armhf 23.3.5-1 [130 kB] Get: 355 http://deb.debian.org/debian trixie/main armhf libglx0 armhf 1.7.0-1 [32.2 kB] Get: 356 http://deb.debian.org/debian trixie/main armhf libgl1 armhf 1.7.0-1 [90.8 kB] Get: 357 http://deb.debian.org/debian trixie/main armhf libfltk-gl1.3 armhf 1.3.8-6+b1 [56.3 kB] Get: 358 http://deb.debian.org/debian trixie/main armhf libgl2ps1.4 armhf 1.4.2+dfsg1-2 [36.5 kB] Get: 359 http://deb.debian.org/debian trixie/main armhf libltdl7 armhf 2.4.7-7 [390 kB] Get: 360 http://deb.debian.org/debian trixie/main armhf libglpk40 armhf 5.0-1+b1 [330 kB] Get: 361 http://deb.debian.org/debian trixie/main armhf libopengl0 armhf 1.7.0-1 [31.9 kB] Get: 362 http://deb.debian.org/debian trixie/main armhf libglu1-mesa armhf 9.0.2-1.1 [137 kB] Get: 363 http://deb.debian.org/debian trixie/main armhf libhwy1 armhf 1.0.7-8+b1 [213 kB] Get: 364 http://deb.debian.org/debian trixie/main armhf liblcms2-2 armhf 2.14-2+b1 [126 kB] Get: 365 http://deb.debian.org/debian trixie/main armhf libjxl0.7 armhf 0.7.0-10.2+b1 [644 kB] Get: 366 http://deb.debian.org/debian trixie/main armhf libwmflite-0.2-7 armhf 0.2.13-1.1 [69.0 kB] Get: 367 http://deb.debian.org/debian trixie/main armhf libgraphicsmagick-q16-3 armhf 1.4+really1.3.42-1+b1 [1103 kB] Get: 368 http://deb.debian.org/debian trixie/main armhf libgraphicsmagick++-q16-12 armhf 1.4+really1.3.42-1+b1 [112 kB] Get: 369 http://deb.debian.org/debian trixie/main armhf libcurl4 armhf 8.5.0-2 [383 kB] Get: 370 http://deb.debian.org/debian trixie/main armhf libaec0 armhf 1.1.3-1 [21.5 kB] Get: 371 http://deb.debian.org/debian trixie/main armhf libsz2 armhf 1.1.3-1 [7724 B] Get: 372 http://deb.debian.org/debian trixie/main armhf libhdf5-103-1 armhf 1.10.10+repack-3+b1 [1190 kB] Get: 373 http://deb.debian.org/debian trixie/main armhf libasound2-data all 1.2.10-3 [20.7 kB] Get: 374 http://deb.debian.org/debian trixie/main armhf libasound2 armhf 1.2.10-3 [316 kB] Get: 375 http://deb.debian.org/debian trixie/main armhf libopus0 armhf 1.4-1+b1 [174 kB] Get: 376 http://deb.debian.org/debian trixie/main armhf libsamplerate0 armhf 0.2.2-4 [946 kB] Get: 377 http://deb.debian.org/debian trixie/main armhf libjack-jackd2-0 armhf 1.9.21~dfsg-3+b1 [238 kB] Get: 378 http://deb.debian.org/debian trixie/main armhf libportaudio2 armhf 19.6.0-1.2+b1 [55.9 kB] Get: 379 http://deb.debian.org/debian trixie/main armhf libqhull-r8.0 armhf 2020.2-6+b1 [219 kB] Get: 380 http://deb.debian.org/debian trixie/main armhf libqrupdate1 armhf 1.1.2-4+b1 [28.2 kB] Get: 381 http://deb.debian.org/debian trixie/main armhf libqscintilla2-qt5-l10n all 2.14.1+dfsg-1 [105 kB] Get: 382 http://deb.debian.org/debian trixie/main armhf shared-mime-info armhf 2.4-1 [746 kB] Get: 383 http://deb.debian.org/debian trixie/main armhf libdouble-conversion3 armhf 3.3.0-1+b1 [38.5 kB] Get: 384 http://deb.debian.org/debian trixie/main armhf libpcre2-16-0 armhf 10.42-4+b1 [212 kB] Get: 385 http://deb.debian.org/debian trixie/main armhf libqt5core5a armhf 5.15.10+dfsg-7 [1576 kB] Get: 386 http://deb.debian.org/debian trixie/main armhf libwayland-server0 armhf 1.22.0-2.1+b1 [26.7 kB] Get: 387 http://deb.debian.org/debian trixie/main armhf libgbm1 armhf 23.3.5-1 [36.6 kB] Get: 388 http://deb.debian.org/debian trixie/main armhf libwayland-client0 armhf 1.22.0-2.1+b1 [20.4 kB] Get: 389 http://deb.debian.org/debian trixie/main armhf libegl-mesa0 armhf 23.3.5-1 [98.1 kB] Get: 390 http://deb.debian.org/debian trixie/main armhf libegl1 armhf 1.7.0-1 [28.7 kB] Get: 391 http://deb.debian.org/debian trixie/main armhf libgles2 armhf 1.7.0-1 [17.4 kB] Get: 392 http://deb.debian.org/debian trixie/main armhf x11-common all 1:7.7+23 [252 kB] Get: 393 http://deb.debian.org/debian trixie/main armhf libice6 armhf 2:1.0.10-1 [51.9 kB] Get: 394 http://deb.debian.org/debian trixie/main armhf libevdev2 armhf 1.13.1+dfsg-1 [25.9 kB] Get: 395 http://deb.debian.org/debian trixie/main armhf libmtdev1 armhf 1.1.6-1+b1 [21.0 kB] Get: 396 http://deb.debian.org/debian trixie/main armhf libgudev-1.0-0 armhf 238-3 [12.5 kB] Get: 397 http://deb.debian.org/debian trixie/main armhf libwacom-common all 2.10.0-1 [62.4 kB] Get: 398 http://deb.debian.org/debian trixie/main armhf libwacom9 armhf 2.10.0-1 [19.5 kB] Get: 399 http://deb.debian.org/debian trixie/main armhf libinput-bin armhf 1.25.0-1 [22.9 kB] Get: 400 http://deb.debian.org/debian trixie/main armhf libinput10 armhf 1.25.0-1 [110 kB] Get: 401 http://deb.debian.org/debian trixie/main armhf libmd4c0 armhf 0.4.8-1+b1 [40.0 kB] Get: 402 http://deb.debian.org/debian trixie/main armhf libdbus-1-3 armhf 1.14.10-4 [180 kB] Get: 403 http://deb.debian.org/debian trixie/main armhf libqt5dbus5 armhf 5.15.10+dfsg-7 [190 kB] Get: 404 http://deb.debian.org/debian trixie/main armhf libqt5network5 armhf 5.15.10+dfsg-7 [597 kB] Get: 405 http://deb.debian.org/debian trixie/main armhf libsm6 armhf 2:1.2.3-1 [33.0 kB] Get: 406 http://deb.debian.org/debian trixie/main armhf libxcb-icccm4 armhf 0.4.1-1.1+b1 [25.7 kB] Get: 407 http://deb.debian.org/debian trixie/main armhf libxcb-util1 armhf 0.4.0-1+b1 [22.2 kB] Get: 408 http://deb.debian.org/debian trixie/main armhf libxcb-image0 armhf 0.4.0-2+b1 [21.1 kB] Get: 409 http://deb.debian.org/debian trixie/main armhf libxcb-keysyms1 armhf 0.4.0-1+b2 [15.8 kB] Get: 410 http://deb.debian.org/debian trixie/main armhf libxcb-render-util0 armhf 0.3.9-1+b1 [17.4 kB] Get: 411 http://deb.debian.org/debian trixie/main armhf libxcb-shape0 armhf 1.15-1 [106 kB] Get: 412 http://deb.debian.org/debian trixie/main armhf libxcb-xinerama0 armhf 1.15-1 [105 kB] Get: 413 http://deb.debian.org/debian trixie/main armhf libxcb-xinput0 armhf 1.15-1 [127 kB] Get: 414 http://deb.debian.org/debian trixie/main armhf libxcb-xkb1 armhf 1.15-1 [127 kB] Get: 415 http://deb.debian.org/debian trixie/main armhf xkb-data all 2.41-2 [795 kB] Get: 416 http://deb.debian.org/debian trixie/main armhf libxkbcommon0 armhf 1.6.0-1 [96.3 kB] Get: 417 http://deb.debian.org/debian trixie/main armhf libxkbcommon-x11-0 armhf 1.6.0-1 [14.1 kB] Get: 418 http://deb.debian.org/debian trixie/main armhf libqt5gui5 armhf 5.15.10+dfsg-7 [2649 kB] Get: 419 http://deb.debian.org/debian trixie/main armhf libavahi-common-data armhf 0.8-13+b1 [111 kB] Get: 420 http://deb.debian.org/debian trixie/main armhf libavahi-common3 armhf 0.8-13+b1 [40.1 kB] Get: 421 http://deb.debian.org/debian trixie/main armhf libavahi-client3 armhf 0.8-13+b1 [43.4 kB] Get: 422 http://deb.debian.org/debian trixie/main armhf libcups2 armhf 2.4.7-1+b1 [212 kB] Get: 423 http://deb.debian.org/debian trixie/main armhf libqt5widgets5 armhf 5.15.10+dfsg-7 [2104 kB] Get: 424 http://deb.debian.org/debian trixie/main armhf libqt5printsupport5 armhf 5.15.10+dfsg-7 [187 kB] Get: 425 http://deb.debian.org/debian trixie/main armhf libqscintilla2-qt5-15 armhf 2.14.1+dfsg-1+b1 [960 kB] Get: 426 http://deb.debian.org/debian trixie/main armhf libqt5sql5 armhf 5.15.10+dfsg-7 [109 kB] Get: 427 http://deb.debian.org/debian trixie/main armhf libqt5help5 armhf 5.15.10-6 [130 kB] Get: 428 http://deb.debian.org/debian trixie/main armhf libqt5xml5 armhf 5.15.10+dfsg-7 [110 kB] Get: 429 http://deb.debian.org/debian trixie/main armhf libogg0 armhf 1.3.5-3 [21.6 kB] Get: 430 http://deb.debian.org/debian trixie/main armhf libflac12 armhf 1.4.3+ds-2+b1 [154 kB] Get: 431 http://deb.debian.org/debian trixie/main armhf libmp3lame0 armhf 3.100-6+b2 [344 kB] Get: 432 http://deb.debian.org/debian trixie/main armhf libmpg123-0 armhf 1.32.5-1 [127 kB] Get: 433 http://deb.debian.org/debian trixie/main armhf libvorbis0a armhf 1.3.7-2 [79.0 kB] Get: 434 http://deb.debian.org/debian trixie/main armhf libvorbisenc2 armhf 1.3.7-2 [69.3 kB] Get: 435 http://deb.debian.org/debian trixie/main armhf libsndfile1 armhf 1.2.2-1 [181 kB] Get: 436 http://deb.debian.org/debian trixie/main armhf libspqr4 armhf 1:7.6.1+dfsg-1 [128 kB] Get: 437 http://deb.debian.org/debian trixie/main armhf libsundials-ida6 armhf 6.4.1+dfsg1-3+b3 [129 kB] Get: 438 http://deb.debian.org/debian trixie/main armhf libbtf2 armhf 1:7.6.1+dfsg-1 [24.0 kB] Get: 439 http://deb.debian.org/debian trixie/main armhf libklu2 armhf 1:7.6.1+dfsg-1 [81.8 kB] Get: 440 http://deb.debian.org/debian trixie/main armhf libevent-core-2.1-7 armhf 2.1.12-stable-8 [120 kB] Get: 441 http://deb.debian.org/debian trixie/main armhf libevent-pthreads-2.1-7 armhf 2.1.12-stable-8 [53.2 kB] Get: 442 http://deb.debian.org/debian trixie/main armhf libnl-3-200 armhf 3.7.0-0.3 [51.7 kB] Get: 443 http://deb.debian.org/debian trixie/main armhf libnl-route-3-200 armhf 3.7.0-0.3 [153 kB] Get: 444 http://deb.debian.org/debian trixie/main armhf libibverbs1 armhf 48.0-1.1 [54.4 kB] Get: 445 http://deb.debian.org/debian trixie/main armhf librdmacm1 armhf 48.0-1.1 [61.6 kB] Get: 446 http://deb.debian.org/debian trixie/main armhf libfabric1 armhf 1.17.0-3 [385 kB] Get: 447 http://deb.debian.org/debian trixie/main armhf libhwloc15 armhf 2.10.0-1+b1 [133 kB] Get: 448 http://deb.debian.org/debian trixie/main armhf libmunge2 armhf 0.5.15-4 [16.4 kB] Get: 449 http://deb.debian.org/debian trixie/main armhf libpciaccess0 armhf 0.17-3 [49.0 kB] Get: 450 http://deb.debian.org/debian trixie/main armhf libxnvctrl0 armhf 535.171.04-1 [12.8 kB] Get: 451 http://deb.debian.org/debian trixie/main armhf ocl-icd-libopencl1 armhf 2.3.2-1 [36.8 kB] Get: 452 http://deb.debian.org/debian trixie/main armhf libhwloc-plugins armhf 2.10.0-1+b1 [16.1 kB] Get: 453 http://deb.debian.org/debian trixie/main armhf libpmix2 armhf 5.0.1-4+b1 [544 kB] Get: 454 http://deb.debian.org/debian trixie/main armhf libopenmpi3 armhf 4.1.6-5 [1855 kB] Get: 455 http://deb.debian.org/debian trixie/main armhf libfftw3-mpi3 armhf 3.3.10-1+b1 [44.9 kB] Get: 456 http://deb.debian.org/debian trixie/main armhf libhdf5-openmpi-103-1 armhf 1.10.10+repack-3+b1 [1247 kB] Get: 457 http://deb.debian.org/debian trixie/main armhf libcombblas2.0.0 armhf 2.0.0-3+b1 [256 kB] Get: 458 http://deb.debian.org/debian trixie/main armhf libmetis5 armhf 5.1.0.dfsg-7+b1 [139 kB] Get: 459 http://deb.debian.org/debian trixie/main armhf libptscotch-7.0 armhf 7.0.4-1+b1 [675 kB] Get: 460 http://deb.debian.org/debian trixie/main armhf libsuperlu-dist8 armhf 8.2.1+dfsg1-1 [480 kB] Get: 461 http://deb.debian.org/debian trixie/main armhf libhypre-2.28.0 armhf 2.28.0-8 [1213 kB] Get: 462 http://deb.debian.org/debian trixie/main armhf openmpi-common all 4.1.6-5 [168 kB] Get: 463 http://deb.debian.org/debian trixie/main armhf openmpi-bin armhf 4.1.6-5 [194 kB] Get: 464 http://deb.debian.org/debian trixie/main armhf mpi-default-bin armhf 1.15 [2408 B] Get: 465 http://deb.debian.org/debian trixie/main armhf libscalapack-openmpi2.2 armhf 2.2.1-3+b1 [1238 kB] Get: 466 http://deb.debian.org/debian trixie/main armhf libmumps-5.6 armhf 5.6.2-2+b1 [1684 kB] Get: 467 http://deb.debian.org/debian trixie/main armhf libsuperlu6 armhf 6.0.1+dfsg1-1+b1 [139 kB] Get: 468 http://deb.debian.org/debian trixie/main armhf libumfpack6 armhf 1:7.6.1+dfsg-1 [267 kB] Get: 469 http://deb.debian.org/debian trixie/main armhf libpetsc-real3.19 armhf 3.19.6+dfsg1-2 [5947 kB] Get: 470 http://deb.debian.org/debian trixie/main armhf libsundials-nvecparallel-petsc6 armhf 6.4.1+dfsg1-3+b3 [55.9 kB] Get: 471 http://deb.debian.org/debian trixie/main armhf libsundials-sunmatrix4 armhf 6.4.1+dfsg1-3+b3 [90.5 kB] Get: 472 http://deb.debian.org/debian trixie/main armhf libsundials-sunlinsol3 armhf 6.4.1+dfsg1-3+b3 [162 kB] Get: 473 http://deb.debian.org/debian trixie/main armhf libtext-unidecode-perl all 1.30-3 [101 kB] Get: 474 http://deb.debian.org/debian trixie/main armhf texinfo-lib armhf 7.1-3 [205 kB] Get: 475 http://deb.debian.org/debian trixie/main armhf tex-common all 6.18 [32.5 kB] Get: 476 http://deb.debian.org/debian trixie/main armhf texinfo all 7.1-3 [1748 kB] Get: 477 http://deb.debian.org/debian trixie/main armhf octave-common all 8.4.0-1 [6368 kB] Get: 478 http://deb.debian.org/debian trixie/main armhf octave armhf 8.4.0-1+b1 [8429 kB] Get: 479 http://deb.debian.org/debian trixie/main armhf libncurses6 armhf 6.4+20240113-1 [81.8 kB] Get: 480 http://deb.debian.org/debian trixie/main armhf libncurses-dev armhf 6.4+20240113-1 [309 kB] Get: 481 http://deb.debian.org/debian trixie/main armhf libreadline-dev armhf 8.2-3+b1 [137 kB] Get: 482 http://deb.debian.org/debian trixie/main armhf libhdf5-fortran-102 armhf 1.10.10+repack-3+b1 [78.5 kB] Get: 483 http://deb.debian.org/debian trixie/main armhf libhdf5-hl-100 armhf 1.10.10+repack-3+b1 [61.1 kB] Get: 484 http://deb.debian.org/debian trixie/main armhf libhdf5-hl-fortran-100 armhf 1.10.10+repack-3+b1 [34.7 kB] Get: 485 http://deb.debian.org/debian trixie/main armhf libhdf5-cpp-103-1 armhf 1.10.10+repack-3+b1 [121 kB] Get: 486 http://deb.debian.org/debian trixie/main armhf libhdf5-hl-cpp-100 armhf 1.10.10+repack-3+b1 [20.8 kB] Get: 487 http://deb.debian.org/debian trixie/main armhf zlib1g-dev armhf 1:1.3.dfsg-3+b1 [904 kB] Get: 488 http://deb.debian.org/debian trixie/main armhf libjpeg62-turbo-dev armhf 1:2.1.5-2+b2 [260 kB] Get: 489 http://deb.debian.org/debian trixie/main armhf libjpeg-dev armhf 1:2.1.5-2+b2 [72.1 kB] Get: 490 http://deb.debian.org/debian trixie/main armhf libaec-dev armhf 1.1.3-1 [18.8 kB] Get: 491 http://deb.debian.org/debian trixie/main armhf libcurl4-openssl-dev armhf 8.5.0-2 [495 kB] Get: 492 http://deb.debian.org/debian trixie/main armhf libssl-dev armhf 3.1.5-1 [2152 kB] Get: 493 http://deb.debian.org/debian trixie/main armhf hdf5-helpers armhf 1.10.10+repack-3+b1 [23.5 kB] Get: 494 http://deb.debian.org/debian trixie/main armhf libhdf5-dev armhf 1.10.10+repack-3+b1 [2611 kB] Get: 495 http://deb.debian.org/debian trixie/main armhf xorg-sgml-doctools all 1:1.11-1.1 [22.1 kB] Get: 496 http://deb.debian.org/debian trixie/main armhf x11proto-dev all 2023.2-1 [598 kB] Get: 497 http://deb.debian.org/debian trixie/main armhf libxau-dev armhf 1:1.0.9-1 [22.4 kB] Get: 498 http://deb.debian.org/debian trixie/main armhf libxdmcp-dev armhf 1:1.1.2-3 [40.7 kB] Get: 499 http://deb.debian.org/debian trixie/main armhf xtrans-dev all 1.4.0-1 [98.7 kB] Get: 500 http://deb.debian.org/debian trixie/main armhf libpthread-stubs0-dev armhf 0.4-1 [5344 B] Get: 501 http://deb.debian.org/debian trixie/main armhf libxcb1-dev armhf 1.15-1 [179 kB] Get: 502 http://deb.debian.org/debian trixie/main armhf libx11-dev armhf 2:1.8.7-1 [816 kB] Get: 503 http://deb.debian.org/debian trixie/main armhf libglx-dev armhf 1.7.0-1 [15.5 kB] Get: 504 http://deb.debian.org/debian trixie/main armhf libgl-dev armhf 1.7.0-1 [100 kB] Get: 505 http://deb.debian.org/debian trixie/main armhf libblas-dev armhf 3.12.0-3 [119 kB] Get: 506 http://deb.debian.org/debian trixie/main armhf liblapack-dev armhf 3.12.0-3 [1903 kB] Get: 507 http://deb.debian.org/debian trixie/main armhf libfftw3-bin armhf 3.3.10-1+b1 [41.0 kB] Get: 508 http://deb.debian.org/debian trixie/main armhf libfftw3-dev armhf 3.3.10-1+b1 [834 kB] Get: 509 http://deb.debian.org/debian trixie/main armhf libgfortran-13-dev armhf 13.2.0-13 [306 kB] Get: 510 http://deb.debian.org/debian trixie/main armhf gfortran-13-arm-linux-gnueabihf armhf 13.2.0-13 [8193 kB] Get: 511 http://deb.debian.org/debian trixie/main armhf gfortran-13 armhf 13.2.0-13 [10.5 kB] Get: 512 http://deb.debian.org/debian trixie/main armhf gfortran-arm-linux-gnueabihf armhf 4:13.2.0-7 [1288 B] Get: 513 http://deb.debian.org/debian trixie/main armhf gfortran armhf 4:13.2.0-7 [1432 B] Get: 514 http://deb.debian.org/debian trixie/main armhf octave-dev armhf 8.4.0-1+b1 [951 kB] Get: 515 http://deb.debian.org/debian trixie/main armhf dh-octave all 1.8.0 [22.7 kB] Get: 516 http://deb.debian.org/debian trixie/main armhf octave-io armhf 2.6.4-3+b1 [198 kB] Fetched 181 MB in 5s (36.3 MB/s) debconf: delaying package configuration, since apt-utils is not installed Selecting previously unselected package libpython3.11-minimal:armhf. (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 ... 19637 files and directories currently installed.) Preparing to unpack .../libpython3.11-minimal_3.11.8-1_armhf.deb ... Unpacking libpython3.11-minimal:armhf (3.11.8-1) ... Selecting previously unselected package libexpat1:armhf. Preparing to unpack .../libexpat1_2.5.0-2+b2_armhf.deb ... Unpacking libexpat1:armhf (2.5.0-2+b2) ... Selecting previously unselected package python3.11-minimal. 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Selecting previously unselected package python3.11. Preparing to unpack .../7-python3.11_3.11.8-1_armhf.deb ... Unpacking python3.11 (3.11.8-1) ... Selecting previously unselected package libpython3-stdlib:armhf. Preparing to unpack .../8-libpython3-stdlib_3.11.6-1_armhf.deb ... Unpacking libpython3-stdlib:armhf (3.11.6-1) ... Setting up python3-minimal (3.11.6-1) ... Selecting previously unselected package python3. (Reading database ... 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Unpacking libsub-exporter-progressive-perl (0.001013-3) ... Selecting previously unselected package libvariable-magic-perl. Preparing to unpack .../194-libvariable-magic-perl_0.63-1+b2_armhf.deb ... Unpacking libvariable-magic-perl (0.63-1+b2) ... Selecting previously unselected package libb-hooks-endofscope-perl. Preparing to unpack .../195-libb-hooks-endofscope-perl_0.28-1_all.deb ... Unpacking libb-hooks-endofscope-perl (0.28-1) ... Selecting previously unselected package libsub-identify-perl. Preparing to unpack .../196-libsub-identify-perl_0.14-3+b1_armhf.deb ... Unpacking libsub-identify-perl (0.14-3+b1) ... Selecting previously unselected package libsub-name-perl:armhf. Preparing to unpack .../197-libsub-name-perl_0.27-1+b1_armhf.deb ... Unpacking libsub-name-perl:armhf (0.27-1+b1) ... Selecting previously unselected package libnamespace-clean-perl. Preparing to unpack .../198-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 .../199-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 .../200-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 .../201-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 .../202-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. 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Selecting previously unselected package libcpanel-json-xs-perl:armhf. Preparing to unpack .../220-libcpanel-json-xs-perl_4.37-1+b1_armhf.deb ... Unpacking libcpanel-json-xs-perl:armhf (4.37-1+b1) ... Selecting previously unselected package libaliased-perl. Preparing to unpack .../221-libaliased-perl_0.34-3_all.deb ... Unpacking libaliased-perl (0.34-3) ... Selecting previously unselected package libclass-data-inheritable-perl. Preparing to unpack .../222-libclass-data-inheritable-perl_0.08-3_all.deb ... Unpacking libclass-data-inheritable-perl (0.08-3) ... Selecting previously unselected package libdevel-stacktrace-perl. Preparing to unpack .../223-libdevel-stacktrace-perl_2.0500-1_all.deb ... Unpacking libdevel-stacktrace-perl (2.0500-1) ... Selecting previously unselected package libexception-class-perl. Preparing to unpack .../224-libexception-class-perl_1.45-1_all.deb ... Unpacking libexception-class-perl (1.45-1) ... Selecting previously unselected package libiterator-perl. 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Selecting previously unselected package libemail-address-xs-perl. Preparing to unpack .../236-libemail-address-xs-perl_1.05-1+b2_armhf.deb ... Unpacking libemail-address-xs-perl (1.05-1+b2) ... Selecting previously unselected package libipc-system-simple-perl. Preparing to unpack .../237-libipc-system-simple-perl_1.30-2_all.deb ... Unpacking libipc-system-simple-perl (1.30-2) ... Selecting previously unselected package libfile-basedir-perl. Preparing to unpack .../238-libfile-basedir-perl_0.09-2_all.deb ... Unpacking libfile-basedir-perl (0.09-2) ... Selecting previously unselected package libfile-find-rule-perl. Preparing to unpack .../239-libfile-find-rule-perl_0.34-3_all.deb ... Unpacking libfile-find-rule-perl (0.34-3) ... Selecting previously unselected package libio-string-perl. Preparing to unpack .../240-libio-string-perl_1.08-4_all.deb ... Unpacking libio-string-perl (1.08-4) ... Selecting previously unselected package libfont-ttf-perl. 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Selecting previously unselected package libterm-readkey-perl. Preparing to unpack .../263-libterm-readkey-perl_2.38-2+b2_armhf.deb ... Unpacking libterm-readkey-perl (2.38-2+b2) ... Selecting previously unselected package libtext-levenshteinxs-perl. Preparing to unpack .../264-libtext-levenshteinxs-perl_0.03-5+b2_armhf.deb ... Unpacking libtext-levenshteinxs-perl (0.03-5+b2) ... Selecting previously unselected package libmarkdown2:armhf. Preparing to unpack .../265-libmarkdown2_2.2.7-2+b1_armhf.deb ... Unpacking libmarkdown2:armhf (2.2.7-2+b1) ... Selecting previously unselected package libtext-markdown-discount-perl. Preparing to unpack .../266-libtext-markdown-discount-perl_0.16-1+b1_armhf.deb ... Unpacking libtext-markdown-discount-perl (0.16-1+b1) ... Selecting previously unselected package libdata-messagepack-perl. Preparing to unpack .../267-libdata-messagepack-perl_1.02-1+b2_armhf.deb ... Unpacking libdata-messagepack-perl (1.02-1+b2) ... Selecting previously unselected package libtext-xslate-perl:armhf. Preparing to unpack .../268-libtext-xslate-perl_3.5.9-1+b3_armhf.deb ... Unpacking libtext-xslate-perl:armhf (3.5.9-1+b3) ... Selecting previously unselected package libtime-duration-perl. Preparing to unpack .../269-libtime-duration-perl_1.21-2_all.deb ... Unpacking libtime-duration-perl (1.21-2) ... Selecting previously unselected package libtime-moment-perl. Preparing to unpack .../270-libtime-moment-perl_0.44-2+b2_armhf.deb ... Unpacking libtime-moment-perl (0.44-2+b2) ... Selecting previously unselected package libunicode-utf8-perl. Preparing to unpack .../271-libunicode-utf8-perl_0.62-2+b1_armhf.deb ... Unpacking libunicode-utf8-perl (0.62-2+b1) ... Selecting previously unselected package libcgi-pm-perl. Preparing to unpack .../272-libcgi-pm-perl_4.64-1_all.deb ... Unpacking libcgi-pm-perl (4.64-1) ... Selecting previously unselected package libhtml-form-perl. 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Setting up libabsl20220623:armhf (20220623.1-3) ... Setting up libxau6:armhf (1:1.0.9-1) ... Setting up libdouble-conversion3:armhf (3.3.0-1+b1) ... Setting up libpsl5:armhf (0.21.2-1+b1) ... Setting up libunicode-utf8-perl (0.62-2+b1) ... Setting up libfftw3-single3:armhf (3.3.10-1+b1) ... Setting up libset-intspan-perl (1.19-3) ... Setting up libicu72:armhf (72.1-4+b1) ... Setting up libmpg123-0:armhf (1.32.5-1) ... Setting up libogg0:armhf (1.3.5-3) ... Setting up libmouse-perl (2.5.10-1+b4) ... Setting up liblerc4:armhf (4.0.0+ds-4+b1) ... Setting up libpod-pom-perl (2.01-4) ... Setting up bsdextrautils (2.39.3-6) ... Setting up hdf5-helpers (1.10.10+repack-3+b1) ... Setting up libwmflite-0.2-7:armhf (0.2.13-1.1) ... Setting up libregexp-pattern-perl (0.2.14-2) ... Setting up libdata-messagepack-perl (1.02-1+b2) ... Setting up libdynaloader-functions-perl (0.003-3) ... Setting up libdatrie1:armhf (0.2.13-3) ... Setting up libtext-glob-perl (0.11-3) ... Setting up libclass-method-modifiers-perl (2.15-1) ... Setting up liblist-compare-perl (0.55-2) ... Setting up libmagic-mgc (1:5.45-2+b1) ... Setting up libcbor0.10:armhf (0.10.2-1.1) ... Setting up libclone-perl:armhf (0.46-1+b1) ... Setting up libarchive-zip-perl (1.68-1) ... Setting up libyaml-0-2:armhf (0.2.5-1) ... Setting up libsub-identify-perl (0.14-3+b1) ... Setting up libglib2.0-0:armhf (2.78.4-1) ... No schema files found: doing nothing. Setting up libcpanel-json-xs-perl:armhf (4.37-1+b1) ... Setting up libglvnd0:armhf (1.7.0-1) ... Setting up libio-stringy-perl (2.111-3) ... Setting up libhtml-tagset-perl (3.24-1) ... Setting up liblog-any-perl (1.717-1) ... Setting up libqscintilla2-qt5-l10n (2.14.1+dfsg-1) ... Setting up libyaml-pp-perl (0.38.0-1) ... Setting up libdevel-size-perl (0.83-2+b2) ... Setting up unzip (6.0-28) ... Setting up libdebhelper-perl (13.15.3) ... Setting up libbrotli1:armhf (1.1.0-2+b3) ... Setting up libregexp-pattern-license-perl (3.11.0-1) ... Setting up libconvert-binhex-perl (1.125-3) ... Setting up liblwp-mediatypes-perl (6.04-2) ... Setting up libyaml-libyaml-perl (0.89+ds-1) ... Setting up fonts-freefont-otf (20211204+svn4273-2) ... Setting up libio-interactive-perl (1.025-1) ... Setting up x11-common (1:7.7+23) ... invoke-rc.d: could not determine current runlevel Setting up X socket directories... /tmp/.X11-unix /tmp/.ICE-unix. Setting up libtry-tiny-perl (0.31-2) ... Setting up libsensors-config (1:3.6.0-9) ... Setting up libcxsparse4:armhf (1:7.6.1+dfsg-1) ... Setting up libnghttp2-14:armhf (1.59.0-1) ... Setting up libmagic1:armhf (1:5.45-2+b1) ... Setting up libdeflate0:armhf (1.20-1) ... Setting up perl-openssl-defaults:armhf (7+b1) ... Setting up libmldbm-perl (2.05-4) ... Setting up libxml-namespacesupport-perl (1.12-2) ... 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:armhf (2020.2-6+b1) ... Setting up xkb-data (2.41-2) ... Setting up liblzo2-2:armhf (2.10-2+b1) ... Setting up libtime-moment-perl (0.44-2+b2) ... Setting up libencode-locale-perl (1.05-3) ... Setting up libhwy1:armhf (1.0.7-8+b1) ... Setting up libmetis5:armhf (5.1.0.dfsg-7+b1) ... Setting up libsvtav1enc1d1:armhf (1.7.0+dfsg-2+b1) ... Setting up file (1:5.45-2+b1) ... Setting up texinfo-lib (7.1-3) ... Setting up libassuan0:armhf (2.5.6-1) ... Setting up libconfig-tiny-perl (2.30-1) ... Setting up libsereal-encoder-perl (5.004+ds-1+b1) ... Setting up liblist-utilsby-perl (0.12-2) ... Setting up libyaml-tiny-perl (1.74-1) ... Setting up libpthread-stubs0-dev:armhf (0.4-1) ... Setting up libjbig0:armhf (2.1-6.1+b1) ... Setting up octave-common (8.4.0-1) ... Setting up libregexp-common-perl (2017060201-3) ... Setting up librav1e0:armhf (0.7.1-2) ... Setting up libpcre2-16-0:armhf (10.42-4+b1) ... Setting up libaec0:armhf (1.1.3-1) ... Setting up libnet-netmask-perl (2.0002-2) ... Setting up libopengl0:armhf (1.7.0-1) ... Setting up libsub-install-perl (0.929-1) ... Setting up libindirect-perl (0.39-2+b2) ... Setting up libxs-parse-sublike-perl:armhf (0.21-2+b1) ... Setting up libnumber-compare-perl (0.03-3) ... Setting up libsasl2-modules-db:armhf (2.1.28+dfsg1-4+b1) ... Setting up tzdata (2024a-1) ... Current default time zone: 'Etc/UTC' Local time is now: Thu Apr 4 00:21:34 UTC 2024. Universal Time is now: Thu Apr 4 00:21:34 UTC 2024. Run 'dpkg-reconfigure tzdata' if you wish to change it. Setting up liberror-perl (0.17029-2) ... Setting up libasound2-data (1.2.10-3) ... Setting up libbtf2:armhf (1:7.6.1+dfsg-1) ... Setting up libjson-maybexs-perl (1.004005-1) ... Setting up libxml-sax-base-perl (1.09-3) ... Setting up libio-string-perl (1.08-4) ... Setting up libboolean-perl (0.46-3) ... Setting up libnetaddr-ip-perl (4.079+dfsg-2+b2) ... Setting up xtrans-dev (1.4.0-1) ... Setting up autotools-dev (20220109.1) ... Setting up libz3-4:armhf (4.8.12-3.1+b2) ... Setting up libblas3:armhf (3.12.0-3) ... update-alternatives: using /usr/lib/arm-linux-gnueabihf/blas/libblas.so.3 to provide /usr/lib/arm-linux-gnueabihf/libblas.so.3 (libblas.so.3-arm-linux-gnueabihf) in auto mode Setting up libclass-data-inheritable-perl (0.08-3) ... Setting up libxs-parse-keyword-perl (0.39-1+b1) ... Setting up libflac12:armhf (1.4.3+ds-2+b1) ... Setting up libalgorithm-c3-perl (0.11-2) ... Setting up libgles2:armhf (1.7.0-1) ... Setting up libmunge2:armhf (0.5.15-4) ... Setting up liblog-log4perl-perl (1.57-1) ... Setting up libtext-reform-perl (1.20-5) ... Setting up libjpeg62-turbo:armhf (1:2.1.5-2+b2) ... Setting up libx11-data (2:1.8.7-1) ... Setting up libjpeg62-turbo-dev:armhf (1:2.1.5-2+b2) ... Setting up libfile-find-rule-perl (0.34-3) ... Setting up librtmp1:armhf (2.4+20151223.gitfa8646d.1-2+b2) ... Setting up libipc-system-simple-perl (1.30-2) ... Setting up libio-tiecombine-perl (1.005-3) ... Setting up libnet-domain-tld-perl (1.75-3) ... Setting up libperlio-utf8-strict-perl (0.010-1+b1) ... Setting up aglfn (1.7+git20191031.4036a9c-2) ... Setting up libavahi-common-data:armhf (0.8-13+b1) ... Setting up libncurses6:armhf (6.4+20240113-1) ... Setting up libdbus-1-3:armhf (1.14.10-4) ... Setting up libfribidi0:armhf (1.0.13-3+b1) ... Setting up libopus0:armhf (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:armhf (3.1.5-1) ... Setting up libpng16-16:armhf (1.6.43-1) ... Setting up libhwloc15:armhf (2.10.0-1+b1) ... Setting up libevent-core-2.1-7:armhf (2.1.12-stable-8) ... Setting up libvorbis0a:armhf (1.3.7-2) ... Setting up libvariable-magic-perl (0.63-1+b2) ... Setting up libio-html-perl (1.004-3) ... Setting up libtext-template-perl (1.61-1) ... Setting up libpod-parser-perl (1.67-1) ... Setting up autopoint (0.21-14) ... Setting up libb-hooks-op-check-perl:armhf (0.22-2+b2) ... Setting up fonts-dejavu-core (2.37-8) ... Setting up libgav1-1:armhf (0.18.0-1+b1) ... Setting up liblist-moreutils-xs-perl (0.430-3+b2) ... Setting up libsensors5:armhf (1:3.6.0-9) ... Setting up libjxl0.7:armhf (0.7.0-10.2+b1) ... Setting up libltdl7:armhf (2.4.7-7) ... Setting up libfftw3-double3:armhf (3.3.10-1+b1) ... Setting up libglapi-mesa:armhf (23.3.5-1) ... Setting up libparams-util-perl (1.102-2+b2) ... Setting up libsasl2-2:armhf (2.1.28+dfsg1-4+b1) ... Setting up libgfortran5:armhf (14-20240201-3) ... Setting up libmtdev1:armhf (1.1.6-1+b1) ... Setting up libvulkan1:armhf (1.3.275.0-1) ... Setting up libtime-duration-perl (1.21-2) ... Setting up autoconf (2.71-3) ... Setting up libtext-xslate-perl:armhf (3.5.9-1+b3) ... Setting up libsub-exporter-progressive-perl (0.001013-3) ... Setting up libwebp7:armhf (1.3.2-0.4) ... Setting up libarray-intspan-perl (2.004-2) ... Setting up libcapture-tiny-perl (0.48-2) ... Setting up libtimedate-perl (2.3300-2) ... Setting up libexporter-lite-perl (0.09-2) ... Setting up libsub-name-perl:armhf (0.27-1+b1) ... Setting up zlib1g-dev:armhf (1:1.3.dfsg-3+b1) ... Setting up libsyntax-keyword-try-perl (0.29-1+b1) ... Setting up libdata-validate-domain-perl (0.10-1.1) ... Setting up libproc-processtable-perl:armhf (0.636-1+b1) ... Setting up libparse-recdescent-perl (1.967015+dfsg-4) ... Setting up libdav1d7:armhf (1.4.1-1) ... Setting up sensible-utils (0.0.22) ... Setting up ocl-icd-libopencl1:armhf (2.3.2-1) ... Setting up libxshmfence1:armhf (1.3-1) ... Setting up libtiff6:armhf (4.5.1+git230720-4) ... Setting up libpath-tiny-perl (0.144-1) ... Setting up libuchardet0:armhf (0.0.8-1+b1) ... Setting up lzop (1.04-2) ... Setting up libjson-perl (4.10000-1) ... Setting up libasound2:armhf (1.2.10-3) ... Setting up liblog-any-adapter-screen-perl (0.140-2) ... Setting up libnl-3-200:armhf (3.7.0-0.3) ... Setting up librole-tiny-perl (2.002004-1) ... Setting up openmpi-common (4.1.6-5) ... Setting up libipc-run3-perl (0.049-1) ... Setting up libmd4c0:armhf (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:armhf (1:7.6.1+dfsg-1) ... Setting up liblua5.4-0:armhf (5.4.6-3) ... Setting up libsub-override-perl (0.10-1) ... Setting up libaliased-perl (0.34-3) ... Setting up libthai-data (0.1.29-2) ... Setting up libssh2-1:armhf (1.11.0-4) ... Setting up xorg-sgml-doctools (1:1.11-1.1) ... Setting up netbase (6.4) ... Setting up libstrictures-perl (2.000006-1) ... Setting up libsub-quote-perl (2.006008-1) ... Setting up libdevel-stacktrace-perl (2.0500-1) ... Setting up libclass-xsaccessor-perl (1.19-4+b2) ... Setting up libtext-autoformat-perl (1.750000-2) ... Setting up libglu1-mesa:armhf (9.0.2-1.1) ... Setting up libtoml-tiny-perl (0.16-1) ... Setting up libsort-versions-perl (1.62-3) ... Setting up libexporter-tiny-perl (1.006002-1) ... Setting up libterm-readkey-perl (2.38-2+b2) ... Setting up libfido2-1:armhf (1.14.0-1) ... Setting up libtext-unidecode-perl (1.30-3) ... Setting up libde265-0:armhf (1.0.15-1) ... Setting up libfont-ttf-perl (1.06-2) ... Setting up libfile-homedir-perl (1.006-2) ... Setting up libgfortran-13-dev:armhf (13.2.0-13) ... Setting up libsamplerate0:armhf (0.2.2-4) ... Setting up openssl (3.1.5-1) ... Setting up libwebpmux3:armhf (1.3.2-0.4) ... Setting up libbsd0:armhf (0.12.2-1) ... Setting up libtext-levenshteinxs-perl (0.03-5+b2) ... Setting up libperlio-gzip-perl (0.20-1+b2) ... Setting up libdrm-common (2.4.120-2) ... Setting up libyuv0:armhf (0.0~git202401110.af6ac82-1) ... Setting up libelf1:armhf (0.190-1+b1) ... Setting up libevdev2:armhf (1.13.1+dfsg-1) ... Setting up readline-common (8.2-3) ... Setting up libxml2:armhf (2.9.14+dfsg-1.3+b2) ... Setting up libhtml-html5-entities-perl (0.004-3) ... Setting up libtext-levenshtein-damerau-perl (0.41-3) ... Setting up libsereal-decoder-perl (5.004+ds-1+b1) ... Setting up libmarkdown2:armhf (2.2.7-2+b1) ... Setting up liburi-perl (5.27-1) ... Setting up iso-codes (4.16.0-1) ... Setting up libnet-ipv6addr-perl (1.02-1) ... Setting up libgudev-1.0-0:armhf (238-3) ... Setting up libmp3lame0:armhf (3.100-6+b2) ... Setting up libblas-dev:armhf (3.12.0-3) ... update-alternatives: using /usr/lib/arm-linux-gnueabihf/blas/libblas.so to provide /usr/lib/arm-linux-gnueabihf/libblas.so (libblas.so-arm-linux-gnueabihf) in auto mode Setting up libsz2:armhf (1.1.3-1) ... Setting up libvorbisenc2:armhf (1.3.7-2) ... Setting up libevent-pthreads-2.1-7:armhf (2.1.12-stable-8) ... Setting up libdata-validate-ip-perl (0.31-1) ... Setting up libwacom-common (2.10.0-1) ... Setting up libmousex-nativetraits-perl (1.09-3) ... Setting up libemail-address-xs-perl (1.05-1+b2) ... Setting up libxkbcommon0:armhf (1.6.0-1) ... Setting up libwayland-client0:armhf (1.22.0-2.1+b1) ... Setting up libnet-ssleay-perl:armhf (1.94-1) ... Setting up automake (1:1.16.5-1.3) ... update-alternatives: using /usr/bin/automake-1.16 to provide /usr/bin/automake (automake) in auto mode Setting up x11proto-dev (2023.2-1) ... Setting up libfile-stripnondeterminism-perl (1.13.1-1) ... Setting up gfortran-13-arm-linux-gnueabihf (13.2.0-13) ... Setting up gnuplot-data (6.0.0+dfsg1-1) ... Setting up libice6:armhf (2:1.0.10-1) ... Setting up libhttp-date-perl (6.06-1) ... Setting up libavif16:armhf (1.0.4-1) ... Setting up libxdmcp6:armhf (1:1.1.2-3) ... Setting up liblapack3:armhf (3.12.0-3) ... update-alternatives: using /usr/lib/arm-linux-gnueabihf/lapack/liblapack.so.3 to provide /usr/lib/arm-linux-gnueabihf/liblapack.so.3 (liblapack.so.3-arm-linux-gnueabihf) in auto mode Setting up libncurses-dev:armhf (6.4+20240113-1) ... Setting up libxcb1:armhf (1.15-1) ... Setting up libfile-basedir-perl (0.09-2) ... Setting up gettext (0.21-14+b1) ... Setting up libfeature-compat-try-perl (0.05-1) ... Setting up libxcb-xfixes0:armhf (1.15-1) ... Setting up libamd3:armhf (1:7.6.1+dfsg-1) ... Setting up libfile-listing-perl (6.16-1) ... Setting up libxau-dev:armhf (1:1.0.9-1) ... Setting up libxcb-xinput0:armhf (1.15-1) ... Setting up libtool (2.4.7-7) ... Setting up libcolamd3:armhf (1:7.6.1+dfsg-1) ... Setting up libxcb-render0:armhf (1.15-1) ... Setting up libfftw3-bin (3.3.10-1+b1) ... Setting up libwacom9:armhf (2.10.0-1) ... Setting up fontconfig-config (2.15.0-1.1) ... Setting up liblist-moreutils-perl (0.430-2) ... Setting up libxcb-glx0:armhf (1.15-1) ... Setting up libpod-constants-perl (0.19-2) ... Setting up libedit2:armhf (3.1-20230828-1) ... Setting up libreadline8:armhf (8.2-3+b1) ... Setting up libhash-merge-perl (0.302-1) ... Setting up libxcb-keysyms1:armhf (0.4.0-1+b2) ... Setting up libsoftware-copyright-perl (0.012-2) ... Setting up libaec-dev:armhf (1.1.3-1) ... Setting up libarpack2:armhf (3.9.1-1+b1) ... Setting up libxcb-shape0:armhf (1.15-1) ... Setting up libavahi-common3:armhf (0.8-13+b1) ... Setting up libjpeg-dev:armhf (1:2.1.5-2+b2) ... Setting up libnet-http-perl (6.23-1) ... Setting up libpath-iterator-rule-perl (1.015-2) ... Setting up libtext-markdown-discount-perl (0.16-1+b1) ... Setting up libxcb-render-util0:armhf (0.3.9-1+b1) ... Setting up libxcb-shm0:armhf (1.15-1) ... Setting up libexception-class-perl (1.45-1) ... Setting up libxcb-icccm4:armhf (0.4.1-1.1+b1) ... Setting up libsundials-sunmatrix4:armhf (6.4.1+dfsg1-3+b3) ... Setting up libclass-c3-perl (0.35-2) ... Setting up libsuperlu6:armhf (6.0.1+dfsg1-1+b1) ... Setting up libreadline-dev:armhf (8.2-3+b1) ... Setting up libqrupdate1:armhf (1.1.2-4+b1) ... Setting up libdevel-callchecker-perl:armhf (0.008-2+b1) ... Setting up libldap-2.5-0:armhf (2.5.13+dfsg-5+b3) ... Setting up libsundials-ida6:armhf (6.4.1+dfsg1-3+b3) ... Setting up libcamd3:armhf (1:7.6.1+dfsg-1) ... Setting up libxcb-util1:armhf (0.4.0-1+b1) ... Setting up gfortran-arm-linux-gnueabihf (4:13.2.0-7) ... Setting up libinput-bin (1.25.0-1) ... Setting up libxcb-xkb1:armhf (1.15-1) ... Setting up libxcb-image0:armhf (0.4.0-2+b1) ... Setting up intltool-debian (0.35.0+20060710.6) ... Setting up libnl-route-3-200:armhf (3.7.0-0.3) ... Setting up libobject-pad-perl (0.808-1+b1) ... Setting up libxcb-present0:armhf (1.15-1) ... Setting up dh-autoreconf (20) ... Setting up patchutils (0.4.2-1) ... Setting up libthai0:armhf (0.1.29-2) ... Setting up ca-certificates (20240203) ... Updating certificates in /etc/ssl/certs... 146 added, 0 removed; done. Setting up libxdmcp-dev:armhf (1:1.1.2-3) ... Setting up libdata-validate-uri-perl (0.07-3) ... Setting up libxcb-xinerama0:armhf (1.15-1) ... Setting up libtest-exception-perl (0.43-3) ... Setting up libfreetype6:armhf (2.13.2+dfsg-1+b1) ... Setting up libglpk40:armhf (5.0-1+b1) ... Setting up libstring-copyright-perl (0.003014-1) ... Setting up libxcb-sync1:armhf (1.15-1) ... Setting up gfortran-13 (13.2.0-13) ... Setting up shared-mime-info (2.4-1) ... Setting up libxkbcommon-x11-0:armhf (1.6.0-1) ... Setting up liblapack-dev:armhf (3.12.0-3) ... update-alternatives: using /usr/lib/arm-linux-gnueabihf/lapack/liblapack.so to provide /usr/lib/arm-linux-gnueabihf/liblapack.so (liblapack.so-arm-linux-gnueabihf) in auto mode Setting up libdata-optlist-perl (0.114-1) ... Setting up ucf (3.0043+nmu1) ... Setting up libqt5core5a:armhf (5.15.10+dfsg-7) ... Setting up libccolamd3:armhf (1:7.6.1+dfsg-1) ... Setting up libxcb-dri2-0:armhf (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:armhf (1.9.21~dfsg-3+b1) ... Setting up libdrm2:armhf (2.4.120-2) ... Setting up dwz (0.15-1) ... Setting up groff-base (1.23.0-3) ... Setting up libqt5dbus5:armhf (5.15.10+dfsg-7) ... Setting up libxcb-randr0:armhf (1.15-1) ... Setting up libhtml-parser-perl:armhf (3.81-1+b1) ... Setting up gpgconf (2.2.40-1.1+b1) ... Setting up libcurl4:armhf (8.5.0-2) ... Setting up libx11-6:armhf (2:1.8.7-1) ... Setting up libharfbuzz0b:armhf (8.3.0-2) ... Setting up libfontconfig1:armhf (2.15.0-1.1) ... Setting up libsndfile1:armhf (1.2.2-1) ... Setting up libmro-compat-perl (0.15-2) ... Setting up libllvm17:armhf (1:17.0.6-5) ... Setting up libsm6:armhf (2:1.2.3-1) ... Setting up libfftw3-dev:armhf (3.3.10-1+b1) ... Setting up libavahi-client3:armhf (0.8-13+b1) ... Setting up libio-socket-ssl-perl (2.085-1) ... Setting up gpg (2.2.40-1.1+b1) ... Setting up libsub-exporter-perl (0.990-1) ... Setting up libhttp-message-perl (6.45-1) ... Setting up libdrm-amdgpu1:armhf (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:armhf (1.15-1) ... Setting up libinput10:armhf (1.25.0-1) ... Setting up libportaudio2:armhf (19.6.0-1.2+b1) ... Setting up libx11-xcb1:armhf (2:1.8.7-1) ... Setting up libhttp-negotiate-perl (6.01-2) ... Setting up libibverbs1:armhf (48.0-1.1) ... Setting up fontconfig (2.15.0-1.1) ... Regenerating fonts cache... done. Setting up libcarp-assert-more-perl (2.4.0-1) ... Setting up libcholmod5:armhf (1:7.6.1+dfsg-1) ... Setting up libdrm-nouveau2:armhf (2.4.120-2) ... Setting up libxcb1-dev:armhf (1.15-1) ... Setting up libxpm4:armhf (1:3.5.17-1) ... Setting up libiterator-util-perl (0.02+ds1-2) ... Setting up libxrender1:armhf (1:0.9.10-1.1) ... Setting up libgbm1:armhf (23.3.5-1) ... Setting up libhttp-cookies-perl (6.11-1) ... Setting up libspqr4:armhf (1:7.6.1+dfsg-1) ... Setting up libdrm-radeon1:armhf (2.4.120-2) ... Setting up openssh-client (1:9.6p1-4) ... Setting up po-debconf (1.0.21+nmu1) ... Setting up libhtml-tree-perl (5.07-3) ... Setting up libpython3.11-stdlib:armhf (3.11.8-1) ... Setting up libparams-classify-perl:armhf (0.015-2+b2) ... Setting up libpango-1.0-0:armhf (1.52.0+ds-1) ... Setting up libcgi-pm-perl (4.64-1) ... Setting up libgl1-mesa-dri:armhf (23.3.5-1) ... Setting up libx11-dev:armhf (2:1.8.7-1) ... Setting up libxext6:armhf (2:1.3.4-1+b1) ... Setting up libcurl3-gnutls:armhf (8.5.0-2) ... Setting up man-db (2.12.0-3) ... Not building database; man-db/auto-update is not 'true'. Setting up libxml-sax-perl (1.02+dfsg-3) ... update-perl-sax-parsers: Registering Perl SAX parser XML::SAX::PurePerl with priority 10... update-perl-sax-parsers: Updating overall Perl SAX parser modules info file... Creating config file /etc/perl/XML/SAX/ParserDetails.ini with new version Setting up gfortran (4:13.2.0-7) ... update-alternatives: using /usr/bin/gfortran to provide /usr/bin/f95 (f95) in auto mode update-alternatives: using /usr/bin/gfortran to provide /usr/bin/f77 (f77) in auto mode Setting up libcairo2:armhf (1.18.0-1+b1) ... Setting up libqt5network5:armhf (5.15.10+dfsg-7) ... Setting up libxxf86vm1:armhf (1:1.1.4-1+b2) ... Setting up libxnvctrl0:armhf (535.171.04-1) ... Setting up libfeature-compat-class-perl (0.06-1) ... Setting up libqt5sql5:armhf (5.15.10+dfsg-7) ... Setting up tex-common (6.18) ... update-language: texlive-base not installed and configured, doing nothing! Setting up libqt5xml5:armhf (5.15.10+dfsg-7) ... Setting up libegl-mesa0:armhf (23.3.5-1) ... Setting up libnet-smtp-ssl-perl (1.04-2) ... Setting up libmodule-runtime-perl (0.016-2) ... Setting up libmailtools-perl (2.21-3) ... Setting up libxfixes3:armhf (1:6.0.0-2) ... Setting up libcurl4-openssl-dev:armhf (8.5.0-2) ... Setting up libklu2:armhf (1:7.6.1+dfsg-1) ... Setting up libconfig-model-perl (2.153-3) ... Setting up libxinerama1:armhf (2:1.1.4-3) ... Setting up libxml-libxml-perl (2.0207+dfsg+really+2.0134-1+b2) ... update-perl-sax-parsers: Registering Perl SAX parser XML::LibXML::SAX::Parser with priority 50... update-perl-sax-parsers: Registering Perl SAX parser XML::LibXML::SAX with priority 50... update-perl-sax-parsers: Updating overall Perl SAX parser modules info file... Replacing config file /etc/perl/XML/SAX/ParserDetails.ini with new version Setting up libcups2:armhf (2.4.7-1+b1) ... Setting up libumfpack6:armhf (1:7.6.1+dfsg-1) ... Setting up libconst-fast-perl (0.014-2) ... Setting up libhdf5-103-1:armhf (1.10.10+repack-3+b1) ... Setting up libdata-section-perl (0.200008-1) ... Setting up libhdf5-cpp-103-1:armhf (1.10.10+repack-3+b1) ... Setting up libegl1:armhf (1.7.0-1) ... Setting up libpangoft2-1.0-0:armhf (1.52.0+ds-1) ... Setting up libdata-dpath-perl (0.59-1) ... Setting up libstring-rewriteprefix-perl (0.009-1) ... Setting up libpangocairo-1.0-0:armhf (1.52.0+ds-1) ... Setting up libpython3-stdlib:armhf (3.11.6-1) ... Setting up libhdf5-hl-100:armhf (1.10.10+repack-3+b1) ... Setting up libconfig-model-backend-yaml-perl (2.134-2) ... Setting up librdmacm1:armhf (48.0-1.1) ... Setting up python3.11 (3.11.8-1) ... Setting up libxft2:armhf (2.3.6-1+b1) ... Setting up libglx-mesa0:armhf (23.3.5-1) ... Setting up libglx0:armhf (1.7.0-1) ... Setting up libmodule-implementation-perl (0.09-2) ... Setting up libpackage-stash-perl (0.40-1) ... Setting up libimport-into-perl (1.002005-2) ... Setting up libmoo-perl (2.005005-1) ... Setting up libxcursor1:armhf (1:1.2.1-1) ... Setting up libqt5gui5:armhf (5.15.10+dfsg-7) ... Setting up liblist-someutils-perl (0.59-1) ... Setting up debhelper (13.15.3) ... Setting up libqt5widgets5:armhf (5.15.10+dfsg-7) ... Setting up python3 (3.11.6-1) ... Setting up libhwloc-plugins:armhf (2.10.0-1+b1) ... Setting up libmime-tools-perl (5.514-1) ... Setting up libqt5help5:armhf (5.15.10-6) ... Setting up libsoftware-license-perl (0.104006-1) ... Setting up libclass-load-perl (0.25-2) ... Setting up libqt5printsupport5:armhf (5.15.10+dfsg-7) ... Setting up libhdf5-hl-cpp-100:armhf (1.10.10+repack-3+b1) ... Setting up libgl1:armhf (1.7.0-1) ... Setting up libhdf5-fortran-102:armhf (1.10.10+repack-3+b1) ... Setting up texinfo (7.1-3) ... Setting up libhdf5-hl-fortran-100:armhf (1.10.10+repack-3+b1) ... Setting up libglx-dev:armhf (1.7.0-1) ... Setting up libmoox-aliases-perl (0.001006-2) ... Setting up libparams-validate-perl:armhf (1.31-2+b1) ... Setting up libb-hooks-endofscope-perl (0.28-1) ... Setting up libgl-dev:armhf (1.7.0-1) ... Setting up libfabric1:armhf (1.17.0-3) ... Setting up libpmix2:armhf (5.0.1-4+b1) ... Setting up libsoftware-licensemoreutils-perl (1.009-1) ... Setting up libopenmpi3:armhf (4.1.6-5) ... Setting up libfltk1.3:armhf (1.3.8-6+b1) ... Setting up libfltk-gl1.3:armhf (1.3.8-6+b1) ... Setting up libfftw3-mpi3:armhf (3.3.10-1+b1) ... Setting up libqscintilla2-qt5-15:armhf (2.14.1+dfsg-1+b1) ... Setting up libgl2ps1.4 (1.4.2+dfsg1-2) ... Setting up libcombblas2.0.0:armhf (2.0.0-3+b1) ... Setting up libhdf5-dev (1.10.10+repack-3+b1) ... update-alternatives: using /usr/lib/arm-linux-gnueabihf/pkgconfig/hdf5-serial.pc to provide /usr/lib/arm-linux-gnueabihf/pkgconfig/hdf5.pc (hdf5.pc) in auto mode Setting up libnamespace-clean-perl (0.27-2) ... Setting up libstring-license-perl (0.0.9-2) ... Setting up libgetopt-long-descriptive-perl (0.111-1) ... Setting up openmpi-bin (4.1.6-5) ... update-alternatives: using /usr/bin/mpirun.openmpi to provide /usr/bin/mpirun (mpirun) in auto mode update-alternatives: using /usr/bin/mpicc.openmpi to provide /usr/bin/mpicc (mpi) in auto mode Setting up licensecheck (3.3.9-1) ... Setting up libhdf5-openmpi-103-1:armhf (1.10.10+repack-3+b1) ... Setting up libptscotch-7.0:armhf (7.0.4-1+b1) ... Setting up libsuperlu-dist8:armhf (8.2.1+dfsg1-1) ... Setting up libapp-cmd-perl (0.336-1) ... Setting up mpi-default-bin (1.15) ... Setting up libhypre-2.28.0:armhf (2.28.0-8) ... Setting up cme (1.040-1) ... Setting up libscalapack-openmpi2.2:armhf (2.2.1-3+b1) ... Setting up libmumps-5.6:armhf (5.6.2-2+b1) ... Setting up libpetsc-real3.19:armhf (3.19.6+dfsg1-2) ... update-alternatives: using /usr/lib/arm-linux-gnueabihf/libpetsc_real.so.3.19.6 to provide /usr/lib/arm-linux-gnueabihf/libpetsc.so.3.19 (libpetsc.so.3.19) in auto mode Setting up libsundials-nvecparallel-petsc6:armhf (6.4.1+dfsg1-3+b3) ... Setting up libsundials-sunlinsol3:armhf (6.4.1+dfsg1-3+b3) ... Setting up libheif-plugin-dav1d:armhf (1.17.6-1) ... Setting up liblwp-protocol-https-perl (6.14-1) ... Setting up libheif-plugin-libde265:armhf (1.17.6-1) ... Setting up libwww-perl (6.77-1) ... Setting up libheif1:armhf (1.17.6-1) ... Setting up libparse-debcontrol-perl (2.005-6) ... Setting up libhtml-tokeparser-simple-perl (3.16-4) ... Setting up libwww-mechanize-perl (2.18-1) ... Setting up libgd3:armhf (2.3.3-9+b1) ... Setting up libgraphicsmagick-q16-3 (1.4+really1.3.42-1+b1) ... Setting up libgraphicsmagick++-q16-12 (1.4+really1.3.42-1+b1) ... Setting up gnuplot-nox (6.0.0+dfsg1-1) ... update-alternatives: using /usr/bin/gnuplot-nox to provide /usr/bin/gnuplot (gnuplot) in auto mode Setting up lintian (2.117.0) ... Setting up libconfig-model-dpkg-perl (3.004) ... Setting up dh-octave-autopkgtest (1.8.0) ... Setting up octave (8.4.0-1+b1) ... Setting up octave-dev (8.4.0-1+b1) ... Setting up octave-io (2.6.4-3+b1) ... Setting up dh-octave (1.8.0) ... Processing triggers for libc-bin (2.37-15) ... Processing triggers for ca-certificates (20240203) ... Updating certificates in /etc/ssl/certs... 0 added, 0 removed; done. Running hooks in /etc/ca-certificates/update.d... done. Reading package lists... Building dependency tree... Reading state information... Reading extended state information... Initializing package states... Writing extended state information... Building tag database... -> Finished parsing the build-deps I: Building the package I: 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 armhf 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/arm-linux-gnueabihf/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 libsvmread.cc -o /tmp/oct-2GlId0.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 -o libsvmread.oct /tmp/oct-2GlId0.o -shared -Wl,-Bsymbolic -Wl,-z,relro -L/usr/lib/arm-linux-gnueabihf -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 libsvmwrite.cc -o /tmp/oct-tATkV1.o libsvmwrite.cc: In function 'void write(std::string, ColumnVector, SparseMatrix)': libsvmwrite.cc:75:25: warning: format '%lu' expects argument of type 'long unsigned int', but argument 3 has type 'size_t' {aka 'unsigned int'} [-Wformat=] 75 | fprintf(fp ," %lu:%g", (size_t)ir[k]+1, samples[k]); | ~~^ ~~~~~~~~~~~~~~~ | | | | long unsigned int size_t {aka unsigned int} | %u g++ -I/usr/include/octave-8.4.0/octave/.. -I/usr/include/octave-8.4.0/octave -pthread -fopenmp -g -O2 -ffile-prefix-map=/build/reproducible-path/octave-statistics-1.6.5=. -fstack-protector-strong -fstack-clash-protection -Wformat -Werror=format-security -o libsvmwrite.oct /tmp/oct-tATkV1.o -shared -Wl,-Bsymbolic -Wl,-z,relro -L/usr/lib/arm-linux-gnueabihf -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 svmpredict.cc -o /tmp/oct-jAGvR9.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 svm.cpp -o /tmp/oct-i6OpdE.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 svm_model_octave.cc -o /tmp/oct-V4FiVw.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 -o svmpredict.oct /tmp/oct-jAGvR9.o /tmp/oct-i6OpdE.o /tmp/oct-V4FiVw.o -shared -Wl,-Bsymbolic -Wl,-z,relro -L/usr/lib/arm-linux-gnueabihf -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 svmtrain.cc -o /tmp/oct-XwIE7W.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 svm.cpp -o /tmp/oct-XYjD7e.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 svm_model_octave.cc -o /tmp/oct-yuuYHE.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 -o svmtrain.oct /tmp/oct-XwIE7W.o /tmp/oct-XYjD7e.o /tmp/oct-yuuYHE.o -shared -Wl,-Bsymbolic -Wl,-z,relro -L/usr/lib/arm-linux-gnueabihf -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/arm-unknown-linux-gnueabihf-api-v58 warning: function /build/reproducible-path/octave-statistics-1.6.5/debian/tmp/usr/share/octave/packages/statistics-1.6.5/shadow9/mean.m shadows a core library function warning: called from /build/reproducible-path/octave-statistics-1.6.5/debian/tmp/usr/share/octave/packages/statistics-1.6.5/PKG_ADD at line 15 column 3 doc_cache_create>gen_doc_cache_in_dir at line 146 column 5 doc_cache_create at line 62 column 12 install>generate_lookfor_cache at line 842 column 5 install at line 243 column 7 pkg at line 619 column 9 /usr/share/dh-octave/install-pkg.m at line 38 column 1 warning: function /build/reproducible-path/octave-statistics-1.6.5/debian/tmp/usr/share/octave/packages/statistics-1.6.5/shadow9/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/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/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/var.m shadows a core library function warning: called from /build/reproducible-path/octave-statistics-1.6.5/debian/tmp/usr/share/octave/packages/statistics-1.6.5/PKG_ADD at line 15 column 3 doc_cache_create>gen_doc_cache_in_dir at line 146 column 5 doc_cache_create at line 62 column 12 install>generate_lookfor_cache at line 842 column 5 install at line 243 column 7 pkg at line 619 column 9 /usr/share/dh-octave/install-pkg.m at line 38 column 1 warning: function /build/reproducible-path/octave-statistics-1.6.5/debian/tmp/usr/share/octave/packages/statistics-1.6.5/shadow9/mean.m shadows a core library function warning: called from doc_cache_create>gen_doc_cache_in_dir at line 146 column 5 doc_cache_create at line 62 column 12 install>generate_lookfor_cache at line 842 column 5 install at line 243 column 7 pkg at line 619 column 9 /usr/share/dh-octave/install-pkg.m at line 38 column 1 warning: function /build/reproducible-path/octave-statistics-1.6.5/debian/tmp/usr/share/octave/packages/statistics-1.6.5/shadow9/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/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/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/var.m shadows a core library function warning: called from doc_cache_create>gen_doc_cache_in_dir at line 146 column 5 doc_cache_create at line 62 column 12 install>generate_lookfor_cache at line 842 column 5 install at line 243 column 7 pkg at line 619 column 9 /usr/share/dh-octave/install-pkg.m at line 38 column 1 For information about changes from previous versions of the statistics package, run 'news statistics'. rm: cannot remove '/build/reproducible-path/octave-statistics-1.6.5/debian/tmp/usr/share/octave/packages/statistics-1.6.5/doc': Is a directory dh_octave_check -O--buildsystem=octave Checking package... Run the unit tests... Checking m files ... warning: function /build/reproducible-path/octave-statistics-1.6.5/debian/tmp/usr/share/octave/packages/statistics-1.6.5/shadow9/mean.m shadows a core library function warning: called from /tmp/tmp.SsMo1UwVTS at line 12 column 1 warning: function /build/reproducible-path/octave-statistics-1.6.5/debian/tmp/usr/share/octave/packages/statistics-1.6.5/shadow9/mad.m shadows a core library function warning: called from /tmp/tmp.SsMo1UwVTS 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.SsMo1UwVTS 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.SsMo1UwVTS 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.SsMo1UwVTS at line 12 column 1 [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/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/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/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 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. 1 test, 1 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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/@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/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/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/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/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/@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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/ExponentialDistribution.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/dist_obj/ExponentialDistribution.m ***** shared pd, t pd = ExponentialDistribution (1); t = truncate (pd, 2, 4); ***** assert (cdf (pd, [0:5]), [0, 0.6321, 0.8647, 0.9502, 0.9817, 0.9933], 1e-4); ***** assert (cdf (t, [0:5]), [0, 0, 0, 0.7311, 1, 1], 1e-4); ***** assert (cdf (pd, [1.5, 2, 3, 4]), [0.7769, 0.8647, 0.9502, 0.9817], 1e-4); ***** assert (cdf (t, [1.5, 2, 3, 4]), [0, 0, 0.7311, 1], 1e-4); ***** assert (icdf (pd, [0:0.2:1]), [0, 0.2231, 0.5108, 0.9163, 1.6094, Inf], 1e-4); ***** assert (icdf (t, [0:0.2:1]), [2, 2.1899, 2.4244, 2.7315, 3.1768, 4], 1e-4); ***** assert (icdf (pd, [-1, 0.4:0.2:1, NaN]), [NaN, 0.5108, 0.9163, 1.6094, Inf, NaN], 1e-4); ***** assert (icdf (t, [-1, 0.4:0.2:1, NaN]), [NaN, 2.4244, 2.7315, 3.1768, 4, NaN], 1e-4); ***** assert (iqr (pd), 1.0986, 1e-4); ***** assert (iqr (t), 0.8020, 1e-4); ***** assert (mean (pd), 1); ***** assert (mean (t), 2.6870, 1e-4); ***** assert (median (pd), 0.6931, 1e-4); ***** assert (median (t), 2.5662, 1e-4); ***** assert (pdf (pd, [0:5]), [1, 0.3679, 0.1353, 0.0498, 0.0183, 0.0067], 1e-4); ***** assert (pdf (t, [0:5]), [0, 0, 1.1565, 0.4255, 0.1565, 0], 1e-4); ***** assert (pdf (pd, [-1, 1:4, NaN]), [0, 0.3679, 0.1353, 0.0498, 0.0183, NaN], 1e-4); ***** assert (pdf (t, [-1, 1:4, NaN]), [0, 0, 1.1565, 0.4255, 0.1565, NaN], 1e-4); ***** assert (isequal (size (random (pd, 100, 50)), [100, 50])) ***** assert (any (random (t, 1000, 1) < 2), false); ***** assert (any (random (t, 1000, 1) > 4), false); ***** assert (std (pd), 1); ***** assert (std (t), 0.5253, 1e-4); ***** assert (var (pd), 1); ***** assert (var (t), 0.2759, 1e-4); ***** error ... ExponentialDistribution(0) ***** error ... ExponentialDistribution(-1) ***** error ... ExponentialDistribution(Inf) ***** error ... ExponentialDistribution(i) ***** error ... ExponentialDistribution("a") ***** error ... ExponentialDistribution([1, 2]) ***** error ... ExponentialDistribution(NaN) ***** error ... cdf (ExponentialDistribution, 2, "uper") ***** error ... cdf (ExponentialDistribution, 2, 3) ***** shared x x = exprnd (1, [100, 1]); ***** error ... paramci (ExponentialDistribution.fit (x), "alpha") ***** error ... paramci (ExponentialDistribution.fit (x), "alpha", 0) ***** error ... paramci (ExponentialDistribution.fit (x), "alpha", 1) ***** error ... paramci (ExponentialDistribution.fit (x), "alpha", [0.5 2]) ***** error ... paramci (ExponentialDistribution.fit (x), "alpha", "") ***** error ... paramci (ExponentialDistribution.fit (x), "alpha", {0.05}) ***** error ... paramci (ExponentialDistribution.fit (x), "parameter", "mu", ... "alpha", {0.05}) ***** error ... paramci (ExponentialDistribution.fit (x), "parameter", {"mu", "param"}) ***** error ... paramci (ExponentialDistribution.fit (x), "alpha", 0.01, ... "parameter", {"mu", "param"}) ***** error ... paramci (ExponentialDistribution.fit (x), "parameter", "param") ***** error ... paramci (ExponentialDistribution.fit (x), "alpha", 0.01, "parameter", "parm") ***** error ... paramci (ExponentialDistribution.fit (x), "NAME", "value") ***** error ... paramci (ExponentialDistribution.fit (x), "alpha", 0.01, "NAME", "value") ***** error ... paramci (ExponentialDistribution.fit (x), "alpha", 0.01, ... "parameter", "mu", "NAME", "value") ***** error ... plot (ExponentialDistribution, "Parent") ***** error ... plot (ExponentialDistribution, "PlotType", 12) ***** error ... plot (ExponentialDistribution, "PlotType", {"pdf", "cdf"}) ***** error ... plot (ExponentialDistribution, "PlotType", "pdfcdf") ***** error ... plot (ExponentialDistribution, "Discrete", "pdfcdf") ***** error ... plot (ExponentialDistribution, "Discrete", [1, 0]) ***** error ... plot (ExponentialDistribution, "Discrete", {true}) ***** error ... plot (ExponentialDistribution, "Parent", 12) ***** error ... plot (ExponentialDistribution, "Parent", "hax") ***** error ... proflik (ExponentialDistribution, 2) ***** error ... proflik (ExponentialDistribution.fit (x), 3) ***** error ... proflik (ExponentialDistribution.fit (x), [1, 2]) ***** error ... proflik (ExponentialDistribution.fit (x), {1}) ***** error ... proflik (ExponentialDistribution.fit (x), 1, ones (2)) ***** error ... proflik (ExponentialDistribution.fit (x), 1, "Display") ***** error ... proflik (ExponentialDistribution.fit (x), 1, "Display", 1) ***** error ... proflik (ExponentialDistribution.fit (x), 1, "Display", {1}) ***** error ... proflik (ExponentialDistribution.fit (x), 1, "Display", {"on"}) ***** error ... proflik (ExponentialDistribution.fit (x), 1, "Display", ["on"; "on"]) ***** error ... proflik (ExponentialDistribution.fit (x), 1, "Display", "onnn") ***** error ... proflik (ExponentialDistribution.fit (x), 1, "NAME", "on") ***** error ... proflik (ExponentialDistribution.fit (x), 1, {"NAME"}, "on") ***** error ... proflik (ExponentialDistribution.fit (x), 1, {[1 2 3 4]}, "Display", "on") ***** error ... truncate (ExponentialDistribution) ***** error ... truncate (ExponentialDistribution, 2) ***** error ... truncate (ExponentialDistribution, 4, 2) ***** shared pd pd = ExponentialDistribution(1); pd(2) = ExponentialDistribution(3); ***** error cdf (pd, 1) ***** error icdf (pd, 0.5) ***** error iqr (pd) ***** error mean (pd) ***** error median (pd) ***** error negloglik (pd) ***** error paramci (pd) ***** error pdf (pd, 1) ***** error plot (pd) ***** error proflik (pd, 2) ***** error random (pd) ***** error std (pd) ***** error ... truncate (pd, 2, 4) ***** error var (pd) 88 tests, 88 passed, 0 known failure, 0 skipped [inst/dist_obj/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/makedist.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/dist_wrap/makedist.m ***** test pd = makedist ("beta"); assert (class (pd), "BetaDistribution"); assert (pd.a, 1); assert (pd.b, 1); ***** test pd = makedist ("beta", "a", 5); assert (pd.a, 5); assert (pd.b, 1); ***** test pd = makedist ("beta", "b", 5); assert (pd.a, 1); assert (pd.b, 5); ***** test pd = makedist ("beta", "a", 3, "b", 5); assert (pd.a, 3); assert (pd.b, 5); ***** test pd = makedist ("binomial"); assert (class (pd), "BinomialDistribution"); assert (pd.N, 1); assert (pd.p, 0.5); ***** test pd = makedist ("binomial", "N", 5); assert (pd.N, 5); assert (pd.p, 0.5); ***** test pd = makedist ("binomial", "p", 0.2); assert (pd.N, 1); assert (pd.p, 0.2); ***** test pd = makedist ("binomial", "N", 3, "p", 0.3); assert (pd.N, 3); assert (pd.p, 0.3); ***** test pd = makedist ("birnbaumsaunders"); assert (class (pd), "BirnbaumSaundersDistribution"); assert (pd.beta, 1); assert (pd.gamma, 1); ***** test pd = makedist ("birnbaumsaunders", "beta", 5); assert (pd.beta, 5); assert (pd.gamma, 1); ***** test pd = makedist ("birnbaumsaunders", "gamma", 5); assert (pd.beta, 1); assert (pd.gamma, 5); ***** test pd = makedist ("birnbaumsaunders", "beta", 3, "gamma", 5); assert (pd.beta, 3); assert (pd.gamma, 5); ***** test pd = makedist ("burr"); assert (class (pd), "BurrDistribution"); assert (pd.alpha, 1); assert (pd.c, 1); assert (pd.k, 1); ***** test pd = makedist ("burr", "k", 5); assert (pd.alpha, 1); assert (pd.c, 1); assert (pd.k, 5); ***** test pd = makedist ("burr", "c", 5); assert (pd.alpha, 1); assert (pd.c, 5); assert (pd.k, 1); ***** test pd = makedist ("burr", "alpha", 3, "c", 5); assert (pd.alpha, 3); assert (pd.c, 5); assert (pd.k, 1); ***** test pd = makedist ("burr", "k", 3, "c", 5); assert (pd.alpha, 1); assert (pd.c, 5); assert (pd.k, 3); ***** test pd = makedist ("exponential"); assert (class (pd), "ExponentialDistribution"); assert (pd.mu, 1); ***** test pd = makedist ("exponential", "mu", 5); assert (pd.mu, 5); ***** test pd = makedist ("extremevalue"); assert (class (pd), "ExtremeValueDistribution"); assert (pd.mu, 0); assert (pd.sigma, 1); ***** test pd = makedist ("extremevalue", "mu", 5); assert (class (pd), "ExtremeValueDistribution"); assert (pd.mu, 5); assert (pd.sigma, 1); ***** test pd = makedist ("ev", "sigma", 5); assert (class (pd), "ExtremeValueDistribution"); assert (pd.mu, 0); assert (pd.sigma, 5); ***** test pd = makedist ("ev", "mu", -3, "sigma", 5); assert (class (pd), "ExtremeValueDistribution"); assert (pd.mu, -3); assert (pd.sigma, 5); ***** test pd = makedist ("gamma"); assert (class (pd), "GammaDistribution"); assert (pd.a, 1); assert (pd.b, 1); ***** test pd = makedist ("gamma", "a", 5); assert (pd.a, 5); assert (pd.b, 1); ***** test pd = makedist ("gamma", "b", 5); assert (pd.a, 1); assert (pd.b, 5); ***** test pd = makedist ("gamma", "a", 3, "b", 5); assert (pd.a, 3); assert (pd.b, 5); ***** test pd = makedist ("GeneralizedExtremeValue"); assert (class (pd), "GeneralizedExtremeValueDistribution"); assert (pd.k, 0); assert (pd.sigma, 1); assert (pd.mu, 0); ***** test pd = makedist ("GeneralizedExtremeValue", "k", 5); assert (pd.k, 5); assert (pd.sigma, 1); assert (pd.mu, 0); ***** test pd = makedist ("GeneralizedExtremeValue", "sigma", 5); assert (pd.k, 0); assert (pd.sigma, 5); assert (pd.mu, 0); ***** test pd = makedist ("GeneralizedExtremeValue", "k", 3, "sigma", 5); assert (pd.k, 3); assert (pd.sigma, 5); assert (pd.mu, 0); ***** test pd = makedist ("GeneralizedExtremeValue", "mu", 3, "sigma", 5); assert (pd.k, 0); assert (pd.sigma, 5); assert (pd.mu, 3); ***** test pd = makedist ("GeneralizedPareto"); assert (class (pd), "GeneralizedParetoDistribution"); assert (pd.k, 1); assert (pd.sigma, 1); assert (pd.theta, 1); ***** test pd = makedist ("GeneralizedPareto", "k", 5); assert (pd.k, 5); assert (pd.sigma, 1); assert (pd.theta, 1); ***** test pd = makedist ("GeneralizedPareto", "sigma", 5); assert (pd.k, 1); assert (pd.sigma, 5); assert (pd.theta, 1); ***** test pd = makedist ("GeneralizedPareto", "k", 3, "sigma", 5); assert (pd.k, 3); assert (pd.sigma, 5); assert (pd.theta, 1); ***** test pd = makedist ("GeneralizedPareto", "theta", 3, "sigma", 5); assert (pd.k, 1); assert (pd.sigma, 5); assert (pd.theta, 3); ***** test pd = makedist ("HalfNormal"); assert (class (pd), "HalfNormalDistribution"); assert (pd.mu, 0); assert (pd.sigma, 1); ***** test pd = makedist ("HalfNormal", "mu", 5); assert (pd.mu, 5); assert (pd.sigma, 1); ***** test pd = makedist ("HalfNormal", "sigma", 5); assert (pd.mu, 0); assert (pd.sigma, 5); ***** test pd = makedist ("HalfNormal", "mu", 3, "sigma", 5); assert (pd.mu, 3); assert (pd.sigma, 5); ***** test pd = makedist ("InverseGaussian"); assert (class (pd), "InverseGaussianDistribution"); assert (pd.mu, 1); assert (pd.lambda, 1); ***** test pd = makedist ("InverseGaussian", "mu", 5); assert (pd.mu, 5); assert (pd.lambda, 1); ***** test pd = makedist ("InverseGaussian", "lambda", 5); assert (pd.mu, 1); assert (pd.lambda, 5); ***** test pd = makedist ("InverseGaussian", "mu", 3, "lambda", 5); assert (pd.mu, 3); assert (pd.lambda, 5); ***** test pd = makedist ("logistic"); assert (class (pd), "LogisticDistribution"); assert (pd.mu, 0); assert (pd.sigma, 1); ***** test pd = makedist ("logistic", "mu", 5); assert (pd.mu, 5); assert (pd.sigma, 1); ***** test pd = makedist ("logistic", "sigma", 5); assert (pd.mu, 0); assert (pd.sigma, 5); ***** test pd = makedist ("logistic", "mu", 3, "sigma", 5); assert (pd.mu, 3); assert (pd.sigma, 5); ***** test pd = makedist ("loglogistic"); assert (class (pd), "LoglogisticDistribution"); assert (pd.mu, 0); assert (pd.sigma, 1); ***** test pd = makedist ("loglogistic", "mu", 5); assert (pd.mu, 5); assert (pd.sigma, 1); ***** test pd = makedist ("loglogistic", "sigma", 5); assert (pd.mu, 0); assert (pd.sigma, 5); ***** test pd = makedist ("loglogistic", "mu", 3, "sigma", 5); assert (pd.mu, 3); assert (pd.sigma, 5); ***** test pd = makedist ("Lognormal"); assert (class (pd), "LognormalDistribution"); assert (pd.mu, 0); assert (pd.sigma, 1); ***** test pd = makedist ("Lognormal", "mu", 5); assert (pd.mu, 5); assert (pd.sigma, 1); ***** test pd = makedist ("Lognormal", "sigma", 5); assert (pd.mu, 0); assert (pd.sigma, 5); ***** test pd = makedist ("Lognormal", "mu", -3, "sigma", 5); assert (pd.mu, -3); assert (pd.sigma, 5); ***** test pd = makedist ("Loguniform"); assert (class (pd), "LoguniformDistribution"); assert (pd.Lower, 1); assert (pd.Upper, 4); ***** test pd = makedist ("Loguniform", "Lower", 2); assert (pd.Lower, 2); assert (pd.Upper, 4); ***** test pd = makedist ("Loguniform", "Lower", 1, "Upper", 3); assert (pd.Lower, 1); assert (pd.Upper, 3); ***** test pd = makedist ("Multinomial"); assert (class (pd), "MultinomialDistribution"); assert (pd.Probabilities, [0.5, 0.5]); ***** test pd = makedist ("Multinomial", "Probabilities", [0.2, 0.3, 0.1, 0.4]); assert (class (pd), "MultinomialDistribution"); assert (pd.Probabilities, [0.2, 0.3, 0.1, 0.4]); ***** test pd = makedist ("Nakagami"); assert (class (pd), "NakagamiDistribution"); assert (pd.mu, 1); assert (pd.omega, 1); ***** test pd = makedist ("Nakagami", "mu", 5); assert (class (pd), "NakagamiDistribution"); assert (pd.mu, 5); assert (pd.omega, 1); ***** test pd = makedist ("Nakagami", "omega", 0.3); assert (class (pd), "NakagamiDistribution"); assert (pd.mu, 1); assert (pd.omega, 0.3); ***** test pd = makedist ("NegativeBinomial"); assert (class (pd), "NegativeBinomialDistribution"); assert (pd.R, 1); assert (pd.P, 0.5); ***** test pd = makedist ("NegativeBinomial", "R", 5); assert (class (pd), "NegativeBinomialDistribution"); assert (pd.R, 5); assert (pd.P, 0.5); ***** test pd = makedist ("NegativeBinomial", "p", 0.3); assert (class (pd), "NegativeBinomialDistribution"); assert (pd.R, 1); assert (pd.P, 0.3); ***** test pd = makedist ("Normal"); assert (class (pd), "NormalDistribution"); assert (pd.mu, 0); assert (pd.sigma, 1); ***** test pd = makedist ("Normal", "mu", 5); assert (class (pd), "NormalDistribution"); assert (pd.mu, 5); assert (pd.sigma, 1); ***** test pd = makedist ("Normal", "sigma", 5); assert (class (pd), "NormalDistribution"); assert (pd.mu, 0); assert (pd.sigma, 5); ***** test pd = makedist ("Normal", "mu", -3, "sigma", 5); assert (class (pd), "NormalDistribution"); assert (pd.mu, -3); assert (pd.sigma, 5); ***** test pd = makedist ("PiecewiseLinear"); assert (class (pd), "PiecewiseLinearDistribution"); assert (pd.x, [0; 1]); assert (pd.Fx, [0; 1]); ***** test pd = makedist ("PiecewiseLinear", "x", [0, 1, 2], "Fx", [0, 0.5, 1]); assert (pd.x, [0; 1; 2]); assert (pd.Fx, [0; 0.5; 1]); ***** test pd = makedist ("Poisson"); assert (class (pd), "PoissonDistribution"); assert (pd.lambda, 1); ***** test pd = makedist ("Poisson", "lambda", 5); assert (pd.lambda, 5); ***** test pd = makedist ("Rayleigh"); assert (class (pd), "RayleighDistribution"); assert (pd.sigma, 1); ***** test pd = makedist ("Rayleigh", "sigma", 5); assert (pd.sigma, 5); ***** test pd = makedist ("Rician"); assert (class (pd), "RicianDistribution"); assert (pd.s, 1); assert (pd.sigma, 1); ***** test pd = makedist ("Rician", "s", 3); assert (pd.s, 3); assert (pd.sigma, 1); ***** test pd = makedist ("Rician", "sigma", 3); assert (pd.s, 1); assert (pd.sigma, 3); ***** test pd = makedist ("Rician", "s", 2, "sigma", 3); assert (pd.s, 2); assert (pd.sigma, 3); ***** warning pd = makedist ("stable"); assert (class (pd), "double"); assert (isempty (pd), true); ***** test pd = makedist ("tlocationscale"); assert (class (pd), "tLocationScaleDistribution"); assert (pd.mu, 0); assert (pd.sigma, 1); assert (pd.nu, 5); ***** test pd = makedist ("tlocationscale", "mu", 5); assert (pd.mu, 5); assert (pd.sigma, 1); assert (pd.nu, 5); ***** test pd = makedist ("tlocationscale", "sigma", 2); assert (pd.mu, 0); assert (pd.sigma, 2); assert (pd.nu, 5); ***** test pd = makedist ("tlocationscale", "mu", 5, "sigma", 2); assert (pd.mu, 5); assert (pd.sigma, 2); assert (pd.nu, 5); ***** test pd = makedist ("tlocationscale", "nu", 1, "sigma", 2); assert (pd.mu, 0); assert (pd.sigma, 2); assert (pd.nu, 1); ***** test pd = makedist ("tlocationscale", "mu", -2, "sigma", 3, "nu", 1); assert (pd.mu, -2); assert (pd.sigma, 3); assert (pd.nu, 1); ***** test pd = makedist ("Triangular"); assert (class (pd), "TriangularDistribution"); assert (pd.A, 0); assert (pd.B, 0.5); assert (pd.C, 1); ***** test pd = makedist ("Triangular", "A", -2); assert (pd.A, -2); assert (pd.B, 0.5); assert (pd.C, 1); ***** test pd = makedist ("Triangular", "A", 0.5, "B", 0.9); assert (pd.A, 0.5); assert (pd.B, 0.9); assert (pd.C, 1); ***** test pd = makedist ("Triangular", "A", 1, "B", 2, "C", 5); assert (pd.A, 1); assert (pd.B, 2); assert (pd.C, 5); ***** test pd = makedist ("Uniform"); assert (class (pd), "UniformDistribution"); assert (pd.Lower, 0); assert (pd.Upper, 1); ***** test pd = makedist ("Uniform", "Lower", -2); assert (pd.Lower, -2); assert (pd.Upper, 1); ***** test pd = makedist ("Uniform", "Lower", 1, "Upper", 3); assert (pd.Lower, 1); assert (pd.Upper, 3); ***** test pd = makedist ("Weibull"); assert (class (pd), "WeibullDistribution"); assert (pd.lambda, 1); assert (pd.k, 1); ***** test pd = makedist ("Weibull", "lambda", 3); assert (pd.lambda, 3); assert (pd.k, 1); ***** test pd = makedist ("Weibull", "lambda", 3, "k", 2); assert (pd.lambda, 3); assert (pd.k, 2); ***** error makedist (1) ***** error makedist (["as";"sd"]) ***** error makedist ("some") ***** error ... makedist ("Beta", "a") ***** error ... makedist ("Beta", "a", 1, "Q", 23) ***** error ... makedist ("Binomial", "N", 1, "Q", 23) ***** error ... makedist ("BirnbaumSaunders", "N", 1) ***** error ... makedist ("Burr", "lambda", 1, "sdfs", 34) ***** error ... makedist ("extremevalue", "mu", 1, "sdfs", 34) ***** error ... makedist ("exponential", "mu", 1, "sdfs", 34) ***** error ... makedist ("Gamma", "k", 1, "sdfs", 34) ***** error ... makedist ("GeneralizedExtremeValue", "k", 1, "sdfs", 34) ***** error ... makedist ("GeneralizedPareto", "k", 1, "sdfs", 34) ***** error ... makedist ("HalfNormal", "k", 1, "sdfs", 34) ***** error ... makedist ("InverseGaussian", "k", 1, "sdfs", 34) ***** error ... makedist ("Logistic", "k", 1, "sdfs", 34) ***** error ... makedist ("Loglogistic", "k", 1, "sdfs", 34) ***** error ... makedist ("Lognormal", "k", 1, "sdfs", 34) ***** error ... makedist ("Loguniform", "k", 1, "sdfs", 34) ***** error ... makedist ("Multinomial", "k", 1, "sdfs", 34) ***** error ... makedist ("Nakagami", "mu", 1, "sdfs", 34) ***** error ... makedist ("NegativeBinomial", "mu", 1, "sdfs", 34) ***** error ... makedist ("Normal", "mu", 1, "sdfs", 34) ***** error ... makedist ("PiecewiseLinear", "mu", 1, "sdfs", 34) ***** error ... makedist ("Poisson", "mu", 1, "sdfs", 34) ***** error ... makedist ("Rayleigh", "mu", 1, "sdfs", 34) ***** error ... makedist ("Rician", "mu", 1, "sdfs", 34) ***** error ... makedist ("Stable", "mu", 1, "sdfs", 34) ***** error ... makedist ("tLocationScale", "mu", 1, "sdfs", 34) ***** error ... makedist ("Triangular", "mu", 1, "sdfs", 34) ***** error ... makedist ("Uniform", "mu", 1, "sdfs", 34) ***** error ... makedist ("Weibull", "mu", 1, "sdfs", 34) 131 tests, 131 passed, 0 known failure, 0 skipped [inst/dist_wrap/random.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/dist_wrap/random.m ***** assert (size (random ("Beta", 5, 2, 2, 10)), size (betarnd (5, 2, 2, 10))) ***** assert (size (random ("beta", 5, 2, 2, 10)), size (betarnd (5, 2, 2, 10))) ***** assert (size (random ("Binomial", 5, 2, [10, 20])), size (binornd (5, 2, 10, 20))) ***** assert (size (random ("bino", 5, 2, [10, 20])), size (binornd (5, 2, 10, 20))) ***** assert (size (random ("Birnbaum-Saunders", 5, 2, [10, 20])), size (bisarnd (5, 2, 10, 20))) ***** assert (size (random ("bisa", 5, 2, [10, 20])), size (bisarnd (5, 2, 10, 20))) ***** assert (size (random ("Burr", 5, 2, 2, [10, 20])), size (burrrnd (5, 2, 2, 10, 20))) ***** assert (size (random ("burr", 5, 2, 2, [10, 20])), size (burrrnd (5, 2, 2, 10, 20))) ***** assert (size (random ("Cauchy", 5, 2, [10, 20])), size (cauchyrnd (5, 2, 10, 20))) ***** assert (size (random ("cauchy", 5, 2, [10, 20])), size (cauchyrnd (5, 2, 10, 20))) ***** assert (size (random ("Chi-squared", 5, [10, 20])), size (chi2rnd (5, 10, 20))) ***** assert (size (random ("chi2", 5, [10, 20])), size (chi2rnd (5, 10, 20))) ***** assert (size (random ("Extreme Value", 5, 2, [10, 20])), size (evrnd (5, 2, 10, 20))) ***** assert (size (random ("ev", 5, 2, [10, 20])), size (evrnd (5, 2, 10, 20))) ***** assert (size (random ("Exponential", 5, [10, 20])), size (exprnd (5, 10, 20))) ***** assert (size (random ("exp", 5, [10, 20])), size (exprnd (5, 10, 20))) ***** assert (size (random ("F-Distribution", 5, 2, [10, 20])), size (frnd (5, 2, 10, 20))) ***** assert (size (random ("f", 5, 2, [10, 20])), size (frnd (5, 2, 10, 20))) ***** assert (size (random ("Gamma", 5, 2, [10, 20])), size (gamrnd (5, 2, 10, 20))) ***** assert (size (random ("gam", 5, 2, [10, 20])), size (gamrnd (5, 2, 10, 20))) ***** assert (size (random ("Geometric", 5, [10, 20])), size (geornd (5, 10, 20))) ***** assert (size (random ("geo", 5, [10, 20])), size (geornd (5, 10, 20))) ***** assert (size (random ("Generalized Extreme Value", 5, 2, 2, [10, 20])), size (gevrnd (5, 2, 2, 10, 20))) ***** assert (size (random ("gev", 5, 2, 2, [10, 20])), size (gevrnd (5, 2, 2, 10, 20))) ***** assert (size (random ("Generalized Pareto", 5, 2, 2, [10, 20])), size (gprnd (5, 2, 2, 10, 20))) ***** assert (size (random ("gp", 5, 2, 2, [10, 20])), size (gprnd (5, 2, 2, 10, 20))) ***** assert (size (random ("Gumbel", 5, 2, [10, 20])), size (gumbelrnd (5, 2, 10, 20))) ***** assert (size (random ("gumbel", 5, 2, [10, 20])), size (gumbelrnd (5, 2, 10, 20))) ***** assert (size (random ("Half-normal", 5, 2, [10, 20])), size (hnrnd (5, 2, 10, 20))) ***** assert (size (random ("hn", 5, 2, [10, 20])), size (hnrnd (5, 2, 10, 20))) ***** assert (size (random ("Hypergeometric", 5, 2, 2, [10, 20])), size (hygernd (5, 2, 2, 10, 20))) ***** assert (size (random ("hyge", 5, 2, 2, [10, 20])), size (hygernd (5, 2, 2, 10, 20))) ***** assert (size (random ("Inverse Gaussian", 5, 2, [10, 20])), size (invgrnd (5, 2, 10, 20))) ***** assert (size (random ("invg", 5, 2, [10, 20])), size (invgrnd (5, 2, 10, 20))) ***** assert (size (random ("Laplace", 5, 2, [10, 20])), size (laplacernd (5, 2, 10, 20))) ***** assert (size (random ("laplace", 5, 2, [10, 20])), size (laplacernd (5, 2, 10, 20))) ***** assert (size (random ("Logistic", 5, 2, [10, 20])), size (logirnd (5, 2, 10, 20))) ***** assert (size (random ("logi", 5, 2, [10, 20])), size (logirnd (5, 2, 10, 20))) ***** assert (size (random ("Log-Logistic", 5, 2, [10, 20])), size (loglrnd (5, 2, 10, 20))) ***** assert (size (random ("logl", 5, 2, [10, 20])), size (loglrnd (5, 2, 10, 20))) ***** assert (size (random ("Lognormal", 5, 2, [10, 20])), size (lognrnd (5, 2, 10, 20))) ***** assert (size (random ("logn", 5, 2, [10, 20])), size (lognrnd (5, 2, 10, 20))) ***** assert (size (random ("Nakagami", 5, 2, [10, 20])), size (nakarnd (5, 2, 10, 20))) ***** assert (size (random ("naka", 5, 2, [10, 20])), size (nakarnd (5, 2, 10, 20))) ***** assert (size (random ("Negative Binomial", 5, 2, [10, 20])), size (nbinrnd (5, 2, 10, 20))) ***** assert (size (random ("nbin", 5, 2, [10, 20])), size (nbinrnd (5, 2, 10, 20))) ***** assert (size (random ("Noncentral F-Distribution", 5, 2, 2, [10, 20])), size (ncfrnd (5, 2, 2, 10, 20))) ***** assert (size (random ("ncf", 5, 2, 2, [10, 20])), size (ncfrnd (5, 2, 2, 10, 20))) ***** assert (size (random ("Noncentral Student T", 5, 2, [10, 20])), size (nctrnd (5, 2, 10, 20))) ***** assert (size (random ("nct", 5, 2, [10, 20])), size (nctrnd (5, 2, 10, 20))) ***** assert (size (random ("Noncentral Chi-Squared", 5, 2, [10, 20])), size (ncx2rnd (5, 2, 10, 20))) ***** assert (size (random ("ncx2", 5, 2, [10, 20])), size (ncx2rnd (5, 2, 10, 20))) ***** assert (size (random ("Normal", 5, 2, [10, 20])), size (normrnd (5, 2, 10, 20))) ***** assert (size (random ("norm", 5, 2, [10, 20])), size (normrnd (5, 2, 10, 20))) ***** assert (size (random ("Poisson", 5, [10, 20])), size (poissrnd (5, 10, 20))) ***** assert (size (random ("poiss", 5, [10, 20])), size (poissrnd (5, 10, 20))) ***** assert (size (random ("Rayleigh", 5, [10, 20])), size (raylrnd (5, 10, 20))) ***** assert (size (random ("rayl", 5, [10, 20])), size (raylrnd (5, 10, 20))) ***** assert (size (random ("Rician", 5, 1, [10, 20])), size (ricernd (5, 1, 10, 20))) ***** assert (size (random ("rice", 5, 1, [10, 20])), size (ricernd (5, 1, 10, 20))) ***** assert (size (random ("Student T", 5, [10, 20])), size (trnd (5, 10, 20))) ***** assert (size (random ("t", 5, [10, 20])), size (trnd (5, 10, 20))) ***** assert (size (random ("location-scale T", 5, 1, 2, [10, 20])), size (tlsrnd (5, 1, 2, 10, 20))) ***** assert (size (random ("tls", 5, 1, 2, [10, 20])), size (tlsrnd (5, 1, 2, 10, 20))) ***** assert (size (random ("Triangular", 5, 2, 2, [10, 20])), size (trirnd (5, 2, 2, 10, 20))) ***** assert (size (random ("tri", 5, 2, 2, [10, 20])), size (trirnd (5, 2, 2, 10, 20))) ***** assert (size (random ("Discrete Uniform", 5, [10, 20])), size (unidrnd (5, 10, 20))) ***** assert (size (random ("unid", 5, [10, 20])), size (unidrnd (5, 10, 20))) ***** assert (size (random ("Uniform", 5, 2, [10, 20])), size (unifrnd (5, 2, 10, 20))) ***** assert (size (random ("unif", 5, 2, [10, 20])), size (unifrnd (5, 2, 10, 20))) ***** assert (size (random ("Von Mises", 5, 2, [10, 20])), size (vmrnd (5, 2, 10, 20))) ***** assert (size (random ("vm", 5, 2, [10, 20])), size (vmrnd (5, 2, 10, 20))) ***** assert (size (random ("Weibull", 5, 2, [10, 20])), size (wblrnd (5, 2, 10, 20))) ***** assert (size (random ("wbl", 5, 2, [10, 20])), size (wblrnd (5, 2, 10, 20))) ***** error random (1) ***** error random ({"beta"}) ***** error ... random ("Beta", "a", 2) ***** error ... random ("Beta", 5, "") ***** error ... random ("Beta", 5, {2}) ***** error ... random ("Beta", "a", 2, 2, 10) ***** error ... random ("Beta", 5, "", 2, 10) ***** error ... random ("Beta", 5, {2}, 2, 10) ***** error ... random ("Beta", 5, "", 2, 10) ***** error random ("chi2") ***** error random ("Beta", 5) ***** error random ("Burr", 5) ***** error random ("Burr", 5, 2) 87 tests, 87 passed, 0 known failure, 0 skipped [inst/dist_wrap/cdf.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/dist_wrap/cdf.m ***** shared x x = [1:5]; ***** assert (cdf ("Beta", x, 5, 2), betacdf (x, 5, 2)) ***** assert (cdf ("beta", x, 5, 2, "upper"), betacdf (x, 5, 2, "upper")) ***** assert (cdf ("Binomial", x, 5, 2), binocdf (x, 5, 2)) ***** assert (cdf ("bino", x, 5, 2, "upper"), binocdf (x, 5, 2, "upper")) ***** assert (cdf ("Birnbaum-Saunders", x, 5, 2), bisacdf (x, 5, 2)) ***** assert (cdf ("bisa", x, 5, 2, "upper"), bisacdf (x, 5, 2, "upper")) ***** assert (cdf ("Burr", x, 5, 2, 2), burrcdf (x, 5, 2, 2)) ***** assert (cdf ("burr", x, 5, 2, 2, "upper"), burrcdf (x, 5, 2, 2, "upper")) ***** assert (cdf ("Cauchy", x, 5, 2), cauchycdf (x, 5, 2)) ***** assert (cdf ("cauchy", x, 5, 2, "upper"), cauchycdf (x, 5, 2, "upper")) ***** assert (cdf ("Chi-squared", x, 5), chi2cdf (x, 5)) ***** assert (cdf ("chi2", x, 5, "upper"), chi2cdf (x, 5, "upper")) ***** assert (cdf ("Extreme Value", x, 5, 2), evcdf (x, 5, 2)) ***** assert (cdf ("ev", x, 5, 2, "upper"), evcdf (x, 5, 2, "upper")) ***** assert (cdf ("Exponential", x, 5), expcdf (x, 5)) ***** assert (cdf ("exp", x, 5, "upper"), expcdf (x, 5, "upper")) ***** assert (cdf ("F-Distribution", x, 5, 2), fcdf (x, 5, 2)) ***** assert (cdf ("f", x, 5, 2, "upper"), fcdf (x, 5, 2, "upper")) ***** assert (cdf ("Gamma", x, 5, 2), gamcdf (x, 5, 2)) ***** assert (cdf ("gam", x, 5, 2, "upper"), gamcdf (x, 5, 2, "upper")) ***** assert (cdf ("Geometric", x, 5), geocdf (x, 5)) ***** assert (cdf ("geo", x, 5, "upper"), geocdf (x, 5, "upper")) ***** assert (cdf ("Generalized Extreme Value", x, 5, 2, 2), gevcdf (x, 5, 2, 2)) ***** assert (cdf ("gev", x, 5, 2, 2, "upper"), gevcdf (x, 5, 2, 2, "upper")) ***** assert (cdf ("Generalized Pareto", x, 5, 2, 2), gpcdf (x, 5, 2, 2)) ***** assert (cdf ("gp", x, 5, 2, 2, "upper"), gpcdf (x, 5, 2, 2, "upper")) ***** assert (cdf ("Gumbel", x, 5, 2), gumbelcdf (x, 5, 2)) ***** assert (cdf ("gumbel", x, 5, 2, "upper"), gumbelcdf (x, 5, 2, "upper")) ***** assert (cdf ("Half-normal", x, 5, 2), hncdf (x, 5, 2)) ***** assert (cdf ("hn", x, 5, 2, "upper"), hncdf (x, 5, 2, "upper")) ***** assert (cdf ("Hypergeometric", x, 5, 2, 2), hygecdf (x, 5, 2, 2)) ***** assert (cdf ("hyge", x, 5, 2, 2, "upper"), hygecdf (x, 5, 2, 2, "upper")) ***** assert (cdf ("Inverse Gaussian", x, 5, 2), invgcdf (x, 5, 2)) ***** assert (cdf ("invg", x, 5, 2, "upper"), invgcdf (x, 5, 2, "upper")) ***** assert (cdf ("Laplace", x, 5, 2), laplacecdf (x, 5, 2)) ***** assert (cdf ("laplace", x, 5, 2, "upper"), laplacecdf (x, 5, 2, "upper")) ***** assert (cdf ("Logistic", x, 5, 2), logicdf (x, 5, 2)) ***** assert (cdf ("logi", x, 5, 2, "upper"), logicdf (x, 5, 2, "upper")) ***** assert (cdf ("Log-Logistic", x, 5, 2), loglcdf (x, 5, 2)) ***** assert (cdf ("logl", x, 5, 2, "upper"), loglcdf (x, 5, 2, "upper")) ***** assert (cdf ("Lognormal", x, 5, 2), logncdf (x, 5, 2)) ***** assert (cdf ("logn", x, 5, 2, "upper"), logncdf (x, 5, 2, "upper")) ***** assert (cdf ("Nakagami", x, 5, 2), nakacdf (x, 5, 2)) ***** assert (cdf ("naka", x, 5, 2, "upper"), nakacdf (x, 5, 2, "upper")) ***** assert (cdf ("Negative Binomial", x, 5, 2), nbincdf (x, 5, 2)) ***** assert (cdf ("nbin", x, 5, 2, "upper"), nbincdf (x, 5, 2, "upper")) ***** assert (cdf ("Noncentral F-Distribution", x, 5, 2, 2), ncfcdf (x, 5, 2, 2)) ***** assert (cdf ("ncf", x, 5, 2, 2, "upper"), ncfcdf (x, 5, 2, 2, "upper")) ***** assert (cdf ("Noncentral Student T", x, 5, 2), nctcdf (x, 5, 2)) ***** assert (cdf ("nct", x, 5, 2, "upper"), nctcdf (x, 5, 2, "upper")) ***** assert (cdf ("Noncentral Chi-Squared", x, 5, 2), ncx2cdf (x, 5, 2)) ***** assert (cdf ("ncx2", x, 5, 2, "upper"), ncx2cdf (x, 5, 2, "upper")) ***** assert (cdf ("Normal", x, 5, 2), normcdf (x, 5, 2)) ***** assert (cdf ("norm", x, 5, 2, "upper"), normcdf (x, 5, 2, "upper")) ***** assert (cdf ("Poisson", x, 5), poisscdf (x, 5)) ***** assert (cdf ("poiss", x, 5, "upper"), poisscdf (x, 5, "upper")) ***** assert (cdf ("Rayleigh", x, 5), raylcdf (x, 5)) ***** assert (cdf ("rayl", x, 5, "upper"), raylcdf (x, 5, "upper")) ***** assert (cdf ("Rician", x, 5, 1), ricecdf (x, 5, 1)) ***** assert (cdf ("rice", x, 5, 1, "upper"), ricecdf (x, 5, 1, "upper")) ***** assert (cdf ("Student T", x, 5), tcdf (x, 5)) ***** assert (cdf ("t", x, 5, "upper"), tcdf (x, 5, "upper")) ***** assert (cdf ("location-scale T", x, 5, 1, 2), tlscdf (x, 5, 1, 2)) ***** assert (cdf ("tls", x, 5, 1, 2, "upper"), tlscdf (x, 5, 1, 2, "upper")) ***** assert (cdf ("Triangular", x, 5, 2, 2), tricdf (x, 5, 2, 2)) ***** assert (cdf ("tri", x, 5, 2, 2, "upper"), tricdf (x, 5, 2, 2, "upper")) ***** assert (cdf ("Discrete Uniform", x, 5), unidcdf (x, 5)) ***** assert (cdf ("unid", x, 5, "upper"), unidcdf (x, 5, "upper")) ***** assert (cdf ("Uniform", x, 5, 2), unifcdf (x, 5, 2)) ***** assert (cdf ("unif", x, 5, 2, "upper"), unifcdf (x, 5, 2, "upper")) ***** assert (cdf ("Von Mises", x, 5, 2), vmcdf (x, 5, 2)) ***** assert (cdf ("vm", x, 5, 2, "upper"), vmcdf (x, 5, 2, "upper")) ***** assert (cdf ("Weibull", x, 5, 2), wblcdf (x, 5, 2)) ***** assert (cdf ("wbl", x, 5, 2, "upper"), wblcdf (x, 5, 2, "upper")) ***** error cdf (1) ***** error cdf ({"beta"}) ***** error cdf ("beta", {[1 2 3 4 5]}) ***** error cdf ("beta", "text") ***** error cdf ("beta", 1+i) ***** error ... cdf ("Beta", x, "a", 2) ***** error ... cdf ("Beta", x, 5, "") ***** error ... cdf ("Beta", x, 5, {2}) ***** error cdf ("chi2", x) ***** error cdf ("Beta", x, 5) ***** error cdf ("Burr", x, 5) ***** error cdf ("Burr", x, 5, 2) 86 tests, 86 passed, 0 known failure, 0 skipped [inst/dist_wrap/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/dendrogram.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/dendrogram.m ***** demo ## simple dendrogram y = [4, 5; 2, 6; 3, 7; 8, 9; 1, 10]; y(:,3) = 1:5; dendrogram (y); title ("simple dendrogram"); ***** demo ## another simple dendrogram v = 2 * rand (30, 1) - 1; d = abs (bsxfun (@minus, v(:, 1), v(:, 1)')); y = linkage (squareform (d, "tovector")); dendrogram (y); title ("another simple dendrogram"); ***** demo ## collapsed tree, find all the leaves of node 5 X = randn (60, 2); D = pdist (X); y = linkage (D, "average"); subplot (2, 1, 1); title ("original tree"); dendrogram (y, 0); subplot (2, 1, 2); title ("collapsed tree"); [~, t] = dendrogram (y, 20); find(t == 5) ***** demo ## optimal leaf order X = randn (30, 2); D = pdist (X); y = linkage (D, "average"); order = optimalleaforder (y, D); subplot (2, 1, 1); title ("original leaf order"); dendrogram (y); subplot (2, 1, 2); title ("optimal leaf order"); dendrogram (y, "Reorder", order); ***** demo ## horizontal orientation and labels X = randn (8, 2); D = pdist (X); L = ["Snow White"; "Doc"; "Grumpy"; "Happy"; "Sleepy"; "Bashful"; ... "Sneezy"; "Dopey"]; y = linkage (D, "average"); dendrogram (y, "Orientation", "left", "Labels", L); title ("horizontal orientation and labels"); ***** shared visibility_setting visibility_setting = get (0, "DefaultFigureVisible"); ***** test hf = figure ("visible", "off"); unwind_protect y = [4, 5; 2, 6; 3, 7; 8, 9; 1, 10]; y(:,3) = 1:5; dendrogram (y); unwind_protect_cleanup close (hf); end_unwind_protect ***** test hf = figure ("visible", "off"); unwind_protect y = [4, 5; 2, 6; 3, 7; 8, 9; 1, 10]; y(:,3) = 1:5; dendrogram (y); unwind_protect_cleanup close (hf); end_unwind_protect ***** test hf = figure ("visible", "off"); unwind_protect v = 2 * rand (30, 1) - 1; d = abs (bsxfun (@minus, v(:, 1), v(:, 1)')); y = linkage (squareform (d, "tovector")); dendrogram (y); unwind_protect_cleanup close (hf); end_unwind_protect ***** test hf = figure ("visible", "off"); unwind_protect X = randn (30, 2); D = pdist (X); y = linkage (D, "average"); order = optimalleaforder (y, D); subplot (2, 1, 1); title ("original leaf order"); dendrogram (y); subplot (2, 1, 2); title ("optimal leaf order"); dendrogram (y, "Reorder", order); unwind_protect_cleanup close (hf); end_unwind_protect ***** error dendrogram (); ***** error dendrogram (ones (2, 2), 1); ***** error dendrogram ([1 2 1], 1, "xxx", "xxx"); ***** error dendrogram ([1 2 1], "Reorder", "xxx"); ***** error dendrogram ([1 2 1], "Reorder", [1 2 3 4]); fail ('dendrogram ([1 2 1], "Orientation", "north")', "invalid orientation .*") 9 tests, 9 passed, 0 known failure, 0 skipped [inst/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/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/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/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/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/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/hnstat.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/dist_stat/hnstat.m ***** error hnstat () ***** error hnstat (1) ***** error hnstat ({}, 2) ***** error hnstat (1, "") ***** error hnstat (i, 2) ***** error hnstat (1, i) ***** error ... hnstat (ones (3), ones (2)) ***** error ... hnstat (ones (2), ones (3)) ***** test [m, v] = hnstat (0, 1); assert (m, 0.7979, 1e-4); assert (v, 0.3634, 1e-4); ***** test [m, v] = hnstat (2, 1); assert (m, 2.7979, 1e-4); assert (v, 0.3634, 1e-4); ***** test [m, v] = hnstat (2, 2); assert (m, 3.5958, 1e-4); assert (v, 1.4535, 1e-4); ***** test [m, v] = hnstat (2, 2.5); assert (m, 3.9947, 1e-4); assert (v, 2.2711, 1e-4); ***** test [m, v] = hnstat (1.5, 0.5); assert (m, 1.8989, 1e-4); assert (v, 0.0908, 1e-4); ***** test [m, v] = hnstat (-1.5, 0.5); assert (m, -1.1011, 1e-4); assert (v, 0.0908, 1e-4); 14 tests, 14 passed, 0 known failure, 0 skipped [inst/dist_stat/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/raylstat.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/dist_stat/raylstat.m ***** error raylstat () ***** error raylstat ({}) ***** error raylstat ("") ***** error raylstat (i) ***** test sigma = 1:6; [m, v] = raylstat (sigma); expected_m = [1.2533, 2.5066, 3.7599, 5.0133, 6.2666, 7.5199]; expected_v = [0.4292, 1.7168, 3.8628, 6.8673, 10.7301, 15.4513]; assert (m, expected_m, 0.001); assert (v, expected_v, 0.001); 5 tests, 5 passed, 0 known failure, 0 skipped [inst/dist_stat/gevstat.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/dist_stat/gevstat.m ***** error gevstat () ***** error gevstat (1) ***** error gevstat (1, 2) ***** error gevstat ({}, 2, 3) ***** error gevstat (1, "", 3) ***** error gevstat (1, 2, "") ***** error gevstat (i, 2, 3) ***** error gevstat (1, i, 3) ***** error gevstat (1, 2, i) ***** error ... gevstat (ones (3), ones (2), 3) ***** error ... gevstat (ones (2), 2, ones (3)) ***** error ... gevstat (1, ones (2), ones (3)) ***** test k = [-1, -0.5, 0, 0.2, 0.4, 0.5, 1]; sigma = 2; mu = 1; [m, v] = gevstat (k, sigma, mu); expected_m = [1, 1.4551, 2.1544, 2.6423, 3.4460, 4.0898, Inf]; expected_v = [4, 3.4336, 6.5797, 13.3761, 59.3288, Inf, Inf]; assert (m, expected_m, -0.001); assert (v, expected_v, -0.001); 13 tests, 13 passed, 0 known failure, 0 skipped [inst/dist_stat/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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.SsMo1UwVTS at line 1118 column 31 1 test, 1 passed, 0 known failure, 0 skipped [inst/Regression/RegressionGAM.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/Regression/RegressionGAM.m ***** demo ## Train a RegressionGAM Model for synthetic values f1 = @(x) cos (3 * x); f2 = @(x) x .^ 3; x1 = 2 * rand (50, 1) - 1; x2 = 2 * rand (50, 1) - 1; y = f1(x1) + f2(x2); y = y + y .* 0.2 .* rand (50,1); X = [x1, x2]; a = fitrgam (X, y, "tol", 1e-3) ***** demo ## Declare two different functions f1 = @(x) cos (3 * x); f2 = @(x) x .^ 3; ## Generate 80 samples for f1 and f2 x = [-4*pi:0.1*pi:4*pi-0.1*pi]'; X1 = f1 (x); X2 = f2 (x); ## Create a synthetic response by adding noise rand ("seed", 3); Ytrue = X1 + X2; Y = Ytrue + Ytrue .* 0.2 .* rand (80,1); ## Assemble predictor data X = [X1, X2]; ## Train the GAM and test on the same data a = fitrgam (X, Y, "order", [5, 5]); [ypred, ySDsd, yInt] = predict (a, X); ## Plot the results figure [sortedY, indY] = sort (Ytrue); plot (sortedY, "r-"); xlim ([0, 80]); hold on plot (ypred(indY), "g+") plot (yInt(indY,1), "k:") plot (yInt(indY,2), "k:") xlabel ("Predictor samples"); ylabel ("Response"); title ("actual vs predicted values for function f1(x) = cos (3x) "); legend ({"Theoretical Response", "Predicted Response", "Prediction Intervals"}); ## Use 30% Holdout partitioning for training and testing data C = cvpartition (80, "HoldOut", 0.3); [ypred, ySDsd, yInt] = predict (a, X(test(C),:)); ## Plot the results figure [sortedY, indY] = sort (Ytrue(test(C))); plot (sortedY, 'r-'); xlim ([0, sum(test(C))]); hold on plot (ypred(indY), "g+") plot (yInt(indY,1),'k:') plot (yInt(indY,2),'k:') xlabel ("Predictor samples"); ylabel ("Response"); title ("actual vs predicted values for function f1(x) = cos (3x) "); legend ({"Theoretical Response", "Predicted Response", "Prediction Intervals"}); ***** test x = [1, 2, 3; 4, 5, 6; 7, 8, 9; 3, 2, 1]; y = [1; 2; 3; 4]; a = RegressionGAM (x, y); assert ({a.X, a.Y}, {x, y}) assert ({a.BaseModel.Intercept}, {2.5000}) assert ({a.Knots, a.Order, a.DoF}, {[5, 5, 5], [3, 3, 3], [8, 8, 8]}) assert ({a.NumObservations, a.NumPredictors}, {4, 3}) assert ({a.ResponseName, a.PredictorNames}, {"Y", {"x1", "x2", "x3"}}) assert ({a.Formula}, {[]}) ***** test x = [1, 2, 3, 4; 4, 5, 6, 7; 7, 8, 9, 1; 3, 2, 1, 2]; y = [1; 2; 3; 4]; pnames = {"A", "B", "C", "D"}; formula = "Y ~ A + B + C + D + A:C"; intMat = logical ([1,0,0,0;0,1,0,0;0,0,1,0;0,0,0,1;1,0,1,0]); a = RegressionGAM (x, y, "predictors", pnames, "formula", formula); assert ({a.IntMatrix}, {intMat}) assert ({a.ResponseName, a.PredictorNames}, {"Y", pnames}) assert ({a.Formula}, {formula}) ***** error RegressionGAM () ***** error RegressionGAM (ones(10,2)) ***** error ... RegressionGAM (ones(10,2), ones (5,1)) ***** error ... RegressionGAM ([1;2;3;"a";4], ones (5,1)) ***** error ... RegressionGAM (ones(10,2), ones (10,1), "some", "some") ***** error RegressionGAM (ones(10,2), ones (10,1), "formula", {"y~x1+x2"}) ***** error RegressionGAM (ones(10,2), ones (10,1), "formula", [0, 1, 0]) ***** error ... RegressionGAM (ones(10,2), ones (10,1), "formula", "something") ***** error ... RegressionGAM (ones(10,2), ones (10,1), "formula", "something~") ***** error ... RegressionGAM (ones(10,2), ones (10,1), "formula", "something~") ***** error ... RegressionGAM (ones(10,2), ones (10,1), "formula", "something~x1:") ***** error ... RegressionGAM (ones(10,2), ones (10,1), "interactions", "some") ***** error ... RegressionGAM (ones(10,2), ones (10,1), "interactions", -1) ***** error ... RegressionGAM (ones(10,2), ones (10,1), "interactions", [1 2 3 4]) ***** error ... RegressionGAM (ones(10,2), ones (10,1), "interactions", 3) ***** error ... RegressionGAM (ones(10,2), ones (10,1), "formula", "y ~ x1 + x2", "interactions", 1) ***** error ... RegressionGAM (ones(10,2), ones (10,1), "interactions", 1, "formula", "y ~ x1 + x2") ***** error ... RegressionGAM (ones(10,2), ones (10,1), "knots", "a") ***** error ... RegressionGAM (ones(10,2), ones (10,1), "order", 3, "dof", 2, "knots", 5) ***** error ... RegressionGAM (ones(10,2), ones (10,1), "dof", 'a') ***** error ... RegressionGAM (ones(10,2), ones (10,1), "knots", 5, "order", 3, "dof", 2) ***** error ... RegressionGAM (ones(10,2), ones (10,1), "order", 'a') ***** error ... RegressionGAM (ones(10,2), ones (10,1), "knots", 5, "dof", 2, "order", 2) ***** error ... RegressionGAM (ones(10,2), ones (10,1), "tol", -1) ***** error ... RegressionGAM (ones(10,2), ones (10,1), "responsename", -1) ***** error ... RegressionGAM (ones(10,2), ones (10,1), "predictors", -1) ***** error ... RegressionGAM (ones(10,2), ones (10,1), "predictors", ['a','b','c']) ***** error ... RegressionGAM (ones(10,2), ones (10,1), "predictors", {'a','b','c'}) ***** error ... predict (RegressionGAM (ones(10,1), ones(10,1))) ***** error ... predict (RegressionGAM (ones(10,1), ones(10,1)), []) ***** error ... predict (RegressionGAM(ones(10,2), ones(10,1)), 2) ***** error ... predict (RegressionGAM(ones(10,2), ones(10,1)), ones (10,2), "some", "some") ***** error ... predict (RegressionGAM(ones(10,2), ones(10,1)), ones (10,2), "includeinteractions", "some") ***** error ... predict (RegressionGAM(ones(10,2), ones(10,1)), ones (10,2), "includeinteractions", 5) ***** error ... predict (RegressionGAM(ones(10,2), ones(10,1)), ones (10,2), "alpha", 5) ***** error ... predict (RegressionGAM(ones(10,2), ones(10,1)), ones (10,2), "alpha", -1) ***** error ... predict (RegressionGAM(ones(10,2), ones(10,1)), ones (10,2), "alpha", 'a') 39 tests, 39 passed, 0 known failure, 0 skipped [inst/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/wbllike.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/dist_fit/wbllike.m ***** test x = 1:50; [nlogL, acov] = wbllike ([2.3, 1.2], x); avar_out = [0.0250, 0.0062; 0.0062, 0.0017]; assert (nlogL, 945.9589180651594, 1e-12); assert (acov, avar_out, 1e-4); ***** test x = 1:50; [nlogL, acov] = wbllike ([2.3, 1.2], x * 0.5); avar_out = [-0.3238, -0.1112; -0.1112, -0.0376]; assert (nlogL, 424.9879809704742, 6e-14); assert (acov, avar_out, 1e-4); ***** test x = 1:50; [nlogL, acov] = wbllike ([21, 15], x); avar_out = [-0.00001236, -0.00001166; -0.00001166, -0.00001009]; assert (nlogL, 1635190.328991511, 1e-8); assert (acov, avar_out, 1e-8); ***** error wbllike ([12, 15]); ***** error wbllike ([12, 15, 3], [1:50]); ***** error wbllike ([12, 3], ones (10, 2)); ***** error wbllike ([12, 15], [1:50], [1, 2, 3]); ***** error wbllike ([12, 15], [1:50], [], [1, 2, 3]); ***** error ... wbllike ([12, 15], [1:5], [], [1, 2, 3, -1, 0]); 9 tests, 9 passed, 0 known failure, 0 skipped [inst/dist_fit/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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_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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/evcdf.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/dist_fun/evcdf.m ***** demo ## Plot various CDFs from the extreme value distribution x = -10:0.01:10; p1 = evcdf (x, 0.5, 2); p2 = evcdf (x, 1.0, 2); p3 = evcdf (x, 1.5, 3); p4 = evcdf (x, 3.0, 4); plot (x, p1, "-b", x, p2, "-g", x, p3, "-r", x, p4, "-c") grid on legend ({"μ = 0.5, σ = 2", "μ = 1.0, σ = 2", ... "μ = 1.5, σ = 3", "μ = 3.0, σ = 4"}, "location", "southeast") title ("Extreme value CDF") xlabel ("values in x") ylabel ("probability") ***** shared x, y x = [-Inf, 1, 2, Inf]; y = [0, 0.6321, 0.9340, 1]; ***** assert (evcdf (x, ones (1,4), ones (1,4)), y, 1e-4) ***** assert (evcdf (x, 1, ones (1,4)), y, 1e-4) ***** assert (evcdf (x, ones (1,4), 1), y, 1e-4) ***** assert (evcdf (x, [0, -Inf, NaN, Inf], 1), [0, 1, NaN, NaN], 1e-4) ***** assert (evcdf (x, 1, [Inf, NaN, -1, 0]), [NaN, NaN, NaN, NaN], 1e-4) ***** assert (evcdf ([x(1:2), NaN, x(4)], 1, 1), [y(1:2), NaN, y(4)], 1e-4) ***** assert (evcdf (x, "upper"), [1, 0.0660, 0.0006, 0], 1e-4) ***** assert (evcdf ([x, NaN], 1, 1), [y, NaN], 1e-4) ***** assert (evcdf (single ([x, NaN]), 1, 1), single ([y, NaN]), 1e-4) ***** assert (evcdf ([x, NaN], single (1), 1), single ([y, NaN]), 1e-4) ***** assert (evcdf ([x, NaN], 1, single (1)), single ([y, NaN]), 1e-4) ***** error evcdf () ***** error evcdf (1,2,3,4,5,6,7) ***** error evcdf (1, 2, 3, 4, "uper") ***** error ... evcdf (ones (3), ones (2), ones (2)) ***** error evcdf (2, 3, 4, [1, 2]) ***** error ... [p, plo, pup] = evcdf (1, 2, 3) ***** error [p, plo, pup] = ... evcdf (1, 2, 3, [1, 0; 0, 1], 0) ***** error [p, plo, pup] = ... evcdf (1, 2, 3, [1, 0; 0, 1], 1.22) ***** error [p, plo, pup] = ... evcdf (1, 2, 3, [1, 0; 0, 1], "alpha", "upper") ***** error evcdf (i, 2, 2) ***** error evcdf (2, i, 2) ***** error evcdf (2, 2, i) ***** error ... [p, plo, pup] = evcdf (1, 2, 3, [1, 0; 0, -inf], 0.04) 24 tests, 24 passed, 0 known failure, 0 skipped [inst/dist_fun/tcdf.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/dist_fun/tcdf.m ***** demo ## Plot various CDFs from the Student's T distribution x = -5:0.01:5; p1 = tcdf (x, 1); p2 = tcdf (x, 2); p3 = tcdf (x, 5); p4 = tcdf (x, Inf); plot (x, p1, "-b", x, p2, "-g", x, p3, "-r", x, p4, "-m") grid on xlim ([-5, 5]) ylim ([0, 1]) legend ({"df = 1", "df = 2", ... "df = 5", 'df = \infty'}, "location", "southeast") title ("Student's T CDF") xlabel ("values in x") ylabel ("probability") ***** shared x,y x = [-Inf 0 1 Inf]; y = [0 1/2 3/4 1]; ***** assert (tcdf (x, ones (1,4)), y, eps) ***** assert (tcdf (x, 1), y, eps) ***** assert (tcdf (x, [0 1 NaN 1]), [NaN 1/2 NaN 1], eps) ***** assert (tcdf ([x(1:2) NaN x(4)], 1), [y(1:2) NaN y(4)], eps) ***** assert (tcdf (2, 3, "upper"), 0.0697, 1e-4) ***** assert (tcdf (205, 5, "upper"), 2.6206e-11, 1e-14) ***** assert (tcdf ([x, NaN], 1), [y, NaN], eps) ***** assert (tcdf (single ([x, NaN]), 1), single ([y, NaN]), eps ("single")) ***** assert (tcdf ([x, NaN], single (1)), single ([y, NaN]), eps ("single")) ***** error tcdf () ***** error tcdf (1) ***** error tcdf (1, 2, "uper") ***** error tcdf (1, 2, 3) ***** error ... tcdf (ones (3), ones (2)) ***** error ... tcdf (ones (3), ones (2)) ***** error ... tcdf (ones (3), ones (2), "upper") ***** error tcdf (i, 2) ***** error tcdf (2, i) ***** shared tol_rel tol_rel = 10 * eps; ***** assert (tcdf (10^(-10), 2.5), 0.50000000003618087, -tol_rel) ***** assert (tcdf (10^(-11), 2.5), 0.50000000000361809, -tol_rel) ***** assert (tcdf (10^(-12), 2.5), 0.50000000000036181, -tol_rel) ***** assert (tcdf (10^(-13), 2.5), 0.50000000000003618, -tol_rel) ***** assert (tcdf (10^(-14), 2.5), 0.50000000000000362, -tol_rel) ***** assert (tcdf (10^(-15), 2.5), 0.50000000000000036, -tol_rel) ***** assert (tcdf (10^(-16), 2.5), 0.50000000000000004, -tol_rel) ***** assert (tcdf (-10^1, 2.5), 2.2207478836537124e-03, -tol_rel) ***** assert (tcdf (-10^2, 2.5), 7.1916492116661878e-06, -tol_rel) ***** assert (tcdf (-10^3, 2.5), 2.2747463948307452e-08, -tol_rel) ***** assert (tcdf (-10^4, 2.5), 7.1933970159922115e-11, -tol_rel) ***** assert (tcdf (-10^5, 2.5), 2.2747519231756221e-13, -tol_rel) 30 tests, 30 passed, 0 known failure, 0 skipped [inst/dist_fun/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/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/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/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/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/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/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/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/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/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/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/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/nbininv.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/dist_fun/nbininv.m ***** demo ## Plot various iCDFs from the negative binomial distribution p = 0.001:0.001:0.999; x1 = nbininv (p, 2, 0.15); x2 = nbininv (p, 5, 0.2); x3 = nbininv (p, 4, 0.4); x4 = nbininv (p, 10, 0.3); plot (p, x1, "-r", p, x2, "-g", p, x3, "-k", p, x4, "-m") grid on ylim ([0, 40]) legend ({"r = 2, ps = 0.15", "r = 5, ps = 0.2", "r = 4, p = 0.4", ... "r = 10, ps = 0.3"}, "location", "northwest") title ("Negative binomial iCDF") xlabel ("probability") ylabel ("values in x (number of failures)") ***** shared p p = [-1 0 3/4 1 2]; ***** assert (nbininv (p, ones (1,5), 0.5*ones (1,5)), [NaN 0 1 Inf NaN]) ***** assert (nbininv (p, 1, 0.5*ones (1,5)), [NaN 0 1 Inf NaN]) ***** assert (nbininv (p, ones (1,5), 0.5), [NaN 0 1 Inf NaN]) ***** assert (nbininv (p, [1 0 NaN Inf 1], 0.5), [NaN NaN NaN NaN NaN]) ***** assert (nbininv (p, [1 0 1.5 Inf 1], 0.5), [NaN NaN 2 NaN NaN]) ***** assert (nbininv (p, 1, 0.5*[1 -Inf NaN Inf 1]), [NaN NaN NaN NaN NaN]) ***** assert (nbininv ([p(1:2) NaN p(4:5)], 1, 0.5), [NaN 0 NaN Inf NaN]) ***** assert (nbininv ([p, NaN], 1, 0.5), [NaN 0 1 Inf NaN NaN]) ***** assert (nbininv (single ([p, NaN]), 1, 0.5), single ([NaN 0 1 Inf NaN NaN])) ***** assert (nbininv ([p, NaN], single (1), 0.5), single ([NaN 0 1 Inf NaN NaN])) ***** assert (nbininv ([p, NaN], 1, single (0.5)), single ([NaN 0 1 Inf NaN NaN])) ***** shared y, tol y = magic (3) + 1; tol = 1; ***** assert (nbininv (nbincdf (1:10, 3, 0.1), 3, 0.1), 1:10, tol) ***** assert (nbininv (nbincdf (1:10, 3./(1:10), 0.1), 3./(1:10), 0.1), 1:10, tol) ***** assert (nbininv (nbincdf (y, 3./y, 1./y), 3./y, 1./y), y, tol) ***** error nbininv () ***** error nbininv (1) ***** error nbininv (1, 2) ***** error ... nbininv (ones (3), ones (2), ones (2)) ***** error ... nbininv (ones (2), ones (3), ones (2)) ***** error ... nbininv (ones (2), ones (2), ones (3)) ***** error nbininv (i, 2, 2) ***** error nbininv (2, i, 2) ***** error nbininv (2, 2, i) 23 tests, 23 passed, 0 known failure, 0 skipped [inst/dist_fun/gumbelcdf.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/dist_fun/gumbelcdf.m ***** demo ## Plot various CDFs from the Gumbel distribution x = -5:0.01:20; p1 = gumbelcdf (x, 0.5, 2); p2 = gumbelcdf (x, 1.0, 2); p3 = gumbelcdf (x, 1.5, 3); p4 = gumbelcdf (x, 3.0, 4); plot (x, p1, "-b", x, p2, "-g", x, p3, "-r", x, p4, "-c") grid on legend ({"μ = 0.5, β = 2", "μ = 1.0, β = 2", ... "μ = 1.5, β = 3", "μ = 3.0, β = 4"}, "location", "southeast") title ("Gumbel CDF") xlabel ("values in x") ylabel ("probability") ***** shared x, y x = [-Inf, 1, 2, Inf]; y = [0, 0.3679, 0.6922, 1]; ***** assert (gumbelcdf (x, ones (1,4), ones (1,4)), y, 1e-4) ***** assert (gumbelcdf (x, 1, ones (1,4)), y, 1e-4) ***** assert (gumbelcdf (x, ones (1,4), 1), y, 1e-4) ***** assert (gumbelcdf (x, [0, -Inf, NaN, Inf], 1), [0, 1, NaN, NaN], 1e-4) ***** assert (gumbelcdf (x, 1, [Inf, NaN, -1, 0]), [NaN, NaN, NaN, NaN], 1e-4) ***** assert (gumbelcdf ([x(1:2), NaN, x(4)], 1, 1), [y(1:2), NaN, y(4)], 1e-4) ***** assert (gumbelcdf (x, "upper"), [1, 0.3078, 0.1266, 0], 1e-4) ***** assert (gumbelcdf ([x, NaN], 1, 1), [y, NaN], 1e-4) ***** assert (gumbelcdf (single ([x, NaN]), 1, 1), single ([y, NaN]), 1e-4) ***** assert (gumbelcdf ([x, NaN], single (1), 1), single ([y, NaN]), 1e-4) ***** assert (gumbelcdf ([x, NaN], 1, single (1)), single ([y, NaN]), 1e-4) ***** error gumbelcdf () ***** error gumbelcdf (1,2,3,4,5,6,7) ***** error gumbelcdf (1, 2, 3, 4, "uper") ***** error ... gumbelcdf (ones (3), ones (2), ones (2)) ***** error gumbelcdf (2, 3, 4, [1, 2]) ***** error ... [p, plo, pup] = gumbelcdf (1, 2, 3) ***** error [p, plo, pup] = ... gumbelcdf (1, 2, 3, [1, 0; 0, 1], 0) ***** error [p, plo, pup] = ... gumbelcdf (1, 2, 3, [1, 0; 0, 1], 1.22) ***** error [p, plo, pup] = ... gumbelcdf (1, 2, 3, [1, 0; 0, 1], "alpha", "upper") ***** error gumbelcdf (i, 2, 2) ***** error gumbelcdf (2, i, 2) ***** error gumbelcdf (2, 2, i) ***** error ... [p, plo, pup] = gumbelcdf (1, 2, 3, [1, 0; 0, -inf], 0.04) 24 tests, 24 passed, 0 known failure, 0 skipped [inst/dist_fun/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/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/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/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/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/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/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/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/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/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/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/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/unifinv.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/dist_fun/unifinv.m ***** demo ## Plot various iCDFs from the continuous uniform distribution p = 0.001:0.001:0.999; x1 = unifinv (p, 2, 5); x2 = unifinv (p, 3, 9); plot (p, x1, "-b", p, x2, "-g") grid on xlim ([0, 1]) ylim ([0, 10]) legend ({"a = 2, b = 5", "a = 3, b = 9"}, "location", "northwest") title ("Continuous uniform iCDF") xlabel ("probability") ylabel ("values in x") ***** shared p p = [-1 0 0.5 1 2]; ***** assert (unifinv (p, ones (1,5), 2*ones (1,5)), [NaN 1 1.5 2 NaN]) ***** assert (unifinv (p, 0, 1), [NaN 1 1.5 2 NaN] - 1) ***** assert (unifinv (p, 1, 2*ones (1,5)), [NaN 1 1.5 2 NaN]) ***** assert (unifinv (p, ones (1,5), 2), [NaN 1 1.5 2 NaN]) ***** assert (unifinv (p, [1 2 NaN 1 1], 2), [NaN NaN NaN 2 NaN]) ***** assert (unifinv (p, 1, 2*[1 0 NaN 1 1]), [NaN NaN NaN 2 NaN]) ***** assert (unifinv ([p(1:2) NaN p(4:5)], 1, 2), [NaN 1 NaN 2 NaN]) ***** assert (unifinv ([p, NaN], 1, 2), [NaN 1 1.5 2 NaN NaN]) ***** assert (unifinv (single ([p, NaN]), 1, 2), single ([NaN 1 1.5 2 NaN NaN])) ***** assert (unifinv ([p, NaN], single (1), 2), single ([NaN 1 1.5 2 NaN NaN])) ***** assert (unifinv ([p, NaN], 1, single (2)), single ([NaN 1 1.5 2 NaN NaN])) ***** error unifinv () ***** error unifinv (1, 2) ***** error ... unifinv (ones (3), ones (2), ones (2)) ***** error ... unifinv (ones (2), ones (3), ones (2)) ***** error ... unifinv (ones (2), ones (2), ones (3)) ***** error unifinv (i, 2, 2) ***** error unifinv (2, i, 2) ***** error unifinv (2, 2, i) 19 tests, 19 passed, 0 known failure, 0 skipped [inst/dist_fun/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/standardizeMissing.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/standardizeMissing.m ***** assert (standardizeMissing (1, 1), NaN) ***** assert (standardizeMissing (1, 0), 1) ***** assert (standardizeMissing (eye(2), 1), [NaN 0;0 NaN]) ***** assert (standardizeMissing ([1:3;4:6], [2 3; 4 5]), [1, NaN, NaN; NaN, NaN, 6]) ***** assert (standardizeMissing (cat (3,1,2,3,4), 3), cat (3,1,2,NaN,4)) ***** assert (standardizeMissing ('foo', 'a'), 'foo') ***** assert (standardizeMissing ('foo', 'f'), ' oo') ***** assert (standardizeMissing ('foo', 'o'), 'f ') ***** assert (standardizeMissing ('foo', 'oo'), 'f ') ***** assert (standardizeMissing ({'foo'}, 'f'), {'foo'}) ***** assert (standardizeMissing ({'foo'}, {'f'}), {'foo'}) ***** assert (standardizeMissing ({'foo'}, 'test'), {'foo'}) ***** assert (standardizeMissing ({'foo'}, {'test'}), {'foo'}) ***** assert (standardizeMissing ({'foo'}, 'foo'), {''}) ***** assert (standardizeMissing ({'foo'}, {'foo'}), {''}) ***** assert (standardizeMissing (['foo';'bar'], 'oar'), ['f ';'b ']) ***** assert (standardizeMissing (['foo';'bar'], ['o';'a';'r']), ['f ';'b ']) ***** assert (standardizeMissing (['foo';'bar'], ['o ';'ar']), ['f ';'b ']) ***** assert (standardizeMissing ({'foo','bar'}, 'foo'), {'','bar'}) ***** assert (standardizeMissing ({'foo','bar'}, 'f'), {'foo','bar'}) ***** assert (standardizeMissing ({'foo','bar'}, {'foo', 'a'}), {'','bar'}) ***** assert (standardizeMissing ({'foo'}, {'f', 'oo'}), {'foo'}) ***** assert (standardizeMissing ({'foo','bar'}, {'foo'}), {'','bar'}) ***** assert (standardizeMissing ({'foo','bar'}, {'foo', 'a'}), {'','bar'}) ***** assert (standardizeMissing (double (1), single (1)), double (NaN)) ***** assert (standardizeMissing (single (1), single (1)), single (NaN)) ***** assert (standardizeMissing (single (1), double (1)), single (NaN)) ***** assert (standardizeMissing (single (1), true), single (NaN)) ***** assert (standardizeMissing (double (1), int32(1)), double (NaN)) ***** assert (standardizeMissing (true, true), true) ***** assert (standardizeMissing (true, 1), true) ***** assert (standardizeMissing (int32 (1), int32 (1)), int32 (1)) ***** assert (standardizeMissing (int32 (1), 1), int32 (1)) ***** assert (standardizeMissing (uint32 (1), uint32 (1)), uint32 (1)) ***** assert (standardizeMissing (uint32 (1), 1), uint32 (1)) ***** error standardizeMissing (); ***** error standardizeMissing (1); ***** error standardizeMissing (1,2,3); ***** error standardizeMissing ({'abc', 1}, 1); ***** error standardizeMissing (struct ('a','b'), 1); ***** error <'indicator' and 'A' must have > standardizeMissing ([1 2 3], {1}); ***** error <'indicator' and 'A' must have > standardizeMissing ([1 2 3], 'a'); ***** error <'indicator' and 'A' must have > standardizeMissing ([1 2 3], struct ('a', 1)); ***** error <'indicator' and 'A' must have > standardizeMissing ('foo', 1); ***** error <'indicator' and 'A' must have > standardizeMissing ('foo', {1}); ***** error <'indicator' and 'A' must have > standardizeMissing ('foo', {'f'}); ***** error <'indicator' and 'A' must have > standardizeMissing ('foo', struct ('a', 1)); ***** error <'indicator' and 'A' must have > standardizeMissing ({'foo'}, 1); ***** error <'indicator' and 'A' must have > standardizeMissing ({'foo'}, 1); 49 tests, 49 passed, 0 known failure, 0 skipped [inst/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/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/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/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/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/regression_ftest.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/regression_ftest.m ***** error regression_ftest (); ***** error ... regression_ftest ([1 2 3]', [2 3 4; 3 4 5]'); ***** error ... regression_ftest ([1 2 NaN]', [2 3 4; 3 4 5]', [1 0.5]); ***** error ... regression_ftest ([1 2 Inf]', [2 3 4; 3 4 5]', [1 0.5]); ***** error ... regression_ftest ([1 2 3+i]', [2 3 4; 3 4 5]', [1 0.5]); ***** error ... regression_ftest ([1 2 3]', [2 3 NaN; 3 4 5]', [1 0.5]); ***** error ... regression_ftest ([1 2 3]', [2 3 Inf; 3 4 5]', [1 0.5]); ***** error ... regression_ftest ([1 2 3]', [2 3 4; 3 4 3+i]', [1 0.5]); ***** error ... regression_ftest ([1 2 3]', [2 3 4; 3 4 5]', [1 0.5], [], "alpha", 0); ***** error ... regression_ftest ([1 2 3]', [2 3 4; 3 4 5]', [1 0.5], [], "alpha", 1.2); ***** error ... regression_ftest ([1 2 3]', [2 3 4; 3 4 5]', [1 0.5], [], "alpha", [.02 .1]); ***** error ... regression_ftest ([1 2 3]', [2 3 4; 3 4 5]', [1 0.5], [], "alpha", "a"); ***** error ... regression_ftest ([1 2 3]', [2 3 4; 3 4 5]', [1 0.5], [], "some", 0.05); ***** error ... regression_ftest ([1 2 3]', [2 3; 3 4]', [1 0.5]); ***** error ... regression_ftest ([1 2; 3 4]', [2 3; 3 4]', [1 0.5]); ***** error ... regression_ftest ([1 2 3]', [2 3 4; 3 4 5]', [1 0.5], ones (2)); ***** error ... regression_ftest ([1 2 3]', [2 3 4; 3 4 5]', [1 0.5], "alpha"); ***** error ... regression_ftest ([1 2 3]', [2 3 4; 3 4 5]', [1 0.5], [1 2]); 18 tests, 18 passed, 0 known failure, 0 skipped [inst/pdist.m] >>>>> /build/reproducible-path/octave-statistics-1.6.5/inst/pdist.m ***** shared xy, t, eucl, x xy = [0 1; 0 2; 7 6; 5 6]; t = 1e-3; eucl = @(v,m) sqrt(sumsq(repmat(v,rows(m),1)-m,2)); x = [1 2 3; 4 5 6; 7 8 9; 3 2 1]; ***** assert (pdist (xy), [1.000 8.602 7.071 8.062 6.403 2.000], t); ***** assert (pdist (xy, eucl), [1.000 8.602 7.071 8.062 6.403 2.000], t); ***** assert (pdist (xy, "euclidean"), [1.000 8.602 7.071 8.062 6.403 2.000], t); ***** assert (pdist (xy, "seuclidean"), [0.380 2.735 2.363 2.486 2.070 0.561], t); ***** assert (pdist (xy, "mahalanobis"), [1.384 1.967 2.446 2.384 1.535 2.045], t); ***** assert (pdist (xy, "cityblock"), [1.000 12.00 10.00 11.00 9.000 2.000], t); ***** assert (pdist (xy, "minkowski"), [1.000 8.602 7.071 8.062 6.403 2.000], t); ***** assert (pdist (xy, "minkowski", 3), [1.000 7.763 6.299 7.410 5.738 2.000], t); ***** assert (pdist (xy, "cosine"), [0.000 0.349 0.231 0.349 0.231 0.013], t); ***** assert (pdist (xy, "correlation"), [0.000 2.000 0.000 2.000 0.000 2.000], t); ***** assert (pdist (xy, "spearman"), [0.000 2.000 0.000 2.000 0.000 2.000], t); ***** assert (pdist (xy, "hamming"), [0.500 1.000 1.000 1.000 1.000 0.500], t); ***** assert (pdist (xy, "jaccard"), [1.000 1.000 1.000 1.000 1.000 0.500], t); ***** assert (pdist (xy, "chebychev"), [1.000 7.000 5.000 7.000 5.000 2.000], t); ***** assert (pdist (x), [5.1962, 10.3923, 2.8284, 5.1962, 5.9161, 10.7703], 1e-4); ***** assert (pdist (x, "euclidean"), ... [5.1962, 10.3923, 2.8284, 5.1962, 5.9161, 10.7703], 1e-4); ***** assert (pdist (x, eucl), ... [5.1962, 10.3923, 2.8284, 5.1962, 5.9161, 10.7703], 1e-4); ***** assert (pdist (x, "squaredeuclidean"), [27, 108, 8, 27, 35, 116]); ***** assert (pdist (x, "seuclidean"), ... [1.8071, 3.6142, 0.9831, 1.8071, 1.8143, 3.4854], 1e-4); ***** warning ... pdist (x, "mahalanobis"); ***** assert (pdist (x, "cityblock"), [9, 18, 4, 9, 9, 18]); ***** assert (pdist (x, "minkowski"), ... [5.1962, 10.3923, 2.8284, 5.1962, 5.9161, 10.7703], 1e-4); ***** assert (pdist (x, "minkowski", 3), ... [4.3267, 8.6535, 2.5198, 4.3267, 5.3485, 9.2521], 1e-4); ***** assert (pdist (x, "cosine"), ... [0.0254, 0.0406, 0.2857, 0.0018, 0.1472, 0.1173], 1e-4); ***** assert (pdist (x, "correlation"), [0, 0, 2, 0, 2, 2], 1e-14); ***** assert (pdist (x, "spearman"), [0, 0, 2, 0, 2, 2], 1e-14); ***** assert (pdist (x, "hamming"), [1, 1, 2/3, 1, 1, 1]); ***** assert (pdist (x, "jaccard"), [1, 1, 2/3, 1, 1, 1]); ***** assert (pdist (x, "chebychev"), [3, 6, 2, 3, 5, 8]); 29 tests, 29 passed, 0 known failure, 0 skipped [inst/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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/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 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/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 [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 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' in '../octave-statistics_1.6.5-3_armhf.deb'. dpkg-deb: building package 'octave-statistics-common' in '../octave-statistics-common_1.6.5-3_all.deb'. dpkg-deb: building package 'octave-statistics-dbgsym' in '../octave-statistics-dbgsym_1.6.5-3_armhf.deb'. dpkg-genbuildinfo --build=binary -O../octave-statistics_1.6.5-3_armhf.buildinfo dpkg-genchanges --build=binary -O../octave-statistics_1.6.5-3_armhf.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/24856 and its subdirectories I: Current time: Wed Apr 3 12:47:14 -12 2024 I: pbuilder-time-stamp: 1712191634 Thu Apr 4 00:47:52 UTC 2024 I: 1st build successful. Starting 2nd build on remote node virt32c-armhf-rb.debian.net. Thu Apr 4 00:47:52 UTC 2024 I: Preparing to do remote build '2' on virt32c-armhf-rb.debian.net. Thu Apr 4 01:16:00 UTC 2024 I: Deleting $TMPDIR on virt32c-armhf-rb.debian.net. Thu Apr 4 01:16:03 UTC 2024 I: octave-statistics_1.6.5-3_armhf.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 armhf 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 168efbcf0b0ecc9bb189aa1d3db24953dab2ee8d 1317940 octave-statistics-dbgsym_1.6.5-3_armhf.deb 611a1af040119d95f1596b618e8e28d2b228dbb5 21944 octave-statistics_1.6.5-3_armhf.buildinfo 16c47abcaef3caae29b4f274c518d205d77df870 68052 octave-statistics_1.6.5-3_armhf.deb Checksums-Sha256: b1a82de3c817da8122706b53386734f730fdd458bb5e2983919f53316a7d300b 7024004 octave-statistics-common_1.6.5-3_all.deb df6235bf6836b021e0854ec030b3d65674953f121ad12554257ba0536de87446 1317940 octave-statistics-dbgsym_1.6.5-3_armhf.deb 1bb670023c185f9cfd7f748dc4ebf56385f9933092f1a7b86339aef3f3253875 21944 octave-statistics_1.6.5-3_armhf.buildinfo f48c14bd5de41f2d2537c947f7ddebc17759cca55637f7ea679c196bae6a8093 68052 octave-statistics_1.6.5-3_armhf.deb Files: 6a73a35751bc15cf23ca6d156080c82b 7024004 math optional octave-statistics-common_1.6.5-3_all.deb 88da18e958db8d3f03bcd475cf26ed40 1317940 debug optional octave-statistics-dbgsym_1.6.5-3_armhf.deb c4b1e57148b71f51c1a21010f86b94a9 21944 math optional octave-statistics_1.6.5-3_armhf.buildinfo 6a620c8bf0a486b8cdb09c919c30278d 68052 math optional octave-statistics_1.6.5-3_armhf.deb Thu Apr 4 01:16:06 UTC 2024 I: diffoscope 262 will be used to compare the two builds: Running as unit: rb-diffoscope-armhf_32-12348.service # Profiling output for: /usr/bin/diffoscope --timeout 7200 --html /srv/reproducible-results/rbuild-debian/r-b-build.NgTE4E7g/octave-statistics_1.6.5-3.diffoscope.html --text /srv/reproducible-results/rbuild-debian/r-b-build.NgTE4E7g/octave-statistics_1.6.5-3.diffoscope.txt --json /srv/reproducible-results/rbuild-debian/r-b-build.NgTE4E7g/octave-statistics_1.6.5-3.diffoscope.json --profile=- /srv/reproducible-results/rbuild-debian/r-b-build.NgTE4E7g/b1/octave-statistics_1.6.5-3_armhf.changes /srv/reproducible-results/rbuild-debian/r-b-build.NgTE4E7g/b2/octave-statistics_1.6.5-3_armhf.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: 0.411s) 0.411s 2 calls outputs 0.000s 1 call cleanup ## recognizes (total time: 0.102s) 0.102s 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: 710ms CPU time consumed: 709ms Thu Apr 4 01:16:08 UTC 2024 I: diffoscope 262 found no differences in the changes files, and a .buildinfo file also exists. Thu Apr 4 01:16:08 UTC 2024 I: octave-statistics from trixie built successfully and reproducibly on armhf. Thu Apr 4 01:16:10 UTC 2024 I: Submitting .buildinfo files to external archives: Thu Apr 4 01:16:10 UTC 2024 I: Submitting 24K b1/octave-statistics_1.6.5-3_armhf.buildinfo.asc Thu Apr 4 01:16:11 UTC 2024 I: Submitting 24K b2/octave-statistics_1.6.5-3_armhf.buildinfo.asc Thu Apr 4 01:16:12 UTC 2024 I: Done submitting .buildinfo files to http://buildinfo.debian.net/api/submit. Thu Apr 4 01:16:12 UTC 2024 I: Done submitting .buildinfo files. Thu Apr 4 01:16:12 UTC 2024 I: Removing signed octave-statistics_1.6.5-3_armhf.buildinfo.asc files: removed './b1/octave-statistics_1.6.5-3_armhf.buildinfo.asc' removed './b2/octave-statistics_1.6.5-3_armhf.buildinfo.asc'