0s autopkgtest [19:59:08]: starting date and time: 2024-03-16 19:59:08+0000 0s autopkgtest [19:59:08]: git checkout: b506e79c ssh-setup/nova: fix ARCH having two lines of data 0s autopkgtest [19:59:08]: host juju-7f2275-prod-proposed-migration-environment-2; command line: /home/ubuntu/autopkgtest/runner/autopkgtest --output-dir /tmp/autopkgtest-work.pvkmycr8/out --timeout-copy=6000 --setup-commands /home/ubuntu/autopkgtest-cloud/worker-config-production/setup-canonical.sh --apt-pocket=proposed=src:r-base,src:curl,src:glib2.0,src:libpng1.6,src:libpsl,src:libtirpc,src:libxt,src:openssl,src:orthanc-python,src:readline,src:wp2latex --apt-upgrade r-cran-rrcov --timeout-short=300 --timeout-copy=20000 --timeout-build=20000 '--env=ADT_TEST_TRIGGERS=r-base/4.3.3-2build1 curl/8.5.0-2ubuntu7 glib2.0/2.79.3-3ubuntu5 libpng1.6/1.6.43-3 libpsl/0.21.2-1.1 libtirpc/1.3.4+ds-1.1 libxt/1:1.2.1-1.2 openssl/3.0.13-0ubuntu1 orthanc-python/4.1+ds-2build3 readline/8.2-3.1 wp2latex/4.4~ds-1build1' -- ssh -s /home/ubuntu/autopkgtest/ssh-setup/nova -- --flavor autopkgtest --security-groups autopkgtest-juju-7f2275-prod-proposed-migration-environment-2@bos03-arm64-9.secgroup --name adt-noble-arm64-r-cran-rrcov-20240316-195908-juju-7f2275-prod-proposed-migration-environment-2 --image adt/ubuntu-noble-arm64-server --keyname testbed-juju-7f2275-prod-proposed-migration-environment-2 --net-id=net_prod-proposed-migration -e TERM=linux -e ''"'"'http_proxy=http://squid.internal:3128'"'"'' -e ''"'"'https_proxy=http://squid.internal:3128'"'"'' -e ''"'"'no_proxy=127.0.0.1,127.0.1.1,login.ubuntu.com,localhost,localdomain,novalocal,internal,archive.ubuntu.com,ports.ubuntu.com,security.ubuntu.com,ddebs.ubuntu.com,changelogs.ubuntu.com,launchpadlibrarian.net,launchpadcontent.net,launchpad.net,10.24.0.0/24,keystone.ps5.canonical.com,objectstorage.prodstack5.canonical.com'"'"'' --mirror=http://ftpmaster.internal/ubuntu/ 147s autopkgtest [20:01:35]: testbed dpkg architecture: arm64 147s autopkgtest [20:01:35]: testbed apt version: 2.7.12 147s autopkgtest [20:01:35]: @@@@@@@@@@@@@@@@@@@@ test bed setup 147s Get:1 http://ftpmaster.internal/ubuntu noble-proposed InRelease [117 kB] 148s Get:2 http://ftpmaster.internal/ubuntu noble-proposed/main Sources [474 kB] 148s Get:3 http://ftpmaster.internal/ubuntu noble-proposed/restricted Sources [6540 B] 148s Get:4 http://ftpmaster.internal/ubuntu noble-proposed/universe Sources [3704 kB] 148s Get:5 http://ftpmaster.internal/ubuntu noble-proposed/multiverse Sources [51.4 kB] 148s Get:6 http://ftpmaster.internal/ubuntu noble-proposed/main arm64 Packages [646 kB] 148s Get:7 http://ftpmaster.internal/ubuntu noble-proposed/main arm64 c-n-f Metadata [3144 B] 148s Get:8 http://ftpmaster.internal/ubuntu noble-proposed/restricted arm64 Packages [33.6 kB] 148s Get:9 http://ftpmaster.internal/ubuntu noble-proposed/restricted arm64 c-n-f Metadata [116 B] 148s Get:10 http://ftpmaster.internal/ubuntu noble-proposed/universe arm64 Packages [4012 kB] 148s Get:11 http://ftpmaster.internal/ubuntu noble-proposed/universe arm64 c-n-f Metadata [8528 B] 148s Get:12 http://ftpmaster.internal/ubuntu noble-proposed/multiverse arm64 Packages [55.5 kB] 148s Get:13 http://ftpmaster.internal/ubuntu noble-proposed/multiverse arm64 c-n-f Metadata [116 B] 152s Fetched 9112 kB in 3s (3145 kB/s) 152s Reading package lists... 155s Reading package lists... 155s Building dependency tree... 155s Reading state information... 155s Calculating upgrade... 156s The following packages will be REMOVED: 156s libglib2.0-0 libssl3 156s The following NEW packages will be installed: 156s libglib2.0-0t64 libssl3t64 xdg-user-dirs 156s The following packages have been kept back: 156s curl 156s The following packages will be upgraded: 156s gir1.2-glib-2.0 libglib2.0-data libtirpc-common openssl readline-common 156s ubuntu-minimal ubuntu-standard 156s 7 upgraded, 3 newly installed, 2 to remove and 1 not upgraded. 156s Need to get 4613 kB of archives. 156s After this operation, 211 kB of additional disk space will be used. 156s Get:1 http://ftpmaster.internal/ubuntu noble-proposed/main arm64 gir1.2-glib-2.0 arm64 2.79.3-3ubuntu5 [182 kB] 156s Get:2 http://ftpmaster.internal/ubuntu noble-proposed/main arm64 libglib2.0-0t64 arm64 2.79.3-3ubuntu5 [1527 kB] 156s Get:3 http://ftpmaster.internal/ubuntu noble-proposed/main arm64 openssl arm64 3.0.13-0ubuntu1 [983 kB] 157s Get:4 http://ftpmaster.internal/ubuntu noble-proposed/main arm64 libssl3t64 arm64 3.0.13-0ubuntu1 [1770 kB] 157s Get:5 http://ftpmaster.internal/ubuntu noble-proposed/main arm64 libglib2.0-data all 2.79.3-3ubuntu5 [46.6 kB] 157s Get:6 http://ftpmaster.internal/ubuntu noble-proposed/main arm64 libtirpc-common all 1.3.4+ds-1.1 [8018 B] 157s Get:7 http://ftpmaster.internal/ubuntu noble-proposed/main arm64 readline-common all 8.2-3.1 [56.4 kB] 157s Get:8 http://ftpmaster.internal/ubuntu noble/main arm64 ubuntu-minimal arm64 1.536 [10.7 kB] 157s Get:9 http://ftpmaster.internal/ubuntu noble/main arm64 xdg-user-dirs arm64 0.18-1 [18.1 kB] 157s Get:10 http://ftpmaster.internal/ubuntu noble/main arm64 ubuntu-standard arm64 1.536 [10.7 kB] 157s Fetched 4613 kB in 1s (5995 kB/s) 158s (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 ... 74758 files and directories currently installed.) 158s Preparing to unpack .../gir1.2-glib-2.0_2.79.3-3ubuntu5_arm64.deb ... 158s Unpacking gir1.2-glib-2.0:arm64 (2.79.3-3ubuntu5) over (2.79.2-1~ubuntu1) ... 158s dpkg: libglib2.0-0:arm64: dependency problems, but removing anyway as you requested: 158s udisks2 depends on libglib2.0-0 (>= 2.77.0). 158s shared-mime-info depends on libglib2.0-0 (>= 2.75.3). 158s python3-gi depends on libglib2.0-0 (>= 2.77.0). 158s python3-dbus depends on libglib2.0-0 (>= 2.16.0). 158s netplan.io depends on libglib2.0-0 (>= 2.70.0). 158s netplan-generator depends on libglib2.0-0 (>= 2.70.0). 158s libxmlb2:arm64 depends on libglib2.0-0 (>= 2.54.0). 158s libvolume-key1:arm64 depends on libglib2.0-0 (>= 2.18.0). 158s libudisks2-0:arm64 depends on libglib2.0-0 (>= 2.75.3). 158s libqrtr-glib0:arm64 depends on libglib2.0-0 (>= 2.56). 158s libqmi-proxy depends on libglib2.0-0 (>= 2.30.0). 158s libqmi-glib5:arm64 depends on libglib2.0-0 (>= 2.54.0). 158s libpolkit-gobject-1-0:arm64 depends on libglib2.0-0 (>= 2.38.0). 158s libpolkit-agent-1-0:arm64 depends on libglib2.0-0 (>= 2.38.0). 158s libnetplan0:arm64 depends on libglib2.0-0 (>= 2.75.3). 158s libmm-glib0:arm64 depends on libglib2.0-0 (>= 2.62.0). 158s libmbim-proxy depends on libglib2.0-0 (>= 2.56). 158s libmbim-glib4:arm64 depends on libglib2.0-0 (>= 2.56). 158s libjson-glib-1.0-0:arm64 depends on libglib2.0-0 (>= 2.75.3). 158s libjcat1:arm64 depends on libglib2.0-0 (>= 2.75.3). 158s libgusb2:arm64 depends on libglib2.0-0 (>= 2.75.3). 158s libgudev-1.0-0:arm64 depends on libglib2.0-0 (>= 2.38.0). 158s libgirepository-1.0-1:arm64 depends on libglib2.0-0 (>= 2.79.0). 158s libfwupd2:arm64 depends on libglib2.0-0 (>= 2.79.0). 158s libblockdev3:arm64 depends on libglib2.0-0 (>= 2.42.2). 158s libblockdev-utils3:arm64 depends on libglib2.0-0 (>= 2.75.3). 158s libblockdev-swap3:arm64 depends on libglib2.0-0 (>= 2.42.2). 158s libblockdev-part3:arm64 depends on libglib2.0-0 (>= 2.42.2). 158s libblockdev-nvme3:arm64 depends on libglib2.0-0 (>= 2.42.2). 158s libblockdev-mdraid3:arm64 depends on libglib2.0-0 (>= 2.42.2). 158s libblockdev-loop3:arm64 depends on libglib2.0-0 (>= 2.42.2). 158s libblockdev-fs3:arm64 depends on libglib2.0-0 (>= 2.42.2). 158s libblockdev-crypto3:arm64 depends on libglib2.0-0 (>= 2.42.2). 158s fwupd depends on libglib2.0-0 (>= 2.79.0). 158s bolt depends on libglib2.0-0 (>= 2.56.0). 158s 158s (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 ... 74758 files and directories currently installed.) 158s Removing libglib2.0-0:arm64 (2.79.2-1~ubuntu1) ... 158s Selecting previously unselected package libglib2.0-0t64:arm64. 158s (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 ... 74733 files and directories currently installed.) 158s Preparing to unpack .../libglib2.0-0t64_2.79.3-3ubuntu5_arm64.deb ... 158s libglib2.0-0t64.preinst: Removing /var/lib/dpkg/info/libglib2.0-0:arm64.postrm to avoid loss of /usr/share/glib-2.0/schemas/gschemas.compiled... 158s removed '/var/lib/dpkg/info/libglib2.0-0:arm64.postrm' 158s Unpacking libglib2.0-0t64:arm64 (2.79.3-3ubuntu5) ... 158s Preparing to unpack .../openssl_3.0.13-0ubuntu1_arm64.deb ... 158s Unpacking openssl (3.0.13-0ubuntu1) over (3.0.10-1ubuntu4) ... 158s dpkg: libssl3:arm64: dependency problems, but removing anyway as you requested: 158s wget depends on libssl3 (>= 3.0.0). 158s u-boot-tools depends on libssl3 (>= 3.0.0). 158s tnftp depends on libssl3 (>= 3.0.0). 158s tcpdump depends on libssl3 (>= 3.0.0). 158s systemd-resolved depends on libssl3 (>= 3.0.0). 158s systemd depends on libssl3 (>= 3.0.0). 158s sudo depends on libssl3 (>= 3.0.0). 158s sbsigntool depends on libssl3 (>= 3.0.0). 158s rsync depends on libssl3 (>= 3.0.0). 158s python3-cryptography depends on libssl3 (>= 3.0.0). 158s openssh-server depends on libssl3 (>= 3.0.10). 158s openssh-client depends on libssl3 (>= 3.0.10). 158s mtd-utils depends on libssl3 (>= 3.0.0). 158s mokutil depends on libssl3 (>= 3.0.0). 158s linux-headers-6.8.0-11-generic depends on libssl3 (>= 3.0.0). 158s libsystemd-shared:arm64 depends on libssl3 (>= 3.0.0). 158s libssh-4:arm64 depends on libssl3 (>= 3.0.0). 158s libsasl2-modules:arm64 depends on libssl3 (>= 3.0.0). 158s libsasl2-2:arm64 depends on libssl3 (>= 3.0.0). 158s libpython3.12-minimal:arm64 depends on libssl3 (>= 3.0.0). 158s libnvme1 depends on libssl3 (>= 3.0.0). 158s libkrb5-3:arm64 depends on libssl3 (>= 3.0.0). 158s libkmod2:arm64 depends on libssl3 (>= 3.0.0). 158s libfido2-1:arm64 depends on libssl3 (>= 3.0.0). 158s libcurl4:arm64 depends on libssl3 (>= 3.0.0). 158s libcryptsetup12:arm64 depends on libssl3 (>= 3.0.0). 158s kmod depends on libssl3 (>= 3.0.0). 158s dhcpcd-base depends on libssl3 (>= 3.0.0). 158s bind9-libs:arm64 depends on libssl3 (>= 3.0.0). 158s 158s (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 ... 74758 files and directories currently installed.) 158s Removing libssl3:arm64 (3.0.10-1ubuntu4) ... 158s Selecting previously unselected package libssl3t64:arm64. 158s (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 ... 74747 files and directories currently installed.) 158s Preparing to unpack .../0-libssl3t64_3.0.13-0ubuntu1_arm64.deb ... 158s Unpacking libssl3t64:arm64 (3.0.13-0ubuntu1) ... 158s Preparing to unpack .../1-libglib2.0-data_2.79.3-3ubuntu5_all.deb ... 158s Unpacking libglib2.0-data (2.79.3-3ubuntu5) over (2.79.2-1~ubuntu1) ... 158s Preparing to unpack .../2-libtirpc-common_1.3.4+ds-1.1_all.deb ... 158s Unpacking libtirpc-common (1.3.4+ds-1.1) over (1.3.4+ds-1build1) ... 158s Preparing to unpack .../3-readline-common_8.2-3.1_all.deb ... 158s Unpacking readline-common (8.2-3.1) over (8.2-3) ... 158s Preparing to unpack .../4-ubuntu-minimal_1.536_arm64.deb ... 158s Unpacking ubuntu-minimal (1.536) over (1.535) ... 158s Selecting previously unselected package xdg-user-dirs. 158s Preparing to unpack .../5-xdg-user-dirs_0.18-1_arm64.deb ... 158s Unpacking xdg-user-dirs (0.18-1) ... 158s Preparing to unpack .../6-ubuntu-standard_1.536_arm64.deb ... 158s Unpacking ubuntu-standard (1.536) over (1.535) ... 158s Setting up ubuntu-minimal (1.536) ... 158s Setting up xdg-user-dirs (0.18-1) ... 158s Setting up libssl3t64:arm64 (3.0.13-0ubuntu1) ... 158s Setting up libtirpc-common (1.3.4+ds-1.1) ... 158s Setting up ubuntu-standard (1.536) ... 158s Setting up libglib2.0-0t64:arm64 (2.79.3-3ubuntu5) ... 159s No schema files found: doing nothing. 159s Setting up libglib2.0-data (2.79.3-3ubuntu5) ... 159s Setting up gir1.2-glib-2.0:arm64 (2.79.3-3ubuntu5) ... 159s Setting up openssl (3.0.13-0ubuntu1) ... 159s Setting up readline-common (8.2-3.1) ... 159s Processing triggers for man-db (2.12.0-3) ... 159s Processing triggers for install-info (7.1-3) ... 159s Processing triggers for libc-bin (2.39-0ubuntu2) ... 160s Reading package lists... 160s Building dependency tree... 160s Reading state information... 161s 0 upgraded, 0 newly installed, 0 to remove and 1 not upgraded. 162s Hit:1 http://ftpmaster.internal/ubuntu noble InRelease 162s Hit:2 http://ftpmaster.internal/ubuntu noble-updates InRelease 162s Hit:3 http://ftpmaster.internal/ubuntu noble-security InRelease 162s Hit:4 http://ftpmaster.internal/ubuntu noble-proposed InRelease 164s Reading package lists... 164s Reading package lists... 165s Building dependency tree... 165s Reading state information... 165s Calculating upgrade... 165s The following packages have been kept back: 165s curl 165s 0 upgraded, 0 newly installed, 0 to remove and 1 not upgraded. 165s Reading package lists... 166s Building dependency tree... 166s Reading state information... 166s 0 upgraded, 0 newly installed, 0 to remove and 1 not upgraded. 169s autopkgtest [20:01:57]: testbed running kernel: Linux 6.8.0-11-generic #11-Ubuntu SMP PREEMPT_DYNAMIC Wed Feb 14 02:53:31 UTC 2024 169s autopkgtest [20:01:57]: @@@@@@@@@@@@@@@@@@@@ apt-source r-cran-rrcov 172s Get:1 http://ftpmaster.internal/ubuntu noble/universe r-cran-rrcov 1.7-5-1 (dsc) [2146 B] 172s Get:2 http://ftpmaster.internal/ubuntu noble/universe r-cran-rrcov 1.7-5-1 (tar) [1563 kB] 172s Get:3 http://ftpmaster.internal/ubuntu noble/universe r-cran-rrcov 1.7-5-1 (diff) [3124 B] 172s gpgv: Signature made Thu Feb 1 16:08:31 2024 UTC 172s gpgv: using RSA key F1F007320A035541F0A663CA578A0494D1C646D1 172s gpgv: issuer "tille@debian.org" 172s gpgv: Can't check signature: No public key 172s dpkg-source: warning: cannot verify inline signature for ./r-cran-rrcov_1.7-5-1.dsc: no acceptable signature found 173s autopkgtest [20:02:01]: testing package r-cran-rrcov version 1.7-5-1 173s autopkgtest [20:02:01]: build not needed 174s autopkgtest [20:02:02]: test run-unit-test: preparing testbed 175s Reading package lists... 176s Building dependency tree... 176s Reading state information... 176s Starting pkgProblemResolver with broken count: 0 176s Starting 2 pkgProblemResolver with broken count: 0 176s Done 177s The following additional packages will be installed: 177s curl fontconfig fontconfig-config fonts-dejavu-core fonts-dejavu-mono 177s libblas3 libcairo2 libcurl4t64 libdatrie1 libdeflate0 libfontconfig1 177s libgfortran5 libgomp1 libgraphite2-3 libharfbuzz0b libice6 libjbig0 177s libjpeg-turbo8 libjpeg8 liblapack3 liblerc4 libpango-1.0-0 177s libpangocairo-1.0-0 libpangoft2-1.0-0 libpaper-utils libpaper1 libpixman-1-0 177s libpng16-16t64 libpsl5t64 libreadline8t64 libsharpyuv0 libsm6 libtcl8.6 177s libthai-data libthai0 libtiff6 libtirpc3t64 libtk8.6 libwebp7 libxcb-render0 177s libxcb-shm0 libxft2 libxrender1 libxss1 libxt6t64 r-base-core 177s r-cran-deoptimr r-cran-lattice r-cran-mass r-cran-mvtnorm r-cran-pcapp 177s r-cran-robustbase r-cran-rrcov unzip x11-common xdg-utils zip 177s Suggested packages: 177s tcl8.6 tk8.6 elpa-ess r-doc-info | r-doc-pdf r-mathlib r-base-html 177s Recommended packages: 177s r-recommended r-base-dev r-doc-html libfile-mimeinfo-perl libnet-dbus-perl 177s libx11-protocol-perl x11-utils x11-xserver-utils 177s The following packages will be REMOVED: 177s libcurl4 libpng16-16 libpsl5 libreadline8 libtirpc3 177s The following NEW packages will be installed: 177s autopkgtest-satdep fontconfig fontconfig-config fonts-dejavu-core 177s fonts-dejavu-mono libblas3 libcairo2 libcurl4t64 libdatrie1 libdeflate0 177s libfontconfig1 libgfortran5 libgomp1 libgraphite2-3 libharfbuzz0b libice6 177s libjbig0 libjpeg-turbo8 libjpeg8 liblapack3 liblerc4 libpango-1.0-0 177s libpangocairo-1.0-0 libpangoft2-1.0-0 libpaper-utils libpaper1 libpixman-1-0 177s libpng16-16t64 libpsl5t64 libreadline8t64 libsharpyuv0 libsm6 libtcl8.6 177s libthai-data libthai0 libtiff6 libtirpc3t64 libtk8.6 libwebp7 libxcb-render0 177s libxcb-shm0 libxft2 libxrender1 libxss1 libxt6t64 r-base-core 177s r-cran-deoptimr r-cran-lattice r-cran-mass r-cran-mvtnorm r-cran-pcapp 177s r-cran-robustbase r-cran-rrcov unzip x11-common xdg-utils zip 177s The following packages will be upgraded: 177s curl 177s 1 upgraded, 57 newly installed, 5 to remove and 0 not upgraded. 177s Need to get 46.7 MB/46.7 MB of archives. 177s After this operation, 86.9 MB of additional disk space will be used. 177s Get:1 /tmp/autopkgtest.EF2nlC/1-autopkgtest-satdep.deb autopkgtest-satdep arm64 0 [712 B] 177s Get:2 http://ftpmaster.internal/ubuntu noble-proposed/main arm64 libpsl5t64 arm64 0.21.2-1.1 [57.4 kB] 177s Get:3 http://ftpmaster.internal/ubuntu noble-proposed/main arm64 curl arm64 8.5.0-2ubuntu7 [222 kB] 178s Get:4 http://ftpmaster.internal/ubuntu noble-proposed/main arm64 libcurl4t64 arm64 8.5.0-2ubuntu7 [332 kB] 178s Get:5 http://ftpmaster.internal/ubuntu noble-proposed/main arm64 libpng16-16t64 arm64 1.6.43-3 [185 kB] 178s Get:6 http://ftpmaster.internal/ubuntu noble-proposed/main arm64 libreadline8t64 arm64 8.2-3.1 [153 kB] 178s Get:7 http://ftpmaster.internal/ubuntu noble-proposed/main arm64 libtirpc3t64 arm64 1.3.4+ds-1.1 [83.5 kB] 178s Get:8 http://ftpmaster.internal/ubuntu noble/main arm64 fonts-dejavu-mono all 2.37-8 [502 kB] 178s Get:9 http://ftpmaster.internal/ubuntu noble/main arm64 fonts-dejavu-core all 2.37-8 [835 kB] 178s Get:10 http://ftpmaster.internal/ubuntu noble/main arm64 fontconfig-config arm64 2.15.0-1ubuntu1 [37.0 kB] 178s Get:11 http://ftpmaster.internal/ubuntu noble/main arm64 libfontconfig1 arm64 2.15.0-1ubuntu1 [142 kB] 178s Get:12 http://ftpmaster.internal/ubuntu noble/main arm64 fontconfig arm64 2.15.0-1ubuntu1 [190 kB] 178s Get:13 http://ftpmaster.internal/ubuntu noble/main arm64 libblas3 arm64 3.12.0-3 [143 kB] 178s Get:14 http://ftpmaster.internal/ubuntu noble/main arm64 libpixman-1-0 arm64 0.42.2-1 [193 kB] 178s Get:15 http://ftpmaster.internal/ubuntu noble/main arm64 libxcb-render0 arm64 1.15-1 [16.1 kB] 178s Get:16 http://ftpmaster.internal/ubuntu noble/main arm64 libxcb-shm0 arm64 1.15-1 [5780 B] 178s Get:17 http://ftpmaster.internal/ubuntu noble/main arm64 libxrender1 arm64 1:0.9.10-1.1 [19.1 kB] 178s Get:18 http://ftpmaster.internal/ubuntu noble/main arm64 libcairo2 arm64 1.18.0-1 [550 kB] 178s Get:19 http://ftpmaster.internal/ubuntu noble/main arm64 libdatrie1 arm64 0.2.13-3 [21.7 kB] 178s Get:20 http://ftpmaster.internal/ubuntu noble/main arm64 libdeflate0 arm64 1.19-1 [43.4 kB] 178s Get:21 http://ftpmaster.internal/ubuntu noble/main arm64 libgfortran5 arm64 14-20240303-1ubuntu1 [444 kB] 178s Get:22 http://ftpmaster.internal/ubuntu noble/main arm64 libgomp1 arm64 14-20240303-1ubuntu1 [144 kB] 178s Get:23 http://ftpmaster.internal/ubuntu noble/main arm64 libgraphite2-3 arm64 1.3.14-2 [81.5 kB] 178s Get:24 http://ftpmaster.internal/ubuntu noble/main arm64 libharfbuzz0b arm64 8.3.0-2 [463 kB] 178s Get:25 http://ftpmaster.internal/ubuntu noble/main arm64 x11-common all 1:7.7+23ubuntu2 [23.4 kB] 178s Get:26 http://ftpmaster.internal/ubuntu noble/main arm64 libice6 arm64 2:1.0.10-1build2 [41.7 kB] 178s Get:27 http://ftpmaster.internal/ubuntu noble/main arm64 libjpeg-turbo8 arm64 2.1.5-2ubuntu1 [160 kB] 178s Get:28 http://ftpmaster.internal/ubuntu noble/main arm64 libjpeg8 arm64 8c-2ubuntu11 [2148 B] 178s Get:29 http://ftpmaster.internal/ubuntu noble/main arm64 liblapack3 arm64 3.12.0-3 [2241 kB] 178s Get:30 http://ftpmaster.internal/ubuntu noble/main arm64 liblerc4 arm64 4.0.0+ds-4ubuntu1 [153 kB] 178s Get:31 http://ftpmaster.internal/ubuntu noble/main arm64 libthai-data all 0.1.29-2 [158 kB] 178s Get:32 http://ftpmaster.internal/ubuntu noble/main arm64 libthai0 arm64 0.1.29-2 [18.1 kB] 178s Get:33 http://ftpmaster.internal/ubuntu noble/main arm64 libpango-1.0-0 arm64 1.51.0+ds-4 [226 kB] 178s Get:34 http://ftpmaster.internal/ubuntu noble/main arm64 libpangoft2-1.0-0 arm64 1.51.0+ds-4 [41.2 kB] 178s Get:35 http://ftpmaster.internal/ubuntu noble/main arm64 libpangocairo-1.0-0 arm64 1.51.0+ds-4 [27.6 kB] 178s Get:36 http://ftpmaster.internal/ubuntu noble/main arm64 libpaper1 arm64 1.1.29 [13.1 kB] 178s Get:37 http://ftpmaster.internal/ubuntu noble/main arm64 libpaper-utils arm64 1.1.29 [8480 B] 178s Get:38 http://ftpmaster.internal/ubuntu noble/main arm64 libsharpyuv0 arm64 1.3.2-0.4 [14.4 kB] 178s Get:39 http://ftpmaster.internal/ubuntu noble/main arm64 libsm6 arm64 2:1.2.3-1build2 [16.1 kB] 178s Get:40 http://ftpmaster.internal/ubuntu noble/main arm64 libtcl8.6 arm64 8.6.13+dfsg-2 [980 kB] 178s Get:41 http://ftpmaster.internal/ubuntu noble/main arm64 libjbig0 arm64 2.1-6.1ubuntu1 [28.9 kB] 178s Get:42 http://ftpmaster.internal/ubuntu noble/main arm64 libwebp7 arm64 1.3.2-0.4 [191 kB] 178s Get:43 http://ftpmaster.internal/ubuntu noble/main arm64 libtiff6 arm64 4.5.1+git230720-3ubuntu1 [226 kB] 178s Get:44 http://ftpmaster.internal/ubuntu noble/main arm64 libxft2 arm64 2.3.6-1 [43.3 kB] 178s Get:45 http://ftpmaster.internal/ubuntu noble/main arm64 libxss1 arm64 1:1.2.3-1build2 [8252 B] 178s Get:46 http://ftpmaster.internal/ubuntu noble/main arm64 libtk8.6 arm64 8.6.13-2 [760 kB] 178s Get:47 http://ftpmaster.internal/ubuntu noble-proposed/main arm64 libxt6t64 arm64 1:1.2.1-1.2 [168 kB] 178s Get:48 http://ftpmaster.internal/ubuntu noble/main arm64 zip arm64 3.0-13 [172 kB] 178s Get:49 http://ftpmaster.internal/ubuntu noble/main arm64 unzip arm64 6.0-28ubuntu3 [171 kB] 178s Get:50 http://ftpmaster.internal/ubuntu noble/main arm64 xdg-utils all 1.1.3-4.1ubuntu3 [62.0 kB] 178s Get:51 http://ftpmaster.internal/ubuntu noble-proposed/universe arm64 r-base-core arm64 4.3.3-2build1 [26.8 MB] 179s Get:52 http://ftpmaster.internal/ubuntu noble/universe arm64 r-cran-deoptimr all 1.1-3-1 [74.4 kB] 179s Get:53 http://ftpmaster.internal/ubuntu noble/universe arm64 r-cran-lattice arm64 0.22-5-1 [1342 kB] 179s Get:54 http://ftpmaster.internal/ubuntu noble/universe arm64 r-cran-mass arm64 7.3-60.0.1-1 [1119 kB] 179s Get:55 http://ftpmaster.internal/ubuntu noble/universe arm64 r-cran-mvtnorm arm64 1.2-4-1 [723 kB] 179s Get:56 http://ftpmaster.internal/ubuntu noble/universe arm64 r-cran-pcapp arm64 2.0-4-1 [363 kB] 179s Get:57 http://ftpmaster.internal/ubuntu noble/universe arm64 r-cran-robustbase arm64 0.99-2-1 [3020 kB] 179s Get:58 http://ftpmaster.internal/ubuntu noble/universe arm64 r-cran-rrcov arm64 1.7-5-1 [2395 kB] 180s Preconfiguring packages ... 180s Fetched 46.7 MB in 2s (23.6 MB/s) 180s dpkg: libpsl5:arm64: dependency problems, but removing anyway as you requested: 180s wget depends on libpsl5 (>= 0.16.0). 180s libcurl4:arm64 depends on libpsl5 (>= 0.16.0). 180s libcurl3-gnutls:arm64 depends on libpsl5 (>= 0.16.0). 180s 181s (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 ... 74774 files and directories currently installed.) 181s Removing libpsl5:arm64 (0.21.2-1build1) ... 181s Selecting previously unselected package libpsl5t64:arm64. 181s (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 ... 74769 files and directories currently installed.) 181s Preparing to unpack .../libpsl5t64_0.21.2-1.1_arm64.deb ... 181s Unpacking libpsl5t64:arm64 (0.21.2-1.1) ... 181s Preparing to unpack .../curl_8.5.0-2ubuntu7_arm64.deb ... 181s Unpacking curl (8.5.0-2ubuntu7) over (8.5.0-2ubuntu2) ... 181s (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 ... 74775 files and directories currently installed.) 181s Removing libcurl4:arm64 (8.5.0-2ubuntu2) ... 181s Selecting previously unselected package libcurl4t64:arm64. 181s (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 ... 74770 files and directories currently installed.) 181s Preparing to unpack .../libcurl4t64_8.5.0-2ubuntu7_arm64.deb ... 181s Unpacking libcurl4t64:arm64 (8.5.0-2ubuntu7) ... 181s dpkg: libpng16-16:arm64: dependency problems, but removing anyway as you requested: 181s libplymouth5:arm64 depends on libpng16-16 (>= 1.6.2). 181s libfreetype6:arm64 depends on libpng16-16 (>= 1.6.2-1). 181s 181s (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 ... 74776 files and directories currently installed.) 181s Removing libpng16-16:arm64 (1.6.43-1) ... 181s Selecting previously unselected package libpng16-16t64:arm64. 181s (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 ... 74766 files and directories currently installed.) 181s Preparing to unpack .../libpng16-16t64_1.6.43-3_arm64.deb ... 181s Unpacking libpng16-16t64:arm64 (1.6.43-3) ... 181s dpkg: libreadline8:arm64: dependency problems, but removing anyway as you requested: 181s parted depends on libreadline8 (>= 6.0). 181s libpython3.12-stdlib:arm64 depends on libreadline8 (>= 7.0~beta). 181s gpgsm depends on libreadline8 (>= 6.0). 181s gpgconf depends on libreadline8 (>= 6.0). 181s gpg depends on libreadline8 (>= 6.0). 181s gawk depends on libreadline8 (>= 6.0). 181s fdisk depends on libreadline8 (>= 6.0). 181s 181s (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 ... 74777 files and directories currently installed.) 181s Removing libreadline8:arm64 (8.2-3) ... 181s Selecting previously unselected package libreadline8t64:arm64. 181s (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 ... 74765 files and directories currently installed.) 181s Preparing to unpack .../libreadline8t64_8.2-3.1_arm64.deb ... 181s Adding 'diversion of /lib/aarch64-linux-gnu/libhistory.so.8 to /lib/aarch64-linux-gnu/libhistory.so.8.usr-is-merged by libreadline8t64' 181s Adding 'diversion of /lib/aarch64-linux-gnu/libhistory.so.8.2 to /lib/aarch64-linux-gnu/libhistory.so.8.2.usr-is-merged by libreadline8t64' 182s Adding 'diversion of /lib/aarch64-linux-gnu/libreadline.so.8 to /lib/aarch64-linux-gnu/libreadline.so.8.usr-is-merged by libreadline8t64' 182s Adding 'diversion of /lib/aarch64-linux-gnu/libreadline.so.8.2 to /lib/aarch64-linux-gnu/libreadline.so.8.2.usr-is-merged by libreadline8t64' 182s Unpacking libreadline8t64:arm64 (8.2-3.1) ... 182s dpkg: libtirpc3:arm64: dependency problems, but removing anyway as you requested: 182s lsof depends on libtirpc3 (>= 1.0.2). 182s libpython3.12-stdlib:arm64 depends on libtirpc3 (>= 1.0.2). 182s libnss-nisplus:arm64 depends on libtirpc3 (>= 1.0.2). 182s libnsl2:arm64 depends on libtirpc3 (>= 1.0.2). 182s iproute2 depends on libtirpc3 (>= 1.0.2). 182s 182s (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 ... 74785 files and directories currently installed.) 182s Removing libtirpc3:arm64 (1.3.4+ds-1build1) ... 182s Selecting previously unselected package libtirpc3t64:arm64. 182s (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 ... 74779 files and directories currently installed.) 182s Preparing to unpack .../00-libtirpc3t64_1.3.4+ds-1.1_arm64.deb ... 182s Adding 'diversion of /lib/aarch64-linux-gnu/libtirpc.so.3 to /lib/aarch64-linux-gnu/libtirpc.so.3.usr-is-merged by libtirpc3t64' 182s Adding 'diversion of /lib/aarch64-linux-gnu/libtirpc.so.3.0.0 to /lib/aarch64-linux-gnu/libtirpc.so.3.0.0.usr-is-merged by libtirpc3t64' 182s Unpacking libtirpc3t64:arm64 (1.3.4+ds-1.1) ... 182s Selecting previously unselected package fonts-dejavu-mono. 182s Preparing to unpack .../01-fonts-dejavu-mono_2.37-8_all.deb ... 182s Unpacking fonts-dejavu-mono (2.37-8) ... 182s Selecting previously unselected package fonts-dejavu-core. 182s Preparing to unpack .../02-fonts-dejavu-core_2.37-8_all.deb ... 182s Unpacking fonts-dejavu-core (2.37-8) ... 182s Selecting previously unselected package fontconfig-config. 182s Preparing to unpack .../03-fontconfig-config_2.15.0-1ubuntu1_arm64.deb ... 182s Unpacking fontconfig-config (2.15.0-1ubuntu1) ... 182s Selecting previously unselected package libfontconfig1:arm64. 182s Preparing to unpack .../04-libfontconfig1_2.15.0-1ubuntu1_arm64.deb ... 182s Unpacking libfontconfig1:arm64 (2.15.0-1ubuntu1) ... 182s Selecting previously unselected package fontconfig. 182s Preparing to unpack .../05-fontconfig_2.15.0-1ubuntu1_arm64.deb ... 182s Unpacking fontconfig (2.15.0-1ubuntu1) ... 182s Selecting previously unselected package libblas3:arm64. 182s Preparing to unpack .../06-libblas3_3.12.0-3_arm64.deb ... 182s Unpacking libblas3:arm64 (3.12.0-3) ... 182s Selecting previously unselected package libpixman-1-0:arm64. 182s Preparing to unpack .../07-libpixman-1-0_0.42.2-1_arm64.deb ... 182s Unpacking libpixman-1-0:arm64 (0.42.2-1) ... 182s Selecting previously unselected package libxcb-render0:arm64. 182s Preparing to unpack .../08-libxcb-render0_1.15-1_arm64.deb ... 182s Unpacking libxcb-render0:arm64 (1.15-1) ... 182s Selecting previously unselected package libxcb-shm0:arm64. 182s Preparing to unpack .../09-libxcb-shm0_1.15-1_arm64.deb ... 182s Unpacking libxcb-shm0:arm64 (1.15-1) ... 182s Selecting previously unselected package libxrender1:arm64. 182s Preparing to unpack .../10-libxrender1_1%3a0.9.10-1.1_arm64.deb ... 182s Unpacking libxrender1:arm64 (1:0.9.10-1.1) ... 182s Selecting previously unselected package libcairo2:arm64. 182s Preparing to unpack .../11-libcairo2_1.18.0-1_arm64.deb ... 182s Unpacking libcairo2:arm64 (1.18.0-1) ... 183s Selecting previously unselected package libdatrie1:arm64. 183s Preparing to unpack .../12-libdatrie1_0.2.13-3_arm64.deb ... 183s Unpacking libdatrie1:arm64 (0.2.13-3) ... 183s Selecting previously unselected package libdeflate0:arm64. 183s Preparing to unpack .../13-libdeflate0_1.19-1_arm64.deb ... 183s Unpacking libdeflate0:arm64 (1.19-1) ... 183s Selecting previously unselected package libgfortran5:arm64. 183s Preparing to unpack .../14-libgfortran5_14-20240303-1ubuntu1_arm64.deb ... 183s Unpacking libgfortran5:arm64 (14-20240303-1ubuntu1) ... 183s Selecting previously unselected package libgomp1:arm64. 183s Preparing to unpack .../15-libgomp1_14-20240303-1ubuntu1_arm64.deb ... 183s Unpacking libgomp1:arm64 (14-20240303-1ubuntu1) ... 183s Selecting previously unselected package libgraphite2-3:arm64. 183s Preparing to unpack .../16-libgraphite2-3_1.3.14-2_arm64.deb ... 183s Unpacking libgraphite2-3:arm64 (1.3.14-2) ... 183s Selecting previously unselected package libharfbuzz0b:arm64. 183s Preparing to unpack .../17-libharfbuzz0b_8.3.0-2_arm64.deb ... 183s Unpacking libharfbuzz0b:arm64 (8.3.0-2) ... 183s Selecting previously unselected package x11-common. 183s Preparing to unpack .../18-x11-common_1%3a7.7+23ubuntu2_all.deb ... 183s Unpacking x11-common (1:7.7+23ubuntu2) ... 183s Selecting previously unselected package libice6:arm64. 183s Preparing to unpack .../19-libice6_2%3a1.0.10-1build2_arm64.deb ... 183s Unpacking libice6:arm64 (2:1.0.10-1build2) ... 183s Selecting previously unselected package libjpeg-turbo8:arm64. 183s Preparing to unpack .../20-libjpeg-turbo8_2.1.5-2ubuntu1_arm64.deb ... 183s Unpacking libjpeg-turbo8:arm64 (2.1.5-2ubuntu1) ... 183s Selecting previously unselected package libjpeg8:arm64. 183s Preparing to unpack .../21-libjpeg8_8c-2ubuntu11_arm64.deb ... 183s Unpacking libjpeg8:arm64 (8c-2ubuntu11) ... 183s Selecting previously unselected package liblapack3:arm64. 183s Preparing to unpack .../22-liblapack3_3.12.0-3_arm64.deb ... 183s Unpacking liblapack3:arm64 (3.12.0-3) ... 183s Selecting previously unselected package liblerc4:arm64. 183s Preparing to unpack .../23-liblerc4_4.0.0+ds-4ubuntu1_arm64.deb ... 183s Unpacking liblerc4:arm64 (4.0.0+ds-4ubuntu1) ... 183s Selecting previously unselected package libthai-data. 183s Preparing to unpack .../24-libthai-data_0.1.29-2_all.deb ... 183s Unpacking libthai-data (0.1.29-2) ... 183s Selecting previously unselected package libthai0:arm64. 183s Preparing to unpack .../25-libthai0_0.1.29-2_arm64.deb ... 183s Unpacking libthai0:arm64 (0.1.29-2) ... 183s Selecting previously unselected package libpango-1.0-0:arm64. 183s Preparing to unpack .../26-libpango-1.0-0_1.51.0+ds-4_arm64.deb ... 183s Unpacking libpango-1.0-0:arm64 (1.51.0+ds-4) ... 183s Selecting previously unselected package libpangoft2-1.0-0:arm64. 183s Preparing to unpack .../27-libpangoft2-1.0-0_1.51.0+ds-4_arm64.deb ... 183s Unpacking libpangoft2-1.0-0:arm64 (1.51.0+ds-4) ... 183s Selecting previously unselected package libpangocairo-1.0-0:arm64. 183s Preparing to unpack .../28-libpangocairo-1.0-0_1.51.0+ds-4_arm64.deb ... 183s Unpacking libpangocairo-1.0-0:arm64 (1.51.0+ds-4) ... 183s Selecting previously unselected package libpaper1:arm64. 183s Preparing to unpack .../29-libpaper1_1.1.29_arm64.deb ... 183s Unpacking libpaper1:arm64 (1.1.29) ... 183s Selecting previously unselected package libpaper-utils. 183s Preparing to unpack .../30-libpaper-utils_1.1.29_arm64.deb ... 183s Unpacking libpaper-utils (1.1.29) ... 183s Selecting previously unselected package libsharpyuv0:arm64. 183s Preparing to unpack .../31-libsharpyuv0_1.3.2-0.4_arm64.deb ... 183s Unpacking libsharpyuv0:arm64 (1.3.2-0.4) ... 183s Selecting previously unselected package libsm6:arm64. 183s Preparing to unpack .../32-libsm6_2%3a1.2.3-1build2_arm64.deb ... 183s Unpacking libsm6:arm64 (2:1.2.3-1build2) ... 183s Selecting previously unselected package libtcl8.6:arm64. 183s Preparing to unpack .../33-libtcl8.6_8.6.13+dfsg-2_arm64.deb ... 183s Unpacking libtcl8.6:arm64 (8.6.13+dfsg-2) ... 183s Selecting previously unselected package libjbig0:arm64. 183s Preparing to unpack .../34-libjbig0_2.1-6.1ubuntu1_arm64.deb ... 183s Unpacking libjbig0:arm64 (2.1-6.1ubuntu1) ... 183s Selecting previously unselected package libwebp7:arm64. 183s Preparing to unpack .../35-libwebp7_1.3.2-0.4_arm64.deb ... 183s Unpacking libwebp7:arm64 (1.3.2-0.4) ... 183s Selecting previously unselected package libtiff6:arm64. 183s Preparing to unpack .../36-libtiff6_4.5.1+git230720-3ubuntu1_arm64.deb ... 183s Unpacking libtiff6:arm64 (4.5.1+git230720-3ubuntu1) ... 183s Selecting previously unselected package libxft2:arm64. 183s Preparing to unpack .../37-libxft2_2.3.6-1_arm64.deb ... 183s Unpacking libxft2:arm64 (2.3.6-1) ... 183s Selecting previously unselected package libxss1:arm64. 183s Preparing to unpack .../38-libxss1_1%3a1.2.3-1build2_arm64.deb ... 183s Unpacking libxss1:arm64 (1:1.2.3-1build2) ... 184s Selecting previously unselected package libtk8.6:arm64. 184s Preparing to unpack .../39-libtk8.6_8.6.13-2_arm64.deb ... 184s Unpacking libtk8.6:arm64 (8.6.13-2) ... 184s Selecting previously unselected package libxt6t64:arm64. 184s Preparing to unpack .../40-libxt6t64_1%3a1.2.1-1.2_arm64.deb ... 184s Unpacking libxt6t64:arm64 (1:1.2.1-1.2) ... 184s Selecting previously unselected package zip. 184s Preparing to unpack .../41-zip_3.0-13_arm64.deb ... 184s Unpacking zip (3.0-13) ... 184s Selecting previously unselected package unzip. 184s Preparing to unpack .../42-unzip_6.0-28ubuntu3_arm64.deb ... 184s Unpacking unzip (6.0-28ubuntu3) ... 184s Selecting previously unselected package xdg-utils. 184s Preparing to unpack .../43-xdg-utils_1.1.3-4.1ubuntu3_all.deb ... 184s Unpacking xdg-utils (1.1.3-4.1ubuntu3) ... 184s Selecting previously unselected package r-base-core. 184s Preparing to unpack .../44-r-base-core_4.3.3-2build1_arm64.deb ... 184s Unpacking r-base-core (4.3.3-2build1) ... 184s Selecting previously unselected package r-cran-deoptimr. 184s Preparing to unpack .../45-r-cran-deoptimr_1.1-3-1_all.deb ... 184s Unpacking r-cran-deoptimr (1.1-3-1) ... 184s Selecting previously unselected package r-cran-lattice. 184s Preparing to unpack .../46-r-cran-lattice_0.22-5-1_arm64.deb ... 184s Unpacking r-cran-lattice (0.22-5-1) ... 184s Selecting previously unselected package r-cran-mass. 184s Preparing to unpack .../47-r-cran-mass_7.3-60.0.1-1_arm64.deb ... 184s Unpacking r-cran-mass (7.3-60.0.1-1) ... 184s Selecting previously unselected package r-cran-mvtnorm. 184s Preparing to unpack .../48-r-cran-mvtnorm_1.2-4-1_arm64.deb ... 184s Unpacking r-cran-mvtnorm (1.2-4-1) ... 184s Selecting previously unselected package r-cran-pcapp. 184s Preparing to unpack .../49-r-cran-pcapp_2.0-4-1_arm64.deb ... 184s Unpacking r-cran-pcapp (2.0-4-1) ... 184s Selecting previously unselected package r-cran-robustbase. 184s Preparing to unpack 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Processing triggers for install-info (7.1-3) ... 190s Processing triggers for libc-bin (2.39-0ubuntu2) ... 196s (Reading database ... 77222 files and directories currently installed.) 196s Removing autopkgtest-satdep (0) ... 197s autopkgtest [20:02:25]: test run-unit-test: [----------------------- 197s BEGIN TEST thubert.R 198s 198s R version 4.3.3 (2024-02-29) -- "Angel Food Cake" 198s Copyright (C) 2024 The R Foundation for Statistical Computing 198s Platform: aarch64-unknown-linux-gnu (64-bit) 198s 198s R is free software and comes with ABSOLUTELY NO WARRANTY. 198s You are welcome to redistribute it under certain conditions. 198s Type 'license()' or 'licence()' for distribution details. 198s 198s R is a collaborative project with many contributors. 198s Type 'contributors()' for more information and 198s 'citation()' on how to cite R or R packages in publications. 198s 198s Type 'demo()' for some demos, 'help()' for on-line help, or 198s 'help.start()' for an HTML browser interface to help. 198s Type 'q()' to quit R. 198s 198s > dodata <- function(nrep=1, time=FALSE, short=FALSE, full=TRUE, 198s + method=c("hubert", "hubert.mcd", "locantore", "cov", "classic", 198s + "grid", "proj")) 198s + { 198s + ## Test the PcaXxx() functions on the literature datasets: 198s + ## 198s + ## Call PcaHubert() and the other functions for all regression 198s + ## data sets available in robustbase/rrcov and print: 198s + ## - execution time (if time == TRUE) 198s + ## - loadings 198s + ## - eigenvalues 198s + ## - scores 198s + ## 198s + 198s + dopca <- function(x, xname, nrep=1){ 198s + 198s + n <- dim(x)[1] 198s + p <- dim(x)[2] 198s + if(method == "hubert.mcd") 198s + pca <- PcaHubert(x, k=p) 198s + else if(method == "hubert") 198s + pca <- PcaHubert(x, mcd=FALSE) 198s + else if(method == "locantore") 198s + pca <- PcaLocantore(x) 198s + else if(method == "cov") 198s + pca <- PcaCov(x) 198s + else if(method == "classic") 198s + pca <- PcaClassic(x) 198s + else if(method == "grid") 198s + pca <- PcaGrid(x) 198s + else if(method == "proj") 198s + pca <- PcaProj(x) 198s + else 198s + stop("Undefined PCA method: ", method) 198s + 198s + 198s + e1 <- getEigenvalues(pca)[1] 198s + e2 <- getEigenvalues(pca)[2] 198s + k <- pca@k 198s + 198s + if(time){ 198s + xtime <- system.time(dorep(x, nrep, method))[1]/nrep 198s + xres <- sprintf("%3d %3d %3d %12.6f %12.6f %10.3f\n", dim(x)[1], dim(x)[2], k, e1, e2, xtime) 198s + } 198s + else{ 198s + xres <- sprintf("%3d %3d %3d %12.6f %12.6f\n", dim(x)[1], dim(x)[2], k, e1, e2) 198s + } 198s + lpad<-lname-nchar(xname) 198s + cat(pad.right(xname, lpad), xres) 198s + 198s + if(!short){ 198s + cat("Scores: \n") 198s + print(getScores(pca)) 198s + 198s + if(full){ 198s + cat("-------------\n") 198s + show(pca) 198s + } 198s + cat("----------------------------------------------------------\n") 198s + } 198s + } 198s + 198s + stopifnot(length(nrep) == 1, nrep >= 1) 198s + method <- match.arg(method) 198s + 198s + options(digits = 5) 198s + set.seed(101) # <<-- sub-sampling algorithm now based on R's RNG and seed 198s + 198s + lname <- 20 198s + 198s + ## VT::15.09.2013 - this will render the output independent 198s + ## from the version of the package 198s + suppressPackageStartupMessages(library(rrcov)) 198s + 198s + data(Animals, package = "MASS") 198s + brain <- Animals[c(1:24, 26:25, 27:28),] 198s + 198s + tmp <- sys.call() 198s + cat("\nCall: ", deparse(substitute(tmp)),"\n") 198s + 198s + cat("Data Set n p k e1 e2\n") 198s + cat("==========================================================\n") 198s + dopca(heart[, 1:2], data(heart), nrep) 198s + dopca(starsCYG, data(starsCYG), nrep) 198s + dopca(data.matrix(subset(phosphor, select = -plant)), data(phosphor), nrep) 198s + dopca(stack.x, data(stackloss), nrep) 198s + ## dopca(data.matrix(subset(coleman, select = -Y)), data(coleman), nrep) # differences between the architectures 198s + dopca(data.matrix(subset(salinity, select = -Y)), data(salinity), nrep) 198s + ## dopca(data.matrix(subset(wood, select = -y)), data(wood), nrep) # differences between the architectures 198s + dopca(data.matrix(subset(hbk, select = -Y)),data(hbk), nrep) 198s + 198s + ## dopca(brain, "Animals", nrep) 198s + dopca(milk, data(milk), nrep) 198s + dopca(bushfire, data(bushfire), nrep) 198s + cat("==========================================================\n") 198s + } 198s > 198s > dogen <- function(nrep=1, eps=0.49, method=c("hubert", "hubert.mcd", "locantore", "cov")){ 198s + 198s + dopca <- function(x, nrep=1){ 198s + gc() 198s + xtime <- system.time(dorep(x, nrep, method))[1]/nrep 198s + cat(sprintf("%6d %3d %10.2f\n", dim(x)[1], dim(x)[2], xtime)) 198s + xtime 198s + } 198s + 198s + set.seed(1234) 198s + 198s + ## VT::15.09.2013 - this will render the output independent 198s + ## from the version of the package 198s + suppressPackageStartupMessages(library(rrcov)) 198s + library(MASS) 198s + 198s + method <- match.arg(method) 198s + 198s + ap <- c(2, 5, 10, 20, 30) 198s + an <- c(100, 500, 1000, 10000, 50000) 198s + 198s + tottime <- 0 198s + cat(" n p Time\n") 198s + cat("=====================\n") 198s + for(i in 1:length(an)) { 198s + for(j in 1:length(ap)) { 198s + n <- an[i] 198s + p <- ap[j] 198s + if(5*p <= n){ 198s + xx <- gendata(n, p, eps) 198s + X <- xx$X 198s + ## print(dimnames(X)) 198s + tottime <- tottime + dopca(X, nrep) 198s + } 198s + } 198s + } 198s + 198s + cat("=====================\n") 198s + cat("Total time: ", tottime*nrep, "\n") 198s + } 198s > 198s > dorep <- function(x, nrep=1, method=c("hubert", "hubert.mcd", "locantore", "cov")){ 198s + 198s + method <- match.arg(method) 198s + for(i in 1:nrep) 198s + if(method == "hubert.mcd") 198s + PcaHubert(x) 198s + else if(method == "hubert") 198s + PcaHubert(x, mcd=FALSE) 198s + else if(method == "locantore") 198s + PcaLocantore(x) 198s + else if(method == "cov") 198s + PcaCov(x) 198s + else 198s + stop("Undefined PCA method: ", method) 198s + } 198s > 198s > #### gendata() #### 198s > # Generates a location contaminated multivariate 198s > # normal sample of n observations in p dimensions 198s > # (1-eps)*Np(0,Ip) + eps*Np(m,Ip) 198s > # where 198s > # m = (b,b,...,b) 198s > # Defaults: eps=0 and b=10 198s > # 198s > gendata <- function(n,p,eps=0,b=10){ 198s + 198s + if(missing(n) || missing(p)) 198s + stop("Please specify (n,p)") 198s + if(eps < 0 || eps >= 0.5) 198s + stop(message="eps must be in [0,0.5)") 198s + X <- mvrnorm(n,rep(0,p),diag(1,nrow=p,ncol=p)) 198s + nbad <- as.integer(eps * n) 198s + xind <- vector("numeric") 198s + if(nbad > 0){ 198s + Xbad <- mvrnorm(nbad,rep(b,p),diag(1,nrow=p,ncol=p)) 198s + xind <- sample(n,nbad) 198s + X[xind,] <- Xbad 198s + } 198s + list(X=X, xind=xind) 198s + } 198s > 198s > pad.right <- function(z, pads) 198s + { 198s + ### Pads spaces to right of text 198s + padding <- paste(rep(" ", pads), collapse = "") 198s + paste(z, padding, sep = "") 198s + } 198s > 198s > whatis <- function(x){ 198s + if(is.data.frame(x)) 198s + cat("Type: data.frame\n") 198s + else if(is.matrix(x)) 198s + cat("Type: matrix\n") 198s + else if(is.vector(x)) 198s + cat("Type: vector\n") 198s + else 198s + cat("Type: don't know\n") 198s + } 198s > 198s > ################################################################# 198s > ## VT::27.08.2010 198s > ## bug report from Stephen Milborrow 198s > ## 198s > test.case.1 <- function() 198s + { 198s + X <- matrix(c( 198s + -0.79984, -1.00103, 0.899794, 0.00000, 198s + 0.34279, 0.52832, -1.303783, -1.17670, 198s + -0.79984, -1.00103, 0.899794, 0.00000, 198s + 0.34279, 0.52832, -1.303783, -1.17670, 198s + 0.34279, 0.52832, -1.303783, -1.17670, 198s + 1.48542, 0.66735, 0.716162, 1.17670, 198s + -0.79984, -1.00103, 0.899794, 0.00000, 198s + 1.69317, 1.91864, -0.018363, 1.76505, 198s + -1.00759, -0.16684, -0.385626, 0.58835, 198s + -0.79984, -1.00103, 0.899794, 0.00000), ncol=4, byrow=TRUE) 198s + 198s + cc1 <- PcaHubert(X, k=3) 198s + 198s + cc2 <- PcaLocantore(X, k=3) 198s + cc3 <- PcaCov(X, k=3, cov.control=CovControlSest()) 198s + 198s + cc4 <- PcaProj(X, k=2) # with k=3 will produce warnings in .distances - too small eignevalues 198s + cc5 <- PcaGrid(X, k=2) # dito 198s + 198s + list(cc1, cc2, cc3, cc4, cc5) 198s + } 198s > 198s > ################################################################# 198s > ## VT::05.08.2016 198s > ## bug report from Matthieu Lesnoff 198s > ## 198s > test.case.2 <- function() 198s + { 198s + do.test.case.2 <- function(z) 198s + { 198s + if(missing(z)) 198s + { 198s + set.seed(12345678) 198s + n <- 5 198s + z <- data.frame(v1 = rnorm(n), v2 = rnorm(n), v3 = rnorm(n)) 198s + z 198s + } 198s + 198s + fm <- PcaLocantore(z, k = 2, scale = TRUE) 198s + fm@scale 198s + apply(z, MARGIN = 2, FUN = mad) 198s + scale(z, center = fm@center, scale = fm@scale) 198s + 198s + T <- fm@scores 198s + P <- fm@loadings 198s + E <- scale(z, center = fm@center, scale = fm@scale) - T %*% t(P) 198s + d2 <- apply(E^2, MARGIN = 1, FUN = sum) 198s + ## print(sqrt(d2)); print(fm@od) 198s + print(ret <- all.equal(sqrt(d2), fm@od)) 198s + 198s + ret 198s + } 198s + do.test.case.2() 198s + do.test.case.2(phosphor) 198s + do.test.case.2(stackloss) 198s + do.test.case.2(salinity) 198s + do.test.case.2(hbk) 198s + do.test.case.2(milk) 198s + do.test.case.2(bushfire) 198s + data(rice); do.test.case.2(rice) 198s + data(un86); do.test.case.2(un86) 198s + } 198s > 198s > ## VT::15.09.2013 - this will render the output independent 198s > ## from the version of the package 198s > suppressPackageStartupMessages(library(rrcov)) 198s > 198s > dodata(method="classic") 198s 198s Call: dodata(method = "classic") 198s Data Set n p k e1 e2 198s ========================================================== 198s heart 12 2 2 812.379735 9.084962 198s Scores: 198s PC1 PC2 198s 1 2.7072 1.46576 198s 2 59.9990 -1.43041 198s 3 -3.5619 -1.54067 198s 4 -7.7696 2.52687 198s 5 14.7660 -0.95822 198s 6 -20.0489 6.91079 198s 7 1.4189 2.25961 198s 8 -34.3308 -4.23717 198s 9 -6.0487 -0.97859 198s 10 -33.0102 -3.73143 198s 11 -18.6372 0.25821 198s 12 44.5163 -0.54476 198s ------------- 198s Call: 198s PcaClassic(x = x) 198s 198s Standard deviations: 198s [1] 28.5023 3.0141 198s ---------------------------------------------------------- 198s starsCYG 47 2 2 0.331279 0.079625 198s Scores: 198s PC1 PC2 198s 1 0.2072999 0.089973 198s 2 0.6855999 0.349644 198s 3 -0.0743007 -0.061028 198s 4 0.6855999 0.349644 198s 5 0.1775161 0.015053 198s 6 0.4223986 0.211351 198s 7 -0.2926077 -0.516156 198s 8 0.2188453 0.293607 198s 9 0.5593696 0.028761 198s 10 0.0983878 0.074540 198s 11 0.8258140 -0.711176 198s 12 0.4167063 0.180244 198s 13 0.3799883 0.225541 198s 14 -0.9105236 -0.432014 198s 15 -0.7418831 -0.125322 198s 16 -0.4432862 0.048287 198s 17 -1.0503005 -0.229623 198s 18 -0.8393302 -0.007831 198s 19 -0.8126742 -0.195952 198s 20 0.9842316 -0.688729 198s 21 -0.6230699 -0.108486 198s 22 -0.7814875 -0.130933 198s 23 -0.6017038 0.025840 198s 24 -0.1857772 0.155474 198s 25 -0.0020261 0.070412 198s 26 -0.3640775 0.059510 198s 27 -0.3458392 -0.069204 198s 28 -0.1208393 0.053577 198s 29 -0.6033482 -0.176391 198s 30 1.1440521 -0.676183 198s 31 -0.5960920 -0.013765 198s 32 0.0519296 0.259855 198s 33 0.1861752 0.167779 198s 34 1.3802755 -0.632611 198s 35 -0.6542566 -0.173505 198s 36 0.5583690 0.392215 198s 37 0.0561384 0.230152 198s 38 0.1861752 0.167779 198s 39 0.1353472 0.241376 198s 40 0.5355195 0.197080 198s 41 -0.3980701 0.014294 198s 42 0.0277576 0.145332 198s 43 0.2979736 0.234120 198s 44 0.3049884 0.184614 198s 45 0.4889809 0.311684 198s 46 -0.0514512 0.134108 198s 47 -0.5224950 0.037063 198s ------------- 198s Call: 198s PcaClassic(x = x) 198s 198s Standard deviations: 198s [1] 0.57557 0.28218 198s ---------------------------------------------------------- 198s phosphor 18 2 2 220.403422 68.346121 198s Scores: 198s PC1 PC2 198s 1 4.04290 -15.3459 198s 2 -22.30489 -1.0004 198s 3 -24.52683 3.2836 198s 4 -12.54839 -6.0848 198s 5 -19.37044 2.2979 198s 6 15.20366 -19.9424 198s 7 0.44222 -3.1379 198s 8 -10.64042 3.6933 198s 9 -11.67967 5.9670 198s 10 14.26805 -7.0221 198s 11 -4.98832 1.5268 198s 12 8.74986 7.9379 198s 13 12.26290 6.0251 198s 14 6.27607 7.5768 198s 15 17.53246 3.1560 198s 16 -10.17024 -5.8994 198s 17 21.05826 5.4492 198s 18 16.39281 11.5191 198s ------------- 198s Call: 198s PcaClassic(x = x) 198s 198s Standard deviations: 198s [1] 14.8460 8.2672 198s ---------------------------------------------------------- 198s stackloss 21 3 3 99.576089 19.581136 198s Scores: 198s PC1 PC2 PC3 198s 1 20.15352 -4.359452 0.324585 198s 2 19.81554 -5.300468 0.308294 198s 3 15.45222 -1.599136 -0.203125 198s 4 2.40370 -0.145282 2.370302 198s 5 1.89538 0.070566 0.448061 198s 6 2.14954 -0.037358 1.409182 198s 7 4.43153 5.500810 2.468051 198s 8 4.43153 5.500810 2.468051 198s 9 -1.47521 1.245404 2.511773 198s 10 -5.11183 -4.802083 -2.407870 198s 11 -2.07009 3.667055 -2.261247 198s 12 -2.66223 2.833964 -3.238659 198s 13 -4.43589 -2.920053 -2.375287 198s 14 -0.46404 7.323193 -1.234961 198s 15 -9.31959 6.232579 -0.056064 198s 16 -10.33350 3.409533 -0.104938 198s 17 -14.81094 -9.872607 0.628103 198s 18 -12.44514 -3.285499 0.742143 198s 19 -11.85300 -2.452408 1.719555 198s 20 -5.73994 -2.494520 0.098250 198s 21 9.98843 1.484952 -3.614198 198s ------------- 198s Call: 198s PcaClassic(x = x) 198s 198s Standard deviations: 198s [1] 9.9788 4.4251 1.8986 198s ---------------------------------------------------------- 198s salinity 28 3 3 11.410736 7.075409 198s Scores: 198s PC1 PC2 PC3 198s 1 -0.937789 -2.40535 0.812909 198s 2 -1.752631 -2.57774 2.004437 198s 3 -6.509364 -0.78762 -1.821906 198s 4 -5.619847 -2.41333 -1.586891 198s 5 -7.268242 1.61012 1.563568 198s 6 -4.316558 -3.20411 0.029376 198s 7 -2.379545 -3.32371 0.703101 198s 8 0.013514 -3.50586 1.260502 198s 9 0.265262 -0.16736 -2.886883 198s 10 1.890755 2.43623 -0.986832 198s 11 0.804196 2.56656 0.387577 198s 12 0.935082 -1.03559 -0.074081 198s 13 1.814839 -1.61087 0.612290 198s 14 3.407535 -0.15880 2.026088 198s 15 1.731273 2.95159 -1.840286 198s 16 -6.129708 7.21368 2.632273 198s 17 -0.645124 1.06260 0.028697 198s 18 -1.307532 -2.54679 -0.280273 198s 19 0.483455 -0.55896 -3.097281 198s 20 2.053267 0.47308 -1.858703 198s 21 3.277664 -1.31002 0.453753 198s 22 4.631644 -0.78005 1.519894 198s 23 1.864403 5.32790 -0.849694 198s 24 0.623899 4.29317 0.056461 198s 25 1.301696 0.37871 -0.646220 198s 26 2.852126 -0.79527 -0.347711 198s 27 4.134051 -0.92756 0.449222 198s 28 4.781679 -0.20467 1.736616 198s ------------- 198s Call: 198s PcaClassic(x = x) 198s 198s Standard deviations: 198s [1] 3.3780 2.6600 1.4836 198s ---------------------------------------------------------- 198s hbk 75 3 3 216.162129 1.981077 198s Scores: 198s PC1 PC2 PC3 198s 1 26.2072 -0.660756 0.503340 198s 2 27.0406 -0.108506 -0.225059 198s 3 28.8351 -1.683721 0.263078 198s 4 29.9221 -0.812174 -0.674480 198s 5 29.3181 -0.909915 -0.121600 198s 6 27.5360 -0.599697 0.916574 198s 7 27.6617 -0.073753 0.676620 198s 8 26.5576 -0.882312 0.159620 198s 9 28.8726 -1.074223 -0.673462 198s 10 27.6643 -1.463829 -0.868593 198s 11 34.2019 -0.664473 -0.567265 198s 12 35.4805 -2.730949 -0.259320 198s 13 34.7544 1.325449 0.749884 198s 14 38.9522 8.171389 0.034382 198s 15 -5.5375 0.390704 1.679172 198s 16 -7.4319 0.803850 1.925633 198s 17 -8.5880 0.957577 -1.010312 198s 18 -6.6022 -0.425109 0.625148 198s 19 -6.5596 1.154721 -0.640680 198s 20 -5.2525 0.812527 1.377832 198s 21 -6.2771 0.067747 0.958907 198s 22 -6.2501 1.325491 -1.104428 198s 23 -7.2419 0.839808 0.728712 198s 24 -7.6489 1.131606 0.154897 198s 25 -9.0763 -0.670721 -0.167577 198s 26 -5.5967 0.999411 -0.810000 198s 27 -5.1460 -0.339018 1.326712 198s 28 -7.1659 -0.993461 0.125933 198s 29 -8.2104 -0.169338 -0.073569 198s 30 -6.2499 -1.689222 -0.877481 198s 31 -7.3180 -0.225795 1.687204 198s 32 -7.9446 1.473868 -0.541790 198s 33 -6.3604 1.237472 0.061800 198s 34 -8.9812 -0.710662 -0.830422 198s 35 -5.1698 -0.435484 1.102817 198s 36 -5.9995 -0.058135 -0.713550 198s 37 -5.8753 0.852882 -1.610556 198s 38 -8.4501 0.334363 0.404813 198s 39 -8.1751 -1.300317 0.633282 198s 40 -7.4495 0.672712 -0.829815 198s 41 -5.6213 -1.106765 1.395315 198s 42 -6.8571 -0.900977 -1.509937 198s 43 -7.0633 1.987372 -1.079934 198s 44 -6.3763 -1.867647 -0.251224 198s 45 -8.6456 -0.866053 0.630132 198s 46 -6.5356 -1.763526 -0.189838 198s 47 -8.2224 -1.183284 1.615150 198s 48 -5.6136 -1.100704 1.079239 198s 49 -5.9907 0.220336 1.443387 198s 50 -5.2675 0.142923 0.194023 198s 51 -7.9324 0.324710 1.113289 198s 52 -7.5544 -1.033884 1.792496 198s 53 -6.7119 -1.712257 -1.711778 198s 54 -7.4679 1.856542 0.046658 198s 55 -7.4666 1.161504 -0.725948 198s 56 -6.7110 1.574868 0.534288 198s 57 -8.2571 -0.399824 0.521995 198s 58 -5.9781 1.312567 0.926790 198s 59 -5.6960 -0.394338 -0.332938 198s 60 -6.1017 -0.797579 -1.679359 198s 61 -5.2628 0.919128 -1.436156 198s 62 -9.1245 -0.516135 -0.229065 198s 63 -7.7140 1.659145 0.068510 198s 64 -4.9886 0.173613 0.865810 198s 65 -6.6157 -1.479786 0.098390 198s 66 -7.9511 0.772770 -0.998321 198s 67 -7.1856 0.459602 0.216588 198s 68 -8.7345 -0.860784 -1.238576 198s 69 -8.5833 -0.313481 0.832074 198s 70 -5.8642 -0.142883 -0.870064 198s 71 -5.8879 0.186456 0.464467 198s 72 -7.1865 0.497156 -0.826767 198s 73 -6.8671 -0.058606 -1.335842 198s 74 -7.1398 0.727642 -1.422331 198s 75 -7.2696 -1.347832 -1.496927 198s ------------- 198s Call: 198s PcaClassic(x = x) 198s 198s Standard deviations: 198s [1] 14.70245 1.40751 0.95725 198s ---------------------------------------------------------- 198s milk 86 8 8 15.940298 2.771345 198s Scores: 198s PC1 PC2 PC3 PC4 PC5 PC6 PC7 198s 1 6.471620 1.031110 0.469432 0.5736412 1.0294362 -0.6054039 -0.2005117 198s 2 7.439545 0.320597 0.081922 -0.6305898 0.7128977 -1.1601053 -0.1170582 198s 3 1.240654 -1.840458 0.520870 -0.1717469 0.2752079 -0.3815506 0.6004089 198s 4 5.952685 -1.856375 1.638710 0.3358626 -0.5834205 -0.0665348 -0.1580799 198s 5 -0.706973 0.261795 0.423736 0.2916399 -0.5307716 -0.3325563 -0.0062349 198s 6 2.524050 0.293380 -0.572997 0.2466367 -0.3497882 0.0386014 -0.1418131 198s 7 3.136085 -0.050202 -0.818165 -0.0451560 -0.5226337 -0.1597194 0.1669050 198s 8 3.260390 0.312365 -0.110776 0.4908006 -0.5225353 -0.1972222 -0.1068433 198s 9 -0.808914 -2.355785 1.344204 -0.4743284 -0.1394914 -0.1390080 -0.2620731 198s 10 -2.511226 -0.995321 -0.087218 -0.5950040 0.4268321 0.2561918 0.0891170 198s 11 -9.204096 -0.598364 1.587275 0.0833647 0.1865626 0.0358228 0.0920394 198s 12 -12.946774 1.951332 -0.179186 0.2560603 0.1300954 -0.1179820 -0.0999494 198s 13 -10.011603 0.726323 -2.102423 -1.3105560 0.3291550 0.0660007 -0.0794410 198s 14 -11.983644 0.768224 -0.532227 -0.5161201 -0.0817164 -0.4358934 -0.1734612 198s 15 -10.465714 -0.704271 2.035437 0.3713778 -0.0564830 -0.2696432 -0.1940091 198s 16 -2.527619 -0.286939 0.354497 0.8571223 0.1585009 0.2272835 0.4386955 198s 17 -0.514527 -2.895087 1.657181 0.2208239 0.1961109 0.1280496 -0.0182491 198s 18 -1.763931 0.854269 -0.686282 0.2848209 -0.4813608 -0.2623962 0.4757030 198s 19 -1.538419 -0.866477 1.103818 0.3874507 0.2086661 0.1267277 0.2354264 198s 20 0.732842 -1.455594 1.097358 -0.2530588 -0.0302385 0.2654274 0.6093330 198s 21 -2.530155 1.932885 -0.873095 0.6202295 -0.4153607 0.0048383 0.0067484 198s 22 -0.772646 0.675846 -0.259539 0.4844670 -0.0893266 -0.2785557 -0.0424662 198s 23 0.185417 1.413719 0.066135 1.1014470 0.0468093 0.0288637 0.2539994 198s 24 -0.280536 0.908864 0.113221 1.3370381 0.3289929 0.2588134 -0.0356289 198s 25 -3.503626 1.971233 0.203620 1.1975494 -0.3175317 0.1149685 0.0584396 198s 26 -0.639313 1.175503 0.403906 0.9082134 -0.2648165 -0.1238813 -0.0174853 198s 27 -2.923327 -0.365168 0.149478 0.8201430 -0.1544609 -0.4856934 -0.0058424 198s 28 2.505633 3.050292 -0.554424 2.1416405 -0.0378764 0.1002280 -0.3888580 198s 29 4.649504 1.054863 -0.081018 1.1454466 0.1502080 0.4967323 0.0879775 198s 30 1.049282 1.355215 -0.142701 0.7805566 -0.2059790 0.0193142 0.0815524 198s 31 1.962583 1.595396 -2.050642 0.3556747 0.1384801 0.1197984 0.1608247 198s 32 1.554846 0.095644 -1.423054 -0.3175620 0.4260008 -0.1612463 -0.0567196 198s 33 2.248977 0.010348 -0.062469 0.6388269 0.2098648 0.1330250 0.0906704 198s 34 0.993109 -0.828812 0.284059 0.3446686 0.1899096 -0.0515571 -0.2281197 198s 35 -0.335103 1.614093 -0.920661 1.2502617 0.2435013 0.1264875 0.0469238 198s 36 4.346795 1.208134 0.368889 1.1429977 -0.1362052 -0.0158169 -0.0183852 198s 37 0.992634 2.013738 -1.350619 0.8714694 0.0057776 -0.2122691 0.1760918 198s 38 2.213341 1.706516 -0.705418 1.2670281 -0.0707149 0.0670467 -0.1863588 198s 39 -1.213255 0.644062 0.163988 1.1213961 0.2945355 0.1093574 0.0019574 198s 40 3.942604 -1.704266 0.660327 0.1618506 0.4259076 0.0070193 0.3462765 198s 41 4.262054 1.687193 0.351875 0.5396477 1.0052810 -0.9331689 0.0056063 198s 42 6.865198 -1.091248 1.153585 1.1248797 0.0873276 0.2565221 0.0333265 198s 43 3.476720 0.555449 -1.030771 -0.3015720 -0.1748109 -0.1584968 0.4079902 198s 44 5.691730 -0.141240 0.565189 0.3174238 0.6478440 1.0579977 -0.5387916 198s 45 0.327134 0.152011 -0.394798 0.4998430 0.1599781 0.3159518 0.1623656 198s 46 0.280225 1.569387 -0.100397 1.2800976 0.0446645 0.0946513 0.0461599 198s 47 3.119928 -0.384834 -3.325600 -1.8865310 -0.1334744 0.1249987 -0.2561273 198s 48 0.501542 0.739816 -1.384556 -0.1244721 0.2948958 0.4836170 -0.1182802 198s 49 -1.953218 0.269986 -1.726474 -0.8510637 0.5047958 0.4860651 0.2318735 198s 50 3.706878 -2.400570 1.361047 -0.4949076 0.2180352 0.4080879 0.1156540 198s 51 -1.060358 -0.521609 -1.387412 -1.2767491 -0.0521356 0.1665452 -0.0044412 198s 52 -4.900528 0.157011 -1.015880 -0.9941168 0.2069608 0.3239762 -0.1921715 198s 53 -0.388496 0.062051 -0.643721 -0.8544141 -0.1857141 0.0063293 0.2664606 198s 54 0.109234 -0.018709 -0.242825 -0.2064701 -0.0585165 0.1720867 0.1117397 198s 55 1.176175 0.644539 -0.373694 0.0038605 -0.3436524 0.0194450 -0.0838883 198s 56 0.407259 -0.606637 0.222915 -0.3622451 -0.0737834 0.0228104 0.0297333 198s 57 -1.022756 -0.071860 0.741957 0.2273628 -0.1388444 -0.2396467 -0.2327738 198s 58 0.245419 1.167059 0.225934 0.8318795 -0.5365166 -0.0090816 -0.1680757 198s 59 -1.300617 -1.110325 -0.262740 -0.8857801 -0.0816954 -0.1186886 -0.0928322 198s 60 -1.110561 -0.832357 -0.212713 -0.4754481 -0.4105982 -0.1886992 -0.0602872 198s 61 0.381831 -1.475116 0.601047 -0.6260156 -0.1854501 -0.1749306 -0.0013904 198s 62 2.734462 -1.887861 0.813453 -0.5856987 0.2310656 0.1117041 -0.0293373 198s 63 3.092464 -0.172602 0.017725 0.4874693 -0.5428206 0.0151218 -0.0683340 198s 64 3.092464 -0.172602 0.017725 0.4874693 -0.5428206 0.0151218 -0.0683340 198s 65 0.004744 -2.712679 1.178987 -0.6677199 0.0208119 0.0621903 -0.0655693 198s 66 -2.014851 -1.060090 -0.099959 -0.7225044 -0.1947648 -0.2282902 -0.0505015 198s 67 0.621739 -1.296106 0.255632 -0.3309504 -0.0880200 0.2524306 0.1465779 198s 68 -0.271385 -1.709161 -1.100349 -2.0937671 0.2166264 0.0191278 0.0114174 198s 69 -0.326350 -0.737232 0.021639 -0.3850383 -0.4338287 0.2156624 0.1597594 198s 70 4.187093 9.708082 4.632803 -4.9751240 -0.0881576 0.2392433 0.0568049 198s 71 -1.868507 -1.600166 0.436353 -0.8078214 -0.1530893 0.0479471 -0.1999893 198s 72 2.768081 -0.556824 -0.148923 -0.3197853 -0.5524427 0.0907804 -0.0694488 198s 73 -1.441846 -2.735114 -0.294134 -1.2172969 0.0109453 -0.0562910 0.1505788 198s 74 -10.995490 0.615992 1.950966 1.1687190 0.2798335 0.2713257 0.0652135 198s 75 0.508992 -2.363945 -0.407064 -0.9522316 0.1040307 0.1088110 -0.7368484 198s 76 -1.015714 -0.307662 -1.088162 -1.0181862 -0.0440888 -0.1362208 0.0271200 198s 77 -8.028891 -0.580763 0.933638 0.4619362 0.3379832 -0.1368644 -0.0669441 198s 78 1.763308 -1.336175 -0.127809 -0.7161775 -0.1904861 -0.0900461 0.0037539 198s 79 0.208944 -0.580698 -0.626297 -0.7620610 -0.0262368 -0.2928202 0.0285908 198s 80 -3.230608 1.251352 0.195280 0.8687004 0.1812011 0.2600692 -0.1516375 198s 81 1.498160 0.669731 -0.266114 0.3772866 -0.2769688 -0.1066593 -0.1608395 198s 82 3.232051 -1.776018 0.485524 0.1170945 0.0557260 0.2219872 0.1187681 198s 83 2.999977 -0.228275 -0.467724 -0.4287672 0.0494902 -0.2337809 -0.0718159 198s 84 1.238083 0.320956 -1.806006 -1.0142266 0.2359630 -0.0857149 0.0593938 198s 85 1.276376 -2.081214 2.540850 0.3745805 -0.2596482 -0.1228412 -0.2199985 198s 86 0.930715 0.836457 -1.385153 -0.6074929 -0.2476354 0.1680713 -0.0117324 198s PC8 198s 1 9.0765e-04 198s 2 2.1811e-04 198s 3 1.1834e-03 198s 4 8.4077e-05 198s 5 9.9209e-04 198s 6 1.6277e-03 198s 7 2.4907e-04 198s 8 6.8383e-04 198s 9 -5.0924e-04 198s 10 3.1215e-04 198s 11 3.0654e-04 198s 12 -1.1951e-03 198s 13 -1.2849e-03 198s 14 -9.0801e-04 198s 15 -1.2686e-03 198s 16 -1.8441e-03 198s 17 -2.1068e-03 198s 18 -5.7816e-04 198s 19 -1.2330e-03 198s 20 3.3857e-05 198s 21 3.8623e-04 198s 22 1.3035e-04 198s 23 -3.8648e-04 198s 24 -1.7400e-04 198s 25 -3.9196e-04 198s 26 -7.6996e-04 198s 27 -4.8042e-04 198s 28 -2.0628e-04 198s 29 -4.5672e-04 198s 30 -1.4716e-04 198s 31 -4.6385e-05 198s 32 -2.0481e-04 198s 33 -3.0020e-04 198s 34 -5.8179e-05 198s 35 1.3870e-04 198s 36 -6.7177e-04 198s 37 -3.0799e-04 198s 38 6.2140e-04 198s 39 4.5912e-04 198s 40 -3.7165e-04 198s 41 -5.4362e-04 198s 42 -1.0155e-03 198s 43 1.3449e-04 198s 44 -5.4761e-04 198s 45 1.0300e-03 198s 46 1.1039e-03 198s 47 -6.4858e-04 198s 48 -7.6886e-05 198s 49 3.2590e-04 198s 50 8.6845e-05 198s 51 4.9423e-04 198s 52 9.2973e-04 198s 53 4.4342e-04 198s 54 4.9888e-04 198s 55 7.2171e-04 198s 56 -3.2133e-05 198s 57 -1.8101e-04 198s 58 -5.4969e-06 198s 59 -8.3841e-04 198s 60 5.9446e-05 198s 61 -6.5683e-05 198s 62 -3.4073e-04 198s 63 -6.5145e-04 198s 64 -6.5145e-04 198s 65 1.4986e-04 198s 66 2.8096e-04 198s 67 -6.5170e-05 198s 68 -1.3775e-04 198s 69 6.8225e-06 198s 70 -1.6290e-04 198s 71 3.9009e-04 198s 72 -1.3981e-04 198s 73 6.2613e-04 198s 74 2.6513e-03 198s 75 3.7088e-04 198s 76 9.9539e-04 198s 77 1.2979e-03 198s 78 5.6500e-04 198s 79 3.0940e-04 198s 80 8.7993e-04 198s 81 -3.1353e-04 198s 82 4.9625e-04 198s 83 -6.3951e-04 198s 84 -4.5582e-04 198s 85 5.9440e-04 198s 86 -3.6234e-04 198s ------------- 198s Call: 198s PcaClassic(x = x) 198s 198s Standard deviations: 198s [1] 3.99253025 1.66473582 1.10660264 0.96987790 0.33004256 0.29263512 0.20843280 198s [8] 0.00074024 198s ---------------------------------------------------------- 198s bushfire 38 5 5 38435.075910 1035.305774 198s Scores: 198s PC1 PC2 PC3 PC4 PC5 198s 1 -111.9345 4.9970 -1.00881 -1.224361 3.180569 198s 2 -113.4128 7.4784 -0.79170 -0.235184 2.385812 198s 3 -105.8364 10.9615 -3.15662 -0.251662 1.017328 198s 4 -89.1684 8.7232 -6.15080 -0.075611 1.431111 198s 5 -58.7216 -1.9543 -12.70661 -0.151328 1.425570 198s 6 -35.0370 -12.8434 -17.06841 -0.525664 3.499743 198s 7 -250.2123 -49.4348 23.31261 -19.070238 0.647348 198s 8 -292.6877 -69.7708 -21.30815 13.093808 -1.288764 198s 9 -294.0765 -70.9903 -23.96326 14.940985 -0.939076 198s 10 -290.0193 -57.3747 3.51346 1.858995 0.083107 198s 11 -289.8168 -43.3207 16.08046 -1.745099 -1.506042 198s 12 -290.8645 6.2503 40.52173 -7.496479 -0.033767 198s 13 -232.6865 41.8090 37.19429 -1.280348 -0.470837 198s 14 9.8483 25.1954 -14.56970 0.538484 1.772046 198s 15 137.1924 11.8521 -37.12452 -5.130459 -0.586695 198s 16 92.9804 10.3923 -24.97267 -7.551314 -1.867125 198s 17 90.4493 10.5630 -21.92735 -5.669651 -1.001362 198s 18 78.6325 5.2211 -19.74718 -6.107880 -1.939986 198s 19 82.1178 3.6913 -21.37810 -4.259855 -1.278838 198s 20 92.9044 7.1961 -21.22900 -4.125571 -0.127089 198s 21 74.9157 10.2991 -16.60924 -5.660751 -0.406343 198s 22 66.7350 12.0460 -16.73298 -4.669080 1.333436 198s 23 -62.1981 22.7394 6.03613 -5.182356 -0.453624 198s 24 -116.5696 32.3182 12.74846 -1.465657 -0.097851 198s 25 -53.8907 22.4278 -2.18861 -2.742014 -0.990071 198s 26 -60.6384 20.2952 -3.05206 -2.953685 -0.629061 198s 27 -74.7621 28.9067 -0.65817 1.473357 -0.443957 198s 28 -50.2202 37.3457 -1.44989 5.530426 -1.073521 198s 29 -38.7483 50.2749 2.34469 10.156457 -0.416262 198s 30 -93.3887 51.7884 20.08872 8.798781 -1.620216 198s 31 35.3096 41.7158 13.46272 14.464358 -0.475973 198s 32 290.8493 3.5924 7.41501 15.244293 2.141354 198s 33 326.7236 -29.8194 15.64898 2.612061 0.064931 198s 34 322.9095 -30.6372 16.21520 1.248005 -0.711322 198s 35 328.5307 -29.9533 16.49656 1.138916 0.974792 198s 36 325.6791 -30.6990 16.83840 -0.050949 -1.211360 198s 37 323.8136 -30.7474 19.55764 -1.545150 -0.267580 198s 38 325.2991 -30.5350 20.31878 -1.928580 -0.120425 198s ------------- 198s Call: 198s PcaClassic(x = x) 198s 198s Standard deviations: 198s [1] 196.0487 32.1762 18.4819 6.9412 1.3510 198s ---------------------------------------------------------- 198s ========================================================== 198s > dodata(method="hubert.mcd") 198s 198s Call: dodata(method = "hubert.mcd") 198s Data Set n p k e1 e2 198s ========================================================== 198s heart 12 2 2 358.175786 4.590630 198s Scores: 198s PC1 PC2 198s 1 -12.2285 0.86283 198s 2 -68.9906 -7.43256 198s 3 -5.7035 -1.53793 198s 4 -1.8988 2.90891 198s 5 -24.0044 -2.68946 198s 6 9.9115 8.43321 198s 7 -11.0210 1.77484 198s 8 25.1826 -1.31573 198s 9 -3.2809 -0.74345 198s 10 23.8200 -0.93701 198s 11 9.1344 1.67701 198s 12 -53.6607 -5.08826 198s ------------- 198s Call: 198s PcaHubert(x = x, k = p) 198s 198s Standard deviations: 198s [1] 18.9255 2.1426 198s ---------------------------------------------------------- 198s starsCYG 47 2 2 0.280653 0.005921 198s Scores: 198s PC1 PC2 198s 1 -0.285731 -0.0899858 198s 2 -0.819689 0.0153191 198s 3 0.028077 -0.1501882 198s 4 -0.819689 0.0153191 198s 5 -0.234971 -0.1526225 198s 6 -0.527231 -0.0382380 198s 7 0.372118 -0.5195605 198s 8 -0.357448 0.1009508 198s 9 -0.603553 -0.2533541 198s 10 -0.177170 -0.0722541 198s 11 -0.637339 -1.0390758 198s 12 -0.512526 -0.0662337 198s 13 -0.490978 -0.0120517 198s 14 0.936868 -0.2550656 198s 15 0.684479 -0.0125787 198s 16 0.347708 0.0641382 198s 17 1.009966 -0.0202111 198s 18 0.742477 0.1286170 198s 19 0.773105 -0.0588983 198s 20 -0.795247 -1.0648673 198s 21 0.566048 -0.0319223 198s 22 0.723956 -0.0061308 198s 23 0.505616 0.0899297 198s 24 0.069956 0.0896997 198s 25 -0.080090 -0.0462652 198s 26 0.268755 0.0512425 198s 27 0.289710 -0.0770574 198s 28 0.038341 -0.0269216 198s 29 0.567463 -0.1026188 198s 30 -0.951542 -1.1005280 198s 31 0.512064 0.0504528 198s 32 -0.188059 0.1184850 198s 33 -0.288758 -0.0094200 198s 34 -1.190016 -1.1293460 198s 35 0.615197 -0.0846898 198s 36 -0.710930 0.0938781 198s 37 -0.183223 0.0888774 198s 38 -0.288758 -0.0094200 198s 39 -0.262177 0.0759816 198s 40 -0.630957 -0.0855773 198s 41 0.314679 0.0182135 198s 42 -0.130850 0.0163715 198s 43 -0.415248 0.0205825 198s 44 -0.407188 -0.0287636 198s 45 -0.620693 0.0376892 198s 46 -0.051896 0.0292672 198s 47 0.426662 0.0770340 198s ------------- 198s Call: 198s PcaHubert(x = x, k = p) 198s 198s Standard deviations: 198s [1] 0.529767 0.076946 198s ---------------------------------------------------------- 198s phosphor 18 2 2 285.985489 32.152099 198s Scores: 198s PC1 PC2 198s 1 -2.89681 -18.08811 198s 2 21.34021 -0.40854 198s 3 22.98065 4.13006 198s 4 12.33544 -6.72947 198s 5 17.99823 2.47611 198s 6 -13.35773 -24.10967 198s 7 -0.92957 -5.51314 198s 8 9.16061 2.71354 198s 9 9.89243 5.10403 198s 10 -14.12600 -11.17832 198s 11 3.84175 -0.17605 198s 12 -10.61905 4.37646 198s 13 -13.85065 2.01919 198s 14 -8.11927 4.34325 198s 15 -18.69805 -1.51673 198s 16 9.95352 -6.85784 198s 17 -22.49433 0.29387 198s 18 -18.66592 6.92359 198s ------------- 198s Call: 198s PcaHubert(x = x, k = p) 198s 198s Standard deviations: 198s [1] 16.9111 5.6703 198s ---------------------------------------------------------- 198s stackloss 21 3 3 78.703690 19.249085 198s Scores: 198s PC1 PC2 PC3 198s 1 -20.323997 10.26124 0.92041 198s 2 -19.761418 11.08797 0.92383 198s 3 -16.469919 6.43190 0.22593 198s 4 -4.171902 1.68262 2.50695 198s 5 -3.756174 1.40774 0.57004 198s 6 -3.964038 1.54518 1.53850 198s 7 -7.547376 -3.27780 2.48643 198s 8 -7.547376 -3.27780 2.48643 198s 9 -0.763294 -0.63699 2.53518 198s 10 4.214079 4.46296 -2.28315 198s 11 -0.849132 -2.97767 -2.31393 198s 12 -0.078689 -2.28838 -3.27896 198s 13 3.088921 2.80948 -2.28999 198s 14 -3.307313 -6.14718 -1.35916 198s 15 5.552354 -7.34201 -0.32057 198s 16 7.240091 -4.86180 -0.31031 198s 17 14.908334 6.84995 0.70603 198s 18 10.970281 1.06279 0.68209 198s 19 10.199838 0.37350 1.64712 198s 20 4.273564 1.99328 0.14526 198s 21 -11.992249 2.19025 -3.37391 198s ------------- 198s Call: 198s PcaHubert(x = x, k = p) 198s 198s Standard deviations: 198s [1] 8.8715 4.3874 2.1990 198s ---------------------------------------------------------- 198s salinity 28 3 3 11.651966 4.107426 198s Scores: 198s PC1 PC2 PC3 198s 1 1.68712 1.62591 0.19812128 198s 2 2.35772 2.37290 1.24965734 198s 3 6.80132 -2.14412 0.68142276 198s 4 6.41982 -0.61348 -0.31907921 198s 5 6.36697 -1.98030 4.87319903 198s 6 5.22050 1.20864 0.10252555 198s 7 3.34007 2.02950 0.00064329 198s 8 1.06220 2.89801 -0.35658064 198s 9 0.34692 -2.20572 -1.71677710 198s 10 -2.21421 -2.74842 0.76862599 198s 11 -1.40111 -2.16163 2.21124383 198s 12 -0.38242 0.32284 -0.23732191 198s 13 -1.12809 1.33152 -0.28800043 198s 14 -3.24998 1.35943 1.17514969 198s 15 -2.11006 -3.70114 0.45102357 198s 16 3.46920 -5.41242 8.56937909 198s 17 0.46682 -1.46753 1.48992481 198s 18 2.21807 0.99168 -0.61894625 198s 19 0.28525 -2.00333 -2.16450483 198s 20 -1.66639 -1.76768 -1.06946404 198s 21 -2.58106 1.23534 -0.65557612 198s 22 -4.15573 1.71244 0.08170141 198s 23 -3.07670 -4.87628 2.53200755 198s 24 -1.70808 -3.71657 2.99305849 198s 25 -1.08172 -1.05713 0.02468813 198s 26 -2.23187 0.27323 -0.85760867 198s 27 -3.50498 1.07657 -0.68503455 198s 28 -4.49819 1.43219 0.53416609 198s ------------- 198s Call: 198s PcaHubert(x = x, k = p) 198s 198s Standard deviations: 198s [1] 3.4135 2.0267 1.0764 198s ---------------------------------------------------------- 198s hbk 75 3 3 1.459908 1.201048 198s Scores: 198s PC1 PC2 PC3 198s 1 -31.105415 4.714217 10.4566165 198s 2 -31.707650 5.748724 10.7682402 198s 3 -33.366131 4.625897 12.1570167 198s 4 -34.173377 6.069657 12.4466895 198s 5 -33.780418 5.508823 11.9872893 198s 6 -32.493478 4.684595 10.5679819 198s 7 -32.592637 5.235522 10.3765493 198s 8 -31.293363 4.865797 10.9379676 198s 9 -33.160964 5.714260 12.3098920 198s 10 -31.919786 5.384537 12.3374332 198s 11 -38.231962 6.810641 13.5994385 198s 12 -39.290479 5.393906 15.2942554 198s 13 -39.418445 7.326461 11.5194898 198s 14 -43.906584 13.214819 8.3282743 198s 15 -1.906326 -0.716061 -0.8635112 198s 16 -0.263255 -0.926016 -1.9009292 198s 17 1.776489 1.072332 -0.5496140 198s 18 -0.464648 -0.702441 0.0482897 198s 19 -0.267826 1.283779 -0.2925812 198s 20 -2.122108 -0.165970 -0.8924686 198s 21 -0.937217 -0.548532 -0.4132196 198s 22 -0.423273 1.781869 -0.0323061 198s 23 -0.047532 -0.018909 -1.1259327 198s 24 0.490041 0.520202 -1.1065753 198s 25 2.143049 -0.720869 -0.0495474 198s 26 -1.094748 1.459175 0.2226246 198s 27 -2.070705 -0.898573 0.0023229 198s 28 0.294998 -0.830258 0.5929001 198s 29 1.242995 -0.300216 -0.2010507 198s 30 -0.147958 -0.439099 2.0003038 198s 31 -0.170818 -1.440946 -0.9755627 198s 32 0.958531 1.199730 -1.0129867 198s 33 -0.697307 0.874343 -0.7260649 198s 34 2.278946 -0.261106 0.4196544 198s 35 -1.962829 -0.809318 0.2033113 198s 36 -0.626631 0.600666 0.8004036 198s 37 -0.550885 1.881448 0.7382776 198s 38 1.249717 -0.336214 -0.9349845 198s 39 1.106696 -1.569418 0.1869576 198s 40 0.684034 0.939963 -0.1034965 198s 41 -1.559314 -1.551408 0.3660323 198s 42 0.538741 0.447358 1.6361099 198s 43 0.252685 2.080564 -0.7765259 198s 44 -0.217012 -1.027281 1.7015154 198s 45 1.497600 -1.349234 -0.2698932 198s 46 -0.100388 -1.026443 1.5390401 198s 47 0.811117 -2.195271 -0.5208141 198s 48 -1.462210 -1.321318 0.5600144 198s 49 -1.383976 -0.740714 -0.7348906 198s 50 -1.636773 0.215464 0.3195369 198s 51 0.530918 -0.759743 -1.2069247 198s 52 0.109566 -2.107455 -0.5315473 198s 53 0.564334 0.060847 2.3910630 198s 54 0.272234 1.122711 -1.5060028 198s 55 0.608660 1.197219 -0.5255609 198s 56 -0.565430 0.710345 -1.3708230 198s 57 1.115629 -0.888816 -0.4186014 198s 58 -1.351288 0.374815 -1.1980618 198s 59 -0.998016 0.151228 0.9007970 198s 60 -0.124017 0.764846 1.9005963 198s 61 -1.189858 1.905264 0.7721322 198s 62 2.190589 -0.579614 -0.1377914 198s 63 0.518278 0.931130 -1.4534768 198s 64 -2.124566 -0.194391 -0.0327092 198s 65 -0.154218 -1.050861 1.1309885 198s 66 1.197852 1.044147 -0.2265269 198s 67 0.114174 0.094763 -0.5168926 198s 68 2.201115 -0.032271 0.8573493 198s 69 1.307843 -1.104815 -0.7741270 198s 70 -0.691449 0.676665 1.0004603 198s 71 -1.150975 -0.050861 -0.0717068 198s 72 0.457293 0.861871 0.1026350 198s 73 0.392258 0.897451 0.9178065 198s 74 0.584658 1.450471 0.3201857 198s 75 0.972517 0.063777 1.8223995 198s ------------- 198s Call: 198s PcaHubert(x = x, k = p) 198s 198s Standard deviations: 198s [1] 1.2083 1.0959 1.0168 198s ---------------------------------------------------------- 198s milk 86 8 8 5.739740 2.405262 198s Scores: 198s PC1 PC2 PC3 PC4 PC5 PC6 PC7 198s 1 -5.710924 -1.346213 0.01332091 -0.3709242 -0.566813 0.7529298 -1.2525433 198s 2 -6.578612 -0.440749 1.16354746 0.2870685 -0.573207 0.7368064 -1.6101427 198s 3 -0.720902 1.777381 -0.21532020 -0.3213950 0.287603 -0.4764464 -0.5638337 198s 4 -5.545889 1.621147 -0.85212883 0.4380154 0.022241 0.0718035 0.1176140 198s 5 1.323210 -0.143897 -0.78611461 0.5966857 0.043139 -0.0512545 -0.1419726 198s 6 -1.760792 -0.662792 0.46402240 0.2149752 0.130000 0.0797221 0.1916948 198s 7 -2.344198 -0.363657 0.92442296 0.3921371 0.241463 -0.2370967 0.0636268 198s 8 -2.556824 -0.680132 0.04339934 0.4635077 0.154136 0.0371259 0.0260340 198s 9 1.203234 2.712342 -1.00693092 0.1251739 0.170679 0.2231851 -0.0118196 198s 10 3.151858 1.255826 -0.01678562 -0.5087398 -0.087933 0.0115055 -0.0097828 198s 11 9.562891 1.580419 -2.65612113 -0.1748178 -0.153031 -0.0880112 -0.1648752 198s 12 13.617821 -0.999033 -1.92168237 0.0326918 -0.038488 0.0870082 -0.1809687 198s 13 10.958032 -0.097916 0.95915085 -0.2348663 0.147875 0.1219202 0.0419067 198s 14 12.675941 0.158747 -1.04153243 0.3117402 0.302036 0.1187749 -0.2310830 198s 15 10.726828 1.775339 -3.36786799 0.1285422 0.151594 0.0998947 -0.2028458 198s 16 3.042705 0.212589 -1.23921907 -0.5596596 0.277061 -0.5037073 0.0612182 198s 17 0.780071 2.990008 -1.58490147 -0.5441119 0.436485 -0.0603833 0.1016610 198s 18 2.523916 -0.923373 -0.03221722 0.3830822 0.208008 -0.5505270 -0.1252648 198s 19 1.990563 1.062648 -1.42038451 -0.3602257 -0.068006 -0.1932744 -0.1197842 198s 20 -0.243938 1.674555 -0.72225359 -0.1475652 -0.397855 -0.5385123 -0.0559660 198s 21 3.354424 -2.001060 -0.22542149 0.3346180 0.032502 -0.0953825 0.1293148 198s 22 1.477177 -0.777534 -0.35362339 0.1224412 0.203208 0.0514382 -0.2166274 198s 23 0.502055 -1.618511 -0.85013853 -0.1298862 -0.144328 -0.1941806 -0.1923681 198s 24 0.900504 -1.227820 -1.07180474 -0.5851197 0.112657 0.0467164 0.0405544 198s 25 4.161393 -1.869015 -1.54507759 0.2003123 -0.152582 -0.1382908 0.0864320 198s 26 1.277795 -1.185179 -1.13445511 0.2771556 -0.101901 0.0070037 -0.1279016 198s 27 3.447256 0.257652 -1.13407954 -0.0077859 0.853002 -0.1376443 -0.1897380 198s 28 -1.695730 -3.781876 -0.72940594 -0.0956421 0.064475 0.3665470 0.0726448 198s 29 -3.923610 -1.654818 -0.16117226 -0.4242302 -0.303749 -0.0209844 0.1723890 198s 30 -0.309616 -1.564739 -0.39909943 0.1657509 -0.178739 -0.0600221 -0.0571706 198s 31 -0.960838 -2.242733 1.50477679 -0.2957897 0.163758 -0.1034399 0.0257903 198s 32 -0.671285 -0.459839 1.39124475 -0.3669914 0.246127 0.2094780 -0.2681284 198s 33 -1.589089 -0.390812 -0.16505762 -0.3992573 0.086870 -0.0402114 -0.0399923 198s 34 -0.421868 0.636139 -0.42563447 -0.2985726 0.311365 0.2398515 -0.0540852 198s 35 1.118429 -2.116328 -0.22329747 -0.4864401 0.289927 -0.0503006 0.0101706 198s 36 -3.660291 -1.630831 -0.57876280 0.1294792 -0.260224 0.0912904 -0.1565668 198s 37 -0.087686 -2.530609 0.50076931 -0.0319873 0.194898 -0.1233526 -0.2494283 198s 38 -1.418620 -2.303011 -0.09405565 -0.0931745 0.169466 0.1581787 0.0850095 198s 39 1.815225 -0.838968 -1.10222194 -0.4897630 0.180933 0.0096330 -0.0600652 198s 40 -3.420975 1.398516 -0.17143314 -0.5852146 0.090464 -0.2066323 -0.2974177 198s 41 -3.462295 -1.795174 -0.17500650 -0.1610267 -0.595086 0.5981680 -1.5930268 198s 42 -6.401429 0.451242 -0.78723149 -0.4285618 0.055395 -0.0212476 0.0808936 198s 43 -2.583017 -0.871790 1.29937081 0.2422349 -0.190002 -0.2822972 -0.2625721 198s 44 -5.027244 -0.167503 -0.02382957 -0.8288929 -0.852207 0.7399343 0.4606076 198s 45 0.364494 -0.440380 -0.07746564 -0.4552133 0.095711 -0.1662998 0.1566706 198s 46 0.420706 -1.880819 -0.82180986 -0.1823454 -0.022661 -0.0304227 -0.0516440 198s 47 -1.932985 -0.120002 4.00934170 0.0930728 0.295428 0.2787446 0.3766231 198s 48 0.395402 -1.021393 1.07953292 -0.4599764 -0.132386 0.1895780 0.2771755 198s 49 2.886100 -0.276587 1.48851137 -0.6314648 -0.203963 -0.0891955 0.1347804 198s 50 -3.255379 2.479232 -0.37933775 -0.3651497 -0.415000 0.0045750 0.0671055 198s 51 1.939333 0.617579 1.57113225 0.0310866 -0.039226 0.0409183 0.1830694 198s 52 5.727154 0.275898 0.58814711 -0.1739820 -0.222791 0.2553797 0.1959402 198s 53 1.207873 0.131451 0.80899235 0.2872465 -0.353544 -0.1697200 -0.0987230 198s 54 0.612921 0.040062 0.17807459 -0.0053074 -0.202244 -0.0671788 0.0530276 198s 55 -0.399075 -0.727144 0.26196635 0.3657576 -0.192705 0.0903564 0.0641289 198s 56 0.240719 0.733792 -0.05030509 0.0967214 -0.186906 0.0310231 -0.0594812 198s 57 1.589641 0.289427 -1.02478822 0.2723190 -0.048378 0.2599262 -0.2040853 198s 58 0.423483 -1.262515 -0.85026016 0.4749963 -0.082647 0.0752412 0.1352259 198s 59 1.983684 1.335122 0.42593757 0.1345894 0.096456 0.1153107 -0.0385994 198s 60 1.770171 0.935428 0.14901569 0.3641973 0.274015 -0.0280119 0.0690244 198s 61 0.182845 1.706453 -0.18364654 0.2517421 -0.035773 0.0357087 -0.1363470 198s 62 -2.191617 1.966324 -0.03573689 -0.2203900 -0.235704 0.1682332 -0.1145174 198s 63 -2.442239 -0.209694 -0.06681921 0.3184048 0.206772 -0.0608468 0.2425649 198s 64 -2.442239 -0.209694 -0.06681921 0.3184048 0.206772 -0.0608468 0.2425649 198s 65 0.407575 2.996346 -0.63021113 -0.1335795 0.087668 0.0627032 0.0486166 198s 66 2.660379 1.322824 0.10122110 0.2420451 0.192938 0.0344019 -0.0771918 198s 67 -0.032273 1.315299 -0.04511689 -0.1293380 -0.025923 -0.1655965 0.1887534 198s 68 1.117637 2.005809 1.97078787 -0.0429209 -0.176568 0.1634287 -0.0916254 198s 69 0.970730 0.837158 0.01621375 0.2347502 -0.071757 -0.2464626 0.2907551 198s 70 -2.688271 -5.335891 -0.64225481 4.1819517 -9.523550 2.0943027 -2.8098426 198s 71 2.428718 1.976051 -0.24749122 0.1308738 0.018276 0.1711292 0.1346284 198s 72 -2.061944 0.405943 0.50472914 0.4393739 -0.056420 -0.0031558 0.2663880 198s 73 2.029606 2.874991 0.68310320 -0.2067254 0.511537 -0.2010371 0.0805608 198s 74 11.293757 0.328931 -3.84783031 -0.4130266 -0.210499 -0.1103148 -0.0381326 198s 75 0.120896 2.287914 0.83639076 -0.2462845 0.551353 0.6629701 0.3789055 198s 76 1.859499 0.422019 1.18435547 0.1546108 0.017266 0.0470615 -0.1071011 198s 77 8.435857 1.147499 -2.19924186 -0.4156770 0.386548 0.0294075 -0.1911399 198s 78 -1.090858 1.311287 0.62897430 0.1727009 0.077341 0.0135972 -0.0096934 198s 79 0.560012 0.623617 0.83727267 0.1680787 0.087477 0.0611949 -0.2588084 198s 80 3.873817 -1.133641 -1.27469019 -0.2717298 -0.165066 0.1696232 0.0635047 198s 81 -0.758664 -0.880260 0.00057124 0.2838720 0.016243 0.1527299 -0.0150514 198s 82 -2.709588 1.464049 -0.12598126 -0.3828567 0.213647 -0.1425385 0.1552827 198s 83 -2.213670 0.059563 0.87565603 0.1255703 -0.082005 0.2189829 -0.2938264 198s 84 -0.242242 -0.483552 2.05089334 -0.0681005 -0.101578 0.1304632 -0.2218093 198s 85 -1.032129 2.375018 -2.19321259 0.2332079 -0.066379 0.1854598 -0.0873859 198s 86 0.015327 -0.948155 1.39530555 0.2701225 -0.268889 0.0578145 0.1608678 198s PC8 198s 1 2.1835e-03 198s 2 1.6801e-03 198s 3 1.6623e-03 198s 4 2.6286e-04 198s 5 9.5884e-04 198s 6 1.4430e-03 198s 7 1.8784e-04 198s 8 6.8473e-04 198s 9 -6.8490e-04 198s 10 1.1565e-04 198s 11 5.6907e-06 198s 12 -1.8395e-03 198s 13 -2.1582e-03 198s 14 -1.6294e-03 198s 15 -1.6964e-03 198s 16 -1.9664e-03 198s 17 -2.2448e-03 198s 18 -6.5884e-04 198s 19 -1.1536e-03 198s 20 2.6887e-04 198s 21 3.3199e-05 198s 22 1.1170e-04 198s 23 -1.7617e-04 198s 24 -2.1577e-04 198s 25 -6.1495e-04 198s 26 -7.2903e-04 198s 27 -6.8773e-04 198s 28 -2.0742e-04 198s 29 -2.6937e-04 198s 30 -6.7472e-05 198s 31 -1.3222e-04 198s 32 -1.6516e-04 198s 33 -1.8836e-04 198s 34 -1.1273e-04 198s 35 3.0703e-05 198s 36 -3.0311e-04 198s 37 -1.9380e-04 198s 38 5.5526e-04 198s 39 4.1987e-04 198s 40 8.4807e-05 198s 41 8.8725e-04 198s 42 -6.5647e-04 198s 43 4.3202e-04 198s 44 -5.3330e-04 198s 45 8.9161e-04 198s 46 1.1588e-03 198s 47 -1.2714e-03 198s 48 -4.0376e-04 198s 49 4.1280e-06 198s 50 3.0116e-04 198s 51 5.8510e-05 198s 52 3.3236e-04 198s 53 4.0982e-04 198s 54 4.0428e-04 198s 55 6.1600e-04 198s 56 -4.0496e-05 198s 57 -1.8342e-04 198s 58 -1.6748e-04 198s 59 -1.0894e-03 198s 60 -2.6876e-04 198s 61 -5.8951e-05 198s 62 -1.5517e-04 198s 63 -7.9933e-04 198s 64 -7.9933e-04 198s 65 2.2592e-05 198s 66 2.4984e-05 198s 67 -2.2714e-04 198s 68 -3.3991e-04 198s 69 -3.0375e-04 198s 70 3.4033e-03 198s 71 2.3288e-05 198s 72 -3.4126e-04 198s 73 2.5528e-04 198s 74 2.2760e-03 198s 75 -2.8985e-04 198s 76 7.9077e-04 198s 77 9.4636e-04 198s 78 4.9099e-04 198s 79 3.0501e-04 198s 80 6.5280e-04 198s 81 -3.6570e-04 198s 82 4.9966e-04 198s 83 -4.3245e-04 198s 84 -4.6152e-04 198s 85 7.4691e-04 198s 86 -6.1103e-04 198s ------------- 198s Call: 198s PcaHubert(x = x, k = p) 198s 198s Standard deviations: 198s [1] 2.39577535 1.55089079 0.92557331 0.33680677 0.19792033 0.17855133 0.16041702 198s [8] 0.00054179 198s ---------------------------------------------------------- 198s bushfire 38 5 5 31248.552973 358.974577 198s Scores: 198s PC1 PC2 PC3 PC4 PC5 198s 1 155.972 1.08098 -23.31135 -1.93015 1.218941 198s 2 157.738 0.35648 -20.95658 -2.42375 0.466415 198s 3 150.667 2.12545 -16.20395 -2.00140 -0.582924 198s 4 133.892 5.25124 -15.88873 -2.78469 -0.275261 198s 5 102.462 13.00611 -21.54096 -4.69409 -0.944176 198s 6 77.694 18.75377 -28.71865 -6.44244 0.446350 198s 7 286.266 -11.36184 -98.67134 10.95233 -3.625338 198s 8 326.627 29.92767 -112.60824 -29.26330 -13.710094 198s 9 327.898 32.39553 -113.34314 -31.65905 -13.830781 198s 10 325.131 5.81628 -105.58927 -13.45695 -8.987971 198s 11 326.458 -7.84562 -94.25242 -6.11547 -8.572845 198s 12 333.171 -37.69907 -50.89207 8.98187 -1.742979 198s 13 279.789 -40.78415 -8.06209 7.65884 0.181748 198s 14 37.714 10.54231 13.46530 -1.55051 2.102662 198s 15 -90.034 34.68964 18.98186 0.69260 0.417573 198s 16 -46.492 23.65086 10.07282 4.36090 -0.748517 198s 17 -43.990 20.36443 9.61049 2.83084 -0.127983 198s 18 -32.938 19.11199 2.64850 2.92879 -1.473988 198s 19 -36.555 20.60142 2.01879 0.63832 -1.235075 198s 20 -46.837 19.89630 6.65142 0.89120 0.271108 198s 21 -28.670 15.29534 6.59311 3.29638 0.402194 198s 22 -20.331 15.06559 7.33721 2.16591 2.006327 198s 23 108.644 -7.92707 -1.45130 6.27388 0.356715 198s 24 163.697 -16.15568 0.61663 4.24231 0.464415 198s 25 100.471 -0.30739 0.87762 2.86452 -0.692735 198s 26 106.922 0.90864 -1.91436 2.54557 -0.565023 198s 27 121.966 -3.29641 4.85626 -0.47676 -0.490047 198s 28 98.650 -4.51455 16.64160 -3.08996 -0.839397 198s 29 88.795 -10.85457 30.46708 -5.37360 0.315657 198s 30 142.981 -27.89100 22.40713 -1.67126 -0.680158 198s 31 14.125 -21.60028 29.80480 -8.25272 -0.019693 198s 32 -244.044 -11.76430 24.53390 -12.52294 2.022312 198s 33 -283.842 -13.21931 -6.23565 -2.63367 -0.080728 198s 34 -280.168 -13.41903 -7.69318 -1.24571 -0.722513 198s 35 -285.666 -13.78452 -6.50318 -1.23756 1.074669 198s 36 -282.938 -13.82281 -7.63902 0.20435 -0.971673 198s 37 -281.129 -16.20408 -8.57154 1.85797 0.234486 198s 38 -282.589 -16.91969 -8.36010 2.35589 0.490630 198s ------------- 198s Call: 198s PcaHubert(x = x, k = p) 198s 198s Standard deviations: 198s [1] 176.77260 18.94662 16.21701 3.95755 0.92761 198s ---------------------------------------------------------- 198s ========================================================== 198s > dodata(method="hubert") 198s 198s Call: dodata(method = "hubert") 198s Data Set n p k e1 e2 198s ========================================================== 198s heart 12 2 1 315.227002 NA 198s Scores: 198s PC1 198s 1 13.2197 198s 2 69.9817 198s 3 6.6946 198s 4 2.8899 198s 5 24.9956 198s 6 -8.9203 198s 7 12.0121 198s 8 -24.1915 198s 9 4.2721 198s 10 -22.8289 198s 11 -8.1433 198s 12 54.6519 198s ------------- 198s Call: 198s PcaHubert(x = x, mcd = FALSE) 198s 198s Standard deviations: 198s [1] 17.755 198s ---------------------------------------------------------- 198s starsCYG 47 2 1 0.308922 NA 198s Scores: 198s PC1 198s 1 0.224695 198s 2 0.758653 198s 3 -0.089113 198s 4 0.758653 198s 5 0.173934 198s 6 0.466195 198s 7 -0.433154 198s 8 0.296411 198s 9 0.542517 198s 10 0.116133 198s 11 0.576303 198s 12 0.451490 198s 13 0.429942 198s 14 -0.997904 198s 15 -0.745515 198s 16 -0.408745 198s 17 -1.071002 198s 18 -0.803514 198s 19 -0.834141 198s 20 0.734210 198s 21 -0.627085 198s 22 -0.784992 198s 23 -0.566652 198s 24 -0.130992 198s 25 0.019053 198s 26 -0.329791 198s 27 -0.350747 198s 28 -0.099378 198s 29 -0.628499 198s 30 0.890506 198s 31 -0.573100 198s 32 0.127022 198s 33 0.227721 198s 34 1.128979 198s 35 -0.676234 198s 36 0.649894 198s 37 0.122186 198s 38 0.227721 198s 39 0.201140 198s 40 0.569920 198s 41 -0.375716 198s 42 0.069814 198s 43 0.354212 198s 44 0.346152 198s 45 0.559656 198s 46 -0.009140 198s 47 -0.487699 198s ------------- 198s Call: 198s PcaHubert(x = x, mcd = FALSE) 198s 198s Standard deviations: 198s [1] 0.55581 198s ---------------------------------------------------------- 198s phosphor 18 2 1 215.172048 NA 198s Scores: 198s PC1 198s 1 1.12634 198s 2 -22.10340 198s 3 -23.49216 198s 4 -13.45927 198s 5 -18.60808 198s 6 11.24086 198s 7 -0.14748 198s 8 -9.77075 198s 9 -10.37022 198s 10 12.71798 198s 11 -4.61857 198s 12 10.07037 198s 13 13.16767 198s 14 7.57254 198s 15 17.81362 198s 16 -11.08799 198s 17 21.70358 198s 18 18.24496 198s ------------- 198s Call: 198s PcaHubert(x = x, mcd = FALSE) 198s 198s Standard deviations: 198s [1] 14.669 198s ---------------------------------------------------------- 199s stackloss 21 3 2 77.038636 18.859777 199s Scores: 199s PC1 PC2 199s 1 -20.334936 10.28081 199s 2 -19.772121 11.10736 199s 3 -16.461573 6.43794 199s 4 -4.258672 1.73213 199s 5 -3.773146 1.41928 199s 6 -4.015909 1.57571 199s 7 -7.635560 -3.22715 199s 8 -7.635560 -3.22715 199s 9 -0.855388 -0.58707 199s 10 4.298129 4.41664 199s 11 -0.767202 -3.02229 199s 12 0.038375 -2.35217 199s 13 3.172500 2.76354 199s 14 -3.261224 -6.17206 199s 15 5.553840 -7.34784 199s 16 7.242284 -4.86820 199s 17 14.878925 6.85989 199s 18 10.939223 1.07406 199s 19 10.133645 0.40394 199s 20 4.267234 1.99501 199s 21 -11.859921 2.12579 199s ------------- 199s Call: 199s PcaHubert(x = x, mcd = FALSE) 199s 199s Standard deviations: 199s [1] 8.7772 4.3428 199s ---------------------------------------------------------- 199s salinity 28 3 2 8.001175 5.858089 199s Scores: 199s PC1 PC2 199s 1 2.858444 1.04359 199s 2 3.807704 1.55974 199s 3 6.220733 -4.32114 199s 4 6.388841 -2.83649 199s 5 6.077450 -3.70092 199s 6 5.974494 -0.67230 199s 7 4.531584 0.78322 199s 8 2.725849 2.41297 199s 9 0.100501 -2.13615 199s 10 -2.358003 -1.49718 199s 11 -1.317688 -1.15391 199s 12 0.434635 0.58230 199s 13 0.116019 1.79022 199s 14 -1.771501 2.71749 199s 15 -2.630757 -2.44003 199s 16 2.289743 -5.51829 199s 17 0.637985 -1.26452 199s 18 3.076147 0.19883 199s 19 0.097381 -1.95868 199s 20 -1.572471 -0.93003 199s 21 -1.284185 2.21858 199s 22 -2.531713 3.30313 199s 23 -3.865359 -3.01230 199s 24 -2.143461 -2.41918 199s 25 -0.714414 -0.41227 199s 26 -1.327781 1.18373 199s 27 -2.201166 2.41566 199s 28 -2.931988 3.20536 199s ------------- 199s Call: 199s PcaHubert(x = x, mcd = FALSE) 199s 199s Standard deviations: 199s [1] 2.8286 2.4203 199s ---------------------------------------------------------- 199s hbk 75 3 3 1.459908 1.201048 199s Scores: 199s PC1 PC2 PC3 199s 1 31.105415 -4.714217 10.4566165 199s 2 31.707650 -5.748724 10.7682402 199s 3 33.366131 -4.625897 12.1570167 199s 4 34.173377 -6.069657 12.4466895 199s 5 33.780418 -5.508823 11.9872893 199s 6 32.493478 -4.684595 10.5679819 199s 7 32.592637 -5.235522 10.3765493 199s 8 31.293363 -4.865797 10.9379676 199s 9 33.160964 -5.714260 12.3098920 199s 10 31.919786 -5.384537 12.3374332 199s 11 38.231962 -6.810641 13.5994385 199s 12 39.290479 -5.393906 15.2942554 199s 13 39.418445 -7.326461 11.5194898 199s 14 43.906584 -13.214819 8.3282743 199s 15 1.906326 0.716061 -0.8635112 199s 16 0.263255 0.926016 -1.9009292 199s 17 -1.776489 -1.072332 -0.5496140 199s 18 0.464648 0.702441 0.0482897 199s 19 0.267826 -1.283779 -0.2925812 199s 20 2.122108 0.165970 -0.8924686 199s 21 0.937217 0.548532 -0.4132196 199s 22 0.423273 -1.781869 -0.0323061 199s 23 0.047532 0.018909 -1.1259327 199s 24 -0.490041 -0.520202 -1.1065753 199s 25 -2.143049 0.720869 -0.0495474 199s 26 1.094748 -1.459175 0.2226246 199s 27 2.070705 0.898573 0.0023229 199s 28 -0.294998 0.830258 0.5929001 199s 29 -1.242995 0.300216 -0.2010507 199s 30 0.147958 0.439099 2.0003038 199s 31 0.170818 1.440946 -0.9755627 199s 32 -0.958531 -1.199730 -1.0129867 199s 33 0.697307 -0.874343 -0.7260649 199s 34 -2.278946 0.261106 0.4196544 199s 35 1.962829 0.809318 0.2033113 199s 36 0.626631 -0.600666 0.8004036 199s 37 0.550885 -1.881448 0.7382776 199s 38 -1.249717 0.336214 -0.9349845 199s 39 -1.106696 1.569418 0.1869576 199s 40 -0.684034 -0.939963 -0.1034965 199s 41 1.559314 1.551408 0.3660323 199s 42 -0.538741 -0.447358 1.6361099 199s 43 -0.252685 -2.080564 -0.7765259 199s 44 0.217012 1.027281 1.7015154 199s 45 -1.497600 1.349234 -0.2698932 199s 46 0.100388 1.026443 1.5390401 199s 47 -0.811117 2.195271 -0.5208141 199s 48 1.462210 1.321318 0.5600144 199s 49 1.383976 0.740714 -0.7348906 199s 50 1.636773 -0.215464 0.3195369 199s 51 -0.530918 0.759743 -1.2069247 199s 52 -0.109566 2.107455 -0.5315473 199s 53 -0.564334 -0.060847 2.3910630 199s 54 -0.272234 -1.122711 -1.5060028 199s 55 -0.608660 -1.197219 -0.5255609 199s 56 0.565430 -0.710345 -1.3708230 199s 57 -1.115629 0.888816 -0.4186014 199s 58 1.351288 -0.374815 -1.1980618 199s 59 0.998016 -0.151228 0.9007970 199s 60 0.124017 -0.764846 1.9005963 199s 61 1.189858 -1.905264 0.7721322 199s 62 -2.190589 0.579614 -0.1377914 199s 63 -0.518278 -0.931130 -1.4534768 199s 64 2.124566 0.194391 -0.0327092 199s 65 0.154218 1.050861 1.1309885 199s 66 -1.197852 -1.044147 -0.2265269 199s 67 -0.114174 -0.094763 -0.5168926 199s 68 -2.201115 0.032271 0.8573493 199s 69 -1.307843 1.104815 -0.7741270 199s 70 0.691449 -0.676665 1.0004603 199s 71 1.150975 0.050861 -0.0717068 199s 72 -0.457293 -0.861871 0.1026350 199s 73 -0.392258 -0.897451 0.9178065 199s 74 -0.584658 -1.450471 0.3201857 199s 75 -0.972517 -0.063777 1.8223995 199s ------------- 199s Call: 199s PcaHubert(x = x, mcd = FALSE) 199s 199s Standard deviations: 199s [1] 1.2083 1.0959 1.0168 199s ---------------------------------------------------------- 199s milk 86 8 2 6.040806 2.473780 199s Scores: 199s PC1 PC2 199s 1 -5.768003 -0.9174359 199s 2 -6.664422 0.0280812 199s 3 -0.484521 1.7923710 199s 4 -5.211590 2.0747301 199s 5 1.422641 -0.3268437 199s 6 -1.810360 -0.5469828 199s 7 -2.402924 -0.1987041 199s 8 -2.553389 -0.4963662 199s 9 1.583399 2.5410448 199s 10 3.267946 0.9141367 199s 11 9.924771 0.6501301 199s 12 13.628569 -2.3009846 199s 13 10.774550 -1.1628697 199s 14 12.716376 -1.0670330 199s 15 11.176408 0.7403371 199s 16 3.209269 -0.0804317 199s 17 1.256577 2.8931153 199s 18 2.468720 -1.2008647 199s 19 2.253229 0.8379608 199s 20 0.021073 1.6394221 199s 21 3.205298 -2.3518286 199s 22 1.470733 -0.9618655 199s 23 0.475732 -1.7044535 199s 24 0.930144 -1.3288398 199s 25 4.151553 -2.2882554 199s 26 1.314488 -1.3527439 199s 27 3.613405 -0.0813605 199s 28 -1.909178 -3.6473200 199s 29 -3.987263 -1.3255834 199s 30 -0.370601 -1.5855086 199s 31 -1.273254 -2.1892809 199s 32 -0.816634 -0.4514478 199s 33 -1.553394 -0.2792004 199s 34 -0.275027 0.6359374 199s 35 0.980782 -2.2353223 199s 36 -3.678470 -1.3459182 199s 37 -0.327102 -2.5615283 199s 38 -1.563492 -2.2008288 199s 39 1.876146 -1.0292641 199s 40 -3.204182 1.6694332 199s 41 -3.561892 -1.5844770 199s 42 -6.175135 1.0123714 199s 43 -2.736601 -0.7040261 199s 44 -4.981783 0.2434304 199s 45 0.368802 -0.5011413 199s 46 0.369508 -1.9511091 199s 47 -2.306673 -0.0089446 199s 48 0.215195 -1.1000357 199s 49 2.704678 -0.5919929 199s 50 -2.930879 2.7161936 199s 51 1.846250 0.3732500 199s 52 5.661288 -0.3139157 199s 53 1.154929 -0.0575094 199s 54 0.625715 -0.0733934 199s 55 -0.453714 -0.7535924 199s 56 0.343722 0.6460318 199s 57 1.743002 0.0794685 199s 58 0.433705 -1.3500731 199s 59 2.078550 1.0860506 199s 60 1.867913 0.7162287 199s 61 0.392645 1.6184583 199s 62 -1.958732 2.0993596 199s 63 -2.383251 -0.0253919 199s 64 -2.383251 -0.0253919 199s 65 0.780239 2.9018927 199s 66 2.785329 1.0142893 199s 67 0.131210 1.2703167 199s 68 1.110073 1.8140467 199s 69 1.076878 0.6954148 199s 70 -3.260160 -5.6233069 199s 71 2.647036 1.6892084 199s 72 -2.017340 0.5353349 199s 73 2.247524 2.6406249 199s 74 11.649291 -0.7374197 199s 75 0.280544 2.2306959 199s 76 1.791213 0.1796005 199s 77 8.730344 0.3412271 199s 78 -0.987405 1.3467910 199s 79 0.560808 0.5006661 199s 80 3.897879 -1.5270179 199s 81 -0.792759 -0.8649399 199s 82 -2.493611 1.6796838 199s 83 -2.245966 0.1889555 199s 84 -0.468812 -0.5359088 199s 85 -0.538372 2.4105954 199s 86 -0.185347 -1.0176989 199s ------------- 199s Call: 199s PcaHubert(x = x, mcd = FALSE) 199s 199s Standard deviations: 199s [1] 2.4578 1.5728 199s ---------------------------------------------------------- 199s bushfire 38 5 1 38435.075910 NA 199s Scores: 199s PC1 199s 1 -111.9345 199s 2 -113.4128 199s 3 -105.8364 199s 4 -89.1684 199s 5 -58.7216 199s 6 -35.0370 199s 7 -250.2123 199s 8 -292.6877 199s 9 -294.0765 199s 10 -290.0193 199s 11 -289.8168 199s 12 -290.8645 199s 13 -232.6865 199s 14 9.8483 199s 15 137.1924 199s 16 92.9804 199s 17 90.4493 199s 18 78.6325 199s 19 82.1178 199s 20 92.9044 199s 21 74.9157 199s 22 66.7350 199s 23 -62.1981 199s 24 -116.5696 199s 25 -53.8907 199s 26 -60.6384 199s 27 -74.7621 199s 28 -50.2202 199s 29 -38.7483 199s 30 -93.3887 199s 31 35.3096 199s 32 290.8493 199s 33 326.7236 199s 34 322.9095 199s 35 328.5307 199s 36 325.6791 199s 37 323.8136 199s 38 325.2991 199s ------------- 199s Call: 199s PcaHubert(x = x, mcd = FALSE) 199s 199s Standard deviations: 199s [1] 196.05 199s ---------------------------------------------------------- 199s ========================================================== 199s > 199s > dodata(method="locantore") 199s 199s Call: dodata(method = "locantore") 199s Data Set n p k e1 e2 199s ========================================================== 199s heart 12 2 2 1.835912 0.084745 199s Scores: 199s PC1 PC2 199s [1,] 7.3042 1.745289 199s [2,] 64.6474 0.164425 199s [3,] 1.1057 -1.404189 199s [4,] -3.1943 2.565728 199s [5,] 19.4154 -0.401369 199s [6,] -15.5709 6.666752 199s [7,] 5.9980 2.509372 199s [8,] -29.5933 -4.805972 199s [9,] -1.3933 -0.899323 199s [10,] -28.2845 -4.270057 199s [11,] -14.0069 0.048311 199s [12,] 49.1484 0.694598 199s ------------- 199s Call: 199s PcaLocantore(x = x) 199s 199s Standard deviations: 199s [1] 1.35496 0.29111 199s ---------------------------------------------------------- 199s starsCYG 47 2 2 0.779919 0.050341 199s Scores: 199s PC1 PC2 199s [1,] 0.174291 -0.0489127 199s [2,] 0.703776 0.0769650 199s [3,] -0.136954 -0.1212071 199s [4,] 0.703776 0.0769650 199s [5,] 0.125991 -0.1134658 199s [6,] 0.413609 0.0121367 199s [7,] -0.466451 -0.5036094 199s [8,] 0.238569 0.1446547 199s [9,] 0.498194 -0.1998666 199s [10,] 0.065125 -0.0353931 199s [11,] 0.562344 -0.9836936 199s [12,] 0.399997 -0.0164068 199s [13,] 0.376370 0.0369013 199s [14,] -1.041009 -0.2611550 199s [15,] -0.798187 -0.0090880 199s [16,] -0.464636 0.0805967 199s [17,] -1.123135 -0.0293034 199s [18,] -0.861603 0.1297588 199s [19,] -0.884955 -0.0588007 199s [20,] 0.721130 -1.0033585 199s [21,] -0.679097 -0.0238366 199s [22,] -0.837884 -0.0041718 199s [23,] -0.623423 0.1002615 199s [24,] -0.188079 0.1168815 199s [25,] -0.032888 -0.0131784 199s [26,] -0.385242 0.0707643 199s [27,] -0.401220 -0.0582501 199s [28,] -0.151978 0.0015702 199s [29,] -0.677776 -0.0945350 199s [30,] 0.878688 -1.0329475 199s [31,] -0.628339 0.0605648 199s [32,] 0.068629 0.1556245 199s [33,] 0.174199 0.0317098 199s [34,] 1.118098 -1.0525206 199s [35,] -0.726168 -0.0784655 199s [36,] 0.592061 0.1512588 199s [37,] 0.064942 0.1258519 199s [38,] 0.174199 0.0317098 199s [39,] 0.144335 0.1160195 199s [40,] 0.519088 -0.0311555 199s [41,] -0.429855 0.0359837 199s [42,] 0.015412 0.0513747 199s [43,] 0.299435 0.0665821 199s [44,] 0.293289 0.0169612 199s [45,] 0.504064 0.0916219 199s [46,] -0.063981 0.0612071 199s [47,] -0.544029 0.0904291 199s ------------- 199s Call: 199s PcaLocantore(x = x) 199s 199s Standard deviations: 199s [1] 0.88313 0.22437 199s ---------------------------------------------------------- 199s phosphor 18 2 2 0.933905 0.279651 199s Scores: 199s PC1 PC2 199s 1 4.5660 -15.58981 199s 2 -21.2978 -0.38905 199s 3 -23.3783 3.96546 199s 4 -11.7131 -5.79023 199s 5 -18.2569 2.81141 199s 6 15.5702 -20.54935 199s 7 1.3671 -3.27043 199s 8 -9.4859 3.92005 199s 9 -10.4501 6.22662 199s 10 15.0583 -7.60532 199s 11 -3.9078 1.56960 199s 12 10.0330 7.52732 199s 13 13.4815 5.50056 199s 14 7.5487 7.24752 199s 15 18.6543 2.46040 199s 16 -9.3301 -5.68285 199s 17 22.2533 4.63689 199s 18 17.7892 10.85633 199s ------------- 199s Call: 199s PcaLocantore(x = x) 199s 199s Standard deviations: 199s [1] 0.96639 0.52882 199s ---------------------------------------------------------- 199s stackloss 21 3 3 1.137747 0.196704 199s Scores: 199s PC1 PC2 PC3 199s [1,] 19.98046 -6.20875 -3.93576 199s [2,] 19.57014 -7.11509 -4.03666 199s [3,] 15.48729 -3.14247 -3.29600 199s [4,] 3.12341 -1.38969 1.50633 199s [5,] 2.35380 -0.84492 -0.25745 199s [6,] 2.73860 -1.11731 0.62444 199s [7,] 5.58533 4.04837 2.11170 199s [8,] 5.58533 4.04837 2.11170 199s [9,] -0.56851 0.17483 2.46656 199s [10,] -5.36478 -4.80766 -2.64915 199s [11,] -1.67190 3.34943 -1.74110 199s [12,] -2.46702 2.71547 -2.72389 199s [13,] -4.54414 -2.99497 -2.44736 199s [14,] 0.35419 6.70241 -0.45563 199s [15,] -8.28612 5.93369 1.94314 199s [16,] -9.51708 3.21466 1.64046 199s [17,] -14.87676 -9.74652 1.10983 199s [18,] -12.00452 -3.40212 1.81609 199s [19,] -11.20939 -2.76816 2.79887 199s [20,] -5.42808 -2.89367 0.23748 199s [21,] 9.83969 0.74095 -5.30190 199s ------------- 199s Call: 199s PcaLocantore(x = x) 199s 199s Standard deviations: 199s [1] 1.06665 0.44351 0.33935 199s ---------------------------------------------------------- 199s salinity 28 3 3 1.038873 0.621380 199s Scores: 199s PC1 PC2 PC3 199s 1 -2.7215590 -0.98924 0.3594538 199s 2 -3.6251829 -1.03361 1.4973993 199s 3 -6.0588883 4.23861 -1.1012038 199s 4 -6.2741857 2.42372 -1.4875092 199s 5 -5.7274076 5.42190 2.9332011 199s 6 -5.8431892 0.57161 -0.3385363 199s 7 -4.4051377 -0.83292 0.0851817 199s 8 -2.6155827 -2.50739 0.3386166 199s 9 -0.0426575 1.19631 -2.5025726 199s 10 2.5297488 1.65029 -0.0110335 199s 11 1.5528097 1.93255 1.4216262 199s 12 -0.3140451 -0.73269 -0.1961364 199s 13 0.0010783 -1.88658 0.1849912 199s 14 1.9554303 -2.13519 1.8471356 199s 15 2.7897250 2.40211 -0.6327944 199s 16 -1.7665706 8.69449 5.6608836 199s 17 -0.4374125 1.72696 0.7230753 199s 18 -2.9752196 -0.54118 -0.6829760 199s 19 -0.0599346 0.84127 -2.8473543 199s 20 1.6597909 0.34191 -1.4847516 199s 21 1.3857395 -2.43924 0.0039271 199s 22 2.6664754 -3.14291 1.0600254 199s 23 4.1202067 3.81886 1.0608640 199s 24 2.4163743 3.45141 1.6874099 199s 25 0.8493897 0.31424 -0.3073115 199s 26 1.4216265 -1.55310 -0.5455012 199s 27 2.3021676 -2.63392 0.0481451 199s 28 3.0877115 -2.85951 1.4378956 199s ------------- 199s Call: 199s PcaLocantore(x = x) 199s 199s Standard deviations: 199s [1] 1.01925 0.78828 0.36470 199s ---------------------------------------------------------- 199s hbk 75 3 3 1.038833 0.363386 199s Scores: 199s PC1 PC2 PC3 199s 1 32.393698 -3.4318297 0.051248 199s 2 33.103072 -4.4154651 0.294662 199s 3 35.038965 -3.5996035 -0.940929 199s 4 35.955809 -4.9285404 -0.479059 199s 5 35.424918 -4.3076292 -0.366699 199s 6 33.753497 -3.2463136 0.289013 199s 7 33.817375 -3.6819421 0.684167 199s 8 32.717119 -3.7074394 -0.279567 199s 9 34.932190 -4.6939061 -0.738196 199s 10 33.737339 -4.5702346 -1.193206 199s 11 40.202273 -5.4336890 -0.229323 199s 12 41.638189 -4.5304173 -1.996311 199s 13 40.768565 -5.0531048 2.123222 199s 14 44.408749 -8.8448536 8.236462 199s 15 0.977343 1.3057899 0.938694 199s 16 -0.900390 1.6169842 1.382855 199s 17 -2.384467 -0.9835430 0.375495 199s 18 -0.143306 0.7859701 -0.237712 199s 19 -0.344479 -0.9791245 0.733869 199s 20 1.199115 0.8330752 1.216827 199s 21 0.184475 0.8630593 0.351029 199s 22 -0.100389 -1.5084406 0.718236 199s 23 -0.847925 0.4823829 0.958677 199s 24 -1.334366 -0.1021190 1.000300 199s 25 -2.669352 0.4692990 -0.811134 199s 26 0.601538 -1.1984283 0.541627 199s 27 1.373423 1.2098621 0.136249 199s 28 -0.721268 0.6164612 -0.963817 199s 29 -1.832615 0.2543279 -0.297658 199s 30 0.120086 -0.1558590 -1.976558 199s 31 -0.747437 1.7749106 0.342824 199s 32 -1.727558 -0.8325772 1.043088 199s 33 -0.073907 -0.3923823 1.083904 199s 34 -2.646454 -0.1350138 -1.101448 199s 35 1.331096 1.0443905 -0.039328 199s 36 0.281192 -0.6569943 -0.404009 199s 37 0.245349 -1.8406517 0.093656 199s 38 -2.049446 0.5320301 0.347219 199s 39 -1.645547 1.3268749 -1.068792 199s 40 -1.216874 -0.8556007 0.201262 199s 41 0.959445 1.6250030 -0.553881 199s 42 -0.603579 -0.9569812 -1.502730 199s 43 -0.946870 -1.6333180 1.324763 199s 44 0.076217 0.5018427 -1.902369 199s 45 -2.140584 1.2192726 -0.677180 199s 46 -0.081677 0.5389288 -1.785347 199s 47 -1.590461 2.1881067 -0.583771 199s 48 0.931421 1.3321181 -0.669782 199s 49 0.512639 1.2123979 0.683099 199s 50 1.095415 0.0045968 0.143109 199s 51 -1.456417 1.1186245 0.619657 199s 52 -0.917904 2.2084467 -0.366392 199s 53 -0.429654 -0.8524437 -2.326637 199s 54 -1.213858 -0.4996891 1.630709 199s 55 -1.253877 -0.9438354 0.692022 199s 56 -0.390657 -0.0427482 1.571167 199s 57 -1.797537 0.8934866 -0.281980 199s 58 0.396886 0.3227454 1.492494 199s 59 0.646360 -0.2194210 -0.562699 199s 60 0.119900 -1.2480691 -1.459763 199s 61 0.867946 -1.7843458 0.232229 199s 62 -2.733997 0.3604288 -0.692947 199s 63 -1.442683 -0.3732483 1.452800 199s 64 1.444934 0.5727959 0.434633 199s 65 -0.147284 0.7055205 -1.413940 199s 66 -1.739552 -0.9838385 0.220303 199s 67 -0.824644 0.1503195 0.411693 199s 68 -2.437638 -0.4835278 -1.392882 199s 69 -2.091970 1.1865192 -0.088483 199s 70 0.403429 -0.7855276 -0.540161 199s 71 0.507512 0.3152001 0.276885 199s 72 -0.944376 -0.8197825 0.044859 199s 73 -0.648597 -1.1160277 -0.658528 199s 74 -0.979453 -1.4589411 0.029182 199s 75 -0.982282 -0.7226425 -1.917060 199s ------------- 199s Call: 199s PcaLocantore(x = x) 199s 199s Standard deviations: 199s [1] 1.01923 0.60282 0.46137 199s ---------------------------------------------------------- 199s milk 86 8 8 1.175171 0.426506 199s Scores: 199s PC1 PC2 PC3 PC4 PC5 PC6 199s [1,] 6.1907998 0.58762698 0.686510 -0.209679 0.3321757 -1.3424985 199s [2,] 7.0503894 -0.49576086 -0.322697 -0.767415 -0.0165833 -1.4596064 199s [3,] 0.7670594 -1.83556812 0.468814 0.346810 -0.0204610 -0.2115383 199s [4,] 5.4656748 -2.29797862 1.612819 -0.378295 -0.2050232 0.3486957 199s [5,] -1.0291160 0.37303007 0.634604 -0.521527 -0.3299543 0.0859469 199s [6,] 2.2186300 0.39396818 -0.236987 -0.033975 -0.2549238 0.2541221 199s [7,] 2.7938591 -0.01152811 -0.600546 -0.098564 -0.3906602 0.3798516 199s [8,] 2.9544176 0.32646226 0.273051 -0.275073 -0.3982959 0.2377581 199s [9,] -1.3344639 -2.45440308 1.001792 -0.104783 -0.1744718 -0.0887272 199s [10,] -2.9294174 -0.79860558 -0.260533 0.375330 0.3425169 -0.2056682 199s [11,] -9.5810648 -0.09577968 1.565111 -0.112002 0.3143032 -0.3190238 199s [12,] -13.1147240 2.95665890 0.228086 -0.180867 0.0136463 -0.4604390 199s [13,] -10.2989319 1.53220781 -2.244629 0.323950 -0.0398642 -0.3463501 199s [14,] -12.2553418 1.62281167 -0.472862 -0.212983 -0.4124280 -0.4253719 199s [15,] -10.8346894 -0.09781844 2.134079 -0.272304 -0.1090226 -0.3725738 199s [16,] -2.8358474 0.28109809 0.945309 0.603249 0.1615955 0.1762086 199s [17,] -1.0353408 -2.75475311 1.677879 0.598578 0.0078965 0.0228522 199s [18,] -2.0271810 1.25894451 -0.266038 -0.168565 -0.3000200 0.2891774 199s [19,] -1.9279394 -0.68339726 1.264416 0.186749 0.3018226 -0.0869321 199s [20,] 0.2568334 -1.62632029 0.854279 -0.088175 0.5458645 0.2217019 199s [21,] -2.7017404 2.45223507 -0.243639 -0.211402 -0.2102323 0.2140100 199s [22,] -1.0386097 0.99459030 0.188462 -0.033434 -0.2857078 -0.1438517 199s [23,] -0.0198126 1.73285416 0.761979 0.005501 0.1671992 -0.0375468 199s [24,] -0.4909448 1.40982693 0.967440 0.521275 0.1625359 -0.0892501 199s [25,] -3.6632699 2.51414455 0.966410 -0.272694 0.0467958 0.1572715 199s [26,] -0.8733564 1.42247465 0.946038 -0.338985 -0.0804141 -0.0080759 199s [27,] -3.2254798 0.26912538 0.799468 0.372442 -0.6886191 -0.0553515 199s [28,] 2.4675785 3.56128696 0.813964 0.118354 -0.1677073 -0.0303774 199s [29,] 4.4177264 1.13316321 0.613509 0.261488 0.4229929 0.1780620 199s [30,] 0.8240097 1.54163297 0.398148 -0.221825 0.0309586 0.0830110 199s [31,] 1.7735990 2.00615332 -1.399933 0.469158 -0.0740282 0.0692312 199s [32,] 1.2348922 0.28918604 -1.239899 0.470999 -0.1511519 -0.3692504 199s [33,] 1.9407276 0.19123540 0.406623 0.389965 0.0994854 -0.0204286 199s [34,] 0.6225565 -0.65636700 0.565253 0.369897 -0.1612501 -0.1774611 199s [35,] -0.4869219 2.26301333 0.071825 0.588101 -0.0579092 -0.0362009 199s [36,] 4.1117242 1.16638974 0.982790 -0.266009 0.0728797 -0.0018914 199s [37,] 0.8415225 2.46677043 -0.526780 0.167456 -0.2370116 -0.0731483 199s [38,] 2.0528334 2.09648023 0.220912 0.206722 -0.1924842 0.0676382 199s [39,] -1.4493644 1.14916103 0.904194 0.455498 0.0678893 -0.1476540 199s [40,] 3.4867792 -1.82367389 0.730183 0.499859 0.2327704 -0.1518819 199s [41,] 4.0222120 1.34765470 0.580852 -0.453301 0.2482908 -1.5306566 199s [42,] 6.4789035 -1.25599522 1.644194 0.381331 0.1699942 0.1847594 199s [43,] 3.1529354 0.44884526 -0.967114 -0.220364 0.0037036 0.0802727 199s [44,] 5.3344976 -0.47975673 0.642789 0.298705 0.9983145 -0.1310548 199s [45,] 0.0325597 0.49900084 0.076948 0.486521 0.1642679 0.1392696 199s [46,] 0.1014401 1.97657735 0.733879 0.127235 0.0650844 -0.0144271 199s [47,] 2.7217685 -0.37859042 -3.696163 0.355401 -0.4123714 0.2114024 199s [48,] 0.2292225 1.01473918 -1.115726 0.434557 0.2668316 0.0103147 199s [49,] -2.2803784 0.59474034 -1.783003 0.549252 0.4660435 -0.0802352 199s [50,] 3.1560404 -2.84820361 0.913015 0.077151 0.5803961 0.0350246 199s [51,] -1.4680905 -0.43078891 -1.733657 0.074684 0.0026718 0.0819023 199s [52,] -5.2469034 0.48385240 -1.246027 0.081379 0.2380924 -0.1663831 199s [53,] -0.7670982 0.00234561 -0.923030 -0.366820 0.1582141 0.0508747 199s [54,] -0.2428655 0.04714401 -0.217187 -0.059549 0.1762969 0.0806339 199s [55,] 0.8723441 0.66109329 -0.224917 -0.360607 -0.0638127 0.1310131 199s [56,] 0.0019700 -0.67624071 0.081304 -0.182908 0.1045597 -0.0281936 199s [57,] -1.3684663 -0.00045069 0.860560 -0.350684 -0.1443970 -0.2270651 199s [58,] 0.0079047 1.36376727 0.750919 -0.437914 -0.1894910 0.2345556 199s [59,] -1.7430794 -1.06973583 -0.569381 -0.055139 -0.1582790 -0.0873605 199s [60,] -1.5171606 -0.69340281 -0.287048 -0.136559 -0.3871182 0.1606979 199s [61,] -0.0955085 -1.64221260 0.263650 -0.265665 -0.0808644 -0.0476862 199s [62,] 2.2259171 -2.22161516 0.426279 0.027834 0.2924338 -0.1784242 199s [63,] 2.7573525 -0.11785122 0.391113 -0.094032 -0.3184760 0.4251268 199s [64,] 2.7573525 -0.11785122 0.391113 -0.094032 -0.3184760 0.4251268 199s [65,] -0.5520071 -2.86186682 0.746248 0.109945 0.0556927 -0.0135739 199s [66,] -2.4472964 -0.94969715 -0.329042 -0.113895 -0.2728443 -0.0523337 199s [67,] 0.1790969 -1.29190443 0.146657 0.140234 0.1534048 0.2318353 199s [68,] -0.8017055 -1.93331421 -1.968273 0.017854 0.1287513 -0.2306786 199s [69,] -0.7356418 -0.68868398 -0.075215 -0.156944 0.0302876 0.4232626 199s [70,] 3.8821693 5.16959880 0.215490 -8.985938 5.2189361 -2.8089276 199s [71,] -2.3478937 -1.60220695 0.058822 -0.111845 -0.0539018 0.0087982 199s [72,] 2.3676739 -0.70331436 -0.214457 -0.307311 -0.1582719 0.3995413 199s [73,] -1.9906385 -2.60946629 -0.730312 0.485522 -0.2391998 0.1009341 199s [74,] -11.2435515 1.44868683 2.482678 0.026711 0.4922865 -0.2822136 199s [75,] 0.0044207 -2.29768358 -0.692425 0.538923 -0.4110598 -0.0824903 199s [76,] -1.4045239 -0.22649785 -1.343257 -0.067382 -0.1322233 -0.1072330 199s [77,] -8.3637576 0.14167751 1.267616 0.384528 -0.0728561 -0.4017300 199s [78,] 1.3022939 -1.47457541 -0.394623 -0.068014 -0.1502832 0.0757414 199s [79,] -0.1950676 -0.58254701 -0.824931 -0.088174 -0.2071634 -0.1896613 199s [80,] -3.4432989 1.73593273 0.777996 0.094211 0.2377017 -0.1520088 199s [81,] 1.2167258 0.77512068 0.085803 -0.214850 -0.2201173 0.0432435 199s [82,] 2.7778798 -1.80071342 0.583878 0.465898 0.0648352 0.2148470 199s [83,] 2.6218578 -0.39825539 -0.553372 -0.145721 -0.0977092 -0.2485337 199s [84,] 0.8946018 0.33790104 -1.974267 0.091828 0.0051986 -0.2606274 199s [85,] 0.7759316 -2.34860124 2.423325 -0.384149 -0.0167182 -0.0353374 199s [86,] 0.6266756 0.87099609 -1.407948 -0.237762 0.0361644 0.1675792 199s PC7 PC8 199s [1,] -0.1014312 1.5884e-03 199s [2,] -0.3831443 1.0212e-03 199s [3,] -0.7164683 1.2035e-03 199s [4,] 0.0892864 3.5409e-04 199s [5,] -0.0943992 1.0547e-03 199s [6,] 0.1184847 1.5031e-03 199s [7,] -0.2509793 1.6850e-05 199s [8,] -0.0136880 7.0308e-04 199s [9,] 0.2238736 -1.9164e-04 199s [10,] 0.0754413 1.3614e-04 199s [11,] 0.0784380 3.5175e-04 199s [12,] 0.2033489 -1.3174e-03 199s [13,] 0.2139525 -1.7101e-03 199s [14,] 0.1209735 -9.1070e-04 199s [15,] 0.2119647 -9.2843e-04 199s [16,] -0.3011483 -2.1474e-03 199s [17,] 0.0660858 -1.9036e-03 199s [18,] -0.5199396 -9.4385e-04 199s [19,] -0.1232622 -1.2649e-03 199s [20,] -0.3900208 -2.6927e-04 199s [21,] 0.0264834 7.6074e-05 199s [22,] -0.0736288 1.7240e-04 199s [23,] -0.2156005 -5.5661e-04 199s [24,] 0.1143327 -2.5248e-04 199s [25,] 0.0481580 -6.1531e-04 199s [26,] -0.0084802 -7.5928e-04 199s [27,] -0.2173883 -3.0971e-04 199s [28,] 0.3288873 -1.8975e-04 199s [29,] 0.0788974 -7.2436e-04 199s [30,] -0.0598663 -3.0463e-04 199s [31,] -0.1511658 -4.8751e-04 199s [32,] -0.0532375 -2.5207e-04 199s [33,] -0.0635290 -3.9270e-04 199s [34,] 0.1598240 1.3024e-04 199s [35,] -0.0355175 -8.5374e-05 199s [36,] -0.0174096 -6.3294e-04 199s [37,] -0.2883141 -5.2809e-04 199s [38,] 0.1426412 5.3331e-04 199s [39,] 0.0313308 4.2738e-04 199s [40,] -0.3536195 -3.4170e-04 199s [41,] -0.3925168 1.4588e-04 199s [42,] -0.0056267 -9.1925e-04 199s [43,] -0.4447402 -1.8415e-04 199s [44,] 0.9184385 -5.9685e-04 199s [45,] -0.0340987 7.2924e-04 199s [46,] -0.0162866 9.7800e-04 199s [47,] 0.2428769 -1.1208e-03 199s [48,] 0.3026758 -4.5769e-04 199s [49,] 0.0246345 -2.6207e-04 199s [50,] 0.0857698 7.6439e-05 199s [51,] 0.1136658 1.3013e-04 199s [52,] 0.3993357 6.2796e-04 199s [53,] -0.1765161 1.1329e-04 199s [54,] 0.0016144 2.5870e-04 199s [55,] 0.1064371 5.8188e-04 199s [56,] 0.0207478 -8.7595e-05 199s [57,] 0.1560065 6.3987e-05 199s [58,] 0.1684561 -5.0193e-05 199s [59,] 0.0778732 -8.5458e-04 199s [60,] 0.0037585 1.0429e-05 199s [61,] -0.0296083 3.1526e-05 199s [62,] 0.0913974 -2.2794e-04 199s [63,] 0.0358917 -7.3721e-04 199s [64,] 0.0358917 -7.3721e-04 199s [65,] 0.1209159 2.9398e-04 199s [66,] -0.0027574 2.9380e-04 199s [67,] -0.0091059 -2.7494e-04 199s [68,] 0.0555970 -3.3016e-04 199s [69,] -0.0149255 -3.1228e-04 199s [70,] 0.9282997 4.7859e-05 199s [71,] 0.2630142 4.2617e-04 199s [72,] 0.1063248 -3.0070e-04 199s [73,] -0.1462452 4.9607e-04 199s [74,] 0.2027591 2.6399e-03 199s [75,] 0.6934350 6.0284e-04 199s [76,] -0.0430524 8.1271e-04 199s [77,] 0.0789302 1.4655e-03 199s [78,] -0.0318359 5.2799e-04 199s [79,] -0.1269568 2.9497e-04 199s [80,] 0.2903958 7.8932e-04 199s [81,] 0.0979443 -3.1531e-04 199s [82,] -0.0548155 4.2140e-04 199s [83,] -0.0371550 -5.6653e-04 199s [84,] -0.0835149 -7.0682e-04 199s [85,] 0.1864954 1.0604e-03 199s [86,] 0.1074252 -7.4859e-04 199s ------------- 199s Call: 199s PcaLocantore(x = x) 199s 199s Standard deviations: 199s [1] 1.08405293 0.65307452 0.28970076 0.11162824 0.09072195 0.06659711 0.05888048 199s [8] 0.00022877 199s ---------------------------------------------------------- 199s bushfire 38 5 5 1.464779 0.043290 199s Scores: 199s PC1 PC2 PC3 PC4 PC5 199s [1,] -69.9562 -13.0364 0.98678 1.054123 2.411188 199s [2,] -71.5209 -10.5459 0.31081 1.631208 1.663470 199s [3,] -63.9308 -7.4622 -2.43241 0.671038 0.465836 199s [4,] -47.0413 -9.6343 -3.83609 0.758349 0.683983 199s [5,] -15.9088 -20.1737 -5.55893 1.181744 -0.053563 199s [6,] 8.3484 -30.7646 -5.51541 1.877227 1.338037 199s [7,] -207.7458 -66.2492 34.48519 -5.894885 -1.051729 199s [8,] -246.4327 -97.0433 -9.57057 22.286225 -9.234869 199s [9,] -247.5984 -98.8613 -12.13406 23.948770 -9.250401 199s [10,] -245.8121 -79.2634 12.47990 13.046128 -5.125478 199s [11,] -246.8887 -62.5899 21.21764 9.111011 -5.080985 199s [12,] -251.1354 -9.2115 31.77448 0.236379 0.707528 199s [13,] -194.0239 27.1288 21.05023 0.940913 1.781359 199s [14,] 51.7182 8.5038 -11.22109 -2.132458 1.984807 199s [15,] 180.5597 -4.8151 -21.36630 -9.390663 -0.817036 199s [16,] 135.7246 -5.0756 -11.33517 -10.015567 -1.670831 199s [17,] 133.0151 -4.0344 -8.95540 -7.702087 -0.923277 199s [18,] 121.2619 -9.0627 -5.96042 -7.210971 -2.092872 199s [19,] 124.9038 -10.6649 -7.22555 -5.349553 -1.771009 199s [20,] 135.5410 -6.8146 -7.52834 -5.562769 -0.396924 199s [21,] 117.1950 -3.5643 -4.67473 -6.862117 -0.234551 199s [22,] 108.9944 -2.3344 -5.90349 -5.928299 1.455538 199s [23,] -21.4031 8.0668 6.19525 -4.784890 0.671394 199s [24,] -76.3499 16.7804 6.52545 -1.391250 1.219282 199s [25,] -12.5732 6.1109 -1.45259 -3.512072 -0.375837 199s [26,] -19.1800 3.4685 -2.02243 -3.490028 -0.169127 199s [27,] -33.6733 12.0757 -3.53322 0.048666 0.067468 199s [28,] -9.3966 21.5055 -5.91671 2.650895 -0.449672 199s [29,] 1.4123 35.8559 -5.98222 5.982362 0.613667 199s [30,] -54.2683 39.6029 7.82694 6.759994 0.035048 199s [31,] 74.8866 34.9048 10.03986 12.592158 0.149308 199s [32,] 331.4144 9.3079 27.73391 17.334531 1.015536 199s [33,] 367.6915 -19.5135 48.52753 10.213314 -1.268047 199s [34,] 363.8686 -20.4079 49.32855 8.986581 -1.930673 199s [35,] 369.4371 -19.5074 49.66761 9.001542 -0.179566 199s [36,] 366.5850 -20.2555 50.30290 7.745330 -2.259131 199s [37,] 364.5463 -19.8198 53.00407 6.757796 -1.083372 199s [38,] 365.9709 -19.3753 53.80168 6.467284 -0.854384 199s ------------- 199s Call: 199s PcaLocantore(x = x) 199s 199s Standard deviations: 199s [1] 1.210280 0.208063 0.177790 0.062694 0.014423 199s ---------------------------------------------------------- 199s ========================================================== 199s > dodata(method="cov") 199s 199s Call: dodata(method = "cov") 199s Data Set n p k e1 e2 199s ========================================================== 199s heart 12 2 2 685.776266 13.127306 199s Scores: 199s PC1 PC2 199s 1 8.18562 1.17998 199s 2 65.41185 -2.80723 199s 3 1.86039 -1.70646 199s 4 -2.26910 2.44051 199s 5 20.19603 -1.47331 199s 6 -14.46264 7.05759 199s 7 6.91264 1.99823 199s 8 -28.95436 -3.81624 199s 9 -0.61523 -1.09711 199s 10 -27.62427 -3.33575 199s 11 -13.17788 0.37931 199s 12 49.94879 -1.62675 199s ------------- 199s Call: 199s PcaCov(x = x) 199s 199s Standard deviations: 199s [1] 26.1873 3.6232 199s ---------------------------------------------------------- 199s starsCYG 47 2 2 0.280150 0.007389 199s Scores: 199s PC1 PC2 199s 1 0.272263 -0.07964458 199s 2 0.804544 0.03382837 199s 3 -0.040587 -0.14464760 199s 4 0.804544 0.03382837 199s 5 0.222468 -0.14305159 199s 6 0.512941 -0.02420304 199s 7 -0.378928 -0.51924735 199s 8 0.341045 0.11236831 199s 9 0.592550 -0.23812462 199s 10 0.163442 -0.06357822 199s 11 0.638370 -1.02323643 199s 12 0.498667 -0.05242075 199s 13 0.476291 0.00142479 199s 14 -0.947664 -0.26343572 199s 15 -0.699020 -0.01711057 199s 16 -0.363464 0.06475681 199s 17 -1.024352 -0.02972862 199s 18 -0.759174 0.12317995 199s 19 -0.786925 -0.06478250 199s 20 0.796654 -1.04660568 199s 21 -0.580307 -0.03463751 199s 22 -0.738591 -0.01126825 199s 23 -0.521748 0.08812607 199s 24 -0.086135 0.09457052 199s 25 0.065975 -0.03907968 199s 26 -0.284322 0.05307219 199s 27 -0.303309 -0.07553370 199s 28 -0.052738 -0.02155274 199s 29 -0.580638 -0.10534741 199s 30 0.953478 -1.07986770 199s 31 -0.527590 0.04855502 199s 32 0.171408 0.12730538 199s 33 0.274054 0.00095808 199s 34 1.192364 -1.10502882 199s 35 -0.628641 -0.08815176 199s 36 0.694595 0.11071187 199s 37 0.167026 0.09762710 199s 38 0.274054 0.00095808 199s 39 0.246168 0.08594248 199s 40 0.617380 -0.06994769 199s 41 -0.329735 0.01934346 199s 42 0.115770 0.02432733 199s 43 0.400071 0.03289494 199s 44 0.392768 -0.01656886 199s 45 0.605229 0.05314718 199s 46 0.036628 0.03601196 199s 47 -0.442606 0.07644144 199s ------------- 199s Call: 199s PcaCov(x = x) 199s 199s Standard deviations: 199s [1] 0.529292 0.085957 199s ---------------------------------------------------------- 199s phosphor 18 2 2 288.018150 22.020514 199s Scores: 199s PC1 PC2 199s 1 2.7987 -19.015683 199s 2 -20.4311 -0.032022 199s 3 -21.8198 4.589809 199s 4 -11.7869 -6.837833 199s 5 -16.9357 2.664785 199s 6 12.9132 -25.602526 199s 7 1.5249 -6.351664 199s 8 -8.0984 2.416616 199s 9 -8.6979 4.843680 199s 10 14.3903 -12.732868 199s 11 -2.9462 -0.760656 199s 12 11.7427 2.991004 199s 13 14.8400 0.459849 199s 14 9.2449 3.095095 199s 15 19.4860 -3.336883 199s 16 -9.4156 -7.096788 199s 17 23.3759 -1.737460 199s 18 19.9173 5.092467 199s ------------- 199s Call: 199s PcaCov(x = x) 199s 199s Standard deviations: 199s [1] 16.9711 4.6926 199s ---------------------------------------------------------- 199s stackloss 21 3 3 28.153060 8.925048 199s Scores: 199s PC1 PC2 PC3 199s [1,] 10.538448 13.596944 12.84989 199s [2,] 9.674846 14.098881 12.89733 199s [3,] 8.993255 9.221043 9.94062 199s [4,] 1.744427 3.649104 0.17292 199s [5,] 0.980215 2.223126 1.34874 199s [6,] 1.362321 2.936115 0.76083 199s [7,] 6.926040 0.637480 -0.11170 199s [8,] 6.926040 0.637480 -0.11170 199s [9,] 0.046655 0.977727 -2.46930 199s [10,] -7.909092 0.926343 0.80232 199s [11,] -0.136672 -3.591094 0.37539 199s [12,] -1.382381 -3.802146 1.01074 199s [13,] -6.181887 -0.077532 0.70744 199s [14,] 3.699843 -4.885854 -0.40226 199s [15,] -2.768005 -7.507870 -6.08487 199s [16,] -5.358811 -6.002058 -5.94256 199s [17,] -17.067135 1.738055 -5.86637 199s [18,] -11.021920 -1.775507 -6.19842 199s [19,] -9.776212 -1.564455 -6.83377 199s [20,] -6.075508 0.369252 -2.08345 199s [21,] 6.301743 2.706174 8.79509 199s ------------- 199s Call: 199s PcaCov(x = x) 199s 199s Standard deviations: 199s [1] 5.3059 2.9875 1.3020 199s ---------------------------------------------------------- 199s salinity 28 3 3 11.801732 3.961826 199s Scores: 199s PC1 PC2 PC3 199s 1 -1.59888 1.582157 0.135248 199s 2 -2.26975 2.429177 1.107832 199s 3 -6.79543 -2.034636 0.853876 199s 4 -6.36795 -0.602960 -0.267268 199s 5 -6.42044 -1.520259 5.022962 199s 6 -5.13821 1.225470 0.016977 199s 7 -3.24014 1.998671 -0.123418 199s 8 -0.93998 2.789889 -0.515656 199s 9 -0.30856 -2.424345 -1.422752 199s 10 2.20362 -2.800513 1.142127 199s 11 1.38120 -2.076832 2.515630 199s 12 0.44997 0.207439 -0.152835 199s 13 1.21669 1.193701 -0.277116 199s 14 3.31664 1.306627 1.213342 199s 15 2.08484 -3.774814 0.905400 199s 16 -3.64862 -4.677257 9.046484 199s 17 -0.46124 -1.411762 1.706719 199s 18 -2.13038 0.890401 -0.633349 199s 19 -0.23610 -2.262304 -1.885048 199s 20 1.70337 -1.970773 -0.781880 199s 21 2.67273 1.038742 -0.610945 199s 22 4.24561 1.547290 0.108927 199s 23 2.99619 -4.785343 3.094945 199s 24 1.64474 -3.564562 3.432429 199s 25 1.11703 -1.158030 0.237700 199s 26 2.30707 0.069668 -0.735809 199s 27 3.59356 0.860498 -0.611380 199s 28 4.57550 1.300407 0.589307 199s ------------- 199s Call: 199s PcaCov(x = x) 199s 199s Standard deviations: 199s [1] 3.43536 1.99043 0.94546 199s ---------------------------------------------------------- 199s hbk 75 3 3 1.436470 1.181766 199s Scores: 199s PC1 PC2 PC3 199s 1 31.105415 -4.714217 10.4566165 199s 2 31.707650 -5.748724 10.7682402 199s 3 33.366131 -4.625897 12.1570167 199s 4 34.173377 -6.069657 12.4466895 199s 5 33.780418 -5.508823 11.9872893 199s 6 32.493478 -4.684595 10.5679819 199s 7 32.592637 -5.235522 10.3765493 199s 8 31.293363 -4.865797 10.9379676 199s 9 33.160964 -5.714260 12.3098920 199s 10 31.919786 -5.384537 12.3374332 199s 11 38.231962 -6.810641 13.5994385 199s 12 39.290479 -5.393906 15.2942554 199s 13 39.418445 -7.326461 11.5194898 199s 14 43.906584 -13.214819 8.3282743 199s 15 1.906326 0.716061 -0.8635112 199s 16 0.263255 0.926016 -1.9009292 199s 17 -1.776489 -1.072332 -0.5496140 199s 18 0.464648 0.702441 0.0482897 199s 19 0.267826 -1.283779 -0.2925812 199s 20 2.122108 0.165970 -0.8924686 199s 21 0.937217 0.548532 -0.4132196 199s 22 0.423273 -1.781869 -0.0323061 199s 23 0.047532 0.018909 -1.1259327 199s 24 -0.490041 -0.520202 -1.1065753 199s 25 -2.143049 0.720869 -0.0495474 199s 26 1.094748 -1.459175 0.2226246 199s 27 2.070705 0.898573 0.0023229 199s 28 -0.294998 0.830258 0.5929001 199s 29 -1.242995 0.300216 -0.2010507 199s 30 0.147958 0.439099 2.0003038 199s 31 0.170818 1.440946 -0.9755627 199s 32 -0.958531 -1.199730 -1.0129867 199s 33 0.697307 -0.874343 -0.7260649 199s 34 -2.278946 0.261106 0.4196544 199s 35 1.962829 0.809318 0.2033113 199s 36 0.626631 -0.600666 0.8004036 199s 37 0.550885 -1.881448 0.7382776 199s 38 -1.249717 0.336214 -0.9349845 199s 39 -1.106696 1.569418 0.1869576 199s 40 -0.684034 -0.939963 -0.1034965 199s 41 1.559314 1.551408 0.3660323 199s 42 -0.538741 -0.447358 1.6361099 199s 43 -0.252685 -2.080564 -0.7765259 199s 44 0.217012 1.027281 1.7015154 199s 45 -1.497600 1.349234 -0.2698932 199s 46 0.100388 1.026443 1.5390401 199s 47 -0.811117 2.195271 -0.5208141 199s 48 1.462210 1.321318 0.5600144 199s 49 1.383976 0.740714 -0.7348906 199s 50 1.636773 -0.215464 0.3195369 199s 51 -0.530918 0.759743 -1.2069247 199s 52 -0.109566 2.107455 -0.5315473 199s 53 -0.564334 -0.060847 2.3910630 199s 54 -0.272234 -1.122711 -1.5060028 199s 55 -0.608660 -1.197219 -0.5255609 199s 56 0.565430 -0.710345 -1.3708230 199s 57 -1.115629 0.888816 -0.4186014 199s 58 1.351288 -0.374815 -1.1980618 199s 59 0.998016 -0.151228 0.9007970 199s 60 0.124017 -0.764846 1.9005963 199s 61 1.189858 -1.905264 0.7721322 199s 62 -2.190589 0.579614 -0.1377914 199s 63 -0.518278 -0.931130 -1.4534768 199s 64 2.124566 0.194391 -0.0327092 199s 65 0.154218 1.050861 1.1309885 199s 66 -1.197852 -1.044147 -0.2265269 199s 67 -0.114174 -0.094763 -0.5168926 199s 68 -2.201115 0.032271 0.8573493 199s 69 -1.307843 1.104815 -0.7741270 199s 70 0.691449 -0.676665 1.0004603 199s 71 1.150975 0.050861 -0.0717068 199s 72 -0.457293 -0.861871 0.1026350 199s 73 -0.392258 -0.897451 0.9178065 199s 74 -0.584658 -1.450471 0.3201857 199s 75 -0.972517 -0.063777 1.8223995 199s ------------- 199s Call: 199s PcaCov(x = x) 199s 199s Standard deviations: 199s [1] 1.1985 1.0871 1.0086 199s ---------------------------------------------------------- 199s milk 86 8 8 5.758630 2.224809 199s Scores: 199s PC1 PC2 PC3 PC4 PC5 PC6 199s 1 5.7090867 1.388263 0.0055924 0.3510505 -0.7335114 -1.41950731 199s 2 6.5825186 0.480410 -1.1356236 -0.3250838 -0.7343177 -1.71595400 199s 3 0.7433619 -1.749281 0.2510521 0.3450575 0.2996413 -0.34585702 199s 4 5.5733255 -1.588521 0.8934908 -0.3412408 0.0087626 0.07235942 199s 5 -1.3030839 0.142394 0.8487785 -0.5847851 0.0588053 -0.08968553 199s 6 1.7708705 0.674240 -0.4153759 -0.1915734 0.1382138 0.12454293 199s 7 2.3570866 0.381017 -0.8771357 -0.3739365 0.2918453 0.13437364 199s 8 2.5700714 0.695006 0.0061108 -0.4323695 0.1643797 -0.00469369 199s 9 -1.1725766 -2.713291 1.0677483 -0.0647875 0.1183120 -0.10762785 199s 10 -3.1357225 -1.255175 0.0666017 0.5083690 -0.1096080 -0.00647493 199s 11 -9.5333894 -1.608943 2.7307809 0.1690156 -0.1682415 -0.06597478 199s 12 -13.6028505 0.941083 2.0136258 -0.1076520 -0.0475905 -0.15295614 199s 13 -10.9497471 0.048776 -0.8765307 0.1518572 0.1428294 -0.00064406 199s 14 -12.6558378 -0.219444 1.1396273 -0.3734679 0.2875578 -0.23870524 199s 15 -10.6924790 -1.818075 3.4560731 -0.1177943 0.1101199 -0.19708172 199s 16 -3.0258070 -0.203186 1.2835368 0.5799363 0.3237454 0.23168871 199s 17 -0.7498665 -2.977505 1.6310512 0.6305329 0.3994006 0.06594881 199s 18 -2.5093526 0.924459 0.0899818 -0.4026675 0.2963072 0.11324019 199s 19 -1.9689970 -1.051282 1.4659908 0.3870104 -0.0708083 -0.02148354 199s 20 0.2695886 -1.646440 0.7597630 0.1750131 -0.3418142 0.21515143 199s 21 -3.3470252 1.989939 0.2887021 -0.3599779 0.0771965 0.16867095 199s 22 -1.4659204 0.777242 0.4090149 -0.1248050 0.1916768 -0.23160291 199s 23 -0.4944476 1.634130 0.8915509 0.1222296 -0.1231015 -0.08351169 199s 24 -0.8945477 1.239223 1.1117165 0.6018455 0.0912200 -0.01204668 199s 25 -4.1499992 1.860190 1.6062973 -0.2139736 -0.1140169 0.16632426 199s 26 -1.2647012 1.188058 1.1893430 -0.2740862 -0.0971504 -0.09851714 199s 27 -3.4280131 -0.267150 1.1969552 0.0354366 0.8482718 -0.18977667 199s 28 1.6896630 3.793723 0.7706325 0.1007287 0.0317704 -0.11269816 199s 29 3.9258127 1.691428 0.1850999 0.4485202 -0.2969916 0.16594044 199s 30 0.3178322 1.577233 0.4455231 -0.1687197 -0.1587136 -0.00823174 199s 31 0.9562350 2.258138 -1.4672169 0.2675668 0.1910110 0.03177387 199s 32 0.6738452 0.470764 -1.3496896 0.3524049 0.2008218 -0.36957179 199s 33 1.5980690 0.413899 0.1999664 0.4232293 0.0768479 -0.04627841 199s 34 0.4365091 -0.626490 0.4718364 0.3392252 0.2554060 -0.19018602 199s 35 -1.1184804 2.124234 0.2650931 0.4791171 0.2927791 -0.01579964 199s 36 3.6673986 1.659798 0.6138972 -0.1092158 -0.2705583 -0.16494176 199s 37 0.0867143 2.541765 -0.4572593 0.0024263 0.2163300 -0.20116352 199s 38 1.4191839 2.315690 0.1365887 0.1028375 0.1595780 -0.02049460 199s 39 -1.8062960 0.845438 1.1469588 0.5022406 0.1603011 -0.08751261 199s 40 3.4380914 -1.358545 0.1956896 0.6314649 0.0716078 -0.21591535 199s 41 3.4608782 1.828575 0.2012565 0.1064437 -0.7454169 -1.64629924 199s 42 6.4162310 -0.402642 0.8070441 0.5146855 0.0331594 0.04373032 199s 43 2.5906567 0.897993 -1.2612252 -0.2620162 -0.1432569 -0.10279385 199s 44 5.0299750 0.203721 0.0439110 0.8775684 -0.9536011 0.15153452 199s 45 -0.3555392 0.454930 0.1173992 0.4688991 0.1137820 0.18752442 199s 46 -0.4155426 1.892410 0.8649578 0.1827426 -0.0186113 -0.04029205 199s 47 1.9328817 0.121936 -3.9578157 -0.1135807 0.2971001 0.18733657 199s 48 -0.3947656 1.028405 -1.0370498 0.4467257 -0.1445498 0.16878692 199s 49 -2.8829860 0.279064 -1.4443310 0.5889970 -0.1883118 0.16947945 199s 50 3.2797246 -2.443968 0.4100655 0.4278962 -0.4414712 0.08598366 199s 51 -1.9272930 -0.622137 -1.5136862 -0.0483369 -0.0272502 0.16006066 199s 52 -5.7161590 -0.298434 -0.5216578 0.1385780 -0.2435931 0.10628617 199s 53 -1.1933277 -0.125878 -0.7556261 -0.3129372 -0.3166453 0.03078643 199s 54 -0.5994394 -0.031069 -0.1296378 0.0061490 -0.1869578 0.09839221 199s 55 0.4104586 0.733465 -0.2088065 -0.3645266 -0.1830137 0.04705775 199s 56 -0.2227671 -0.724741 0.1007592 -0.0838897 -0.1939960 -0.04223579 199s 57 -1.5706297 -0.292436 1.0849660 -0.2559591 -0.0917278 -0.27423151 199s 58 -0.4102168 1.263831 0.9082556 -0.4592777 -0.0676902 0.11089798 199s 59 -1.9640736 -1.340173 -0.3652736 -0.1267573 0.0775692 -0.07977644 199s 60 -1.7490968 -0.941370 -0.0849901 -0.3453455 0.2858594 0.06413468 199s 61 -0.1583416 -1.699326 0.2385988 -0.2231496 -0.0513883 -0.12227279 199s 62 2.2124878 -1.942366 0.0743514 0.2627321 -0.2844018 -0.15848039 199s 63 2.4578489 0.226019 0.1148050 -0.2715718 0.2322085 0.22346659 199s 64 2.4578489 0.226019 0.1148050 -0.2715718 0.2322085 0.22346659 199s 65 -0.3779208 -2.987354 0.6819006 0.1942611 0.0529259 0.01315140 199s 66 -2.6385498 -1.331204 -0.0367809 -0.2327572 0.1845076 -0.08521680 199s 67 0.0526645 -1.301299 0.0912198 0.1634869 -0.0068236 0.24131589 199s 68 -1.1013065 -2.004809 -1.9168056 0.0260663 -0.2029903 -0.12625268 199s 69 -0.9495853 -0.831697 0.0389476 -0.2123483 -0.0202267 0.38463410 199s 70 2.6935893 5.369312 0.6987368 -4.5754846 -9.6833013 -2.32910628 199s 71 -2.4037611 -1.983509 0.3109848 -0.1015686 -0.0071432 0.06410351 199s 72 2.0795505 -0.392730 -0.4534128 -0.4054224 -0.0312781 0.25408988 199s 73 -2.0038405 -2.874605 -0.6269939 0.2408421 0.5184666 0.11140104 199s 74 -11.2683996 -0.361851 3.9219448 0.4045689 -0.2203308 0.05930132 199s 75 -0.1028287 -2.295813 -0.7769187 0.3071821 0.4537196 0.00522380 199s 76 -1.8466137 -0.425825 -1.1261209 -0.1760585 0.0165729 -0.10698465 199s 77 -8.4124493 -1.174820 2.2700712 0.4213953 0.3446597 -0.20636892 199s 78 1.1103236 -1.299480 -0.5787732 -0.1455945 0.0732148 -0.01806218 199s 79 -0.5451834 -0.620170 -0.7830595 -0.1746479 0.0723052 -0.26017118 199s 80 -3.8647223 1.126328 1.3299567 0.2645241 -0.1881443 0.00485531 199s 81 0.7690939 0.887363 0.0513096 -0.2730980 0.0076447 -0.07590882 199s 82 2.7287618 -1.435327 0.1602865 0.4465859 0.2129425 0.16104418 199s 83 2.2241485 -0.042822 -0.8316486 -0.1230697 -0.1193057 -0.35207561 199s 84 0.2452905 0.491732 -2.0050683 0.0286567 -0.1159415 -0.24887542 199s 85 1.0655845 -2.360746 2.2456131 -0.1479972 -0.1186670 -0.14020891 199s 86 -0.0091659 0.952208 -1.3429189 -0.2944676 -0.2433277 0.15354490 199s PC7 PC8 199s 1 -0.09778744 2.3157e-03 199s 2 0.05189698 1.8077e-03 199s 3 0.70506895 1.2838e-03 199s 4 -0.08541140 3.2781e-04 199s 5 0.11768945 8.3496e-04 199s 6 -0.17886391 1.5222e-03 199s 7 0.14143613 1.3261e-04 199s 8 -0.07724578 7.1241e-04 199s 9 -0.12298048 -7.0110e-04 199s 10 0.07569878 2.3093e-05 199s 11 0.29299858 -3.4542e-04 199s 12 0.07764899 -2.1390e-03 199s 13 -0.08945524 -2.2633e-03 199s 14 0.03597787 -1.8891e-03 199s 15 0.11780498 -2.0279e-03 199s 16 0.46501534 -2.3266e-03 199s 17 0.08603290 -2.4073e-03 199s 18 0.52605757 -9.8822e-04 199s 19 0.31007227 -1.3919e-03 199s 20 0.61582059 -2.3549e-05 199s 21 0.01199350 -6.1649e-05 199s 22 0.03654587 1.3302e-05 199s 23 0.27549986 -3.6759e-04 199s 24 -0.04155354 -2.9882e-04 199s 25 0.11473708 -7.9629e-04 199s 26 0.06673183 -8.3728e-04 199s 27 0.16937729 -9.5775e-04 199s 28 -0.41753592 -7.5544e-05 199s 29 -0.03693100 -2.2481e-04 199s 30 0.08461537 -1.3611e-04 199s 31 0.02476253 -1.4319e-04 199s 32 -0.09756048 -1.2234e-04 199s 33 0.06442434 -2.4915e-04 199s 34 -0.17828409 -9.5882e-05 199s 35 0.00881239 -7.1427e-05 199s 36 -0.01041003 -2.8489e-04 199s 37 0.15994729 -3.1472e-04 199s 38 -0.22386895 6.1384e-04 199s 39 0.03666242 2.8506e-04 199s 40 0.35883231 -8.3062e-05 199s 41 0.18521851 8.5509e-04 199s 42 0.00733985 -6.4477e-04 199s 43 0.35466617 3.2923e-04 199s 44 -0.74952524 -7.6869e-05 199s 45 0.09907237 7.9128e-04 199s 46 0.05119980 1.0606e-03 199s 47 -0.48571583 -9.3780e-04 199s 48 -0.27463442 -2.7037e-04 199s 49 0.06787536 -3.0554e-05 199s 50 0.08499400 3.1181e-04 199s 51 -0.09197457 1.1213e-04 199s 52 -0.24513244 3.9100e-04 199s 53 0.24012780 3.2068e-04 199s 54 0.07999888 3.5689e-04 199s 55 -0.09825475 6.6675e-04 199s 56 0.05133674 -7.2984e-05 199s 57 -0.10302363 -2.0693e-04 199s 58 -0.12323360 -1.6620e-04 199s 59 -0.05119989 -1.1016e-03 199s 60 0.00082131 -3.2951e-04 199s 61 0.08128272 -1.1550e-04 199s 62 -0.01789040 -1.1579e-04 199s 63 -0.07188070 -7.8367e-04 199s 64 -0.07188070 -7.8367e-04 199s 65 0.00917085 -2.6800e-05 199s 66 0.03121573 -5.3492e-05 199s 67 0.12202335 -3.0466e-04 199s 68 -0.04764366 -2.6126e-04 199s 69 0.13828337 -3.9331e-04 199s 70 0.10401069 4.2870e-03 199s 71 -0.14369640 3.7669e-05 199s 72 -0.10334451 -2.6456e-04 199s 73 0.17655402 1.0917e-04 199s 74 0.26779696 1.8685e-03 199s 75 -0.75016549 2.1079e-05 199s 76 0.01802016 7.7555e-04 199s 77 0.13081368 6.4286e-04 199s 78 0.01409131 4.9476e-04 199s 79 0.06643384 2.6590e-04 199s 80 -0.12624376 5.9801e-04 199s 81 -0.14074469 -3.2172e-04 199s 82 0.09228230 4.4064e-04 199s 83 -0.06352151 -3.6274e-04 199s 84 -0.02642452 -3.9742e-04 199s 85 -0.03502188 6.9814e-04 199s 86 -0.11749109 -5.1283e-04 199s ------------- 199s Call: 199s PcaCov(x = x) 199s 199s Standard deviations: 199s [1] 2.39971451 1.49157920 0.93184037 0.33183258 0.19628996 0.16485446 0.12784351 199s [8] 0.00052622 199s ---------------------------------------------------------- 199s bushfire 38 5 5 11393.979994 197.523453 199s Scores: 199s PC1 PC2 PC3 PC4 PC5 199s 1 -91.383 -16.17804 0.56195 -0.252428 1.261840 199s 2 -93.033 -13.93251 -0.67212 0.042287 0.470924 199s 3 -85.400 -10.72512 -3.09832 -1.224797 -0.504718 199s 4 -68.381 -12.12202 -3.31950 -0.676880 -0.228383 199s 5 -36.742 -21.04171 -1.98872 0.397655 -0.932613 199s 6 -12.095 -30.21719 0.59595 2.100702 0.384714 199s 7 -227.949 -71.40450 35.57308 -7.880296 -2.710415 199s 8 -262.815 -111.81228 -11.04574 2.397832 -13.646407 199s 9 -263.767 -114.13702 -13.71407 3.131736 -13.825200 199s 10 -264.312 -90.69643 9.72320 0.967173 -8.800150 199s 11 -266.681 -72.85993 16.55010 0.291092 -8.373583 199s 12 -274.050 -18.41395 20.74273 -2.464589 -1.505967 199s 13 -218.299 19.16040 7.69765 0.069012 0.054846 199s 14 29.646 10.52526 -7.50754 0.855493 1.966680 199s 15 159.575 3.86633 -6.95837 -2.753953 0.616068 199s 16 114.286 2.47164 0.62690 -3.146317 -0.501623 199s 17 111.289 3.45086 1.97182 -0.303064 -0.094416 199s 18 99.626 -1.80416 4.88197 -0.013096 -1.438397 199s 19 103.353 -3.50426 3.58993 1.578169 -1.317194 199s 20 113.769 0.84544 3.28254 2.204926 0.131167 199s 21 95.186 3.50703 4.97153 0.916181 0.351658 199s 22 86.996 4.00938 2.95209 1.281788 1.920404 199s 23 -44.232 8.50898 6.30689 -1.038871 0.400078 199s 24 -99.527 13.81377 1.75130 -0.260669 0.394804 199s 25 -34.855 5.99709 -0.57224 -1.660513 -0.620158 199s 26 -41.265 2.94659 -1.04825 -2.243950 -0.440017 199s 27 -56.148 10.14428 -5.41858 0.321752 -0.608412 199s 28 -32.366 20.27795 -8.60687 3.806572 -1.267249 199s 29 -22.438 34.73585 -11.19123 8.296154 -0.511610 199s 30 -79.035 37.05713 -1.51591 9.892959 -1.618635 199s 31 49.465 39.37414 5.95714 22.874813 -1.883481 199s 32 304.825 30.19205 37.68900 45.175923 -1.293939 199s 33 341.237 7.04985 65.43451 44.553009 -3.148116 199s 34 337.467 6.16879 66.48222 43.278480 -3.688631 199s 35 342.929 7.38548 66.91291 43.941556 -1.937887 199s 36 340.143 6.70203 67.85433 42.479161 -3.873639 199s 37 337.931 7.43184 70.50828 42.333220 -2.645830 199s 38 339.281 8.07267 71.34405 42.400459 -2.392774 199s ------------- 199s Call: 199s PcaCov(x = x) 199s 199s Standard deviations: 199s [1] 106.7426 14.0543 4.9184 1.8263 1.0193 199s ---------------------------------------------------------- 199s ========================================================== 199s > dodata(method="grid") 199s 199s Call: dodata(method = "grid") 199s Data Set n p k e1 e2 199s ========================================================== 199s heart 12 2 2 516.143549 23.932102 199s Scores: 199s PC1 PC2 199s [1,] 6.4694 3.8179 199s [2,] 61.7387 19.1814 199s [3,] 1.4722 -1.0161 199s [4,] -3.8056 1.5127 199s [5,] 18.6760 5.3303 199s [6,] -16.8411 1.7900 199s [7,] 4.9962 4.1638 199s [8,] -26.8665 -13.3010 199s [9,] -1.0648 -1.2690 199s [10,] -25.7734 -12.4037 199s [11,] -13.3987 -4.0751 199s [12,] 46.7700 15.1272 199s ------------- 199s Call: 199s PcaGrid(x = x) 199s 199s Standard deviations: 199s [1] 22.719 4.892 199s ---------------------------------------------------------- 199s starsCYG 47 2 2 0.473800 0.026486 199s Scores: 199s PC1 PC2 199s [1,] 0.181489 -0.0300854 199s [2,] 0.695337 0.1492475 199s [3,] -0.120738 -0.1338110 199s [4,] 0.695337 0.1492475 199s [5,] 0.140039 -0.0992368 199s [6,] 0.413314 0.0551030 199s [7,] -0.409428 -0.5478860 199s [8,] 0.225647 0.1690378 199s [9,] 0.519123 -0.1471454 199s [10,] 0.071513 -0.0277935 199s [11,] 0.663045 -0.9203119 199s [12,] 0.402691 0.0253179 199s [13,] 0.373739 0.0759321 199s [14,] -1.005756 -0.3654219 199s [15,] -0.789968 -0.0898580 199s [16,] -0.467328 0.0334465 199s [17,] -1.111148 -0.1431778 199s [18,] -0.867242 0.0417806 199s [19,] -0.871200 -0.1481782 199s [20,] 0.823011 -0.9236455 199s [21,] -0.669994 -0.0923582 199s [22,] -0.829959 -0.0890246 199s [23,] -0.627294 0.0367802 199s [24,] -0.195929 0.0978059 199s [25,] -0.028257 -0.0157122 199s [26,] -0.387346 0.0317797 199s [27,] -0.390054 -0.0981920 199s [28,] -0.148231 -0.0132120 199s [29,] -0.661454 -0.1625514 199s [30,] 0.982767 -0.9369769 199s [31,] -0.628127 -0.0032112 199s [32,] 0.055476 0.1625819 199s [33,] 0.173158 0.0501056 199s [34,] 1.222924 -0.9319795 199s [35,] -0.711235 -0.1515118 199s [36,] 0.576613 0.2117347 199s [37,] 0.054851 0.1325884 199s [38,] 0.173158 0.0501056 199s [39,] 0.134833 0.1309216 199s [40,] 0.522665 0.0228177 199s [41,] -0.428171 -0.0073782 199s [42,] 0.013192 0.0534392 199s [43,] 0.294173 0.0975945 199s [44,] 0.293132 0.0476054 199s [45,] 0.495172 0.1434167 199s [46,] -0.066790 0.0551060 199s [47,] -0.547311 0.0351134 199s ------------- 199s Call: 199s PcaGrid(x = x) 199s 199s Standard deviations: 199s [1] 0.68833 0.16275 199s ---------------------------------------------------------- 199s phosphor 18 2 2 392.155327 50.657228 199s Scores: 199s PC1 PC2 199s 1 5.6537 -15.2305 199s 2 -21.2150 -1.8862 199s 3 -23.5966 2.3112 199s 4 -11.2742 -6.6000 199s 5 -18.4067 1.5202 199s 6 16.9795 -19.4039 199s 7 1.5964 -3.1666 199s 8 -9.7354 3.2429 199s 9 -10.8594 5.4759 199s 10 15.5585 -6.5279 199s 11 -4.0058 1.2905 199s 12 9.4815 8.2139 199s 13 13.0640 6.4346 199s 14 7.0230 7.7600 199s 15 18.4378 3.7658 199s 16 -8.9047 -6.3253 199s 17 21.8748 6.1900 199s 18 16.9843 12.0801 199s ------------- 199s Call: 199s PcaGrid(x = x) 199s 199s Standard deviations: 199s [1] 19.8029 7.1174 199s ---------------------------------------------------------- 199s stackloss 21 3 3 109.445054 16.741203 199s Scores: 199s PC1 PC2 PC3 199s [1,] 15.136434 14.82909 -2.0387704 199s [2,] 14.393636 15.46816 -1.8391595 199s [3,] 12.351209 10.12290 -2.3458098 199s [4,] 2.510036 2.07589 1.8251581 199s [5,] 1.767140 1.78527 -0.0088651 199s [6,] 2.138588 1.93058 0.9081465 199s [7,] 6.966825 -1.75851 0.6274924 199s [8,] 6.966825 -1.75851 0.6274924 199s [9,] -0.089513 -1.09062 2.2894224 199s [10,] -7.146340 2.65628 -0.8983590 199s [11,] -0.461157 -3.09532 -2.6948576 199s [12,] -1.575403 -2.60157 -3.4122582 199s [13,] -5.660744 1.37815 -1.2975809 199s [14,] 2.881484 -5.50628 -2.5762898 199s [15,] -4.917360 -9.13772 0.0676942 199s [16,] -7.145755 -7.22052 0.6665270 199s [17,] -17.173481 1.87173 4.3780920 199s [18,] -11.973894 -2.60174 2.9808153 199s [19,] -10.859648 -3.09549 3.6982160 199s [20,] -6.031899 0.15817 1.2270803 199s [21,] 8.451640 4.98077 -5.4038839 199s ------------- 199s Call: 199s PcaGrid(x = x) 199s 199s Standard deviations: 199s [1] 10.4616 4.0916 2.8271 199s ---------------------------------------------------------- 199s salinity 28 3 3 14.911546 8.034974 199s Scores: 199s PC1 PC2 PC3 199s 1 -2.72400 0.79288 0.688038 199s 2 -3.45684 0.86162 1.941690 199s 3 -5.73471 -4.79507 0.129202 199s 4 -6.17045 -3.04372 -0.352797 199s 5 -4.72453 -5.59543 4.144851 199s 6 -5.75447 -1.07062 0.579975 199s 7 -4.40759 0.47731 0.680203 199s 8 -2.76360 2.30716 0.540271 199s 9 -0.28782 -1.40644 -2.373399 199s 10 2.64361 -1.43362 -0.266957 199s 11 1.91078 -1.66975 1.312215 199s 12 -0.40661 0.68573 -0.200135 199s 13 -0.14911 1.88993 0.044001 199s 14 1.99005 2.43874 1.373229 199s 15 2.88128 -2.21263 -0.863674 199s 16 -0.12935 -8.28831 6.483875 199s 17 -0.16895 -1.68742 0.905190 199s 18 -3.08054 0.23753 -0.269165 199s 19 -0.38685 -1.08501 -2.736860 199s 20 1.45520 -0.33209 -1.686406 199s 21 1.13834 2.53553 -0.381657 199s 22 2.48522 3.42927 0.417050 199s 23 4.56487 -3.36542 0.711908 199s 24 2.94072 -3.08490 1.556939 199s 25 0.82140 -0.26895 -0.406490 199s 26 1.17794 1.61119 -0.863764 199s 27 2.02965 2.80707 -0.489050 199s 28 2.98039 3.21462 0.747622 199s ------------- 199s Call: 199s PcaGrid(x = x) 199s 199s Standard deviations: 199s [1] 3.86155 2.83460 0.95394 199s ---------------------------------------------------------- 199s hbk 75 3 3 3.714805 3.187126 199s Scores: 199s PC1 PC2 PC3 199s 1 8.423138 24.765818 19.413334 199s 2 7.823138 25.295092 20.356662 199s 3 9.023138 27.411905 20.218454 199s 4 8.223138 28.010236 21.568269 199s 5 8.623138 27.442650 21.123471 199s 6 9.123138 25.601873 20.279943 199s 7 8.823138 25.463855 20.770811 199s 8 8.223138 25.264348 19.451646 199s 9 8.023138 27.373593 20.716984 199s 10 7.623138 26.752275 19.666288 199s 11 9.323138 31.108975 24.313778 199s 12 10.323138 33.179719 23.469966 199s 13 10.323138 29.958667 26.231274 199s 14 9.323138 29.345676 34.207755 199s 15 1.723138 -0.077538 0.754886 199s 16 1.423138 -1.818609 -0.080979 199s 17 -1.676862 -1.872341 -0.686878 199s 18 0.623138 -0.077633 -0.548955 199s 19 -0.876862 -0.576068 0.716574 199s 20 1.423138 -0.016144 1.261078 199s 21 0.923138 -0.223313 0.041619 199s 22 -1.276862 -0.299937 1.038679 199s 23 0.323138 -1.327742 0.057038 199s 24 -0.376862 -1.626860 0.034051 199s 25 -0.676862 -1.550331 -2.266849 199s 26 -0.776862 0.290637 1.184359 199s 27 1.623138 0.750760 0.417361 199s 28 0.123138 -0.016334 -1.346603 199s 29 -0.476862 -1.220468 -1.338846 199s 30 -0.476862 1.387213 -1.339036 199s 31 1.423138 -1.059368 -0.824991 199s 32 -1.176862 -1.833934 0.118433 199s 33 -0.176862 -0.691099 0.908323 199s 34 -1.276862 -1.251213 -2.243862 199s 35 1.423138 0.858128 0.325317 199s 36 -0.576862 0.574335 0.102918 199s 37 -1.576862 0.413330 0.892903 199s 38 -0.176862 -1.841691 -1.085702 199s 39 0.423138 -0.752683 -2.205550 199s 40 -1.176862 -0.905930 -0.211430 199s 41 1.723138 0.819721 -0.479993 199s 42 -1.376862 0.666284 -1.093554 199s 43 -1.576862 -1.304659 1.061761 199s 44 0.123138 1.203126 -1.553772 199s 45 0.223138 -1.358581 -2.151818 199s 46 0.123138 1.003714 -1.569097 199s 47 1.323138 -1.159169 -2.136494 199s 48 1.423138 0.919427 -0.472331 199s 49 1.423138 -0.246300 0.340737 199s 50 0.423138 0.727773 0.716479 199s 51 0.623138 -1.665267 -0.771259 199s 52 1.623138 -0.798657 -1.607314 199s 53 -1.376862 1.310494 -1.645816 199s 54 -0.576862 -1.879908 0.716669 199s 55 -1.176862 -1.235698 0.164407 199s 56 0.123138 -1.296997 0.962055 199s 57 0.123138 -1.304849 -1.545920 199s 58 0.723138 -0.714086 1.207441 199s 59 -0.076862 0.881115 0.026199 199s 60 -1.376862 1.226208 -0.549050 199s 61 -1.276862 0.781504 1.322377 199s 62 -0.776862 -1.657699 -2.174806 199s 63 -0.576862 -1.956627 0.409888 199s 64 1.123138 0.712448 0.915891 199s 65 0.323138 0.689271 -1.392672 199s 66 -1.476862 -1.289430 -0.441492 199s 67 -0.076862 -0.905930 -0.211430 199s 68 -1.576862 -0.852389 -2.213213 199s 69 0.323138 -1.696011 -1.676276 199s 70 -0.676862 0.773747 0.118243 199s 71 0.523138 0.152524 0.371386 199s 72 -1.076862 -0.606812 -0.188443 199s 73 -1.376862 0.114117 -0.433924 199s 74 -1.676862 -0.522431 0.018632 199s 75 -1.376862 0.612552 -1.699453 199s ------------- 199s Call: 199s PcaGrid(x = x) 199s 199s Standard deviations: 199s [1] 1.9274 1.7853 1.6714 199s ---------------------------------------------------------- 199s milk 86 8 8 9.206694 2.910585 199s Scores: 199s PC1 PC2 PC3 PC4 PC5 PC6 199s [1,] 6.090978 0.590424 1.1644466 -0.3835606 1.0342867 -0.4752288 199s [2,] 6.903009 -0.575027 0.8613622 -1.1221795 0.7221616 -1.3097951 199s [3,] 0.622903 -1.594239 1.2122863 -0.0555128 0.3252629 -0.2799581 199s [4,] 5.282665 -1.815742 2.2543268 0.9824543 -0.5345577 -0.7331037 199s [5,] -1.039753 0.663906 0.3353811 0.3070599 -0.3224317 -0.4056666 199s [6,] 2.247786 0.218255 -0.3382923 0.1270005 -0.0271307 -0.2035021 199s [7,] 2.784293 -0.291678 -0.4897587 0.0198481 0.0752345 -0.5986846 199s [8,] 2.942266 0.315608 0.1603961 0.3568462 -0.0647311 -0.5316127 199s [9,] -1.420086 -1.751212 1.7027572 0.0708340 -0.9226517 0.0738411 199s [10,] -2.921113 -0.727554 0.0113966 -0.3915037 -0.0772913 0.6062573 199s [11,] -9.568075 0.792291 1.0217507 0.2554182 -0.6254883 0.8899897 199s [12,] -12.885166 3.423607 -1.2579351 -0.4300397 -0.4094558 1.1727128 199s [13,] -10.038470 1.274931 -2.6913262 -1.6219658 -0.3284974 1.1228303 199s [14,] -12.044003 2.096254 -1.2859668 -0.9602250 -0.7937418 0.8264019 199s [15,] -10.798341 1.159257 1.4870766 0.3248231 -1.0787537 0.8723637 199s [16,] -2.841629 0.500846 0.4771762 0.5975365 0.3197882 0.5804087 199s [17,] -1.150691 -1.978038 2.3229313 0.5275273 -0.5339514 0.5421631 199s [18,] -1.992369 1.131288 -0.8385615 0.1156462 0.2253010 -0.3393814 199s [19,] -1.999699 -0.252876 1.2229972 0.5081648 0.0082612 0.3373454 199s [20,] 0.091385 -1.439422 1.1836134 0.6297789 0.0961407 -0.2126653 199s [21,] -2.571346 2.280701 -1.2845660 0.1463583 0.0949331 0.0902039 199s [22,] -0.990078 1.087033 -0.1638640 -0.0351472 0.0743205 -0.0040605 199s [23,] -0.010631 1.704171 0.0038808 0.5765418 0.6086460 0.0329995 199s [24,] -0.440350 1.500798 0.2769870 0.5556999 0.4751445 0.6516120 199s [25,] -3.578249 2.672783 -0.3534268 0.7398104 0.1108289 0.2704730 199s [26,] -0.854914 1.626684 0.2301131 0.5530224 0.0662862 -0.0999969 199s [27,] -3.175381 0.762609 0.5101987 0.0849002 -0.2137237 0.2729808 199s [28,] 2.599844 3.370137 -0.5174736 0.7409946 0.6853156 0.2430943 199s [29,] 4.395534 0.823611 0.1610152 0.8184845 0.7665555 0.0779724 199s [30,] 0.843794 1.438263 -0.2366601 0.4600650 0.3424806 -0.1768083 199s [31,] 1.890815 1.266935 -1.8218143 -0.3909337 0.8390127 0.1026821 199s [32,] 1.300145 -0.085976 -0.8965312 -0.8855787 0.4156780 0.1478055 199s [33,] 1.923087 0.137638 0.3487435 0.2958367 0.4245932 0.1566678 199s [34,] 0.615762 -0.390711 0.8107376 0.0295536 -0.1169590 0.2940241 199s [35,] -0.372946 2.037079 -0.7663299 0.1907237 0.6959350 0.5366205 199s [36,] 4.068134 1.129044 0.5492962 0.7640964 0.4799859 -0.4080205 199s [37,] 0.937617 2.048258 -1.2326566 -0.0942856 0.7885267 -0.1004018 199s [38,] 2.141223 1.877022 -0.5178216 0.3750868 0.4767003 0.1240656 199s [39,] -1.403505 1.327163 0.3165610 0.3989824 0.3505825 0.5915956 199s [40,] 3.337528 -1.689495 1.4737175 0.2584843 0.4308444 -0.0810597 199s [41,] 3.938506 1.384908 0.8103687 -0.5875595 1.1616535 -0.6492603 199s [42,] 6.327471 -1.061362 1.9861187 1.1016484 0.3512405 -0.1540592 199s [43,] 3.120160 -0.064108 -0.8370717 -0.2229341 0.5623447 -0.7152184 199s [44,] 5.290520 -0.669008 0.8597130 0.5518503 0.2470856 0.6454703 199s [45,] 0.058291 0.356399 -0.1896007 0.2427518 0.3705541 0.3975085 199s [46,] 0.150881 1.942057 -0.1140726 0.5656469 0.5227623 0.2151825 199s [47,] 2.870881 -1.446283 -2.8450062 -1.7292144 -0.0888429 -0.1347003 199s [48,] 0.335593 0.500884 -1.3154520 -0.3874864 0.3449038 0.5387692 199s [49,] -2.179494 -0.021237 -1.7792344 -0.8445930 0.4435338 0.6547961 199s [50,] 2.968304 -2.588546 1.8552104 0.4590101 -0.1755089 -0.0550378 199s [51,] -1.399208 -0.820296 -1.3660014 -0.8890243 -0.2344105 0.1236943 199s [52,] -5.112989 0.318983 -1.3852993 -0.8461529 -0.3467685 0.7349666 199s [53,] -0.773103 -0.267333 -0.8154896 -0.3783062 0.0113880 -0.3304648 199s [54,] -0.244565 -0.066211 -0.2541557 0.0043037 0.0390890 0.0074067 199s [55,] 0.894921 0.516411 -0.4443369 0.0708354 -0.0637890 -0.2799646 199s [56,] -0.038706 -0.588256 0.3166588 -0.0196663 -0.1793472 -0.1179341 199s [57,] -1.377469 0.428939 0.7502430 0.1458375 -0.3818977 -0.0380258 199s [58,] 0.042787 1.488605 0.0252606 0.6377516 -0.1524172 -0.1898723 199s [59,] -1.734357 -0.966494 -0.1026850 -0.5656888 -0.4831402 0.0308069 199s [60,] -1.501991 -0.544918 -0.0837127 -0.2362486 -0.5382026 -0.1351338 199s [61,] -0.175102 -1.339436 0.8403933 -0.0907428 -0.4846145 -0.2795153 199s [62,] 2.100915 -2.004702 1.3031556 -0.0041957 -0.2067776 -0.0793613 199s [63,] 2.735432 -0.102018 0.3215454 0.5331904 -0.1499209 -0.3536272 199s [64,] 2.735432 -0.102018 0.3215454 0.5331904 -0.1499209 -0.3536272 199s [65,] -0.665219 -2.325594 1.6287363 0.0607163 -0.6996720 0.1353325 199s [66,] -2.439244 -0.737375 0.0187770 -0.4561269 -0.5425315 -0.0208332 199s [67,] 0.121564 -1.214385 0.4877707 0.1809998 -0.1943262 0.0662506 199s [68,] -0.804267 -2.238327 -0.8547917 -1.3449926 -0.3577254 -0.0293779 199s [69,] -0.761319 -0.676391 -0.0245494 0.2262894 -0.3396872 -0.1166505 199s [70,] 3.385399 4.360467 -0.7946150 -0.0417895 0.4474362 -4.6626174 199s [71,] -2.364955 -1.257673 0.5226907 -0.2346145 -0.7838777 0.1815821 199s [72,] 2.334511 -0.794530 0.0175620 0.1848925 -0.3437761 -0.4522442 199s [73,] -2.023440 -2.449907 0.2525041 -0.6657474 -0.5509480 0.2118442 199s [74,] -11.180192 2.456516 1.1036540 0.8711496 -0.3833194 1.3548314 199s [75,] 0.058297 -2.094811 0.3075211 -0.8052760 -0.9527729 0.5850255 199s [76,] -1.355742 -0.464355 -1.0183333 -0.8525619 -0.1577144 -0.0767323 199s [77,] -8.296881 0.945092 0.8088967 -0.0071463 -0.4527530 1.0614233 199s [78,] 1.251696 -1.460466 0.2511701 -0.2717606 -0.3158308 -0.2964813 199s [79,] -0.192380 -0.662365 -0.3671703 -0.6722658 -0.1243452 -0.2388225 199s [80,] -3.355201 1.915096 -0.1086672 0.3560062 0.0956865 0.6974817 199s [81,] 1.245305 0.736787 -0.1662155 0.1309822 -0.0122872 -0.2182528 199s [82,] 2.679561 -1.666401 1.1576691 0.3960280 -0.0059146 0.0584136 199s [83,] 2.596651 -0.556654 -0.0807307 -0.4468501 0.0964927 -0.3922894 199s [84,] 0.959377 -0.272038 -1.5879803 -1.1153057 0.3412508 -0.1281556 199s [85,] 0.602737 -1.384591 2.8844745 0.9479144 -0.7946454 -0.2014038 199s [86,] 0.698125 0.335743 -1.5248055 -0.4443037 0.0768256 -0.1999790 199s PC7 PC8 199s [1,] 0.9281777 -0.05158594 199s [2,] 0.8397946 -0.04276628 199s [3,] -0.5189230 0.04913688 199s [4,] -0.0178377 0.01578074 199s [5,] -0.0129237 0.01056305 199s [6,] -0.0764270 0.01469518 199s [7,] -0.3059779 0.04237267 199s [8,] -0.0684673 0.02289928 199s [9,] -0.2549733 -0.00832119 199s [10,] -0.0578118 -0.01894694 199s [11,] 0.0415545 -0.03474479 199s [12,] 0.0869267 -0.04485633 199s [13,] -0.2843977 -0.03100709 199s [14,] -0.3375083 -0.02155574 199s [15,] -0.1718828 -0.02996980 199s [16,] -0.4176728 0.03232381 199s [17,] -0.5923252 0.01765700 199s [18,] -0.3190679 0.04476532 199s [19,] -0.0279426 -0.00236626 199s [20,] 0.1299811 0.00586022 199s [21,] 0.0474059 0.00563264 199s [22,] -0.1240299 0.01123557 199s [23,] 0.2232631 0.00551065 199s [24,] 0.0122404 0.00060079 199s [25,] 0.2627442 -0.00824800 199s [26,] 0.2257329 -0.00440907 199s [27,] -0.8496967 0.05266701 199s [28,] 0.3473502 -0.00500580 199s [29,] 0.4172329 -0.00542705 199s [30,] 0.2773880 -0.00014648 199s [31,] -0.1224270 0.02372808 199s [32,] -0.2224748 0.00757892 199s [33,] -0.0633903 0.01236118 199s [34,] -0.2616599 0.00561781 199s [35,] -0.1671986 0.01988458 199s [36,] 0.4502086 -0.00418541 199s [37,] -0.0773232 0.02768282 199s [38,] 0.0464683 0.01134849 199s [39,] -0.0927182 0.00555823 199s [40,] -0.2162796 0.02467605 199s [41,] 0.9440753 -0.04806541 199s [42,] -0.0078920 0.02022925 199s [43,] 0.1152244 0.02074199 199s [44,] 1.0406693 -0.08815111 199s [45,] -0.1376804 0.01424369 199s [46,] 0.1673461 0.00442877 199s [47,] -0.4125225 0.01038694 199s [48,] 0.1556289 -0.02103354 199s [49,] 0.0434415 -0.01782739 199s [50,] 0.2518610 -0.02154540 199s [51,] -0.1186185 -0.00881133 199s [52,] 0.1507435 -0.04523343 199s [53,] 0.2161208 -0.00967982 199s [54,] 0.1374909 -0.00783970 199s [55,] 0.2417108 -0.00895268 199s [56,] 0.1253846 -0.01188643 199s [57,] 0.1390898 -0.01831232 199s [58,] 0.2219634 -0.00364174 199s [59,] -0.2045636 -0.00589047 199s [60,] -0.3679942 0.01673699 199s [61,] -0.0705611 -0.00273407 199s [62,] 0.1447701 -0.02026768 199s [63,] -0.1854788 0.02686899 199s [64,] -0.1854788 0.02686899 199s [65,] -0.2626650 -0.00376657 199s [66,] -0.3044266 0.00484197 199s [67,] -0.1358811 0.00605789 199s [68,] -0.0551482 -0.02379410 199s [69,] -0.0914891 0.00812122 199s [70,] 10.2524854 -0.64367029 199s [71,] -0.1326972 -0.01666774 199s [72,] 0.0051905 0.00656777 199s [73,] -0.8236843 0.03367265 199s [74,] 0.2140104 -0.04092219 199s [75,] -0.5684260 -0.00987116 199s [76,] -0.1225779 -0.00204629 199s [77,] -0.4235612 -0.00450631 199s [78,] -0.1935155 0.00973901 199s [79,] -0.1615883 0.00518643 199s [80,] 0.2915052 -0.02960159 199s [81,] 0.0908823 0.00038216 199s [82,] -0.3392789 0.02605374 199s [83,] 0.1112141 -0.00629308 199s [84,] 0.0510771 -0.00845572 199s [85,] 0.0748700 -0.01174487 199s [86,] 0.2488127 -0.01446339 199s ------------- 199s Call: 199s PcaGrid(x = x) 199s 199s Standard deviations: 199s [1] 3.034253 1.706044 1.167717 0.670864 0.536071 0.396285 0.266625 0.020768 199s ---------------------------------------------------------- 199s bushfire 38 5 5 38232.614428 1580.825276 199s Scores: 199s PC1 PC2 PC3 PC4 PC5 199s [1,] -67.120 -23.70481 -1.06551 1.129721 1.311630 199s [2,] -69.058 -21.42113 -1.54798 0.983735 0.430774 199s [3,] -61.939 -17.23665 -3.81386 -0.635074 -0.600149 199s [4,] -44.952 -16.53458 -5.16114 0.411753 -0.390518 199s [5,] -12.644 -21.62271 -7.14146 3.519877 -1.211923 199s [6,] 12.820 -27.86930 -7.66114 7.230422 0.040330 199s [7,] -194.634 -100.67730 27.43084 -0.026242 -0.134248 199s [8,] -229.349 -129.75912 -19.46346 25.591651 -18.592601 199s [9,] -230.306 -131.28743 -22.22175 27.251157 -19.214683 199s [10,] -231.118 -115.10815 3.70208 16.303210 -10.573515 199s [11,] -234.540 -100.24984 13.67112 10.325539 -8.727961 199s [12,] -246.507 -51.03515 27.61698 -5.352226 0.514087 199s [13,] -195.712 -5.81324 20.04485 -9.226807 1.721886 199s [14,] 49.881 16.90911 -9.97400 -1.900739 2.190429 199s [15,] 179.545 23.96999 -18.71166 -2.987136 1.332713 199s [16,] 135.356 15.81282 -9.24353 -4.703584 0.971669 199s [17,] 132.350 16.65014 -7.01838 -2.428578 1.346198 199s [18,] 121.499 9.75832 -4.45699 -1.587450 0.131923 199s [19,] 125.222 9.17601 -5.88919 0.582516 -0.061642 199s [20,] 135.112 14.63812 -5.90351 0.411704 1.460488 199s [21,] 116.581 14.47390 -3.04021 -1.842579 2.005998 199s [22,] 108.223 14.62103 -4.47428 -1.196993 3.288463 199s [23,] -22.095 3.26439 6.58391 -6.164581 2.125258 199s [24,] -77.831 3.46616 6.59280 -6.373595 1.545789 199s [25,] -13.092 3.41344 -0.99296 -5.076733 0.299636 199s [26,] -19.206 -0.17007 -1.84209 -4.858675 0.347945 199s [27,] -35.022 6.54155 -3.12767 -3.556587 -0.327873 199s [28,] -12.651 20.14894 -4.61607 -2.025539 -1.214190 199s [29,] -4.404 36.39823 -3.81590 -0.633155 -0.602027 199s [30,] -60.018 30.40980 9.44610 -1.763156 -0.765133 199s [31,] 67.689 47.40087 12.70229 9.791794 -0.671751 199s [32,] 324.134 63.46147 31.52512 30.099817 2.406344 199s [33,] 364.639 38.84260 51.20467 30.648590 3.218678 199s [34,] 361.089 37.09494 52.00522 29.394356 2.861158 199s [35,] 366.403 38.88889 52.31879 29.878844 4.650618 199s [36,] 363.821 37.40859 53.10394 28.286557 2.922632 199s [37,] 361.761 37.21276 55.73012 27.648760 4.477279 199s [38,] 363.106 37.78395 56.56345 27.460078 4.845396 199s ------------- 199s Call: 199s PcaGrid(x = x) 199s 199s Standard deviations: 199s [1] 195.5316 39.7596 11.7329 7.3743 1.7656 199s ---------------------------------------------------------- 199s ========================================================== 199s > 199s > ## IGNORE_RDIFF_BEGIN 199s > dodata(method="proj") 199s 199s Call: dodata(method = "proj") 199s Data Set n p k e1 e2 199s ========================================================== 199s heart 12 2 2 512.772467 29.052346 199s Scores: 199s PC1 PC2 199s [1,] 6.7568 3.2826 199s [2,] 63.0869 14.1293 199s [3,] 1.3852 -1.1318 199s [4,] -3.6709 1.8153 199s [5,] 19.0457 3.8035 199s [6,] -16.6413 3.1452 199s [7,] 5.3163 3.7464 199s [8,] -27.8536 -11.0863 199s [9,] -1.1638 -1.1788 199s [10,] -26.6915 -10.2803 199s [11,] -13.6842 -2.9790 199s [12,] 47.8395 11.2980 199s ------------- 199s Call: 199s PcaProj(x = x) 199s 199s Standard deviations: 199s [1] 22.644 5.390 199s ---------------------------------------------------------- 199s starsCYG 47 2 2 0.470874 0.024681 199s Scores: 199s PC1 PC2 199s [1,] 0.181333 -3.1013e-02 199s [2,] 0.696091 1.4569e-01 199s [3,] -0.121421 -1.3319e-01 199s [4,] 0.696091 1.4569e-01 199s [5,] 0.139530 -9.9951e-02 199s [6,] 0.413590 5.2989e-02 199s [7,] -0.412224 -5.4579e-01 199s [8,] 0.226508 1.6788e-01 199s [9,] 0.518364 -1.4980e-01 199s [10,] 0.071370 -2.8159e-02 199s [11,] 0.658332 -9.2369e-01 199s [12,] 0.402815 2.3259e-02 199s [13,] 0.374123 7.4020e-02 199s [14,] -1.007611 -3.6028e-01 199s [15,] -0.790417 -8.5818e-02 199s [16,] -0.467151 3.5835e-02 199s [17,] -1.111866 -1.3750e-01 199s [18,] -0.867017 4.6214e-02 199s [19,] -0.871946 -1.4372e-01 199s [20,] 0.818278 -9.2784e-01 199s [21,] -0.670457 -8.8932e-02 199s [22,] -0.830403 -8.4781e-02 199s [23,] -0.627097 3.9987e-02 199s [24,] -0.195426 9.8806e-02 199s [25,] -0.028337 -1.5568e-02 199s [26,] -0.387178 3.3760e-02 199s [27,] -0.390551 -9.6197e-02 199s [28,] -0.148297 -1.2454e-02 199s [29,] -0.662277 -1.5917e-01 199s [30,] 0.977965 -9.4199e-01 199s [31,] -0.628135 -7.3179e-16 199s [32,] 0.056306 1.6230e-01 199s [33,] 0.173412 4.9220e-02 199s [34,] 1.218143 -9.3822e-01 199s [35,] -0.712000 -1.4787e-01 199s [36,] 0.577688 2.0878e-01 199s [37,] 0.055528 1.3231e-01 199s [38,] 0.173412 4.9220e-02 199s [39,] 0.135501 1.3023e-01 199s [40,] 0.522775 2.0145e-02 199s [41,] -0.428203 -5.1892e-03 199s [42,] 0.013465 5.3371e-02 199s [43,] 0.294668 9.6089e-02 199s [44,] 0.293371 4.6106e-02 199s [45,] 0.495898 1.4088e-01 199s [46,] -0.066508 5.5447e-02 199s [47,] -0.547124 3.7911e-02 199s ------------- 199s Call: 199s PcaProj(x = x) 199s 199s Standard deviations: 199s [1] 0.6862 0.1571 199s ---------------------------------------------------------- 199s phosphor 18 2 2 388.639033 51.954664 199s Scores: 199s PC1 PC2 199s 1 5.8164 -15.1691 199s 2 -21.1936 -2.1132 199s 3 -23.6199 2.0585 199s 4 -11.2029 -6.7203 199s 5 -18.4220 1.3231 199s 6 17.1862 -19.2211 199s 7 1.6302 -3.1493 199s 8 -9.7695 3.1385 199s 9 -10.9174 5.3594 199s 10 15.6275 -6.3610 199s 11 -4.0194 1.2476 199s 12 9.3931 8.3149 199s 13 12.9944 6.5741 199s 14 6.9396 7.8348 199s 15 18.3964 3.9629 199s 16 -8.8365 -6.4202 199s 17 21.8073 6.4237 199s 18 16.8541 12.2611 199s ------------- 199s Call: 199s PcaProj(x = x) 199s 199s Standard deviations: 199s [1] 19.714 7.208 199s ---------------------------------------------------------- 199s stackloss 21 3 3 97.347030 38.052774 199s Scores: 199s PC1 PC2 PC3 199s [1,] 19.08066 -9.06092 -2.64544 199s [2,] 18.55152 -9.90152 -2.76118 199s [3,] 15.04269 -5.37517 -2.31373 199s [4,] 2.79667 -1.78925 1.70823 199s [5,] 2.21768 -1.17513 -0.10495 199s [6,] 2.50717 -1.48219 0.80164 199s [7,] 5.97151 3.25438 2.40268 199s [8,] 5.97151 3.25438 2.40268 199s [9,] -0.68332 0.30263 2.42495 199s [10,] -5.83478 -4.04630 -2.91819 199s [11,] -1.07253 3.51914 -1.87651 199s [12,] -1.89116 2.98559 -2.89885 199s [13,] -4.77650 -2.36509 -2.68671 199s [14,] 1.33353 6.57450 -0.50696 199s [15,] -7.45351 7.08878 1.37012 199s [16,] -9.04093 4.56697 1.02289 199s [17,] -16.15938 -7.50855 0.30909 199s [18,] -12.45541 -1.62432 1.11929 199s [19,] -11.63677 -1.09077 2.14162 199s [20,] -5.79275 -2.08680 -0.06187 199s [21,] 10.13623 -0.76824 -4.70180 199s ------------- 199s Call: 199s PcaProj(x = x) 199s 199s Standard deviations: 199s [1] 9.8665 6.1687 3.2669 199s ---------------------------------------------------------- 199s salinity 28 3 3 12.120566 8.431549 199s Scores: 199s PC1 PC2 PC3 199s 1 -2.52547 1.45945 -1.1943e-01 199s 2 -3.32298 2.15704 8.7594e-01 199s 3 -6.64947 -3.26398 1.0135e+00 199s 4 -6.64427 -1.81382 -1.6392e-01 199s 5 -6.16898 -2.52222 5.1373e+00 199s 6 -5.87594 0.26440 -3.1956e-15 199s 7 -4.23084 1.46250 -2.8008e-01 199s 8 -2.21502 2.76478 -8.3789e-01 199s 9 -0.40186 -2.17785 -1.6702e+00 199s 10 2.27089 -1.84923 7.3391e-01 199s 11 1.37935 -1.29276 2.1418e+00 199s 12 -0.22635 0.60372 -5.0980e-01 199s 13 0.27224 1.73920 -7.0505e-01 199s 14 2.36592 2.40462 6.4320e-01 199s 15 2.37640 -2.83174 5.2669e-01 199s 16 -2.49175 -4.77664 9.0404e+00 199s 17 -0.61250 -1.11672 1.4398e+00 199s 18 -2.91853 0.63310 -8.3666e-01 199s 19 -0.39732 -2.02029 -2.1396e+00 199s 20 1.47554 -1.23407 -1.1712e+00 199s 21 1.70104 1.92401 -1.1292e+00 199s 22 3.14437 2.81928 -5.2415e-01 199s 23 3.62890 -3.51450 2.6740e+00 199s 24 2.04538 -2.63992 3.0718e+00 199s 25 0.77088 -0.54783 -1.3370e-01 199s 26 1.57254 0.89176 -1.2089e+00 199s 27 2.63610 1.97075 -1.1855e+00 199s 28 3.55112 2.67606 -6.0915e-02 199s ------------- 199s Call: 199s PcaProj(x = x) 199s 199s Standard deviations: 199s [1] 3.4815 2.9037 1.3810 199s ---------------------------------------------------------- 199s hbk 75 3 3 3.801978 3.574192 199s Scores: 199s PC1 PC2 PC3 199s 1 28.747049 15.134042 2.3959241 199s 2 29.021724 16.318941 2.6207988 199s 3 31.271908 15.869319 3.4420860 199s 4 31.586189 17.508798 3.6246706 199s 5 31.299168 16.838093 3.2402573 199s 6 30.037754 15.591930 2.1421166 199s 7 29.888160 16.139376 1.9750096 199s 8 28.994463 15.350167 2.8226275 199s 9 30.758047 16.820526 3.7269602 199s 10 29.759314 16.079531 4.0486097 199s 11 35.301371 19.637962 3.7433562 199s 12 37.193371 18.709303 4.9915250 199s 13 35.634808 20.497713 1.4740727 199s 14 36.816439 27.523024 -2.3006796 199s 15 1.237203 -0.331072 -1.3801401 199s 16 -0.451166 -1.118847 -1.9707479 199s 17 -2.604733 0.067276 0.0130015 199s 18 0.179177 -0.804398 -0.1285240 199s 19 -0.765512 0.982349 -0.2513990 199s 20 1.236727 0.259123 -1.4210070 199s 21 0.428326 -0.503724 -0.6830690 199s 22 -0.724774 1.507943 -0.0022175 199s 23 -0.745349 -0.330094 -1.0982084 199s 24 -1.407850 -0.011831 -0.8987075 199s 25 -2.190427 -1.732051 0.4497793 199s 26 0.058631 1.444044 0.0446166 199s 27 1.680557 -0.429402 -0.6031146 199s 28 -0.315122 -1.179169 0.5822607 199s 29 -1.563355 -1.026914 0.1040012 199s 30 0.329957 -0.633156 1.8533795 199s 31 -0.110108 -1.617131 -1.0958807 199s 32 -2.035875 0.463421 -0.6346632 199s 33 -0.356033 0.740564 -0.8116369 199s 34 -2.342887 -1.340168 0.9724491 199s 35 1.607131 -0.379763 -0.3747630 199s 36 0.084455 0.486671 0.6551654 199s 37 -0.436144 1.659467 0.7145344 199s 38 -1.754819 -1.076076 -0.6037590 199s 39 -0.904375 -2.161949 0.3436723 199s 40 -1.455274 0.331839 0.1499308 199s 41 1.539788 -1.212921 -0.1715110 199s 42 -0.688338 -0.048173 1.7491184 199s 43 -1.635822 1.539067 -0.5208916 199s 44 0.511762 -1.165641 1.5020865 199s 45 -1.454500 -2.099954 0.0219268 199s 46 0.362645 -1.208389 1.3758464 199s 47 -0.615800 -2.658098 -0.4629006 199s 48 1.426278 -1.027667 0.0582638 199s 49 0.809592 -0.533893 -1.1232120 199s 50 0.996105 0.469082 -0.0988805 199s 51 -1.036368 -1.227376 -1.0843166 199s 52 -0.016464 -2.331540 -0.6477169 199s 53 -0.376625 -0.405855 2.4526088 199s 54 -1.524100 0.621590 -1.2927429 199s 55 -1.588523 0.591668 -0.2559428 199s 56 -0.592710 0.529426 -1.4111404 199s 57 -1.306991 -1.538024 -0.1841717 199s 58 0.275991 0.491888 -1.4739863 199s 59 0.598971 0.196673 0.6208960 199s 60 -0.127953 0.485014 1.8571970 199s 61 0.140584 1.905037 0.5838465 199s 62 -2.305069 -1.617811 0.3880825 199s 63 -1.666479 0.357251 -1.1934779 199s 64 1.480143 0.248671 -0.5959984 199s 65 0.309561 -1.219790 0.9671263 199s 66 -1.986789 0.248245 0.1723620 199s 67 -0.765691 -0.269054 -0.4611368 199s 68 -2.232721 -1.090790 1.3915841 199s 69 -1.502453 -1.813763 -0.4936268 199s 70 0.170883 0.584046 0.8369571 199s 71 0.543623 0.043244 -0.3707674 199s 72 -1.168908 0.341335 0.2837393 199s 73 -0.902885 0.411872 1.0546196 199s 74 -1.425273 0.852445 0.5719123 199s 75 -0.898536 -0.555475 2.0107684 199s ------------- 199s Call: 199s PcaProj(x = x) 199s 199s Standard deviations: 199s [1] 1.9499 1.8906 1.2797 199s ---------------------------------------------------------- 199s milk 86 8 8 8.369408 3.530461 199s Scores: 199s PC1 PC2 PC3 PC4 PC5 PC6 199s [1,] 6.337004 -0.245000 0.7704092 -4.9848e-01 -1.6599e-01 1.1763e-01 199s [2,] 7.021899 1.030349 0.2832977 -1.2673e+00 -8.7296e-01 2.0547e-01 199s [3,] 0.600831 1.686247 0.9682032 -3.2663e-02 7.4112e-02 4.7412e-01 199s [4,] 5.206465 2.665956 1.5942253 9.8285e-01 -5.4159e-01 -2.0155e-01 199s [5,] -0.955757 -0.579889 0.3206393 5.1174e-01 -6.1684e-01 -3.8990e-02 199s [6,] 2.198695 0.073770 -0.5712493 1.9440e-01 -1.0237e-01 4.1825e-02 199s [7,] 2.695361 0.644049 -0.8645373 8.1894e-02 -2.6953e-01 1.6884e-01 199s [8,] 2.945361 0.137227 -0.2071463 5.0841e-01 -4.2075e-01 5.8589e-02 199s [9,] -1.539013 1.879894 1.6952390 1.6792e-01 -2.8195e-01 5.0563e-02 199s [10,] -2.977110 0.319666 0.3515636 -5.2496e-01 4.6898e-01 8.5978e-03 199s [11,] -9.375355 -1.638105 1.9026171 4.1237e-01 1.8768e-02 -1.8546e-01 199s [12,] -12.602600 -4.715888 0.0273004 -4.7798e-02 -1.2246e-02 9.6858e-03 199s [13,] -10.114331 -2.487462 -1.6331544 -1.5139e+00 4.1903e-01 2.8313e-01 199s [14,] -11.949336 -3.190157 -0.2146943 -5.0060e-01 -2.9537e-01 3.2160e-01 199s [15,] -10.595396 -1.905517 2.3716887 7.6651e-01 -3.3531e-01 1.9933e-02 199s [16,] -2.735720 -0.748282 0.6750464 7.2415e-01 5.5304e-01 2.2283e-01 199s [17,] -1.248116 2.131195 2.2596886 6.4958e-01 3.5634e-01 2.9021e-01 199s [18,] -1.904210 -1.285804 -0.7746460 3.0198e-01 -2.7407e-01 1.7500e-01 199s [19,] -1.902313 0.095461 1.3824711 5.0369e-01 2.2193e-01 -5.5628e-02 199s [20,] 0.123220 1.399444 1.1517634 3.2546e-01 7.8261e-02 -4.0733e-01 199s [21,] -2.436023 -2.524827 -1.0197416 3.4819e-01 -1.4914e-01 -4.3669e-02 199s [22,] -0.904931 -1.114894 -0.1235807 2.0285e-01 -1.6200e-01 2.5681e-01 199s [23,] 0.220231 -1.767325 0.0482262 6.4418e-01 9.8618e-02 -5.7683e-02 199s [24,] -0.274403 -1.561826 0.3820323 7.0016e-01 5.5220e-01 1.4376e-01 199s [25,] -3.306400 -2.980247 0.0252488 9.4001e-01 -1.0841e-01 -2.5303e-01 199s [26,] -0.658015 -1.625199 0.3021005 7.2702e-01 -3.0299e-01 -1.2339e-01 199s [27,] -3.137066 -0.774218 0.5577497 6.4188e-01 -8.0125e-02 7.7819e-01 199s [28,] 2.867950 -3.099435 -0.6435415 1.0366e+00 1.5908e-01 7.6524e-02 199s [29,] 4.523097 -0.527338 -0.1032516 6.4537e-01 4.7286e-01 -2.7166e-01 199s [30,] 1.002381 -1.376693 -0.2735956 5.0522e-01 -1.2750e-01 -1.6178e-01 199s [31,] 1.894615 -1.296202 -1.9117282 -3.8032e-01 4.6473e-01 3.1085e-01 199s [32,] 1.210291 0.067230 -0.9832930 -8.5379e-01 3.2823e-01 4.9994e-01 199s [33,] 1.964118 0.022175 0.1818518 3.0464e-01 3.5596e-01 1.4985e-01 199s [34,] 0.576738 0.567851 0.6982155 1.8415e-01 1.8695e-01 3.2706e-01 199s [35,] -0.231793 -2.143909 -0.6825523 4.0681e-01 5.4492e-01 3.6259e-01 199s [36,] 4.250883 -0.719760 0.2157706 7.7167e-01 -1.9064e-01 -2.0611e-01 199s [37,] 1.077364 -2.054664 -1.3064867 1.0043e-01 8.6092e-02 3.5416e-01 199s [38,] 2.259260 -1.653588 -0.6730692 5.7300e-01 1.6930e-01 1.6986e-01 199s [39,] -1.251576 -1.451593 0.4671580 5.8957e-01 4.2672e-01 2.2495e-01 199s [40,] 3.304245 1.998193 1.0941231 1.3734e-01 3.7012e-01 2.4142e-01 199s [41,] 4.286315 -1.280951 0.5856744 -6.0980e-01 -4.3090e-01 1.9801e-01 199s [42,] 6.343820 1.801880 1.3481119 1.0355e+00 2.9802e-01 -8.4501e-04 199s [43,] 3.119491 0.214077 -1.1216236 -3.8134e-01 -1.9523e-01 -2.6706e-02 199s [44,] 5.285254 0.938072 0.7440487 1.1539e-02 8.1629e-01 -7.9286e-01 199s [45,] 0.082429 -0.416631 -0.1588203 2.3098e-01 5.1867e-01 9.4503e-02 199s [46,] 0.357862 -1.951997 -0.0731829 7.0393e-01 1.8828e-01 1.5707e-02 199s [47,] 2.428744 1.522538 -3.0467213 -1.9114e+00 2.4638e-01 3.5871e-01 199s [48,] 0.282348 -0.697287 -1.1592508 -5.4929e-01 6.2199e-01 -5.4596e-02 199s [49,] -2.266009 -0.559548 -1.3794914 -1.1300e+00 7.8872e-01 -2.0411e-02 199s [50,] 2.868649 2.860857 1.6128307 6.7382e-02 2.2344e-01 -4.1484e-01 199s [51,] -1.596061 0.546812 -1.1779327 -1.0512e+00 1.3522e-01 -9.4865e-03 199s [52,] -5.186121 -1.000829 -0.7440599 -9.6302e-01 3.0732e-01 -1.7009e-01 199s [53,] -0.800232 0.049087 -0.6946842 -5.8284e-01 -2.1277e-01 -2.7004e-01 199s [54,] -0.246388 -0.030606 -0.1814302 -1.1632e-01 5.7767e-02 -1.8637e-01 199s [55,] 0.914315 -0.428594 -0.4919557 4.5039e-02 -2.7868e-01 -2.2140e-01 199s [56,] -0.061827 0.583572 0.3263056 -1.1589e-01 -1.2973e-01 -1.6518e-01 199s [57,] -1.295979 -0.421943 0.8410805 3.0441e-01 -3.9478e-01 -4.5233e-02 199s [58,] 0.174908 -1.343854 0.0115086 8.0227e-01 -3.9364e-01 -2.2918e-01 199s [59,] -1.869684 0.840823 0.0109543 -5.5536e-01 -1.4155e-01 1.0613e-01 199s [60,] -1.614271 0.557309 -0.0690787 -9.1753e-02 -3.0975e-01 1.6192e-01 199s [61,] -0.258192 1.434984 0.7684636 -1.1998e-01 -3.4662e-01 -4.8808e-02 199s [62,] 2.000275 2.204730 1.1194067 -2.3783e-01 5.9953e-02 -1.5836e-01 199s [63,] 2.694063 0.555482 -0.0340910 6.4470e-01 -2.2417e-01 1.9442e-02 199s [64,] 2.694063 0.555482 -0.0340910 6.4470e-01 -2.2417e-01 1.9442e-02 199s [65,] -0.822201 2.427550 1.5859438 -3.5437e-16 2.2436e-15 -4.7251e-15 199s [66,] -2.545586 0.605953 0.1469837 -3.5318e-01 -2.5871e-01 1.6901e-01 199s [67,] 0.028900 1.253717 0.4474540 5.3595e-02 1.6063e-01 -1.0980e-01 199s [68,] -1.086135 1.968868 -0.7220293 -1.6576e+00 6.2061e-02 -7.0998e-04 199s [69,] -0.836638 0.660453 0.0049966 1.3663e-01 -1.0131e-01 -2.4008e-01 199s [70,] 4.843092 -6.035092 0.8250084 -3.4481e+00 -4.8538e+00 -7.8407e+00 199s [71,] -2.500038 1.146245 0.6967314 -2.4611e-01 -1.4266e-01 -8.2996e-02 199s [72,] 2.220676 1.122951 -0.2444075 1.1066e-01 -3.1540e-01 -2.1344e-01 199s [73,] -2.310518 2.354552 0.2706503 -6.4192e-01 2.0566e-01 4.5520e-01 199s [74,] -10.802799 -3.462655 2.2031446 1.1326e+00 2.8049e-01 -2.9749e-01 199s [75,] -0.301038 2.284366 0.2440764 -6.9450e-01 2.6435e-01 4.3129e-01 199s [76,] -1.477936 0.245154 -0.8869850 -8.9900e-01 -9.8013e-02 1.1983e-01 199s [77,] -8.169236 -1.599780 1.4987144 3.7767e-01 2.4726e-01 3.8246e-01 199s [78,] 1.096654 1.646072 0.0591327 -3.3138e-01 -1.7936e-01 6.2716e-02 199s [79,] -0.289199 0.625796 -0.3974294 -6.6099e-01 -2.0857e-01 2.1190e-01 199s [80,] -3.160557 -2.282579 0.3255355 4.6181e-01 2.7753e-01 -1.5673e-01 199s [81,] 1.284356 -0.548854 -0.2907281 2.4017e-01 -2.5254e-01 -1.4289e-03 199s [82,] 2.562817 2.019485 0.8249162 3.2973e-01 3.3866e-01 1.3889e-01 199s [83,] 2.538825 0.759863 -0.3142506 -5.1028e-01 -2.0539e-01 8.8979e-02 199s [84,] 0.841123 0.110035 -1.5793120 -1.2807e+00 1.2332e-01 1.6224e-01 199s [85,] 0.636271 1.793014 2.6824860 1.0329e+00 -4.8850e-01 -2.3012e-01 199s [86,] 0.633183 -0.426511 -1.4791366 -6.1314e-01 -7.0534e-02 -2.3778e-01 199s PC7 PC8 199s [1,] 1.0196e-01 -1.7180e-03 199s [2,] 2.6131e-01 -8.5191e-03 199s [3,] 6.9637e-01 -8.0573e-03 199s [4,] -1.3548e-01 -1.4969e-03 199s [5,] 3.1443e-02 -2.7307e-03 199s [6,] -2.5079e-01 3.6450e-03 199s [7,] 4.5377e-02 -2.6071e-03 199s [8,] -1.6060e-01 -2.3761e-04 199s [9,] -1.5152e-01 -4.3079e-04 199s [10,] 9.1089e-02 1.9536e-03 199s [11,] 2.5654e-01 -1.4875e-03 199s [12,] -2.3798e-03 -1.0954e-04 199s [13,] -1.3687e-01 2.8402e-03 199s [14,] -6.5248e-02 -1.5114e-03 199s [15,] 3.7695e-02 -2.7827e-03 199s [16,] 3.8131e-01 -3.7990e-03 199s [17,] 4.5661e-02 -1.4965e-03 199s [18,] 3.9910e-01 -7.2703e-03 199s [19,] 2.9353e-01 -3.3342e-03 199s [20,] 6.0915e-01 -6.0837e-03 199s [21,] -1.0079e-01 1.0179e-03 199s [22,] -2.2945e-02 -1.0515e-03 199s [23,] 2.3631e-01 -2.5558e-03 199s [24,] -7.7207e-02 3.4800e-03 199s [25,] 1.4903e-02 -3.2430e-04 199s [26,] 3.8032e-03 -2.1705e-03 199s [27,] 3.7208e-02 -3.0631e-03 199s [28,] -4.8147e-01 6.1089e-03 199s [29,] -4.0388e-02 2.8549e-03 199s [30,] 3.4318e-02 -1.0014e-03 199s [31,] -2.2872e-02 1.8706e-03 199s [32,] -8.4542e-02 1.3368e-03 199s [33,] 4.5274e-02 5.3383e-04 199s [34,] -2.0048e-01 2.4727e-03 199s [35,] -5.6482e-02 2.9923e-03 199s [36,] -2.6046e-02 -1.2910e-03 199s [37,] 9.6038e-02 -1.8897e-03 199s [38,] -2.9035e-01 4.4317e-03 199s [39,] -4.6322e-03 2.4336e-03 199s [40,] 3.8686e-01 -3.9300e-03 199s [41,] 3.7834e-01 -7.8976e-03 199s [42,] -8.2037e-04 -4.3106e-05 199s [43,] 3.3467e-01 -5.2401e-03 199s [44,] -6.2170e-01 1.2840e-02 199s [45,] 5.3557e-02 2.9156e-03 199s [46,] 5.1785e-04 2.0738e-03 199s [47,] -5.2141e-01 5.7206e-03 199s [48,] -2.7669e-01 6.7329e-03 199s [49,] 8.4319e-02 3.8528e-03 199s [50,] 1.4210e-01 1.6961e-04 199s [51,] -1.1871e-01 2.6676e-03 199s [52,] -2.5036e-01 6.4121e-03 199s [53,] 2.2399e-01 -2.8200e-03 199s [54,] 5.6532e-02 4.9304e-04 199s [55,] -1.4343e-01 1.2558e-03 199s [56,] 4.1682e-02 -9.6490e-04 199s [57,] -1.3014e-01 -6.2709e-04 199s [58,] -2.1428e-01 8.2594e-04 199s [59,] -7.9775e-02 -8.9776e-04 199s [60,] -8.6835e-02 -1.0498e-03 199s [61,] 6.2470e-02 -2.7499e-03 199s [62,] 3.3052e-02 -3.2369e-04 199s [63,] -1.7137e-01 -3.1087e-04 199s [64,] -1.7137e-01 -3.1087e-04 199s [65,] -1.4435e-14 -1.8299e-12 199s [66,] -2.2016e-02 -1.2206e-03 199s [67,] 8.5160e-02 -1.4837e-04 199s [68,] -2.2535e-03 1.9054e-04 199s [69,] 5.9976e-02 -8.6961e-04 199s [70,] 1.0448e+00 -2.0167e-02 199s [71,] -1.7609e-01 1.9378e-03 199s [72,] -1.7047e-01 2.6076e-04 199s [73,] 1.1885e-01 -8.1624e-04 199s [74,] 2.0942e-01 3.3164e-03 199s [75,] -7.7528e-01 9.9316e-03 199s [76,] -4.6285e-03 2.5153e-04 199s [77,] 7.0218e-02 1.5708e-03 199s [78,] -1.4859e-02 -6.7049e-04 199s [79,] 5.1054e-02 -2.0198e-03 199s [80,] -1.5770e-01 4.9579e-03 199s [81,] -1.9411e-01 4.4401e-04 199s [82,] 6.0634e-02 8.7960e-04 199s [83,] -4.4635e-02 -1.7048e-03 199s [84,] -2.3612e-03 -2.2242e-04 199s [85,] -5.5171e-02 -1.1222e-03 199s [86,] -1.4972e-01 1.4543e-03 199s ------------- 199s Call: 199s PcaProj(x = x) 199s 199s Standard deviations: 199s [1] 2.8929930 1.8789522 0.9946460 0.7479403 0.3744197 0.2596328 0.1421387 199s [8] 0.0025753 199s ---------------------------------------------------------- 199s bushfire 38 5 5 37473.439646 1742.633018 199s Scores: 199s PC1 PC2 PC3 PC4 PC5 199s [1,] -67.2152 -2.3010e+01 4.4179e+00 1.0892e+00 1.7536e+00 199s [2,] -69.0225 -2.1417e+01 2.5382e+00 1.1092e+00 9.3919e-01 199s [3,] -61.6651 -1.8580e+01 -6.1022e-01 -8.1124e-01 -1.6462e-01 199s [4,] -44.5883 -1.8234e+01 -3.9899e-01 -5.2145e-01 2.0050e-01 199s [5,] -12.2941 -2.2954e+01 3.5970e+00 1.1037e+00 -2.4384e-01 199s [6,] 13.0282 -2.8133e+01 8.7670e+00 3.4751e+00 1.3728e+00 199s [7,] -199.0774 -7.7956e+01 5.4935e+01 6.3134e+00 -1.9919e+00 199s [8,] -228.2849 -1.3258e+02 2.2340e+01 2.1656e+01 -1.2594e+01 199s [9,] -228.9164 -1.3560e+02 2.0463e+01 2.2625e+01 -1.2743e+01 199s [10,] -232.4703 -1.0661e+02 3.5597e+01 1.7915e+01 -7.7659e+00 199s [11,] -236.7410 -8.8072e+01 3.6632e+01 1.5095e+01 -7.4695e+00 199s [12,] -249.4091 -3.6830e+01 2.4010e+01 4.7317e+00 -1.2986e+00 199s [13,] -197.0450 2.3179e-14 2.4481e-14 -1.1772e-13 -5.9580e-13 199s [14,] 50.9487 1.1397e+01 -1.1247e+01 -4.8733e+00 2.4511e+00 199s [15,] 180.7896 1.7571e+01 -8.0454e+00 -1.0582e+01 1.2714e+00 199s [16,] 135.6178 1.4189e+01 -4.9116e-01 -9.2701e+00 1.4021e-01 199s [17,] 132.5344 1.5577e+01 2.2990e-01 -6.4963e+00 7.3370e-01 199s [18,] 121.3422 1.0471e+01 4.5656e+00 -4.9831e+00 -5.2314e-01 199s [19,] 125.2722 9.0272e+00 3.7365e+00 -3.3313e+00 -2.9097e-01 199s [20,] 135.2370 1.4091e+01 2.0639e+00 -3.6800e+00 1.1733e+00 199s [21,] 116.4250 1.5147e+01 2.9085e+00 -4.8084e+00 1.2603e+00 199s [22,] 108.2925 1.4223e+01 7.7165e-01 -4.5065e+00 2.7943e+00 199s [23,] -22.8258 6.4234e+00 2.4654e+00 -3.9627e+00 7.9847e-01 199s [24,] -78.1850 4.6631e+00 -3.6818e+00 -2.7688e+00 5.8508e-01 199s [25,] -13.0417 2.7521e+00 -3.1955e+00 -4.6824e+00 -3.1085e-01 199s [26,] -19.1244 -9.5045e-01 -2.6771e+00 -4.7104e+00 -1.6172e-01 199s [27,] -34.4379 3.2761e+00 -9.2826e+00 -2.9861e+00 -3.3561e-01 199s [28,] -11.5852 1.4506e+01 -1.5649e+01 -1.6260e+00 -8.5347e-01 199s [29,] -2.9366 2.8741e+01 -2.2907e+01 3.9749e-01 3.5861e-02 199s [30,] -59.7518 2.8633e+01 -1.4710e+01 3.5226e+00 -9.9066e-01 199s [31,] 67.8017 4.7241e+01 -9.1255e+00 1.3201e+01 6.9227e-14 199s [32,] 321.9941 7.6188e+01 2.2491e+01 3.1537e+01 3.2368e+00 199s [33,] 359.5155 6.6710e+01 5.6061e+01 3.4541e+01 2.0718e+00 199s [34,] 355.8007 6.5695e+01 5.7430e+01 3.3578e+01 1.4640e+00 199s [35,] 361.1076 6.7577e+01 5.7402e+01 3.3832e+01 3.2618e+00 199s [36,] 358.3592 6.6791e+01 5.8643e+01 3.2720e+01 1.2487e+00 199s [37,] 355.9974 6.8071e+01 6.0927e+01 3.2560e+01 2.4898e+00 199s [38,] 357.2530 6.9073e+01 6.1517e+01 3.2523e+01 2.7558e+00 199s ------------- 199s Call: 199s PcaProj(x = x) 199s 199s Standard deviations: 199s [1] 193.5806 41.7449 16.7665 8.1585 1.6074 199s ---------------------------------------------------------- 199s ========================================================== 199s > ## IGNORE_RDIFF_END 199s > 199s > ## VT::14.11.2018 - commented out - on some platforms PcaHubert will choose only 1 PC 199s > ## and will show difference 199s > ## test.case.1() 199s > 199s > test.case.2() 199s [1] TRUE 199s [1] TRUE 199s [1] TRUE 199s [1] TRUE 199s [1] TRUE 199s [1] TRUE 199s [1] TRUE 199s [1] TRUE 199s [1] TRUE 199s [1] TRUE 199s > 199s BEGIN TEST tlda.R 199s 199s R version 4.3.3 (2024-02-29) -- "Angel Food Cake" 199s Copyright (C) 2024 The R Foundation for Statistical Computing 199s Platform: aarch64-unknown-linux-gnu (64-bit) 199s 199s R is free software and comes with ABSOLUTELY NO WARRANTY. 199s You are welcome to redistribute it under certain conditions. 199s Type 'license()' or 'licence()' for distribution details. 199s 199s R is a collaborative project with many contributors. 199s Type 'contributors()' for more information and 199s 'citation()' on how to cite R or R packages in publications. 199s 199s Type 'demo()' for some demos, 'help()' for on-line help, or 199s 'help.start()' for an HTML browser interface to help. 199s Type 'q()' to quit R. 199s 199s > ## VT::15.09.2013 - this will render the output independent 199s > ## from the version of the package 199s > suppressPackageStartupMessages(library(rrcov)) 200s > library(MASS) 200s > 200s > ## VT::14.01.2020 200s > ## On some platforms minor differences are shown - use 200s > ## IGNORE_RDIFF_BEGIN 200s > ## IGNORE_RDIFF_END 200s > 200s > dodata <- function(method) { 200s + 200s + options(digits = 5) 200s + set.seed(101) # <<-- sub-sampling algorithm now based on R's RNG and seed 200s + 200s + tmp <- sys.call() 200s + cat("\nCall: ", deparse(substitute(tmp)),"\n") 200s + cat("===================================================\n") 200s + 200s + cat("\nData: ", "hemophilia\n") 200s + data(hemophilia) 200s + show(rlda <- Linda(as.factor(gr)~., data=hemophilia, method=method)) 200s + show(predict(rlda)) 200s + 200s + cat("\nData: ", "anorexia\n") 200s + data(anorexia) 200s + show(rlda <- Linda(Treat~., data=anorexia, method=method)) 200s + show(predict(rlda)) 200s + 200s + cat("\nData: ", "Pima\n") 200s + data(Pima.tr) 200s + show(rlda <- Linda(type~., data=Pima.tr, method=method)) 200s + show(predict(rlda)) 200s + 200s + cat("\nData: ", "Forest soils\n") 200s + data(soil) 200s + soil1983 <- soil[soil$D == 0, -2] # only 1983, remove column D (always 0) 200s + 200s + ## This will not work within the function, of course 200s + ## - comment it out 200s + ## IGNORE_RDIFF_BEGIN 200s + rlda <- Linda(F~., data=soil1983, method=method) 200s + ## show(rlda) 200s + ## IGNORE_RDIFF_END 200s + show(predict(rlda)) 200s + 200s + cat("\nData: ", "Raven and Miller diabetes data\n") 200s + data(diabetes) 200s + show(rlda <- Linda(group~insulin+glucose+sspg, data=diabetes, method=method)) 200s + show(predict(rlda)) 200s + 200s + cat("\nData: ", "iris\n") 200s + data(iris) 200s + if(method != "mcdA") 200s + { 200s + show(rlda <- Linda(Species~., data=iris, method=method, l1med=TRUE)) 200s + show(predict(rlda)) 200s + } 200s + 200s + cat("\nData: ", "crabs\n") 200s + data(crabs) 200s + show(rlda <- Linda(sp~., data=crabs, method=method)) 200s + show(predict(rlda)) 200s + 200s + cat("\nData: ", "fish\n") 200s + data(fish) 200s + fish <- fish[-14,] # remove observation #14 containing missing value 200s + 200s + # The height and width are calculated as percentages 200s + # of the third length variable 200s + fish[,5] <- fish[,5]*fish[,4]/100 200s + fish[,6] <- fish[,6]*fish[,4]/100 200s + 200s + ## There is one class with only 6 observations (p=6). Normally 200s + ## Linda will fail, therefore use l1med=TRUE. 200s + ## This works only for methods mcdB and mcdC 200s + 200s + table(fish$Species) 200s + if(method != "mcdA") 200s + { 200s + ## IGNORE_RDIFF_BEGIN 200s + rlda <- Linda(Species~., data=fish, method=method, l1med=TRUE) 200s + ## show(rlda) 200s + ## IGNORE_RDIFF_END 200s + show(predict(rlda)) 200s + } 200s + 200s + cat("\nData: ", "pottery\n") 200s + data(pottery) 200s + show(rlda <- Linda(origin~., data=pottery, method=method)) 200s + show(predict(rlda)) 200s + 200s + cat("\nData: ", "olitos\n") 200s + data(olitos) 200s + if(method != "mcdA") 200s + { 200s + ## IGNORE_RDIFF_BEGIN 200s + rlda <- Linda(grp~., data=olitos, method=method, l1med=TRUE) 200s + ## show(rlda) 200s + ## IGNORE_RDIFF_END 200s + show(predict(rlda)) 200s + } 200s + 200s + cat("===================================================\n") 200s + } 200s > 200s > 200s > ## -- now do it: 200s > dodata(method="mcdA") 200s 200s Call: dodata(method = "mcdA") 200s =================================================== 200s 200s Data: hemophilia 200s Call: 200s Linda(as.factor(gr) ~ ., data = hemophilia, method = method) 200s 200s Prior Probabilities of Groups: 200s carrier normal 200s 0.6 0.4 200s 200s Group means: 200s AHFactivity AHFantigen 200s carrier -0.30795 -0.0059911 200s normal -0.12920 -0.0603000 200s 200s Within-groups Covariance Matrix: 200s AHFactivity AHFantigen 200s AHFactivity 0.018036 0.011853 200s AHFantigen 0.011853 0.019185 200s 200s Linear Coeficients: 200s AHFactivity AHFantigen 200s carrier -28.4029 17.2368 200s normal -8.5834 2.1602 200s 200s Constants: 200s carrier normal 200s -4.8325 -1.4056 200s 200s Apparent error rate 0.1333 200s 200s Classification table 200s Predicted 200s Actual carrier normal 200s carrier 39 6 200s normal 4 26 200s 200s Confusion matrix 200s Predicted 200s Actual carrier normal 200s carrier 0.867 0.133 200s normal 0.133 0.867 200s 200s Data: anorexia 200s Call: 200s Linda(Treat ~ ., data = anorexia, method = method) 200s 200s Prior Probabilities of Groups: 200s CBT Cont FT 200s 0.40278 0.36111 0.23611 200s 200s Group means: 200s Prewt Postwt 200s CBT 82.633 82.950 200s Cont 81.558 81.108 200s FT 84.331 94.762 200s 200s Within-groups Covariance Matrix: 200s Prewt Postwt 200s Prewt 26.9291 3.3862 200s Postwt 3.3862 18.2368 200s 200s Linear Coeficients: 200s Prewt Postwt 200s CBT 2.5563 4.0738 200s Cont 2.5284 3.9780 200s FT 2.5374 4.7250 200s 200s Constants: 200s CBT Cont FT 200s -275.49 -265.45 -332.31 200s 200s Apparent error rate 0.3889 200s 200s Classification table 200s Predicted 200s Actual CBT Cont FT 200s CBT 16 5 8 200s Cont 11 15 0 200s FT 0 4 13 200s 200s Confusion matrix 200s Predicted 200s Actual CBT Cont FT 200s CBT 0.552 0.172 0.276 200s Cont 0.423 0.577 0.000 200s FT 0.000 0.235 0.765 200s 200s Data: Pima 200s Call: 200s Linda(type ~ ., data = Pima.tr, method = method) 200s 200s Prior Probabilities of Groups: 200s No Yes 200s 0.66 0.34 200s 200s Group means: 200s npreg glu bp skin bmi ped age 200s No 1.8602 107.69 67.344 25.29 30.642 0.40777 24.667 200s Yes 5.3167 145.85 74.283 31.80 34.095 0.49533 37.883 200s 200s Within-groups Covariance Matrix: 200s npreg glu bp skin bmi ped age 200s npreg 8.51105 -5.61029 4.756672 1.52732 0.82066 -0.010070 12.382693 200s glu -5.61029 656.11894 49.855724 16.67486 23.07833 -0.352475 17.724967 200s bp 4.75667 49.85572 119.426757 29.64563 12.90698 -0.049538 21.287178 200s skin 1.52732 16.67486 29.645632 113.19900 44.15972 -0.157594 6.741105 200s bmi 0.82066 23.07833 12.906985 44.15972 35.54164 0.038640 1.481520 200s ped -0.01007 -0.35247 -0.049538 -0.15759 0.03864 0.062664 -0.069636 200s age 12.38269 17.72497 21.287178 6.74110 1.48152 -0.069636 64.887154 200s 200s Linear Coeficients: 200s npreg glu bp skin bmi ped age 200s No -0.45855 0.092789 0.45848 -0.30675 1.0075 6.2670 0.30749 200s Yes -0.22400 0.150013 0.44787 -0.26148 1.0015 8.2935 0.45187 200s 200s Constants: 200s No Yes 200s -37.050 -51.586 200s 200s Apparent error rate 0.22 200s 200s Classification table 200s Predicted 200s Actual No Yes 200s No 107 25 200s Yes 19 49 200s 200s Confusion matrix 200s Predicted 200s Actual No Yes 200s No 0.811 0.189 200s Yes 0.279 0.721 200s 200s Data: Forest soils 200s 200s Apparent error rate 0.3103 200s 200s Classification table 200s Predicted 200s Actual 1 2 3 200s 1 7 2 2 200s 2 3 13 7 200s 3 1 3 20 200s 200s Confusion matrix 200s Predicted 200s Actual 1 2 3 200s 1 0.636 0.182 0.182 200s 2 0.130 0.565 0.304 200s 3 0.042 0.125 0.833 200s 200s Data: Raven and Miller diabetes data 200s Call: 200s Linda(group ~ insulin + glucose + sspg, data = diabetes, method = method) 200s 200s Prior Probabilities of Groups: 200s normal chemical overt 200s 0.52414 0.24828 0.22759 200s 200s Group means: 200s insulin glucose sspg 200s normal 163.939 345.8 99.076 200s chemical 299.448 476.9 223.621 200s overt 95.958 1026.4 343.000 200s 200s Within-groups Covariance Matrix: 200s insulin glucose sspg 200s insulin 7582.0 -1263.1 1095.8 200s glucose -1263.1 18952.4 4919.3 200s sspg 1095.8 4919.3 3351.2 200s 200s Linear Coeficients: 200s insulin glucose sspg 200s normal 0.027694 0.023859 -0.014514 200s chemical 0.040288 0.022532 0.020479 200s overt 0.017144 0.048768 0.025158 200s 200s Constants: 200s normal chemical overt 200s -6.3223 -15.0879 -31.6445 200s 200s Apparent error rate 0.1862 200s 200s Classification table 200s Predicted 200s Actual normal chemical overt 200s normal 69 7 0 200s chemical 13 23 0 200s overt 2 5 26 200s 200s Confusion matrix 200s Predicted 200s Actual normal chemical overt 200s normal 0.908 0.092 0.000 200s chemical 0.361 0.639 0.000 200s overt 0.061 0.152 0.788 200s 200s Data: iris 200s 200s Data: crabs 200s Call: 200s Linda(sp ~ ., data = crabs, method = method) 200s 200s Prior Probabilities of Groups: 200s B O 200s 0.5 0.5 200s 200s Group means: 200s sexM index FL RW CL CW BD 200s B 0.34722 27.333 14.211 12.253 30.397 35.117 12.765 200s O 0.56627 25.554 17.131 13.405 34.247 38.155 15.525 200s 200s Within-groups Covariance Matrix: 200s sexM index FL RW CL CW BD 200s sexM 0.26391 0.76754 0.18606 -0.33763 0.65944 0.59857 0.28932 200s index 0.76754 191.38080 38.42685 26.32923 82.43953 91.89091 38.13688 200s FL 0.18606 38.42685 8.50147 5.68789 18.13749 20.30739 8.30920 200s RW -0.33763 26.32923 5.68789 4.95782 11.90225 13.61117 5.45814 200s CL 0.65944 82.43953 18.13749 11.90225 39.60115 44.10886 18.09504 200s CW 0.59857 91.89091 20.30739 13.61117 44.10886 49.42616 20.17554 200s BD 0.28932 38.13688 8.30920 5.45814 18.09504 20.17554 8.39525 200s 200s Linear Coeficients: 200s sexM index FL RW CL CW BD 200s B 29.104 -2.4938 10.809 15.613 0.8320 -4.2978 -0.46788 200s O 42.470 -3.9361 26.427 22.857 2.8582 -17.1526 12.31048 200s 200s Constants: 200s B O 200s -78.317 -159.259 200s 200s Apparent error rate 0 200s 200s Classification table 200s Predicted 200s Actual B O 200s B 100 0 200s O 0 100 200s 200s Confusion matrix 200s Predicted 200s Actual B O 200s B 1 0 200s O 0 1 200s 200s Data: fish 200s 200s Data: pottery 200s Call: 200s Linda(origin ~ ., data = pottery, method = method) 200s 200s Prior Probabilities of Groups: 200s Attic Eritrean 200s 0.48148 0.51852 200s 200s Group means: 200s SI AL FE MG CA TI 200s Attic 55.36 13.73 9.82 5.45 6.03 0.863 200s Eritrean 52.52 16.23 9.13 3.09 6.26 0.814 200s 200s Within-groups Covariance Matrix: 200s SI AL FE MG CA TI 200s SI 13.5941404 2.986675 -0.651132 0.173577 -0.350984 -0.0051996 200s AL 2.9866747 1.622412 0.485167 0.712400 0.077443 0.0133306 200s FE -0.6511317 0.485167 1.065427 -0.403601 -1.936552 0.0576472 200s MG 0.1735766 0.712400 -0.403601 2.814948 3.262786 -0.0427129 200s CA -0.3509837 0.077443 -1.936552 3.262786 7.720320 -0.1454065 200s TI -0.0051996 0.013331 0.057647 -0.042713 -0.145406 0.0044093 200s 200s Linear Coeficients: 200s SI AL FE MG CA TI 200s Attic 63.235 -196.99 312.92 7.28960 57.082 -1272.23 200s Eritrean 41.554 -123.49 201.47 -0.95431 43.616 -597.91 200s 200s Constants: 200s Attic Eritrean 200s -1578.14 -901.13 200s 200s Apparent error rate 0.1111 200s 200s Classification table 200s Predicted 200s Actual Attic Eritrean 200s Attic 12 1 200s Eritrean 2 12 200s 200s Confusion matrix 200s Predicted 200s Actual Attic Eritrean 200s Attic 0.923 0.077 200s Eritrean 0.143 0.857 200s 200s Data: olitos 200s =================================================== 200s > dodata(method="mcdB") 200s 200s Call: dodata(method = "mcdB") 200s =================================================== 200s 200s Data: hemophilia 200s Call: 200s Linda(as.factor(gr) ~ ., data = hemophilia, method = method) 200s 200s Prior Probabilities of Groups: 200s carrier normal 200s 0.6 0.4 200s 200s Group means: 200s AHFactivity AHFantigen 200s carrier -0.31456 -0.014775 200s normal -0.13582 -0.069084 200s 200s Within-groups Covariance Matrix: 200s AHFactivity AHFantigen 200s AHFactivity 0.0125319 0.0086509 200s AHFantigen 0.0086509 0.0182424 200s 200s Linear Coeficients: 200s AHFactivity AHFantigen 200s carrier -36.486 16.4923 200s normal -12.226 2.0107 200s 200s Constants: 200s carrier normal 200s -6.1276 -1.6771 200s 200s Apparent error rate 0.16 200s 200s Classification table 200s Predicted 200s Actual carrier normal 200s carrier 38 7 200s normal 5 25 200s 200s Confusion matrix 200s Predicted 200s Actual carrier normal 200s carrier 0.844 0.156 200s normal 0.167 0.833 200s 200s Data: anorexia 200s Call: 200s Linda(Treat ~ ., data = anorexia, method = method) 200s 200s Prior Probabilities of Groups: 200s CBT Cont FT 200s 0.40278 0.36111 0.23611 200s 200s Group means: 200s Prewt Postwt 200s CBT 83.254 82.381 200s Cont 82.178 80.539 200s FT 84.951 94.193 200s 200s Within-groups Covariance Matrix: 200s Prewt Postwt 200s Prewt 19.1751 8.8546 200s Postwt 8.8546 25.2326 200s 200s Linear Coeficients: 200s Prewt Postwt 200s CBT 3.3822 2.0780 200s Cont 3.3555 2.0144 200s FT 3.2299 2.5996 200s 200s Constants: 200s CBT Cont FT 200s -227.29 -220.01 -261.06 200s 200s Apparent error rate 0.4444 200s 200s Classification table 200s Predicted 200s Actual CBT Cont FT 200s CBT 16 5 8 200s Cont 12 11 3 200s FT 0 4 13 200s 200s Confusion matrix 200s Predicted 200s Actual CBT Cont FT 200s CBT 0.552 0.172 0.276 200s Cont 0.462 0.423 0.115 200s FT 0.000 0.235 0.765 200s 200s Data: Pima 200s Call: 200s Linda(type ~ ., data = Pima.tr, method = method) 200s 200s Prior Probabilities of Groups: 200s No Yes 200s 0.66 0.34 200s 200s Group means: 200s npreg glu bp skin bmi ped age 200s No 2.0767 109.45 67.790 26.158 30.930 0.41455 24.695 200s Yes 5.5938 145.40 74.748 33.754 34.501 0.49898 37.821 200s 200s Within-groups Covariance Matrix: 200s npreg glu bp skin bmi ped age 200s npreg 6.601330 9.54054 7.33480 3.5803 1.66539 -0.019992 10.661763 200s glu 9.540535 573.03642 60.57124 28.3698 30.28444 -0.436611 28.318034 200s bp 7.334803 60.57124 112.03792 27.7566 13.54085 -0.040510 24.692240 200s skin 3.580339 28.36976 27.75661 112.0036 47.22411 0.100399 13.408195 200s bmi 1.665393 30.28444 13.54085 47.2241 38.37753 0.175891 6.640765 200s ped -0.019992 -0.43661 -0.04051 0.1004 0.17589 0.062551 -0.070673 200s age 10.661763 28.31803 24.69224 13.4082 6.64077 -0.070673 40.492363 200s 200s Linear Coeficients: 200s npreg glu bp skin bmi ped age 200s No -1.3073 0.10851 0.48404 -0.30638 0.86002 5.9796 0.55388 200s Yes -1.3136 0.16260 0.44480 -0.25518 0.79826 8.1199 0.86269 200s 200s Constants: 200s No Yes 200s -38.774 -53.654 200s 200s Apparent error rate 0.25 200s 200s Classification table 200s Predicted 200s Actual No Yes 200s No 104 28 200s Yes 22 46 200s 200s Confusion matrix 200s Predicted 200s Actual No Yes 200s No 0.788 0.212 200s Yes 0.324 0.676 200s 200s Data: Forest soils 200s 200s Apparent error rate 0.3448 200s 200s Classification table 200s Predicted 200s Actual 1 2 3 200s 1 4 3 4 200s 2 2 14 7 200s 3 2 2 20 200s 200s Confusion matrix 200s Predicted 200s Actual 1 2 3 200s 1 0.364 0.273 0.364 200s 2 0.087 0.609 0.304 200s 3 0.083 0.083 0.833 200s 200s Data: Raven and Miller diabetes data 200s Call: 200s Linda(group ~ insulin + glucose + sspg, data = diabetes, method = method) 200s 200s Prior Probabilities of Groups: 200s normal chemical overt 200s 0.52414 0.24828 0.22759 200s 200s Group means: 200s insulin glucose sspg 200s normal 152.405 346.55 99.387 200s chemical 288.244 478.80 226.226 200s overt 84.754 1028.28 345.605 200s 200s Within-groups Covariance Matrix: 200s insulin glucose sspg 200s insulin 5061.46 289.69 2071.71 200s glucose 289.69 1983.07 385.31 200s sspg 2071.71 385.31 3000.17 200s 200s Linear Coeficients: 200s insulin glucose sspg 200s normal 0.021952 0.17236 -0.0041671 200s chemical 0.034852 0.23217 0.0215200 200s overt -0.045700 0.50940 0.0813292 200s 200s Constants: 200s normal chemical overt 200s -31.976 -64.433 -275.502 200s 200s Apparent error rate 0.0966 200s 200s Classification table 200s Predicted 200s Actual normal chemical overt 200s normal 73 3 0 200s chemical 4 32 0 200s overt 0 7 26 200s 200s Confusion matrix 200s Predicted 200s Actual normal chemical overt 200s normal 0.961 0.039 0.000 200s chemical 0.111 0.889 0.000 200s overt 0.000 0.212 0.788 200s 200s Data: iris 200s Call: 200s Linda(Species ~ ., data = iris, method = method, l1med = TRUE) 200s 200s Prior Probabilities of Groups: 200s setosa versicolor virginica 200s 0.33333 0.33333 0.33333 200s 200s Group means: 200s Sepal.Length Sepal.Width Petal.Length Petal.Width 200s setosa 4.9834 3.4153 1.4532 0.22474 200s versicolor 5.8947 2.8149 4.2263 1.35024 200s virginica 6.5255 3.0017 5.4485 2.06756 200s 200s Within-groups Covariance Matrix: 200s Sepal.Length Sepal.Width Petal.Length Petal.Width 200s Sepal.Length 0.201176 0.084299 0.102984 0.037019 200s Sepal.Width 0.084299 0.108394 0.050253 0.031757 200s Petal.Length 0.102984 0.050253 0.120215 0.045016 200s Petal.Width 0.037019 0.031757 0.045016 0.032825 200s 200s Linear Coeficients: 200s Sepal.Length Sepal.Width Petal.Length Petal.Width 200s setosa 22.536 27.422168 -3.6855 -40.0445 200s versicolor 17.559 6.374082 24.1965 -18.0178 200s virginica 16.488 0.015576 29.9586 3.2926 200s 200s Constants: 200s setosa versicolor virginica 200s -96.901 -100.790 -139.937 200s 200s Apparent error rate 0.0267 200s 200s Classification table 200s Predicted 200s Actual setosa versicolor virginica 200s setosa 50 0 0 200s versicolor 0 48 2 200s virginica 0 2 48 200s 200s Confusion matrix 200s Predicted 200s Actual setosa versicolor virginica 200s setosa 1 0.00 0.00 200s versicolor 0 0.96 0.04 200s virginica 0 0.04 0.96 200s 200s Data: crabs 200s Call: 200s Linda(sp ~ ., data = crabs, method = method) 200s 200s Prior Probabilities of Groups: 200s B O 200s 0.5 0.5 200s 200s Group means: 200s sexM index FL RW CL CW BD 200s B 0.41060 25.420 13.947 11.922 29.783 34.404 12.470 200s O 0.60279 23.202 16.782 13.086 33.401 37.230 15.131 200s 200s Within-groups Covariance Matrix: 200s sexM index FL RW CL CW BD 200s sexM 0.27470 0.24656 0.12787 -0.34713 0.48937 0.41525 0.20253 200s index 0.24656 204.06823 42.17347 28.25816 89.28109 100.21077 40.74069 200s FL 0.12787 42.17347 9.45366 6.24808 19.97936 22.49310 9.03804 200s RW -0.34713 28.25816 6.24808 5.12921 13.01576 14.90535 5.89729 200s CL 0.48937 89.28109 19.97936 13.01576 43.06030 48.30814 19.44568 200s CW 0.41525 100.21077 22.49310 14.90535 48.30814 54.45265 21.82356 200s BD 0.20253 40.74069 9.03804 5.89729 19.44568 21.82356 8.89498 200s 200s Linear Coeficients: 200s sexM index FL RW CL CW BD 200s B 12.295 -2.3199 7.2512 9.4085 2.2846 -2.6196 -0.42557 200s O 13.138 -3.7530 21.1374 11.5680 5.0125 -13.9120 12.61928 200s 200s Constants: 200s B O 200s -66.688 -134.375 200s 200s Apparent error rate 0 200s 200s Classification table 200s Predicted 200s Actual B O 200s B 100 0 200s O 0 100 200s 200s Confusion matrix 200s Predicted 200s Actual B O 200s B 1 0 200s O 0 1 200s 200s Data: fish 200s 200s Apparent error rate 0.0949 200s 200s Classification table 200s Predicted 200s Actual 1 2 3 4 5 6 7 200s 1 34 0 0 0 0 0 0 200s 2 0 6 0 0 0 0 0 200s 3 0 0 20 0 0 0 0 200s 4 0 0 0 11 0 0 0 200s 5 0 0 0 0 13 0 1 200s 6 0 0 0 0 0 17 0 200s 7 0 13 0 0 1 0 42 200s 200s Confusion matrix 200s Predicted 200s Actual 1 2 3 4 5 6 7 200s 1 1 0.000 0 0 0.000 0 0.000 200s 2 0 1.000 0 0 0.000 0 0.000 200s 3 0 0.000 1 0 0.000 0 0.000 200s 4 0 0.000 0 1 0.000 0 0.000 200s 5 0 0.000 0 0 0.929 0 0.071 200s 6 0 0.000 0 0 0.000 1 0.000 200s 7 0 0.232 0 0 0.018 0 0.750 200s 200s Data: pottery 200s Call: 200s Linda(origin ~ ., data = pottery, method = method) 200s 200s Prior Probabilities of Groups: 200s Attic Eritrean 200s 0.48148 0.51852 200s 200s Group means: 200s SI AL FE MG CA TI 200s Attic 55.362 13.847 10.0065 5.3141 5.5371 0.87124 200s Eritrean 52.522 16.347 9.3165 2.9541 5.7671 0.82224 200s 200s Within-groups Covariance Matrix: 200s SI AL FE MG CA TI 200s SI 9.708953 2.3634831 -0.112005 0.514666 -0.591122 0.0253885 200s AL 2.363483 0.8510105 0.044491 0.485132 0.241384 0.0023349 200s FE -0.112005 0.0444910 0.247768 -0.263894 -0.503218 0.0163218 200s MG 0.514666 0.4851316 -0.263894 1.608899 1.516228 -0.0292787 200s CA -0.591122 0.2413842 -0.503218 1.516228 2.455516 -0.0531548 200s TI 0.025389 0.0023349 0.016322 -0.029279 -0.053155 0.0017412 200s 200s Linear Coeficients: 200s SI AL FE MG CA TI 200s Attic 112.705 -368.69 530.54 7.5837 149.60 -927.45 200s Eritrean 77.198 -244.65 366.95 -3.7987 116.88 -260.83 200s 200s Constants: 200s Attic Eritrean 200s -3252.6 -1961.9 200s 200s Apparent error rate 0.1111 200s 200s Classification table 200s Predicted 200s Actual Attic Eritrean 200s Attic 12 1 200s Eritrean 2 12 200s 200s Confusion matrix 200s Predicted 200s Actual Attic Eritrean 200s Attic 0.923 0.077 200s Eritrean 0.143 0.857 200s 200s Data: olitos 201s 201s Apparent error rate 0.15 201s 201s Classification table 201s Predicted 201s Actual 1 2 3 4 201s 1 44 1 4 1 201s 2 2 23 0 0 201s 3 6 1 26 1 201s 4 1 1 0 9 201s 201s Confusion matrix 201s Predicted 201s Actual 1 2 3 4 201s 1 0.880 0.020 0.080 0.020 201s 2 0.080 0.920 0.000 0.000 201s 3 0.176 0.029 0.765 0.029 201s 4 0.091 0.091 0.000 0.818 201s =================================================== 201s > dodata(method="mcdC") 201s 201s Call: dodata(method = "mcdC") 201s =================================================== 201s 201s Data: hemophilia 201s Call: 201s Linda(as.factor(gr) ~ ., data = hemophilia, method = method) 201s 201s Prior Probabilities of Groups: 201s carrier normal 201s 0.6 0.4 201s 201s Group means: 201s AHFactivity AHFantigen 201s carrier -0.32583 -0.011545 201s normal -0.12783 -0.071377 201s 201s Within-groups Covariance Matrix: 201s AHFactivity AHFantigen 201s AHFactivity 0.0120964 0.0075536 201s AHFantigen 0.0075536 0.0164883 201s 201s Linear Coeficients: 201s AHFactivity AHFantigen 201s carrier -37.117 16.30377 201s normal -11.015 0.71742 201s 201s Constants: 201s carrier normal 201s -6.4636 -1.5947 201s 201s Apparent error rate 0.16 201s 201s Classification table 201s Predicted 201s Actual carrier normal 201s carrier 38 7 201s normal 5 25 201s 201s Confusion matrix 201s Predicted 201s Actual carrier normal 201s carrier 0.844 0.156 201s normal 0.167 0.833 201s 201s Data: anorexia 201s Call: 201s Linda(Treat ~ ., data = anorexia, method = method) 201s 201s Prior Probabilities of Groups: 201s CBT Cont FT 201s 0.40278 0.36111 0.23611 201s 201s Group means: 201s Prewt Postwt 201s CBT 82.477 82.073 201s Cont 82.039 80.835 201s FT 85.242 94.750 201s 201s Within-groups Covariance Matrix: 201s Prewt Postwt 201s Prewt 19.6589 8.3891 201s Postwt 8.3891 22.8805 201s 201s Linear Coeficients: 201s Prewt Postwt 201s CBT 3.1590 2.4288 201s Cont 3.1599 2.3743 201s FT 3.0454 3.0245 201s 201s Constants: 201s CBT Cont FT 201s -230.85 -226.60 -274.53 201s 201s Apparent error rate 0.4583 201s 201s Classification table 201s Predicted 201s Actual CBT Cont FT 201s CBT 16 5 8 201s Cont 14 10 2 201s FT 0 4 13 201s 201s Confusion matrix 201s Predicted 201s Actual CBT Cont FT 201s CBT 0.552 0.172 0.276 201s Cont 0.538 0.385 0.077 201s FT 0.000 0.235 0.765 201s 201s Data: Pima 201s Call: 201s Linda(type ~ ., data = Pima.tr, method = method) 201s 201s Prior Probabilities of Groups: 201s No Yes 201s 0.66 0.34 201s 201s Group means: 201s npreg glu bp skin bmi ped age 201s No 2.3056 110.63 67.991 26.444 31.010 0.41653 25.806 201s Yes 5.0444 142.58 74.267 33.067 34.309 0.49422 35.156 201s 201s Within-groups Covariance Matrix: 201s npreg glu bp skin bmi ped age 201s npreg 6.164422 8.43753 6.879286 3.252980 1.54269 -0.020158 9.543745 201s glu 8.437528 542.79578 57.156929 26.218837 28.63494 -0.421819 23.809124 201s bp 6.879286 57.15693 106.687356 26.315526 12.86691 -0.039577 22.992973 201s skin 3.252980 26.21884 26.315526 106.552759 44.95420 0.094311 12.005740 201s bmi 1.542689 28.63494 12.866911 44.954202 36.56262 0.167258 6.112925 201s ped -0.020158 -0.42182 -0.039577 0.094311 0.16726 0.059609 -0.072712 201s age 9.543745 23.80912 22.992973 12.005740 6.11292 -0.072712 35.594886 201s 201s Linear Coeficients: 201s npreg glu bp skin bmi ped age 201s No -1.4165 0.11776 0.49336 -0.31564 0.88761 6.5013 0.67462 201s Yes -1.3784 0.17062 0.46662 -0.26771 0.83745 8.5204 0.90557 201s 201s Constants: 201s No Yes 201s -41.716 -55.056 201s 201s Apparent error rate 0.235 201s 201s Classification table 201s Predicted 201s Actual No Yes 201s No 107 25 201s Yes 22 46 201s 201s Confusion matrix 201s Predicted 201s Actual No Yes 201s No 0.811 0.189 201s Yes 0.324 0.676 201s 201s Data: Forest soils 201s 201s Apparent error rate 0.3276 201s 201s Classification table 201s Predicted 201s Actual 1 2 3 201s 1 5 2 4 201s 2 2 13 8 201s 3 1 2 21 201s 201s Confusion matrix 201s Predicted 201s Actual 1 2 3 201s 1 0.455 0.182 0.364 201s 2 0.087 0.565 0.348 201s 3 0.042 0.083 0.875 201s 201s Data: Raven and Miller diabetes data 201s Call: 201s Linda(group ~ insulin + glucose + sspg, data = diabetes, method = method) 201s 201s Prior Probabilities of Groups: 201s normal chemical overt 201s 0.52414 0.24828 0.22759 201s 201s Group means: 201s insulin glucose sspg 201s normal 167.31 348.69 106.44 201s chemical 247.18 478.18 213.36 201s overt 101.83 932.92 322.42 201s 201s Within-groups Covariance Matrix: 201s insulin glucose sspg 201s insulin 4070.84 118.89 1701.54 201s glucose 118.89 2195.95 426.95 201s sspg 1701.54 426.95 2664.49 201s 201s Linear Coeficients: 201s insulin glucose sspg 201s normal 0.041471 0.15888 -0.011992 201s chemical 0.048103 0.21216 0.015359 201s overt -0.013579 0.41323 0.063462 201s 201s Constants: 201s normal chemical overt 201s -31.177 -59.703 -203.775 201s 201s Apparent error rate 0.0828 201s 201s Classification table 201s Predicted 201s Actual normal chemical overt 201s normal 72 4 0 201s chemical 2 34 0 201s overt 0 6 27 201s 201s Confusion matrix 201s Predicted 201s Actual normal chemical overt 201s normal 0.947 0.053 0.000 201s chemical 0.056 0.944 0.000 201s overt 0.000 0.182 0.818 201s 201s Data: iris 201s Call: 201s Linda(Species ~ ., data = iris, method = method, l1med = TRUE) 201s 201s Prior Probabilities of Groups: 201s setosa versicolor virginica 201s 0.33333 0.33333 0.33333 201s 201s Group means: 201s Sepal.Length Sepal.Width Petal.Length Petal.Width 201s setosa 5.0163 3.4510 1.4653 0.2449 201s versicolor 5.9435 2.7891 4.2543 1.3239 201s virginica 6.3867 3.0033 5.3767 2.0700 201s 201s Within-groups Covariance Matrix: 201s Sepal.Length Sepal.Width Petal.Length Petal.Width 201s Sepal.Length 0.186186 0.082478 0.094998 0.035445 201s Sepal.Width 0.082478 0.100137 0.049723 0.030678 201s Petal.Length 0.094998 0.049723 0.113105 0.043078 201s Petal.Width 0.035445 0.030678 0.043078 0.030885 201s 201s Linear Coeficients: 201s Sepal.Length Sepal.Width Petal.Length Petal.Width 201s setosa 23.678 30.2896 -3.1124 -44.9900 201s versicolor 20.342 4.6372 27.3265 -23.2006 201s virginica 18.377 -2.0004 31.4235 4.0906 201s 201s Constants: 201s setosa versicolor virginica 201s -104.96 -110.79 -145.49 201s 201s Apparent error rate 0.0333 201s 201s Classification table 201s Predicted 201s Actual setosa versicolor virginica 201s setosa 50 0 0 201s versicolor 0 48 2 201s virginica 0 3 47 201s 201s Confusion matrix 201s Predicted 201s Actual setosa versicolor virginica 201s setosa 1 0.00 0.00 201s versicolor 0 0.96 0.04 201s virginica 0 0.06 0.94 201s 201s Data: crabs 201s Call: 201s Linda(sp ~ ., data = crabs, method = method) 201s 201s Prior Probabilities of Groups: 201s B O 201s 0.5 0.5 201s 201s Group means: 201s sexM index FL RW CL CW BD 201s B 0.50000 23.956 13.790 11.649 29.390 33.934 12.274 201s O 0.51087 24.478 16.903 13.330 33.707 37.595 15.276 201s 201s Within-groups Covariance Matrix: 201s sexM index FL RW CL CW BD 201s sexM 0.25272 0.39179 0.14054 -0.30017 0.51191 0.45114 0.21708 201s index 0.39179 192.47099 39.97343 26.56698 84.63152 94.99987 38.67917 201s FL 0.14054 39.97343 8.97950 5.91408 18.98672 21.38046 8.60313 201s RW -0.30017 26.56698 5.91408 4.81389 12.31798 14.10613 5.58933 201s CL 0.51191 84.63152 18.98672 12.31798 40.94109 45.94330 18.52367 201s CW 0.45114 94.99987 21.38046 14.10613 45.94330 51.80106 20.79704 201s BD 0.21708 38.67917 8.60313 5.58933 18.52367 20.79704 8.49355 201s 201s Linear Coeficients: 201s sexM index FL RW CL CW BD 201s B 13.993 -2.5515 9.152 9.9187 2.2321 -2.9774 -0.66797 201s O 14.362 -4.0280 23.369 12.1556 5.3672 -14.9236 12.94057 201s 201s Constants: 201s B O 201s -72.687 -142.365 201s 201s Apparent error rate 0 201s 201s Classification table 201s Predicted 201s Actual B O 201s B 100 0 201s O 0 100 201s 201s Confusion matrix 201s Predicted 201s Actual B O 201s B 1 0 201s O 0 1 201s 201s Data: fish 201s 201s Apparent error rate 0.0316 201s 201s Classification table 201s Predicted 201s Actual 1 2 3 4 5 6 7 201s 1 34 0 0 0 0 0 0 201s 2 0 5 0 0 1 0 0 201s 3 0 0 20 0 0 0 0 201s 4 0 0 0 11 0 0 0 201s 5 0 0 0 0 13 0 1 201s 6 0 0 0 0 0 17 0 201s 7 0 0 0 0 3 0 53 201s 201s Confusion matrix 201s Predicted 201s Actual 1 2 3 4 5 6 7 201s 1 1 0.000 0 0 0.000 0 0.000 201s 2 0 0.833 0 0 0.167 0 0.000 201s 3 0 0.000 1 0 0.000 0 0.000 201s 4 0 0.000 0 1 0.000 0 0.000 201s 5 0 0.000 0 0 0.929 0 0.071 201s 6 0 0.000 0 0 0.000 1 0.000 201s 7 0 0.000 0 0 0.054 0 0.946 201s 201s Data: pottery 201s Call: 201s Linda(origin ~ ., data = pottery, method = method) 201s 201s Prior Probabilities of Groups: 201s Attic Eritrean 201s 0.48148 0.51852 201s 201s Group means: 201s SI AL FE MG CA TI 201s Attic 55.450 13.738 10.0000 5.0750 5.0750 0.87375 201s Eritrean 52.444 16.444 9.3222 3.1667 6.1778 0.82000 201s 201s Within-groups Covariance Matrix: 201s SI AL FE MG CA TI 201s SI 6.565481 1.6098148 -0.075259 0.369556 -0.359407 0.0169667 201s AL 1.609815 0.5640648 0.029407 0.302056 0.112426 0.0018583 201s FE -0.075259 0.0294074 0.167704 -0.180222 -0.343704 0.0110667 201s MG 0.369556 0.3020556 -0.180222 1.031667 0.915222 -0.0192167 201s CA -0.359407 0.1124259 -0.343704 0.915222 1.447370 -0.0348167 201s TI 0.016967 0.0018583 0.011067 -0.019217 -0.034817 0.0011725 201s 201s Linear Coeficients: 201s SI AL FE MG CA TI 201s Attic 190.17 -622.48 922.21 1.5045 293.30 -990.323 201s Eritrean 135.34 -431.40 666.59 -14.3288 237.68 -44.025 201s 201s Constants: 201s Attic Eritrean 201s -5924.2 -3802.9 201s 201s Apparent error rate 0.1111 201s 201s Classification table 201s Predicted 201s Actual Attic Eritrean 201s Attic 12 1 201s Eritrean 2 12 201s 201s Confusion matrix 201s Predicted 201s Actual Attic Eritrean 201s Attic 0.923 0.077 201s Eritrean 0.143 0.857 201s 201s Data: olitos 201s 201s Apparent error rate 0.1667 201s 201s Classification table 201s Predicted 201s Actual 1 2 3 4 201s 1 44 1 2 3 201s 2 2 22 0 1 201s 3 5 2 25 2 201s 4 1 1 0 9 201s 201s Confusion matrix 201s Predicted 201s Actual 1 2 3 4 201s 1 0.880 0.020 0.040 0.060 201s 2 0.080 0.880 0.000 0.040 201s 3 0.147 0.059 0.735 0.059 201s 4 0.091 0.091 0.000 0.818 201s =================================================== 201s > dodata(method="mrcd") 201s 201s Call: dodata(method = "mrcd") 201s =================================================== 201s 201s Data: hemophilia 201s Call: 201s Linda(as.factor(gr) ~ ., data = hemophilia, method = method) 201s 201s Prior Probabilities of Groups: 201s carrier normal 201s 0.6 0.4 201s 201s Group means: 201s AHFactivity AHFantigen 201s carrier -0.34048 -0.055943 201s normal -0.13566 -0.081191 201s 201s Within-groups Covariance Matrix: 201s AHFactivity AHFantigen 201s AHFactivity 0.0133676 0.0088055 201s AHFantigen 0.0088055 0.0221225 201s 201s Linear Coeficients: 201s AHFactivity AHFantigen 201s carrier -32.264 10.31334 201s normal -10.478 0.50044 201s 201s Constants: 201s carrier normal 201s -5.7149 -1.6067 201s 201s Apparent error rate 0.16 201s 201s Classification table 201s Predicted 201s Actual carrier normal 201s carrier 38 7 201s normal 5 25 201s 201s Confusion matrix 201s Predicted 201s Actual carrier normal 201s carrier 0.844 0.156 201s normal 0.167 0.833 201s 201s Data: anorexia 201s Call: 201s Linda(Treat ~ ., data = anorexia, method = method) 201s 201s Prior Probabilities of Groups: 201s CBT Cont FT 201s 0.40278 0.36111 0.23611 201s 201s Group means: 201s Prewt Postwt 201s CBT 83.114 84.009 201s Cont 80.327 80.125 201s FT 85.161 94.371 201s 201s Within-groups Covariance Matrix: 201s Prewt Postwt 201s Prewt 22.498 11.860 201s Postwt 11.860 20.426 201s 201s Linear Coeficients: 201s Prewt Postwt 201s CBT 2.1994 2.8357 201s Cont 2.1653 2.6654 201s FT 1.9451 3.4907 201s 201s Constants: 201s CBT Cont FT 201s -211.42 -194.77 -248.97 201s 201s Apparent error rate 0.3889 201s 201s Classification table 201s Predicted 201s Actual CBT Cont FT 201s CBT 15 6 8 201s Cont 6 16 4 201s FT 0 4 13 201s 201s Confusion matrix 201s Predicted 201s Actual CBT Cont FT 201s CBT 0.517 0.207 0.276 201s Cont 0.231 0.615 0.154 201s FT 0.000 0.235 0.765 201s 201s Data: Pima 202s Call: 202s Linda(type ~ ., data = Pima.tr, method = method) 202s 202s Prior Probabilities of Groups: 202s No Yes 202s 0.66 0.34 202s 202s Group means: 202s npreg glu bp skin bmi ped age 202s No 1.9925 108.32 66.240 24.856 30.310 0.37382 24.747 202s Yes 5.8855 145.88 75.715 32.541 33.915 0.39281 38.857 202s 202s Within-groups Covariance Matrix: 202s npreg glu bp skin bmi ped age 202s npreg 4.090330 7.9547 3.818380 3.35899 2.470242 0.032557 9.5929 202s glu 7.954730 770.4187 76.377665 53.32216 54.100400 -1.139087 28.5677 202s bp 3.818380 76.3777 108.201622 42.61184 18.574983 -0.089151 20.3558 202s skin 3.358992 53.3222 42.611844 146.81170 65.210794 -0.277335 15.0162 202s bmi 2.470242 54.1004 18.574983 65.21079 52.871847 0.062145 9.0741 202s ped 0.032557 -1.1391 -0.089151 -0.27733 0.062145 0.063490 0.1762 202s age 9.592948 28.5677 20.355803 15.01616 9.074109 0.176201 53.5163 202s 202s Linear Coeficients: 202s npreg glu bp skin bmi ped age 202s No -1.30832 0.065773 0.54772 -0.32738 0.70207 5.2556 0.40900 202s Yes -0.76566 0.106435 0.55777 -0.28044 0.61709 5.9199 0.54892 202s 202s Constants: 202s No Yes 202s -33.429 -45.434 202s 202s Apparent error rate 0.28 202s 202s Classification table 202s Predicted 202s Actual No Yes 202s No 105 27 202s Yes 29 39 202s 202s Confusion matrix 202s Predicted 202s Actual No Yes 202s No 0.795 0.205 202s Yes 0.426 0.574 202s 202s Data: Forest soils 202s 202s Apparent error rate 0.3448 202s 202s Classification table 202s Predicted 202s Actual 1 2 3 202s 1 7 2 2 202s 2 4 14 5 202s 3 3 4 17 202s 202s Confusion matrix 202s Predicted 202s Actual 1 2 3 202s 1 0.636 0.182 0.182 202s 2 0.174 0.609 0.217 202s 3 0.125 0.167 0.708 202s 202s Data: Raven and Miller diabetes data 202s Call: 202s Linda(group ~ insulin + glucose + sspg, data = diabetes, method = method) 202s 202s Prior Probabilities of Groups: 202s normal chemical overt 202s 0.52414 0.24828 0.22759 202s 202s Group means: 202s insulin glucose sspg 202s normal 154.014 346.07 91.606 202s chemical 248.841 451.10 221.936 202s overt 89.766 1064.16 335.100 202s 202s Within-groups Covariance Matrix: 202s insulin glucose sspg 202s insulin 4948.1 1007.61 1471.12 202s glucose 1007.6 2597.38 358.57 202s sspg 1471.1 358.57 3180.04 202s 202s Linear Coeficients: 202s insulin glucose sspg 202s normal 0.00027839 0.13121 0.013882 202s chemical 0.00148074 0.16615 0.050371 202s overt -0.10102404 0.43466 0.103100 202s 202s Constants: 202s normal chemical overt 202s -24.008 -44.642 -245.497 202s 202s Apparent error rate 0.0966 202s 202s Classification table 202s Predicted 202s Actual normal chemical overt 202s normal 71 5 0 202s chemical 2 34 0 202s overt 0 7 26 202s 202s Confusion matrix 202s Predicted 202s Actual normal chemical overt 202s normal 0.934 0.066 0.000 202s chemical 0.056 0.944 0.000 202s overt 0.000 0.212 0.788 202s 202s Data: iris 202s Call: 202s Linda(Species ~ ., data = iris, method = method, l1med = TRUE) 202s 202s Prior Probabilities of Groups: 202s setosa versicolor virginica 202s 0.33333 0.33333 0.33333 202s 202s Group means: 202s Sepal.Length Sepal.Width Petal.Length Petal.Width 202s setosa 4.9755 3.3826 1.4608 0.22053 202s versicolor 5.8868 2.7823 4.2339 1.34603 202s virginica 6.5176 2.9691 5.4560 2.06335 202s 202s Within-groups Covariance Matrix: 202s Sepal.Length Sepal.Width Petal.Length Petal.Width 202s Sepal.Length 0.238417 0.136325 0.086377 0.036955 202s Sepal.Width 0.136325 0.148452 0.067500 0.034804 202s Petal.Length 0.086377 0.067500 0.100934 0.035968 202s Petal.Width 0.036955 0.034804 0.035968 0.023856 202s 202s Linear Coeficients: 202s Sepal.Length Sepal.Width Petal.Length Petal.Width 202s setosa 17.106 15.693 7.8806 -52.031 202s versicolor 21.744 -15.813 38.0139 -11.505 202s virginica 23.032 -26.567 43.6391 23.777 202s 202s Constants: 202s setosa versicolor virginica 202s -70.214 -115.832 -180.294 202s 202s Apparent error rate 0.02 202s 202s Classification table 202s Predicted 202s Actual setosa versicolor virginica 202s setosa 50 0 0 202s versicolor 0 49 1 202s virginica 0 2 48 202s 202s Confusion matrix 202s Predicted 202s Actual setosa versicolor virginica 202s setosa 1 0.00 0.00 202s versicolor 0 0.98 0.02 202s virginica 0 0.04 0.96 202s 202s Data: crabs 202s Call: 202s Linda(sp ~ ., data = crabs, method = method) 202s 202s Prior Probabilities of Groups: 202s B O 202s 0.5 0.5 202s 202s Group means: 202s sexM index FL RW CL CW BD 202s B 0 25.5 13.270 12.138 28.102 32.624 11.816 202s O 1 25.5 16.626 12.262 33.688 37.188 15.324 202s 202s Within-groups Covariance Matrix: 202s sexM index FL RW CL CW BD 202s sexM 1.5255e-07 0.000 0.0000 0.0000 0.000 0.000 0.000 202s index 0.0000e+00 337.501 62.8107 46.5073 137.713 154.451 63.514 202s FL 0.0000e+00 62.811 15.3164 9.8612 29.911 33.479 13.805 202s RW 0.0000e+00 46.507 9.8612 8.6949 21.878 24.604 10.092 202s CL 0.0000e+00 137.713 29.9112 21.8779 73.888 73.891 30.486 202s CW 0.0000e+00 154.451 33.4788 24.6038 73.891 92.801 34.122 202s BD 0.0000e+00 63.514 13.8053 10.0923 30.486 34.122 15.854 202s 202s Linear Coeficients: 202s sexM index FL RW CL CW BD 202s B 0 -0.64890 0.95529 2.7299 0.20747 0.28549 -0.23815 202s O 6555120 -0.83294 1.67920 1.8896 0.32330 0.23479 0.51136 202s 202s Constants: 202s B O 202s -2.1491e+01 -3.2776e+06 202s 202s Apparent error rate 0.5 202s 202s Classification table 202s Predicted 202s Actual B O 202s B 50 50 202s O 50 50 202s 202s Confusion matrix 202s Predicted 202s Actual B O 202s B 0.5 0.5 202s O 0.5 0.5 202s 202s Data: fish 202s 202s Apparent error rate 0.2532 202s 202s Classification table 202s Predicted 202s Actual 1 2 3 4 5 6 7 202s 1 33 0 0 1 0 0 0 202s 2 0 3 0 0 0 0 3 202s 3 0 2 5 0 0 0 13 202s 4 0 0 0 11 0 0 0 202s 5 0 0 0 0 14 0 0 202s 6 0 0 0 0 0 17 0 202s 7 0 19 0 0 2 0 35 202s 202s Confusion matrix 202s Predicted 202s Actual 1 2 3 4 5 6 7 202s 1 0.971 0.000 0.00 0.029 0.000 0 0.000 202s 2 0.000 0.500 0.00 0.000 0.000 0 0.500 202s 3 0.000 0.100 0.25 0.000 0.000 0 0.650 202s 4 0.000 0.000 0.00 1.000 0.000 0 0.000 202s 5 0.000 0.000 0.00 0.000 1.000 0 0.000 202s 6 0.000 0.000 0.00 0.000 0.000 1 0.000 202s 7 0.000 0.339 0.00 0.000 0.036 0 0.625 202s 202s Data: pottery 202s Call: 202s Linda(origin ~ ., data = pottery, method = method) 202s 202s Prior Probabilities of Groups: 202s Attic Eritrean 202s 0.48148 0.51852 202s 202s Group means: 202s SI AL FE MG CA TI 202s Attic 55.872 13.986 10.113 5.0235 4.7316 0.88531 202s Eritrean 52.487 16.286 9.499 2.4520 5.3745 0.83959 202s 202s Within-groups Covariance Matrix: 202s SI AL FE MG CA TI 202s SI 12.795913 3.2987125 -0.35496855 0.9399999 -0.0143514 0.01132392 202s AL 3.298713 1.0829436 -0.03394751 0.2838724 0.0501000 0.00117721 202s FE -0.354969 -0.0339475 0.08078156 0.0341568 -0.0457411 0.00043177 202s MG 0.940000 0.2838724 0.03415675 0.4350013 0.1417876 0.00396576 202s CA -0.014351 0.0501000 -0.04574114 0.1417876 0.4196628 -0.00104893 202s TI 0.011324 0.0011772 0.00043177 0.0039658 -0.0010489 0.00026205 202s 202s Linear Coeficients: 202s SI AL FE MG CA TI 202s Attic 36.451 -63.784 352.90 -124.07 110.08 3826.6 202s Eritrean 29.763 -41.039 325.12 -128.32 107.36 3938.1 202s 202s Constants: 202s Attic Eritrean 202s -4000.1 -3776.1 202s 202s Apparent error rate 0.1111 202s 202s Classification table 202s Predicted 202s Actual Attic Eritrean 202s Attic 12 1 202s Eritrean 2 12 202s 202s Confusion matrix 202s Predicted 202s Actual Attic Eritrean 202s Attic 0.923 0.077 202s Eritrean 0.143 0.857 202s 202s Data: olitos 202s 202s Apparent error rate 0.125 202s 202s Classification table 202s Predicted 202s Actual 1 2 3 4 202s 1 44 2 3 1 202s 2 1 23 1 0 202s 3 4 1 27 2 202s 4 0 0 0 11 202s 202s Confusion matrix 202s Predicted 202s Actual 1 2 3 4 202s 1 0.880 0.040 0.060 0.020 202s 2 0.040 0.920 0.040 0.000 202s 3 0.118 0.029 0.794 0.059 202s 4 0.000 0.000 0.000 1.000 202s =================================================== 202s > dodata(method="ogk") 202s 202s Call: dodata(method = "ogk") 202s =================================================== 202s 202s Data: hemophilia 202s Call: 202s Linda(as.factor(gr) ~ ., data = hemophilia, method = method) 202s 202s Prior Probabilities of Groups: 202s carrier normal 202s 0.6 0.4 202s 202s Group means: 202s AHFactivity AHFantigen 202s carrier -0.29043 -0.00052902 202s normal -0.12463 -0.06715037 202s 202s Within-groups Covariance Matrix: 202s AHFactivity AHFantigen 202s AHFactivity 0.015688 0.010544 202s AHFantigen 0.010544 0.016633 202s 202s Linear Coeficients: 202s AHFactivity AHFantigen 202s carrier -32.2203 20.3935 202s normal -9.1149 1.7409 202s 202s Constants: 202s carrier normal 202s -5.1843 -1.4259 202s 202s Apparent error rate 0.1467 202s 202s Classification table 202s Predicted 202s Actual carrier normal 202s carrier 38 7 202s normal 4 26 202s 202s Confusion matrix 202s Predicted 202s Actual carrier normal 202s carrier 0.844 0.156 202s normal 0.133 0.867 202s 202s Data: anorexia 202s Call: 202s Linda(Treat ~ ., data = anorexia, method = method) 202s 202s Prior Probabilities of Groups: 202s CBT Cont FT 202s 0.40278 0.36111 0.23611 202s 202s Group means: 202s Prewt Postwt 202s CBT 82.634 82.060 202s Cont 81.605 80.459 202s FT 85.157 93.822 202s 202s Within-groups Covariance Matrix: 202s Prewt Postwt 202s Prewt 15.8294 4.4663 202s Postwt 4.4663 19.6356 202s 202s Linear Coeficients: 202s Prewt Postwt 202s CBT 4.3183 3.1970 202s Cont 4.2734 3.1256 202s FT 4.3080 3.7983 202s 202s Constants: 202s CBT Cont FT 202s -310.50 -301.12 -363.05 202s 202s Apparent error rate 0.4583 202s 202s Classification table 202s Predicted 202s Actual CBT Cont FT 202s CBT 15 5 9 202s Cont 14 11 1 202s FT 0 4 13 202s 202s Confusion matrix 202s Predicted 202s Actual CBT Cont FT 202s CBT 0.517 0.172 0.310 202s Cont 0.538 0.423 0.038 202s FT 0.000 0.235 0.765 202s 202s Data: Pima 202s Call: 202s Linda(type ~ ., data = Pima.tr, method = method) 202s 202s Prior Probabilities of Groups: 202s No Yes 202s 0.66 0.34 202s 202s Group means: 202s npreg glu bp skin bmi ped age 202s No 2.4175 109.93 67.332 26.324 30.344 0.38740 26.267 202s Yes 5.1853 142.29 75.194 33.151 34.878 0.47977 37.626 202s 202s Within-groups Covariance Matrix: 202s npreg glu bp skin bmi ped age 202s npreg 7.218576 7.52457 6.96595 4.86613 0.45567 -0.054245 14.42648 202s glu 7.524571 517.38370 58.53812 31.57321 22.68396 -0.200222 22.88780 202s bp 6.965950 58.53812 101.50317 27.86784 10.89215 -0.152784 25.41819 202s skin 4.866127 31.57321 27.86784 95.16949 37.45066 -0.117375 14.60676 202s bmi 0.455675 22.68396 10.89215 37.45066 30.89491 0.043400 4.05584 202s ped -0.054245 -0.20022 -0.15278 -0.11737 0.04340 0.051268 -0.18131 202s age 14.426479 22.88780 25.41819 14.60676 4.05584 -0.181311 57.89570 202s 202s Linear Coeficients: 202s npreg glu bp skin bmi ped age 202s No -0.99043 0.12339 0.54101 -0.35335 1.0721 8.4945 0.45482 202s Yes -1.01369 0.17577 0.53898 -0.35554 1.1563 11.0474 0.63966 202s 202s Constants: 202s No Yes 202s -43.449 -60.176 202s 202s Apparent error rate 0.23 202s 202s Classification table 202s Predicted 202s Actual No Yes 202s No 108 24 202s Yes 22 46 202s 202s Confusion matrix 202s Predicted 202s Actual No Yes 202s No 0.818 0.182 202s Yes 0.324 0.676 202s 202s Data: Forest soils 202s 202s Apparent error rate 0.3621 202s 202s Classification table 202s Predicted 202s Actual 1 2 3 202s 1 7 3 1 202s 2 4 13 6 202s 3 3 4 17 202s 202s Confusion matrix 202s Predicted 202s Actual 1 2 3 202s 1 0.636 0.273 0.091 202s 2 0.174 0.565 0.261 202s 3 0.125 0.167 0.708 202s 202s Data: Raven and Miller diabetes data 202s Call: 202s Linda(group ~ insulin + glucose + sspg, data = diabetes, method = method) 202s 202s Prior Probabilities of Groups: 202s normal chemical overt 202s 0.52414 0.24828 0.22759 202s 202s Group means: 202s insulin glucose sspg 202s normal 159.540 344.06 99.486 202s chemical 252.992 478.16 219.442 202s overt 79.635 1094.96 338.517 202s 202s Within-groups Covariance Matrix: 202s insulin glucose sspg 202s insulin 3844.877 67.238 1456.55 202s glucose 67.238 2228.396 324.21 202s sspg 1456.548 324.205 2181.73 202s 202s Linear Coeficients: 202s insulin glucose sspg 202s normal 0.040407 0.15379 -0.0042303 202s chemical 0.047858 0.20764 0.0377766 202s overt -0.026158 0.47736 0.1016873 202s 202s Constants: 202s normal chemical overt 202s -30.115 -61.233 -278.996 202s 202s Apparent error rate 0.0966 202s 202s Classification table 202s Predicted 202s Actual normal chemical overt 202s normal 71 5 0 202s chemical 2 34 0 202s overt 0 7 26 202s 202s Confusion matrix 202s Predicted 202s Actual normal chemical overt 202s normal 0.934 0.066 0.000 202s chemical 0.056 0.944 0.000 202s overt 0.000 0.212 0.788 202s 202s Data: iris 202s Call: 202s Linda(Species ~ ., data = iris, method = method, l1med = TRUE) 202s 202s Prior Probabilities of Groups: 202s setosa versicolor virginica 202s 0.33333 0.33333 0.33333 202s 202s Group means: 202s Sepal.Length Sepal.Width Petal.Length Petal.Width 202s setosa 4.9654 3.3913 1.4507 0.21639 202s versicolor 5.8767 2.7909 4.2238 1.34189 202s virginica 6.5075 2.9777 5.4459 2.05921 202s 202s Within-groups Covariance Matrix: 202s Sepal.Length Sepal.Width Petal.Length Petal.Width 202s Sepal.Length 0.180280 0.068876 0.101512 0.036096 202s Sepal.Width 0.068876 0.079556 0.047722 0.029409 202s Petal.Length 0.101512 0.047722 0.111492 0.038658 202s Petal.Width 0.036096 0.029409 0.038658 0.029965 202s 202s Linear Coeficients: 202s Sepal.Length Sepal.Width Petal.Length Petal.Width 202s setosa 28.582 46.5236 -13.859 -54.9877 202s versicolor 19.837 11.9601 20.865 -17.7704 202s virginica 16.999 1.9046 29.808 7.9189 202s 202s Constants: 202s setosa versicolor virginica 202s -134.94 -108.22 -148.56 202s 202s Apparent error rate 0.0133 202s 202s Classification table 202s Predicted 202s Actual setosa versicolor virginica 202s setosa 50 0 0 202s versicolor 0 49 1 202s virginica 0 1 49 202s 202s Confusion matrix 202s Predicted 202s Actual setosa versicolor virginica 202s setosa 1 0.00 0.00 202s versicolor 0 0.98 0.02 202s virginica 0 0.02 0.98 202s 202s Data: crabs 202s Call: 202s Linda(sp ~ ., data = crabs, method = method) 202s 202s Prior Probabilities of Groups: 202s B O 202s 0.5 0.5 202s 202s Group means: 202s sexM index FL RW CL CW BD 202s B 0.48948 24.060 13.801 11.738 29.491 34.062 12.329 202s O 0.56236 24.043 16.825 13.158 33.574 37.418 15.223 202s 202s Within-groups Covariance Matrix: 202s sexM index FL RW CL CW BD 202s sexM 0.24961 0.50421 0.16645 -0.28574 0.54159 0.48449 0.22563 202s index 0.50421 186.86616 38.46284 25.26749 82.29121 92.11253 37.67723 202s FL 0.16645 38.46284 8.58830 5.56769 18.33015 20.58235 8.32030 202s RW -0.28574 25.26749 5.56769 4.52038 11.70881 13.37643 5.32779 202s CL 0.54159 82.29121 18.33015 11.70881 39.78186 44.52112 18.01179 202s CW 0.48449 92.11253 20.58235 13.37643 44.52112 50.06150 20.16852 202s BD 0.22563 37.67723 8.32030 5.32779 18.01179 20.16852 8.25884 202s 202s Linear Coeficients: 202s sexM index FL RW CL CW BD 202s B 16.497 -2.5896 8.3966 11.518 1.7536 -2.5325 -0.67361 202s O 17.010 -4.0452 23.5400 13.702 4.7871 -14.8264 13.04556 202s 202s Constants: 202s B O 202s -77.695 -147.287 202s 202s Apparent error rate 0 202s 202s Classification table 202s Predicted 202s Actual B O 202s B 100 0 202s O 0 100 202s 202s Confusion matrix 202s Predicted 202s Actual B O 202s B 1 0 202s O 0 1 202s 202s Data: fish 202s 202s Apparent error rate 0.0063 202s 202s Classification table 202s Predicted 202s Actual 1 2 3 4 5 6 7 202s 1 34 0 0 0 0 0 0 202s 2 0 6 0 0 0 0 0 202s 3 0 0 20 0 0 0 0 202s 4 0 0 0 11 0 0 0 202s 5 0 0 0 0 14 0 0 202s 6 0 0 0 0 0 17 0 202s 7 0 0 0 0 1 0 55 202s 202s Confusion matrix 202s Predicted 202s Actual 1 2 3 4 5 6 7 202s 1 1 0 0 0 0.000 0 0.000 202s 2 0 1 0 0 0.000 0 0.000 202s 3 0 0 1 0 0.000 0 0.000 202s 4 0 0 0 1 0.000 0 0.000 202s 5 0 0 0 0 1.000 0 0.000 202s 6 0 0 0 0 0.000 1 0.000 202s 7 0 0 0 0 0.018 0 0.982 202s 202s Data: pottery 202s Call: 202s Linda(origin ~ ., data = pottery, method = method) 202s 202s Prior Probabilities of Groups: 202s Attic Eritrean 202s 0.48148 0.51852 202s 202s Group means: 202s SI AL FE MG CA TI 202s Attic 55.381 14.088 10.1316 4.9588 4.7684 0.88444 202s Eritrean 53.559 16.251 9.1145 2.6213 5.8980 0.82501 202s 202s Within-groups Covariance Matrix: 202s SI AL FE MG CA TI 202s SI 7.878378 1.9064112 -0.545403 0.4167407 -0.11589 0.01850748 202s AL 1.906411 0.6678763 -0.037744 0.1120891 -0.10733 0.00805556 202s FE -0.545403 -0.0377438 0.213914 -0.0192356 -0.23121 0.00582800 202s MG 0.416741 0.1120891 -0.019236 0.2336721 0.17284 -0.00183128 202s CA -0.115888 -0.1073297 -0.231213 0.1728385 0.71388 -0.01895968 202s TI 0.018507 0.0080556 0.005828 -0.0018313 -0.01896 0.00081815 202s 202s Linear Coeficients: 202s SI AL FE MG CA TI 202s Attic 57.784 -107.297 319.31 -152.94 241.66 3813.6 202s Eritrean 52.523 -86.545 306.58 -165.71 242.36 3734.1 202s 202s Constants: 202s Attic Eritrean 202s -4346 -4139 202s 202s Apparent error rate 0.1111 202s 202s Classification table 202s Predicted 202s Actual Attic Eritrean 202s Attic 12 1 202s Eritrean 2 12 202s 202s Confusion matrix 202s Predicted 202s Actual Attic Eritrean 202s Attic 0.923 0.077 202s Eritrean 0.143 0.857 202s 202s Data: olitos 202s 202s Apparent error rate 0.1 202s 202s Classification table 202s Predicted 202s Actual 1 2 3 4 202s 1 45 2 2 1 202s 2 0 25 0 0 202s 3 4 1 27 2 202s 4 0 0 0 11 202s 202s Confusion matrix 202s Predicted 202s Actual 1 2 3 4 202s 1 0.900 0.040 0.040 0.020 202s 2 0.000 1.000 0.000 0.000 202s 3 0.118 0.029 0.794 0.059 202s 4 0.000 0.000 0.000 1.000 202s =================================================== 202s > #dodata(method="fsa") 202s > 203s BEGIN TEST tldapp.R 203s 203s R version 4.3.3 (2024-02-29) -- "Angel Food Cake" 203s Copyright (C) 2024 The R Foundation for Statistical Computing 203s Platform: aarch64-unknown-linux-gnu (64-bit) 203s 203s R is free software and comes with ABSOLUTELY NO WARRANTY. 203s You are welcome to redistribute it under certain conditions. 203s Type 'license()' or 'licence()' for distribution details. 203s 203s R is a collaborative project with many contributors. 203s Type 'contributors()' for more information and 203s 'citation()' on how to cite R or R packages in publications. 203s 203s Type 'demo()' for some demos, 'help()' for on-line help, or 203s 'help.start()' for an HTML browser interface to help. 203s Type 'q()' to quit R. 203s 203s > ## VT::15.09.2013 - this will render the output independent 203s > ## from the version of the package 203s > suppressPackageStartupMessages(library(rrcov)) 204s > library(MASS) 204s > 204s > dodata <- function(method) { 204s + 204s + options(digits = 5) 204s + set.seed(101) 204s + 204s + tmp <- sys.call() 204s + cat("\nCall: ", deparse(substitute(tmp)),"\n") 204s + cat("===================================================\n") 204s + 204s + data(pottery); show(lda <- LdaPP(origin~., data=pottery, method=method)); show(predict(lda)) 204s + data(hemophilia); show(lda <- LdaPP(as.factor(gr)~., data=hemophilia, method=method)); show(predict(lda)) 204s + data(anorexia); show(lda <- LdaPP(Treat~., data=anorexia, method=method)); show(predict(lda)) 204s + data(Pima.tr); show(lda <- LdaPP(type~., data=Pima.tr, method=method)); show(predict(lda)) 204s + data(crabs); show(lda <- LdaPP(sp~., data=crabs, method=method)); show(predict(lda)) 204s + 204s + cat("===================================================\n") 204s + } 204s > 204s > 204s > ## -- now do it: 204s > 204s > ## Commented out - still to slow 204s > ##dodata(method="huber") 204s > ##dodata(method="sest") 204s > 204s > ## VT::14.11.2018 - Commented out: too slow 204s > ## dodata(method="mad") 204s > ## dodata(method="class") 204s > 204s BEGIN TEST tmcd4.R 204s 204s R version 4.3.3 (2024-02-29) -- "Angel Food Cake" 204s Copyright (C) 2024 The R Foundation for Statistical Computing 204s Platform: aarch64-unknown-linux-gnu (64-bit) 204s 204s R is free software and comes with ABSOLUTELY NO WARRANTY. 204s You are welcome to redistribute it under certain conditions. 204s Type 'license()' or 'licence()' for distribution details. 204s 204s R is a collaborative project with many contributors. 204s Type 'contributors()' for more information and 204s 'citation()' on how to cite R or R packages in publications. 204s 204s Type 'demo()' for some demos, 'help()' for on-line help, or 204s 'help.start()' for an HTML browser interface to help. 204s Type 'q()' to quit R. 204s 204s > ## Test the exact fit property of CovMcd 204s > doexactfit <- function(){ 204s + exact <-function(seed=1234){ 204s + 204s + set.seed(seed) 204s + 204s + n1 <- 45 204s + p <- 2 204s + x1 <- matrix(rnorm(p*n1),nrow=n1, ncol=p) 204s + x1[,p] <- x1[,p] + 3 204s + n2 <- 55 204s + m1 <- 0 204s + m2 <- 3 204s + x2 <- cbind(rnorm(n2),rep(m2,n2)) 204s + x<-rbind(x1,x2) 204s + colnames(x) <- c("X1","X2") 204s + x 204s + } 204s + print(CovMcd(exact())) 204s + } 204s > 204s > dodata <- function(nrep=1, time=FALSE, short=FALSE, full=TRUE, method = c("FASTMCD","MASS", "deterministic", "exact", "MRCD")){ 204s + ##@bdescr 204s + ## Test the function covMcd() on the literature datasets: 204s + ## 204s + ## Call CovMcd() for all regression datasets available in rrcov and print: 204s + ## - execution time (if time == TRUE) 204s + ## - objective fucntion 204s + ## - best subsample found (if short == false) 204s + ## - outliers identified (with cutoff 0.975) (if short == false) 204s + ## - estimated center and covarinance matrix if full == TRUE) 204s + ## 204s + ##@edescr 204s + ## 204s + ##@in nrep : [integer] number of repetitions to use for estimating the 204s + ## (average) execution time 204s + ##@in time : [boolean] whether to evaluate the execution time 204s + ##@in short : [boolean] whether to do short output (i.e. only the 204s + ## objective function value). If short == FALSE, 204s + ## the best subsample and the identified outliers are 204s + ## printed. See also the parameter full below 204s + ##@in full : [boolean] whether to print the estimated cente and covariance matrix 204s + ##@in method : [character] select a method: one of (FASTMCD, MASS) 204s + 204s + doest <- function(x, xname, nrep=1){ 204s + n <- dim(x)[1] 204s + p <- dim(x)[2] 204s + if(method == "MASS"){ 204s + mcd<-cov.mcd(x) 204s + quan <- as.integer(floor((n + p + 1)/2)) #default: floor((n+p+1)/2) 204s + } 204s + else{ 204s + mcd <- if(method=="deterministic") CovMcd(x, nsamp="deterministic", trace=FALSE) 204s + else if(method=="exact") CovMcd(x, nsamp="exact", trace=FALSE) 204s + else if(method=="MRCD") CovMrcd(x, trace=FALSE) 204s + else CovMcd(x, trace=FALSE) 204s + quan <- as.integer(mcd@quan) 204s + } 204s + 204s + crit <- mcd@crit 204s + 204s + if(time){ 204s + xtime <- system.time(dorep(x, nrep, method))[1]/nrep 204s + xres <- sprintf("%3d %3d %3d %12.6f %10.3f\n", dim(x)[1], dim(x)[2], quan, crit, xtime) 204s + } 204s + else{ 204s + xres <- sprintf("%3d %3d %3d %12.6f\n", dim(x)[1], dim(x)[2], quan, crit) 204s + } 204s + lpad<-lname-nchar(xname) 204s + cat(pad.right(xname,lpad), xres) 204s + 204s + if(!short){ 204s + cat("Best subsample: \n") 204s + if(length(mcd@best) > 150) 204s + cat("Too long... \n") 204s + else 204s + print(mcd@best) 204s + 204s + ibad <- which(mcd@wt==0) 204s + names(ibad) <- NULL 204s + nbad <- length(ibad) 204s + cat("Outliers: ",nbad,"\n") 204s + if(nbad > 0 & nbad < 150) 204s + print(ibad) 204s + else 204s + cat("Too many to print ... \n") 204s + if(full){ 204s + cat("-------------\n") 204s + show(mcd) 204s + } 204s + cat("--------------------------------------------------------\n") 204s + } 204s + } 204s + 204s + options(digits = 5) 204s + set.seed(101) # <<-- sub-sampling algorithm now based on R's RNG and seed 204s + 204s + lname <- 20 204s + 204s + ## VT::15.09.2013 - this will render the output independent 204s + ## from the version of the package 204s + suppressPackageStartupMessages(library(rrcov)) 204s + 204s + method <- match.arg(method) 204s + if(method == "MASS") 204s + library(MASS) 204s + 204s + data(Animals, package = "MASS") 204s + brain <- Animals[c(1:24, 26:25, 27:28),] 204s + 204s + data(fish) 204s + data(pottery) 204s + data(rice) 204s + data(un86) 204s + data(wages) 204s + 204s + tmp <- sys.call() 204s + cat("\nCall: ", deparse(substitute(tmp)),"\n") 204s + 204s + cat("Data Set n p Half LOG(obj) Time\n") 204s + cat("========================================================\n") 204s + 204s + if(method=="exact") 204s + { 204s + ## only small data sets 204s + doest(heart[, 1:2], data(heart), nrep) 204s + doest(starsCYG, data(starsCYG), nrep) 204s + doest(data.matrix(subset(phosphor, select = -plant)), data(phosphor), nrep) 204s + doest(data.matrix(subset(coleman, select = -Y)), data(coleman), nrep) 204s + doest(data.matrix(subset(salinity, select = -Y)), data(salinity), nrep) 204s + doest(data.matrix(subset(wood, select = -y)), data(wood), nrep) 204s + doest(brain, "Animals", nrep) 204s + doest(lactic, data(lactic), nrep) 204s + doest(pension, data(pension), nrep) 204s + doest(data.matrix(subset(vaso, select = -Y)), data(vaso), nrep) 204s + doest(stack.x, data(stackloss), nrep) 204s + doest(pilot, data(pilot), nrep) 204s + } else 204s + { 204s + doest(heart[, 1:2], data(heart), nrep) 204s + doest(starsCYG, data(starsCYG), nrep) 204s + doest(data.matrix(subset(phosphor, select = -plant)), data(phosphor), nrep) 204s + doest(stack.x, data(stackloss), nrep) 204s + doest(data.matrix(subset(coleman, select = -Y)), data(coleman), nrep) 204s + doest(data.matrix(subset(salinity, select = -Y)), data(salinity), nrep) 204s + doest(data.matrix(subset(wood, select = -y)), data(wood), nrep) 204s + doest(data.matrix(subset(hbk, select = -Y)),data(hbk), nrep) 204s + 204s + doest(brain, "Animals", nrep) 204s + ## doest(milk, data(milk), nrep) # difference between 386 and x64 204s + doest(bushfire, data(bushfire), nrep) 204s + 204s + doest(lactic, data(lactic), nrep) 204s + doest(pension, data(pension), nrep) 204s + ## doest(pilot, data(pilot), nrep) # difference between 386 and x64 204s + 204s + if(method != "MRCD") # these two are quite slow for MRCD, especially the second one 204s + { 204s + doest(radarImage, data(radarImage), nrep) 204s + doest(NOxEmissions, data(NOxEmissions), nrep) 204s + } 204s + 204s + doest(data.matrix(subset(vaso, select = -Y)), data(vaso), nrep) 204s + doest(data.matrix(subset(wagnerGrowth, select = -Period)), data(wagnerGrowth), nrep) 204s + 204s + doest(data.matrix(subset(fish, select = -Species)), data(fish), nrep) 204s + doest(data.matrix(subset(pottery, select = -origin)), data(pottery), nrep) 204s + doest(rice, data(rice), nrep) 204s + doest(un86, data(un86), nrep) 204s + 204s + doest(wages, data(wages), nrep) 204s + 204s + ## from package 'datasets' 204s + doest(airquality[,1:4], data(airquality), nrep) 204s + doest(attitude, data(attitude), nrep) 204s + doest(attenu, data(attenu), nrep) 204s + doest(USJudgeRatings, data(USJudgeRatings), nrep) 204s + doest(USArrests, data(USArrests), nrep) 204s + doest(longley, data(longley), nrep) 204s + doest(Loblolly, data(Loblolly), nrep) 204s + doest(quakes[,1:4], data(quakes), nrep) 204s + } 204s + cat("========================================================\n") 204s + } 204s > 204s > dogen <- function(nrep=1, eps=0.49, method=c("FASTMCD", "MASS")){ 204s + 204s + doest <- function(x, nrep=1){ 204s + gc() 204s + xtime <- system.time(dorep(x, nrep, method))[1]/nrep 204s + cat(sprintf("%6d %3d %10.2f\n", dim(x)[1], dim(x)[2], xtime)) 204s + xtime 204s + } 204s + 204s + set.seed(1234) 204s + 204s + ## VT::15.09.2013 - this will render the output independent 204s + ## from the version of the package 204s + suppressPackageStartupMessages(library(rrcov)) 204s + 204s + library(MASS) 204s + method <- match.arg(method) 204s + 204s + ap <- c(2, 5, 10, 20, 30) 204s + an <- c(100, 500, 1000, 10000, 50000) 204s + 204s + tottime <- 0 204s + cat(" n p Time\n") 204s + cat("=====================\n") 204s + for(i in 1:length(an)) { 204s + for(j in 1:length(ap)) { 204s + n <- an[i] 204s + p <- ap[j] 204s + if(5*p <= n){ 204s + xx <- gendata(n, p, eps) 204s + X <- xx$X 204s + tottime <- tottime + doest(X, nrep) 204s + } 204s + } 204s + } 204s + 204s + cat("=====================\n") 204s + cat("Total time: ", tottime*nrep, "\n") 204s + } 204s > 204s > docheck <- function(n, p, eps){ 204s + xx <- gendata(n,p,eps) 204s + mcd <- CovMcd(xx$X) 204s + check(mcd, xx$xind) 204s + } 204s > 204s > check <- function(mcd, xind){ 204s + ## check if mcd is robust w.r.t xind, i.e. check how many of xind 204s + ## did not get zero weight 204s + mymatch <- xind %in% which(mcd@wt == 0) 204s + length(xind) - length(which(mymatch)) 204s + } 204s > 204s > dorep <- function(x, nrep=1, method=c("FASTMCD","MASS", "deterministic", "exact", "MRCD")){ 204s + 204s + method <- match.arg(method) 204s + for(i in 1:nrep) 204s + if(method == "MASS") 204s + cov.mcd(x) 204s + else 204s + { 204s + if(method=="deterministic") CovMcd(x, nsamp="deterministic", trace=FALSE) 204s + else if(method=="exact") CovMcd(x, nsamp="exact", trace=FALSE) 204s + else if(method=="MRCD") CovMrcd(x, trace=FALSE) 204s + else CovMcd(x, trace=FALSE) 204s + } 204s + } 204s > 204s > #### gendata() #### 204s > # Generates a location contaminated multivariate 204s > # normal sample of n observations in p dimensions 204s > # (1-eps)*Np(0,Ip) + eps*Np(m,Ip) 204s > # where 204s > # m = (b,b,...,b) 204s > # Defaults: eps=0 and b=10 204s > # 204s > gendata <- function(n,p,eps=0,b=10){ 204s + 204s + if(missing(n) || missing(p)) 204s + stop("Please specify (n,p)") 204s + if(eps < 0 || eps >= 0.5) 204s + stop(message="eps must be in [0,0.5)") 204s + X <- mvrnorm(n,rep(0,p),diag(1,nrow=p,ncol=p)) 204s + nbad <- as.integer(eps * n) 204s + if(nbad > 0){ 204s + Xbad <- mvrnorm(nbad,rep(b,p),diag(1,nrow=p,ncol=p)) 204s + xind <- sample(n,nbad) 204s + X[xind,] <- Xbad 204s + } 204s + list(X=X, xind=xind) 204s + } 204s > 204s > pad.right <- function(z, pads) 204s + { 204s + ### Pads spaces to right of text 204s + padding <- paste(rep(" ", pads), collapse = "") 204s + paste(z, padding, sep = "") 204s + } 204s > 204s > whatis<-function(x){ 204s + if(is.data.frame(x)) 204s + cat("Type: data.frame\n") 204s + else if(is.matrix(x)) 204s + cat("Type: matrix\n") 204s + else if(is.vector(x)) 204s + cat("Type: vector\n") 204s + else 204s + cat("Type: don't know\n") 204s + } 204s > 204s > ## VT::15.09.2013 - this will render the output independent 204s > ## from the version of the package 204s > suppressPackageStartupMessages(library(rrcov)) 204s > 204s > dodata() 204s 204s Call: dodata() 204s Data Set n p Half LOG(obj) Time 204s ======================================================== 204s heart 12 2 7 5.678742 204s Best subsample: 204s [1] 1 3 4 5 7 9 11 204s Outliers: 0 204s Too many to print ... 204s ------------- 204s 204s Call: 204s CovMcd(x = x, trace = FALSE) 204s -> Method: Fast MCD(alpha=0.5 ==> h=7); nsamp = 500; (n,k)mini = (300,5) 204s 204s Robust Estimate of Location: 204s height weight 204s 38.3 33.1 204s 204s Robust Estimate of Covariance: 204s height weight 204s height 135 259 204s weight 259 564 204s -------------------------------------------------------- 204s starsCYG 47 2 25 -8.031215 204s Best subsample: 204s [1] 1 2 4 6 8 10 12 13 16 24 25 26 28 32 33 37 38 39 40 41 42 43 44 45 46 204s Outliers: 7 204s [1] 7 9 11 14 20 30 34 204s ------------- 204s 204s Call: 204s CovMcd(x = x, trace = FALSE) 204s -> Method: Fast MCD(alpha=0.5 ==> h=25); nsamp = 500; (n,k)mini = (300,5) 204s 204s Robust Estimate of Location: 204s log.Te log.light 204s 4.41 4.95 204s 204s Robust Estimate of Covariance: 204s log.Te log.light 204s log.Te 0.0132 0.0394 204s log.light 0.0394 0.2743 204s -------------------------------------------------------- 204s phosphor 18 2 10 6.878847 204s Best subsample: 204s [1] 3 5 8 9 11 12 13 14 15 17 204s Outliers: 3 204s [1] 1 6 10 204s ------------- 204s 204s Call: 204s CovMcd(x = x, trace = FALSE) 204s -> Method: Fast MCD(alpha=0.5 ==> h=10); nsamp = 500; (n,k)mini = (300,5) 204s 204s Robust Estimate of Location: 204s inorg organic 204s 13.4 38.8 204s 204s Robust Estimate of Covariance: 204s inorg organic 204s inorg 129 130 204s organic 130 182 204s -------------------------------------------------------- 204s stackloss 21 3 12 5.472581 204s Best subsample: 204s [1] 4 5 6 7 8 9 10 11 12 13 14 20 204s Outliers: 9 204s [1] 1 2 3 15 16 17 18 19 21 204s ------------- 204s 204s Call: 204s CovMcd(x = x, trace = FALSE) 204s -> Method: Fast MCD(alpha=0.5 ==> h=12); nsamp = 500; (n,k)mini = (300,5) 204s 204s Robust Estimate of Location: 204s Air.Flow Water.Temp Acid.Conc. 204s 59.5 20.8 87.3 204s 204s Robust Estimate of Covariance: 204s Air.Flow Water.Temp Acid.Conc. 204s Air.Flow 6.29 5.85 5.74 204s Water.Temp 5.85 9.23 6.14 204s Acid.Conc. 5.74 6.14 23.25 204s -------------------------------------------------------- 204s coleman 20 5 13 1.286808 204s Best subsample: 204s [1] 2 3 4 5 7 8 12 13 14 16 17 19 20 204s Outliers: 7 204s [1] 1 6 9 10 11 15 18 204s ------------- 204s 204s Call: 204s CovMcd(x = x, trace = FALSE) 204s -> Method: Fast MCD(alpha=0.5 ==> h=13); nsamp = 500; (n,k)mini = (300,5) 204s 204s Robust Estimate of Location: 204s salaryP fatherWc sstatus teacherSc motherLev 204s 2.76 48.38 6.12 25.00 6.40 204s 204s Robust Estimate of Covariance: 204s salaryP fatherWc sstatus teacherSc motherLev 204s salaryP 0.253 1.786 -0.266 0.151 0.075 204s fatherWc 1.786 1303.382 330.496 12.604 34.503 204s sstatus -0.266 330.496 119.888 3.833 10.131 204s teacherSc 0.151 12.604 3.833 0.785 0.555 204s motherLev 0.075 34.503 10.131 0.555 1.043 204s -------------------------------------------------------- 204s salinity 28 3 16 1.326364 204s Best subsample: 204s [1] 1 2 6 7 8 12 13 14 18 20 21 22 25 26 27 28 204s Outliers: 4 204s [1] 5 16 23 24 204s ------------- 204s 204s Call: 204s CovMcd(x = x, trace = FALSE) 204s -> Method: Fast MCD(alpha=0.5 ==> h=16); nsamp = 500; (n,k)mini = (300,5) 204s 204s Robust Estimate of Location: 204s X1 X2 X3 204s 10.08 2.78 22.78 204s 204s Robust Estimate of Covariance: 204s X1 X2 X3 204s X1 10.44 1.01 -3.19 204s X2 1.01 3.83 -1.44 204s X3 -3.19 -1.44 2.39 204s -------------------------------------------------------- 204s wood 20 5 13 -36.270094 204s Best subsample: 204s [1] 1 2 3 5 9 10 12 13 14 15 17 18 20 204s Outliers: 7 204s [1] 4 6 7 8 11 16 19 204s ------------- 204s 204s Call: 204s CovMcd(x = x, trace = FALSE) 204s -> Method: Fast MCD(alpha=0.5 ==> h=13); nsamp = 500; (n,k)mini = (300,5) 204s 204s Robust Estimate of Location: 204s x1 x2 x3 x4 x5 204s 0.587 0.122 0.531 0.538 0.892 204s 204s Robust Estimate of Covariance: 204s x1 x2 x3 x4 x5 204s x1 1.00e-02 1.88e-03 3.15e-03 -5.86e-04 -1.63e-03 204s x2 1.88e-03 4.85e-04 1.27e-03 -5.20e-05 2.36e-05 204s x3 3.15e-03 1.27e-03 6.63e-03 -8.71e-04 3.52e-04 204s x4 -5.86e-04 -5.20e-05 -8.71e-04 2.85e-03 1.83e-03 204s x5 -1.63e-03 2.36e-05 3.52e-04 1.83e-03 2.77e-03 204s -------------------------------------------------------- 204s hbk 75 3 39 -1.047858 204s Best subsample: 204s [1] 15 16 17 18 19 20 21 22 23 24 26 27 31 32 33 35 36 37 38 40 43 49 50 51 54 204s [26] 55 56 58 59 61 63 64 66 67 70 71 72 73 74 204s Outliers: 14 204s [1] 1 2 3 4 5 6 7 8 9 10 11 12 13 14 204s ------------- 204s 204s Call: 204s CovMcd(x = x, trace = FALSE) 204s -> Method: Fast MCD(alpha=0.5 ==> h=39); nsamp = 500; (n,k)mini = (300,5) 204s 204s Robust Estimate of Location: 204s X1 X2 X3 204s 1.54 1.78 1.69 204s 204s Robust Estimate of Covariance: 204s X1 X2 X3 204s X1 1.227 0.055 0.127 204s X2 0.055 1.249 0.153 204s X3 0.127 0.153 1.160 204s -------------------------------------------------------- 204s Animals 28 2 15 14.555543 204s Best subsample: 204s [1] 1 3 4 5 10 11 17 18 19 20 21 22 23 26 27 204s Outliers: 14 204s [1] 2 6 7 8 9 12 13 14 15 16 23 24 25 28 204s ------------- 204s 204s Call: 204s CovMcd(x = x, trace = FALSE) 204s -> Method: Fast MCD(alpha=0.5 ==> h=15); nsamp = 500; (n,k)mini = (300,5) 204s 204s Robust Estimate of Location: 204s body brain 204s 18.7 64.9 204s 204s Robust Estimate of Covariance: 204s body brain 204s body 929 1576 204s brain 1576 5646 204s -------------------------------------------------------- 204s bushfire 38 5 22 18.135810 204s Best subsample: 204s [1] 1 2 3 4 5 6 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 204s Outliers: 16 204s [1] 7 8 9 10 11 12 29 30 31 32 33 34 35 36 37 38 204s ------------- 204s 204s Call: 204s CovMcd(x = x, trace = FALSE) 204s -> Method: Fast MCD(alpha=0.5 ==> h=22); nsamp = 500; (n,k)mini = (300,5) 204s 204s Robust Estimate of Location: 204s V1 V2 V3 V4 V5 204s 105 147 274 218 279 204s 204s Robust Estimate of Covariance: 204s V1 V2 V3 V4 V5 204s V1 346 268 -1692 -381 -311 204s V2 268 236 -1125 -230 -194 204s V3 -1692 -1125 9993 2455 1951 204s V4 -381 -230 2455 647 505 204s V5 -311 -194 1951 505 398 204s -------------------------------------------------------- 204s lactic 20 2 11 0.359580 204s Best subsample: 204s [1] 1 2 3 4 5 7 8 9 10 11 12 204s Outliers: 4 204s [1] 17 18 19 20 204s ------------- 204s 204s Call: 204s CovMcd(x = x, trace = FALSE) 204s -> Method: Fast MCD(alpha=0.5 ==> h=11); nsamp = 500; (n,k)mini = (300,5) 204s 204s Robust Estimate of Location: 204s X Y 204s 3.86 5.01 204s 204s Robust Estimate of Covariance: 204s X Y 204s X 10.6 14.6 204s Y 14.6 21.3 204s -------------------------------------------------------- 204s pension 18 2 10 16.675508 204s Best subsample: 204s [1] 1 2 3 4 5 6 8 9 11 12 204s Outliers: 5 204s [1] 14 15 16 17 18 204s ------------- 204s 204s Call: 204s CovMcd(x = x, trace = FALSE) 204s -> Method: Fast MCD(alpha=0.5 ==> h=10); nsamp = 500; (n,k)mini = (300,5) 204s 204s Robust Estimate of Location: 204s Income Reserves 204s 52.3 560.9 204s 204s Robust Estimate of Covariance: 204s Income Reserves 204s Income 1420 11932 204s Reserves 11932 208643 204s -------------------------------------------------------- 204s radarImage 1573 5 789 36.694425 204s Best subsample: 204s Too long... 204s Outliers: 117 204s [1] 164 237 238 242 261 262 351 450 451 462 480 481 509 516 535 204s [16] 542 572 597 620 643 654 669 697 737 802 803 804 818 832 833 204s [31] 834 862 863 864 892 900 939 989 1029 1064 1123 1132 1145 1202 1223 204s [46] 1224 1232 1233 1249 1250 1258 1259 1267 1303 1347 1357 1368 1375 1376 1393 204s [61] 1394 1402 1403 1411 1417 1419 1420 1428 1436 1443 1444 1453 1470 1479 1487 204s [76] 1492 1504 1510 1511 1512 1517 1518 1519 1520 1521 1522 1525 1526 1527 1528 204s [91] 1530 1532 1534 1543 1544 1546 1547 1548 1549 1550 1551 1552 1553 1554 1555 204s [106] 1557 1558 1561 1562 1564 1565 1566 1567 1569 1570 1571 1573 204s ------------- 204s 204s Call: 204s CovMcd(x = x, trace = FALSE) 204s -> Method: Fast MCD(alpha=0.5 ==> h=789); nsamp = 500; (n,k)mini = (300,5) 204s 204s Robust Estimate of Location: 204s X.coord Y.coord Band.1 Band.2 Band.3 204s 52.80 35.12 6.77 18.44 8.90 204s 204s Robust Estimate of Covariance: 204s X.coord Y.coord Band.1 Band.2 Band.3 204s X.coord 123.6 23.0 -361.9 -197.1 -22.5 204s Y.coord 23.0 400.6 34.3 -191.1 -39.1 204s Band.1 -361.9 34.3 27167.9 8178.8 473.7 204s Band.2 -197.1 -191.1 8178.8 26021.8 952.4 204s Band.3 -22.5 -39.1 473.7 952.4 4458.4 204s -------------------------------------------------------- 204s NOxEmissions 8088 4 4046 2.474539 204s Best subsample: 204s Too long... 204s Outliers: 2156 204s Too many to print ... 204s ------------- 204s 204s Call: 204s CovMcd(x = x, trace = FALSE) 204s -> Method: Fast MCD(alpha=0.5 ==> h=4046); nsamp = 500; (n,k)mini = (300,5) 204s 204s Robust Estimate of Location: 204s julday LNOx LNOxEm sqrtWS 204s 168.19 4.73 7.91 1.37 204s 204s Robust Estimate of Covariance: 204s julday LNOx LNOxEm sqrtWS 204s julday 9180.6297 12.0306 0.7219 -10.1273 204s LNOx 12.0306 0.4721 0.1418 -0.1526 204s LNOxEm 0.7219 0.1418 0.2516 0.0438 204s sqrtWS -10.1273 -0.1526 0.0438 0.2073 204s -------------------------------------------------------- 204s vaso 39 2 21 -3.972244 204s Best subsample: 204s [1] 3 4 8 14 18 19 20 21 22 23 24 25 26 27 28 33 34 35 37 38 39 204s Outliers: 4 204s [1] 1 2 17 31 204s ------------- 204s 204s Call: 204s CovMcd(x = x, trace = FALSE) 204s -> Method: Fast MCD(alpha=0.5 ==> h=21); nsamp = 500; (n,k)mini = (300,5) 204s 204s Robust Estimate of Location: 204s Volume Rate 204s 1.16 1.72 204s 204s Robust Estimate of Covariance: 204s Volume Rate 204s Volume 0.313 -0.167 204s Rate -0.167 0.728 204s -------------------------------------------------------- 205s wagnerGrowth 63 6 35 6.572208 205s Best subsample: 205s [1] 2 3 4 5 6 7 9 10 11 12 13 14 16 17 18 20 23 25 27 31 32 35 36 38 44 205s [26] 48 51 52 53 54 55 56 57 60 62 205s Outliers: 13 205s [1] 1 8 15 21 22 28 29 33 42 43 46 50 63 205s ------------- 205s 205s Call: 205s CovMcd(x = x, trace = FALSE) 205s -> Method: Fast MCD(alpha=0.5 ==> h=35); nsamp = 500; (n,k)mini = (300,5) 205s 205s Robust Estimate of Location: 205s Region PA GPA HS GHS y 205s 11.00 33.66 -2.00 2.48 0.31 7.48 205s 205s Robust Estimate of Covariance: 205s Region PA GPA HS GHS y 205s Region 35.5615 17.9337 -0.5337 -0.9545 -0.3093 -14.0090 205s PA 17.9337 27.7333 -4.9017 -1.4174 0.0343 -28.7040 205s GPA -0.5337 -4.9017 5.3410 0.2690 -0.1484 4.0006 205s HS -0.9545 -1.4174 0.2690 0.8662 -0.0454 2.9024 205s GHS -0.3093 0.0343 -0.1484 -0.0454 0.1772 0.7457 205s y -14.0090 -28.7040 4.0006 2.9024 0.7457 82.6877 205s -------------------------------------------------------- 205s fish 159 6 82 8.879005 205s Best subsample: 205s [1] 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 205s [20] 20 21 22 23 24 25 26 27 28 30 32 35 36 37 42 43 44 45 46 205s [39] 47 48 49 50 51 52 53 54 55 56 57 58 59 60 107 109 110 111 113 205s [58] 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 205s [77] 134 135 136 137 138 139 205s Outliers: 63 205s [1] 30 39 40 41 42 62 63 64 65 66 68 69 70 73 74 75 76 77 78 205s [20] 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 205s [39] 98 99 100 101 102 103 104 105 141 143 144 145 147 148 149 150 151 152 153 205s [58] 154 155 156 157 158 159 205s ------------- 205s 205s Call: 205s CovMcd(x = x, trace = FALSE) 205s -> Method: Fast MCD(alpha=0.5 ==> h=82); nsamp = 500; (n,k)mini = (300,5) 205s 205s Robust Estimate of Location: 205s Weight Length1 Length2 Length3 Height Width 205s 329.9 24.5 26.6 29.7 31.1 14.7 205s 205s Robust Estimate of Covariance: 205s Weight Length1 Length2 Length3 Height Width 205s Weight 69082.99 1477.81 1613.64 1992.62 1439.32 -62.12 205s Length1 1477.81 34.68 37.61 45.51 28.82 -1.31 205s Length2 1613.64 37.61 40.88 49.52 31.81 -1.40 205s Length3 1992.62 45.51 49.52 61.16 42.65 -2.25 205s Height 1439.32 28.82 31.81 42.65 46.74 -2.82 205s Width -62.12 -1.31 -1.40 -2.25 -2.82 1.01 205s -------------------------------------------------------- 205s pottery 27 6 17 -10.586933 205s Best subsample: 205s [1] 1 2 4 5 6 9 10 11 13 14 15 19 20 21 22 26 27 205s Outliers: 9 205s [1] 3 8 12 16 17 18 23 24 25 205s ------------- 205s 205s Call: 205s CovMcd(x = x, trace = FALSE) 205s -> Method: Fast MCD(alpha=0.5 ==> h=17); nsamp = 500; (n,k)mini = (300,5) 205s 205s Robust Estimate of Location: 205s SI AL FE MG CA TI 205s 54.983 15.206 9.700 3.817 5.211 0.859 205s 205s Robust Estimate of Covariance: 205s SI AL FE MG CA TI 205s SI 20.58227 2.28743 -0.02039 2.12648 -1.80227 0.08821 205s AL 2.28743 4.03605 -0.63021 -2.49966 0.20842 -0.02038 205s FE -0.02039 -0.63021 0.27803 0.53382 -0.35125 0.01427 205s MG 2.12648 -2.49966 0.53382 2.79561 -0.15786 0.02847 205s CA -1.80227 0.20842 -0.35125 -0.15786 1.23240 -0.03465 205s TI 0.08821 -0.02038 0.01427 0.02847 -0.03465 0.00175 205s -------------------------------------------------------- 205s rice 105 6 56 -14.463986 205s Best subsample: 205s [1] 2 4 6 8 10 12 15 18 21 22 24 29 30 31 32 33 34 36 37 205s [20] 38 41 44 45 47 51 52 53 54 55 59 61 65 67 68 69 70 72 76 205s [39] 78 79 80 81 82 83 84 85 86 92 93 94 95 97 98 99 102 105 205s Outliers: 13 205s [1] 9 14 19 28 40 42 49 58 62 71 75 77 89 205s ------------- 205s 205s Call: 205s CovMcd(x = x, trace = FALSE) 205s -> Method: Fast MCD(alpha=0.5 ==> h=56); nsamp = 500; (n,k)mini = (300,5) 205s 205s Robust Estimate of Location: 205s Favor Appearance Taste Stickiness 205s -0.2731 0.0600 -0.1468 0.0646 205s Toughness Overall_evaluation 205s 0.0894 -0.2192 205s 205s Robust Estimate of Covariance: 205s Favor Appearance Taste Stickiness Toughness 205s Favor 0.388 0.323 0.393 0.389 -0.195 205s Appearance 0.323 0.503 0.494 0.494 -0.270 205s Taste 0.393 0.494 0.640 0.629 -0.361 205s Stickiness 0.389 0.494 0.629 0.815 -0.486 205s Toughness -0.195 -0.270 -0.361 -0.486 0.451 205s Overall_evaluation 0.471 0.575 0.723 0.772 -0.457 205s Overall_evaluation 205s Favor 0.471 205s Appearance 0.575 205s Taste 0.723 205s Stickiness 0.772 205s Toughness -0.457 205s Overall_evaluation 0.882 205s -------------------------------------------------------- 205s un86 73 7 40 17.009322 205s Best subsample: 205s [1] 1 2 9 10 12 14 16 17 18 20 23 24 26 27 31 32 37 39 41 42 45 47 48 49 50 205s [26] 51 52 55 56 60 61 62 63 64 65 67 70 71 72 73 205s Outliers: 30 205s [1] 3 4 5 6 7 8 11 13 15 19 21 22 28 29 30 34 35 36 38 40 43 44 46 53 54 205s [26] 58 59 66 68 69 205s ------------- 205s 205s Call: 205s CovMcd(x = x, trace = FALSE) 205s -> Method: Fast MCD(alpha=0.5 ==> h=40); nsamp = 500; (n,k)mini = (300,5) 205s 205s Robust Estimate of Location: 205s POP MOR CAR DR GNP DEN TB 205s 20.740 71.023 6.435 0.817 1.146 56.754 0.441 205s 205s Robust Estimate of Covariance: 205s POP MOR CAR DR GNP DEN 205s POP 582.4034 224.9343 -12.6722 -1.6729 -3.3664 226.1952 205s MOR 224.9343 2351.3907 -286.9504 -32.0743 -35.5649 -527.4684 205s CAR -12.6722 -286.9504 58.1190 5.7393 6.6365 83.6180 205s DR -1.6729 -32.0743 5.7393 0.8339 0.5977 12.1938 205s GNP -3.3664 -35.5649 6.6365 0.5977 1.4175 13.0709 205s DEN 226.1952 -527.4684 83.6180 12.1938 13.0709 2041.5809 205s TB 0.4002 -1.1807 0.2701 0.0191 0.0058 -0.9346 205s TB 205s POP 0.4002 205s MOR -1.1807 205s CAR 0.2701 205s DR 0.0191 205s GNP 0.0058 205s DEN -0.9346 205s TB 0.0184 205s -------------------------------------------------------- 205s wages 39 10 19 22.994272 205s Best subsample: 205s [1] 1 2 6 7 8 9 10 11 12 13 14 15 17 18 19 25 26 27 28 205s Outliers: 9 205s [1] 4 5 6 24 28 30 32 33 34 205s ------------- 205s 205s Call: 205s CovMcd(x = x, trace = FALSE) 205s -> Method: Fast MCD(alpha=0.5 ==> h=19); nsamp = 500; (n,k)mini = (300,5) 205s 205s Robust Estimate of Location: 205s HRS RATE ERSP ERNO NEIN ASSET AGE DEP 205s 2153.37 2.87 1129.16 297.53 360.58 6876.58 39.48 2.36 205s RACE SCHOOL 205s 38.88 10.17 205s 205s Robust Estimate of Covariance: 205s HRS RATE ERSP ERNO NEIN ASSET 205s HRS 6.12e+03 1.73e+01 -1.67e+03 -2.06e+03 9.10e+03 2.02e+05 205s RATE 1.73e+01 2.52e-01 2.14e+01 -3.54e+00 5.85e+01 1.37e+03 205s ERSP -1.67e+03 2.14e+01 1.97e+04 7.76e+01 -1.71e+03 -1.41e+04 205s ERNO -2.06e+03 -3.54e+00 7.76e+01 2.06e+03 -2.02e+03 -4.83e+04 205s NEIN 9.10e+03 5.85e+01 -1.71e+03 -2.02e+03 2.02e+04 4.54e+05 205s ASSET 2.02e+05 1.37e+03 -1.41e+04 -4.83e+04 4.54e+05 1.03e+07 205s AGE -6.29e+01 -2.61e-01 4.83e+00 2.44e+01 -1.08e+02 -2.46e+03 205s DEP -6.17e+00 -7.05e-02 -2.13e+01 2.29e+00 -1.30e+01 -3.16e+02 205s RACE -2.17e+03 -9.46e+00 7.19e+02 5.59e+02 -3.95e+03 -8.77e+04 205s SCHOOL 7.12e+01 5.87e-01 5.39e+01 -2.14e+01 1.63e+02 3.79e+03 205s AGE DEP RACE SCHOOL 205s HRS -6.29e+01 -6.17e+00 -2.17e+03 7.12e+01 205s RATE -2.61e-01 -7.05e-02 -9.46e+00 5.87e-01 205s ERSP 4.83e+00 -2.13e+01 7.19e+02 5.39e+01 205s ERNO 2.44e+01 2.29e+00 5.59e+02 -2.14e+01 205s NEIN -1.08e+02 -1.30e+01 -3.95e+03 1.63e+02 205s ASSET -2.46e+03 -3.16e+02 -8.77e+04 3.79e+03 205s AGE 1.01e+00 7.03e-02 2.39e+01 -9.52e-01 205s DEP 7.03e-02 4.62e-02 2.72e+00 -1.94e-01 205s RACE 2.39e+01 2.72e+00 8.74e+02 -3.09e+01 205s SCHOOL -9.52e-01 -1.94e-01 -3.09e+01 1.62e+00 205s -------------------------------------------------------- 205s airquality 153 4 58 18.213499 205s Best subsample: 205s [1] 3 22 24 25 28 29 32 33 35 36 37 38 39 40 41 42 43 44 46 205s [20] 47 48 49 50 52 56 57 58 59 60 64 66 67 68 69 71 72 73 74 205s [39] 76 78 80 82 83 84 86 87 89 90 91 92 93 94 95 97 98 105 109 205s [58] 110 205s Outliers: 14 205s [1] 8 9 15 18 20 21 23 24 28 30 48 62 117 148 205s ------------- 205s 205s Call: 205s CovMcd(x = x, trace = FALSE) 205s -> Method: Fast MCD(alpha=0.5 ==> h=58); nsamp = 500; (n,k)mini = (300,5) 205s 205s Robust Estimate of Location: 205s Ozone Solar.R Wind Temp 205s 43.2 192.9 9.6 80.5 205s 205s Robust Estimate of Covariance: 205s Ozone Solar.R Wind Temp 205s Ozone 959.69 771.68 -60.92 198.38 205s Solar.R 771.68 7089.72 -1.72 95.75 205s Wind -60.92 -1.72 10.71 -11.96 205s Temp 198.38 95.75 -11.96 62.78 205s -------------------------------------------------------- 205s attitude 30 7 19 24.442803 205s Best subsample: 205s [1] 2 3 4 5 7 8 10 12 15 17 19 20 22 23 25 27 28 29 30 205s Outliers: 10 205s [1] 1 6 9 13 14 16 18 21 24 26 205s ------------- 205s 205s Call: 205s CovMcd(x = x, trace = FALSE) 205s -> Method: Fast MCD(alpha=0.5 ==> h=19); nsamp = 500; (n,k)mini = (300,5) 205s 205s Robust Estimate of Location: 205s rating complaints privileges learning raises critical 205s 67.1 68.0 52.4 57.6 67.2 77.4 205s advance 205s 43.4 205s 205s Robust Estimate of Covariance: 205s rating complaints privileges learning raises critical advance 205s rating 169.34 127.83 40.48 110.26 91.71 -3.59 53.84 205s complaints 127.83 156.80 52.65 110.97 96.56 7.27 76.03 205s privileges 40.48 52.65 136.91 92.38 69.00 9.53 87.98 205s learning 110.26 110.97 92.38 157.77 112.92 6.74 75.51 205s raises 91.71 96.56 69.00 112.92 112.79 4.91 70.22 205s critical -3.59 7.27 9.53 6.74 4.91 52.25 15.00 205s advance 53.84 76.03 87.98 75.51 70.22 15.00 93.11 205s -------------------------------------------------------- 205s attenu 182 5 86 6.440834 205s Best subsample: 205s [1] 68 69 70 71 72 73 74 75 76 77 79 82 83 84 85 86 87 88 89 205s [20] 90 91 92 101 102 103 104 106 107 109 110 111 112 113 114 115 116 117 118 205s [39] 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 205s [58] 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 205s [77] 157 158 159 160 161 162 163 164 165 166 205s Outliers: 61 205s [1] 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 205s [20] 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 36 37 38 39 205s [39] 40 45 46 47 54 55 56 57 58 59 60 61 64 65 82 97 98 100 101 205s [58] 102 103 104 105 205s ------------- 205s 205s Call: 205s CovMcd(x = x, trace = FALSE) 205s -> Method: Fast MCD(alpha=0.5 ==> h=86); nsamp = 500; (n,k)mini = (300,5) 205s 205s Robust Estimate of Location: 205s event mag station dist accel 205s 18.624 5.752 67.861 22.770 0.141 205s 205s Robust Estimate of Covariance: 205s event mag station dist accel 205s event 1.64e+01 -1.22e+00 5.59e+01 9.98e+00 -8.37e-02 205s mag -1.22e+00 4.13e-01 -3.19e+00 1.35e+00 1.22e-02 205s station 5.59e+01 -3.19e+00 1.03e+03 7.00e+01 5.56e-01 205s dist 9.98e+00 1.35e+00 7.00e+01 2.21e+02 -9.24e-01 205s accel -8.37e-02 1.22e-02 5.56e-01 -9.24e-01 9.62e-03 205s -------------------------------------------------------- 205s USJudgeRatings 43 12 28 -47.889993 205s Best subsample: 205s [1] 1 2 3 4 6 9 10 11 15 16 17 18 19 22 24 25 26 27 28 29 32 33 34 36 37 205s [26] 38 41 43 205s Outliers: 14 205s [1] 5 7 8 12 13 14 20 21 23 30 31 35 40 42 205s ------------- 205s 205s Call: 205s CovMcd(x = x, trace = FALSE) 205s -> Method: Fast MCD(alpha=0.5 ==> h=28); nsamp = 500; (n,k)mini = (300,5) 205s 205s Robust Estimate of Location: 205s CONT INTG DMNR DILG CFMG DECI PREP FAMI ORAL WRIT PHYS RTEN 205s 7.40 8.19 7.80 7.96 7.74 7.82 7.74 7.73 7.57 7.63 8.25 7.94 205s 205s Robust Estimate of Covariance: 205s CONT INTG DMNR DILG CFMG DECI PREP FAMI ORAL 205s CONT 0.852 -0.266 -0.422 -0.155 -0.049 -0.074 -0.117 -0.119 -0.177 205s INTG -0.266 0.397 0.537 0.406 0.340 0.325 0.404 0.409 0.430 205s DMNR -0.422 0.537 0.824 0.524 0.458 0.437 0.520 0.504 0.569 205s DILG -0.155 0.406 0.524 0.486 0.426 0.409 0.506 0.515 0.511 205s CFMG -0.049 0.340 0.458 0.426 0.427 0.403 0.466 0.476 0.478 205s DECI -0.074 0.325 0.437 0.409 0.403 0.396 0.449 0.462 0.460 205s PREP -0.117 0.404 0.520 0.506 0.466 0.449 0.552 0.565 0.551 205s FAMI -0.119 0.409 0.504 0.515 0.476 0.462 0.565 0.594 0.571 205s ORAL -0.177 0.430 0.569 0.511 0.478 0.460 0.551 0.571 0.575 205s WRIT -0.159 0.427 0.549 0.515 0.480 0.461 0.556 0.580 0.574 205s PHYS -0.184 0.269 0.362 0.308 0.298 0.307 0.335 0.358 0.369 205s RTEN -0.260 0.472 0.642 0.519 0.467 0.455 0.539 0.554 0.573 205s WRIT PHYS RTEN 205s CONT -0.159 -0.184 -0.260 205s INTG 0.427 0.269 0.472 205s DMNR 0.549 0.362 0.642 205s DILG 0.515 0.308 0.519 205s CFMG 0.480 0.298 0.467 205s DECI 0.461 0.307 0.455 205s PREP 0.556 0.335 0.539 205s FAMI 0.580 0.358 0.554 205s ORAL 0.574 0.369 0.573 205s WRIT 0.580 0.365 0.567 205s PHYS 0.365 0.300 0.378 205s RTEN 0.567 0.378 0.615 205s -------------------------------------------------------- 205s USArrests 50 4 27 15.391648 205s Best subsample: 205s [1] 4 7 9 12 13 14 15 16 19 21 23 26 27 29 30 32 34 35 36 38 41 42 43 45 46 205s [26] 49 50 205s Outliers: 11 205s [1] 2 3 5 6 10 18 24 28 33 37 47 205s ------------- 205s 205s Call: 205s CovMcd(x = x, trace = FALSE) 205s -> Method: Fast MCD(alpha=0.5 ==> h=27); nsamp = 500; (n,k)mini = (300,5) 205s 205s Robust Estimate of Location: 205s Murder Assault UrbanPop Rape 205s 6.71 145.42 65.06 17.88 205s 205s Robust Estimate of Covariance: 205s Murder Assault UrbanPop Rape 205s Murder 16.1 269.3 20.3 25.2 205s Assault 269.3 6613.0 567.8 453.7 205s UrbanPop 20.3 567.8 225.4 47.7 205s Rape 25.2 453.7 47.7 50.9 205s -------------------------------------------------------- 205s longley 16 7 12 12.747678 205s Best subsample: 205s [1] 5 6 7 8 9 10 11 12 13 14 15 16 205s Outliers: 4 205s [1] 1 2 3 4 205s ------------- 205s 205s Call: 205s CovMcd(x = x, trace = FALSE) 205s -> Method: Fast MCD(alpha=0.5 ==> h=12); nsamp = 500; (n,k)mini = (300,5) 205s 205s Robust Estimate of Location: 205s GNP.deflator GNP Unemployed Armed.Forces Population 205s 106.5 430.6 328.2 295.0 120.2 205s Year Employed 205s 1956.5 66.9 205s 205s Robust Estimate of Covariance: 205s GNP.deflator GNP Unemployed Armed.Forces Population 205s GNP.deflator 108.5 1039.9 1231.9 -465.6 81.4 205s GNP 1039.9 10300.0 11161.6 -4277.6 803.4 205s Unemployed 1231.9 11161.6 19799.4 -5805.6 929.1 205s Armed.Forces -465.6 -4277.6 -5805.6 2805.5 -327.4 205s Population 81.4 803.4 929.1 -327.4 63.5 205s Year 51.6 504.3 595.6 -216.7 39.7 205s Employed 34.2 344.1 323.6 -149.5 26.2 205s Year Employed 205s GNP.deflator 51.6 34.2 205s GNP 504.3 344.1 205s Unemployed 595.6 323.6 205s Armed.Forces -216.7 -149.5 205s Population 39.7 26.2 205s Year 25.1 16.7 205s Employed 16.7 12.4 205s -------------------------------------------------------- 205s Loblolly 84 3 44 4.898174 205s Best subsample: 205s [1] 1 2 4 7 8 10 13 14 19 20 21 25 26 28 31 32 33 34 37 38 39 40 43 44 45 205s [26] 46 49 50 51 55 56 58 61 62 64 67 68 69 73 74 75 79 80 81 205s Outliers: 31 205s [1] 5 6 11 12 15 17 18 23 24 29 30 35 36 41 42 47 48 53 54 59 60 65 66 70 71 205s [26] 72 76 77 78 83 84 205s ------------- 205s 205s Call: 205s CovMcd(x = x, trace = FALSE) 205s -> Method: Fast MCD(alpha=0.5 ==> h=44); nsamp = 500; (n,k)mini = (300,5) 205s 205s Robust Estimate of Location: 205s height age Seed 205s 20.44 8.19 7.72 205s 205s Robust Estimate of Covariance: 205s height age Seed 205s height 247.8 79.5 11.9 205s age 79.5 25.7 3.0 205s Seed 11.9 3.0 17.1 205s -------------------------------------------------------- 205s quakes 1000 4 502 8.274369 205s Best subsample: 205s Too long... 205s Outliers: 265 205s Too many to print ... 205s ------------- 205s 205s Call: 205s CovMcd(x = x, trace = FALSE) 205s -> Method: Fast MCD(alpha=0.5 ==> h=502); nsamp = 500; (n,k)mini = (300,5) 205s 205s Robust Estimate of Location: 205s lat long depth mag 205s -21.31 182.48 361.35 4.54 205s 205s Robust Estimate of Covariance: 205s lat long depth mag 205s lat 1.47e+01 3.53e+00 1.34e+02 -2.52e-01 205s long 3.53e+00 4.55e+00 -3.63e+02 4.36e-02 205s depth 1.34e+02 -3.63e+02 4.84e+04 -1.29e+01 205s mag -2.52e-01 4.36e-02 -1.29e+01 1.38e-01 205s -------------------------------------------------------- 205s ======================================================== 205s > dodata(method="deterministic") 205s 205s Call: dodata(method = "deterministic") 205s Data Set n p Half LOG(obj) Time 205s ======================================================== 205s heart 12 2 7 5.678742 205s Best subsample: 205s [1] 1 3 4 5 7 9 11 205s Outliers: 0 205s Too many to print ... 205s ------------- 205s 205s Call: 205s CovMcd(x = x, nsamp = "deterministic", trace = FALSE) 205s -> Method: Deterministic MCD(alpha=0.5 ==> h=7) 205s 205s Robust Estimate of Location: 205s height weight 205s 38.3 33.1 205s 205s Robust Estimate of Covariance: 205s height weight 205s height 135 259 205s weight 259 564 205s -------------------------------------------------------- 205s starsCYG 47 2 25 -8.028718 205s Best subsample: 205s [1] 1 6 10 12 13 16 23 24 25 26 28 31 32 33 37 38 39 40 41 42 43 44 45 46 47 205s Outliers: 7 205s [1] 7 9 11 14 20 30 34 205s ------------- 205s 205s Call: 205s CovMcd(x = x, nsamp = "deterministic", trace = FALSE) 205s -> Method: Deterministic MCD(alpha=0.5 ==> h=25) 205s 205s Robust Estimate of Location: 205s log.Te log.light 205s 4.41 4.95 205s 205s Robust Estimate of Covariance: 205s log.Te log.light 205s log.Te 0.0132 0.0394 205s log.light 0.0394 0.2743 205s -------------------------------------------------------- 205s phosphor 18 2 10 7.732906 205s Best subsample: 205s [1] 2 4 5 7 8 9 11 12 14 16 205s Outliers: 1 205s [1] 6 205s ------------- 205s 205s Call: 205s CovMcd(x = x, nsamp = "deterministic", trace = FALSE) 205s -> Method: Deterministic MCD(alpha=0.5 ==> h=10) 205s 205s Robust Estimate of Location: 205s inorg organic 205s 12.5 40.8 205s 205s Robust Estimate of Covariance: 205s inorg organic 205s inorg 124 101 205s organic 101 197 205s -------------------------------------------------------- 205s stackloss 21 3 12 6.577286 205s Best subsample: 205s [1] 4 5 6 7 8 9 11 13 16 18 19 20 205s Outliers: 2 205s [1] 1 2 205s ------------- 205s 205s Call: 205s CovMcd(x = x, nsamp = "deterministic", trace = FALSE) 205s -> Method: Deterministic MCD(alpha=0.5 ==> h=12) 205s 205s Robust Estimate of Location: 205s Air.Flow Water.Temp Acid.Conc. 205s 58.4 20.5 86.1 205s 205s Robust Estimate of Covariance: 205s Air.Flow Water.Temp Acid.Conc. 205s Air.Flow 56.28 13.33 26.68 205s Water.Temp 13.33 8.28 6.98 205s Acid.Conc. 26.68 6.98 37.97 205s -------------------------------------------------------- 205s coleman 20 5 13 2.149184 205s Best subsample: 205s [1] 3 4 5 7 8 12 13 14 16 17 18 19 20 205s Outliers: 2 205s [1] 6 10 205s ------------- 205s 205s Call: 205s CovMcd(x = x, nsamp = "deterministic", trace = FALSE) 205s -> Method: Deterministic MCD(alpha=0.5 ==> h=13) 205s 205s Robust Estimate of Location: 205s salaryP fatherWc sstatus teacherSc motherLev 205s 2.76 41.08 2.76 25.01 6.27 205s 205s Robust Estimate of Covariance: 205s salaryP fatherWc sstatus teacherSc motherLev 205s salaryP 0.391 2.956 2.146 0.447 0.110 205s fatherWc 2.956 1358.640 442.724 12.235 32.842 205s sstatus 2.146 442.724 205.590 6.464 11.382 205s teacherSc 0.447 12.235 6.464 1.179 0.510 205s motherLev 0.110 32.842 11.382 0.510 0.919 205s -------------------------------------------------------- 205s salinity 28 3 16 1.940763 205s Best subsample: 205s [1] 1 8 10 12 13 14 15 17 18 20 21 22 25 26 27 28 205s Outliers: 2 205s [1] 5 16 205s ------------- 205s 205s Call: 205s CovMcd(x = x, nsamp = "deterministic", trace = FALSE) 205s -> Method: Deterministic MCD(alpha=0.5 ==> h=16) 205s 205s Robust Estimate of Location: 205s X1 X2 X3 205s 10.50 2.58 23.12 205s 205s Robust Estimate of Covariance: 205s X1 X2 X3 205s X1 10.90243 -0.00457 -1.46156 205s X2 -0.00457 3.85051 -1.94604 205s X3 -1.46156 -1.94604 3.21424 205s -------------------------------------------------------- 205s wood 20 5 13 -35.240819 205s Best subsample: 205s [1] 1 2 3 5 9 11 12 13 14 15 17 18 20 205s Outliers: 4 205s [1] 4 6 8 19 205s ------------- 205s 205s Call: 205s CovMcd(x = x, nsamp = "deterministic", trace = FALSE) 205s -> Method: Deterministic MCD(alpha=0.5 ==> h=13) 205s 205s Robust Estimate of Location: 205s x1 x2 x3 x4 x5 205s 0.582 0.125 0.530 0.534 0.888 205s 205s Robust Estimate of Covariance: 205s x1 x2 x3 x4 x5 205s x1 1.05e-02 1.81e-03 2.08e-03 -6.41e-04 -9.61e-04 205s x2 1.81e-03 5.55e-04 8.76e-04 -2.03e-04 -4.70e-05 205s x3 2.08e-03 8.76e-04 5.60e-03 -1.11e-03 -1.26e-05 205s x4 -6.41e-04 -2.03e-04 -1.11e-03 4.27e-03 2.60e-03 205s x5 -9.61e-04 -4.70e-05 -1.26e-05 2.60e-03 2.95e-03 205s -------------------------------------------------------- 205s hbk 75 3 39 -1.045501 205s Best subsample: 205s [1] 15 17 18 19 20 21 22 23 24 26 27 28 29 32 33 35 36 38 40 41 43 48 49 50 51 205s [26] 54 55 56 58 59 63 64 66 67 70 71 72 73 74 205s Outliers: 14 205s [1] 1 2 3 4 5 6 7 8 9 10 11 12 13 14 205s ------------- 205s 205s Call: 205s CovMcd(x = x, nsamp = "deterministic", trace = FALSE) 205s -> Method: Deterministic MCD(alpha=0.5 ==> h=39) 205s 205s Robust Estimate of Location: 205s X1 X2 X3 205s 1.54 1.78 1.69 205s 205s Robust Estimate of Covariance: 205s X1 X2 X3 205s X1 1.227 0.055 0.127 205s X2 0.055 1.249 0.153 205s X3 0.127 0.153 1.160 205s -------------------------------------------------------- 205s Animals 28 2 15 14.555543 205s Best subsample: 205s [1] 1 3 4 5 10 11 17 18 19 20 21 22 23 26 27 205s Outliers: 14 205s [1] 2 6 7 8 9 12 13 14 15 16 23 24 25 28 205s ------------- 205s 205s Call: 205s CovMcd(x = x, nsamp = "deterministic", trace = FALSE) 205s -> Method: Deterministic MCD(alpha=0.5 ==> h=15) 205s 205s Robust Estimate of Location: 205s body brain 205s 18.7 64.9 205s 205s Robust Estimate of Covariance: 205s body brain 205s body 929 1576 205s brain 1576 5646 205s -------------------------------------------------------- 205s bushfire 38 5 22 18.135810 205s Best subsample: 205s [1] 1 2 3 4 5 6 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 205s Outliers: 16 205s [1] 7 8 9 10 11 12 29 30 31 32 33 34 35 36 37 38 205s ------------- 205s 205s Call: 205s CovMcd(x = x, nsamp = "deterministic", trace = FALSE) 205s -> Method: Deterministic MCD(alpha=0.5 ==> h=22) 205s 205s Robust Estimate of Location: 205s V1 V2 V3 V4 V5 205s 105 147 274 218 279 205s 205s Robust Estimate of Covariance: 205s V1 V2 V3 V4 V5 205s V1 346 268 -1692 -381 -311 205s V2 268 236 -1125 -230 -194 205s V3 -1692 -1125 9993 2455 1951 205s V4 -381 -230 2455 647 505 205s V5 -311 -194 1951 505 398 205s -------------------------------------------------------- 205s lactic 20 2 11 0.359580 205s Best subsample: 205s [1] 1 2 3 4 5 7 8 9 10 11 12 205s Outliers: 4 205s [1] 17 18 19 20 205s ------------- 205s 205s Call: 205s CovMcd(x = x, nsamp = "deterministic", trace = FALSE) 205s -> Method: Deterministic MCD(alpha=0.5 ==> h=11) 205s 205s Robust Estimate of Location: 205s X Y 205s 3.86 5.01 205s 205s Robust Estimate of Covariance: 205s X Y 205s X 10.6 14.6 205s Y 14.6 21.3 205s -------------------------------------------------------- 205s pension 18 2 10 16.675508 205s Best subsample: 205s [1] 1 2 3 4 5 6 8 9 11 12 205s Outliers: 5 205s [1] 14 15 16 17 18 205s ------------- 205s 205s Call: 205s CovMcd(x = x, nsamp = "deterministic", trace = FALSE) 205s -> Method: Deterministic MCD(alpha=0.5 ==> h=10) 205s 205s Robust Estimate of Location: 205s Income Reserves 205s 52.3 560.9 205s 205s Robust Estimate of Covariance: 205s Income Reserves 205s Income 1420 11932 205s Reserves 11932 208643 205s -------------------------------------------------------- 205s radarImage 1573 5 789 36.694865 205s Best subsample: 205s Too long... 205s Outliers: 114 205s [1] 164 237 238 242 261 262 351 450 451 462 463 480 481 509 516 205s [16] 535 542 572 597 620 643 654 669 679 697 737 802 803 804 818 205s [31] 832 833 834 862 863 864 892 900 939 989 1029 1064 1123 1132 1145 205s [46] 1202 1223 1224 1232 1233 1249 1250 1258 1259 1267 1303 1347 1357 1368 1375 205s [61] 1376 1393 1394 1402 1411 1417 1419 1420 1428 1436 1443 1444 1453 1470 1504 205s [76] 1510 1511 1512 1518 1519 1520 1521 1522 1525 1526 1527 1528 1530 1532 1534 205s [91] 1543 1544 1546 1547 1548 1549 1550 1551 1552 1553 1554 1555 1557 1558 1561 205s [106] 1562 1564 1565 1566 1567 1569 1570 1571 1573 205s ------------- 205s 205s Call: 205s CovMcd(x = x, nsamp = "deterministic", trace = FALSE) 205s -> Method: Deterministic MCD(alpha=0.5 ==> h=789) 205s 205s Robust Estimate of Location: 205s X.coord Y.coord Band.1 Band.2 Band.3 205s 52.78 35.37 7.12 18.81 9.09 205s 205s Robust Estimate of Covariance: 205s X.coord Y.coord Band.1 Band.2 Band.3 205s X.coord 123.2 21.5 -363.9 -200.1 -24.3 205s Y.coord 21.5 410.7 46.5 -177.3 -33.4 205s Band.1 -363.9 46.5 27051.1 8138.9 469.3 205s Band.2 -200.1 -177.3 8138.9 25938.0 946.2 205s Band.3 -24.3 -33.4 469.3 946.2 4470.1 205s -------------------------------------------------------- 206s NOxEmissions 8088 4 4046 2.474536 206s Best subsample: 206s Too long... 206s Outliers: 2152 206s Too many to print ... 206s ------------- 206s 206s Call: 206s CovMcd(x = x, nsamp = "deterministic", trace = FALSE) 206s -> Method: Deterministic MCD(alpha=0.5 ==> h=4046) 206s 206s Robust Estimate of Location: 206s julday LNOx LNOxEm sqrtWS 206s 168.20 4.73 7.91 1.37 206s 206s Robust Estimate of Covariance: 206s julday LNOx LNOxEm sqrtWS 206s julday 9176.2934 12.0355 0.7022 -10.1387 206s LNOx 12.0355 0.4736 0.1430 -0.1528 206s LNOxEm 0.7022 0.1430 0.2527 0.0436 206s sqrtWS -10.1387 -0.1528 0.0436 0.2074 206s -------------------------------------------------------- 206s vaso 39 2 21 -3.972244 206s Best subsample: 206s [1] 3 4 8 14 18 19 20 21 22 23 24 25 26 27 28 33 34 35 37 38 39 206s Outliers: 4 206s [1] 1 2 17 31 206s ------------- 206s 206s Call: 206s CovMcd(x = x, nsamp = "deterministic", trace = FALSE) 206s -> Method: Deterministic MCD(alpha=0.5 ==> h=21) 206s 206s Robust Estimate of Location: 206s Volume Rate 206s 1.16 1.72 206s 206s Robust Estimate of Covariance: 206s Volume Rate 206s Volume 0.313 -0.167 206s Rate -0.167 0.728 206s -------------------------------------------------------- 206s wagnerGrowth 63 6 35 6.511864 206s Best subsample: 206s [1] 2 3 4 5 6 7 9 10 11 12 13 16 17 18 20 23 25 27 31 32 35 36 38 41 44 206s [26] 48 51 52 53 54 55 56 57 60 62 206s Outliers: 15 206s [1] 1 8 15 21 22 28 29 33 39 42 43 46 49 50 63 206s ------------- 206s 206s Call: 206s CovMcd(x = x, nsamp = "deterministic", trace = FALSE) 206s -> Method: Deterministic MCD(alpha=0.5 ==> h=35) 206s 206s Robust Estimate of Location: 206s Region PA GPA HS GHS y 206s 10.91 33.65 -2.05 2.43 0.31 6.98 206s 206s Robust Estimate of Covariance: 206s Region PA GPA HS GHS y 206s Region 35.1365 17.7291 -1.4003 -0.6554 -0.4728 -14.9305 206s PA 17.7291 28.4297 -5.5245 -1.2444 -0.0452 -29.6181 206s GPA -1.4003 -5.5245 5.2170 0.3954 -0.2152 3.8252 206s HS -0.6554 -1.2444 0.3954 0.7273 -0.0107 2.1514 206s GHS -0.4728 -0.0452 -0.2152 -0.0107 0.1728 0.8440 206s y -14.9305 -29.6181 3.8252 2.1514 0.8440 79.0511 206s -------------------------------------------------------- 206s fish 159 6 82 8.880459 206s Best subsample: 206s [1] 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 206s [20] 20 21 22 23 24 25 26 27 35 36 37 42 43 44 45 46 47 48 49 206s [39] 50 51 52 53 54 55 56 57 58 59 60 106 107 108 109 110 111 112 113 206s [58] 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 206s [77] 134 135 136 137 138 139 206s Outliers: 64 206s [1] 30 39 40 41 62 63 64 65 66 68 69 70 73 74 75 76 77 78 79 206s [20] 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 206s [39] 99 100 101 102 103 104 105 141 142 143 144 145 146 147 148 149 150 151 152 206s [58] 153 154 155 156 157 158 159 206s ------------- 206s 206s Call: 206s CovMcd(x = x, nsamp = "deterministic", trace = FALSE) 206s -> Method: Deterministic MCD(alpha=0.5 ==> h=82) 206s 206s Robust Estimate of Location: 206s Weight Length1 Length2 Length3 Height Width 206s 316.3 24.1 26.3 29.3 31.0 14.7 206s 206s Robust Estimate of Covariance: 206s Weight Length1 Length2 Length3 Height Width 206s Weight 64662.19 1412.34 1541.95 1917.21 1420.83 -61.15 206s Length1 1412.34 34.14 37.04 45.07 29.25 -1.26 206s Length2 1541.95 37.04 40.26 49.04 32.21 -1.34 206s Length3 1917.21 45.07 49.04 60.82 43.03 -2.15 206s Height 1420.83 29.25 32.21 43.03 46.50 -2.66 206s Width -61.15 -1.26 -1.34 -2.15 -2.66 1.02 206s -------------------------------------------------------- 206s pottery 27 6 17 -10.586933 206s Best subsample: 206s [1] 1 2 4 5 6 9 10 11 13 14 15 19 20 21 22 26 27 206s Outliers: 9 206s [1] 3 8 12 16 17 18 23 24 25 206s ------------- 206s 206s Call: 206s CovMcd(x = x, nsamp = "deterministic", trace = FALSE) 206s -> Method: Deterministic MCD(alpha=0.5 ==> h=17) 206s 206s Robust Estimate of Location: 206s SI AL FE MG CA TI 206s 54.983 15.206 9.700 3.817 5.211 0.859 206s 206s Robust Estimate of Covariance: 206s SI AL FE MG CA TI 206s SI 20.58227 2.28743 -0.02039 2.12648 -1.80227 0.08821 206s AL 2.28743 4.03605 -0.63021 -2.49966 0.20842 -0.02038 206s FE -0.02039 -0.63021 0.27803 0.53382 -0.35125 0.01427 206s MG 2.12648 -2.49966 0.53382 2.79561 -0.15786 0.02847 206s CA -1.80227 0.20842 -0.35125 -0.15786 1.23240 -0.03465 206s TI 0.08821 -0.02038 0.01427 0.02847 -0.03465 0.00175 206s -------------------------------------------------------- 206s rice 105 6 56 -14.423048 206s Best subsample: 206s [1] 4 6 8 10 13 15 16 17 18 25 27 29 30 31 32 33 34 36 37 206s [20] 38 44 45 47 51 52 53 55 59 60 65 66 67 70 72 74 76 78 79 206s [39] 80 81 82 83 84 85 86 90 92 93 94 95 97 98 99 100 101 105 206s Outliers: 13 206s [1] 9 19 28 40 42 43 49 58 62 64 71 75 77 206s ------------- 206s 206s Call: 206s CovMcd(x = x, nsamp = "deterministic", trace = FALSE) 206s -> Method: Deterministic MCD(alpha=0.5 ==> h=56) 206s 206s Robust Estimate of Location: 206s Favor Appearance Taste Stickiness 206s -0.2950 0.0799 -0.1555 0.0363 206s Toughness Overall_evaluation 206s 0.0530 -0.2284 206s 206s Robust Estimate of Covariance: 206s Favor Appearance Taste Stickiness Toughness 206s Favor 0.466 0.389 0.471 0.447 -0.198 206s Appearance 0.389 0.610 0.592 0.570 -0.293 206s Taste 0.471 0.592 0.760 0.718 -0.356 206s Stickiness 0.447 0.570 0.718 0.820 -0.419 206s Toughness -0.198 -0.293 -0.356 -0.419 0.400 206s Overall_evaluation 0.557 0.669 0.838 0.846 -0.425 206s Overall_evaluation 206s Favor 0.557 206s Appearance 0.669 206s Taste 0.838 206s Stickiness 0.846 206s Toughness -0.425 206s Overall_evaluation 0.987 206s -------------------------------------------------------- 206s un86 73 7 40 17.117142 206s Best subsample: 206s [1] 2 9 10 12 14 16 17 18 19 20 23 24 25 26 27 31 32 33 37 39 42 48 49 50 51 206s [26] 52 55 56 57 60 61 62 63 64 65 67 70 71 72 73 206s Outliers: 30 206s [1] 3 4 5 6 7 8 11 13 15 21 22 28 29 30 35 36 38 40 41 43 44 45 46 53 54 206s [26] 58 59 66 68 69 206s ------------- 206s 206s Call: 206s CovMcd(x = x, nsamp = "deterministic", trace = FALSE) 206s -> Method: Deterministic MCD(alpha=0.5 ==> h=40) 206s 206s Robust Estimate of Location: 206s POP MOR CAR DR GNP DEN TB 206s 17.036 68.512 6.444 0.877 1.134 64.140 0.433 206s 206s Robust Estimate of Covariance: 206s POP MOR CAR DR GNP DEN 206s POP 3.61e+02 1.95e+02 -6.28e+00 -1.91e-02 -2.07e+00 5.79e+01 206s MOR 1.95e+02 2.39e+03 -2.79e+02 -3.37e+01 -3.39e+01 -9.21e+02 206s CAR -6.28e+00 -2.79e+02 5.76e+01 5.77e+00 6.59e+00 7.81e+01 206s DR -1.91e-02 -3.37e+01 5.77e+00 9.07e-01 5.66e-01 1.69e+01 206s GNP -2.07e+00 -3.39e+01 6.59e+00 5.66e-01 1.42e+00 9.28e+00 206s DEN 5.79e+01 -9.21e+02 7.81e+01 1.69e+01 9.28e+00 3.53e+03 206s TB -6.09e-02 -9.93e-01 2.50e-01 1.98e-02 6.82e-03 -9.75e-01 206s TB 206s POP -6.09e-02 206s MOR -9.93e-01 206s CAR 2.50e-01 206s DR 1.98e-02 206s GNP 6.82e-03 206s DEN -9.75e-01 206s TB 1.64e-02 206s -------------------------------------------------------- 206s wages 39 10 19 23.119456 206s Best subsample: 206s [1] 1 2 5 6 7 9 10 11 12 13 14 15 19 21 23 25 26 27 28 206s Outliers: 9 206s [1] 4 5 9 24 25 26 28 32 34 206s ------------- 206s 206s Call: 206s CovMcd(x = x, nsamp = "deterministic", trace = FALSE) 206s -> Method: Deterministic MCD(alpha=0.5 ==> h=19) 206s 206s Robust Estimate of Location: 206s HRS RATE ERSP ERNO NEIN ASSET AGE DEP 206s 2161.89 2.95 1114.21 297.68 374.00 7269.37 39.13 2.43 206s RACE SCHOOL 206s 36.13 10.39 206s 206s Robust Estimate of Covariance: 206s HRS RATE ERSP ERNO NEIN ASSET 206s HRS 3.53e+03 8.31e+00 -5.96e+03 -6.43e+02 5.15e+03 1.12e+05 206s RATE 8.31e+00 1.78e-01 8.19e+00 2.70e+00 3.90e+01 8.94e+02 206s ERSP -5.96e+03 8.19e+00 1.90e+04 1.13e+03 -4.73e+03 -9.49e+04 206s ERNO -6.43e+02 2.70e+00 1.13e+03 1.80e+03 -3.56e+02 -7.33e+03 206s NEIN 5.15e+03 3.90e+01 -4.73e+03 -3.56e+02 1.38e+04 3.00e+05 206s ASSET 1.12e+05 8.94e+02 -9.49e+04 -7.33e+03 3.00e+05 6.62e+06 206s AGE -3.33e+01 -6.55e-02 8.33e+01 1.50e+00 -3.28e+01 -7.55e+02 206s DEP 4.50e+00 -4.01e-02 -2.77e+01 1.31e+00 -8.09e+00 -1.61e+02 206s RACE -1.30e+03 -6.06e+00 1.80e+03 1.48e+02 -2.58e+03 -5.59e+04 206s SCHOOL 3.01e+01 3.58e-01 -5.57e+00 2.84e+00 9.26e+01 2.10e+03 206s AGE DEP RACE SCHOOL 206s HRS -3.33e+01 4.50e+00 -1.30e+03 3.01e+01 206s RATE -6.55e-02 -4.01e-02 -6.06e+00 3.58e-01 206s ERSP 8.33e+01 -2.77e+01 1.80e+03 -5.57e+00 206s ERNO 1.50e+00 1.31e+00 1.48e+02 2.84e+00 206s NEIN -3.28e+01 -8.09e+00 -2.58e+03 9.26e+01 206s ASSET -7.55e+02 -1.61e+02 -5.59e+04 2.10e+03 206s AGE 6.57e-01 -1.64e-01 1.13e+01 -2.67e-01 206s DEP -1.64e-01 9.20e-02 2.38e-01 -6.01e-02 206s RACE 1.13e+01 2.38e-01 5.73e+02 -1.67e+01 206s SCHOOL -2.67e-01 -6.01e-02 -1.67e+01 7.95e-01 206s -------------------------------------------------------- 206s airquality 153 4 58 18.316848 206s Best subsample: 206s [1] 2 3 8 10 24 25 28 32 33 35 36 37 38 39 40 41 42 43 46 206s [20] 47 48 49 50 52 54 56 57 58 59 60 66 67 69 71 72 73 76 78 206s [39] 81 82 84 86 87 89 90 91 92 95 97 98 100 101 105 106 108 109 110 206s [58] 111 206s Outliers: 10 206s [1] 8 9 15 18 24 30 48 62 117 148 206s ------------- 206s 206s Call: 206s CovMcd(x = x, nsamp = "deterministic", trace = FALSE) 206s -> Method: Deterministic MCD(alpha=0.5 ==> h=58) 206s 206s Robust Estimate of Location: 206s Ozone Solar.R Wind Temp 206s 40.80 189.37 9.66 78.81 206s 206s Robust Estimate of Covariance: 206s Ozone Solar.R Wind Temp 206s Ozone 935.54 857.76 -56.30 220.48 206s Solar.R 857.76 8507.83 1.36 155.13 206s Wind -56.30 1.36 9.90 -11.61 206s Temp 220.48 155.13 -11.61 84.00 206s -------------------------------------------------------- 206s attitude 30 7 19 24.464288 206s Best subsample: 206s [1] 2 3 4 5 7 8 10 11 12 15 17 19 21 22 23 25 27 28 29 206s Outliers: 8 206s [1] 6 9 13 14 16 18 24 26 206s ------------- 206s 206s Call: 206s CovMcd(x = x, nsamp = "deterministic", trace = FALSE) 206s -> Method: Deterministic MCD(alpha=0.5 ==> h=19) 206s 206s Robust Estimate of Location: 206s rating complaints privileges learning raises critical 206s 64.4 65.2 51.0 55.5 65.9 77.4 206s advance 206s 43.2 206s 206s Robust Estimate of Covariance: 206s rating complaints privileges learning raises critical advance 206s rating 199.95 162.36 115.83 160.44 128.87 -13.55 66.20 206s complaints 162.36 204.84 130.33 170.66 150.19 16.28 96.66 206s privileges 115.83 130.33 181.31 152.63 106.56 4.52 91.44 206s learning 160.44 170.66 152.63 213.06 156.57 9.92 88.31 206s raises 128.87 150.19 106.56 156.57 152.05 23.10 84.00 206s critical -13.55 16.28 4.52 9.92 23.10 80.22 27.15 206s advance 66.20 96.66 91.44 88.31 84.00 27.15 95.51 206s -------------------------------------------------------- 206s attenu 182 5 86 6.593068 206s Best subsample: 206s [1] 41 42 43 44 48 49 51 68 70 72 73 74 75 76 77 82 83 84 85 206s [20] 86 87 88 89 90 91 92 101 102 103 104 106 107 109 110 111 112 113 114 206s [39] 115 116 117 119 120 121 122 124 125 126 127 128 129 130 131 132 133 134 135 206s [58] 136 137 138 139 140 141 144 145 146 147 148 149 150 151 152 153 154 155 156 206s [77] 157 158 159 160 161 162 163 164 165 166 206s Outliers: 49 206s [1] 1 2 4 5 6 7 8 9 10 11 12 13 14 15 16 19 20 21 22 206s [20] 23 24 25 27 28 29 30 31 32 33 40 45 47 59 60 61 64 65 78 206s [39] 82 83 97 98 100 101 102 103 104 105 117 206s ------------- 206s 206s Call: 206s CovMcd(x = x, nsamp = "deterministic", trace = FALSE) 206s -> Method: Deterministic MCD(alpha=0.5 ==> h=86) 206s 206s Robust Estimate of Location: 206s event mag station dist accel 206s 17.122 5.798 63.461 25.015 0.131 206s 206s Robust Estimate of Covariance: 206s event mag station dist accel 206s event 2.98e+01 -1.58e+00 9.49e+01 -8.36e+00 -3.59e-02 206s mag -1.58e+00 4.26e-01 -3.88e+00 3.13e+00 5.30e-03 206s station 9.49e+01 -3.88e+00 1.10e+03 2.60e+01 5.38e-01 206s dist -8.36e+00 3.13e+00 2.60e+01 2.66e+02 -9.23e-01 206s accel -3.59e-02 5.30e-03 5.38e-01 -9.23e-01 7.78e-03 206s -------------------------------------------------------- 206s USJudgeRatings 43 12 28 -47.886937 206s Best subsample: 206s [1] 2 3 4 6 9 10 11 15 16 18 19 22 24 25 26 27 28 29 30 32 33 34 36 37 38 206s [26] 40 41 43 206s Outliers: 14 206s [1] 1 5 7 8 12 13 14 17 20 21 23 31 35 42 206s ------------- 206s 206s Call: 206s CovMcd(x = x, nsamp = "deterministic", trace = FALSE) 206s -> Method: Deterministic MCD(alpha=0.5 ==> h=28) 206s 206s Robust Estimate of Location: 206s CONT INTG DMNR DILG CFMG DECI PREP FAMI ORAL WRIT PHYS RTEN 206s 7.46 8.26 7.88 8.06 7.85 7.92 7.84 7.83 7.67 7.74 8.31 8.03 206s 206s Robust Estimate of Covariance: 206s CONT INTG DMNR DILG CFMG DECI PREP FAMI 206s CONT 0.7363 -0.2916 -0.4193 -0.1943 -0.0555 -0.0690 -0.1703 -0.1727 206s INTG -0.2916 0.4179 0.5511 0.4167 0.3176 0.3102 0.4247 0.4279 206s DMNR -0.4193 0.5511 0.8141 0.5256 0.4092 0.3934 0.5294 0.5094 206s DILG -0.1943 0.4167 0.5256 0.4820 0.3904 0.3819 0.5054 0.5104 206s CFMG -0.0555 0.3176 0.4092 0.3904 0.3595 0.3368 0.4180 0.4206 206s DECI -0.0690 0.3102 0.3934 0.3819 0.3368 0.3310 0.4135 0.4194 206s PREP -0.1703 0.4247 0.5294 0.5054 0.4180 0.4135 0.5647 0.5752 206s FAMI -0.1727 0.4279 0.5094 0.5104 0.4206 0.4194 0.5752 0.6019 206s ORAL -0.2109 0.4453 0.5646 0.5054 0.4200 0.4121 0.5575 0.5735 206s WRIT -0.2033 0.4411 0.5466 0.5087 0.4222 0.4147 0.5592 0.5787 206s PHYS -0.1624 0.2578 0.3163 0.2833 0.2268 0.2362 0.3108 0.3284 206s RTEN -0.2622 0.4872 0.6324 0.5203 0.4145 0.4081 0.5488 0.5595 206s ORAL WRIT PHYS RTEN 206s CONT -0.2109 -0.2033 -0.1624 -0.2622 206s INTG 0.4453 0.4411 0.2578 0.4872 206s DMNR 0.5646 0.5466 0.3163 0.6324 206s DILG 0.5054 0.5087 0.2833 0.5203 206s CFMG 0.4200 0.4222 0.2268 0.4145 206s DECI 0.4121 0.4147 0.2362 0.4081 206s PREP 0.5575 0.5592 0.3108 0.5488 206s FAMI 0.5735 0.5787 0.3284 0.5595 206s ORAL 0.5701 0.5677 0.3283 0.5688 206s WRIT 0.5677 0.5715 0.3268 0.5645 206s PHYS 0.3283 0.3268 0.2302 0.3308 206s RTEN 0.5688 0.5645 0.3308 0.6057 206s -------------------------------------------------------- 206s USArrests 50 4 27 15.438912 206s Best subsample: 206s [1] 4 7 12 13 14 15 16 19 21 23 25 26 27 29 30 32 34 35 36 38 41 43 45 46 48 206s [26] 49 50 206s Outliers: 7 206s [1] 2 5 6 10 24 28 33 206s ------------- 206s 206s Call: 206s CovMcd(x = x, nsamp = "deterministic", trace = FALSE) 206s -> Method: Deterministic MCD(alpha=0.5 ==> h=27) 206s 206s Robust Estimate of Location: 206s Murder Assault UrbanPop Rape 206s 6.91 150.10 65.88 18.75 206s 206s Robust Estimate of Covariance: 206s Murder Assault UrbanPop Rape 206s Murder 17.9 285.4 17.6 25.0 206s Assault 285.4 6572.8 524.9 465.0 206s UrbanPop 17.6 524.9 211.9 50.5 206s Rape 25.0 465.0 50.5 56.4 206s -------------------------------------------------------- 206s longley 16 7 12 12.747678 206s Best subsample: 206s [1] 5 6 7 8 9 10 11 12 13 14 15 16 206s Outliers: 4 206s [1] 1 2 3 4 206s ------------- 206s 206s Call: 206s CovMcd(x = x, nsamp = "deterministic", trace = FALSE) 206s -> Method: Deterministic MCD(alpha=0.5 ==> h=12) 206s 206s Robust Estimate of Location: 206s GNP.deflator GNP Unemployed Armed.Forces Population 206s 106.5 430.6 328.2 295.0 120.2 206s Year Employed 206s 1956.5 66.9 206s 206s Robust Estimate of Covariance: 206s GNP.deflator GNP Unemployed Armed.Forces Population 206s GNP.deflator 108.5 1039.9 1231.9 -465.6 81.4 206s GNP 1039.9 10300.0 11161.6 -4277.6 803.4 206s Unemployed 1231.9 11161.6 19799.4 -5805.6 929.1 206s Armed.Forces -465.6 -4277.6 -5805.6 2805.5 -327.4 206s Population 81.4 803.4 929.1 -327.4 63.5 206s Year 51.6 504.3 595.6 -216.7 39.7 206s Employed 34.2 344.1 323.6 -149.5 26.2 206s Year Employed 206s GNP.deflator 51.6 34.2 206s GNP 504.3 344.1 206s Unemployed 595.6 323.6 206s Armed.Forces -216.7 -149.5 206s Population 39.7 26.2 206s Year 25.1 16.7 206s Employed 16.7 12.4 206s -------------------------------------------------------- 206s Loblolly 84 3 44 4.898174 206s Best subsample: 206s [1] 1 2 4 7 8 10 13 14 19 20 21 25 26 28 31 32 33 34 37 38 39 40 43 44 45 206s [26] 46 49 50 51 55 56 58 61 62 64 67 68 69 73 74 75 79 80 81 206s Outliers: 31 206s [1] 5 6 11 12 15 17 18 23 24 29 30 35 36 41 42 47 48 53 54 59 60 65 66 70 71 206s [26] 72 76 77 78 83 84 206s ------------- 206s 206s Call: 206s CovMcd(x = x, nsamp = "deterministic", trace = FALSE) 206s -> Method: Deterministic MCD(alpha=0.5 ==> h=44) 206s 206s Robust Estimate of Location: 206s height age Seed 206s 20.44 8.19 7.72 206s 206s Robust Estimate of Covariance: 206s height age Seed 206s height 247.8 79.5 11.9 206s age 79.5 25.7 3.0 206s Seed 11.9 3.0 17.1 206s -------------------------------------------------------- 207s quakes 1000 4 502 8.274209 207s Best subsample: 207s Too long... 207s Outliers: 266 207s Too many to print ... 207s ------------- 207s 207s Call: 207s CovMcd(x = x, nsamp = "deterministic", trace = FALSE) 207s -> Method: Deterministic MCD(alpha=0.5 ==> h=502) 207s 207s Robust Estimate of Location: 207s lat long depth mag 207s -21.34 182.47 360.58 4.54 207s 207s Robust Estimate of Covariance: 207s lat long depth mag 207s lat 1.50e+01 3.58e+00 1.37e+02 -2.66e-01 207s long 3.58e+00 4.55e+00 -3.61e+02 4.64e-02 207s depth 1.37e+02 -3.61e+02 4.84e+04 -1.36e+01 207s mag -2.66e-01 4.64e-02 -1.36e+01 1.34e-01 207s -------------------------------------------------------- 207s ======================================================== 207s > dodata(method="exact") 207s 207s Call: dodata(method = "exact") 207s Data Set n p Half LOG(obj) Time 207s ======================================================== 207s heart 12 2 7 5.678742 207s Best subsample: 207s [1] 1 3 4 5 7 9 11 207s Outliers: 0 207s Too many to print ... 207s ------------- 207s 207s Call: 207s CovMcd(x = x, nsamp = "exact", trace = FALSE) 207s -> Method: Fast MCD(alpha=0.5 ==> h=7); nsamp = exact; (n,k)mini = (300,5) 207s 207s Robust Estimate of Location: 207s height weight 207s 38.3 33.1 207s 207s Robust Estimate of Covariance: 207s height weight 207s height 135 259 207s weight 259 564 207s -------------------------------------------------------- 207s starsCYG 47 2 25 -8.031215 207s Best subsample: 207s [1] 1 2 4 6 8 10 12 13 16 24 25 26 28 32 33 37 38 39 40 41 42 43 44 45 46 207s Outliers: 7 207s [1] 7 9 11 14 20 30 34 207s ------------- 207s 207s Call: 207s CovMcd(x = x, nsamp = "exact", trace = FALSE) 207s -> Method: Fast MCD(alpha=0.5 ==> h=25); nsamp = exact; (n,k)mini = (300,5) 207s 207s Robust Estimate of Location: 207s log.Te log.light 207s 4.41 4.95 207s 207s Robust Estimate of Covariance: 207s log.Te log.light 207s log.Te 0.0132 0.0394 207s log.light 0.0394 0.2743 207s -------------------------------------------------------- 207s phosphor 18 2 10 6.878847 207s Best subsample: 207s [1] 3 5 8 9 11 12 13 14 15 17 207s Outliers: 3 207s [1] 1 6 10 207s ------------- 207s 207s Call: 207s CovMcd(x = x, nsamp = "exact", trace = FALSE) 207s -> Method: Fast MCD(alpha=0.5 ==> h=10); nsamp = exact; (n,k)mini = (300,5) 207s 207s Robust Estimate of Location: 207s inorg organic 207s 13.4 38.8 207s 207s Robust Estimate of Covariance: 207s inorg organic 207s inorg 129 130 207s organic 130 182 207s -------------------------------------------------------- 207s coleman 20 5 13 1.286808 207s Best subsample: 207s [1] 2 3 4 5 7 8 12 13 14 16 17 19 20 207s Outliers: 7 207s [1] 1 6 9 10 11 15 18 207s ------------- 207s 207s Call: 207s CovMcd(x = x, nsamp = "exact", trace = FALSE) 207s -> Method: Fast MCD(alpha=0.5 ==> h=13); nsamp = exact; (n,k)mini = (300,5) 207s 207s Robust Estimate of Location: 207s salaryP fatherWc sstatus teacherSc motherLev 207s 2.76 48.38 6.12 25.00 6.40 207s 207s Robust Estimate of Covariance: 207s salaryP fatherWc sstatus teacherSc motherLev 207s salaryP 0.253 1.786 -0.266 0.151 0.075 207s fatherWc 1.786 1303.382 330.496 12.604 34.503 207s sstatus -0.266 330.496 119.888 3.833 10.131 207s teacherSc 0.151 12.604 3.833 0.785 0.555 207s motherLev 0.075 34.503 10.131 0.555 1.043 207s -------------------------------------------------------- 207s salinity 28 3 16 1.326364 207s Best subsample: 207s [1] 1 2 6 7 8 12 13 14 18 20 21 22 25 26 27 28 207s Outliers: 4 207s [1] 5 16 23 24 207s ------------- 207s 207s Call: 207s CovMcd(x = x, nsamp = "exact", trace = FALSE) 207s -> Method: Fast MCD(alpha=0.5 ==> h=16); nsamp = exact; (n,k)mini = (300,5) 207s 207s Robust Estimate of Location: 207s X1 X2 X3 207s 10.08 2.78 22.78 207s 207s Robust Estimate of Covariance: 207s X1 X2 X3 207s X1 10.44 1.01 -3.19 207s X2 1.01 3.83 -1.44 207s X3 -3.19 -1.44 2.39 207s -------------------------------------------------------- 207s wood 20 5 13 -36.270094 207s Best subsample: 207s [1] 1 2 3 5 9 10 12 13 14 15 17 18 20 207s Outliers: 7 207s [1] 4 6 7 8 11 16 19 207s ------------- 207s 207s Call: 207s CovMcd(x = x, nsamp = "exact", trace = FALSE) 207s -> Method: Fast MCD(alpha=0.5 ==> h=13); nsamp = exact; (n,k)mini = (300,5) 207s 207s Robust Estimate of Location: 207s x1 x2 x3 x4 x5 207s 0.587 0.122 0.531 0.538 0.892 207s 207s Robust Estimate of Covariance: 207s x1 x2 x3 x4 x5 207s x1 1.00e-02 1.88e-03 3.15e-03 -5.86e-04 -1.63e-03 207s x2 1.88e-03 4.85e-04 1.27e-03 -5.20e-05 2.36e-05 207s x3 3.15e-03 1.27e-03 6.63e-03 -8.71e-04 3.52e-04 207s x4 -5.86e-04 -5.20e-05 -8.71e-04 2.85e-03 1.83e-03 207s x5 -1.63e-03 2.36e-05 3.52e-04 1.83e-03 2.77e-03 207s -------------------------------------------------------- 207s Animals 28 2 15 14.555543 207s Best subsample: 207s [1] 1 3 4 5 10 11 17 18 19 20 21 22 23 26 27 207s Outliers: 14 207s [1] 2 6 7 8 9 12 13 14 15 16 23 24 25 28 207s ------------- 207s 207s Call: 207s CovMcd(x = x, nsamp = "exact", trace = FALSE) 207s -> Method: Fast MCD(alpha=0.5 ==> h=15); nsamp = exact; (n,k)mini = (300,5) 207s 207s Robust Estimate of Location: 207s body brain 207s 18.7 64.9 207s 207s Robust Estimate of Covariance: 207s body brain 207s body 929 1576 207s brain 1576 5646 207s -------------------------------------------------------- 207s lactic 20 2 11 0.359580 207s Best subsample: 207s [1] 1 2 3 4 5 7 8 9 10 11 12 207s Outliers: 4 207s [1] 17 18 19 20 207s ------------- 207s 207s Call: 207s CovMcd(x = x, nsamp = "exact", trace = FALSE) 207s -> Method: Fast MCD(alpha=0.5 ==> h=11); nsamp = exact; (n,k)mini = (300,5) 207s 207s Robust Estimate of Location: 207s X Y 207s 3.86 5.01 207s 207s Robust Estimate of Covariance: 207s X Y 207s X 10.6 14.6 207s Y 14.6 21.3 207s -------------------------------------------------------- 207s pension 18 2 10 16.675508 207s Best subsample: 207s [1] 1 2 3 4 5 6 8 9 11 12 207s Outliers: 5 207s [1] 14 15 16 17 18 207s ------------- 207s 207s Call: 207s CovMcd(x = x, nsamp = "exact", trace = FALSE) 207s -> Method: Fast MCD(alpha=0.5 ==> h=10); nsamp = exact; (n,k)mini = (300,5) 207s 207s Robust Estimate of Location: 207s Income Reserves 207s 52.3 560.9 207s 207s Robust Estimate of Covariance: 207s Income Reserves 207s Income 1420 11932 207s Reserves 11932 208643 207s -------------------------------------------------------- 207s vaso 39 2 21 -3.972244 207s Best subsample: 207s [1] 3 4 8 14 18 19 20 21 22 23 24 25 26 27 28 33 34 35 37 38 39 207s Outliers: 4 207s [1] 1 2 17 31 207s ------------- 207s 207s Call: 207s CovMcd(x = x, nsamp = "exact", trace = FALSE) 207s -> Method: Fast MCD(alpha=0.5 ==> h=21); nsamp = exact; (n,k)mini = (300,5) 207s 207s Robust Estimate of Location: 207s Volume Rate 207s 1.16 1.72 207s 207s Robust Estimate of Covariance: 207s Volume Rate 207s Volume 0.313 -0.167 207s Rate -0.167 0.728 207s -------------------------------------------------------- 207s stackloss 21 3 12 5.472581 207s Best subsample: 207s [1] 4 5 6 7 8 9 10 11 12 13 14 20 207s Outliers: 9 207s [1] 1 2 3 15 16 17 18 19 21 207s ------------- 207s 207s Call: 207s CovMcd(x = x, nsamp = "exact", trace = FALSE) 207s -> Method: Fast MCD(alpha=0.5 ==> h=12); nsamp = exact; (n,k)mini = (300,5) 207s 207s Robust Estimate of Location: 207s Air.Flow Water.Temp Acid.Conc. 207s 59.5 20.8 87.3 207s 207s Robust Estimate of Covariance: 207s Air.Flow Water.Temp Acid.Conc. 207s Air.Flow 6.29 5.85 5.74 207s Water.Temp 5.85 9.23 6.14 207s Acid.Conc. 5.74 6.14 23.25 207s -------------------------------------------------------- 207s pilot 20 2 11 6.487287 207s Best subsample: 207s [1] 2 3 6 7 9 12 15 16 17 18 20 207s Outliers: 0 207s Too many to print ... 207s ------------- 207s 207s Call: 207s CovMcd(x = x, nsamp = "exact", trace = FALSE) 207s -> Method: Fast MCD(alpha=0.5 ==> h=11); nsamp = exact; (n,k)mini = (300,5) 207s 207s Robust Estimate of Location: 207s X Y 207s 101.1 67.7 207s 207s Robust Estimate of Covariance: 207s X Y 207s X 3344 1070 207s Y 1070 343 207s -------------------------------------------------------- 207s ======================================================== 207s > dodata(method="MRCD") 207s 207s Call: dodata(method = "MRCD") 207s Data Set n p Half LOG(obj) Time 207s ======================================================== 207s heart 12 2 6 7.446266 207s Best subsample: 207s [1] 1 3 4 7 9 11 207s Outliers: 0 207s Too many to print ... 207s ------------- 207s 207s Call: 207s CovMrcd(x = x, trace = FALSE) 207s -> Method: Minimum Regularized Covariance Determinant MRCD(alpha=0.5 ==> h=6) 207s 207s Robust Estimate of Location: 207s height weight 207s 38.8 33.0 207s 207s Robust Estimate of Covariance: 207s height weight 207s height 47.4 75.2 207s weight 75.2 155.4 207s -------------------------------------------------------- 207s starsCYG 47 2 24 -5.862050 207s Best subsample: 207s [1] 1 6 10 12 13 16 23 24 25 26 28 31 33 37 38 39 40 41 42 43 44 45 46 47 207s Outliers: 0 207s Too many to print ... 207s ------------- 207s 207s Call: 207s CovMrcd(x = x, trace = FALSE) 207s -> Method: Minimum Regularized Covariance Determinant MRCD(alpha=0.5 ==> h=24) 207s 207s Robust Estimate of Location: 207s log.Te log.light 207s 4.44 5.05 207s 207s Robust Estimate of Covariance: 207s log.Te log.light 207s log.Te 0.00867 0.02686 207s log.light 0.02686 0.41127 207s -------------------------------------------------------- 207s phosphor 18 2 9 9.954788 207s Best subsample: 207s [1] 4 7 8 9 11 12 13 14 16 207s Outliers: 0 207s Too many to print ... 207s ------------- 207s 207s Call: 207s CovMrcd(x = x, trace = FALSE) 207s -> Method: Minimum Regularized Covariance Determinant MRCD(alpha=0.5 ==> h=9) 207s 207s Robust Estimate of Location: 207s inorg organic 207s 12.5 39.0 207s 207s Robust Estimate of Covariance: 207s inorg organic 207s inorg 236 140 207s organic 140 172 207s -------------------------------------------------------- 207s stackloss 21 3 11 7.991165 207s Best subsample: 207s [1] 4 5 6 7 8 9 10 13 18 19 20 207s Outliers: 0 207s Too many to print ... 207s ------------- 207s 207s Call: 207s CovMrcd(x = x, trace = FALSE) 207s -> Method: Minimum Regularized Covariance Determinant MRCD(alpha=0.5 ==> h=11) 207s 207s Robust Estimate of Location: 207s Air.Flow Water.Temp Acid.Conc. 207s 58.2 21.4 85.2 207s 207s Robust Estimate of Covariance: 207s Air.Flow Water.Temp Acid.Conc. 207s Air.Flow 49.8 17.2 42.7 207s Water.Temp 17.2 13.8 25.2 207s Acid.Conc. 42.7 25.2 58.2 207s -------------------------------------------------------- 207s coleman 20 5 10 5.212156 207s Best subsample: 207s [1] 3 4 5 7 8 9 14 16 19 20 207s Outliers: 0 207s Too many to print ... 207s ------------- 207s 207s Call: 207s CovMrcd(x = x, trace = FALSE) 207s -> Method: Minimum Regularized Covariance Determinant MRCD(alpha=0.5 ==> h=10) 207s 207s Robust Estimate of Location: 207s salaryP fatherWc sstatus teacherSc motherLev 207s 2.78 59.44 9.28 25.41 6.70 207s 207s Robust Estimate of Covariance: 207s salaryP fatherWc sstatus teacherSc motherLev 207s salaryP 0.1582 -0.2826 0.4112 0.1754 0.0153 207s fatherWc -0.2826 902.9210 201.5815 -2.1236 18.8736 207s sstatus 0.4112 201.5815 65.4580 -0.3876 4.7794 207s teacherSc 0.1754 -2.1236 -0.3876 0.7233 -0.0322 207s motherLev 0.0153 18.8736 4.7794 -0.0322 0.5417 207s -------------------------------------------------------- 207s salinity 28 3 14 3.586919 207s Best subsample: 207s [1] 1 7 8 12 13 14 18 20 21 22 25 26 27 28 207s Outliers: 0 207s Too many to print ... 207s ------------- 207s 207s Call: 207s CovMrcd(x = x, trace = FALSE) 207s -> Method: Minimum Regularized Covariance Determinant MRCD(alpha=0.5 ==> h=14) 207s 207s Robust Estimate of Location: 207s X1 X2 X3 207s 10.95 3.71 21.99 207s 207s Robust Estimate of Covariance: 207s X1 X2 X3 207s X1 14.153 0.718 -3.359 207s X2 0.718 3.565 -0.722 207s X3 -3.359 -0.722 1.607 207s -------------------------------------------------------- 207s wood 20 5 10 -33.100492 207s Best subsample: 207s [1] 1 2 3 5 11 14 15 17 18 20 207s Outliers: 0 207s Too many to print ... 207s ------------- 207s 207s Call: 207s CovMrcd(x = x, trace = FALSE) 207s -> Method: Minimum Regularized Covariance Determinant MRCD(alpha=0.5 ==> h=10) 207s 207s Robust Estimate of Location: 207s x1 x2 x3 x4 x5 207s 0.572 0.120 0.504 0.545 0.899 207s 207s Robust Estimate of Covariance: 207s x1 x2 x3 x4 x5 207s x1 0.007543 0.001720 0.000412 -0.001230 -0.001222 207s x2 0.001720 0.000568 0.000355 -0.000533 -0.000132 207s x3 0.000412 0.000355 0.002478 0.000190 0.000811 207s x4 -0.001230 -0.000533 0.000190 0.002327 0.000967 207s x5 -0.001222 -0.000132 0.000811 0.000967 0.001894 207s -------------------------------------------------------- 207s hbk 75 3 38 1.539545 207s Best subsample: 207s [1] 15 17 18 19 20 21 22 23 24 26 27 29 32 33 35 36 38 40 41 43 48 49 50 51 54 207s [26] 55 56 58 59 63 64 66 67 70 71 72 73 74 207s Outliers: 0 207s Too many to print ... 207s ------------- 207s 207s Call: 207s CovMrcd(x = x, trace = FALSE) 207s -> Method: Minimum Regularized Covariance Determinant MRCD(alpha=0.5 ==> h=38) 207s 207s Robust Estimate of Location: 207s X1 X2 X3 207s 1.60 2.37 1.64 207s 207s Robust Estimate of Covariance: 207s X1 X2 X3 207s X1 2.810 0.124 1.248 207s X2 0.124 1.017 0.208 207s X3 1.248 0.208 2.218 207s -------------------------------------------------------- 207s Animals 28 2 14 16.278395 207s Best subsample: 207s [1] 1 3 4 5 10 11 18 19 20 21 22 23 26 27 207s Outliers: 0 207s Too many to print ... 207s ------------- 207s 207s Call: 207s CovMrcd(x = x, trace = FALSE) 207s -> Method: Minimum Regularized Covariance Determinant MRCD(alpha=0.5 ==> h=14) 207s 207s Robust Estimate of Location: 207s body brain 207s 19.5 56.8 207s 207s Robust Estimate of Covariance: 207s body brain 207s body 2802 5179 207s brain 5179 13761 207s -------------------------------------------------------- 207s bushfire 38 5 19 28.483413 207s Best subsample: 207s [1] 1 2 3 4 5 14 15 16 17 18 19 20 21 22 23 24 25 26 27 207s Outliers: 0 207s Too many to print ... 207s ------------- 207s 207s Call: 207s CovMrcd(x = x, trace = FALSE) 207s -> Method: Minimum Regularized Covariance Determinant MRCD(alpha=0.5 ==> h=19) 207s 207s Robust Estimate of Location: 207s V1 V2 V3 V4 V5 207s 103 145 287 221 281 207s 207s Robust Estimate of Covariance: 207s V1 V2 V3 V4 V5 207s V1 366 249 -1993 -503 -396 207s V2 249 252 -1223 -291 -233 207s V3 -1993 -1223 14246 3479 2718 207s V4 -503 -291 3479 1083 748 207s V5 -396 -233 2718 748 660 207s -------------------------------------------------------- 207s lactic 20 2 10 2.593141 207s Best subsample: 207s [1] 1 2 3 4 5 7 8 9 10 11 207s Outliers: 0 207s Too many to print ... 207s ------------- 207s 207s Call: 207s CovMrcd(x = x, trace = FALSE) 207s -> Method: Minimum Regularized Covariance Determinant MRCD(alpha=0.5 ==> h=10) 207s 207s Robust Estimate of Location: 207s X Y 207s 2.60 3.63 207s 207s Robust Estimate of Covariance: 207s X Y 207s X 8.13 13.54 207s Y 13.54 24.17 207s -------------------------------------------------------- 207s pension 18 2 9 18.931204 207s Best subsample: 207s [1] 2 3 4 5 6 8 9 11 12 207s Outliers: 0 207s Too many to print ... 207s ------------- 207s 207s Call: 207s CovMrcd(x = x, trace = FALSE) 207s -> Method: Minimum Regularized Covariance Determinant MRCD(alpha=0.5 ==> h=9) 207s 207s Robust Estimate of Location: 207s Income Reserves 207s 45.7 466.9 207s 207s Robust Estimate of Covariance: 207s Income Reserves 207s Income 2127 23960 207s Reserves 23960 348275 207s -------------------------------------------------------- 207s vaso 39 2 20 -1.864710 207s Best subsample: 207s [1] 3 4 8 14 18 20 21 22 23 24 25 26 27 28 33 34 35 37 38 39 207s Outliers: 0 207s Too many to print ... 207s ------------- 207s 207s Call: 207s CovMrcd(x = x, trace = FALSE) 207s -> Method: Minimum Regularized Covariance Determinant MRCD(alpha=0.5 ==> h=20) 207s 207s Robust Estimate of Location: 207s Volume Rate 207s 1.14 1.77 207s 207s Robust Estimate of Covariance: 207s Volume Rate 207s Volume 0.44943 -0.00465 207s Rate -0.00465 0.34480 207s -------------------------------------------------------- 207s wagnerGrowth 63 6 32 9.287760 207s Best subsample: 207s [1] 2 3 4 5 6 7 9 10 11 12 16 18 20 23 25 27 31 32 35 36 38 41 44 48 52 207s [26] 53 54 55 56 57 60 62 207s Outliers: 0 207s Too many to print ... 207s ------------- 207s 207s Call: 207s CovMrcd(x = x, trace = FALSE) 207s -> Method: Minimum Regularized Covariance Determinant MRCD(alpha=0.5 ==> h=32) 207s 207s Robust Estimate of Location: 207s Region PA GPA HS GHS y 207s 10.719 33.816 -2.144 2.487 0.293 4.918 207s 207s Robust Estimate of Covariance: 207s Region PA GPA HS GHS y 207s Region 56.7128 17.4919 -2.9710 -0.6491 -0.4545 -10.4287 207s PA 17.4919 29.9968 -7.6846 -1.3141 0.5418 -35.6434 207s GPA -2.9710 -7.6846 6.3238 1.1257 -0.4757 12.4707 207s HS -0.6491 -1.3141 1.1257 1.1330 -0.0915 3.3617 207s GHS -0.4545 0.5418 -0.4757 -0.0915 0.1468 -1.1228 207s y -10.4287 -35.6434 12.4707 3.3617 -1.1228 67.4215 207s -------------------------------------------------------- 207s fish 159 6 79 22.142828 207s Best subsample: 207s [1] 2 3 4 5 6 7 8 9 10 11 12 14 15 16 17 18 19 20 21 207s [20] 22 23 24 25 26 27 35 36 37 42 43 44 45 46 47 48 49 50 51 207s [39] 52 53 54 55 56 57 58 59 60 71 105 106 107 109 110 111 113 114 115 207s [58] 116 117 118 119 120 122 123 124 125 126 127 128 129 130 131 132 134 135 136 207s [77] 137 138 139 207s Outliers: 0 207s Too many to print ... 207s ------------- 207s 207s Call: 207s CovMrcd(x = x, trace = FALSE) 207s -> Method: Minimum Regularized Covariance Determinant MRCD(alpha=0.5 ==> h=79) 207s 207s Robust Estimate of Location: 207s Weight Length1 Length2 Length3 Height Width 207s 291.7 23.8 25.9 28.9 30.4 14.7 207s 207s Robust Estimate of Covariance: 207s Weight Length1 Length2 Length3 Height Width 207s Weight 77155.07 1567.55 1713.74 2213.16 1912.62 -103.97 207s Length1 1567.55 45.66 41.57 52.14 38.66 -2.39 207s Length2 1713.74 41.57 54.26 56.77 42.72 -2.55 207s Length3 2213.16 52.14 56.77 82.57 58.84 -3.65 207s Height 1912.62 38.66 42.72 58.84 70.51 -3.80 207s Width -103.97 -2.39 -2.55 -3.65 -3.80 1.19 207s -------------------------------------------------------- 207s pottery 27 6 14 -6.897459 207s Best subsample: 207s [1] 1 2 4 5 6 10 11 13 14 15 19 21 22 26 207s Outliers: 0 207s Too many to print ... 207s ------------- 207s 207s Call: 207s CovMrcd(x = x, trace = FALSE) 207s -> Method: Minimum Regularized Covariance Determinant MRCD(alpha=0.5 ==> h=14) 207s 207s Robust Estimate of Location: 207s SI AL FE MG CA TI 207s 54.39 14.93 9.78 3.82 5.11 0.86 207s 207s Robust Estimate of Covariance: 207s SI AL FE MG CA TI 207s SI 17.47469 -0.16656 0.39943 4.48192 -0.71153 0.06515 207s AL -0.16656 3.93154 -0.35738 -2.29899 0.14770 -0.02050 207s FE 0.39943 -0.35738 0.20434 0.37562 -0.22460 0.00943 207s MG 4.48192 -2.29899 0.37562 2.82339 -0.16027 0.02943 207s CA -0.71153 0.14770 -0.22460 -0.16027 0.88443 -0.01711 207s TI 0.06515 -0.02050 0.00943 0.02943 -0.01711 0.00114 207s -------------------------------------------------------- 208s rice 105 6 53 -8.916472 208s Best subsample: 208s [1] 4 6 8 10 13 15 16 17 18 25 27 29 30 31 32 33 34 36 37 208s [20] 38 44 45 47 51 52 53 54 55 59 60 65 67 70 72 76 79 80 81 208s [39] 82 83 84 85 86 90 92 93 94 95 97 98 99 101 105 208s Outliers: 0 208s Too many to print ... 208s ------------- 208s 208s Call: 208s CovMrcd(x = x, trace = FALSE) 208s -> Method: Minimum Regularized Covariance Determinant MRCD(alpha=0.5 ==> h=53) 208s 208s Robust Estimate of Location: 208s Favor Appearance Taste Stickiness 208s -0.1741 0.0774 -0.0472 0.1868 208s Toughness Overall_evaluation 208s -0.0346 -0.0683 208s 208s Robust Estimate of Covariance: 208s Favor Appearance Taste Stickiness Toughness 208s Favor 0.402 0.306 0.378 0.364 -0.134 208s Appearance 0.306 0.508 0.474 0.407 -0.146 208s Taste 0.378 0.474 0.708 0.611 -0.258 208s Stickiness 0.364 0.407 0.611 0.795 -0.320 208s Toughness -0.134 -0.146 -0.258 -0.320 0.302 208s Overall_evaluation 0.453 0.536 0.746 0.745 -0.327 208s Overall_evaluation 208s Favor 0.453 208s Appearance 0.536 208s Taste 0.746 208s Stickiness 0.745 208s Toughness -0.327 208s Overall_evaluation 0.963 208s -------------------------------------------------------- 208s un86 73 7 37 19.832993 208s Best subsample: 208s [1] 9 10 12 14 16 17 18 20 23 24 25 26 27 31 32 33 37 39 42 48 49 50 51 52 55 208s [26] 56 57 60 62 63 64 65 67 70 71 72 73 208s Outliers: 0 208s Too many to print ... 208s ------------- 208s 208s Call: 208s CovMrcd(x = x, trace = FALSE) 208s -> Method: Minimum Regularized Covariance Determinant MRCD(alpha=0.5 ==> h=37) 208s 208s Robust Estimate of Location: 208s POP MOR CAR DR GNP DEN TB 208s 14.462 66.892 6.670 0.858 1.251 55.518 0.429 208s 208s Robust Estimate of Covariance: 208s POP MOR CAR DR GNP DEN 208s POP 3.00e+02 1.58e+02 9.83e+00 2.74e+00 5.51e-01 6.87e+01 208s MOR 1.58e+02 2.96e+03 -4.24e+02 -4.72e+01 -5.40e+01 -1.01e+03 208s CAR 9.83e+00 -4.24e+02 9.12e+01 8.71e+00 1.13e+01 1.96e+02 208s DR 2.74e+00 -4.72e+01 8.71e+00 1.25e+00 1.03e+00 2.74e+01 208s GNP 5.51e-01 -5.40e+01 1.13e+01 1.03e+00 2.31e+00 2.36e+01 208s DEN 6.87e+01 -1.01e+03 1.96e+02 2.74e+01 2.36e+01 3.12e+03 208s TB 2.04e-02 -1.81e+00 3.42e-01 2.57e-02 2.09e-02 -6.88e-01 208s TB 208s POP 2.04e-02 208s MOR -1.81e+00 208s CAR 3.42e-01 208s DR 2.57e-02 208s GNP 2.09e-02 208s DEN -6.88e-01 208s TB 2.59e-02 208s -------------------------------------------------------- 208s wages 39 10 14 35.698016 208s Best subsample: 208s [1] 1 2 5 6 9 10 11 13 15 19 23 25 26 28 208s Outliers: 0 208s Too many to print ... 208s ------------- 208s 208s Call: 208s CovMrcd(x = x, trace = FALSE) 208s -> Method: Minimum Regularized Covariance Determinant MRCD(alpha=0.5 ==> h=14) 208s 208s Robust Estimate of Location: 208s HRS RATE ERSP ERNO NEIN ASSET AGE DEP 208s 2167.71 2.96 1113.50 300.43 382.29 7438.00 39.06 2.41 208s RACE SCHOOL 208s 33.00 10.45 208s 208s Robust Estimate of Covariance: 208s HRS RATE ERSP ERNO NEIN ASSET 208s HRS 1.97e+03 -4.14e-01 -4.71e+03 -6.58e+02 1.81e+03 3.84e+04 208s RATE -4.14e-01 1.14e-01 1.79e+01 3.08e+00 1.40e+01 3.57e+02 208s ERSP -4.71e+03 1.79e+01 1.87e+04 2.33e+03 -2.06e+03 -3.57e+04 208s ERNO -6.58e+02 3.08e+00 2.33e+03 5.36e+02 -3.42e+02 -5.56e+03 208s NEIN 1.81e+03 1.40e+01 -2.06e+03 -3.42e+02 5.77e+03 1.10e+05 208s ASSET 3.84e+04 3.57e+02 -3.57e+04 -5.56e+03 1.10e+05 2.86e+06 208s AGE -1.83e+01 1.09e-02 6.69e+01 8.78e+00 -5.07e+00 -1.51e+02 208s DEP 4.82e+00 -3.14e-02 -2.52e+01 -2.96e+00 -5.33e+00 -1.03e+02 208s RACE -5.67e+02 -1.33e+00 1.21e+03 1.81e+02 -9.13e+02 -1.96e+04 208s SCHOOL 5.33e+00 1.87e-01 1.86e+01 3.12e+00 3.20e+01 7.89e+02 208s AGE DEP RACE SCHOOL 208s HRS -1.83e+01 4.82e+00 -5.67e+02 5.33e+00 208s RATE 1.09e-02 -3.14e-02 -1.33e+00 1.87e-01 208s ERSP 6.69e+01 -2.52e+01 1.21e+03 1.86e+01 208s ERNO 8.78e+00 -2.96e+00 1.81e+02 3.12e+00 208s NEIN -5.07e+00 -5.33e+00 -9.13e+02 3.20e+01 208s ASSET -1.51e+02 -1.03e+02 -1.96e+04 7.89e+02 208s AGE 5.71e-01 -1.56e-01 4.58e+00 -5.00e-02 208s DEP -1.56e-01 8.08e-02 -3.02e-01 -4.47e-02 208s RACE 4.58e+00 -3.02e-01 2.36e+02 -4.54e+00 208s SCHOOL -5.00e-02 -4.47e-02 -4.54e+00 4.23e-01 208s -------------------------------------------------------- 208s airquality 153 4 56 21.136376 208s Best subsample: 208s [1] 2 3 8 10 24 25 28 32 33 35 36 37 38 39 40 41 42 43 46 208s [20] 47 48 49 52 54 56 57 58 59 60 66 67 69 71 72 73 76 78 81 208s [39] 82 84 86 87 89 90 91 92 96 97 98 100 101 105 106 109 110 111 208s Outliers: 0 208s Too many to print ... 208s ------------- 208s 208s Call: 208s CovMrcd(x = x, trace = FALSE) 208s -> Method: Minimum Regularized Covariance Determinant MRCD(alpha=0.5 ==> h=56) 208s 208s Robust Estimate of Location: 208s Ozone Solar.R Wind Temp 208s 41.84 197.21 8.93 80.39 208s 208s Robust Estimate of Covariance: 208s Ozone Solar.R Wind Temp 208s Ozone 1480.7 1562.8 -99.9 347.3 208s Solar.R 1562.8 11401.2 -35.2 276.8 208s Wind -99.9 -35.2 11.4 -23.5 208s Temp 347.3 276.8 -23.5 107.7 208s -------------------------------------------------------- 208s attitude 30 7 15 27.040805 208s Best subsample: 208s [1] 2 3 4 5 7 8 10 12 15 19 22 23 25 27 28 208s Outliers: 0 208s Too many to print ... 208s ------------- 208s 208s Call: 208s CovMrcd(x = x, trace = FALSE) 208s -> Method: Minimum Regularized Covariance Determinant MRCD(alpha=0.5 ==> h=15) 208s 208s Robust Estimate of Location: 208s rating complaints privileges learning raises critical 208s 65.8 66.5 50.1 56.1 66.7 78.1 208s advance 208s 41.7 208s 208s Robust Estimate of Covariance: 208s rating complaints privileges learning raises critical advance 208s rating 138.77 80.02 59.22 107.33 95.83 -1.24 54.36 208s complaints 80.02 97.23 50.59 99.50 79.15 -2.71 42.81 208s privileges 59.22 50.59 84.92 90.03 60.88 22.39 44.93 208s learning 107.33 99.50 90.03 187.67 128.71 15.48 63.67 208s raises 95.83 79.15 60.88 128.71 123.94 -1.46 49.98 208s critical -1.24 -2.71 22.39 15.48 -1.46 61.23 12.88 208s advance 54.36 42.81 44.93 63.67 49.98 12.88 48.61 208s -------------------------------------------------------- 208s attenu 182 5 83 9.710111 208s Best subsample: 208s [1] 41 42 43 44 48 49 51 68 70 72 73 74 75 76 77 82 83 84 85 208s [20] 86 87 88 89 90 91 92 101 102 103 104 106 107 109 110 111 112 113 114 208s [39] 115 116 117 121 122 124 125 126 127 128 129 130 131 132 133 134 135 136 137 208s [58] 138 139 140 141 144 145 146 147 148 149 150 151 152 153 155 156 157 158 159 208s [77] 160 161 162 163 164 165 166 208s Outliers: 0 208s Too many to print ... 208s ------------- 208s 208s Call: 208s CovMrcd(x = x, trace = FALSE) 208s -> Method: Minimum Regularized Covariance Determinant MRCD(alpha=0.5 ==> h=83) 208s 208s Robust Estimate of Location: 208s event mag station dist accel 208s 18.940 5.741 67.988 23.365 0.124 208s 208s Robust Estimate of Covariance: 208s event mag station dist accel 208s event 2.86e+01 -2.31e+00 1.02e+02 2.68e+01 -1.99e-01 208s mag -2.31e+00 6.17e-01 -7.03e+00 4.67e-01 2.59e-02 208s station 1.02e+02 -7.03e+00 1.66e+03 1.62e+02 7.96e-02 208s dist 2.68e+01 4.67e-01 1.62e+02 3.61e+02 -1.23e+00 208s accel -1.99e-01 2.59e-02 7.96e-02 -1.23e+00 9.42e-03 208s -------------------------------------------------------- 208s USJudgeRatings 43 12 22 -23.463708 208s Best subsample: 208s [1] 2 3 4 6 9 11 15 16 18 19 24 25 26 27 28 29 32 33 34 36 37 38 208s Outliers: 0 208s Too many to print ... 208s ------------- 208s 208s Call: 208s CovMrcd(x = x, trace = FALSE) 208s -> Method: Minimum Regularized Covariance Determinant MRCD(alpha=0.5 ==> h=22) 208s 208s Robust Estimate of Location: 208s CONT INTG DMNR DILG CFMG DECI PREP FAMI ORAL WRIT PHYS RTEN 208s 7.24 8.42 8.10 8.19 7.95 8.00 7.96 7.96 7.81 7.89 8.40 8.20 208s 208s Robust Estimate of Covariance: 208s CONT INTG DMNR DILG CFMG DECI PREP 208s CONT 0.61805 -0.05601 -0.09540 0.00694 0.09853 0.06261 0.03939 208s INTG -0.05601 0.23560 0.27537 0.20758 0.16603 0.17281 0.21128 208s DMNR -0.09540 0.27537 0.55349 0.28872 0.24014 0.24293 0.28886 208s DILG 0.00694 0.20758 0.28872 0.34099 0.23502 0.23917 0.29672 208s CFMG 0.09853 0.16603 0.24014 0.23502 0.31649 0.23291 0.27651 208s DECI 0.06261 0.17281 0.24293 0.23917 0.23291 0.30681 0.27737 208s PREP 0.03939 0.21128 0.28886 0.29672 0.27651 0.27737 0.42020 208s FAMI 0.04588 0.20388 0.26072 0.29037 0.27179 0.27737 0.34857 208s ORAL 0.03000 0.21379 0.29606 0.28764 0.27338 0.27424 0.33503 208s WRIT 0.03261 0.20258 0.26931 0.27962 0.26382 0.26610 0.32677 208s PHYS -0.04485 0.13598 0.17659 0.16834 0.14554 0.16467 0.18948 208s RTEN 0.01543 0.22654 0.32117 0.27307 0.23826 0.24669 0.29450 208s FAMI ORAL WRIT PHYS RTEN 208s CONT 0.04588 0.03000 0.03261 -0.04485 0.01543 208s INTG 0.20388 0.21379 0.20258 0.13598 0.22654 208s DMNR 0.26072 0.29606 0.26931 0.17659 0.32117 208s DILG 0.29037 0.28764 0.27962 0.16834 0.27307 208s CFMG 0.27179 0.27338 0.26382 0.14554 0.23826 208s DECI 0.27737 0.27424 0.26610 0.16467 0.24669 208s PREP 0.34857 0.33503 0.32677 0.18948 0.29450 208s FAMI 0.47232 0.33762 0.33420 0.19759 0.29015 208s ORAL 0.33762 0.40361 0.32208 0.19794 0.29544 208s WRIT 0.33420 0.32208 0.38733 0.19276 0.28184 208s PHYS 0.19759 0.19794 0.19276 0.20284 0.18097 208s RTEN 0.29015 0.29544 0.28184 0.18097 0.36877 208s -------------------------------------------------------- 208s USArrests 50 4 25 17.834643 208s Best subsample: 208s [1] 4 7 12 13 14 15 16 19 21 23 25 26 27 29 30 32 34 35 36 38 41 45 46 49 50 208s Outliers: 0 208s Too many to print ... 208s ------------- 208s 208s Call: 208s CovMrcd(x = x, trace = FALSE) 208s -> Method: Minimum Regularized Covariance Determinant MRCD(alpha=0.5 ==> h=25) 208s 208s Robust Estimate of Location: 208s Murder Assault UrbanPop Rape 208s 5.38 121.68 63.80 16.33 208s 208s Robust Estimate of Covariance: 208s Murder Assault UrbanPop Rape 208s Murder 17.8 316.3 48.5 31.1 208s Assault 316.3 6863.0 1040.0 548.9 208s UrbanPop 48.5 1040.0 424.8 93.6 208s Rape 31.1 548.9 93.6 63.8 208s -------------------------------------------------------- 208s longley 16 7 8 31.147844 208s Best subsample: 208s [1] 5 6 7 9 10 11 13 14 208s Outliers: 0 208s Too many to print ... 208s ------------- 208s 208s Call: 208s CovMrcd(x = x, trace = FALSE) 208s -> Method: Minimum Regularized Covariance Determinant MRCD(alpha=0.5 ==> h=8) 208s 208s Robust Estimate of Location: 208s GNP.deflator GNP Unemployed Armed.Forces Population 208s 104.3 410.8 278.8 300.1 118.2 208s Year Employed 208s 1955.4 66.5 208s 208s Robust Estimate of Covariance: 208s GNP.deflator GNP Unemployed Armed.Forces Population 208s GNP.deflator 85.0 652.3 784.4 -370.7 48.7 208s GNP 652.3 7502.9 7328.6 -3414.2 453.9 208s Unemployed 784.4 7328.6 10760.3 -4646.7 548.1 208s Armed.Forces -370.7 -3414.2 -4646.7 2824.3 -253.9 208s Population 48.7 453.9 548.1 -253.9 40.2 208s Year 33.5 312.7 378.8 -176.1 23.4 208s Employed 23.9 224.8 263.6 -128.3 16.8 208s Year Employed 208s GNP.deflator 33.5 23.9 208s GNP 312.7 224.8 208s Unemployed 378.8 263.6 208s Armed.Forces -176.1 -128.3 208s Population 23.4 16.8 208s Year 18.9 11.7 208s Employed 11.7 10.3 208s -------------------------------------------------------- 208s Loblolly 84 3 42 11.163448 208s Best subsample: 208s [1] 3 4 5 6 10 21 22 23 24 28 29 33 34 35 36 39 40 41 42 45 46 47 48 51 52 208s [26] 53 54 57 58 59 63 64 65 66 70 71 76 77 81 82 83 84 208s Outliers: 0 208s Too many to print ... 208s ------------- 208s 208s Call: 208s CovMrcd(x = x, trace = FALSE) 208s -> Method: Minimum Regularized Covariance Determinant MRCD(alpha=0.5 ==> h=42) 208s 208s Robust Estimate of Location: 208s height age Seed 208s 44.20 17.26 6.76 208s 208s Robust Estimate of Covariance: 208s height age Seed 208s height 326.74 139.18 3.50 208s age 139.18 68.48 -2.72 208s Seed 3.50 -2.72 25.43 208s -------------------------------------------------------- 208s quakes 1000 4 500 11.802478 208s Best subsample: 208s Too long... 208s Outliers: 0 208s Too many to print ... 208s ------------- 208s 208s Call: 208s CovMrcd(x = x, trace = FALSE) 208s -> Method: Minimum Regularized Covariance Determinant MRCD(alpha=0.5 ==> h=500) 208s 208s Robust Estimate of Location: 208s lat long depth mag 208s -20.59 182.13 432.46 4.42 208s 208s Robust Estimate of Covariance: 208s lat long depth mag 208s lat 15.841 5.702 -106.720 -0.441 208s long 5.702 7.426 -577.189 -0.136 208s depth -106.720 -577.189 66701.479 3.992 208s mag -0.441 -0.136 3.992 0.144 208s -------------------------------------------------------- 208s ======================================================== 208s > ##doexactfit() 208s > 208s BEGIN TEST tmest4.R 209s 209s R version 4.3.3 (2024-02-29) -- "Angel Food Cake" 209s Copyright (C) 2024 The R Foundation for Statistical Computing 209s Platform: aarch64-unknown-linux-gnu (64-bit) 209s 209s R is free software and comes with ABSOLUTELY NO WARRANTY. 209s You are welcome to redistribute it under certain conditions. 209s Type 'license()' or 'licence()' for distribution details. 209s 209s R is a collaborative project with many contributors. 209s Type 'contributors()' for more information and 209s 'citation()' on how to cite R or R packages in publications. 209s 209s Type 'demo()' for some demos, 'help()' for on-line help, or 209s 'help.start()' for an HTML browser interface to help. 209s Type 'q()' to quit R. 209s 209s > ## VT::15.09.2013 - this will render the output independent 209s > ## from the version of the package 209s > suppressPackageStartupMessages(library(rrcov)) 209s > 209s > library(MASS) 209s > dodata <- function(nrep = 1, time = FALSE, full = TRUE) { 209s + domest <- function(x, xname, nrep = 1) { 209s + n <- dim(x)[1] 209s + p <- dim(x)[2] 209s + mm <- CovMest(x) 209s + crit <- log(mm@crit) 209s + ## c1 <- mm@psi@c1 209s + ## M <- mm$psi@M 209s + 209s + xres <- sprintf("%3d %3d %12.6f\n", dim(x)[1], dim(x)[2], crit) 209s + lpad <- lname-nchar(xname) 209s + cat(pad.right(xname,lpad), xres) 209s + 209s + dist <- getDistance(mm) 209s + quantiel <- qchisq(0.975, p) 209s + ibad <- which(dist >= quantiel) 209s + names(ibad) <- NULL 209s + nbad <- length(ibad) 209s + cat("Outliers: ",nbad,"\n") 209s + if(nbad > 0) 209s + print(ibad) 209s + cat("-------------\n") 209s + show(mm) 209s + cat("--------------------------------------------------------\n") 209s + } 209s + 209s + options(digits = 5) 209s + set.seed(101) # <<-- sub-sampling algorithm now based on R's RNG and seed 209s + 209s + lname <- 20 209s + 209s + data(heart) 209s + data(starsCYG) 209s + data(phosphor) 209s + data(stackloss) 209s + data(coleman) 209s + data(salinity) 209s + data(wood) 209s + data(hbk) 209s + 209s + data(Animals, package = "MASS") 209s + brain <- Animals[c(1:24, 26:25, 27:28),] 209s + data(milk) 209s + data(bushfire) 209s + 209s + tmp <- sys.call() 209s + cat("\nCall: ", deparse(substitute(tmp)),"\n") 209s + 209s + cat("Data Set n p c1 M LOG(det) Time\n") 209s + cat("======================================================================\n") 209s + domest(heart[, 1:2], data(heart), nrep) 209s + domest(starsCYG, data(starsCYG), nrep) 209s + domest(data.matrix(subset(phosphor, select = -plant)), data(phosphor), nrep) 209s + domest(stack.x, data(stackloss), nrep) 209s + domest(data.matrix(subset(coleman, select = -Y)), data(coleman), nrep) 209s + domest(data.matrix(subset(salinity, select = -Y)), data(salinity), nrep) 209s + domest(data.matrix(subset(wood, select = -y)), data(wood), nrep) 209s + domest(data.matrix(subset(hbk, select = -Y)), data(hbk), nrep) 209s + 209s + 209s + domest(brain, "Animals", nrep) 209s + domest(milk, data(milk), nrep) 209s + domest(bushfire, data(bushfire), nrep) 209s + cat("======================================================================\n") 209s + } 209s > 209s > # generate contaminated data using the function gendata with different 209s > # number of outliers and check if the M-estimate breaks - i.e. the 209s > # largest eigenvalue is larger than e.g. 5. 209s > # For n=50 and p=10 and d=5 the M-estimate can break for number of 209s > # outliers grater than 20. 209s > dogen <- function(){ 209s + eig <- vector("numeric",26) 209s + for(i in 0:25) { 209s + gg <- gendata(eps=i) 209s + mm <- CovMest(gg$x, t0=gg$tgood, S0=gg$sgood, arp=0.001) 209s + eig[i+1] <- ev <- getEvals(mm)[1] 209s + # cat(i, ev, "\n") 209s + 209s + stopifnot(ev < 5 || i > 20) 209s + } 209s + # plot(0:25, eig, type="l", xlab="Number of outliers", ylab="Largest Eigenvalue") 209s + } 209s > 209s > # 209s > # generate data 50x10 as multivariate normal N(0,I) and add 209s > # eps % outliers by adding d=5.0 to each component. 209s > # - if eps <0 and eps <=0.5, the number of outliers is eps*n 209s > # - if eps >= 1, it is the number of outliers 209s > # - use the center and cov of the good data as good start 209s > # - use the center and the cov of all data as a bad start 209s > # If using a good start, the M-estimate must iterate to 209s > # the good solution: the largest eigenvalue is less then e.g. 5 209s > # 209s > gendata <- function(n=50, p=10, eps=0, d=5.0){ 209s + 209s + if(eps < 0 || eps > 0.5 && eps < 1.0 || eps > 0.5*n) 209s + stop("eps is out of range") 209s + 209s + library(MASS) 209s + 209s + x <- mvrnorm(n, rep(0,p), diag(p)) 209s + bad <- vector("numeric") 209s + nbad = if(eps < 1) eps*n else eps 209s + if(nbad > 0){ 209s + bad <- sample(n, nbad) 209s + x[bad,] <- x[bad,] + d 209s + } 209s + cov1 <- cov.wt(x) 209s + cov2 <- if(nbad <= 0) cov1 else cov.wt(x[-bad,]) 209s + 209s + list(x=x, bad=sort(bad), tgood=cov2$center, sgood=cov2$cov, tbad=cov1$center, sbad=cov1$cov) 209s + } 209s > 209s > pad.right <- function(z, pads) 209s + { 209s + ## Pads spaces to right of text 209s + padding <- paste(rep(" ", pads), collapse = "") 209s + paste(z, padding, sep = "") 209s + } 209s > 209s > 209s > ## -- now do it: 209s > dodata() 209s 209s Call: dodata() 209s Data Set n p c1 M LOG(det) Time 209s ====================================================================== 209s heart 12 2 7.160341 209s Outliers: 3 209s [1] 2 6 12 209s ------------- 209s 209s Call: 209s CovMest(x = x) 209s -> Method: M-Estimates 209s 209s Robust Estimate of Location: 209s height weight 209s 34.9 27.0 209s 209s Robust Estimate of Covariance: 209s height weight 209s height 102 155 209s weight 155 250 209s -------------------------------------------------------- 209s starsCYG 47 2 -5.994588 209s Outliers: 7 209s [1] 7 9 11 14 20 30 34 209s ------------- 209s 209s Call: 209s CovMest(x = x) 209s -> Method: M-Estimates 209s 209s Robust Estimate of Location: 209s log.Te log.light 209s 4.42 4.95 209s 209s Robust Estimate of Covariance: 209s log.Te log.light 209s log.Te 0.0169 0.0587 209s log.light 0.0587 0.3523 209s -------------------------------------------------------- 209s phosphor 18 2 8.867522 209s Outliers: 3 209s [1] 1 6 10 209s ------------- 209s 209s Call: 209s CovMest(x = x) 209s -> Method: M-Estimates 209s 209s Robust Estimate of Location: 209s inorg organic 209s 15.4 39.1 209s 209s Robust Estimate of Covariance: 209s inorg organic 209s inorg 169 213 209s organic 213 308 209s -------------------------------------------------------- 209s stackloss 21 3 7.241400 209s Outliers: 9 209s [1] 1 2 3 15 16 17 18 19 21 209s ------------- 209s 209s Call: 209s CovMest(x = x) 209s -> Method: M-Estimates 209s 209s Robust Estimate of Location: 209s Air.Flow Water.Temp Acid.Conc. 209s 59.5 20.8 87.3 209s 209s Robust Estimate of Covariance: 209s Air.Flow Water.Temp Acid.Conc. 209s Air.Flow 9.34 8.69 8.52 209s Water.Temp 8.69 13.72 9.13 209s Acid.Conc. 8.52 9.13 34.54 209s -------------------------------------------------------- 209s coleman 20 5 2.574752 209s Outliers: 7 209s [1] 2 6 9 10 12 13 15 209s ------------- 209s 209s Call: 209s CovMest(x = x) 209s -> Method: M-Estimates 209s 209s Robust Estimate of Location: 209s salaryP fatherWc sstatus teacherSc motherLev 209s 2.82 48.44 5.30 25.19 6.51 209s 209s Robust Estimate of Covariance: 209s salaryP fatherWc sstatus teacherSc motherLev 209s salaryP 0.2850 0.1045 1.7585 0.3074 0.0355 209s fatherWc 0.1045 824.8305 260.7062 3.7507 17.7959 209s sstatus 1.7585 260.7062 105.6135 4.1140 5.7714 209s teacherSc 0.3074 3.7507 4.1140 0.6753 0.1563 209s motherLev 0.0355 17.7959 5.7714 0.1563 0.4147 209s -------------------------------------------------------- 209s salinity 28 3 3.875096 209s Outliers: 9 209s [1] 3 5 10 11 15 16 17 23 24 209s ------------- 209s 209s Call: 209s CovMest(x = x) 209s -> Method: M-Estimates 209s 209s Robust Estimate of Location: 209s X1 X2 X3 209s 10.02 3.21 22.36 209s 209s Robust Estimate of Covariance: 209s X1 X2 X3 209s X1 15.353 1.990 -5.075 209s X2 1.990 5.210 -0.769 209s X3 -5.075 -0.769 2.314 209s -------------------------------------------------------- 209s wood 20 5 -35.156305 209s Outliers: 7 209s [1] 4 6 7 8 11 16 19 209s ------------- 209s 209s Call: 209s CovMest(x = x) 209s -> Method: M-Estimates 209s 209s Robust Estimate of Location: 209s x1 x2 x3 x4 x5 209s 0.587 0.122 0.531 0.538 0.892 209s 209s Robust Estimate of Covariance: 209s x1 x2 x3 x4 x5 209s x1 6.45e-03 1.21e-03 2.03e-03 -3.77e-04 -1.05e-03 209s x2 1.21e-03 3.12e-04 8.16e-04 -3.34e-05 1.52e-05 209s x3 2.03e-03 8.16e-04 4.27e-03 -5.60e-04 2.27e-04 209s x4 -3.77e-04 -3.34e-05 -5.60e-04 1.83e-03 1.18e-03 209s x5 -1.05e-03 1.52e-05 2.27e-04 1.18e-03 1.78e-03 209s -------------------------------------------------------- 209s hbk 75 3 1.432485 209s Outliers: 14 209s [1] 1 2 3 4 5 6 7 8 9 10 11 12 13 14 209s ------------- 209s 209s Call: 209s CovMest(x = x) 209s -> Method: M-Estimates 209s 209s Robust Estimate of Location: 209s X1 X2 X3 209s 1.54 1.78 1.69 209s 209s Robust Estimate of Covariance: 209s X1 X2 X3 209s X1 1.6485 0.0739 0.1709 209s X2 0.0739 1.6780 0.2049 209s X3 0.1709 0.2049 1.5584 209s -------------------------------------------------------- 209s Animals 28 2 18.194822 209s Outliers: 10 209s [1] 2 6 7 9 12 14 15 16 25 28 209s ------------- 209s 209s Call: 209s CovMest(x = x) 209s -> Method: M-Estimates 209s 209s Robust Estimate of Location: 209s body brain 209s 18.7 64.9 209s 209s Robust Estimate of Covariance: 209s body brain 209s body 4993 8466 209s brain 8466 30335 209s -------------------------------------------------------- 209s milk 86 8 -25.041802 209s Outliers: 20 209s [1] 1 2 3 11 12 13 14 15 16 17 18 20 27 41 44 47 70 74 75 77 209s ------------- 209s 209s Call: 209s CovMest(x = x) 209s -> Method: M-Estimates 209s 209s Robust Estimate of Location: 209s X1 X2 X3 X4 X5 X6 X7 X8 209s 1.03 35.88 33.04 26.11 25.09 25.02 123.12 14.39 209s 209s Robust Estimate of Covariance: 209s X1 X2 X3 X4 X5 X6 X7 209s X1 4.89e-07 9.64e-05 1.83e-04 1.76e-04 1.57e-04 1.48e-04 6.53e-04 209s X2 9.64e-05 2.05e+00 3.38e-01 2.37e-01 1.70e-01 2.71e-01 1.91e+00 209s X3 1.83e-04 3.38e-01 1.16e+00 8.56e-01 8.48e-01 8.31e-01 8.85e-01 209s X4 1.76e-04 2.37e-01 8.56e-01 6.83e-01 6.55e-01 6.40e-01 6.91e-01 209s X5 1.57e-04 1.70e-01 8.48e-01 6.55e-01 6.93e-01 6.52e-01 6.90e-01 209s X6 1.48e-04 2.71e-01 8.31e-01 6.40e-01 6.52e-01 6.61e-01 6.95e-01 209s X7 6.53e-04 1.91e+00 8.85e-01 6.91e-01 6.90e-01 6.95e-01 4.40e+00 209s X8 5.56e-06 2.60e-01 1.98e-01 1.29e-01 1.12e-01 1.19e-01 4.12e-01 209s X8 209s X1 5.56e-06 209s X2 2.60e-01 209s X3 1.98e-01 209s X4 1.29e-01 209s X5 1.12e-01 209s X6 1.19e-01 209s X7 4.12e-01 209s X8 1.65e-01 209s -------------------------------------------------------- 209s bushfire 38 5 23.457490 209s Outliers: 15 209s [1] 7 8 9 10 11 29 30 31 32 33 34 35 36 37 38 209s ------------- 209s 209s Call: 209s CovMest(x = x) 209s -> Method: M-Estimates 209s 209s Robust Estimate of Location: 209s V1 V2 V3 V4 V5 209s 107 147 263 215 277 209s 209s Robust Estimate of Covariance: 209s V1 V2 V3 V4 V5 209s V1 775 560 -4179 -925 -759 209s V2 560 478 -2494 -510 -431 209s V3 -4179 -2494 27433 6441 5196 209s V4 -925 -510 6441 1607 1276 209s V5 -759 -431 5196 1276 1020 209s -------------------------------------------------------- 209s ====================================================================== 209s > dogen() 209s > #cat('Time elapsed: ', proc.time(),'\n') # for ``statistical reasons'' 209s > 209s BEGIN TEST tmve4.R 209s 209s R version 4.3.3 (2024-02-29) -- "Angel Food Cake" 209s Copyright (C) 2024 The R Foundation for Statistical Computing 209s Platform: aarch64-unknown-linux-gnu (64-bit) 209s 209s R is free software and comes with ABSOLUTELY NO WARRANTY. 209s You are welcome to redistribute it under certain conditions. 209s Type 'license()' or 'licence()' for distribution details. 209s 209s R is a collaborative project with many contributors. 209s Type 'contributors()' for more information and 209s 'citation()' on how to cite R or R packages in publications. 209s 209s Type 'demo()' for some demos, 'help()' for on-line help, or 209s 'help.start()' for an HTML browser interface to help. 209s Type 'q()' to quit R. 209s 209s > dodata <- function(nrep=1, time=FALSE, short=FALSE, full=TRUE, method = c("FASTMVE","MASS")){ 209s + ##@bdescr 209s + ## Test the function covMve() on the literature datasets: 209s + ## 209s + ## Call covMve() for all regression datasets available in rrco/robustbasev and print: 209s + ## - execution time (if time == TRUE) 209s + ## - objective fucntion 209s + ## - best subsample found (if short == false) 209s + ## - outliers identified (with cutoff 0.975) (if short == false) 209s + ## - estimated center and covarinance matrix if full == TRUE) 209s + ## 209s + ##@edescr 209s + ## 209s + ##@in nrep : [integer] number of repetitions to use for estimating the 209s + ## (average) execution time 209s + ##@in time : [boolean] whether to evaluate the execution time 209s + ##@in short : [boolean] whether to do short output (i.e. only the 209s + ## objective function value). If short == FALSE, 209s + ## the best subsample and the identified outliers are 209s + ## printed. See also the parameter full below 209s + ##@in full : [boolean] whether to print the estimated cente and covariance matrix 209s + ##@in method : [character] select a method: one of (FASTMCD, MASS) 209s + 209s + domve <- function(x, xname, nrep=1){ 209s + n <- dim(x)[1] 209s + p <- dim(x)[2] 209s + alpha <- 0.5 209s + h <- h.alpha.n(alpha, n, p) 209s + if(method == "MASS"){ 209s + mve <- cov.mve(x, quantile.used=h) 209s + quan <- h #default: floor((n+p+1)/2) 209s + crit <- mve$crit 209s + best <- mve$best 209s + mah <- mahalanobis(x, mve$center, mve$cov) 209s + quantiel <- qchisq(0.975, p) 209s + wt <- as.numeric(mah < quantiel) 209s + } 209s + else{ 209s + mve <- CovMve(x, trace=FALSE) 209s + quan <- as.integer(mve@quan) 209s + crit <- log(mve@crit) 209s + best <- mve@best 209s + wt <- mve@wt 209s + } 209s + 209s + 209s + if(time){ 209s + xtime <- system.time(dorep(x, nrep, method))[1]/nrep 209s + xres <- sprintf("%3d %3d %3d %12.6f %10.3f\n", dim(x)[1], dim(x)[2], quan, crit, xtime) 209s + } 209s + else{ 209s + xres <- sprintf("%3d %3d %3d %12.6f\n", dim(x)[1], dim(x)[2], quan, crit) 209s + } 209s + 209s + lpad<-lname-nchar(xname) 209s + cat(pad.right(xname,lpad), xres) 209s + 209s + if(!short){ 209s + cat("Best subsample: \n") 209s + print(best) 209s + 209s + ibad <- which(wt == 0) 209s + names(ibad) <- NULL 209s + nbad <- length(ibad) 209s + cat("Outliers: ", nbad, "\n") 209s + if(nbad > 0) 209s + print(ibad) 209s + if(full){ 209s + cat("-------------\n") 209s + show(mve) 209s + } 209s + cat("--------------------------------------------------------\n") 209s + } 209s + } 209s + 209s + options(digits = 5) 209s + set.seed(101) # <<-- sub-sampling algorithm now based on R's RNG and seed 209s + 209s + lname <- 20 209s + 209s + ## VT::15.09.2013 - this will render the output independent 209s + ## from the version of the package 209s + suppressPackageStartupMessages(library(rrcov)) 209s + 209s + method <- match.arg(method) 209s + if(method == "MASS") 209s + library(MASS) 209s + 209s + 209s + data(heart) 209s + data(starsCYG) 209s + data(phosphor) 209s + data(stackloss) 209s + data(coleman) 209s + data(salinity) 209s + data(wood) 209s + 209s + data(hbk) 209s + 209s + data(Animals, package = "MASS") 209s + brain <- Animals[c(1:24, 26:25, 27:28),] 209s + data(milk) 209s + data(bushfire) 209s + 209s + tmp <- sys.call() 209s + cat("\nCall: ", deparse(substitute(tmp)),"\n") 209s + 209s + cat("Data Set n p Half LOG(obj) Time\n") 209s + cat("========================================================\n") 209s + domve(heart[, 1:2], data(heart), nrep) 209s + domve(starsCYG, data(starsCYG), nrep) 209s + domve(data.matrix(subset(phosphor, select = -plant)), data(phosphor), nrep) 209s + domve(stack.x, data(stackloss), nrep) 209s + domve(data.matrix(subset(coleman, select = -Y)), data(coleman), nrep) 209s + domve(data.matrix(subset(salinity, select = -Y)), data(salinity), nrep) 209s + domve(data.matrix(subset(wood, select = -y)), data(wood), nrep) 209s + domve(data.matrix(subset(hbk, select = -Y)),data(hbk), nrep) 209s + 209s + domve(brain, "Animals", nrep) 209s + domve(milk, data(milk), nrep) 209s + domve(bushfire, data(bushfire), nrep) 209s + cat("========================================================\n") 209s + } 209s > 209s > dogen <- function(nrep=1, eps=0.49, method=c("FASTMVE", "MASS")){ 209s + 209s + domve <- function(x, nrep=1){ 209s + gc() 209s + xtime <- system.time(dorep(x, nrep, method))[1]/nrep 209s + cat(sprintf("%6d %3d %10.2f\n", dim(x)[1], dim(x)[2], xtime)) 209s + xtime 209s + } 209s + 209s + set.seed(1234) 209s + 209s + ## VT::15.09.2013 - this will render the output independent 209s + ## from the version of the package 209s + suppressPackageStartupMessages(library(rrcov)) 209s + library(MASS) 209s + 209s + method <- match.arg(method) 209s + 209s + ap <- c(2, 5, 10, 20, 30) 209s + an <- c(100, 500, 1000, 10000, 50000) 209s + 209s + tottime <- 0 209s + cat(" n p Time\n") 209s + cat("=====================\n") 210s + for(i in 1:length(an)) { 210s + for(j in 1:length(ap)) { 210s + n <- an[i] 210s + p <- ap[j] 210s + if(5*p <= n){ 210s + xx <- gendata(n, p, eps) 210s + X <- xx$X 210s + tottime <- tottime + domve(X, nrep) 210s + } 210s + } 210s + } 210s + 210s + cat("=====================\n") 210s + cat("Total time: ", tottime*nrep, "\n") 210s + } 210s > 210s > docheck <- function(n, p, eps){ 210s + xx <- gendata(n,p,eps) 210s + mve <- CovMve(xx$X) 210s + check(mve, xx$xind) 210s + } 210s > 210s > check <- function(mcd, xind){ 210s + ## check if mcd is robust w.r.t xind, i.e. check how many of xind 210s + ## did not get zero weight 210s + mymatch <- xind %in% which(mcd@wt == 0) 210s + length(xind) - length(which(mymatch)) 210s + } 210s > 210s > dorep <- function(x, nrep=1, method=c("FASTMVE","MASS")){ 210s + 210s + method <- match.arg(method) 210s + for(i in 1:nrep) 210s + if(method == "MASS") 210s + cov.mve(x) 210s + else 210s + CovMve(x) 210s + } 210s > 210s > #### gendata() #### 210s > # Generates a location contaminated multivariate 210s > # normal sample of n observations in p dimensions 210s > # (1-eps)*Np(0,Ip) + eps*Np(m,Ip) 210s > # where 210s > # m = (b,b,...,b) 210s > # Defaults: eps=0 and b=10 210s > # 210s > gendata <- function(n,p,eps=0,b=10){ 210s + 210s + if(missing(n) || missing(p)) 210s + stop("Please specify (n,p)") 210s + if(eps < 0 || eps >= 0.5) 210s + stop(message="eps must be in [0,0.5)") 210s + X <- mvrnorm(n,rep(0,p),diag(1,nrow=p,ncol=p)) 210s + nbad <- as.integer(eps * n) 210s + if(nbad > 0){ 210s + Xbad <- mvrnorm(nbad,rep(b,p),diag(1,nrow=p,ncol=p)) 210s + xind <- sample(n,nbad) 210s + X[xind,] <- Xbad 210s + } 210s + list(X=X, xind=xind) 210s + } 210s > 210s > pad.right <- function(z, pads) 210s + { 210s + ### Pads spaces to right of text 210s + padding <- paste(rep(" ", pads), collapse = "") 210s + paste(z, padding, sep = "") 210s + } 210s > 210s > whatis<-function(x){ 210s + if(is.data.frame(x)) 210s + cat("Type: data.frame\n") 210s + else if(is.matrix(x)) 210s + cat("Type: matrix\n") 210s + else if(is.vector(x)) 210s + cat("Type: vector\n") 210s + else 210s + cat("Type: don't know\n") 210s + } 210s > 210s > ## VT::15.09.2013 - this will render the output independent 210s > ## from the version of the package 210s > suppressPackageStartupMessages(library(rrcov)) 210s > 210s > dodata() 210s 210s Call: dodata() 210s Data Set n p Half LOG(obj) Time 210s ======================================================== 210s heart 12 2 7 3.827606 210s Best subsample: 210s [1] 1 4 7 8 9 10 11 210s Outliers: 3 210s [1] 2 6 12 210s ------------- 210s 210s Call: 210s CovMve(x = x, trace = FALSE) 210s -> Method: Minimum volume ellipsoid estimator 210s 210s Robust Estimate of Location: 210s height weight 210s 34.9 27.0 210s 210s Robust Estimate of Covariance: 210s height weight 210s height 142 217 210s weight 217 350 210s -------------------------------------------------------- 210s starsCYG 47 2 25 -2.742997 210s Best subsample: 210s [1] 2 4 6 8 12 13 16 23 24 25 26 28 31 32 33 37 38 39 41 42 43 44 45 46 47 210s Outliers: 7 210s [1] 7 9 11 14 20 30 34 210s ------------- 210s 210s Call: 210s CovMve(x = x, trace = FALSE) 210s -> Method: Minimum volume ellipsoid estimator 210s 210s Robust Estimate of Location: 210s log.Te log.light 210s 4.41 4.93 210s 210s Robust Estimate of Covariance: 210s log.Te log.light 210s log.Te 0.0173 0.0578 210s log.light 0.0578 0.3615 210s -------------------------------------------------------- 210s phosphor 18 2 10 4.443101 210s Best subsample: 210s [1] 3 5 8 9 11 12 13 14 15 17 210s Outliers: 3 210s [1] 1 6 10 210s ------------- 210s 210s Call: 210s CovMve(x = x, trace = FALSE) 210s -> Method: Minimum volume ellipsoid estimator 210s 210s Robust Estimate of Location: 210s inorg organic 210s 15.2 39.4 210s 210s Robust Estimate of Covariance: 210s inorg organic 210s inorg 188 230 210s organic 230 339 210s -------------------------------------------------------- 210s stackloss 21 3 12 3.327582 210s Best subsample: 210s [1] 4 5 6 7 8 9 10 11 12 13 14 20 210s Outliers: 3 210s [1] 1 2 3 210s ------------- 210s 210s Call: 210s CovMve(x = x, trace = FALSE) 210s -> Method: Minimum volume ellipsoid estimator 210s 210s Robust Estimate of Location: 210s Air.Flow Water.Temp Acid.Conc. 210s 56.7 20.2 85.5 210s 210s Robust Estimate of Covariance: 210s Air.Flow Water.Temp Acid.Conc. 210s Air.Flow 34.31 11.07 23.54 210s Water.Temp 11.07 9.23 7.85 210s Acid.Conc. 23.54 7.85 47.35 210s -------------------------------------------------------- 210s coleman 20 5 13 2.065143 210s Best subsample: 210s [1] 1 3 4 5 7 8 11 14 16 17 18 19 20 210s Outliers: 5 210s [1] 2 6 9 10 13 210s ------------- 210s 210s Call: 210s CovMve(x = x, trace = FALSE) 210s -> Method: Minimum volume ellipsoid estimator 210s 210s Robust Estimate of Location: 210s salaryP fatherWc sstatus teacherSc motherLev 210s 2.79 44.26 3.59 25.08 6.38 210s 210s Robust Estimate of Covariance: 210s salaryP fatherWc sstatus teacherSc motherLev 210s salaryP 0.2920 1.1188 2.0421 0.3487 0.0748 210s fatherWc 1.1188 996.7540 338.6587 7.1673 23.1783 210s sstatus 2.0421 338.6587 148.2501 4.4894 7.8135 210s teacherSc 0.3487 7.1673 4.4894 0.9082 0.3204 210s motherLev 0.0748 23.1783 7.8135 0.3204 0.6024 210s -------------------------------------------------------- 210s salinity 28 3 16 2.002555 210s Best subsample: 210s [1] 1 7 8 9 12 13 14 18 19 20 21 22 25 26 27 28 210s Outliers: 5 210s [1] 5 11 16 23 24 210s ------------- 210s 210s Call: 210s CovMve(x = x, trace = FALSE) 210s -> Method: Minimum volume ellipsoid estimator 210s 210s Robust Estimate of Location: 210s X1 X2 X3 210s 10.2 3.1 22.4 210s 210s Robust Estimate of Covariance: 210s X1 X2 X3 210s X1 14.387 1.153 -4.072 210s X2 1.153 5.005 -0.954 210s X3 -4.072 -0.954 2.222 210s -------------------------------------------------------- 210s wood 20 5 13 -5.471407 210s Best subsample: 210s [1] 1 2 3 5 9 10 12 13 14 15 17 18 20 210s Outliers: 5 210s [1] 4 6 8 11 19 210s ------------- 210s 210s Call: 210s CovMve(x = x, trace = FALSE) 210s -> Method: Minimum volume ellipsoid estimator 210s 210s Robust Estimate of Location: 210s x1 x2 x3 x4 x5 210s 0.576 0.123 0.531 0.538 0.889 210s 210s Robust Estimate of Covariance: 210s x1 x2 x3 x4 x5 210s x1 7.45e-03 1.11e-03 1.83e-03 -2.90e-05 -5.65e-04 210s x2 1.11e-03 3.11e-04 7.68e-04 3.37e-05 3.85e-05 210s x3 1.83e-03 7.68e-04 4.30e-03 -9.96e-04 -6.27e-05 210s x4 -2.90e-05 3.37e-05 -9.96e-04 3.02e-03 1.91e-03 210s x5 -5.65e-04 3.85e-05 -6.27e-05 1.91e-03 2.25e-03 210s -------------------------------------------------------- 210s hbk 75 3 39 1.096831 210s Best subsample: 210s [1] 15 17 18 19 20 21 24 27 28 30 32 33 35 36 40 41 42 43 44 46 48 49 50 53 54 210s [26] 55 56 58 59 64 65 66 67 70 71 72 73 74 75 210s Outliers: 14 210s [1] 1 2 3 4 5 6 7 8 9 10 11 12 13 14 210s ------------- 210s 210s Call: 210s CovMve(x = x, trace = FALSE) 210s -> Method: Minimum volume ellipsoid estimator 210s 210s Robust Estimate of Location: 210s X1 X2 X3 210s 1.48 1.86 1.73 210s 210s Robust Estimate of Covariance: 210s X1 X2 X3 210s X1 1.695 0.230 0.265 210s X2 0.230 1.679 0.119 210s X3 0.265 0.119 1.683 210s -------------------------------------------------------- 210s Animals 28 2 15 8.945423 210s Best subsample: 210s [1] 1 3 4 5 10 11 17 18 21 22 23 24 26 27 28 210s Outliers: 9 210s [1] 2 6 7 9 12 14 15 16 25 210s ------------- 210s 210s Call: 210s CovMve(x = x, trace = FALSE) 210s -> Method: Minimum volume ellipsoid estimator 210s 210s Robust Estimate of Location: 210s body brain 210s 48.3 127.3 210s 210s Robust Estimate of Covariance: 210s body brain 210s body 10767 16872 210s brain 16872 46918 210s -------------------------------------------------------- 210s milk 86 8 47 -1.160085 210s Best subsample: 210s [1] 4 5 7 8 9 10 11 19 21 22 23 24 26 30 31 33 34 35 36 37 38 39 42 43 45 210s [26] 46 54 56 57 59 60 61 62 63 64 65 66 67 69 72 76 78 79 81 82 83 85 210s Outliers: 18 210s [1] 1 2 3 12 13 14 15 16 17 18 20 27 41 44 47 70 74 75 210s ------------- 210s 210s Call: 210s CovMve(x = x, trace = FALSE) 210s -> Method: Minimum volume ellipsoid estimator 210s 210s Robust Estimate of Location: 210s X1 X2 X3 X4 X5 X6 X7 X8 210s 1.03 35.91 33.02 26.08 25.06 24.99 122.93 14.38 210s 210s Robust Estimate of Covariance: 210s X1 X2 X3 X4 X5 X6 X7 210s X1 6.00e-07 1.51e-04 3.34e-04 3.09e-04 2.82e-04 2.77e-04 1.09e-03 210s X2 1.51e-04 2.03e+00 3.83e-01 3.04e-01 2.20e-01 3.51e-01 2.18e+00 210s X3 3.34e-04 3.83e-01 1.58e+00 1.21e+00 1.18e+00 1.20e+00 1.60e+00 210s X4 3.09e-04 3.04e-01 1.21e+00 9.82e-01 9.39e-01 9.53e-01 1.36e+00 210s X5 2.82e-04 2.20e-01 1.18e+00 9.39e-01 9.67e-01 9.52e-01 1.34e+00 210s X6 2.77e-04 3.51e-01 1.20e+00 9.53e-01 9.52e-01 9.92e-01 1.38e+00 210s X7 1.09e-03 2.18e+00 1.60e+00 1.36e+00 1.34e+00 1.38e+00 6.73e+00 210s X8 3.33e-05 2.92e-01 2.65e-01 1.83e-01 1.65e-01 1.76e-01 5.64e-01 210s X8 210s X1 3.33e-05 210s X2 2.92e-01 210s X3 2.65e-01 210s X4 1.83e-01 210s X5 1.65e-01 210s X6 1.76e-01 210s X7 5.64e-01 210s X8 1.80e-01 210s -------------------------------------------------------- 210s bushfire 38 5 22 5.644315 210s Best subsample: 210s [1] 1 2 3 4 5 6 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 210s Outliers: 15 210s [1] 7 8 9 10 11 29 30 31 32 33 34 35 36 37 38 210s ------------- 210s 210s Call: 210s CovMve(x = x, trace = FALSE) 210s -> Method: Minimum volume ellipsoid estimator 210s 210s Robust Estimate of Location: 210s V1 V2 V3 V4 V5 210s 107 147 263 215 277 210s 210s Robust Estimate of Covariance: 210s V1 V2 V3 V4 V5 210s V1 519 375 -2799 -619 -509 210s V2 375 320 -1671 -342 -289 210s V3 -2799 -1671 18373 4314 3480 210s V4 -619 -342 4314 1076 854 210s V5 -509 -289 3480 854 683 210s -------------------------------------------------------- 210s ======================================================== 210s > 210s BEGIN TEST togk4.R 210s 210s R version 4.3.3 (2024-02-29) -- "Angel Food Cake" 210s Copyright (C) 2024 The R Foundation for Statistical Computing 210s Platform: aarch64-unknown-linux-gnu (64-bit) 210s 210s R is free software and comes with ABSOLUTELY NO WARRANTY. 210s You are welcome to redistribute it under certain conditions. 210s Type 'license()' or 'licence()' for distribution details. 210s 210s R is a collaborative project with many contributors. 210s Type 'contributors()' for more information and 210s 'citation()' on how to cite R or R packages in publications. 210s 210s Type 'demo()' for some demos, 'help()' for on-line help, or 210s 'help.start()' for an HTML browser interface to help. 210s Type 'q()' to quit R. 210s 210s > ## VT::15.09.2013 - this will render the output independent 210s > ## from the version of the package 210s > suppressPackageStartupMessages(library(rrcov)) 211s > 211s > ## VT::14.01.2020 211s > ## On some platforms minor differences are shown - use 211s > ## IGNORE_RDIFF_BEGIN 211s > ## IGNORE_RDIFF_END 211s > 211s > dodata <- function(nrep=1, time=FALSE, short=FALSE, full=TRUE, method = c("FASTMCD","MASS")){ 211s + domcd <- function(x, xname, nrep=1){ 211s + n <- dim(x)[1] 211s + p <- dim(x)[2] 211s + 211s + mcd<-CovOgk(x) 211s + 211s + xres <- sprintf("%3d %3d\n", dim(x)[1], dim(x)[2]) 211s + 211s + lpad<-lname-nchar(xname) 211s + cat(pad.right(xname,lpad), xres) 211s + 211s + dist <- getDistance(mcd) 211s + quantiel <- qchisq(0.975, p) 211s + ibad <- which(dist >= quantiel) 211s + names(ibad) <- NULL 211s + nbad <- length(ibad) 211s + cat("Outliers: ",nbad,"\n") 211s + if(nbad > 0) 211s + print(ibad) 211s + cat("-------------\n") 211s + show(mcd) 211s + cat("--------------------------------------------------------\n") 211s + } 211s + 211s + lname <- 20 211s + 211s + ## VT::15.09.2013 - this will render the output independent 211s + ## from the version of the package 211s + suppressPackageStartupMessages(library(rrcov)) 211s + 211s + method <- match.arg(method) 211s + 211s + data(heart) 211s + data(starsCYG) 211s + data(phosphor) 211s + data(stackloss) 211s + data(coleman) 211s + data(salinity) 211s + data(wood) 211s + 211s + data(hbk) 211s + 211s + data(Animals, package = "MASS") 211s + brain <- Animals[c(1:24, 26:25, 27:28),] 211s + data(milk) 211s + data(bushfire) 211s + 211s + tmp <- sys.call() 211s + cat("\nCall: ", deparse(substitute(tmp)),"\n") 211s + 211s + cat("Data Set n p Half LOG(obj) Time\n") 211s + cat("========================================================\n") 211s + domcd(heart[, 1:2], data(heart), nrep) 211s + ## This will not work within the function, of course 211s + ## - comment it out 211s + ## IGNORE_RDIFF_BEGIN 211s + ## domcd(starsCYG,data(starsCYG), nrep) 211s + ## IGNORE_RDIFF_END 211s + domcd(data.matrix(subset(phosphor, select = -plant)), data(phosphor), nrep) 211s + domcd(stack.x,data(stackloss), nrep) 211s + domcd(data.matrix(subset(coleman, select = -Y)), data(coleman), nrep) 211s + domcd(data.matrix(subset(salinity, select = -Y)), data(salinity), nrep) 211s + ## IGNORE_RDIFF_BEGIN 211s + ## domcd(data.matrix(subset(wood, select = -y)), data(wood), nrep) 211s + ## IGNORE_RDIFF_END 211s + domcd(data.matrix(subset(hbk, select = -Y)), data(hbk), nrep) 211s + 211s + domcd(brain, "Animals", nrep) 211s + domcd(milk, data(milk), nrep) 211s + domcd(bushfire, data(bushfire), nrep) 211s + cat("========================================================\n") 211s + } 211s > 211s > pad.right <- function(z, pads) 211s + { 211s + ### Pads spaces to right of text 211s + padding <- paste(rep(" ", pads), collapse = "") 211s + paste(z, padding, sep = "") 211s + } 211s > 211s > dodata() 212s 212s Call: dodata() 212s Data Set n p Half LOG(obj) Time 212s ======================================================== 212s heart 12 2 212s Outliers: 5 212s [1] 2 6 8 10 12 212s ------------- 212s 212s Call: 212s CovOgk(x = x) 212s -> Method: Orthogonalized Gnanadesikan-Kettenring Estimator 212s 212s Robust Estimate of Location: 212s height weight 212s 39.76 35.71 212s 212s Robust Estimate of Covariance: 212s height weight 212s height 15.88 32.07 212s weight 32.07 78.28 212s -------------------------------------------------------- 212s phosphor 18 2 212s Outliers: 2 212s [1] 1 6 212s ------------- 212s 212s Call: 212s CovOgk(x = x) 212s -> Method: Orthogonalized Gnanadesikan-Kettenring Estimator 212s 212s Robust Estimate of Location: 212s inorg organic 212s 13.31 40.00 212s 212s Robust Estimate of Covariance: 212s inorg organic 212s inorg 92.82 93.24 212s organic 93.24 152.62 212s -------------------------------------------------------- 212s stackloss 21 3 212s Outliers: 2 212s [1] 1 2 212s ------------- 212s 212s Call: 212s CovOgk(x = x) 212s -> Method: Orthogonalized Gnanadesikan-Kettenring Estimator 212s 212s Robust Estimate of Location: 212s Air.Flow Water.Temp Acid.Conc. 212s 57.72 20.50 85.78 212s 212s Robust Estimate of Covariance: 212s Air.Flow Water.Temp Acid.Conc. 212s Air.Flow 38.423 11.306 18.605 212s Water.Temp 11.306 6.806 5.889 212s Acid.Conc. 18.605 5.889 29.840 212s -------------------------------------------------------- 212s coleman 20 5 212s Outliers: 3 212s [1] 1 6 10 212s ------------- 212s 212s Call: 212s CovOgk(x = x) 212s -> Method: Orthogonalized Gnanadesikan-Kettenring Estimator 212s 212s Robust Estimate of Location: 212s salaryP fatherWc sstatus teacherSc motherLev 212s 2.723 43.202 2.912 25.010 6.290 212s 212s Robust Estimate of Covariance: 212s salaryP fatherWc sstatus teacherSc motherLev 212s salaryP 0.12867 2.80048 0.92026 0.15118 0.06413 212s fatherWc 2.80048 678.72549 227.36415 9.30826 16.15102 212s sstatus 0.92026 227.36415 101.39094 3.38013 5.63283 212s teacherSc 0.15118 9.30826 3.38013 0.57112 0.27701 212s motherLev 0.06413 16.15102 5.63283 0.27701 0.44801 212s -------------------------------------------------------- 212s salinity 28 3 212s Outliers: 3 212s [1] 3 5 16 212s ------------- 212s 212s Call: 212s CovOgk(x = x) 212s -> Method: Orthogonalized Gnanadesikan-Kettenring Estimator 212s 212s Robust Estimate of Location: 212s X1 X2 X3 212s 10.74 2.68 22.99 212s 212s Robust Estimate of Covariance: 212s X1 X2 X3 212s X1 8.1047 -0.6365 -0.4720 212s X2 -0.6365 3.0976 -1.3520 212s X3 -0.4720 -1.3520 2.3648 212s -------------------------------------------------------- 212s hbk 75 3 212s Outliers: 14 212s [1] 1 2 3 4 5 6 7 8 9 10 11 12 13 14 212s ------------- 212s 212s Call: 212s CovOgk(x = x) 212s -> Method: Orthogonalized Gnanadesikan-Kettenring Estimator 212s 212s Robust Estimate of Location: 212s X1 X2 X3 212s 1.538 1.780 1.687 212s 212s Robust Estimate of Covariance: 212s X1 X2 X3 212s X1 1.11350 0.04992 0.11541 212s X2 0.04992 1.13338 0.13843 212s X3 0.11541 0.13843 1.05261 212s -------------------------------------------------------- 212s Animals 28 2 212s Outliers: 12 212s [1] 2 6 7 9 12 14 15 16 17 24 25 28 212s ------------- 212s 212s Call: 212s CovOgk(x = x) 212s -> Method: Orthogonalized Gnanadesikan-Kettenring Estimator 212s 212s Robust Estimate of Location: 212s body brain 212s 39.65 105.83 212s 212s Robust Estimate of Covariance: 212s body brain 212s body 3981 7558 212s brain 7558 16594 212s -------------------------------------------------------- 212s milk 86 8 212s Outliers: 22 212s [1] 1 2 3 11 12 13 14 15 16 17 18 20 27 41 44 47 50 70 74 75 77 85 212s ------------- 212s 212s Call: 212s CovOgk(x = x) 212s -> Method: Orthogonalized Gnanadesikan-Kettenring Estimator 212s 212s Robust Estimate of Location: 212s X1 X2 X3 X4 X5 X6 X7 X8 212s 1.03 35.80 33.10 26.15 25.13 25.06 123.06 14.39 212s 212s Robust Estimate of Covariance: 212s X1 X2 X3 X4 X5 X6 X7 212s X1 4.074e-07 5.255e-05 1.564e-04 1.506e-04 1.340e-04 1.234e-04 5.308e-04 212s X2 5.255e-05 1.464e+00 3.425e-01 2.465e-01 1.847e-01 2.484e-01 1.459e+00 212s X3 1.564e-04 3.425e-01 1.070e+00 7.834e-01 7.665e-01 7.808e-01 7.632e-01 212s X4 1.506e-04 2.465e-01 7.834e-01 6.178e-01 5.868e-01 5.959e-01 5.923e-01 212s X5 1.340e-04 1.847e-01 7.665e-01 5.868e-01 6.124e-01 5.967e-01 5.868e-01 212s X6 1.234e-04 2.484e-01 7.808e-01 5.959e-01 5.967e-01 6.253e-01 5.819e-01 212s X7 5.308e-04 1.459e+00 7.632e-01 5.923e-01 5.868e-01 5.819e-01 3.535e+00 212s X8 1.990e-07 1.851e-01 1.861e-01 1.210e-01 1.041e-01 1.116e-01 3.046e-01 212s X8 212s X1 1.990e-07 212s X2 1.851e-01 212s X3 1.861e-01 212s X4 1.210e-01 212s X5 1.041e-01 212s X6 1.116e-01 212s X7 3.046e-01 212s X8 1.292e-01 212s -------------------------------------------------------- 212s bushfire 38 5 212s Outliers: 17 212s [1] 7 8 9 10 11 12 28 29 30 31 32 33 34 35 36 37 38 212s ------------- 212s 212s Call: 212s CovOgk(x = x) 212s -> Method: Orthogonalized Gnanadesikan-Kettenring Estimator 212s 212s Robust Estimate of Location: 212s V1 V2 V3 V4 V5 212s 104.5 146.0 275.6 217.8 279.3 212s 212s Robust Estimate of Covariance: 212s V1 V2 V3 V4 V5 212s V1 266.8 203.2 -1380.7 -311.1 -252.2 212s V2 203.2 178.4 -910.9 -185.9 -155.9 212s V3 -1380.7 -910.9 8279.7 2035.5 1615.4 212s V4 -311.1 -185.9 2035.5 536.5 418.6 212s V5 -252.2 -155.9 1615.4 418.6 329.2 212s -------------------------------------------------------- 212s ======================================================== 212s > 212s BEGIN TEST tqda.R 212s 212s R version 4.3.3 (2024-02-29) -- "Angel Food Cake" 212s Copyright (C) 2024 The R Foundation for Statistical Computing 212s Platform: aarch64-unknown-linux-gnu (64-bit) 212s 212s R is free software and comes with ABSOLUTELY NO WARRANTY. 212s You are welcome to redistribute it under certain conditions. 212s Type 'license()' or 'licence()' for distribution details. 212s 212s R is a collaborative project with many contributors. 212s Type 'contributors()' for more information and 212s 'citation()' on how to cite R or R packages in publications. 212s 212s Type 'demo()' for some demos, 'help()' for on-line help, or 212s 'help.start()' for an HTML browser interface to help. 212s Type 'q()' to quit R. 212s 212s > ## VT::15.09.2013 - this will render the output independent 212s > ## from the version of the package 212s > suppressPackageStartupMessages(library(rrcov)) 212s > 212s > dodata <- function(method) { 212s + 212s + options(digits = 5) 212s + set.seed(101) # <<-- sub-sampling algorithm now based on R's RNG and seed 212s + 212s + tmp <- sys.call() 212s + cat("\nCall: ", deparse(substitute(tmp)),"\n") 212s + cat("===================================================\n") 212s + 212s + data(hemophilia); show(QdaCov(as.factor(gr)~., data=hemophilia, method=method)) 212s + data(anorexia, package="MASS"); show(QdaCov(Treat~., data=anorexia, method=method)) 212s + data(Pima.tr, package="MASS"); show(QdaCov(type~., data=Pima.tr, method=method)) 212s + data(iris); # show(QdaCov(Species~., data=iris, method=method)) 212s + data(crabs, package="MASS"); # show(QdaCov(sp~., data=crabs, method=method)) 212s + 212s + show(QdaClassic(as.factor(gr)~., data=hemophilia)) 212s + show(QdaClassic(Treat~., data=anorexia)) 212s + show(QdaClassic(type~., data=Pima.tr)) 212s + show(QdaClassic(Species~., data=iris)) 212s + ## show(QdaClassic(sp~., data=crabs)) 212s + cat("===================================================\n") 212s + } 212s > 212s > 212s > ## -- now do it: 212s > dodata(method="mcd") 212s 212s Call: dodata(method = "mcd") 212s =================================================== 212s Call: 212s QdaCov(as.factor(gr) ~ ., data = hemophilia, method = method) 212s 212s Prior Probabilities of Groups: 212s carrier normal 212s 0.6 0.4 212s 212s Group means: 212s AHFactivity AHFantigen 212s carrier -0.30795 -0.0059911 212s normal -0.12920 -0.0603000 212s 212s Group: carrier 212s AHFactivity AHFantigen 212s AHFactivity 0.023784 0.015376 212s AHFantigen 0.015376 0.024035 212s 212s Group: normal 212s AHFactivity AHFantigen 212s AHFactivity 0.0057546 0.0042606 212s AHFantigen 0.0042606 0.0084914 212s Call: 212s QdaCov(Treat ~ ., data = anorexia, method = method) 212s 212s Prior Probabilities of Groups: 212s CBT Cont FT 212s 0.40278 0.36111 0.23611 212s 212s Group means: 212s Prewt Postwt 212s CBT 82.633 82.950 212s Cont 81.558 81.108 212s FT 84.331 94.762 212s 212s Group: CBT 212s Prewt Postwt 212s Prewt 9.8671 8.6611 212s Postwt 8.6611 11.8966 212s 212s Group: Cont 212s Prewt Postwt 212s Prewt 32.5705 -4.3705 212s Postwt -4.3705 22.5079 212s 212s Group: FT 212s Prewt Postwt 212s Prewt 33.056 10.814 212s Postwt 10.814 14.265 212s Call: 212s QdaCov(type ~ ., data = Pima.tr, method = method) 212s 212s Prior Probabilities of Groups: 212s No Yes 212s 0.66 0.34 212s 212s Group means: 212s npreg glu bp skin bmi ped age 212s No 1.8602 107.69 67.344 25.29 30.642 0.40777 24.667 212s Yes 5.3167 145.85 74.283 31.80 34.095 0.49533 37.883 212s 212s Group: No 212s npreg glu bp skin bmi ped age 212s npreg 2.221983 -0.18658 1.86507 -0.44427 0.1725348 -0.0683616 2.63439 212s glu -0.186582 471.88789 45.28021 8.95404 30.6551510 -0.6359899 3.50218 212s bp 1.865066 45.28021 110.09787 26.11192 14.4739180 -0.2104074 13.23392 212s skin -0.444272 8.95404 26.11192 118.30521 52.3115719 -0.2995751 8.65861 212s bmi 0.172535 30.65515 14.47392 52.31157 43.3140415 0.0079866 6.75720 212s ped -0.068362 -0.63599 -0.21041 -0.29958 0.0079866 0.0587710 -0.18683 212s age 2.634387 3.50218 13.23392 8.65861 6.7572019 -0.1868284 12.09493 212s 212s Group: Yes 212s npreg glu bp skin bmi ped age 212s npreg 17.875215 -13.740021 9.03580 4.498580 1.787458 0.079504 26.92283 212s glu -13.740021 917.719003 55.30399 27.976265 10.755113 0.092673 38.94970 212s bp 9.035798 55.303991 129.97953 34.130200 10.104275 0.198342 32.95351 212s skin 4.498580 27.976265 34.13020 101.842647 30.297210 0.064739 3.59427 212s bmi 1.787458 10.755113 10.10428 30.297210 22.529467 0.084369 -6.64317 212s ped 0.079504 0.092673 0.19834 0.064739 0.084369 0.066667 0.11199 212s age 26.922828 38.949697 32.95351 3.594266 -6.643165 0.111992 143.69752 212s Call: 212s QdaClassic(as.factor(gr) ~ ., data = hemophilia) 212s 212s Prior Probabilities of Groups: 212s carrier normal 212s 0.6 0.4 212s 212s Group means: 212s AHFactivity AHFantigen 212s carrier -0.30795 -0.0059911 212s normal -0.13487 -0.0778567 212s 212s Group: carrier 212s AHFactivity AHFantigen 212s AHFactivity 0.023784 0.015376 212s AHFantigen 0.015376 0.024035 212s 212s Group: normal 212s AHFactivity AHFantigen 212s AHFactivity 0.020897 0.015515 212s AHFantigen 0.015515 0.017920 212s Call: 212s QdaClassic(Treat ~ ., data = anorexia) 212s 212s Prior Probabilities of Groups: 212s CBT Cont FT 212s 0.40278 0.36111 0.23611 212s 212s Group means: 212s Prewt Postwt 212s CBT 82.690 85.697 212s Cont 81.558 81.108 212s FT 83.229 90.494 212s 212s Group: CBT 212s Prewt Postwt 212s Prewt 23.479 19.910 212s Postwt 19.910 69.755 212s 212s Group: Cont 212s Prewt Postwt 212s Prewt 32.5705 -4.3705 212s Postwt -4.3705 22.5079 212s 212s Group: FT 212s Prewt Postwt 212s Prewt 25.167 22.883 212s Postwt 22.883 71.827 212s Call: 212s QdaClassic(type ~ ., data = Pima.tr) 212s 212s Prior Probabilities of Groups: 212s No Yes 212s 0.66 0.34 212s 212s Group means: 212s npreg glu bp skin bmi ped age 212s No 2.9167 113.11 69.545 27.205 31.074 0.41548 29.235 212s Yes 4.8382 145.06 74.588 33.118 34.709 0.54866 37.691 212s 212s Group: No 212s npreg glu bp skin bmi ped age 212s npreg 7.878499 10.77226 8.190840 2.910305 -0.035751 -0.207341 16.82888 212s glu 10.772265 709.56118 81.430257 13.237682 19.037867 -0.518609 59.01307 212s bp 8.190840 81.43026 122.845246 33.879944 16.612630 -0.077183 46.78695 212s skin 2.910305 13.23768 33.879944 119.446391 50.125920 0.074282 18.47068 212s bmi -0.035751 19.03787 16.612630 50.125920 40.722996 0.145242 6.99999 212s ped -0.207341 -0.51861 -0.077183 0.074282 0.145242 0.071388 -0.53814 212s age 16.828880 59.01307 46.786954 18.470680 6.999988 -0.538138 91.08183 212s 212s Group: Yes 212s npreg glu bp skin bmi ped age 212s npreg 15.77941 -8.199298 6.42493 -0.51800 -1.03288 -0.133011 21.93437 212s glu -8.19930 907.250219 23.71115 87.51536 9.98156 -0.082159 58.12291 212s bp 6.42493 23.711150 134.18613 19.70588 5.15891 -0.795470 26.30378 212s skin -0.51800 87.515364 19.70588 151.32924 28.28551 0.347951 26.67867 212s bmi -1.03288 9.981563 5.15891 28.28551 23.14529 0.457694 -7.91216 212s ped -0.13301 -0.082159 -0.79547 0.34795 0.45769 0.128883 -0.41737 212s age 21.93437 58.122915 26.30378 26.67867 -7.91216 -0.417375 131.79873 212s Call: 212s QdaClassic(Species ~ ., data = iris) 212s 212s Prior Probabilities of Groups: 212s setosa versicolor virginica 212s 0.33333 0.33333 0.33333 212s 212s Group means: 212s Sepal.Length Sepal.Width Petal.Length Petal.Width 212s setosa 5.006 3.428 1.462 0.246 212s versicolor 5.936 2.770 4.260 1.326 212s virginica 6.588 2.974 5.552 2.026 212s 212s Group: setosa 212s Sepal.Length Sepal.Width Petal.Length Petal.Width 212s Sepal.Length 0.124249 0.099216 0.0163551 0.0103306 212s Sepal.Width 0.099216 0.143690 0.0116980 0.0092980 212s Petal.Length 0.016355 0.011698 0.0301592 0.0060694 212s Petal.Width 0.010331 0.009298 0.0060694 0.0111061 212s 212s Group: versicolor 212s Sepal.Length Sepal.Width Petal.Length Petal.Width 212s Sepal.Length 0.266433 0.085184 0.182898 0.055780 212s Sepal.Width 0.085184 0.098469 0.082653 0.041204 212s Petal.Length 0.182898 0.082653 0.220816 0.073102 212s Petal.Width 0.055780 0.041204 0.073102 0.039106 212s 212s Group: virginica 212s Sepal.Length Sepal.Width Petal.Length Petal.Width 212s Sepal.Length 0.404343 0.093763 0.303290 0.049094 212s Sepal.Width 0.093763 0.104004 0.071380 0.047629 212s Petal.Length 0.303290 0.071380 0.304588 0.048824 212s Petal.Width 0.049094 0.047629 0.048824 0.075433 212s =================================================== 212s > dodata(method="m") 212s 212s Call: dodata(method = "m") 212s =================================================== 212s Call: 212s QdaCov(as.factor(gr) ~ ., data = hemophilia, method = method) 212s 212s Prior Probabilities of Groups: 212s carrier normal 212s 0.6 0.4 212s 212s Group means: 212s AHFactivity AHFantigen 212s carrier -0.29810 -0.0028222 212s normal -0.13081 -0.0675283 212s 212s Group: carrier 212s AHFactivity AHFantigen 212s AHFactivity 0.026018 0.017653 212s AHFantigen 0.017653 0.030128 212s 212s Group: normal 212s AHFactivity AHFantigen 212s AHFactivity 0.0081933 0.0065737 212s AHFantigen 0.0065737 0.0118565 212s Call: 212s QdaCov(Treat ~ ., data = anorexia, method = method) 212s 212s Prior Probabilities of Groups: 212s CBT Cont FT 212s 0.40278 0.36111 0.23611 212s 212s Group means: 212s Prewt Postwt 212s CBT 82.436 82.631 212s Cont 81.559 80.272 212s FT 85.120 94.657 212s 212s Group: CBT 212s Prewt Postwt 212s Prewt 23.630 25.128 212s Postwt 25.128 38.142 212s 212s Group: Cont 212s Prewt Postwt 212s Prewt 35.8824 -8.2405 212s Postwt -8.2405 23.7416 212s 212s Group: FT 212s Prewt Postwt 212s Prewt 33.805 18.206 212s Postwt 18.206 24.639 212s Call: 212s QdaCov(type ~ ., data = Pima.tr, method = method) 212s 212s Prior Probabilities of Groups: 212s No Yes 212s 0.66 0.34 212s 212s Group means: 212s npreg glu bp skin bmi ped age 212s No 2.5225 111.26 68.081 26.640 30.801 0.40452 26.306 212s Yes 5.0702 144.32 75.088 31.982 34.267 0.47004 37.140 212s 212s Group: No 212s npreg glu bp skin bmi ped age 212s npreg 5.74219 14.47051 6.63766 4.98559 0.826570 -0.128106 10.71303 212s glu 14.47051 591.08717 68.81219 44.73311 40.658393 -0.545716 38.01918 212s bp 6.63766 68.81219 121.02716 30.46466 16.789801 -0.320065 25.29371 212s skin 4.98559 44.73311 30.46466 136.52176 56.604475 -0.250711 19.73259 212s bmi 0.82657 40.65839 16.78980 56.60447 47.859747 0.046358 6.94523 212s ped -0.12811 -0.54572 -0.32006 -0.25071 0.046358 0.061485 -0.34653 212s age 10.71303 38.01918 25.29371 19.73259 6.945227 -0.346527 35.66101 212s 212s Group: Yes 212s npreg glu bp skin bmi ped age 212s npreg 15.98861 -1.2430 10.48556 9.05947 2.425316 0.162453 30.149872 212s glu -1.24304 867.1076 46.43838 25.92297 5.517382 1.044360 31.152650 212s bp 10.48556 46.4384 130.12536 17.21407 6.343942 -0.235121 41.091494 212s skin 9.05947 25.9230 17.21407 85.96314 26.089017 0.170061 14.562516 212s bmi 2.42532 5.5174 6.34394 26.08902 22.051976 0.097786 -5.297971 212s ped 0.16245 1.0444 -0.23512 0.17006 0.097786 0.057112 0.055286 212s age 30.14987 31.1527 41.09149 14.56252 -5.297971 0.055286 137.440921 212s Call: 212s QdaClassic(as.factor(gr) ~ ., data = hemophilia) 212s 212s Prior Probabilities of Groups: 212s carrier normal 212s 0.6 0.4 212s 212s Group means: 212s AHFactivity AHFantigen 212s carrier -0.30795 -0.0059911 212s normal -0.13487 -0.0778567 212s 212s Group: carrier 212s AHFactivity AHFantigen 212s AHFactivity 0.023784 0.015376 212s AHFantigen 0.015376 0.024035 212s 212s Group: normal 212s AHFactivity AHFantigen 212s AHFactivity 0.020897 0.015515 212s AHFantigen 0.015515 0.017920 212s Call: 212s QdaClassic(Treat ~ ., data = anorexia) 212s 212s Prior Probabilities of Groups: 212s CBT Cont FT 212s 0.40278 0.36111 0.23611 212s 212s Group means: 212s Prewt Postwt 212s CBT 82.690 85.697 212s Cont 81.558 81.108 212s FT 83.229 90.494 212s 212s Group: CBT 212s Prewt Postwt 212s Prewt 23.479 19.910 212s Postwt 19.910 69.755 212s 212s Group: Cont 212s Prewt Postwt 212s Prewt 32.5705 -4.3705 212s Postwt -4.3705 22.5079 212s 212s Group: FT 212s Prewt Postwt 212s Prewt 25.167 22.883 212s Postwt 22.883 71.827 212s Call: 212s QdaClassic(type ~ ., data = Pima.tr) 212s 212s Prior Probabilities of Groups: 212s No Yes 212s 0.66 0.34 212s 212s Group means: 212s npreg glu bp skin bmi ped age 212s No 2.9167 113.11 69.545 27.205 31.074 0.41548 29.235 212s Yes 4.8382 145.06 74.588 33.118 34.709 0.54866 37.691 212s 212s Group: No 212s npreg glu bp skin bmi ped age 212s npreg 7.878499 10.77226 8.190840 2.910305 -0.035751 -0.207341 16.82888 212s glu 10.772265 709.56118 81.430257 13.237682 19.037867 -0.518609 59.01307 212s bp 8.190840 81.43026 122.845246 33.879944 16.612630 -0.077183 46.78695 212s skin 2.910305 13.23768 33.879944 119.446391 50.125920 0.074282 18.47068 212s bmi -0.035751 19.03787 16.612630 50.125920 40.722996 0.145242 6.99999 212s ped -0.207341 -0.51861 -0.077183 0.074282 0.145242 0.071388 -0.53814 212s age 16.828880 59.01307 46.786954 18.470680 6.999988 -0.538138 91.08183 212s 212s Group: Yes 212s npreg glu bp skin bmi ped age 212s npreg 15.77941 -8.199298 6.42493 -0.51800 -1.03288 -0.133011 21.93437 212s glu -8.19930 907.250219 23.71115 87.51536 9.98156 -0.082159 58.12291 212s bp 6.42493 23.711150 134.18613 19.70588 5.15891 -0.795470 26.30378 212s skin -0.51800 87.515364 19.70588 151.32924 28.28551 0.347951 26.67867 212s bmi -1.03288 9.981563 5.15891 28.28551 23.14529 0.457694 -7.91216 212s ped -0.13301 -0.082159 -0.79547 0.34795 0.45769 0.128883 -0.41737 212s age 21.93437 58.122915 26.30378 26.67867 -7.91216 -0.417375 131.79873 212s Call: 212s QdaClassic(Species ~ ., data = iris) 212s 212s Prior Probabilities of Groups: 212s setosa versicolor virginica 212s 0.33333 0.33333 0.33333 212s 212s Group means: 212s Sepal.Length Sepal.Width Petal.Length Petal.Width 212s setosa 5.006 3.428 1.462 0.246 212s versicolor 5.936 2.770 4.260 1.326 212s virginica 6.588 2.974 5.552 2.026 212s 212s Group: setosa 212s Sepal.Length Sepal.Width Petal.Length Petal.Width 212s Sepal.Length 0.124249 0.099216 0.0163551 0.0103306 212s Sepal.Width 0.099216 0.143690 0.0116980 0.0092980 212s Petal.Length 0.016355 0.011698 0.0301592 0.0060694 212s Petal.Width 0.010331 0.009298 0.0060694 0.0111061 212s 212s Group: versicolor 212s Sepal.Length Sepal.Width Petal.Length Petal.Width 212s Sepal.Length 0.266433 0.085184 0.182898 0.055780 212s Sepal.Width 0.085184 0.098469 0.082653 0.041204 212s Petal.Length 0.182898 0.082653 0.220816 0.073102 212s Petal.Width 0.055780 0.041204 0.073102 0.039106 212s 212s Group: virginica 212s Sepal.Length Sepal.Width Petal.Length Petal.Width 212s Sepal.Length 0.404343 0.093763 0.303290 0.049094 212s Sepal.Width 0.093763 0.104004 0.071380 0.047629 212s Petal.Length 0.303290 0.071380 0.304588 0.048824 212s Petal.Width 0.049094 0.047629 0.048824 0.075433 212s =================================================== 212s > dodata(method="ogk") 212s 212s Call: dodata(method = "ogk") 212s =================================================== 212s Call: 212s QdaCov(as.factor(gr) ~ ., data = hemophilia, method = method) 212s 212s Prior Probabilities of Groups: 212s carrier normal 212s 0.6 0.4 212s 212s Group means: 212s AHFactivity AHFantigen 212s carrier -0.29324 0.00033953 212s normal -0.12744 -0.06628182 212s 212s Group: carrier 212s AHFactivity AHFantigen 212s AHFactivity 0.019260 0.013026 212s AHFantigen 0.013026 0.021889 212s 212s Group: normal 212s AHFactivity AHFantigen 212s AHFactivity 0.0049651 0.0039707 212s AHFantigen 0.0039707 0.0066084 212s Call: 212s QdaCov(Treat ~ ., data = anorexia, method = method) 212s 212s Prior Probabilities of Groups: 212s CBT Cont FT 212s 0.40278 0.36111 0.23611 212s 212s Group means: 212s Prewt Postwt 212s CBT 82.587 82.709 212s Cont 81.558 81.108 212s FT 85.110 94.470 212s 212s Group: CBT 212s Prewt Postwt 212s Prewt 10.452 15.115 212s Postwt 15.115 37.085 212s 212s Group: Cont 212s Prewt Postwt 212s Prewt 31.3178 -4.2024 212s Postwt -4.2024 21.6422 212s 212s Group: FT 212s Prewt Postwt 212s Prewt 5.5309 1.4813 212s Postwt 1.4813 7.5501 212s Call: 212s QdaCov(type ~ ., data = Pima.tr, method = method) 212s 212s Prior Probabilities of Groups: 212s No Yes 212s 0.66 0.34 212s 212s Group means: 212s npreg glu bp skin bmi ped age 212s No 2.4286 110.35 67.495 25.905 30.275 0.39587 26.248 212s Yes 5.1964 142.71 75.357 32.732 34.809 0.48823 37.607 212s 212s Group: No 212s npreg glu bp skin bmi ped age 212s npreg 3.97823 8.70612 4.58776 4.16463 0.250612 -0.117238 8.21769 212s glu 8.70612 448.91392 51.71120 38.66213 21.816345 -0.296524 24.29370 212s bp 4.58776 51.71120 99.41188 24.27574 10.491311 -0.290753 20.02975 212s skin 4.16463 38.66213 24.27574 98.61950 41.682404 -0.335213 16.60454 212s bmi 0.25061 21.81634 10.49131 41.68240 35.237101 -0.019774 5.12042 212s ped -0.11724 -0.29652 -0.29075 -0.33521 -0.019774 0.051431 -0.36275 212s age 8.21769 24.29370 20.02975 16.60454 5.120417 -0.362748 31.32916 212s 212s Group: Yes 212s npreg glu bp skin bmi ped age 212s npreg 15.26499 6.30612 3.01913 3.76690 0.94825 0.12076 22.64860 212s glu 6.30612 688.16837 22.22704 12.81633 3.55791 0.68833 32.28061 212s bp 3.01913 22.22704 103.97959 9.95281 2.09860 0.45672 31.17602 212s skin 3.76690 12.81633 9.95281 67.51754 19.51489 0.59831 -2.35523 212s bmi 0.94825 3.55791 2.09860 19.51489 17.20331 0.24347 -6.88221 212s ped 0.12076 0.68833 0.45672 0.59831 0.24347 0.05933 0.43798 212s age 22.64860 32.28061 31.17602 -2.35523 -6.88221 0.43798 111.16709 212s Call: 212s QdaClassic(as.factor(gr) ~ ., data = hemophilia) 212s 212s Prior Probabilities of Groups: 212s carrier normal 212s 0.6 0.4 212s 212s Group means: 212s AHFactivity AHFantigen 212s carrier -0.30795 -0.0059911 212s normal -0.13487 -0.0778567 212s 212s Group: carrier 212s AHFactivity AHFantigen 212s AHFactivity 0.023784 0.015376 212s AHFantigen 0.015376 0.024035 212s 212s Group: normal 212s AHFactivity AHFantigen 212s AHFactivity 0.020897 0.015515 212s AHFantigen 0.015515 0.017920 212s Call: 212s QdaClassic(Treat ~ ., data = anorexia) 212s 212s Prior Probabilities of Groups: 212s CBT Cont FT 212s 0.40278 0.36111 0.23611 212s 212s Group means: 212s Prewt Postwt 212s CBT 82.690 85.697 212s Cont 81.558 81.108 212s FT 83.229 90.494 212s 212s Group: CBT 212s Prewt Postwt 212s Prewt 23.479 19.910 212s Postwt 19.910 69.755 212s 212s Group: Cont 212s Prewt Postwt 212s Prewt 32.5705 -4.3705 212s Postwt -4.3705 22.5079 212s 212s Group: FT 212s Prewt Postwt 212s Prewt 25.167 22.883 212s Postwt 22.883 71.827 212s Call: 212s QdaClassic(type ~ ., data = Pima.tr) 212s 212s Prior Probabilities of Groups: 212s No Yes 212s 0.66 0.34 212s 212s Group means: 212s npreg glu bp skin bmi ped age 212s No 2.9167 113.11 69.545 27.205 31.074 0.41548 29.235 212s Yes 4.8382 145.06 74.588 33.118 34.709 0.54866 37.691 212s 212s Group: No 212s npreg glu bp skin bmi ped age 212s npreg 7.878499 10.77226 8.190840 2.910305 -0.035751 -0.207341 16.82888 212s glu 10.772265 709.56118 81.430257 13.237682 19.037867 -0.518609 59.01307 212s bp 8.190840 81.43026 122.845246 33.879944 16.612630 -0.077183 46.78695 212s skin 2.910305 13.23768 33.879944 119.446391 50.125920 0.074282 18.47068 212s bmi -0.035751 19.03787 16.612630 50.125920 40.722996 0.145242 6.99999 212s ped -0.207341 -0.51861 -0.077183 0.074282 0.145242 0.071388 -0.53814 212s age 16.828880 59.01307 46.786954 18.470680 6.999988 -0.538138 91.08183 212s 212s Group: Yes 212s npreg glu bp skin bmi ped age 212s npreg 15.77941 -8.199298 6.42493 -0.51800 -1.03288 -0.133011 21.93437 212s glu -8.19930 907.250219 23.71115 87.51536 9.98156 -0.082159 58.12291 212s bp 6.42493 23.711150 134.18613 19.70588 5.15891 -0.795470 26.30378 212s skin -0.51800 87.515364 19.70588 151.32924 28.28551 0.347951 26.67867 212s bmi -1.03288 9.981563 5.15891 28.28551 23.14529 0.457694 -7.91216 212s ped -0.13301 -0.082159 -0.79547 0.34795 0.45769 0.128883 -0.41737 212s age 21.93437 58.122915 26.30378 26.67867 -7.91216 -0.417375 131.79873 212s Call: 212s QdaClassic(Species ~ ., data = iris) 212s 212s Prior Probabilities of Groups: 212s setosa versicolor virginica 212s 0.33333 0.33333 0.33333 212s 212s Group means: 212s Sepal.Length Sepal.Width Petal.Length Petal.Width 212s setosa 5.006 3.428 1.462 0.246 212s versicolor 5.936 2.770 4.260 1.326 212s virginica 6.588 2.974 5.552 2.026 212s 212s Group: setosa 212s Sepal.Length Sepal.Width Petal.Length Petal.Width 212s Sepal.Length 0.124249 0.099216 0.0163551 0.0103306 212s Sepal.Width 0.099216 0.143690 0.0116980 0.0092980 212s Petal.Length 0.016355 0.011698 0.0301592 0.0060694 212s Petal.Width 0.010331 0.009298 0.0060694 0.0111061 212s 212s Group: versicolor 212s Sepal.Length Sepal.Width Petal.Length Petal.Width 212s Sepal.Length 0.266433 0.085184 0.182898 0.055780 212s Sepal.Width 0.085184 0.098469 0.082653 0.041204 212s Petal.Length 0.182898 0.082653 0.220816 0.073102 212s Petal.Width 0.055780 0.041204 0.073102 0.039106 212s 212s Group: virginica 212s Sepal.Length Sepal.Width Petal.Length Petal.Width 212s Sepal.Length 0.404343 0.093763 0.303290 0.049094 212s Sepal.Width 0.093763 0.104004 0.071380 0.047629 212s Petal.Length 0.303290 0.071380 0.304588 0.048824 212s Petal.Width 0.049094 0.047629 0.048824 0.075433 212s =================================================== 212s > dodata(method="sde") 212s 212s Call: dodata(method = "sde") 212s =================================================== 212s Call: 212s QdaCov(as.factor(gr) ~ ., data = hemophilia, method = method) 212s 212s Prior Probabilities of Groups: 212s carrier normal 212s 0.6 0.4 212s 212s Group means: 212s AHFactivity AHFantigen 212s carrier -0.29834 -0.0032286 212s normal -0.12944 -0.0676930 212s 212s Group: carrier 212s AHFactivity AHFantigen 212s AHFactivity 0.025398 0.017810 212s AHFantigen 0.017810 0.030639 212s 212s Group: normal 212s AHFactivity AHFantigen 212s AHFactivity 0.0083435 0.0067686 212s AHFantigen 0.0067686 0.0119565 212s Call: 212s QdaCov(Treat ~ ., data = anorexia, method = method) 212s 212s Prior Probabilities of Groups: 212s CBT Cont FT 212s 0.40278 0.36111 0.23611 212s 212s Group means: 212s Prewt Postwt 212s CBT 82.949 83.323 212s Cont 81.484 80.840 212s FT 84.596 93.835 212s 212s Group: CBT 212s Prewt Postwt 212s Prewt 22.283 17.084 212s Postwt 17.084 25.308 212s 212s Group: Cont 212s Prewt Postwt 212s Prewt 37.1864 -8.8896 212s Postwt -8.8896 31.1930 212s 212s Group: FT 212s Prewt Postwt 212s Prewt 20.7108 3.1531 212s Postwt 3.1531 25.7046 212s Call: 212s QdaCov(type ~ ., data = Pima.tr, method = method) 212s 212s Prior Probabilities of Groups: 212s No Yes 212s 0.66 0.34 212s 212s Group means: 212s npreg glu bp skin bmi ped age 212s No 2.2567 109.91 67.538 25.484 30.355 0.38618 25.628 212s Yes 5.2216 141.64 75.048 32.349 34.387 0.47742 37.634 212s 212s Group: No 212s npreg glu bp skin bmi ped age 212s npreg 4.396832 10.20629 5.43346 4.38313 7.9891e-01 -0.09389257 7.45638 212s glu 10.206286 601.12211 56.62047 49.67071 3.3829e+01 -0.31896741 31.64508 212s bp 5.433462 56.62047 120.38052 34.38984 1.4817e+01 -0.21784446 26.44853 212s skin 4.383134 49.67071 34.38984 136.94931 6.1576e+01 -0.47532490 17.74141 212s bmi 0.798908 33.82928 14.81668 61.57578 5.1441e+01 0.00061983 8.56856 212s ped -0.093893 -0.31897 -0.21784 -0.47532 6.1983e-04 0.06012655 -0.26872 212s age 7.456376 31.64508 26.44853 17.74141 8.5686e+00 -0.26872005 29.93856 212s 212s Group: Yes 212s npreg glu bp skin bmi ped age 212s npreg 15.91978 7.7491 7.24229 10.46802 5.40627 0.320434 25.88314 212s glu 7.74907 856.4955 58.59554 29.65331 11.44745 1.388745 38.24430 212s bp 7.24229 58.5955 89.66288 21.36597 6.46859 0.764486 36.30462 212s skin 10.46802 29.6533 21.36597 86.79253 26.22071 0.620654 5.28665 212s bmi 5.40627 11.4475 6.46859 26.22071 20.12351 0.211701 0.71583 212s ped 0.32043 1.3887 0.76449 0.62065 0.21170 0.062727 0.93743 212s age 25.88314 38.2443 36.30462 5.28665 0.71583 0.937430 136.24335 212s Call: 212s QdaClassic(as.factor(gr) ~ ., data = hemophilia) 212s 212s Prior Probabilities of Groups: 212s carrier normal 212s 0.6 0.4 212s 212s Group means: 212s AHFactivity AHFantigen 212s carrier -0.30795 -0.0059911 212s normal -0.13487 -0.0778567 212s 212s Group: carrier 212s AHFactivity AHFantigen 212s AHFactivity 0.023784 0.015376 212s AHFantigen 0.015376 0.024035 212s 212s Group: normal 212s AHFactivity AHFantigen 212s AHFactivity 0.020897 0.015515 212s AHFantigen 0.015515 0.017920 212s Call: 212s QdaClassic(Treat ~ ., data = anorexia) 212s 212s Prior Probabilities of Groups: 212s CBT Cont FT 212s 0.40278 0.36111 0.23611 212s 212s Group means: 212s Prewt Postwt 212s CBT 82.690 85.697 212s Cont 81.558 81.108 212s FT 83.229 90.494 212s 212s Group: CBT 212s Prewt Postwt 212s Prewt 23.479 19.910 212s Postwt 19.910 69.755 212s 212s Group: Cont 212s Prewt Postwt 212s Prewt 32.5705 -4.3705 212s Postwt -4.3705 22.5079 212s 212s Group: FT 212s Prewt Postwt 212s Prewt 25.167 22.883 212s Postwt 22.883 71.827 212s Call: 212s QdaClassic(type ~ ., data = Pima.tr) 212s 212s Prior Probabilities of Groups: 212s No Yes 212s 0.66 0.34 212s 212s Group means: 212s npreg glu bp skin bmi ped age 212s No 2.9167 113.11 69.545 27.205 31.074 0.41548 29.235 212s Yes 4.8382 145.06 74.588 33.118 34.709 0.54866 37.691 212s 212s Group: No 212s npreg glu bp skin bmi ped age 212s npreg 7.878499 10.77226 8.190840 2.910305 -0.035751 -0.207341 16.82888 212s glu 10.772265 709.56118 81.430257 13.237682 19.037867 -0.518609 59.01307 212s bp 8.190840 81.43026 122.845246 33.879944 16.612630 -0.077183 46.78695 212s skin 2.910305 13.23768 33.879944 119.446391 50.125920 0.074282 18.47068 212s bmi -0.035751 19.03787 16.612630 50.125920 40.722996 0.145242 6.99999 212s ped -0.207341 -0.51861 -0.077183 0.074282 0.145242 0.071388 -0.53814 212s age 16.828880 59.01307 46.786954 18.470680 6.999988 -0.538138 91.08183 212s 212s Group: Yes 212s npreg glu bp skin bmi ped age 212s npreg 15.77941 -8.199298 6.42493 -0.51800 -1.03288 -0.133011 21.93437 212s glu -8.19930 907.250219 23.71115 87.51536 9.98156 -0.082159 58.12291 212s bp 6.42493 23.711150 134.18613 19.70588 5.15891 -0.795470 26.30378 212s skin -0.51800 87.515364 19.70588 151.32924 28.28551 0.347951 26.67867 212s bmi -1.03288 9.981563 5.15891 28.28551 23.14529 0.457694 -7.91216 212s ped -0.13301 -0.082159 -0.79547 0.34795 0.45769 0.128883 -0.41737 212s age 21.93437 58.122915 26.30378 26.67867 -7.91216 -0.417375 131.79873 212s Call: 212s QdaClassic(Species ~ ., data = iris) 212s 212s Prior Probabilities of Groups: 212s setosa versicolor virginica 212s 0.33333 0.33333 0.33333 212s 212s Group means: 212s Sepal.Length Sepal.Width Petal.Length Petal.Width 212s setosa 5.006 3.428 1.462 0.246 212s versicolor 5.936 2.770 4.260 1.326 212s virginica 6.588 2.974 5.552 2.026 212s 212s Group: setosa 212s Sepal.Length Sepal.Width Petal.Length Petal.Width 212s Sepal.Length 0.124249 0.099216 0.0163551 0.0103306 212s Sepal.Width 0.099216 0.143690 0.0116980 0.0092980 212s Petal.Length 0.016355 0.011698 0.0301592 0.0060694 212s Petal.Width 0.010331 0.009298 0.0060694 0.0111061 212s 212s Group: versicolor 212s Sepal.Length Sepal.Width Petal.Length Petal.Width 212s Sepal.Length 0.266433 0.085184 0.182898 0.055780 212s Sepal.Width 0.085184 0.098469 0.082653 0.041204 212s Petal.Length 0.182898 0.082653 0.220816 0.073102 212s Petal.Width 0.055780 0.041204 0.073102 0.039106 212s 212s Group: virginica 212s Sepal.Length Sepal.Width Petal.Length Petal.Width 212s Sepal.Length 0.404343 0.093763 0.303290 0.049094 212s Sepal.Width 0.093763 0.104004 0.071380 0.047629 212s Petal.Length 0.303290 0.071380 0.304588 0.048824 212s Petal.Width 0.049094 0.047629 0.048824 0.075433 212s =================================================== 212s > 212s BEGIN TEST tsde.R 212s 212s R version 4.3.3 (2024-02-29) -- "Angel Food Cake" 212s Copyright (C) 2024 The R Foundation for Statistical Computing 212s Platform: aarch64-unknown-linux-gnu (64-bit) 212s 212s R is free software and comes with ABSOLUTELY NO WARRANTY. 212s You are welcome to redistribute it under certain conditions. 212s Type 'license()' or 'licence()' for distribution details. 212s 212s R is a collaborative project with many contributors. 212s Type 'contributors()' for more information and 212s 'citation()' on how to cite R or R packages in publications. 212s 212s Type 'demo()' for some demos, 'help()' for on-line help, or 212s 'help.start()' for an HTML browser interface to help. 212s Type 'q()' to quit R. 212s 212s > ## Test for singularity 212s > doexact <- function(){ 212s + exact <-function(){ 212s + n1 <- 45 212s + p <- 2 212s + x1 <- matrix(rnorm(p*n1),nrow=n1, ncol=p) 212s + x1[,p] <- x1[,p] + 3 212s + ## library(MASS) 212s + ## x1 <- mvrnorm(n=n1, mu=c(0,3), Sigma=diag(1,nrow=p)) 212s + 212s + n2 <- 55 212s + m1 <- 0 212s + m2 <- 3 212s + x2 <- cbind(rnorm(n2),rep(m2,n2)) 212s + x<-rbind(x1,x2) 212s + colnames(x) <- c("X1","X2") 212s + x 212s + } 212s + print(CovSde(exact())) 212s + } 212s > 212s > dodata <- function(nrep=1, time=FALSE, short=FALSE, full=TRUE){ 212s + 212s + domcd <- function(x, xname, nrep=1){ 212s + n <- dim(x)[1] 212s + p <- dim(x)[2] 212s + 212s + mcd<-CovSde(x) 212s + 212s + if(time){ 212s + xtime <- system.time(dorep(x, nrep))[1]/nrep 212s + xres <- sprintf("%3d %3d %3d\n", dim(x)[1], dim(x)[2], xtime) 212s + } 212s + else{ 212s + xres <- sprintf("%3d %3d\n", dim(x)[1], dim(x)[2]) 212s + } 212s + lpad<-lname-nchar(xname) 212s + cat(pad.right(xname,lpad), xres) 212s + 212s + if(!short){ 212s + 212s + ibad <- which(mcd@wt==0) 212s + names(ibad) <- NULL 212s + nbad <- length(ibad) 212s + cat("Outliers: ",nbad,"\n") 212s + if(nbad > 0) 212s + print(ibad) 212s + if(full){ 212s + cat("-------------\n") 212s + show(mcd) 212s + } 212s + cat("--------------------------------------------------------\n") 212s + } 212s + } 212s + 212s + options(digits = 5) 212s + set.seed(101) # <<-- sub-sampling algorithm now based on R's RNG and seed 212s + 212s + lname <- 20 212s + 212s + ## VT::15.09.2013 - this will render the output independent 212s + ## from the version of the package 212s + suppressPackageStartupMessages(library(rrcov)) 212s + 212s + data(heart) 212s + data(starsCYG) 212s + data(phosphor) 212s + data(stackloss) 212s + data(coleman) 212s + data(salinity) 212s + data(wood) 212s + 212s + data(hbk) 212s + 212s + data(Animals, package = "MASS") 212s + brain <- Animals[c(1:24, 26:25, 27:28),] 212s + data(milk) 212s + data(bushfire) 212s + 212s + tmp <- sys.call() 212s + cat("\nCall: ", deparse(substitute(tmp)),"\n") 212s + 212s + cat("Data Set n p Half LOG(obj) Time\n") 212s + cat("========================================================\n") 212s + domcd(heart[, 1:2], data(heart), nrep) 212s + domcd(starsCYG, data(starsCYG), nrep) 212s + domcd(data.matrix(subset(phosphor, select = -plant)), data(phosphor), nrep) 212s + domcd(stack.x, data(stackloss), nrep) 212s + domcd(data.matrix(subset(coleman, select = -Y)), data(coleman), nrep) 212s + domcd(data.matrix(subset(salinity, select = -Y)), data(salinity), nrep) 212s + domcd(data.matrix(subset(wood, select = -y)), data(wood), nrep) 212s + domcd(data.matrix(subset(hbk, select = -Y)),data(hbk), nrep) 212s + 212s + domcd(brain, "Animals", nrep) 212s + domcd(milk, data(milk), nrep) 212s + domcd(bushfire, data(bushfire), nrep) 212s + ## VT::19.07.2010: test the univariate SDE 212s + for(i in 1:ncol(bushfire)) 212s + domcd(bushfire[i], data(bushfire), nrep) 212s + cat("========================================================\n") 212s + } 212s > 212s > dogen <- function(nrep=1, eps=0.49){ 212s + 212s + library(MASS) 212s + domcd <- function(x, nrep=1){ 212s + gc() 212s + xtime <- system.time(dorep(x, nrep))[1]/nrep 212s + cat(sprintf("%6d %3d %10.2f\n", dim(x)[1], dim(x)[2], xtime)) 212s + xtime 212s + } 212s + 212s + set.seed(1234) 212s + 212s + ## VT::15.09.2013 - this will render the output independent 212s + ## from the version of the package 212s + suppressPackageStartupMessages(library(rrcov)) 212s + 212s + ap <- c(2, 5, 10, 20, 30) 212s + an <- c(100, 500, 1000, 10000, 50000) 212s + 212s + tottime <- 0 212s + cat(" n p Time\n") 212s + cat("=====================\n") 212s + for(i in 1:length(an)) { 212s + for(j in 1:length(ap)) { 212s + n <- an[i] 212s + p <- ap[j] 212s + if(5*p <= n){ 212s + xx <- gendata(n, p, eps) 212s + X <- xx$X 212s + tottime <- tottime + domcd(X, nrep) 212s + } 212s + } 212s + } 212s + 212s + cat("=====================\n") 212s + cat("Total time: ", tottime*nrep, "\n") 212s + } 212s > 212s > docheck <- function(n, p, eps){ 212s + xx <- gendata(n,p,eps) 212s + mcd <- CovSde(xx$X) 212s + check(mcd, xx$xind) 212s + } 212s > 212s > check <- function(mcd, xind){ 212s + ## check if mcd is robust w.r.t xind, i.e. check how many of xind 212s + ## did not get zero weight 212s + mymatch <- xind %in% which(mcd@wt == 0) 212s + length(xind) - length(which(mymatch)) 212s + } 212s > 212s > dorep <- function(x, nrep=1){ 212s + 212s + for(i in 1:nrep) 212s + CovSde(x) 212s + } 212s > 212s > #### gendata() #### 212s > # Generates a location contaminated multivariate 212s > # normal sample of n observations in p dimensions 212s > # (1-eps)*Np(0,Ip) + eps*Np(m,Ip) 212s > # where 212s > # m = (b,b,...,b) 212s > # Defaults: eps=0 and b=10 212s > # 212s > gendata <- function(n,p,eps=0,b=10){ 212s + 212s + if(missing(n) || missing(p)) 212s + stop("Please specify (n,p)") 212s + if(eps < 0 || eps >= 0.5) 212s + stop(message="eps must be in [0,0.5)") 212s + X <- mvrnorm(n,rep(0,p),diag(1,nrow=p,ncol=p)) 212s + nbad <- as.integer(eps * n) 212s + if(nbad > 0){ 212s + Xbad <- mvrnorm(nbad,rep(b,p),diag(1,nrow=p,ncol=p)) 212s + xind <- sample(n,nbad) 212s + X[xind,] <- Xbad 212s + } 212s + list(X=X, xind=xind) 212s + } 212s > 212s > pad.right <- function(z, pads) 212s + { 212s + ### Pads spaces to right of text 212s + padding <- paste(rep(" ", pads), collapse = "") 212s + paste(z, padding, sep = "") 212s + } 212s > 212s > whatis<-function(x){ 212s + if(is.data.frame(x)) 212s + cat("Type: data.frame\n") 212s + else if(is.matrix(x)) 212s + cat("Type: matrix\n") 212s + else if(is.vector(x)) 212s + cat("Type: vector\n") 212s + else 212s + cat("Type: don't know\n") 212s + } 212s > 212s > ## VT::15.09.2013 - this will render the output independent 212s > ## from the version of the package 212s > suppressPackageStartupMessages(library(rrcov)) 212s > 212s > dodata() 212s 212s Call: dodata() 212s Data Set n p Half LOG(obj) Time 212s ======================================================== 212s heart 12 2 212s Outliers: 5 212s [1] 2 6 8 10 12 212s ------------- 212s 212s Call: 212s CovSde(x = x) 212s -> Method: Stahel-Donoho estimator 212s 212s Robust Estimate of Location: 212s height weight 212s 39.8 35.7 212s 212s Robust Estimate of Covariance: 212s height weight 212s height 38.2 77.1 212s weight 77.1 188.1 212s -------------------------------------------------------- 212s starsCYG 47 2 212s Outliers: 7 212s [1] 7 9 11 14 20 30 34 212s ------------- 212s 212s Call: 212s CovSde(x = x) 212s -> Method: Stahel-Donoho estimator 212s 212s Robust Estimate of Location: 212s log.Te log.light 212s 4.42 4.96 212s 212s Robust Estimate of Covariance: 212s log.Te log.light 212s log.Te 0.0163 0.0522 212s log.light 0.0522 0.3243 212s -------------------------------------------------------- 212s phosphor 18 2 212s Outliers: 2 212s [1] 1 6 212s ------------- 212s 212s Call: 212s CovSde(x = x) 212s -> Method: Stahel-Donoho estimator 212s 212s Robust Estimate of Location: 212s inorg organic 212s 13.3 39.7 212s 212s Robust Estimate of Covariance: 212s inorg organic 212s inorg 133 134 212s organic 134 204 212s -------------------------------------------------------- 212s stackloss 21 3 212s Outliers: 6 212s [1] 1 2 3 15 17 21 212s ------------- 212s 212s Call: 212s CovSde(x = x) 212s -> Method: Stahel-Donoho estimator 212s 212s Robust Estimate of Location: 212s Air.Flow Water.Temp Acid.Conc. 212s 57.8 20.7 86.4 212s 212s Robust Estimate of Covariance: 212s Air.Flow Water.Temp Acid.Conc. 212s Air.Flow 39.7 15.6 25.0 212s Water.Temp 15.6 13.0 11.9 212s Acid.Conc. 25.0 11.9 40.3 212s -------------------------------------------------------- 212s coleman 20 5 212s Outliers: 8 212s [1] 1 2 6 10 11 12 15 18 212s ------------- 212s 212s Call: 212s CovSde(x = x) 212s -> Method: Stahel-Donoho estimator 212s 212s Robust Estimate of Location: 212s salaryP fatherWc sstatus teacherSc motherLev 212s 2.78 58.64 9.09 25.37 6.69 212s 212s Robust Estimate of Covariance: 212s salaryP fatherWc sstatus teacherSc motherLev 212s salaryP 0.2556 -1.0144 0.6599 0.2673 0.0339 212s fatherWc -1.0144 1615.9192 382.7846 -4.8287 36.0227 212s sstatus 0.6599 382.7846 108.1781 -0.7904 9.1027 212s teacherSc 0.2673 -4.8287 -0.7904 0.9346 -0.0239 212s motherLev 0.0339 36.0227 9.1027 -0.0239 0.9155 212s -------------------------------------------------------- 212s salinity 28 3 212s Outliers: 9 212s [1] 3 4 5 9 11 16 19 23 24 212s ------------- 212s 212s Call: 212s CovSde(x = x) 212s -> Method: Stahel-Donoho estimator 212s 212s Robust Estimate of Location: 212s X1 X2 X3 212s 10.84 3.35 22.48 212s 212s Robust Estimate of Covariance: 212s X1 X2 X3 212s X1 10.75 -1.62 -2.05 212s X2 -1.62 4.21 -1.43 212s X3 -2.05 -1.43 2.63 212s -------------------------------------------------------- 212s wood 20 5 212s Outliers: 11 212s [1] 4 6 7 8 9 10 12 13 16 19 20 212s ------------- 212s 212s Call: 212s CovSde(x = x) 212s -> Method: Stahel-Donoho estimator 212s 212s Robust Estimate of Location: 212s x1 x2 x3 x4 x5 212s 0.573 0.119 0.517 0.549 0.904 212s 212s Robust Estimate of Covariance: 212s x1 x2 x3 x4 x5 212s x1 0.025185 0.004279 -0.001262 -0.000382 -0.001907 212s x2 0.004279 0.001011 0.000197 -0.000117 0.000247 212s x3 -0.001262 0.000197 0.003042 0.002034 0.001773 212s x4 -0.000382 -0.000117 0.002034 0.007943 0.001137 212s x5 -0.001907 0.000247 0.001773 0.001137 0.005392 212s -------------------------------------------------------- 212s hbk 75 3 212s Outliers: 15 212s [1] 1 2 3 4 5 6 7 8 9 10 11 12 13 14 53 212s ------------- 212s 212s Call: 212s CovSde(x = x) 212s -> Method: Stahel-Donoho estimator 212s 212s Robust Estimate of Location: 212s X1 X2 X3 212s 1.59 1.79 1.67 212s 212s Robust Estimate of Covariance: 212s X1 X2 X3 212s X1 1.6354 0.0793 0.2284 212s X2 0.0793 1.6461 0.3186 212s X3 0.2284 0.3186 1.5673 212s -------------------------------------------------------- 212s Animals 28 2 212s Outliers: 13 212s [1] 2 6 7 8 9 12 13 14 15 16 24 25 28 212s ------------- 212s 212s Call: 212s CovSde(x = x) 212s -> Method: Stahel-Donoho estimator 212s 212s Robust Estimate of Location: 212s body brain 212s 18.7 64.9 212s 212s Robust Estimate of Covariance: 212s body brain 212s body 4702 7973 212s brain 7973 28571 212s -------------------------------------------------------- 213s milk 86 8 213s Outliers: 21 213s [1] 1 2 3 6 11 12 13 14 15 16 17 18 20 27 41 44 47 70 74 75 77 213s ------------- 213s 213s Call: 213s CovSde(x = x) 213s -> Method: Stahel-Donoho estimator 213s 213s Robust Estimate of Location: 213s X1 X2 X3 X4 X5 X6 X7 X8 213s 1.03 35.90 33.04 26.11 25.10 25.02 123.06 14.37 213s 213s Robust Estimate of Covariance: 213s X1 X2 X3 X4 X5 X6 X7 213s X1 4.73e-07 6.57e-05 1.79e-04 1.71e-04 1.62e-04 1.42e-04 6.85e-04 213s X2 6.57e-05 1.57e+00 1.36e-01 9.28e-02 4.18e-02 1.30e-01 1.58e+00 213s X3 1.79e-04 1.36e-01 1.12e+00 8.20e-01 8.27e-01 8.00e-01 6.66e-01 213s X4 1.71e-04 9.28e-02 8.20e-01 6.57e-01 6.41e-01 6.18e-01 5.47e-01 213s X5 1.62e-04 4.18e-02 8.27e-01 6.41e-01 6.93e-01 6.44e-01 5.71e-01 213s X6 1.42e-04 1.30e-01 8.00e-01 6.18e-01 6.44e-01 6.44e-01 5.55e-01 213s X7 6.85e-04 1.58e+00 6.66e-01 5.47e-01 5.71e-01 5.55e-01 4.17e+00 213s X8 1.40e-05 2.33e-01 1.74e-01 1.06e-01 9.44e-02 9.86e-02 3.54e-01 213s X8 213s X1 1.40e-05 213s X2 2.33e-01 213s X3 1.74e-01 213s X4 1.06e-01 213s X5 9.44e-02 213s X6 9.86e-02 213s X7 3.54e-01 213s X8 1.57e-01 213s -------------------------------------------------------- 213s bushfire 38 5 213s Outliers: 23 213s [1] 1 5 6 7 8 9 10 11 12 13 15 16 28 29 30 31 32 33 34 35 36 37 38 213s ------------- 213s 213s Call: 213s CovSde(x = x) 213s -> Method: Stahel-Donoho estimator 213s 213s Robust Estimate of Location: 213s V1 V2 V3 V4 V5 213s 105 148 287 223 283 213s 213s Robust Estimate of Covariance: 213s V1 V2 V3 V4 V5 213s V1 1964 1712 -10230 -2504 -2066 213s V2 1712 1526 -8732 -2145 -1763 213s V3 -10230 -8732 56327 13803 11472 213s V4 -2504 -2145 13803 3509 2894 213s V5 -2066 -1763 11472 2894 2404 213s -------------------------------------------------------- 213s bushfire 38 1 213s Outliers: 2 213s [1] 13 30 213s ------------- 213s 213s Call: 213s CovSde(x = x) 213s -> Method: Stahel-Donoho estimator 213s 213s Robust Estimate of Location: 213s V1 213s 98.5 213s 213s Robust Estimate of Covariance: 213s V1 213s V1 431 213s -------------------------------------------------------- 213s bushfire 38 1 213s Outliers: 6 213s [1] 33 34 35 36 37 38 213s ------------- 213s 213s Call: 213s CovSde(x = x) 213s -> Method: Stahel-Donoho estimator 213s 213s Robust Estimate of Location: 213s V2 213s 141 213s 213s Robust Estimate of Covariance: 213s V2 213s V2 528 213s -------------------------------------------------------- 213s bushfire 38 1 213s Outliers: 0 213s ------------- 213s 213s Call: 213s CovSde(x = x) 213s -> Method: Stahel-Donoho estimator 213s 213s Robust Estimate of Location: 213s V3 213s 238 213s 213s Robust Estimate of Covariance: 213s V3 213s V3 37148 213s -------------------------------------------------------- 213s bushfire 38 1 213s Outliers: 9 213s [1] 8 9 32 33 34 35 36 37 38 213s ------------- 213s 213s Call: 213s CovSde(x = x) 213s -> Method: Stahel-Donoho estimator 213s 213s Robust Estimate of Location: 213s V4 213s 210 213s 213s Robust Estimate of Covariance: 213s V4 213s V4 2543 213s -------------------------------------------------------- 213s bushfire 38 1 213s Outliers: 9 213s [1] 8 9 32 33 34 35 36 37 38 213s ------------- 213s 213s Call: 213s CovSde(x = x) 213s -> Method: Stahel-Donoho estimator 213s 213s Robust Estimate of Location: 213s V5 213s 273 213s 213s Robust Estimate of Covariance: 213s V5 213s V5 1575 213s -------------------------------------------------------- 213s ======================================================== 213s > ##doexact() 213s > 213s BEGIN TEST tsest.R 213s 213s R version 4.3.3 (2024-02-29) -- "Angel Food Cake" 213s Copyright (C) 2024 The R Foundation for Statistical Computing 213s Platform: aarch64-unknown-linux-gnu (64-bit) 213s 213s R is free software and comes with ABSOLUTELY NO WARRANTY. 213s You are welcome to redistribute it under certain conditions. 213s Type 'license()' or 'licence()' for distribution details. 213s 213s R is a collaborative project with many contributors. 213s Type 'contributors()' for more information and 213s 'citation()' on how to cite R or R packages in publications. 213s 213s Type 'demo()' for some demos, 'help()' for on-line help, or 213s 'help.start()' for an HTML browser interface to help. 213s Type 'q()' to quit R. 213s 213s > ## VT::15.09.2013 - this will render the output independent 213s > ## from the version of the package 213s > suppressPackageStartupMessages(library(rrcov)) 213s > 213s > library(MASS) 213s > 213s > dodata <- function(nrep = 1, time = FALSE, full = TRUE, method) { 213s + doest <- function(x, xname, nrep = 1, method=c("sfast", "surreal", "bisquare", "rocke", "suser", "MM", "sdet")) { 213s + 213s + method <- match.arg(method) 213s + 213s + lname <- 20 213s + n <- dim(x)[1] 213s + p <- dim(x)[2] 213s + 213s + mm <- if(method == "MM") CovMMest(x) else CovSest(x, method=method) 213s + 213s + crit <- log(mm@crit) 213s + 213s + xres <- sprintf("%3d %3d %12.6f\n", dim(x)[1], dim(x)[2], crit) 213s + lpad <- lname-nchar(xname) 213s + cat(pad.right(xname,lpad), xres) 213s + 213s + dist <- getDistance(mm) 213s + quantiel <- qchisq(0.975, p) 213s + ibad <- which(dist >= quantiel) 213s + names(ibad) <- NULL 213s + nbad <- length(ibad) 213s + cat("Outliers: ",nbad,"\n") 213s + if(nbad > 0) 213s + print(ibad) 213s + cat("-------------\n") 213s + show(mm) 213s + cat("--------------------------------------------------------\n") 213s + } 213s + 213s + options(digits = 5) 213s + set.seed(101) # <<-- sub-sampling algorithm now based on R's RNG and seed 213s + 213s + data(heart) 213s + data(starsCYG) 213s + data(phosphor) 213s + data(stackloss) 213s + data(coleman) 213s + data(salinity) 213s + data(wood) 213s + data(hbk) 213s + 213s + data(Animals, package = "MASS") 213s + brain <- Animals[c(1:24, 26:25, 27:28),] 213s + data(milk) 213s + data(bushfire) 213s + ### 213s + data(rice) 213s + data(hemophilia) 213s + data(fish) 213s + 213s + tmp <- sys.call() 213s + cat("\nCall: ", deparse(substitute(tmp)),"\n") 213s + 213s + cat("Data Set n p LOG(det) Time\n") 213s + cat("===================================================\n") 213s + doest(heart[, 1:2], data(heart), nrep, method=method) 213s + doest(starsCYG, data(starsCYG), nrep, method=method) 213s + doest(data.matrix(subset(phosphor, select = -plant)), data(phosphor), nrep, method=method) 213s + doest(stack.x, data(stackloss), nrep, method=method) 213s + doest(data.matrix(subset(coleman, select = -Y)), data(coleman), nrep, method=method) 213s + doest(data.matrix(subset(salinity, select = -Y)), data(salinity), nrep, method=method) 213s + doest(data.matrix(subset(wood, select = -y)), data(wood), nrep, method=method) 213s + doest(data.matrix(subset(hbk, select = -Y)), data(hbk), nrep, method=method) 213s + 213s + 213s + doest(brain, "Animals", nrep, method=method) 213s + doest(milk, data(milk), nrep, method=method) 213s + doest(bushfire, data(bushfire), nrep, method=method) 213s + 213s + doest(data.matrix(subset(rice, select = -Overall_evaluation)), data(rice), nrep, method=method) 213s + doest(data.matrix(subset(hemophilia, select = -gr)), data(hemophilia), nrep, method=method) 213s + doest(data.matrix(subset(fish, select = -Species)), data(fish), nrep, method=method) 213s + 213s + ## from package 'datasets' 213s + doest(airquality[,1:4], data(airquality), nrep, method=method) 213s + doest(attitude, data(attitude), nrep, method=method) 213s + doest(attenu, data(attenu), nrep, method=method) 213s + doest(USJudgeRatings, data(USJudgeRatings), nrep, method=method) 213s + doest(USArrests, data(USArrests), nrep, method=method) 213s + doest(longley, data(longley), nrep, method=method) 213s + doest(Loblolly, data(Loblolly), nrep, method=method) 213s + doest(quakes[,1:4], data(quakes), nrep, method=method) 213s + 213s + cat("===================================================\n") 213s + } 213s > 213s > # generate contaminated data using the function gendata with different 213s > # number of outliers and check if the M-estimate breaks - i.e. the 213s > # largest eigenvalue is larger than e.g. 5. 213s > # For n=50 and p=10 and d=5 the M-estimate can break for number of 213s > # outliers grater than 20. 213s > dogen <- function(){ 213s + eig <- vector("numeric",26) 213s + for(i in 0:25) { 213s + gg <- gendata(eps=i) 213s + mm <- CovSRocke(gg$x, t0=gg$tgood, S0=gg$sgood) 213s + eig[i+1] <- ev <- getEvals(mm)[1] 213s + cat(i, ev, "\n") 213s + 213s + ## stopifnot(ev < 5 || i > 20) 213s + } 213s + plot(0:25, eig, type="l", xlab="Number of outliers", ylab="Largest Eigenvalue") 213s + } 213s > 213s > # 213s > # generate data 50x10 as multivariate normal N(0,I) and add 213s > # eps % outliers by adding d=5.0 to each component. 213s > # - if eps <0 and eps <=0.5, the number of outliers is eps*n 213s > # - if eps >= 1, it is the number of outliers 213s > # - use the center and cov of the good data as good start 213s > # - use the center and the cov of all data as a bad start 213s > # If using a good start, the M-estimate must iterate to 213s > # the good solution: the largest eigenvalue is less then e.g. 5 213s > # 213s > gendata <- function(n=50, p=10, eps=0, d=5.0){ 213s + 213s + if(eps < 0 || eps > 0.5 && eps < 1.0 || eps > 0.5*n) 213s + stop("eps is out of range") 213s + 213s + library(MASS) 213s + 213s + x <- mvrnorm(n, rep(0,p), diag(p)) 213s + bad <- vector("numeric") 213s + nbad = if(eps < 1) eps*n else eps 213s + if(nbad > 0){ 213s + bad <- sample(n, nbad) 213s + x[bad,] <- x[bad,] + d 213s + } 213s + cov1 <- cov.wt(x) 213s + cov2 <- if(nbad <= 0) cov1 else cov.wt(x[-bad,]) 213s + 213s + list(x=x, bad=sort(bad), tgood=cov2$center, sgood=cov2$cov, tbad=cov1$center, sbad=cov1$cov) 213s + } 213s > 213s > pad.right <- function(z, pads) 213s + { 213s + ## Pads spaces to right of text 213s + padding <- paste(rep(" ", pads), collapse = "") 213s + paste(z, padding, sep = "") 213s + } 213s > 213s > 213s > ## -- now do it: 213s > dodata(method="sfast") 213s 213s Call: dodata(method = "sfast") 213s Data Set n p LOG(det) Time 213s =================================================== 213s heart 12 2 2.017701 213s Outliers: 3 213s [1] 2 6 12 213s ------------- 213s 213s Call: 213s CovSest(x = x, method = method) 213s -> Method: S-estimates: S-FAST 213s 213s Robust Estimate of Location: 213s [1] 36.1 29.5 213s 213s Robust Estimate of Covariance: 213s height weight 213s height 129 210 213s weight 210 365 213s -------------------------------------------------------- 213s starsCYG 47 2 -1.450032 213s Outliers: 7 213s [1] 7 9 11 14 20 30 34 213s ------------- 213s 213s Call: 213s CovSest(x = x, method = method) 213s -> Method: S-estimates: S-FAST 213s 213s Robust Estimate of Location: 213s [1] 4.42 4.97 213s 213s Robust Estimate of Covariance: 213s log.Te log.light 213s log.Te 0.0176 0.0617 213s log.light 0.0617 0.3880 213s -------------------------------------------------------- 213s phosphor 18 2 2.320721 213s Outliers: 2 213s [1] 1 6 213s ------------- 213s 213s Call: 213s CovSest(x = x, method = method) 213s -> Method: S-estimates: S-FAST 213s 213s Robust Estimate of Location: 213s [1] 14.1 38.8 213s 213s Robust Estimate of Covariance: 213s inorg organic 213s inorg 174 190 213s organic 190 268 213s -------------------------------------------------------- 213s stackloss 21 3 1.470031 213s Outliers: 3 213s [1] 1 2 3 213s ------------- 213s 213s Call: 213s CovSest(x = x, method = method) 213s -> Method: S-estimates: S-FAST 213s 213s Robust Estimate of Location: 213s [1] 57.5 20.5 86.0 213s 213s Robust Estimate of Covariance: 213s Air.Flow Water.Temp Acid.Conc. 213s Air.Flow 38.94 11.66 22.89 213s Water.Temp 11.66 9.96 7.81 213s Acid.Conc. 22.89 7.81 40.48 213s -------------------------------------------------------- 213s coleman 20 5 0.491419 213s Outliers: 2 213s [1] 6 10 213s ------------- 213s 213s Call: 213s CovSest(x = x, method = method) 213s -> Method: S-estimates: S-FAST 213s 213s Robust Estimate of Location: 213s [1] 2.77 45.58 4.13 25.13 6.39 213s 213s Robust Estimate of Covariance: 213s salaryP fatherWc sstatus teacherSc motherLev 213s salaryP 0.2209 1.9568 1.4389 0.2638 0.0674 213s fatherWc 1.9568 940.7409 307.8297 8.3290 21.9143 213s sstatus 1.4389 307.8297 134.0540 4.1808 7.4799 213s teacherSc 0.2638 8.3290 4.1808 0.7604 0.2917 213s motherLev 0.0674 21.9143 7.4799 0.2917 0.5817 213s -------------------------------------------------------- 213s salinity 28 3 0.734619 213s Outliers: 4 213s [1] 5 16 23 24 213s ------------- 213s 213s Call: 213s CovSest(x = x, method = method) 213s -> Method: S-estimates: S-FAST 213s 213s Robust Estimate of Location: 213s [1] 10.31 3.07 22.60 213s 213s Robust Estimate of Covariance: 213s X1 X2 X3 213s X1 13.200 0.784 -3.611 213s X2 0.784 4.441 -1.658 213s X3 -3.611 -1.658 2.877 213s -------------------------------------------------------- 213s wood 20 5 -3.202636 213s Outliers: 2 213s [1] 7 9 213s ------------- 213s 213s Call: 213s CovSest(x = x, method = method) 213s -> Method: S-estimates: S-FAST 213s 213s Robust Estimate of Location: 213s [1] 0.551 0.135 0.496 0.511 0.916 213s 213s Robust Estimate of Covariance: 213s x1 x2 x3 x4 x5 213s x1 0.011361 -0.000791 0.005473 0.004204 -0.004747 213s x2 -0.000791 0.000701 -0.000534 -0.001452 0.000864 213s x3 0.005473 -0.000534 0.004905 0.002960 -0.001914 213s x4 0.004204 -0.001452 0.002960 0.005154 -0.002187 213s x5 -0.004747 0.000864 -0.001914 -0.002187 0.003214 213s -------------------------------------------------------- 213s hbk 75 3 0.283145 213s Outliers: 14 213s [1] 1 2 3 4 5 6 7 8 9 10 11 12 13 14 213s ------------- 213s 213s Call: 213s CovSest(x = x, method = method) 213s -> Method: S-estimates: S-FAST 213s 213s Robust Estimate of Location: 213s [1] 1.53 1.83 1.66 213s 213s Robust Estimate of Covariance: 213s X1 X2 X3 213s X1 1.8091 0.0479 0.2446 213s X2 0.0479 1.8190 0.2513 213s X3 0.2446 0.2513 1.7288 213s -------------------------------------------------------- 213s Animals 28 2 4.685129 213s Outliers: 10 213s [1] 2 6 7 9 12 14 15 16 24 25 213s ------------- 213s 213s Call: 213s CovSest(x = x, method = method) 213s -> Method: S-estimates: S-FAST 213s 213s Robust Estimate of Location: 213s [1] 30.8 84.2 213s 213s Robust Estimate of Covariance: 213s body brain 213s body 14806 28767 213s brain 28767 65195 213s -------------------------------------------------------- 213s milk 86 8 -1.437863 213s Outliers: 15 213s [1] 1 2 3 12 13 14 15 16 17 41 44 47 70 74 75 213s ------------- 213s 213s Call: 213s CovSest(x = x, method = method) 213s -> Method: S-estimates: S-FAST 213s 213s Robust Estimate of Location: 213s [1] 1.03 35.81 32.97 26.04 25.02 24.94 122.81 14.36 213s 213s Robust Estimate of Covariance: 213s X1 X2 X3 X4 X5 X6 X7 213s X1 8.30e-07 2.53e-04 4.43e-04 4.02e-04 3.92e-04 3.96e-04 1.44e-03 213s X2 2.53e-04 2.24e+00 4.77e-01 3.63e-01 2.91e-01 3.94e-01 2.44e+00 213s X3 4.43e-04 4.77e-01 1.58e+00 1.20e+00 1.18e+00 1.19e+00 1.65e+00 213s X4 4.02e-04 3.63e-01 1.20e+00 9.74e-01 9.37e-01 9.39e-01 1.39e+00 213s X5 3.92e-04 2.91e-01 1.18e+00 9.37e-01 9.78e-01 9.44e-01 1.37e+00 213s X6 3.96e-04 3.94e-01 1.19e+00 9.39e-01 9.44e-01 9.82e-01 1.41e+00 213s X7 1.44e-03 2.44e+00 1.65e+00 1.39e+00 1.37e+00 1.41e+00 6.96e+00 213s X8 7.45e-05 3.33e-01 2.82e-01 2.01e-01 1.80e-01 1.91e-01 6.38e-01 213s X8 213s X1 7.45e-05 213s X2 3.33e-01 213s X3 2.82e-01 213s X4 2.01e-01 213s X5 1.80e-01 213s X6 1.91e-01 213s X7 6.38e-01 213s X8 2.01e-01 213s -------------------------------------------------------- 213s bushfire 38 5 2.443148 213s Outliers: 13 213s [1] 7 8 9 10 11 31 32 33 34 35 36 37 38 213s ------------- 213s 213s Call: 213s CovSest(x = x, method = method) 213s -> Method: S-estimates: S-FAST 213s 213s Robust Estimate of Location: 213s [1] 108 149 266 216 278 213s 213s Robust Estimate of Covariance: 213s V1 V2 V3 V4 V5 213s V1 911 688 -3961 -856 -707 213s V2 688 587 -2493 -492 -420 213s V3 -3961 -2493 24146 5765 4627 213s V4 -856 -492 5765 1477 1164 213s V5 -707 -420 4627 1164 925 213s -------------------------------------------------------- 213s rice 105 5 -0.724874 213s Outliers: 7 213s [1] 9 40 42 49 57 58 71 213s ------------- 213s 213s Call: 213s CovSest(x = x, method = method) 213s -> Method: S-estimates: S-FAST 213s 213s Robust Estimate of Location: 213s [1] -0.2472 0.1211 -0.1207 0.0715 0.0640 213s 213s Robust Estimate of Covariance: 213s Favor Appearance Taste Stickiness Toughness 213s Favor 0.423 0.345 0.427 0.405 -0.202 213s Appearance 0.345 0.592 0.570 0.549 -0.316 213s Taste 0.427 0.570 0.739 0.706 -0.393 213s Stickiness 0.405 0.549 0.706 0.876 -0.497 213s Toughness -0.202 -0.316 -0.393 -0.497 0.467 213s -------------------------------------------------------- 213s hemophilia 75 2 -1.868949 213s Outliers: 2 213s [1] 11 36 213s ------------- 213s 213s Call: 213s CovSest(x = x, method = method) 213s -> Method: S-estimates: S-FAST 213s 213s Robust Estimate of Location: 213s [1] -0.2126 -0.0357 213s 213s Robust Estimate of Covariance: 213s AHFactivity AHFantigen 213s AHFactivity 0.0317 0.0112 213s AHFantigen 0.0112 0.0218 213s -------------------------------------------------------- 213s fish 159 6 1.285876 213s Outliers: 21 213s [1] 61 62 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 213s [20] 103 142 213s ------------- 213s 213s Call: 213s CovSest(x = x, method = method) 213s -> Method: S-estimates: S-FAST 213s 213s Robust Estimate of Location: 213s [1] 358.3 24.7 26.9 29.7 30.0 14.7 213s 213s Robust Estimate of Covariance: 213s Weight Length1 Length2 Length3 Height Width 213s Weight 1.33e+05 3.09e+03 3.34e+03 3.78e+03 1.72e+03 2.24e+02 213s Length1 3.09e+03 7.92e+01 8.54e+01 9.55e+01 4.04e+01 7.43e+00 213s Length2 3.34e+03 8.54e+01 9.22e+01 1.03e+02 4.49e+01 8.07e+00 213s Length3 3.78e+03 9.55e+01 1.03e+02 1.18e+02 5.92e+01 7.65e+00 213s Height 1.72e+03 4.04e+01 4.49e+01 5.92e+01 7.12e+01 8.51e-01 213s Width 2.24e+02 7.43e+00 8.07e+00 7.65e+00 8.51e-01 3.57e+00 213s -------------------------------------------------------- 213s airquality 153 4 2.684374 213s Outliers: 7 213s [1] 7 14 23 30 34 77 107 213s ------------- 213s 213s Call: 213s CovSest(x = x, method = method) 213s -> Method: S-estimates: S-FAST 213s 213s Robust Estimate of Location: 213s [1] 39.34 192.12 9.67 78.71 213s 213s Robust Estimate of Covariance: 213s Ozone Solar.R Wind Temp 213s Ozone 973.104 894.011 -61.856 243.560 213s Solar.R 894.011 9677.269 0.388 179.429 213s Wind -61.856 0.388 11.287 -14.310 213s Temp 243.560 179.429 -14.310 96.714 213s -------------------------------------------------------- 213s attitude 30 7 2.091968 213s Outliers: 4 213s [1] 14 16 18 24 213s ------------- 213s 213s Call: 213s CovSest(x = x, method = method) 213s -> Method: S-estimates: S-FAST 213s 213s Robust Estimate of Location: 213s [1] 65.7 66.8 51.9 56.1 66.4 76.7 43.0 213s 213s Robust Estimate of Covariance: 213s rating complaints privileges learning raises critical advance 213s rating 170.59 136.40 77.41 125.46 99.72 8.01 49.52 213s complaints 136.40 170.94 94.62 136.73 120.76 23.52 78.52 213s privileges 77.41 94.62 150.49 112.77 87.92 6.43 72.33 213s learning 125.46 136.73 112.77 173.77 131.46 25.81 81.38 213s raises 99.72 120.76 87.92 131.46 136.76 29.50 91.70 213s critical 8.01 23.52 6.43 25.81 29.50 84.75 30.59 213s advance 49.52 78.52 72.33 81.38 91.70 30.59 116.28 213s -------------------------------------------------------- 213s attenu 182 5 1.148032 213s Outliers: 31 213s [1] 2 5 6 7 8 9 10 11 15 16 19 20 21 22 23 24 25 27 28 213s [20] 29 30 31 32 64 65 80 94 95 96 97 100 213s ------------- 213s 213s Call: 213s CovSest(x = x, method = method) 213s -> Method: S-estimates: S-FAST 213s 213s Robust Estimate of Location: 213s [1] 16.432 5.849 60.297 27.144 0.134 213s 213s Robust Estimate of Covariance: 213s event mag station dist accel 213s event 54.9236 -3.0733 181.0954 -49.4194 -0.0628 213s mag -3.0733 0.6530 -8.4388 6.7388 0.0161 213s station 181.0954 -8.4388 1689.7161 -114.6319 0.7285 213s dist -49.4194 6.7388 -114.6319 597.3606 -1.7988 213s accel -0.0628 0.0161 0.7285 -1.7988 0.0152 213s -------------------------------------------------------- 214s USJudgeRatings 43 12 -1.683847 214s Outliers: 7 214s [1] 5 7 12 13 14 23 31 214s ------------- 214s 214s Call: 214s CovSest(x = x, method = method) 214s -> Method: S-estimates: S-FAST 214s 214s Robust Estimate of Location: 214s [1] 7.43 8.16 7.75 7.89 7.68 7.76 7.67 7.67 7.51 7.58 8.19 7.86 214s 214s Robust Estimate of Covariance: 214s CONT INTG DMNR DILG CFMG DECI PREP FAMI 214s CONT 0.8710 -0.3019 -0.4682 -0.1893 -0.0569 -0.0992 -0.1771 -0.1975 214s INTG -0.3019 0.6401 0.8598 0.6955 0.5732 0.5439 0.7091 0.7084 214s DMNR -0.4682 0.8598 1.2412 0.9107 0.7668 0.7305 0.9292 0.9158 214s DILG -0.1893 0.6955 0.9107 0.8554 0.7408 0.7036 0.8865 0.8791 214s CFMG -0.0569 0.5732 0.7668 0.7408 0.6994 0.6545 0.7788 0.7721 214s DECI -0.0992 0.5439 0.7305 0.7036 0.6545 0.6342 0.7492 0.7511 214s PREP -0.1771 0.7091 0.9292 0.8865 0.7788 0.7492 0.9541 0.9556 214s FAMI -0.1975 0.7084 0.9158 0.8791 0.7721 0.7511 0.9556 0.9785 214s ORAL -0.2444 0.7453 0.9939 0.8917 0.7842 0.7551 0.9554 0.9680 214s WRIT -0.2344 0.7319 0.9649 0.8853 0.7781 0.7511 0.9498 0.9668 214s PHYS -0.1983 0.4676 0.6263 0.5629 0.5073 0.5039 0.5990 0.6140 214s RTEN -0.3152 0.8000 1.0798 0.9234 0.7952 0.7663 0.9637 0.9693 214s ORAL WRIT PHYS RTEN 214s CONT -0.2444 -0.2344 -0.1983 -0.3152 214s INTG 0.7453 0.7319 0.4676 0.8000 214s DMNR 0.9939 0.9649 0.6263 1.0798 214s DILG 0.8917 0.8853 0.5629 0.9234 214s CFMG 0.7842 0.7781 0.5073 0.7952 214s DECI 0.7551 0.7511 0.5039 0.7663 214s PREP 0.9554 0.9498 0.5990 0.9637 214s FAMI 0.9680 0.9668 0.6140 0.9693 214s ORAL 0.9853 0.9744 0.6280 1.0032 214s WRIT 0.9744 0.9711 0.6184 0.9870 214s PHYS 0.6280 0.6184 0.4716 0.6520 214s RTEN 1.0032 0.9870 0.6520 1.0622 214s -------------------------------------------------------- 214s USArrests 50 4 2.411726 214s Outliers: 4 214s [1] 2 28 33 39 214s ------------- 214s 214s Call: 214s CovSest(x = x, method = method) 214s -> Method: S-estimates: S-FAST 214s 214s Robust Estimate of Location: 214s [1] 7.05 150.66 64.66 19.37 214s 214s Robust Estimate of Covariance: 214s Murder Assault UrbanPop Rape 214s Murder 23.8 380.8 19.2 29.7 214s Assault 380.8 8436.2 605.6 645.3 214s UrbanPop 19.2 605.6 246.5 78.8 214s Rape 29.7 645.3 78.8 77.3 214s -------------------------------------------------------- 214s longley 16 7 1.038316 214s Outliers: 5 214s [1] 1 2 3 4 5 214s ------------- 214s 214s Call: 214s CovSest(x = x, method = method) 214s -> Method: S-estimates: S-FAST 214s 214s Robust Estimate of Location: 214s [1] 107.6 440.8 339.7 292.5 121.0 1957.1 67.2 214s 214s Robust Estimate of Covariance: 214s GNP.deflator GNP Unemployed Armed.Forces Population 214s GNP.deflator 100.6 954.7 1147.1 -507.6 74.2 214s GNP 954.7 9430.9 10115.8 -4616.5 730.1 214s Unemployed 1147.1 10115.8 19838.3 -6376.9 850.6 214s Armed.Forces -507.6 -4616.5 -6376.9 3240.2 -351.3 214s Population 74.2 730.1 850.6 -351.3 57.5 214s Year 46.4 450.8 539.5 -233.0 35.3 214s Employed 30.8 310.5 274.0 -160.8 23.3 214s Year Employed 214s GNP.deflator 46.4 30.8 214s GNP 450.8 310.5 214s Unemployed 539.5 274.0 214s Armed.Forces -233.0 -160.8 214s Population 35.3 23.3 214s Year 21.9 14.6 214s Employed 14.6 11.2 214s -------------------------------------------------------- 214s Loblolly 84 3 1.481317 214s Outliers: 14 214s [1] 6 12 18 24 30 36 42 48 54 60 66 72 78 84 214s ------------- 214s 214s Call: 214s CovSest(x = x, method = method) 214s -> Method: S-estimates: S-FAST 214s 214s Robust Estimate of Location: 214s [1] 24.22 9.65 7.50 214s 214s Robust Estimate of Covariance: 214s height age Seed 214s height 525.08 179.21 14.27 214s age 179.21 61.85 2.94 214s Seed 14.27 2.94 25.86 214s -------------------------------------------------------- 214s quakes 1000 4 1.576855 214s Outliers: 223 214s [1] 7 12 15 17 22 25 27 28 32 37 40 41 45 48 53 214s [16] 63 64 73 78 87 91 92 94 99 108 110 117 118 119 120 214s [31] 121 122 126 133 136 141 143 145 148 152 154 155 157 159 160 214s [46] 163 170 192 205 222 226 230 239 243 250 251 252 254 258 263 214s [61] 267 268 271 283 292 300 301 305 311 312 318 320 321 325 328 214s [76] 330 334 352 357 360 365 381 382 384 389 400 402 408 413 416 214s [91] 417 419 426 429 437 441 443 453 456 467 474 477 490 492 496 214s [106] 504 507 508 509 517 524 527 528 531 532 534 536 538 539 541 214s [121] 542 543 544 545 546 547 552 553 560 571 581 583 587 593 594 214s [136] 596 597 605 612 613 618 620 625 629 638 642 647 649 653 655 214s [151] 656 672 675 681 686 699 701 702 712 714 716 721 725 726 735 214s [166] 744 754 756 759 765 766 769 779 781 782 785 787 797 804 813 214s [181] 825 827 837 840 844 852 853 857 860 865 866 869 870 872 873 214s [196] 883 884 887 888 890 891 893 908 909 912 915 916 921 927 930 214s [211] 952 962 963 969 974 980 982 986 987 988 992 997 1000 214s ------------- 214s 214s Call: 214s CovSest(x = x, method = method) 214s -> Method: S-estimates: S-FAST 214s 214s Robust Estimate of Location: 214s [1] -21.54 182.35 369.21 4.54 214s 214s Robust Estimate of Covariance: 214s lat long depth mag 214s lat 2.81e+01 6.19e+00 3.27e+02 -4.56e-01 214s long 6.19e+00 7.54e+00 -5.95e+02 9.56e-02 214s depth 3.27e+02 -5.95e+02 8.36e+04 -2.70e+01 214s mag -4.56e-01 9.56e-02 -2.70e+01 2.35e-01 214s -------------------------------------------------------- 214s =================================================== 214s > dodata(method="sdet") 214s 214s Call: dodata(method = "sdet") 214s Data Set n p LOG(det) Time 214s =================================================== 214s heart 12 2 2.017701 214s Outliers: 3 214s [1] 2 6 12 214s ------------- 214s 214s Call: 214s CovSest(x = x, method = method) 214s -> Method: S-estimates: DET-S 214s 214s Robust Estimate of Location: 214s [1] 36.1 29.5 214s 214s Robust Estimate of Covariance: 214s height weight 214s height 129 210 214s weight 210 365 214s -------------------------------------------------------- 214s starsCYG 47 2 -1.450032 214s Outliers: 7 214s [1] 7 9 11 14 20 30 34 214s ------------- 214s 214s Call: 214s CovSest(x = x, method = method) 214s -> Method: S-estimates: DET-S 214s 214s Robust Estimate of Location: 214s [1] 4.42 4.97 214s 214s Robust Estimate of Covariance: 214s log.Te log.light 214s log.Te 0.0176 0.0617 214s log.light 0.0617 0.3880 214s -------------------------------------------------------- 214s phosphor 18 2 2.320721 214s Outliers: 2 214s [1] 1 6 214s ------------- 214s 214s Call: 214s CovSest(x = x, method = method) 214s -> Method: S-estimates: DET-S 214s 214s Robust Estimate of Location: 214s [1] 14.1 38.8 214s 214s Robust Estimate of Covariance: 214s inorg organic 214s inorg 174 190 214s organic 190 268 214s -------------------------------------------------------- 214s stackloss 21 3 1.470031 214s Outliers: 3 214s [1] 1 2 3 214s ------------- 214s 214s Call: 214s CovSest(x = x, method = method) 214s -> Method: S-estimates: DET-S 214s 214s Robust Estimate of Location: 214s [1] 57.5 20.5 86.0 214s 214s Robust Estimate of Covariance: 214s Air.Flow Water.Temp Acid.Conc. 214s Air.Flow 38.94 11.66 22.89 214s Water.Temp 11.66 9.96 7.81 214s Acid.Conc. 22.89 7.81 40.48 214s -------------------------------------------------------- 214s coleman 20 5 0.491419 214s Outliers: 2 214s [1] 6 10 214s ------------- 214s 214s Call: 214s CovSest(x = x, method = method) 214s -> Method: S-estimates: DET-S 214s 214s Robust Estimate of Location: 214s [1] 2.77 45.58 4.13 25.13 6.39 214s 214s Robust Estimate of Covariance: 214s salaryP fatherWc sstatus teacherSc motherLev 214s salaryP 0.2209 1.9568 1.4389 0.2638 0.0674 214s fatherWc 1.9568 940.7409 307.8297 8.3290 21.9143 214s sstatus 1.4389 307.8297 134.0540 4.1808 7.4799 214s teacherSc 0.2638 8.3290 4.1808 0.7604 0.2917 214s motherLev 0.0674 21.9143 7.4799 0.2917 0.5817 214s -------------------------------------------------------- 214s salinity 28 3 0.734619 214s Outliers: 4 214s [1] 5 16 23 24 214s ------------- 214s 214s Call: 214s CovSest(x = x, method = method) 214s -> Method: S-estimates: DET-S 214s 214s Robust Estimate of Location: 214s [1] 10.31 3.07 22.60 214s 214s Robust Estimate of Covariance: 214s X1 X2 X3 214s X1 13.200 0.784 -3.611 214s X2 0.784 4.441 -1.658 214s X3 -3.611 -1.658 2.877 214s -------------------------------------------------------- 215s wood 20 5 -3.220754 215s Outliers: 4 215s [1] 4 6 8 19 215s ------------- 215s 215s Call: 215s CovSest(x = x, method = method) 215s -> Method: S-estimates: DET-S 215s 215s Robust Estimate of Location: 215s [1] 0.580 0.123 0.530 0.538 0.890 215s 215s Robust Estimate of Covariance: 215s x1 x2 x3 x4 x5 215s x1 8.16e-03 1.39e-03 1.97e-03 -2.82e-04 -7.61e-04 215s x2 1.39e-03 4.00e-04 8.14e-04 -8.51e-05 -5.07e-06 215s x3 1.97e-03 8.14e-04 4.74e-03 -9.59e-04 2.06e-05 215s x4 -2.82e-04 -8.51e-05 -9.59e-04 3.09e-03 1.87e-03 215s x5 -7.61e-04 -5.07e-06 2.06e-05 1.87e-03 2.28e-03 215s -------------------------------------------------------- 215s hbk 75 3 0.283145 215s Outliers: 14 215s [1] 1 2 3 4 5 6 7 8 9 10 11 12 13 14 215s ------------- 215s 215s Call: 215s CovSest(x = x, method = method) 215s -> Method: S-estimates: DET-S 215s 215s Robust Estimate of Location: 215s [1] 1.53 1.83 1.66 215s 215s Robust Estimate of Covariance: 215s X1 X2 X3 215s X1 1.8091 0.0479 0.2446 215s X2 0.0479 1.8190 0.2513 215s X3 0.2446 0.2513 1.7288 215s -------------------------------------------------------- 215s Animals 28 2 4.685129 215s Outliers: 10 215s [1] 2 6 7 9 12 14 15 16 24 25 215s ------------- 215s 215s Call: 215s CovSest(x = x, method = method) 215s -> Method: S-estimates: DET-S 215s 215s Robust Estimate of Location: 215s [1] 30.8 84.2 215s 215s Robust Estimate of Covariance: 215s body brain 215s body 14806 28767 215s brain 28767 65194 215s -------------------------------------------------------- 216s milk 86 8 -1.437863 216s Outliers: 15 216s [1] 1 2 3 12 13 14 15 16 17 41 44 47 70 74 75 216s ------------- 216s 216s Call: 216s CovSest(x = x, method = method) 216s -> Method: S-estimates: DET-S 216s 216s Robust Estimate of Location: 216s [1] 1.03 35.81 32.97 26.04 25.02 24.94 122.81 14.36 216s 216s Robust Estimate of Covariance: 216s X1 X2 X3 X4 X5 X6 X7 216s X1 8.30e-07 2.53e-04 4.43e-04 4.02e-04 3.92e-04 3.96e-04 1.44e-03 216s X2 2.53e-04 2.24e+00 4.77e-01 3.63e-01 2.91e-01 3.94e-01 2.44e+00 216s X3 4.43e-04 4.77e-01 1.58e+00 1.20e+00 1.18e+00 1.19e+00 1.65e+00 216s X4 4.02e-04 3.63e-01 1.20e+00 9.74e-01 9.37e-01 9.39e-01 1.39e+00 216s X5 3.92e-04 2.91e-01 1.18e+00 9.37e-01 9.78e-01 9.44e-01 1.37e+00 216s X6 3.96e-04 3.94e-01 1.19e+00 9.39e-01 9.44e-01 9.82e-01 1.41e+00 216s X7 1.44e-03 2.44e+00 1.65e+00 1.39e+00 1.37e+00 1.41e+00 6.96e+00 216s X8 7.45e-05 3.33e-01 2.82e-01 2.01e-01 1.80e-01 1.91e-01 6.38e-01 216s X8 216s X1 7.45e-05 216s X2 3.33e-01 216s X3 2.82e-01 216s X4 2.01e-01 216s X5 1.80e-01 216s X6 1.91e-01 216s X7 6.38e-01 216s X8 2.01e-01 216s -------------------------------------------------------- 216s bushfire 38 5 2.443148 216s Outliers: 13 216s [1] 7 8 9 10 11 31 32 33 34 35 36 37 38 216s ------------- 216s 216s Call: 216s CovSest(x = x, method = method) 216s -> Method: S-estimates: DET-S 216s 216s Robust Estimate of Location: 216s [1] 108 149 266 216 278 216s 216s Robust Estimate of Covariance: 216s V1 V2 V3 V4 V5 216s V1 911 688 -3961 -856 -707 216s V2 688 587 -2493 -492 -420 216s V3 -3961 -2493 24146 5765 4627 216s V4 -856 -492 5765 1477 1164 216s V5 -707 -420 4627 1164 925 216s -------------------------------------------------------- 216s rice 105 5 -0.724874 216s Outliers: 7 216s [1] 9 40 42 49 57 58 71 216s ------------- 216s 216s Call: 216s CovSest(x = x, method = method) 216s -> Method: S-estimates: DET-S 216s 216s Robust Estimate of Location: 216s [1] -0.2472 0.1211 -0.1207 0.0715 0.0640 216s 216s Robust Estimate of Covariance: 216s Favor Appearance Taste Stickiness Toughness 216s Favor 0.423 0.345 0.427 0.405 -0.202 216s Appearance 0.345 0.592 0.570 0.549 -0.316 216s Taste 0.427 0.570 0.739 0.706 -0.393 216s Stickiness 0.405 0.549 0.706 0.876 -0.497 216s Toughness -0.202 -0.316 -0.393 -0.497 0.467 216s -------------------------------------------------------- 216s hemophilia 75 2 -1.868949 216s Outliers: 2 216s [1] 11 36 216s ------------- 216s 216s Call: 216s CovSest(x = x, method = method) 216s -> Method: S-estimates: DET-S 216s 216s Robust Estimate of Location: 216s [1] -0.2126 -0.0357 216s 216s Robust Estimate of Covariance: 216s AHFactivity AHFantigen 216s AHFactivity 0.0317 0.0112 216s AHFantigen 0.0112 0.0218 216s -------------------------------------------------------- 217s fish 159 6 1.267294 217s Outliers: 33 217s [1] 61 72 73 74 75 76 77 78 79 80 81 82 83 85 86 87 88 89 90 217s [20] 91 92 93 94 95 96 97 98 99 100 101 102 103 142 217s ------------- 217s 217s Call: 217s CovSest(x = x, method = method) 217s -> Method: S-estimates: DET-S 217s 217s Robust Estimate of Location: 217s [1] 381.2 25.6 27.8 30.8 31.0 14.9 217s 217s Robust Estimate of Covariance: 217s Weight Length1 Length2 Length3 Height Width 217s Weight 148372.04 3260.48 3508.71 3976.93 1507.43 127.94 217s Length1 3260.48 77.00 82.52 92.18 27.56 3.29 217s Length2 3508.71 82.52 88.57 99.20 30.83 3.43 217s Length3 3976.93 92.18 99.20 113.97 45.50 2.21 217s Height 1507.43 27.56 30.83 45.50 70.54 -4.95 217s Width 127.94 3.29 3.43 2.21 -4.95 2.28 217s -------------------------------------------------------- 217s airquality 153 4 2.684374 217s Outliers: 7 217s [1] 7 14 23 30 34 77 107 217s ------------- 217s 217s Call: 217s CovSest(x = x, method = method) 217s -> Method: S-estimates: DET-S 217s 217s Robust Estimate of Location: 217s [1] 39.34 192.12 9.67 78.71 217s 217s Robust Estimate of Covariance: 217s Ozone Solar.R Wind Temp 217s Ozone 973.104 894.011 -61.856 243.560 217s Solar.R 894.011 9677.269 0.388 179.429 217s Wind -61.856 0.388 11.287 -14.310 217s Temp 243.560 179.429 -14.310 96.714 217s -------------------------------------------------------- 217s attitude 30 7 2.091968 217s Outliers: 4 217s [1] 14 16 18 24 217s ------------- 217s 217s Call: 217s CovSest(x = x, method = method) 217s -> Method: S-estimates: DET-S 217s 217s Robust Estimate of Location: 217s [1] 65.7 66.8 51.9 56.1 66.4 76.7 43.0 217s 217s Robust Estimate of Covariance: 217s rating complaints privileges learning raises critical advance 217s rating 170.59 136.40 77.41 125.46 99.72 8.01 49.52 217s complaints 136.40 170.94 94.62 136.73 120.76 23.52 78.52 217s privileges 77.41 94.62 150.49 112.77 87.92 6.43 72.33 217s learning 125.46 136.73 112.77 173.77 131.46 25.81 81.38 217s raises 99.72 120.76 87.92 131.46 136.76 29.50 91.70 217s critical 8.01 23.52 6.43 25.81 29.50 84.75 30.59 217s advance 49.52 78.52 72.33 81.38 91.70 30.59 116.28 217s -------------------------------------------------------- 217s attenu 182 5 1.148032 217s Outliers: 31 217s [1] 2 5 6 7 8 9 10 11 15 16 19 20 21 22 23 24 25 27 28 217s [20] 29 30 31 32 64 65 80 94 95 96 97 100 217s ------------- 217s 217s Call: 217s CovSest(x = x, method = method) 217s -> Method: S-estimates: DET-S 217s 217s Robust Estimate of Location: 217s [1] 16.432 5.849 60.297 27.144 0.134 217s 217s Robust Estimate of Covariance: 217s event mag station dist accel 217s event 54.9236 -3.0733 181.0954 -49.4195 -0.0628 217s mag -3.0733 0.6530 -8.4388 6.7388 0.0161 217s station 181.0954 -8.4388 1689.7161 -114.6321 0.7285 217s dist -49.4195 6.7388 -114.6321 597.3609 -1.7988 217s accel -0.0628 0.0161 0.7285 -1.7988 0.0152 217s -------------------------------------------------------- 218s USJudgeRatings 43 12 -1.683847 218s Outliers: 7 218s [1] 5 7 12 13 14 23 31 218s ------------- 218s 218s Call: 218s CovSest(x = x, method = method) 218s -> Method: S-estimates: DET-S 218s 218s Robust Estimate of Location: 218s [1] 7.43 8.16 7.75 7.89 7.68 7.76 7.67 7.67 7.51 7.58 8.19 7.86 218s 218s Robust Estimate of Covariance: 218s CONT INTG DMNR DILG CFMG DECI PREP FAMI 218s CONT 0.8715 -0.3020 -0.4683 -0.1894 -0.0569 -0.0993 -0.1772 -0.1976 218s INTG -0.3020 0.6403 0.8600 0.6956 0.5733 0.5440 0.7093 0.7086 218s DMNR -0.4683 0.8600 1.2416 0.9109 0.7669 0.7307 0.9295 0.9161 218s DILG -0.1894 0.6956 0.9109 0.8555 0.7410 0.7037 0.8867 0.8793 218s CFMG -0.0569 0.5733 0.7669 0.7410 0.6995 0.6546 0.7789 0.7723 218s DECI -0.0993 0.5440 0.7307 0.7037 0.6546 0.6343 0.7493 0.7513 218s PREP -0.1772 0.7093 0.9295 0.8867 0.7789 0.7493 0.9543 0.9559 218s FAMI -0.1976 0.7086 0.9161 0.8793 0.7723 0.7513 0.9559 0.9788 218s ORAL -0.2445 0.7456 0.9942 0.8919 0.7844 0.7553 0.9557 0.9683 218s WRIT -0.2345 0.7321 0.9652 0.8856 0.7783 0.7513 0.9501 0.9671 218s PHYS -0.1986 0.4676 0.6264 0.5628 0.5072 0.5038 0.5990 0.6140 218s RTEN -0.3154 0.8002 1.0801 0.9236 0.7954 0.7665 0.9639 0.9695 218s ORAL WRIT PHYS RTEN 218s CONT -0.2445 -0.2345 -0.1986 -0.3154 218s INTG 0.7456 0.7321 0.4676 0.8002 218s DMNR 0.9942 0.9652 0.6264 1.0801 218s DILG 0.8919 0.8856 0.5628 0.9236 218s CFMG 0.7844 0.7783 0.5072 0.7954 218s DECI 0.7553 0.7513 0.5038 0.7665 218s PREP 0.9557 0.9501 0.5990 0.9639 218s FAMI 0.9683 0.9671 0.6140 0.9695 218s ORAL 0.9856 0.9748 0.6281 1.0035 218s WRIT 0.9748 0.9714 0.6184 0.9873 218s PHYS 0.6281 0.6184 0.4713 0.6520 218s RTEN 1.0035 0.9873 0.6520 1.0624 218s -------------------------------------------------------- 218s USArrests 50 4 2.411726 218s Outliers: 4 218s [1] 2 28 33 39 218s ------------- 218s 218s Call: 218s CovSest(x = x, method = method) 218s -> Method: S-estimates: DET-S 218s 218s Robust Estimate of Location: 218s [1] 7.05 150.66 64.66 19.37 218s 218s Robust Estimate of Covariance: 218s Murder Assault UrbanPop Rape 218s Murder 23.8 380.8 19.2 29.7 218s Assault 380.8 8436.2 605.6 645.3 218s UrbanPop 19.2 605.6 246.5 78.8 218s Rape 29.7 645.3 78.8 77.3 218s -------------------------------------------------------- 218s longley 16 7 1.143113 218s Outliers: 4 218s [1] 1 2 3 4 218s ------------- 218s 218s Call: 218s CovSest(x = x, method = method) 218s -> Method: S-estimates: DET-S 218s 218s Robust Estimate of Location: 218s [1] 107 435 334 293 120 1957 67 218s 218s Robust Estimate of Covariance: 218s GNP.deflator GNP Unemployed Armed.Forces Population 218s GNP.deflator 89.2 850.1 1007.4 -404.4 66.2 218s GNP 850.1 8384.4 9020.8 -3692.0 650.5 218s Unemployed 1007.4 9020.8 16585.4 -4990.7 752.5 218s Armed.Forces -404.4 -3692.0 -4990.7 2474.2 -280.9 218s Population 66.2 650.5 752.5 -280.9 51.2 218s Year 41.9 407.6 481.9 -186.4 31.9 218s Employed 27.9 279.7 255.6 -128.8 21.1 218s Year Employed 218s GNP.deflator 41.9 27.9 218s GNP 407.6 279.7 218s Unemployed 481.9 255.6 218s Armed.Forces -186.4 -128.8 218s Population 31.9 21.1 218s Year 20.2 13.4 218s Employed 13.4 10.1 218s -------------------------------------------------------- 219s Loblolly 84 3 1.481317 219s Outliers: 14 219s [1] 6 12 18 24 30 36 42 48 54 60 66 72 78 84 219s ------------- 219s 219s Call: 219s CovSest(x = x, method = method) 219s -> Method: S-estimates: DET-S 219s 219s Robust Estimate of Location: 219s [1] 24.22 9.65 7.50 219s 219s Robust Estimate of Covariance: 219s height age Seed 219s height 525.08 179.21 14.27 219s age 179.21 61.85 2.94 219s Seed 14.27 2.94 25.86 219s -------------------------------------------------------- 219s quakes 1000 4 1.576855 219s Outliers: 223 219s [1] 7 12 15 17 22 25 27 28 32 37 40 41 45 48 53 219s [16] 63 64 73 78 87 91 92 94 99 108 110 117 118 119 120 219s [31] 121 122 126 133 136 141 143 145 148 152 154 155 157 159 160 219s [46] 163 170 192 205 222 226 230 239 243 250 251 252 254 258 263 219s [61] 267 268 271 283 292 300 301 305 311 312 318 320 321 325 328 219s [76] 330 334 352 357 360 365 381 382 384 389 400 402 408 413 416 219s [91] 417 419 426 429 437 441 443 453 456 467 474 477 490 492 496 219s [106] 504 507 508 509 517 524 527 528 531 532 534 536 538 539 541 219s [121] 542 543 544 545 546 547 552 553 560 571 581 583 587 593 594 219s [136] 596 597 605 612 613 618 620 625 629 638 642 647 649 653 655 219s [151] 656 672 675 681 686 699 701 702 712 714 716 721 725 726 735 219s [166] 744 754 756 759 765 766 769 779 781 782 785 787 797 804 813 219s [181] 825 827 837 840 844 852 853 857 860 865 866 869 870 872 873 219s [196] 883 884 887 888 890 891 893 908 909 912 915 916 921 927 930 219s [211] 952 962 963 969 974 980 982 986 987 988 992 997 1000 219s ------------- 219s 219s Call: 219s CovSest(x = x, method = method) 219s -> Method: S-estimates: DET-S 219s 219s Robust Estimate of Location: 219s [1] -21.54 182.35 369.21 4.54 219s 219s Robust Estimate of Covariance: 219s lat long depth mag 219s lat 2.81e+01 6.19e+00 3.27e+02 -4.56e-01 219s long 6.19e+00 7.54e+00 -5.95e+02 9.56e-02 219s depth 3.27e+02 -5.95e+02 8.36e+04 -2.70e+01 219s mag -4.56e-01 9.56e-02 -2.70e+01 2.35e-01 219s -------------------------------------------------------- 219s =================================================== 219s > ##dodata(method="suser") 219s > ##dodata(method="surreal") 219s > dodata(method="bisquare") 219s 219s Call: dodata(method = "bisquare") 219s Data Set n p LOG(det) Time 219s =================================================== 219s heart 12 2 7.721793 219s Outliers: 3 219s [1] 2 6 12 219s ------------- 219s 219s Call: 219s CovSest(x = x, method = method) 219s -> Method: S-estimates: bisquare 219s 219s Robust Estimate of Location: 219s height weight 219s 36.1 29.4 219s 219s Robust Estimate of Covariance: 219s height weight 219s height 109 177 219s weight 177 307 219s -------------------------------------------------------- 219s starsCYG 47 2 -5.942108 219s Outliers: 7 219s [1] 7 9 11 14 20 30 34 219s ------------- 219s 219s Call: 219s CovSest(x = x, method = method) 219s -> Method: S-estimates: bisquare 219s 219s Robust Estimate of Location: 219s log.Te log.light 219s 4.42 4.97 219s 219s Robust Estimate of Covariance: 219s log.Te log.light 219s log.Te 0.0164 0.0574 219s log.light 0.0574 0.3613 219s -------------------------------------------------------- 219s phosphor 18 2 9.269096 219s Outliers: 2 219s [1] 1 6 219s ------------- 219s 219s Call: 219s CovSest(x = x, method = method) 219s -> Method: S-estimates: bisquare 219s 219s Robust Estimate of Location: 219s inorg organic 219s 14.1 38.7 219s 219s Robust Estimate of Covariance: 219s inorg organic 219s inorg 173 189 219s organic 189 268 219s -------------------------------------------------------- 219s stackloss 21 3 8.411100 219s Outliers: 3 219s [1] 1 2 3 219s ------------- 219s 219s Call: 219s CovSest(x = x, method = method) 219s -> Method: S-estimates: bisquare 219s 219s Robust Estimate of Location: 219s Air.Flow Water.Temp Acid.Conc. 219s 57.5 20.5 86.0 219s 219s Robust Estimate of Covariance: 219s Air.Flow Water.Temp Acid.Conc. 219s Air.Flow 33.82 10.17 20.02 219s Water.Temp 10.17 8.70 6.84 219s Acid.Conc. 20.02 6.84 35.51 219s -------------------------------------------------------- 219s coleman 20 5 4.722046 219s Outliers: 2 219s [1] 6 10 219s ------------- 219s 219s Call: 219s CovSest(x = x, method = method) 219s -> Method: S-estimates: bisquare 219s 219s Robust Estimate of Location: 219s salaryP fatherWc sstatus teacherSc motherLev 219s 2.77 45.59 4.14 25.13 6.39 219s 219s Robust Estimate of Covariance: 219s salaryP fatherWc sstatus teacherSc motherLev 219s salaryP 0.2135 1.8732 1.3883 0.2547 0.0648 219s fatherWc 1.8732 905.6704 296.1916 7.9820 21.0848 219s sstatus 1.3883 296.1916 128.9536 4.0196 7.1917 219s teacherSc 0.2547 7.9820 4.0196 0.7321 0.2799 219s motherLev 0.0648 21.0848 7.1917 0.2799 0.5592 219s -------------------------------------------------------- 219s salinity 28 3 4.169963 219s Outliers: 4 219s [1] 5 16 23 24 219s ------------- 219s 219s Call: 219s CovSest(x = x, method = method) 219s -> Method: S-estimates: bisquare 219s 219s Robust Estimate of Location: 219s X1 X2 X3 219s 10.30 3.07 22.59 219s 219s Robust Estimate of Covariance: 219s X1 X2 X3 219s X1 12.234 0.748 -3.369 219s X2 0.748 4.115 -1.524 219s X3 -3.369 -1.524 2.655 219s -------------------------------------------------------- 219s wood 20 5 -33.862485 219s Outliers: 5 219s [1] 4 6 8 11 19 219s ------------- 219s 219s Call: 219s CovSest(x = x, method = method) 219s -> Method: S-estimates: bisquare 219s 219s Robust Estimate of Location: 219s x1 x2 x3 x4 x5 219s 0.580 0.123 0.530 0.538 0.890 219s 219s Robust Estimate of Covariance: 219s x1 x2 x3 x4 x5 219s x1 5.88e-03 9.96e-04 1.43e-03 -1.96e-04 -5.46e-04 219s x2 9.96e-04 2.86e-04 5.89e-04 -5.78e-05 -2.24e-06 219s x3 1.43e-03 5.89e-04 3.42e-03 -6.95e-04 1.43e-05 219s x4 -1.96e-04 -5.78e-05 -6.95e-04 2.23e-03 1.35e-03 219s x5 -5.46e-04 -2.24e-06 1.43e-05 1.35e-03 1.65e-03 219s -------------------------------------------------------- 219s hbk 75 3 1.472421 219s Outliers: 14 219s [1] 1 2 3 4 5 6 7 8 9 10 11 12 13 14 219s ------------- 219s 219s Call: 219s CovSest(x = x, method = method) 219s -> Method: S-estimates: bisquare 219s 219s Robust Estimate of Location: 219s X1 X2 X3 219s 1.53 1.83 1.66 219s 219s Robust Estimate of Covariance: 219s X1 X2 X3 219s X1 1.6775 0.0447 0.2268 219s X2 0.0447 1.6865 0.2325 219s X3 0.2268 0.2325 1.6032 219s -------------------------------------------------------- 219s Animals 28 2 18.528307 219s Outliers: 11 219s [1] 2 6 7 9 12 14 15 16 24 25 28 219s ------------- 219s 219s Call: 219s CovSest(x = x, method = method) 219s -> Method: S-estimates: bisquare 219s 219s Robust Estimate of Location: 219s body brain 219s 30.7 84.1 219s 219s Robust Estimate of Covariance: 219s body brain 219s body 13278 25795 219s brain 25795 58499 219s -------------------------------------------------------- 219s milk 86 8 -24.816943 219s Outliers: 19 219s [1] 1 2 3 11 12 13 14 15 16 17 20 27 41 44 47 70 74 75 77 219s ------------- 219s 219s Call: 219s CovSest(x = x, method = method) 219s -> Method: S-estimates: bisquare 219s 219s Robust Estimate of Location: 219s X1 X2 X3 X4 X5 X6 X7 X8 219s 1.03 35.81 32.96 26.04 25.02 24.94 122.79 14.35 219s 219s Robust Estimate of Covariance: 219s X1 X2 X3 X4 X5 X6 X7 219s X1 6.80e-07 2.20e-04 3.70e-04 3.35e-04 3.27e-04 3.30e-04 1.21e-03 219s X2 2.20e-04 1.80e+00 3.96e-01 3.03e-01 2.45e-01 3.27e-01 2.00e+00 219s X3 3.70e-04 3.96e-01 1.27e+00 9.68e-01 9.49e-01 9.56e-01 1.37e+00 219s X4 3.35e-04 3.03e-01 9.68e-01 7.86e-01 7.55e-01 7.57e-01 1.15e+00 219s X5 3.27e-04 2.45e-01 9.49e-01 7.55e-01 7.88e-01 7.61e-01 1.14e+00 219s X6 3.30e-04 3.27e-01 9.56e-01 7.57e-01 7.61e-01 7.90e-01 1.17e+00 219s X7 1.21e-03 2.00e+00 1.37e+00 1.15e+00 1.14e+00 1.17e+00 5.71e+00 219s X8 6.57e-05 2.71e-01 2.30e-01 1.64e-01 1.48e-01 1.57e-01 5.27e-01 219s X8 219s X1 6.57e-05 219s X2 2.71e-01 219s X3 2.30e-01 219s X4 1.64e-01 219s X5 1.48e-01 219s X6 1.57e-01 219s X7 5.27e-01 219s X8 1.62e-01 219s -------------------------------------------------------- 219s bushfire 38 5 21.704243 219s Outliers: 13 219s [1] 7 8 9 10 11 31 32 33 34 35 36 37 38 219s ------------- 219s 219s Call: 219s CovSest(x = x, method = method) 219s -> Method: S-estimates: bisquare 219s 219s Robust Estimate of Location: 219s V1 V2 V3 V4 V5 219s 108 149 266 216 278 219s 219s Robust Estimate of Covariance: 219s V1 V2 V3 V4 V5 219s V1 528 398 -2298 -497 -410 219s V2 398 340 -1445 -285 -244 219s V3 -2298 -1445 14026 3348 2687 219s V4 -497 -285 3348 857 676 219s V5 -410 -244 2687 676 537 219s -------------------------------------------------------- 219s rice 105 5 -7.346939 219s Outliers: 8 219s [1] 9 14 40 42 49 57 58 71 219s ------------- 219s 219s Call: 219s CovSest(x = x, method = method) 219s -> Method: S-estimates: bisquare 219s 219s Robust Estimate of Location: 219s Favor Appearance Taste Stickiness Toughness 219s -0.2480 0.1203 -0.1213 0.0710 0.0644 219s 219s Robust Estimate of Covariance: 219s Favor Appearance Taste Stickiness Toughness 219s Favor 0.415 0.338 0.419 0.398 -0.198 219s Appearance 0.338 0.580 0.559 0.539 -0.310 219s Taste 0.419 0.559 0.725 0.693 -0.386 219s Stickiness 0.398 0.539 0.693 0.859 -0.487 219s Toughness -0.198 -0.310 -0.386 -0.487 0.457 219s -------------------------------------------------------- 219s hemophilia 75 2 -7.465173 219s Outliers: 2 219s [1] 11 36 219s ------------- 219s 219s Call: 219s CovSest(x = x, method = method) 219s -> Method: S-estimates: bisquare 219s 219s Robust Estimate of Location: 219s AHFactivity AHFantigen 219s -0.2128 -0.0366 219s 219s Robust Estimate of Covariance: 219s AHFactivity AHFantigen 219s AHFactivity 0.0321 0.0115 219s AHFantigen 0.0115 0.0220 219s -------------------------------------------------------- 219s fish 159 6 13.465134 219s Outliers: 35 219s [1] 38 61 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 219s [20] 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 142 219s ------------- 219s 219s Call: 219s CovSest(x = x, method = method) 219s -> Method: S-estimates: bisquare 219s 219s Robust Estimate of Location: 219s Weight Length1 Length2 Length3 Height Width 219s 381.4 25.6 27.8 30.8 31.0 14.9 219s 219s Robust Estimate of Covariance: 219s Weight Length1 Length2 Length3 Height Width 219s Weight 111094.92 2440.81 2626.59 2976.92 1129.78 95.85 219s Length1 2440.81 57.63 61.75 68.98 20.67 2.46 219s Length2 2626.59 61.75 66.28 74.24 23.13 2.57 219s Length3 2976.92 68.98 74.24 85.29 34.11 1.65 219s Height 1129.78 20.67 23.13 34.11 52.75 -3.70 219s Width 95.85 2.46 2.57 1.65 -3.70 1.71 219s -------------------------------------------------------- 219s airquality 153 4 21.282926 219s Outliers: 8 219s [1] 7 11 14 23 30 34 77 107 219s ------------- 219s 219s Call: 219s CovSest(x = x, method = method) 219s -> Method: S-estimates: bisquare 219s 219s Robust Estimate of Location: 219s Ozone Solar.R Wind Temp 219s 39.40 192.29 9.66 78.74 219s 219s Robust Estimate of Covariance: 219s Ozone Solar.R Wind Temp 219s Ozone 930.566 849.644 -59.157 232.459 219s Solar.R 849.644 9207.569 0.594 168.122 219s Wind -59.157 0.594 10.783 -13.645 219s Temp 232.459 168.122 -13.645 92.048 219s -------------------------------------------------------- 219s attitude 30 7 28.084183 219s Outliers: 6 219s [1] 6 9 14 16 18 24 219s ------------- 219s 219s Call: 219s CovSest(x = x, method = method) 219s -> Method: S-estimates: bisquare 219s 219s Robust Estimate of Location: 219s rating complaints privileges learning raises critical 219s 65.7 66.8 51.9 56.1 66.4 76.7 219s advance 219s 43.0 219s 219s Robust Estimate of Covariance: 219s rating complaints privileges learning raises critical advance 219s rating 143.88 114.95 64.97 105.69 83.95 6.96 41.78 219s complaints 114.95 143.84 79.28 115.00 101.48 19.69 66.13 219s privileges 64.97 79.28 126.38 94.70 73.87 5.37 61.07 219s learning 105.69 115.00 94.70 146.14 110.50 21.67 68.49 219s raises 83.95 101.48 73.87 110.50 115.01 24.91 77.16 219s critical 6.96 19.69 5.37 21.67 24.91 71.74 25.88 219s advance 41.78 66.13 61.07 68.49 77.16 25.88 97.71 219s -------------------------------------------------------- 219s attenu 182 5 10.109049 219s Outliers: 35 219s [1] 2 4 5 6 7 8 9 10 11 15 16 19 20 21 22 23 24 25 27 219s [20] 28 29 30 31 32 64 65 80 93 94 95 96 97 98 99 100 219s ------------- 219s 219s Call: 219s CovSest(x = x, method = method) 219s -> Method: S-estimates: bisquare 219s 219s Robust Estimate of Location: 219s event mag station dist accel 219s 16.418 5.850 60.243 27.307 0.134 219s 219s Robust Estimate of Covariance: 219s event mag station dist accel 219s event 41.9000 -2.3543 137.8110 -39.0321 -0.0447 219s mag -2.3543 0.4978 -6.4461 5.2644 0.0118 219s station 137.8110 -6.4461 1283.9675 -90.1657 0.5554 219s dist -39.0321 5.2644 -90.1657 462.3898 -1.3672 219s accel -0.0447 0.0118 0.5554 -1.3672 0.0114 219s -------------------------------------------------------- 219s USJudgeRatings 43 12 -43.367499 219s Outliers: 10 219s [1] 5 7 8 12 13 14 20 23 31 35 219s ------------- 219s 219s Call: 219s CovSest(x = x, method = method) 219s -> Method: S-estimates: bisquare 219s 219s Robust Estimate of Location: 219s CONT INTG DMNR DILG CFMG DECI PREP FAMI ORAL WRIT PHYS RTEN 219s 7.43 8.16 7.75 7.89 7.69 7.76 7.68 7.67 7.52 7.59 8.19 7.87 219s 219s Robust Estimate of Covariance: 219s CONT INTG DMNR DILG CFMG DECI PREP FAMI 219s CONT 0.6895 -0.2399 -0.3728 -0.1514 -0.0461 -0.0801 -0.1419 -0.1577 219s INTG -0.2399 0.5021 0.6746 0.5446 0.4479 0.4254 0.5564 0.5558 219s DMNR -0.3728 0.6746 0.9753 0.7128 0.5992 0.5715 0.7289 0.7181 219s DILG -0.1514 0.5446 0.7128 0.6691 0.5789 0.5501 0.6949 0.6892 219s CFMG -0.0461 0.4479 0.5992 0.5789 0.5468 0.5118 0.6100 0.6049 219s DECI -0.0801 0.4254 0.5715 0.5501 0.5118 0.4965 0.5872 0.5890 219s PREP -0.1419 0.5564 0.7289 0.6949 0.6100 0.5872 0.7497 0.7511 219s FAMI -0.1577 0.5558 0.7181 0.6892 0.6049 0.5890 0.7511 0.7696 219s ORAL -0.1950 0.5848 0.7798 0.6990 0.6143 0.5921 0.7508 0.7610 219s WRIT -0.1866 0.5747 0.7575 0.6946 0.6101 0.5895 0.7470 0.7607 219s PHYS -0.1620 0.3640 0.4878 0.4361 0.3927 0.3910 0.4655 0.4779 219s RTEN -0.2522 0.6268 0.8462 0.7220 0.6210 0.5991 0.7553 0.7599 219s ORAL WRIT PHYS RTEN 219s CONT -0.1950 -0.1866 -0.1620 -0.2522 219s INTG 0.5848 0.5747 0.3640 0.6268 219s DMNR 0.7798 0.7575 0.4878 0.8462 219s DILG 0.6990 0.6946 0.4361 0.7220 219s CFMG 0.6143 0.6101 0.3927 0.6210 219s DECI 0.5921 0.5895 0.3910 0.5991 219s PREP 0.7508 0.7470 0.4655 0.7553 219s FAMI 0.7610 0.7607 0.4779 0.7599 219s ORAL 0.7745 0.7665 0.4893 0.7866 219s WRIT 0.7665 0.7645 0.4823 0.7745 219s PHYS 0.4893 0.4823 0.3620 0.5062 219s RTEN 0.7866 0.7745 0.5062 0.8313 219s -------------------------------------------------------- 219s USArrests 50 4 19.266763 219s Outliers: 4 219s [1] 2 28 33 39 219s ------------- 219s 219s Call: 219s CovSest(x = x, method = method) 219s -> Method: S-estimates: bisquare 219s 219s Robust Estimate of Location: 219s Murder Assault UrbanPop Rape 219s 7.04 150.55 64.64 19.34 219s 219s Robust Estimate of Covariance: 219s Murder Assault UrbanPop Rape 219s Murder 23.7 378.9 19.1 29.5 219s Assault 378.9 8388.2 601.3 639.7 219s UrbanPop 19.1 601.3 245.3 77.9 219s Rape 29.5 639.7 77.9 76.3 219s -------------------------------------------------------- 219s longley 16 7 13.789499 219s Outliers: 4 219s [1] 1 2 3 4 219s ------------- 219s 219s Call: 219s CovSest(x = x, method = method) 219s -> Method: S-estimates: bisquare 219s 219s Robust Estimate of Location: 219s GNP.deflator GNP Unemployed Armed.Forces Population 219s 107 435 333 293 120 219s Year Employed 219s 1957 67 219s 219s Robust Estimate of Covariance: 219s GNP.deflator GNP Unemployed Armed.Forces Population 219s GNP.deflator 65.05 619.75 734.33 -294.02 48.27 219s GNP 619.75 6112.14 6578.12 -2684.52 474.26 219s Unemployed 734.33 6578.12 12075.90 -3627.79 548.58 219s Armed.Forces -294.02 -2684.52 -3627.79 1797.05 -204.25 219s Population 48.27 474.26 548.58 -204.25 37.36 219s Year 30.58 297.29 351.44 -135.53 23.29 219s Employed 20.36 203.96 186.62 -93.64 15.42 219s Year Employed 219s GNP.deflator 30.58 20.36 219s GNP 297.29 203.96 219s Unemployed 351.44 186.62 219s Armed.Forces -135.53 -93.64 219s Population 23.29 15.42 219s Year 14.70 9.80 219s Employed 9.80 7.36 219s -------------------------------------------------------- 219s Loblolly 84 3 8.518440 219s Outliers: 14 219s [1] 6 12 18 24 30 36 42 48 54 60 66 72 78 84 219s ------------- 219s 219s Call: 219s CovSest(x = x, method = method) 219s -> Method: S-estimates: bisquare 219s 219s Robust Estimate of Location: 219s height age Seed 219s 24.14 9.62 7.51 219s 219s Robust Estimate of Covariance: 219s height age Seed 219s height 464.64 158.43 12.83 219s age 158.43 54.62 2.67 219s Seed 12.83 2.67 22.98 219s -------------------------------------------------------- 219s quakes 1000 4 11.611413 219s Outliers: 234 219s [1] 7 12 15 17 22 25 27 28 32 37 40 41 45 48 53 219s [16] 63 64 73 78 87 91 92 94 99 108 110 117 118 119 120 219s [31] 121 122 126 133 136 141 143 145 148 152 154 155 157 159 160 219s [46] 163 166 170 174 192 205 222 226 230 239 243 250 251 252 254 219s [61] 258 263 267 268 271 283 292 297 300 301 305 311 312 318 320 219s [76] 321 325 328 330 331 334 352 357 360 365 368 376 381 382 384 219s [91] 389 399 400 402 408 413 416 417 418 419 426 429 437 441 443 219s [106] 453 456 467 474 477 490 492 496 504 507 508 509 517 524 527 219s [121] 528 531 532 534 536 538 539 541 542 543 544 545 546 547 552 219s [136] 553 558 560 570 571 581 583 587 593 594 596 597 605 612 613 219s [151] 618 620 625 629 638 642 647 649 653 655 656 672 675 681 686 219s [166] 699 701 702 712 714 716 721 725 726 735 744 753 754 756 759 219s [181] 765 766 769 779 781 782 785 787 797 804 813 825 827 837 840 219s [196] 844 852 853 857 860 865 866 869 870 872 873 883 884 887 888 219s [211] 890 891 893 908 909 912 915 916 921 927 930 952 962 963 969 219s [226] 974 980 982 986 987 988 992 997 1000 219s ------------- 219s 219s Call: 219s CovSest(x = x, method = method) 219s -> Method: S-estimates: bisquare 219s 219s Robust Estimate of Location: 219s lat long depth mag 219s -21.54 182.35 369.29 4.54 219s 219s Robust Estimate of Covariance: 219s lat long depth mag 219s lat 2.18e+01 4.82e+00 2.53e+02 -3.54e-01 219s long 4.82e+00 5.87e+00 -4.63e+02 7.45e-02 219s depth 2.53e+02 -4.63e+02 6.51e+04 -2.10e+01 219s mag -3.54e-01 7.45e-02 -2.10e+01 1.83e-01 219s -------------------------------------------------------- 219s =================================================== 219s > dodata(method="rocke") 219s 219s Call: dodata(method = "rocke") 219s Data Set n p LOG(det) Time 219s =================================================== 220s heart 12 2 7.285196 220s Outliers: 3 220s [1] 2 6 12 220s ------------- 220s 220s Call: 220s CovSest(x = x, method = method) 220s -> Method: S-estimates: Rocke type 220s 220s Robust Estimate of Location: 220s height weight 220s 34.3 26.1 220s 220s Robust Estimate of Covariance: 220s height weight 220s height 105 159 220s weight 159 256 220s -------------------------------------------------------- 220s starsCYG 47 2 -5.929361 220s Outliers: 7 220s [1] 7 9 11 14 20 30 34 220s ------------- 220s 220s Call: 220s CovSest(x = x, method = method) 220s -> Method: S-estimates: Rocke type 220s 220s Robust Estimate of Location: 220s log.Te log.light 220s 4.42 4.93 220s 220s Robust Estimate of Covariance: 220s log.Te log.light 220s log.Te 0.0193 0.0709 220s log.light 0.0709 0.3987 220s -------------------------------------------------------- 220s phosphor 18 2 8.907518 220s Outliers: 3 220s [1] 1 6 10 220s ------------- 220s 220s Call: 220s CovSest(x = x, method = method) 220s -> Method: S-estimates: Rocke type 220s 220s Robust Estimate of Location: 220s inorg organic 220s 15.8 39.4 220s 220s Robust Estimate of Covariance: 220s inorg organic 220s inorg 196 252 220s organic 252 360 220s -------------------------------------------------------- 220s stackloss 21 3 8.143313 220s Outliers: 4 220s [1] 1 2 3 21 220s ------------- 220s 220s Call: 220s CovSest(x = x, method = method) 220s -> Method: S-estimates: Rocke type 220s 220s Robust Estimate of Location: 220s Air.Flow Water.Temp Acid.Conc. 220s 56.8 20.2 86.4 220s 220s Robust Estimate of Covariance: 220s Air.Flow Water.Temp Acid.Conc. 220s Air.Flow 29.26 9.62 14.78 220s Water.Temp 9.62 8.54 6.25 220s Acid.Conc. 14.78 6.25 29.70 220s -------------------------------------------------------- 220s coleman 20 5 4.001659 220s Outliers: 5 220s [1] 2 6 9 10 13 220s ------------- 220s 220s Call: 220s CovSest(x = x, method = method) 220s -> Method: S-estimates: Rocke type 220s 220s Robust Estimate of Location: 220s salaryP fatherWc sstatus teacherSc motherLev 220s 2.81 40.27 2.11 25.01 6.27 220s 220s Robust Estimate of Covariance: 220s salaryP fatherWc sstatus teacherSc motherLev 220s salaryP 0.2850 1.1473 2.0254 0.3536 0.0737 220s fatherWc 1.1473 798.0714 278.0145 6.4590 18.6357 220s sstatus 2.0254 278.0145 128.7601 4.0666 6.3845 220s teacherSc 0.3536 6.4590 4.0666 0.8749 0.2980 220s motherLev 0.0737 18.6357 6.3845 0.2980 0.4948 220s -------------------------------------------------------- 220s salinity 28 3 3.455146 220s Outliers: 9 220s [1] 3 5 10 11 15 16 17 23 24 220s ------------- 220s 220s Call: 220s CovSest(x = x, method = method) 220s -> Method: S-estimates: Rocke type 220s 220s Robust Estimate of Location: 220s X1 X2 X3 220s 9.89 3.10 22.46 220s 220s Robust Estimate of Covariance: 220s X1 X2 X3 220s X1 12.710 1.868 -4.135 220s X2 1.868 4.710 -0.663 220s X3 -4.135 -0.663 1.907 220s -------------------------------------------------------- 220s wood 20 5 -35.020244 220s Outliers: 7 220s [1] 4 6 7 8 11 16 19 220s ------------- 220s 220s Call: 220s CovSest(x = x, method = method) 220s -> Method: S-estimates: Rocke type 220s 220s Robust Estimate of Location: 220s x1 x2 x3 x4 x5 220s 0.588 0.123 0.534 0.535 0.891 220s 220s Robust Estimate of Covariance: 220s x1 x2 x3 x4 x5 220s x1 6.60e-03 1.25e-03 2.16e-03 -3.73e-04 -1.10e-03 220s x2 1.25e-03 3.30e-04 8.91e-04 -1.23e-05 2.62e-05 220s x3 2.16e-03 8.91e-04 4.55e-03 -4.90e-04 1.93e-04 220s x4 -3.73e-04 -1.23e-05 -4.90e-04 2.01e-03 1.36e-03 220s x5 -1.10e-03 2.62e-05 1.93e-04 1.36e-03 1.95e-03 220s -------------------------------------------------------- 220s hbk 75 3 1.413303 220s Outliers: 14 220s [1] 1 2 3 4 5 6 7 8 9 10 11 12 13 14 220s ------------- 220s 220s Call: 220s CovSest(x = x, method = method) 220s -> Method: S-estimates: Rocke type 220s 220s Robust Estimate of Location: 220s X1 X2 X3 220s 1.56 1.77 1.68 220s 220s Robust Estimate of Covariance: 220s X1 X2 X3 220s X1 1.6483 0.0825 0.2133 220s X2 0.0825 1.6928 0.2334 220s X3 0.2133 0.2334 1.5334 220s -------------------------------------------------------- 220s Animals 28 2 17.787210 220s Outliers: 11 220s [1] 2 6 7 9 12 14 15 16 24 25 28 220s ------------- 220s 220s Call: 220s CovSest(x = x, method = method) 220s -> Method: S-estimates: Rocke type 220s 220s Robust Estimate of Location: 220s body brain 220s 60.6 150.2 220s 220s Robust Estimate of Covariance: 220s body brain 220s body 10670 19646 220s brain 19646 41147 220s -------------------------------------------------------- 220s milk 86 8 -25.169970 220s Outliers: 22 220s [1] 1 2 3 11 12 13 14 15 16 17 18 20 27 28 41 44 47 70 73 74 75 77 220s ------------- 220s 220s Call: 220s CovSest(x = x, method = method) 220s -> Method: S-estimates: Rocke type 220s 220s Robust Estimate of Location: 220s X1 X2 X3 X4 X5 X6 X7 X8 220s 1.03 35.87 33.14 26.19 25.17 25.11 123.16 14.41 220s 220s Robust Estimate of Covariance: 220s X1 X2 X3 X4 X5 X6 X7 220s X1 4.47e-07 1.77e-04 1.94e-04 1.79e-04 1.60e-04 1.45e-04 6.45e-04 220s X2 1.77e-04 2.36e+00 4.03e-01 3.08e-01 2.08e-01 3.45e-01 2.18e+00 220s X3 1.94e-04 4.03e-01 1.13e+00 8.31e-01 8.08e-01 7.79e-01 9.83e-01 220s X4 1.79e-04 3.08e-01 8.31e-01 6.62e-01 6.22e-01 5.95e-01 7.82e-01 220s X5 1.60e-04 2.08e-01 8.08e-01 6.22e-01 6.51e-01 5.93e-01 7.60e-01 220s X6 1.45e-04 3.45e-01 7.79e-01 5.95e-01 5.93e-01 5.88e-01 7.81e-01 220s X7 6.45e-04 2.18e+00 9.83e-01 7.82e-01 7.60e-01 7.81e-01 4.81e+00 220s X8 2.47e-05 2.57e-01 2.00e-01 1.37e-01 1.13e-01 1.28e-01 4.38e-01 220s X8 220s X1 2.47e-05 220s X2 2.57e-01 220s X3 2.00e-01 220s X4 1.37e-01 220s X5 1.13e-01 220s X6 1.28e-01 220s X7 4.38e-01 220s X8 1.61e-01 220s -------------------------------------------------------- 220s bushfire 38 5 21.641566 220s Outliers: 13 220s [1] 7 8 9 10 11 31 32 33 34 35 36 37 38 220s ------------- 220s 220s Call: 220s CovSest(x = x, method = method) 220s -> Method: S-estimates: Rocke type 220s 220s Robust Estimate of Location: 220s V1 V2 V3 V4 V5 220s 111 150 256 214 276 220s 220s Robust Estimate of Covariance: 220s V1 V2 V3 V4 V5 220s V1 554 408 -2321 -464 -393 220s V2 408 343 -1361 -244 -215 220s V3 -2321 -1361 14690 3277 2684 220s V4 -464 -244 3277 783 629 220s V5 -393 -215 2684 629 509 220s -------------------------------------------------------- 220s rice 105 5 -7.208835 220s Outliers: 8 220s [1] 9 14 40 42 49 57 58 71 220s ------------- 220s 220s Call: 220s CovSest(x = x, method = method) 220s -> Method: S-estimates: Rocke type 220s 220s Robust Estimate of Location: 220s Favor Appearance Taste Stickiness Toughness 220s -0.21721 0.20948 -0.04581 0.15355 -0.00254 220s 220s Robust Estimate of Covariance: 220s Favor Appearance Taste Stickiness Toughness 220s Favor 0.432 0.337 0.417 0.382 -0.201 220s Appearance 0.337 0.591 0.553 0.510 -0.295 220s Taste 0.417 0.553 0.735 0.683 -0.385 220s Stickiness 0.382 0.510 0.683 0.834 -0.462 220s Toughness -0.201 -0.295 -0.385 -0.462 0.408 220s -------------------------------------------------------- 220s hemophilia 75 2 -7.453807 220s Outliers: 2 220s [1] 46 53 220s ------------- 220s 220s Call: 220s CovSest(x = x, method = method) 220s -> Method: S-estimates: Rocke type 220s 220s Robust Estimate of Location: 220s AHFactivity AHFantigen 220s -0.2276 -0.0637 220s 220s Robust Estimate of Covariance: 220s AHFactivity AHFantigen 220s AHFactivity 0.0405 0.0221 220s AHFantigen 0.0221 0.0263 220s -------------------------------------------------------- 220s fish 159 6 13.110263 220s Outliers: 47 220s [1] 38 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 220s [20] 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 220s [39] 98 99 100 101 102 103 104 140 142 220s ------------- 220s 220s Call: 220s CovSest(x = x, method = method) 220s -> Method: S-estimates: Rocke type 220s 220s Robust Estimate of Location: 220s Weight Length1 Length2 Length3 Height Width 220s 452.1 27.2 29.5 32.6 30.8 15.0 220s 220s Robust Estimate of Covariance: 220s Weight Length1 Length2 Length3 Height Width 220s Weight 132559.85 2817.97 3035.69 3369.07 1231.68 112.19 220s Length1 2817.97 64.16 68.74 75.36 22.52 2.37 220s Length2 3035.69 68.74 73.77 81.12 25.57 2.47 220s Length3 3369.07 75.36 81.12 91.65 37.39 1.40 220s Height 1231.68 22.52 25.57 37.39 50.91 -3.92 220s Width 112.19 2.37 2.47 1.40 -3.92 1.87 220s -------------------------------------------------------- 220s airquality 153 4 21.181656 220s Outliers: 13 220s [1] 6 7 11 14 17 20 23 30 34 53 63 77 107 220s ------------- 220s 220s Call: 220s CovSest(x = x, method = method) 220s -> Method: S-estimates: Rocke type 220s 220s Robust Estimate of Location: 220s Ozone Solar.R Wind Temp 220s 40.21 198.33 9.76 79.35 220s 220s Robust Estimate of Covariance: 220s Ozone Solar.R Wind Temp 220s Ozone 885.7 581.1 -57.3 226.4 220s Solar.R 581.1 8870.9 26.2 -15.1 220s Wind -57.3 26.2 11.8 -13.4 220s Temp 226.4 -15.1 -13.4 89.4 220s -------------------------------------------------------- 220s attitude 30 7 27.836398 220s Outliers: 8 220s [1] 1 9 13 14 17 18 24 26 220s ------------- 220s 220s Call: 220s CovSest(x = x, method = method) 220s -> Method: S-estimates: Rocke type 220s 220s Robust Estimate of Location: 220s rating complaints privileges learning raises critical 220s 64.0 65.4 50.5 54.9 63.1 72.6 220s advance 220s 40.5 220s 220s Robust Estimate of Covariance: 220s rating complaints privileges learning raises critical advance 220s rating 180.10 153.16 42.04 128.90 90.25 18.75 39.81 220s complaints 153.16 192.38 58.32 142.48 94.29 8.13 45.33 220s privileges 42.04 58.32 113.65 82.31 69.53 23.13 61.96 220s learning 128.90 142.48 82.31 156.99 101.74 13.22 49.64 220s raises 90.25 94.29 69.53 101.74 110.85 47.84 55.76 220s critical 18.75 8.13 23.13 13.22 47.84 123.00 36.97 220s advance 39.81 45.33 61.96 49.64 55.76 36.97 53.59 220s -------------------------------------------------------- 220s attenu 182 5 9.726797 220s Outliers: 44 220s [1] 1 2 4 5 6 7 8 9 10 11 13 15 16 19 20 21 22 23 24 220s [20] 25 27 28 29 30 31 32 40 45 60 61 64 65 78 80 81 93 94 95 220s [39] 96 97 98 99 100 108 220s ------------- 220s 220s Call: 220s CovSest(x = x, method = method) 220s -> Method: S-estimates: Rocke type 220s 220s Robust Estimate of Location: 220s event mag station dist accel 220s 16.39 5.82 60.89 27.97 0.12 220s 220s Robust Estimate of Covariance: 220s event mag station dist accel 220s event 4.20e+01 -1.97e+00 1.44e+02 -3.50e+01 4.05e-02 220s mag -1.97e+00 5.05e-01 -4.78e+00 4.63e+00 4.19e-03 220s station 1.44e+02 -4.78e+00 1.47e+03 -5.74e+01 7.88e-01 220s dist -3.50e+01 4.63e+00 -5.74e+01 3.99e+02 -1.18e+00 220s accel 4.05e-02 4.19e-03 7.88e-01 -1.18e+00 7.71e-03 220s -------------------------------------------------------- 220s USJudgeRatings 43 12 -46.356873 220s Outliers: 15 220s [1] 1 5 7 8 12 13 14 17 20 21 23 30 31 35 42 220s ------------- 220s 220s Call: 220s CovSest(x = x, method = method) 220s -> Method: S-estimates: Rocke type 220s 220s Robust Estimate of Location: 220s CONT INTG DMNR DILG CFMG DECI PREP FAMI ORAL WRIT PHYS RTEN 220s 7.56 8.12 7.70 7.91 7.74 7.82 7.66 7.66 7.50 7.58 8.22 7.86 220s 220s Robust Estimate of Covariance: 220s CONT INTG DMNR DILG CFMG DECI PREP 220s CONT 0.63426 -0.20121 -0.31858 -0.09578 0.00521 -0.00436 -0.07140 220s INTG -0.20121 0.28326 0.37540 0.27103 0.20362 0.19838 0.25706 220s DMNR -0.31858 0.37540 0.58265 0.33615 0.25649 0.24804 0.31696 220s DILG -0.09578 0.27103 0.33615 0.32588 0.27022 0.26302 0.32236 220s CFMG 0.00521 0.20362 0.25649 0.27022 0.25929 0.24217 0.27784 220s DECI -0.00436 0.19838 0.24804 0.26302 0.24217 0.23830 0.27284 220s PREP -0.07140 0.25706 0.31696 0.32236 0.27784 0.27284 0.35071 220s FAMI -0.07118 0.25858 0.29511 0.32582 0.27863 0.27657 0.35941 220s ORAL -0.11149 0.27055 0.33919 0.31768 0.27339 0.26739 0.34200 220s WRIT -0.10050 0.26857 0.32570 0.32327 0.27860 0.27201 0.34399 220s PHYS -0.09693 0.15339 0.18416 0.17089 0.13837 0.14895 0.18472 220s RTEN -0.15643 0.31793 0.40884 0.33863 0.27073 0.26854 0.34049 220s FAMI ORAL WRIT PHYS RTEN 220s CONT -0.07118 -0.11149 -0.10050 -0.09693 -0.15643 220s INTG 0.25858 0.27055 0.26857 0.15339 0.31793 220s DMNR 0.29511 0.33919 0.32570 0.18416 0.40884 220s DILG 0.32582 0.31768 0.32327 0.17089 0.33863 220s CFMG 0.27863 0.27339 0.27860 0.13837 0.27073 220s DECI 0.27657 0.26739 0.27201 0.14895 0.26854 220s PREP 0.35941 0.34200 0.34399 0.18472 0.34049 220s FAMI 0.38378 0.35617 0.36094 0.19998 0.35048 220s ORAL 0.35617 0.34918 0.34808 0.19759 0.35217 220s WRIT 0.36094 0.34808 0.35242 0.19666 0.35090 220s PHYS 0.19998 0.19759 0.19666 0.14770 0.20304 220s RTEN 0.35048 0.35217 0.35090 0.20304 0.39451 220s -------------------------------------------------------- 220s USArrests 50 4 19.206310 220s Outliers: 4 220s [1] 2 28 33 39 220s ------------- 220s 220s Call: 220s CovSest(x = x, method = method) 220s -> Method: S-estimates: Rocke type 220s 220s Robust Estimate of Location: 220s Murder Assault UrbanPop Rape 220s 7.55 160.94 65.10 19.97 220s 220s Robust Estimate of Covariance: 220s Murder Assault UrbanPop Rape 220s Murder 25.6 409.5 23.4 32.1 220s Assault 409.5 8530.9 676.9 669.4 220s UrbanPop 23.4 676.9 269.9 76.6 220s Rape 32.1 669.4 76.6 76.6 220s -------------------------------------------------------- 220s longley 16 7 13.387132 220s Outliers: 4 220s [1] 1 2 3 4 220s ------------- 220s 220s Call: 220s CovSest(x = x, method = method) 220s -> Method: S-estimates: Rocke type 220s 220s Robust Estimate of Location: 220s GNP.deflator GNP Unemployed Armed.Forces Population 220s 105.5 422.4 318.3 299.7 119.5 220s Year Employed 220s 1956.1 66.5 220s 220s Robust Estimate of Covariance: 220s GNP.deflator GNP Unemployed Armed.Forces Population 220s GNP.deflator 59.97 582.66 694.99 -237.75 46.12 220s GNP 582.66 5849.82 6383.68 -2207.26 461.15 220s Unemployed 694.99 6383.68 11155.03 -3104.18 534.25 220s Armed.Forces -237.75 -2207.26 -3104.18 1429.11 -171.28 220s Population 46.12 461.15 534.25 -171.28 36.79 220s Year 29.01 287.48 340.95 -112.61 22.85 220s Employed 18.99 193.66 186.31 -76.88 14.94 220s Year Employed 220s GNP.deflator 29.01 18.99 220s GNP 287.48 193.66 220s Unemployed 340.95 186.31 220s Armed.Forces -112.61 -76.88 220s Population 22.85 14.94 220s Year 14.36 9.45 220s Employed 9.45 6.90 220s -------------------------------------------------------- 220s Loblolly 84 3 7.757906 220s Outliers: 27 220s [1] 5 6 11 12 18 23 24 29 30 35 36 41 42 47 48 53 54 59 60 65 66 71 72 77 78 220s [26] 83 84 220s ------------- 220s 220s Call: 220s CovSest(x = x, method = method) 220s -> Method: S-estimates: Rocke type 220s 220s Robust Estimate of Location: 220s height age Seed 220s 21.72 8.60 7.58 220s 220s Robust Estimate of Covariance: 220s height age Seed 220s height 316.590 102.273 5.939 220s age 102.273 33.465 -0.121 220s Seed 5.939 -0.121 27.203 220s -------------------------------------------------------- 220s quakes 1000 4 11.473431 220s Outliers: 237 220s [1] 7 12 15 17 22 25 27 28 32 37 40 41 45 48 53 220s [16] 63 64 73 78 87 91 92 94 99 108 110 117 118 119 120 220s [31] 121 122 126 133 136 141 143 145 148 152 154 155 157 159 160 220s [46] 163 166 170 174 176 192 205 222 226 230 239 243 244 250 251 220s [61] 252 254 258 263 267 268 271 283 292 297 300 301 305 311 312 220s [76] 318 320 321 325 328 330 331 334 352 357 360 365 368 376 381 220s [91] 382 384 389 399 400 402 408 410 413 416 417 418 419 426 429 220s [106] 437 441 443 453 456 467 474 477 490 492 496 504 507 508 509 220s [121] 517 524 527 528 531 532 534 536 538 539 541 542 543 544 545 220s [136] 546 547 552 553 558 560 570 571 581 583 587 593 594 596 597 220s [151] 605 612 613 618 620 625 629 638 642 647 649 653 655 656 672 220s [166] 675 681 686 699 701 702 712 714 716 721 725 726 735 744 753 220s [181] 754 756 759 765 766 769 779 781 782 785 787 797 804 813 825 220s [196] 827 837 840 844 852 853 857 860 865 866 869 870 872 873 883 220s [211] 884 887 888 890 891 893 908 909 912 915 916 921 927 930 952 220s [226] 962 963 969 974 980 982 986 987 988 992 997 1000 220s ------------- 220s 220s Call: 220s CovSest(x = x, method = method) 220s -> Method: S-estimates: Rocke type 220s 220s Robust Estimate of Location: 220s lat long depth mag 220s -21.45 182.54 351.18 4.55 220s 220s Robust Estimate of Covariance: 220s lat long depth mag 220s lat 2.10e+01 4.66e+00 2.45e+02 -3.38e-01 220s long 4.66e+00 5.88e+00 -4.63e+02 9.36e-02 220s depth 2.45e+02 -4.63e+02 6.38e+04 -2.02e+01 220s mag -3.38e-01 9.36e-02 -2.02e+01 1.78e-01 220s -------------------------------------------------------- 220s =================================================== 220s > dodata(method="MM") 220s 220s Call: dodata(method = "MM") 220s Data Set n p LOG(det) Time 220s =================================================== 220s heart 12 2 2.017701 220s Outliers: 1 220s [1] 6 220s ------------- 220s 220s Call: 220s CovMMest(x = x) 220s -> Method: MM-estimates 220s 220s Robust Estimate of Location: 220s height weight 220s 40.0 37.7 220s 220s Robust Estimate of Covariance: 220s height weight 220s height 99.2 205.7 220s weight 205.7 458.9 220s -------------------------------------------------------- 220s starsCYG 47 2 -1.450032 220s Outliers: 7 220s [1] 7 9 11 14 20 30 34 220s ------------- 220s 220s Call: 220s CovMMest(x = x) 220s -> Method: MM-estimates 220s 220s Robust Estimate of Location: 220s log.Te log.light 220s 4.41 4.94 220s 220s Robust Estimate of Covariance: 220s log.Te log.light 220s log.Te 0.0180 0.0526 220s log.light 0.0526 0.3217 220s -------------------------------------------------------- 220s phosphor 18 2 2.320721 220s Outliers: 1 220s [1] 6 220s ------------- 220s 220s Call: 220s CovMMest(x = x) 220s -> Method: MM-estimates 220s 220s Robust Estimate of Location: 220s inorg organic 220s 12.3 41.4 220s 220s Robust Estimate of Covariance: 220s inorg organic 220s inorg 94.2 67.2 220s organic 67.2 162.1 220s -------------------------------------------------------- 220s stackloss 21 3 1.470031 220s Outliers: 0 220s ------------- 220s 220s Call: 220s CovMMest(x = x) 220s -> Method: MM-estimates 220s 220s Robust Estimate of Location: 220s Air.Flow Water.Temp Acid.Conc. 220s 60.2 21.0 86.4 220s 220s Robust Estimate of Covariance: 220s Air.Flow Water.Temp Acid.Conc. 220s Air.Flow 81.13 21.99 23.15 220s Water.Temp 21.99 10.01 6.43 220s Acid.Conc. 23.15 6.43 27.22 220s -------------------------------------------------------- 220s coleman 20 5 0.491419 220s Outliers: 1 220s [1] 10 220s ------------- 220s 220s Call: 220s CovMMest(x = x) 220s -> Method: MM-estimates 220s 220s Robust Estimate of Location: 220s salaryP fatherWc sstatus teacherSc motherLev 220s 2.74 43.14 3.65 25.07 6.32 220s 220s Robust Estimate of Covariance: 220s salaryP fatherWc sstatus teacherSc motherLev 220s salaryP 0.1878 2.0635 1.0433 0.2721 0.0582 220s fatherWc 2.0635 670.2232 211.0609 4.3625 15.6083 220s sstatus 1.0433 211.0609 92.8743 2.6532 5.1816 220s teacherSc 0.2721 4.3625 2.6532 1.2757 0.1613 220s motherLev 0.0582 15.6083 5.1816 0.1613 0.4192 220s -------------------------------------------------------- 220s salinity 28 3 0.734619 220s Outliers: 2 220s [1] 5 16 220s ------------- 220s 220s Call: 220s CovMMest(x = x) 220s -> Method: MM-estimates 220s 220s Robust Estimate of Location: 220s X1 X2 X3 220s 10.46 2.66 23.15 220s 220s Robust Estimate of Covariance: 220s X1 X2 X3 220s X1 10.079 -0.024 -1.899 220s X2 -0.024 3.466 -1.817 220s X3 -1.899 -1.817 3.665 220s -------------------------------------------------------- 220s wood 20 5 -3.202636 220s Outliers: 0 220s ------------- 220s 220s Call: 220s CovMMest(x = x) 220s -> Method: MM-estimates 220s 220s Robust Estimate of Location: 220s x1 x2 x3 x4 x5 220s 0.550 0.133 0.506 0.511 0.909 220s 220s Robust Estimate of Covariance: 220s x1 x2 x3 x4 x5 220s x1 0.008454 -0.000377 0.003720 0.002874 -0.003065 220s x2 -0.000377 0.000516 -0.000399 -0.000933 0.000645 220s x3 0.003720 -0.000399 0.004186 0.001720 -0.001714 220s x4 0.002874 -0.000933 0.001720 0.003993 -0.001028 220s x5 -0.003065 0.000645 -0.001714 -0.001028 0.002744 220s -------------------------------------------------------- 220s hbk 75 3 0.283145 220s Outliers: 14 220s [1] 1 2 3 4 5 6 7 8 9 10 11 12 13 14 220s ------------- 220s 220s Call: 220s CovMMest(x = x) 220s -> Method: MM-estimates 220s 220s Robust Estimate of Location: 220s X1 X2 X3 220s 1.54 1.79 1.68 220s 220s Robust Estimate of Covariance: 220s X1 X2 X3 220s X1 1.8016 0.0739 0.2000 220s X2 0.0739 1.8301 0.2295 220s X3 0.2000 0.2295 1.7101 220s -------------------------------------------------------- 220s Animals 28 2 4.685129 220s Outliers: 10 220s [1] 2 6 7 9 12 14 15 16 24 25 220s ------------- 220s 220s Call: 220s CovMMest(x = x) 220s -> Method: MM-estimates 220s 220s Robust Estimate of Location: 220s body brain 220s 82 148 220s 220s Robust Estimate of Covariance: 220s body brain 220s body 21050 24534 220s brain 24534 35135 220s -------------------------------------------------------- 221s milk 86 8 -1.437863 221s Outliers: 12 221s [1] 1 2 3 12 13 17 41 44 47 70 74 75 221s ------------- 221s 221s Call: 221s CovMMest(x = x) 221s -> Method: MM-estimates 221s 221s Robust Estimate of Location: 221s X1 X2 X3 X4 X5 X6 X7 X8 221s 1.03 35.73 32.87 25.96 24.94 24.85 122.55 14.33 221s 221s Robust Estimate of Covariance: 221s X1 X2 X3 X4 X5 X6 X7 221s X1 1.08e-06 5.36e-04 6.80e-04 5.96e-04 5.87e-04 5.91e-04 2.22e-03 221s X2 5.36e-04 2.42e+00 7.07e-01 5.51e-01 4.89e-01 5.70e-01 3.08e+00 221s X3 6.80e-04 7.07e-01 1.64e+00 1.28e+00 1.25e+00 1.26e+00 2.38e+00 221s X4 5.96e-04 5.51e-01 1.28e+00 1.05e+00 1.01e+00 1.02e+00 2.01e+00 221s X5 5.87e-04 4.89e-01 1.25e+00 1.01e+00 1.05e+00 1.02e+00 1.96e+00 221s X6 5.91e-04 5.70e-01 1.26e+00 1.02e+00 1.02e+00 1.05e+00 2.01e+00 221s X7 2.22e-03 3.08e+00 2.38e+00 2.01e+00 1.96e+00 2.01e+00 9.22e+00 221s X8 1.68e-04 4.13e-01 3.37e-01 2.53e-01 2.34e-01 2.43e-01 8.81e-01 221s X8 221s X1 1.68e-04 221s X2 4.13e-01 221s X3 3.37e-01 221s X4 2.53e-01 221s X5 2.34e-01 221s X6 2.43e-01 221s X7 8.81e-01 221s X8 2.11e-01 221s -------------------------------------------------------- 221s bushfire 38 5 2.443148 221s Outliers: 12 221s [1] 8 9 10 11 31 32 33 34 35 36 37 38 221s ------------- 221s 221s Call: 221s CovMMest(x = x) 221s -> Method: MM-estimates 221s 221s Robust Estimate of Location: 221s V1 V2 V3 V4 V5 221s 109 149 258 215 276 221s 221s Robust Estimate of Covariance: 221s V1 V2 V3 V4 V5 221s V1 708 538 -2705 -558 -464 221s V2 538 497 -1376 -248 -216 221s V3 -2705 -1376 20521 4833 3914 221s V4 -558 -248 4833 1217 969 221s V5 -464 -216 3914 969 778 221s -------------------------------------------------------- 221s rice 105 5 -0.724874 221s Outliers: 5 221s [1] 9 42 49 58 71 221s ------------- 221s 221s Call: 221s CovMMest(x = x) 221s -> Method: MM-estimates 221s 221s Robust Estimate of Location: 221s Favor Appearance Taste Stickiness Toughness 221s -0.2653 0.0969 -0.1371 0.0483 0.0731 221s 221s Robust Estimate of Covariance: 221s Favor Appearance Taste Stickiness Toughness 221s Favor 0.421 0.349 0.427 0.405 -0.191 221s Appearance 0.349 0.605 0.565 0.553 -0.316 221s Taste 0.427 0.565 0.725 0.701 -0.378 221s Stickiness 0.405 0.553 0.701 0.868 -0.484 221s Toughness -0.191 -0.316 -0.378 -0.484 0.464 221s -------------------------------------------------------- 221s hemophilia 75 2 -1.868949 221s Outliers: 2 221s [1] 11 36 221s ------------- 221s 221s Call: 221s CovMMest(x = x) 221s -> Method: MM-estimates 221s 221s Robust Estimate of Location: 221s AHFactivity AHFantigen 221s -0.2342 -0.0333 221s 221s Robust Estimate of Covariance: 221s AHFactivity AHFantigen 221s AHFactivity 0.0309 0.0122 221s AHFantigen 0.0122 0.0231 221s -------------------------------------------------------- 221s fish 159 6 1.285876 221s Outliers: 20 221s [1] 61 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 221s [20] 142 221s ------------- 221s 221s Call: 221s CovMMest(x = x) 221s -> Method: MM-estimates 221s 221s Robust Estimate of Location: 221s Weight Length1 Length2 Length3 Height Width 221s 352.7 24.3 26.4 29.2 29.7 14.6 221s 221s Robust Estimate of Covariance: 221s Weight Length1 Length2 Length3 Height Width 221s Weight 1.20e+05 2.89e+03 3.12e+03 3.51e+03 1.49e+03 2.83e+02 221s Length1 2.89e+03 7.73e+01 8.35e+01 9.28e+01 3.73e+01 9.26e+00 221s Length2 3.12e+03 8.35e+01 9.04e+01 1.01e+02 4.16e+01 1.01e+01 221s Length3 3.51e+03 9.28e+01 1.01e+02 1.14e+02 5.37e+01 1.01e+01 221s Height 1.49e+03 3.73e+01 4.16e+01 5.37e+01 6.75e+01 3.22e+00 221s Width 2.83e+02 9.26e+00 1.01e+01 1.01e+01 3.22e+00 4.18e+00 221s -------------------------------------------------------- 221s airquality 153 4 2.684374 221s Outliers: 6 221s [1] 7 14 23 30 34 77 221s ------------- 221s 221s Call: 221s CovMMest(x = x) 221s -> Method: MM-estimates 221s 221s Robust Estimate of Location: 221s Ozone Solar.R Wind Temp 221s 40.35 186.21 9.86 78.09 221s 221s Robust Estimate of Covariance: 221s Ozone Solar.R Wind Temp 221s Ozone 951.0 959.9 -62.5 224.6 221s Solar.R 959.9 8629.9 -28.1 244.9 221s Wind -62.5 -28.1 11.6 -15.8 221s Temp 224.6 244.9 -15.8 93.1 221s -------------------------------------------------------- 221s attitude 30 7 2.091968 221s Outliers: 4 221s [1] 14 16 18 24 221s ------------- 221s 221s Call: 221s CovMMest(x = x) 221s -> Method: MM-estimates 221s 221s Robust Estimate of Location: 221s rating complaints privileges learning raises critical 221s 65.0 66.5 52.4 56.2 65.3 75.6 221s advance 221s 42.7 221s 221s Robust Estimate of Covariance: 221s rating complaints privileges learning raises critical advance 221s rating 143.5 123.4 62.4 92.5 79.2 17.7 28.2 221s complaints 123.4 159.8 83.9 99.7 96.0 27.3 44.0 221s privileges 62.4 83.9 133.5 78.6 62.0 13.4 46.4 221s learning 92.5 99.7 78.6 136.0 90.9 18.9 62.6 221s raises 79.2 96.0 62.0 90.9 107.6 34.6 63.3 221s critical 17.7 27.3 13.4 18.9 34.6 84.9 25.9 221s advance 28.2 44.0 46.4 62.6 63.3 25.9 94.4 221s -------------------------------------------------------- 221s attenu 182 5 1.148032 221s Outliers: 21 221s [1] 2 7 8 9 10 11 15 16 24 25 28 29 30 31 32 64 65 94 95 221s [20] 96 100 221s ------------- 221s 221s Call: 221s CovMMest(x = x) 221s -> Method: MM-estimates 221s 221s Robust Estimate of Location: 221s event mag station dist accel 221s 15.36 5.95 58.11 33.56 0.14 221s 221s Robust Estimate of Covariance: 221s event mag station dist accel 221s event 4.88e+01 -2.74e+00 1.53e+02 -1.14e+02 5.95e-02 221s mag -2.74e+00 5.32e-01 -6.29e+00 1.10e+01 9.37e-03 221s station 1.53e+02 -6.29e+00 1.29e+03 -2.95e+02 1.04e+00 221s dist -1.14e+02 1.10e+01 -2.95e+02 1.13e+03 -2.41e+00 221s accel 5.95e-02 9.37e-03 1.04e+00 -2.41e+00 1.70e-02 221s -------------------------------------------------------- 221s USJudgeRatings 43 12 -1.683847 221s Outliers: 7 221s [1] 5 7 12 13 14 23 31 221s ------------- 221s 221s Call: 221s CovMMest(x = x) 221s -> Method: MM-estimates 221s 221s Robust Estimate of Location: 221s CONT INTG DMNR DILG CFMG DECI PREP FAMI ORAL WRIT PHYS RTEN 221s 7.45 8.15 7.74 7.87 7.67 7.74 7.65 7.65 7.50 7.57 8.17 7.85 221s 221s Robust Estimate of Covariance: 221s CONT INTG DMNR DILG CFMG DECI PREP FAMI 221s CONT 0.9403 -0.2500 -0.3953 -0.1418 -0.0176 -0.0620 -0.1304 -0.1517 221s INTG -0.2500 0.6314 0.8479 0.6889 0.5697 0.5386 0.7007 0.6985 221s DMNR -0.3953 0.8479 1.2186 0.9027 0.7613 0.7232 0.9191 0.9055 221s DILG -0.1418 0.6889 0.9027 0.8474 0.7344 0.6949 0.8751 0.8655 221s CFMG -0.0176 0.5697 0.7613 0.7344 0.6904 0.6442 0.7683 0.7594 221s DECI -0.0620 0.5386 0.7232 0.6949 0.6442 0.6219 0.7362 0.7360 221s PREP -0.1304 0.7007 0.9191 0.8751 0.7683 0.7362 0.9370 0.9357 221s FAMI -0.1517 0.6985 0.9055 0.8655 0.7594 0.7360 0.9357 0.9547 221s ORAL -0.1866 0.7375 0.9841 0.8816 0.7747 0.7433 0.9400 0.9496 221s WRIT -0.1881 0.7208 0.9516 0.8711 0.7646 0.7357 0.9302 0.9439 221s PHYS -0.1407 0.4673 0.6261 0.5661 0.5105 0.5039 0.5996 0.6112 221s RTEN -0.2494 0.7921 1.0688 0.9167 0.7902 0.7585 0.9533 0.9561 221s ORAL WRIT PHYS RTEN 221s CONT -0.1866 -0.1881 -0.1407 -0.2494 221s INTG 0.7375 0.7208 0.4673 0.7921 221s DMNR 0.9841 0.9516 0.6261 1.0688 221s DILG 0.8816 0.8711 0.5661 0.9167 221s CFMG 0.7747 0.7646 0.5105 0.7902 221s DECI 0.7433 0.7357 0.5039 0.7585 221s PREP 0.9400 0.9302 0.5996 0.9533 221s FAMI 0.9496 0.9439 0.6112 0.9561 221s ORAL 0.9712 0.9558 0.6271 0.9933 221s WRIT 0.9558 0.9483 0.6135 0.9725 221s PHYS 0.6271 0.6135 0.4816 0.6549 221s RTEN 0.9933 0.9725 0.6549 1.0540 221s -------------------------------------------------------- 221s USArrests 50 4 2.411726 221s Outliers: 3 221s [1] 2 33 39 221s ------------- 221s 221s Call: 221s CovMMest(x = x) 221s -> Method: MM-estimates 221s 221s Robust Estimate of Location: 221s Murder Assault UrbanPop Rape 221s 7.52 163.86 65.66 20.64 221s 221s Robust Estimate of Covariance: 221s Murder Assault UrbanPop Rape 221s Murder 19.05 295.96 8.32 23.40 221s Assault 295.96 6905.03 396.53 523.49 221s UrbanPop 8.32 396.53 202.98 62.81 221s Rape 23.40 523.49 62.81 79.10 221s -------------------------------------------------------- 221s longley 16 7 1.038316 221s Outliers: 5 221s [1] 1 2 3 4 5 221s ------------- 221s 221s Call: 221s CovMMest(x = x) 221s -> Method: MM-estimates 221s 221s Robust Estimate of Location: 221s GNP.deflator GNP Unemployed Armed.Forces Population 221s 107.5 440.4 339.4 293.0 120.9 221s Year Employed 221s 1957.0 67.2 221s 221s Robust Estimate of Covariance: 221s GNP.deflator GNP Unemployed Armed.Forces Population 221s GNP.deflator 100.4 953.8 1140.8 -501.8 74.3 221s GNP 953.8 9434.3 10084.3 -4573.8 731.3 221s Unemployed 1140.8 10084.3 19644.6 -6296.3 848.4 221s Armed.Forces -501.8 -4573.8 -6296.3 3192.3 -348.5 221s Population 74.3 731.3 848.4 -348.5 57.7 221s Year 46.3 450.7 537.0 -230.7 35.3 221s Employed 30.8 310.2 273.8 -159.4 23.3 221s Year Employed 221s GNP.deflator 46.3 30.8 221s GNP 450.7 310.2 221s Unemployed 537.0 273.8 221s Armed.Forces -230.7 -159.4 221s Population 35.3 23.3 221s Year 21.9 14.6 221s Employed 14.6 11.2 221s -------------------------------------------------------- 221s Loblolly 84 3 1.481317 221s Outliers: 0 221s ------------- 221s 221s Call: 221s CovMMest(x = x) 221s -> Method: MM-estimates 221s 221s Robust Estimate of Location: 221s height age Seed 221s 31.93 12.79 7.48 221s 221s Robust Estimate of Covariance: 221s height age Seed 221s height 440.644 165.652 6.958 221s age 165.652 63.500 0.681 221s Seed 6.958 0.681 16.564 221s -------------------------------------------------------- 221s quakes 1000 4 1.576855 221s Outliers: 218 221s [1] 7 12 15 17 22 27 32 37 40 41 45 48 53 63 64 221s [16] 73 78 87 91 92 94 99 108 110 117 118 119 120 121 122 221s [31] 126 133 136 141 143 145 148 152 154 155 157 159 160 163 170 221s [46] 192 205 222 226 230 239 243 250 251 252 254 258 263 267 268 221s [61] 271 283 292 300 301 305 311 312 318 320 321 325 328 330 334 221s [76] 352 357 360 365 381 382 384 389 400 402 408 413 416 417 419 221s [91] 429 437 441 443 453 456 467 474 477 490 492 496 504 507 508 221s [106] 509 517 524 527 528 531 532 534 536 538 539 541 542 543 544 221s [121] 545 546 547 552 553 560 571 581 583 587 593 594 596 597 605 221s [136] 612 613 618 620 625 629 638 642 647 649 653 655 656 672 675 221s [151] 681 686 699 701 702 712 714 716 721 725 726 735 744 754 756 221s [166] 759 765 766 769 779 781 782 785 787 797 804 813 825 827 837 221s [181] 840 844 852 853 857 860 865 866 869 870 872 873 883 884 887 221s [196] 888 890 891 893 908 909 912 915 916 921 927 930 962 963 969 221s [211] 974 980 982 986 987 988 997 1000 221s ------------- 221s 221s Call: 221s CovMMest(x = x) 221s -> Method: MM-estimates 221s 221s Robust Estimate of Location: 221s lat long depth mag 221s -21.74 182.37 356.37 4.56 221s 221s Robust Estimate of Covariance: 221s lat long depth mag 221s lat 2.97e+01 6.53e+00 3.46e+02 -4.66e-01 221s long 6.53e+00 6.92e+00 -5.05e+02 5.62e-02 221s depth 3.46e+02 -5.05e+02 7.39e+04 -2.51e+01 221s mag -4.66e-01 5.62e-02 -2.51e+01 2.32e-01 221s -------------------------------------------------------- 221s =================================================== 221s > ##dogen() 221s > ##cat('Time elapsed: ', proc.time(),'\n') # for ``statistical reasons'' 221s > 222s autopkgtest [20:02:50]: test run-unit-test: -----------------------] 223s autopkgtest [20:02:51]: test run-unit-test: - - - - - - - - - - results - - - - - - - - - - 223s run-unit-test PASS 223s autopkgtest [20:02:51]: test pkg-r-autopkgtest: preparing testbed 225s Reading package lists... 225s Building dependency tree... 225s Reading state information... 225s Starting pkgProblemResolver with broken count: 0 226s Starting 2 pkgProblemResolver with broken count: 0 226s Done 228s The following additional packages will be installed: 228s build-essential cpp cpp-13 cpp-13-aarch64-linux-gnu cpp-aarch64-linux-gnu 228s dctrl-tools g++ g++-13 g++-13-aarch64-linux-gnu g++-aarch64-linux-gnu gcc 228s gcc-13 gcc-13-aarch64-linux-gnu gcc-aarch64-linux-gnu gfortran gfortran-13 228s gfortran-13-aarch64-linux-gnu gfortran-aarch64-linux-gnu icu-devtools 228s libasan8 libatomic1 libblas-dev libbz2-dev libc-dev-bin libc6-dev libcc1-0 228s libcrypt-dev libgcc-13-dev libgfortran-13-dev libhwasan0 libicu-dev libisl23 228s libitm1 libjpeg-dev libjpeg-turbo8-dev libjpeg8-dev liblapack-dev liblsan0 228s liblzma-dev libmpc3 libncurses-dev libnsl-dev libpcre2-16-0 libpcre2-32-0 228s libpcre2-dev libpcre2-posix3 libpkgconf3 libpng-dev libreadline-dev 228s libstdc++-13-dev libtirpc-dev libtsan2 libubsan1 linux-libc-dev pkg-config 228s pkg-r-autopkgtest pkgconf pkgconf-bin r-base-dev rpcsvc-proto zlib1g-dev 228s Suggested packages: 228s cpp-doc gcc-13-locales cpp-13-doc debtags gcc-13-doc gcc-multilib 228s manpages-dev autoconf automake libtool flex bison gdb gcc-doc 228s gdb-aarch64-linux-gnu gfortran-doc gfortran-13-doc libcoarrays-dev 228s liblapack-doc glibc-doc icu-doc liblzma-doc ncurses-doc readline-doc 228s libstdc++-13-doc texlive-base texlive-latex-base texlive-plain-generic 228s texlive-fonts-recommended texlive-fonts-extra texlive-extra-utils 228s texlive-latex-recommended texlive-latex-extra texinfo 228s Recommended packages: 228s bzip2-doc manpages manpages-dev libc-devtools libpng-tools 230s The following NEW packages will be installed: 230s autopkgtest-satdep build-essential cpp cpp-13 cpp-13-aarch64-linux-gnu 230s cpp-aarch64-linux-gnu dctrl-tools g++ g++-13 g++-13-aarch64-linux-gnu 230s g++-aarch64-linux-gnu gcc gcc-13 gcc-13-aarch64-linux-gnu 230s gcc-aarch64-linux-gnu gfortran gfortran-13 gfortran-13-aarch64-linux-gnu 230s gfortran-aarch64-linux-gnu icu-devtools libasan8 libatomic1 libblas-dev 230s libbz2-dev libc-dev-bin libc6-dev libcc1-0 libcrypt-dev libgcc-13-dev 230s libgfortran-13-dev libhwasan0 libicu-dev libisl23 libitm1 libjpeg-dev 230s libjpeg-turbo8-dev libjpeg8-dev liblapack-dev liblsan0 liblzma-dev libmpc3 230s libncurses-dev libnsl-dev libpcre2-16-0 libpcre2-32-0 libpcre2-dev 230s libpcre2-posix3 libpkgconf3 libpng-dev libreadline-dev libstdc++-13-dev 230s libtirpc-dev libtsan2 libubsan1 linux-libc-dev pkg-config pkg-r-autopkgtest 230s pkgconf pkgconf-bin r-base-dev rpcsvc-proto zlib1g-dev 231s 0 upgraded, 62 newly installed, 0 to remove and 0 not upgraded. 231s Need to get 92.8 MB/92.8 MB of archives. 231s After this operation, 343 MB of additional disk space will be used. 231s Get:1 /tmp/autopkgtest.EF2nlC/2-autopkgtest-satdep.deb autopkgtest-satdep arm64 0 [724 B] 232s Get:2 http://ftpmaster.internal/ubuntu noble/main arm64 libc-dev-bin arm64 2.39-0ubuntu2 [19.7 kB] 232s Get:3 http://ftpmaster.internal/ubuntu noble/main arm64 linux-libc-dev arm64 6.8.0-11.11 [1569 kB] 232s Get:4 http://ftpmaster.internal/ubuntu noble/main arm64 libcrypt-dev arm64 1:4.4.36-4 [136 kB] 232s Get:5 http://ftpmaster.internal/ubuntu noble-proposed/main arm64 libtirpc-dev arm64 1.3.4+ds-1.1 [201 kB] 232s Get:6 http://ftpmaster.internal/ubuntu noble/main arm64 libnsl-dev arm64 1.3.0-3 [71.9 kB] 232s Get:7 http://ftpmaster.internal/ubuntu noble/main arm64 rpcsvc-proto arm64 1.4.2-0ubuntu6 [65.4 kB] 232s Get:8 http://ftpmaster.internal/ubuntu noble/main arm64 libc6-dev arm64 2.39-0ubuntu2 [1596 kB] 232s Get:9 http://ftpmaster.internal/ubuntu noble/main arm64 libisl23 arm64 0.26-3 [713 kB] 232s Get:10 http://ftpmaster.internal/ubuntu noble/main arm64 libmpc3 arm64 1.3.1-1 [55.3 kB] 232s Get:11 http://ftpmaster.internal/ubuntu noble/main arm64 cpp-13-aarch64-linux-gnu arm64 13.2.0-17ubuntu2 [10.3 MB] 233s Get:12 http://ftpmaster.internal/ubuntu noble/main arm64 cpp-13 arm64 13.2.0-17ubuntu2 [1028 B] 233s Get:13 http://ftpmaster.internal/ubuntu noble/main arm64 cpp-aarch64-linux-gnu arm64 4:13.2.0-7ubuntu1 [5316 B] 233s Get:14 http://ftpmaster.internal/ubuntu noble/main arm64 cpp arm64 4:13.2.0-7ubuntu1 [22.4 kB] 233s Get:15 http://ftpmaster.internal/ubuntu noble/main arm64 libcc1-0 arm64 14-20240303-1ubuntu1 [44.7 kB] 233s Get:16 http://ftpmaster.internal/ubuntu noble/main arm64 libitm1 arm64 14-20240303-1ubuntu1 [27.7 kB] 233s Get:17 http://ftpmaster.internal/ubuntu noble/main arm64 libatomic1 arm64 14-20240303-1ubuntu1 [11.4 kB] 233s Get:18 http://ftpmaster.internal/ubuntu noble/main arm64 libasan8 arm64 14-20240303-1ubuntu1 [2919 kB] 233s Get:19 http://ftpmaster.internal/ubuntu noble/main arm64 liblsan0 arm64 14-20240303-1ubuntu1 [1282 kB] 233s Get:20 http://ftpmaster.internal/ubuntu noble/main arm64 libtsan2 arm64 14-20240303-1ubuntu1 [2687 kB] 233s Get:21 http://ftpmaster.internal/ubuntu noble/main arm64 libubsan1 arm64 14-20240303-1ubuntu1 [1151 kB] 233s Get:22 http://ftpmaster.internal/ubuntu noble/main arm64 libhwasan0 arm64 14-20240303-1ubuntu1 [1597 kB] 233s Get:23 http://ftpmaster.internal/ubuntu noble/main arm64 libgcc-13-dev arm64 13.2.0-17ubuntu2 [2464 kB] 233s Get:24 http://ftpmaster.internal/ubuntu noble/main arm64 gcc-13-aarch64-linux-gnu arm64 13.2.0-17ubuntu2 [20.1 MB] 233s Get:25 http://ftpmaster.internal/ubuntu noble/main arm64 gcc-13 arm64 13.2.0-17ubuntu2 [467 kB] 233s Get:26 http://ftpmaster.internal/ubuntu noble/main arm64 gcc-aarch64-linux-gnu arm64 4:13.2.0-7ubuntu1 [1198 B] 233s Get:27 http://ftpmaster.internal/ubuntu noble/main arm64 gcc arm64 4:13.2.0-7ubuntu1 [5018 B] 233s Get:28 http://ftpmaster.internal/ubuntu noble/main arm64 libstdc++-13-dev arm64 13.2.0-17ubuntu2 [2322 kB] 234s Get:29 http://ftpmaster.internal/ubuntu noble/main arm64 g++-13-aarch64-linux-gnu arm64 13.2.0-17ubuntu2 [11.7 MB] 234s Get:30 http://ftpmaster.internal/ubuntu noble/main arm64 g++-13 arm64 13.2.0-17ubuntu2 [14.4 kB] 234s Get:31 http://ftpmaster.internal/ubuntu noble/main arm64 g++-aarch64-linux-gnu arm64 4:13.2.0-7ubuntu1 [962 B] 234s Get:32 http://ftpmaster.internal/ubuntu noble/main arm64 g++ arm64 4:13.2.0-7ubuntu1 [1082 B] 234s Get:33 http://ftpmaster.internal/ubuntu noble/main arm64 build-essential arm64 12.10ubuntu1 [4932 B] 234s Get:34 http://ftpmaster.internal/ubuntu noble/main arm64 dctrl-tools arm64 2.24-3build2 [65.2 kB] 234s Get:35 http://ftpmaster.internal/ubuntu noble/main arm64 libgfortran-13-dev arm64 13.2.0-17ubuntu2 [478 kB] 234s Get:36 http://ftpmaster.internal/ubuntu noble/main arm64 gfortran-13-aarch64-linux-gnu arm64 13.2.0-17ubuntu2 [10.8 MB] 234s Get:37 http://ftpmaster.internal/ubuntu noble/main arm64 gfortran-13 arm64 13.2.0-17ubuntu2 [10.3 kB] 234s Get:38 http://ftpmaster.internal/ubuntu noble/main arm64 gfortran-aarch64-linux-gnu arm64 4:13.2.0-7ubuntu1 [1022 B] 234s Get:39 http://ftpmaster.internal/ubuntu noble/main arm64 gfortran arm64 4:13.2.0-7ubuntu1 [1164 B] 234s Get:40 http://ftpmaster.internal/ubuntu noble/main arm64 icu-devtools arm64 74.2-1ubuntu1 [209 kB] 234s Get:41 http://ftpmaster.internal/ubuntu noble/main arm64 libblas-dev arm64 3.12.0-3 [111 kB] 234s Get:42 http://ftpmaster.internal/ubuntu noble/main arm64 libbz2-dev arm64 1.0.8-5ubuntu1 [35.8 kB] 234s Get:43 http://ftpmaster.internal/ubuntu noble/main arm64 libicu-dev arm64 74.2-1ubuntu1 [11.9 MB] 234s Get:44 http://ftpmaster.internal/ubuntu noble/main arm64 libjpeg-turbo8-dev arm64 2.1.5-2ubuntu1 [304 kB] 234s Get:45 http://ftpmaster.internal/ubuntu noble/main arm64 libjpeg8-dev arm64 8c-2ubuntu11 [1484 B] 234s Get:46 http://ftpmaster.internal/ubuntu noble/main arm64 libjpeg-dev arm64 8c-2ubuntu11 [1482 B] 234s Get:47 http://ftpmaster.internal/ubuntu noble/main arm64 liblapack-dev arm64 3.12.0-3 [4293 kB] 234s Get:48 http://ftpmaster.internal/ubuntu noble/main arm64 libncurses-dev arm64 6.4+20240113-1ubuntu1 [385 kB] 234s Get:49 http://ftpmaster.internal/ubuntu noble/main arm64 libpcre2-16-0 arm64 10.42-4ubuntu1 [195 kB] 234s Get:50 http://ftpmaster.internal/ubuntu noble/main arm64 libpcre2-32-0 arm64 10.42-4ubuntu1 [183 kB] 234s Get:51 http://ftpmaster.internal/ubuntu noble/main arm64 libpcre2-posix3 arm64 10.42-4ubuntu1 [6654 B] 234s Get:52 http://ftpmaster.internal/ubuntu noble/main arm64 libpcre2-dev arm64 10.42-4ubuntu1 [679 kB] 234s Get:53 http://ftpmaster.internal/ubuntu noble/main arm64 libpkgconf3 arm64 1.8.1-2 [31.2 kB] 234s Get:54 http://ftpmaster.internal/ubuntu noble/main arm64 zlib1g-dev arm64 1:1.3.dfsg-3ubuntu1 [895 kB] 234s Get:55 http://ftpmaster.internal/ubuntu noble-proposed/main arm64 libpng-dev arm64 1.6.43-3 [267 kB] 235s Get:56 http://ftpmaster.internal/ubuntu noble-proposed/main arm64 libreadline-dev arm64 8.2-3.1 [177 kB] 235s Get:57 http://ftpmaster.internal/ubuntu noble/main arm64 pkgconf-bin arm64 1.8.1-2 [20.4 kB] 235s Get:58 http://ftpmaster.internal/ubuntu noble/main arm64 pkgconf arm64 1.8.1-2 [16.7 kB] 235s Get:59 http://ftpmaster.internal/ubuntu noble/main arm64 pkg-config arm64 1.8.1-2 [7170 B] 235s Get:60 http://ftpmaster.internal/ubuntu noble/main arm64 liblzma-dev arm64 5.4.5-0.3 [209 kB] 235s Get:61 http://ftpmaster.internal/ubuntu noble-proposed/universe arm64 r-base-dev all 4.3.3-2build1 [4334 B] 235s Get:62 http://ftpmaster.internal/ubuntu noble/universe arm64 pkg-r-autopkgtest all 20231212ubuntu1 [6448 B] 235s Fetched 92.8 MB in 4s (21.1 MB/s) 235s Selecting previously unselected package libc-dev-bin. 235s (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 ... 77222 files and directories currently installed.) 235s Preparing to unpack .../00-libc-dev-bin_2.39-0ubuntu2_arm64.deb ... 235s Unpacking libc-dev-bin (2.39-0ubuntu2) ... 235s Selecting previously unselected package linux-libc-dev:arm64. 235s Preparing to unpack .../01-linux-libc-dev_6.8.0-11.11_arm64.deb ... 235s Unpacking linux-libc-dev:arm64 (6.8.0-11.11) ... 236s Selecting previously unselected package libcrypt-dev:arm64. 236s Preparing to unpack .../02-libcrypt-dev_1%3a4.4.36-4_arm64.deb ... 236s Unpacking libcrypt-dev:arm64 (1:4.4.36-4) ... 236s Selecting previously unselected package libtirpc-dev:arm64. 236s Preparing to unpack .../03-libtirpc-dev_1.3.4+ds-1.1_arm64.deb ... 236s Unpacking libtirpc-dev:arm64 (1.3.4+ds-1.1) ... 236s Selecting previously unselected package libnsl-dev:arm64. 236s Preparing to unpack .../04-libnsl-dev_1.3.0-3_arm64.deb ... 236s Unpacking libnsl-dev:arm64 (1.3.0-3) ... 236s Selecting previously unselected package rpcsvc-proto. 236s Preparing to unpack .../05-rpcsvc-proto_1.4.2-0ubuntu6_arm64.deb ... 236s Unpacking rpcsvc-proto (1.4.2-0ubuntu6) ... 236s Selecting previously unselected package libc6-dev:arm64. 236s Preparing to unpack .../06-libc6-dev_2.39-0ubuntu2_arm64.deb ... 236s Unpacking libc6-dev:arm64 (2.39-0ubuntu2) ... 236s Selecting previously unselected package libisl23:arm64. 236s Preparing to unpack .../07-libisl23_0.26-3_arm64.deb ... 236s Unpacking libisl23:arm64 (0.26-3) ... 236s Selecting previously unselected package libmpc3:arm64. 236s Preparing to unpack .../08-libmpc3_1.3.1-1_arm64.deb ... 236s Unpacking libmpc3:arm64 (1.3.1-1) ... 236s Selecting previously unselected package cpp-13-aarch64-linux-gnu. 236s Preparing to unpack .../09-cpp-13-aarch64-linux-gnu_13.2.0-17ubuntu2_arm64.deb ... 236s Unpacking cpp-13-aarch64-linux-gnu (13.2.0-17ubuntu2) ... 236s Selecting previously unselected package cpp-13. 236s Preparing to unpack .../10-cpp-13_13.2.0-17ubuntu2_arm64.deb ... 236s Unpacking cpp-13 (13.2.0-17ubuntu2) ... 236s Selecting previously unselected package cpp-aarch64-linux-gnu. 236s Preparing to unpack .../11-cpp-aarch64-linux-gnu_4%3a13.2.0-7ubuntu1_arm64.deb ... 236s Unpacking cpp-aarch64-linux-gnu (4:13.2.0-7ubuntu1) ... 236s Selecting previously unselected package cpp. 236s Preparing to unpack .../12-cpp_4%3a13.2.0-7ubuntu1_arm64.deb ... 236s Unpacking cpp (4:13.2.0-7ubuntu1) ... 236s Selecting previously unselected package libcc1-0:arm64. 236s Preparing to unpack .../13-libcc1-0_14-20240303-1ubuntu1_arm64.deb ... 236s Unpacking libcc1-0:arm64 (14-20240303-1ubuntu1) ... 236s Selecting previously unselected package libitm1:arm64. 236s Preparing to unpack .../14-libitm1_14-20240303-1ubuntu1_arm64.deb ... 236s Unpacking libitm1:arm64 (14-20240303-1ubuntu1) ... 236s Selecting previously unselected package libatomic1:arm64. 236s Preparing to unpack .../15-libatomic1_14-20240303-1ubuntu1_arm64.deb ... 236s Unpacking libatomic1:arm64 (14-20240303-1ubuntu1) ... 236s Selecting previously unselected package libasan8:arm64. 236s Preparing to unpack .../16-libasan8_14-20240303-1ubuntu1_arm64.deb ... 236s Unpacking libasan8:arm64 (14-20240303-1ubuntu1) ... 236s Selecting previously unselected package liblsan0:arm64. 236s Preparing to unpack .../17-liblsan0_14-20240303-1ubuntu1_arm64.deb ... 236s Unpacking liblsan0:arm64 (14-20240303-1ubuntu1) ... 236s Selecting previously unselected package libtsan2:arm64. 236s Preparing to unpack .../18-libtsan2_14-20240303-1ubuntu1_arm64.deb ... 236s Unpacking libtsan2:arm64 (14-20240303-1ubuntu1) ... 237s Selecting previously unselected package libubsan1:arm64. 237s Preparing to unpack .../19-libubsan1_14-20240303-1ubuntu1_arm64.deb ... 237s Unpacking libubsan1:arm64 (14-20240303-1ubuntu1) ... 237s Selecting previously unselected package libhwasan0:arm64. 237s Preparing to unpack .../20-libhwasan0_14-20240303-1ubuntu1_arm64.deb ... 237s Unpacking libhwasan0:arm64 (14-20240303-1ubuntu1) ... 237s Selecting previously unselected package libgcc-13-dev:arm64. 237s Preparing to unpack .../21-libgcc-13-dev_13.2.0-17ubuntu2_arm64.deb ... 237s Unpacking libgcc-13-dev:arm64 (13.2.0-17ubuntu2) ... 237s Selecting previously unselected package gcc-13-aarch64-linux-gnu. 237s Preparing to unpack .../22-gcc-13-aarch64-linux-gnu_13.2.0-17ubuntu2_arm64.deb ... 237s Unpacking gcc-13-aarch64-linux-gnu (13.2.0-17ubuntu2) ... 237s Selecting previously unselected package gcc-13. 237s Preparing to unpack .../23-gcc-13_13.2.0-17ubuntu2_arm64.deb ... 237s Unpacking gcc-13 (13.2.0-17ubuntu2) ... 237s Selecting previously unselected package gcc-aarch64-linux-gnu. 237s Preparing to unpack .../24-gcc-aarch64-linux-gnu_4%3a13.2.0-7ubuntu1_arm64.deb ... 237s Unpacking gcc-aarch64-linux-gnu (4:13.2.0-7ubuntu1) ... 237s Selecting previously unselected package gcc. 237s Preparing to unpack .../25-gcc_4%3a13.2.0-7ubuntu1_arm64.deb ... 237s Unpacking gcc (4:13.2.0-7ubuntu1) ... 237s Selecting previously unselected package libstdc++-13-dev:arm64. 237s Preparing to unpack .../26-libstdc++-13-dev_13.2.0-17ubuntu2_arm64.deb ... 237s Unpacking libstdc++-13-dev:arm64 (13.2.0-17ubuntu2) ... 238s Selecting previously unselected package g++-13-aarch64-linux-gnu. 238s Preparing to unpack .../27-g++-13-aarch64-linux-gnu_13.2.0-17ubuntu2_arm64.deb ... 238s Unpacking g++-13-aarch64-linux-gnu (13.2.0-17ubuntu2) ... 238s Selecting previously unselected package g++-13. 238s Preparing to unpack .../28-g++-13_13.2.0-17ubuntu2_arm64.deb ... 238s Unpacking g++-13 (13.2.0-17ubuntu2) ... 238s Selecting previously unselected package g++-aarch64-linux-gnu. 238s Preparing to unpack .../29-g++-aarch64-linux-gnu_4%3a13.2.0-7ubuntu1_arm64.deb ... 238s Unpacking g++-aarch64-linux-gnu (4:13.2.0-7ubuntu1) ... 238s Selecting previously unselected package g++. 238s Preparing to unpack .../30-g++_4%3a13.2.0-7ubuntu1_arm64.deb ... 238s Unpacking g++ (4:13.2.0-7ubuntu1) ... 238s Selecting previously unselected package build-essential. 238s Preparing to unpack .../31-build-essential_12.10ubuntu1_arm64.deb ... 238s Unpacking build-essential (12.10ubuntu1) ... 238s Selecting previously unselected package dctrl-tools. 238s Preparing to unpack .../32-dctrl-tools_2.24-3build2_arm64.deb ... 238s Unpacking dctrl-tools (2.24-3build2) ... 238s Selecting previously unselected package libgfortran-13-dev:arm64. 238s Preparing to unpack .../33-libgfortran-13-dev_13.2.0-17ubuntu2_arm64.deb ... 238s Unpacking libgfortran-13-dev:arm64 (13.2.0-17ubuntu2) ... 238s Selecting previously unselected package gfortran-13-aarch64-linux-gnu. 238s Preparing to unpack .../34-gfortran-13-aarch64-linux-gnu_13.2.0-17ubuntu2_arm64.deb ... 238s Unpacking gfortran-13-aarch64-linux-gnu (13.2.0-17ubuntu2) ... 238s Selecting previously unselected package gfortran-13. 238s Preparing to unpack .../35-gfortran-13_13.2.0-17ubuntu2_arm64.deb ... 238s Unpacking gfortran-13 (13.2.0-17ubuntu2) ... 238s Selecting previously unselected package gfortran-aarch64-linux-gnu. 238s Preparing to unpack .../36-gfortran-aarch64-linux-gnu_4%3a13.2.0-7ubuntu1_arm64.deb ... 238s Unpacking gfortran-aarch64-linux-gnu (4:13.2.0-7ubuntu1) ... 238s Selecting previously unselected package gfortran. 238s Preparing to unpack .../37-gfortran_4%3a13.2.0-7ubuntu1_arm64.deb ... 238s Unpacking gfortran (4:13.2.0-7ubuntu1) ... 238s Selecting previously unselected package icu-devtools. 238s Preparing to unpack .../38-icu-devtools_74.2-1ubuntu1_arm64.deb ... 238s Unpacking icu-devtools (74.2-1ubuntu1) ... 238s Selecting previously unselected package libblas-dev:arm64. 238s Preparing to unpack .../39-libblas-dev_3.12.0-3_arm64.deb ... 238s Unpacking libblas-dev:arm64 (3.12.0-3) ... 238s Selecting previously unselected package libbz2-dev:arm64. 238s Preparing to unpack .../40-libbz2-dev_1.0.8-5ubuntu1_arm64.deb ... 238s Unpacking libbz2-dev:arm64 (1.0.8-5ubuntu1) ... 239s Selecting previously unselected package libicu-dev:arm64. 239s Preparing to unpack .../41-libicu-dev_74.2-1ubuntu1_arm64.deb ... 239s Unpacking libicu-dev:arm64 (74.2-1ubuntu1) ... 239s Selecting previously unselected package libjpeg-turbo8-dev:arm64. 239s Preparing to unpack .../42-libjpeg-turbo8-dev_2.1.5-2ubuntu1_arm64.deb ... 239s Unpacking libjpeg-turbo8-dev:arm64 (2.1.5-2ubuntu1) ... 239s Selecting previously unselected package libjpeg8-dev:arm64. 239s Preparing to unpack .../43-libjpeg8-dev_8c-2ubuntu11_arm64.deb ... 239s Unpacking libjpeg8-dev:arm64 (8c-2ubuntu11) ... 239s Selecting previously unselected package libjpeg-dev:arm64. 239s Preparing to unpack .../44-libjpeg-dev_8c-2ubuntu11_arm64.deb ... 239s Unpacking libjpeg-dev:arm64 (8c-2ubuntu11) ... 239s Selecting previously unselected package liblapack-dev:arm64. 239s Preparing to unpack .../45-liblapack-dev_3.12.0-3_arm64.deb ... 239s Unpacking liblapack-dev:arm64 (3.12.0-3) ... 239s Selecting previously unselected package libncurses-dev:arm64. 239s Preparing to unpack .../46-libncurses-dev_6.4+20240113-1ubuntu1_arm64.deb ... 239s Unpacking libncurses-dev:arm64 (6.4+20240113-1ubuntu1) ... 239s Selecting previously unselected package libpcre2-16-0:arm64. 239s Preparing to unpack .../47-libpcre2-16-0_10.42-4ubuntu1_arm64.deb ... 239s Unpacking libpcre2-16-0:arm64 (10.42-4ubuntu1) ... 239s Selecting previously unselected package libpcre2-32-0:arm64. 239s Preparing to unpack .../48-libpcre2-32-0_10.42-4ubuntu1_arm64.deb ... 239s Unpacking libpcre2-32-0:arm64 (10.42-4ubuntu1) ... 239s Selecting previously unselected package libpcre2-posix3:arm64. 239s Preparing to unpack .../49-libpcre2-posix3_10.42-4ubuntu1_arm64.deb ... 239s Unpacking libpcre2-posix3:arm64 (10.42-4ubuntu1) ... 239s Selecting previously unselected package libpcre2-dev:arm64. 239s Preparing to unpack .../50-libpcre2-dev_10.42-4ubuntu1_arm64.deb ... 239s Unpacking libpcre2-dev:arm64 (10.42-4ubuntu1) ... 240s Selecting previously unselected package libpkgconf3:arm64. 240s Preparing to unpack .../51-libpkgconf3_1.8.1-2_arm64.deb ... 240s Unpacking libpkgconf3:arm64 (1.8.1-2) ... 240s Selecting previously unselected package zlib1g-dev:arm64. 240s Preparing to unpack .../52-zlib1g-dev_1%3a1.3.dfsg-3ubuntu1_arm64.deb ... 240s Unpacking zlib1g-dev:arm64 (1:1.3.dfsg-3ubuntu1) ... 240s Selecting previously unselected package libpng-dev:arm64. 240s Preparing to unpack .../53-libpng-dev_1.6.43-3_arm64.deb ... 240s Unpacking libpng-dev:arm64 (1.6.43-3) ... 240s Selecting previously unselected package libreadline-dev:arm64. 240s Preparing to unpack .../54-libreadline-dev_8.2-3.1_arm64.deb ... 240s Unpacking libreadline-dev:arm64 (8.2-3.1) ... 240s Selecting previously unselected package pkgconf-bin. 240s Preparing to unpack .../55-pkgconf-bin_1.8.1-2_arm64.deb ... 240s Unpacking pkgconf-bin (1.8.1-2) ... 240s Selecting previously unselected package pkgconf:arm64. 240s Preparing to unpack .../56-pkgconf_1.8.1-2_arm64.deb ... 240s Unpacking pkgconf:arm64 (1.8.1-2) ... 240s Selecting previously unselected package pkg-config:arm64. 240s Preparing to unpack .../57-pkg-config_1.8.1-2_arm64.deb ... 240s Unpacking pkg-config:arm64 (1.8.1-2) ... 240s Selecting previously unselected package liblzma-dev:arm64. 240s Preparing to unpack .../58-liblzma-dev_5.4.5-0.3_arm64.deb ... 240s Unpacking liblzma-dev:arm64 (5.4.5-0.3) ... 240s Selecting previously unselected package r-base-dev. 240s Preparing to unpack .../59-r-base-dev_4.3.3-2build1_all.deb ... 240s Unpacking r-base-dev (4.3.3-2build1) ... 240s Selecting previously unselected package pkg-r-autopkgtest. 240s Preparing to unpack .../60-pkg-r-autopkgtest_20231212ubuntu1_all.deb ... 240s Unpacking pkg-r-autopkgtest (20231212ubuntu1) ... 240s Selecting previously unselected package autopkgtest-satdep. 240s Preparing to unpack .../61-2-autopkgtest-satdep.deb ... 240s Unpacking autopkgtest-satdep (0) ... 240s Setting up linux-libc-dev:arm64 (6.8.0-11.11) ... 240s Setting up libpcre2-16-0:arm64 (10.42-4ubuntu1) ... 240s Setting up libpcre2-32-0:arm64 (10.42-4ubuntu1) ... 240s Setting up libtirpc-dev:arm64 (1.3.4+ds-1.1) ... 240s Setting up libpkgconf3:arm64 (1.8.1-2) ... 240s Setting up rpcsvc-proto (1.4.2-0ubuntu6) ... 240s Setting up libmpc3:arm64 (1.3.1-1) ... 240s Setting up libatomic1:arm64 (14-20240303-1ubuntu1) ... 240s Setting up icu-devtools (74.2-1ubuntu1) ... 240s Setting up pkgconf-bin (1.8.1-2) ... 240s Setting up liblzma-dev:arm64 (5.4.5-0.3) ... 240s Setting up libubsan1:arm64 (14-20240303-1ubuntu1) ... 240s Setting up libpcre2-posix3:arm64 (10.42-4ubuntu1) ... 240s Setting up libnsl-dev:arm64 (1.3.0-3) ... 240s Setting up libhwasan0:arm64 (14-20240303-1ubuntu1) ... 240s Setting up libcrypt-dev:arm64 (1:4.4.36-4) ... 240s Setting up libasan8:arm64 (14-20240303-1ubuntu1) ... 240s Setting up libtsan2:arm64 (14-20240303-1ubuntu1) ... 240s Setting up libisl23:arm64 (0.26-3) ... 240s Setting up libc-dev-bin (2.39-0ubuntu2) ... 240s Setting up libcc1-0:arm64 (14-20240303-1ubuntu1) ... 240s Setting up liblsan0:arm64 (14-20240303-1ubuntu1) ... 240s Setting up libblas-dev:arm64 (3.12.0-3) ... 240s update-alternatives: using /usr/lib/aarch64-linux-gnu/blas/libblas.so to provide /usr/lib/aarch64-linux-gnu/libblas.so (libblas.so-aarch64-linux-gnu) in auto mode 240s Setting up dctrl-tools (2.24-3build2) ... 240s Setting up libitm1:arm64 (14-20240303-1ubuntu1) ... 240s Setting up cpp-13-aarch64-linux-gnu (13.2.0-17ubuntu2) ... 240s Setting up pkgconf:arm64 (1.8.1-2) ... 240s Setting up cpp-aarch64-linux-gnu (4:13.2.0-7ubuntu1) ... 240s Setting up liblapack-dev:arm64 (3.12.0-3) ... 240s update-alternatives: using /usr/lib/aarch64-linux-gnu/lapack/liblapack.so to provide /usr/lib/aarch64-linux-gnu/liblapack.so (liblapack.so-aarch64-linux-gnu) in auto mode 240s Setting up pkg-config:arm64 (1.8.1-2) ... 240s Setting up libgcc-13-dev:arm64 (13.2.0-17ubuntu2) ... 240s Setting up libc6-dev:arm64 (2.39-0ubuntu2) ... 240s Setting up libgfortran-13-dev:arm64 (13.2.0-17ubuntu2) ... 240s Setting up libicu-dev:arm64 (74.2-1ubuntu1) ... 240s Setting up libstdc++-13-dev:arm64 (13.2.0-17ubuntu2) ... 240s Setting up libbz2-dev:arm64 (1.0.8-5ubuntu1) ... 240s Setting up libjpeg-turbo8-dev:arm64 (2.1.5-2ubuntu1) ... 240s Setting up libncurses-dev:arm64 (6.4+20240113-1ubuntu1) ... 240s Setting up libpcre2-dev:arm64 (10.42-4ubuntu1) ... 240s Setting up cpp-13 (13.2.0-17ubuntu2) ... 240s Setting up gcc-13-aarch64-linux-gnu (13.2.0-17ubuntu2) ... 240s Setting up libreadline-dev:arm64 (8.2-3.1) ... 240s Setting up gcc-13 (13.2.0-17ubuntu2) ... 240s Setting up zlib1g-dev:arm64 (1:1.3.dfsg-3ubuntu1) ... 240s Setting up cpp (4:13.2.0-7ubuntu1) ... 240s Setting up libjpeg8-dev:arm64 (8c-2ubuntu11) ... 240s Setting up g++-13-aarch64-linux-gnu (13.2.0-17ubuntu2) ... 240s Setting up gcc-aarch64-linux-gnu (4:13.2.0-7ubuntu1) ... 240s Setting up g++-13 (13.2.0-17ubuntu2) ... 240s Setting up libpng-dev:arm64 (1.6.43-3) ... 240s Setting up libjpeg-dev:arm64 (8c-2ubuntu11) ... 240s Setting up gfortran-13-aarch64-linux-gnu (13.2.0-17ubuntu2) ... 240s Setting up gcc (4:13.2.0-7ubuntu1) ... 240s Setting up gfortran-13 (13.2.0-17ubuntu2) ... 240s Setting up g++-aarch64-linux-gnu (4:13.2.0-7ubuntu1) ... 240s Setting up gfortran-aarch64-linux-gnu (4:13.2.0-7ubuntu1) ... 240s Setting up gfortran (4:13.2.0-7ubuntu1) ... 240s update-alternatives: using /usr/bin/gfortran to provide /usr/bin/f95 (f95) in auto mode 240s update-alternatives: warning: skip creation of /usr/share/man/man1/f95.1.gz because associated file /usr/share/man/man1/gfortran.1.gz (of link group f95) doesn't exist 240s update-alternatives: using /usr/bin/gfortran to provide /usr/bin/f77 (f77) in auto mode 240s update-alternatives: warning: skip creation of /usr/share/man/man1/f77.1.gz because associated file /usr/share/man/man1/gfortran.1.gz (of link group f77) doesn't exist 240s Setting up g++ (4:13.2.0-7ubuntu1) ... 240s update-alternatives: using /usr/bin/g++ to provide /usr/bin/c++ (c++) in auto mode 240s Setting up build-essential (12.10ubuntu1) ... 240s Setting up r-base-dev (4.3.3-2build1) ... 240s Setting up pkg-r-autopkgtest (20231212ubuntu1) ... 240s Setting up autopkgtest-satdep (0) ... 240s Processing triggers for man-db (2.12.0-3) ... 241s Processing triggers for install-info (7.1-3) ... 241s Processing triggers for libc-bin (2.39-0ubuntu2) ... 245s (Reading database ... 80781 files and directories currently installed.) 245s Removing autopkgtest-satdep (0) ... 245s autopkgtest [20:03:13]: test pkg-r-autopkgtest: /usr/share/dh-r/pkg-r-autopkgtest 245s autopkgtest [20:03:13]: test pkg-r-autopkgtest: [----------------------- 246s Test: Try to load the R library rrcov 246s 246s R version 4.3.3 (2024-02-29) -- "Angel Food Cake" 246s Copyright (C) 2024 The R Foundation for Statistical Computing 246s Platform: aarch64-unknown-linux-gnu (64-bit) 246s 246s R is free software and comes with ABSOLUTELY NO WARRANTY. 246s You are welcome to redistribute it under certain conditions. 246s Type 'license()' or 'licence()' for distribution details. 246s 246s R is a collaborative project with many contributors. 246s Type 'contributors()' for more information and 246s 'citation()' on how to cite R or R packages in publications. 246s 246s Type 'demo()' for some demos, 'help()' for on-line help, or 246s 'help.start()' for an HTML browser interface to help. 246s Type 'q()' to quit R. 246s 246s > library('rrcov') 246s Loading required package: robustbase 246s Scalable Robust Estimators with High Breakdown Point (version 1.7-5) 246s 246s > 246s > 246s Other tests are currently unsupported! 246s They will be progressively added. 247s autopkgtest [20:03:15]: test pkg-r-autopkgtest: -----------------------] 247s autopkgtest [20:03:15]: test pkg-r-autopkgtest: - - - - - - - - - - results - - - - - - - - - - 247s pkg-r-autopkgtest PASS 247s autopkgtest [20:03:15]: @@@@@@@@@@@@@@@@@@@@ summary 247s run-unit-test PASS 247s pkg-r-autopkgtest PASS 252s Creating nova instance adt-noble-arm64-r-cran-rrcov-20240316-195908-juju-7f2275-prod-proposed-migration-environment-2 from image adt/ubuntu-noble-arm64-server-20240314.img (UUID 7faf5f09-d335-4346-a441-4eab2f9c04fe)...