0s autopkgtest [23:09:31]: starting date and time: 2026-02-09 23:09:31+0000 0s autopkgtest [23:09:31]: git checkout: 4b346b80 nova: make wait_reboot return success even when a no-op 0s autopkgtest [23:09:31]: host juju-7f2275-prod-proposed-migration-environment-2; command line: /home/ubuntu/autopkgtest/runner/autopkgtest --output-dir /tmp/autopkgtest-work.3pk1nxan/out --timeout-copy=6000 --needs-internet=try --setup-commands /home/ubuntu/autopkgtest-cloud/worker-config-production/setup-canonical.sh --apt-pocket=proposed=src:lattice --apt-upgrade r-cran-rrcov --timeout-short=300 --timeout-copy=20000 --timeout-build=20000 --env=ADT_TEST_TRIGGERS=lattice/0.22-9-1 -- ssh -s /home/ubuntu/autopkgtest/ssh-setup/nova -- --flavor autopkgtest-cpu2-ram4-disk20-arm64 --security-groups autopkgtest-juju-7f2275-prod-proposed-migration-environment-2@sto01-arm64-15.secgroup --name adt-resolute-arm64-r-cran-rrcov-20260209-230930-juju-7f2275-prod-proposed-migration-environment-2-a2bfbf0a-025e-4e46-9c0b-6fa530caf41c --image adt/ubuntu-resolute-arm64-server --keyname testbed-juju-7f2275-prod-proposed-migration-environment-2 --net-id=net_prod-autopkgtest-workers-arm64 -e TERM=linux --mirror=http://ftpmaster.internal/ubuntu/ 4s Creating nova instance adt-resolute-arm64-r-cran-rrcov-20260209-230930-juju-7f2275-prod-proposed-migration-environment-2-a2bfbf0a-025e-4e46-9c0b-6fa530caf41c from image adt/ubuntu-resolute-arm64-server-20260209.img (UUID 793037ca-75af-461b-82de-f8081300b2e3)... 108s autopkgtest [23:11:19]: testbed dpkg architecture: arm64 108s autopkgtest [23:11:19]: testbed apt version: 3.1.15 108s autopkgtest [23:11:19]: @@@@@@@@@@@@@@@@@@@@ test bed setup 109s autopkgtest [23:11:20]: testbed release detected to be: None 109s autopkgtest [23:11:20]: updating testbed package index (apt update) 110s Get:1 http://ftpmaster.internal/ubuntu resolute-proposed InRelease [124 kB] 110s Hit:2 http://ftpmaster.internal/ubuntu resolute InRelease 110s Hit:3 http://ftpmaster.internal/ubuntu resolute-updates InRelease 110s Hit:4 http://ftpmaster.internal/ubuntu resolute-security InRelease 110s Get:5 http://ftpmaster.internal/ubuntu resolute-proposed/universe Sources [1645 kB] 112s Get:6 http://ftpmaster.internal/ubuntu resolute-proposed/main Sources [176 kB] 112s Get:7 http://ftpmaster.internal/ubuntu resolute-proposed/multiverse Sources [29.4 kB] 112s Get:8 http://ftpmaster.internal/ubuntu resolute-proposed/main arm64 Packages [246 kB] 112s Get:9 http://ftpmaster.internal/ubuntu resolute-proposed/main arm64 c-n-f Metadata [6216 B] 112s Get:10 http://ftpmaster.internal/ubuntu resolute-proposed/restricted arm64 c-n-f Metadata [304 B] 112s Get:11 http://ftpmaster.internal/ubuntu resolute-proposed/universe arm64 Packages [1580 kB] 114s Get:12 http://ftpmaster.internal/ubuntu resolute-proposed/universe arm64 c-n-f Metadata [32.0 kB] 114s Get:13 http://ftpmaster.internal/ubuntu resolute-proposed/multiverse arm64 Packages [21.7 kB] 114s Get:14 http://ftpmaster.internal/ubuntu resolute-proposed/multiverse arm64 c-n-f Metadata [688 B] 116s Fetched 3862 kB in 5s (805 kB/s) 117s Reading package lists... 117s Hit:1 http://ftpmaster.internal/ubuntu resolute-proposed InRelease 117s Hit:2 http://ftpmaster.internal/ubuntu resolute InRelease 117s Hit:3 http://ftpmaster.internal/ubuntu resolute-updates InRelease 117s Hit:4 http://ftpmaster.internal/ubuntu resolute-security InRelease 118s Reading package lists... 118s Reading package lists... 119s Building dependency tree... 119s Reading state information... 119s Calculating upgrade... 119s The following packages will be upgraded: 119s cryptsetup-bin dracut-install iproute2 iptables libcryptsetup12 libip4tc2 119s libip6tc2 libxtables12 wget 119s 9 upgraded, 0 newly installed, 0 to remove and 0 not upgraded. 119s Need to get 2534 kB of archives. 119s After this operation, 18.4 kB of additional disk space will be used. 119s Get:1 http://ftpmaster.internal/ubuntu resolute/main arm64 iptables arm64 1.8.11-2ubuntu3 [386 kB] 119s Get:2 http://ftpmaster.internal/ubuntu resolute/main arm64 libip4tc2 arm64 1.8.11-2ubuntu3 [24.3 kB] 119s Get:3 http://ftpmaster.internal/ubuntu resolute/main arm64 libip6tc2 arm64 1.8.11-2ubuntu3 [24.7 kB] 119s Get:4 http://ftpmaster.internal/ubuntu resolute/main arm64 libxtables12 arm64 1.8.11-2ubuntu3 [36.7 kB] 120s Get:5 http://ftpmaster.internal/ubuntu resolute/main arm64 iproute2 arm64 6.18.0-1ubuntu1 [1171 kB] 121s Get:6 http://ftpmaster.internal/ubuntu resolute/main arm64 libcryptsetup12 arm64 2:2.8.0-1ubuntu3 [274 kB] 121s Get:7 http://ftpmaster.internal/ubuntu resolute/main arm64 wget arm64 1.25.0-2ubuntu4 [344 kB] 121s Get:8 http://ftpmaster.internal/ubuntu resolute/main arm64 cryptsetup-bin arm64 2:2.8.0-1ubuntu3 [227 kB] 121s Get:9 http://ftpmaster.internal/ubuntu resolute/main arm64 dracut-install arm64 109-11ubuntu1 [45.3 kB] 121s dpkg-preconfigure: unable to re-open stdin: No such file or directory 121s Fetched 2534 kB in 2s (1435 kB/s) 122s (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 ... 136597 files and directories currently installed.) 122s Preparing to unpack .../0-iptables_1.8.11-2ubuntu3_arm64.deb ... 122s Unpacking iptables (1.8.11-2ubuntu3) over (1.8.11-2ubuntu2) ... 122s Preparing to unpack .../1-libip4tc2_1.8.11-2ubuntu3_arm64.deb ... 122s Unpacking libip4tc2:arm64 (1.8.11-2ubuntu3) over (1.8.11-2ubuntu2) ... 122s Preparing to unpack .../2-libip6tc2_1.8.11-2ubuntu3_arm64.deb ... 122s Unpacking libip6tc2:arm64 (1.8.11-2ubuntu3) over (1.8.11-2ubuntu2) ... 122s Preparing to unpack .../3-libxtables12_1.8.11-2ubuntu3_arm64.deb ... 122s Unpacking libxtables12:arm64 (1.8.11-2ubuntu3) over (1.8.11-2ubuntu2) ... 122s Preparing to unpack .../4-iproute2_6.18.0-1ubuntu1_arm64.deb ... 122s Unpacking iproute2 (6.18.0-1ubuntu1) over (6.16.0-1ubuntu3) ... 122s Preparing to unpack .../5-libcryptsetup12_2%3a2.8.0-1ubuntu3_arm64.deb ... 122s Unpacking libcryptsetup12:arm64 (2:2.8.0-1ubuntu3) over (2:2.8.0-1ubuntu2) ... 122s Preparing to unpack .../6-wget_1.25.0-2ubuntu4_arm64.deb ... 122s Unpacking wget (1.25.0-2ubuntu4) over (1.25.0-2ubuntu3) ... 123s Preparing to unpack .../7-cryptsetup-bin_2%3a2.8.0-1ubuntu3_arm64.deb ... 123s Unpacking cryptsetup-bin (2:2.8.0-1ubuntu3) over (2:2.8.0-1ubuntu2) ... 123s Preparing to unpack .../8-dracut-install_109-11ubuntu1_arm64.deb ... 123s Unpacking dracut-install (109-11ubuntu1) over (109-9ubuntu1) ... 123s Setting up libip4tc2:arm64 (1.8.11-2ubuntu3) ... 123s Setting up wget (1.25.0-2ubuntu4) ... 123s Setting up libip6tc2:arm64 (1.8.11-2ubuntu3) ... 123s Setting up libxtables12:arm64 (1.8.11-2ubuntu3) ... 123s Setting up dracut-install (109-11ubuntu1) ... 123s Setting up libcryptsetup12:arm64 (2:2.8.0-1ubuntu3) ... 123s Setting up cryptsetup-bin (2:2.8.0-1ubuntu3) ... 123s Setting up iptables (1.8.11-2ubuntu3) ... 123s Setting up iproute2 (6.18.0-1ubuntu1) ... 123s Processing triggers for man-db (2.13.1-1build1) ... 124s Processing triggers for install-info (7.2-5) ... 124s Processing triggers for libc-bin (2.42-2ubuntu4) ... 124s autopkgtest [23:11:35]: upgrading testbed (apt dist-upgrade and autopurge) 125s Reading package lists... 125s Building dependency tree... 125s Reading state information... 125s Calculating upgrade... 125s 0 upgraded, 0 newly installed, 0 to remove and 0 not upgraded. 126s Reading package lists... 126s Building dependency tree... 126s Reading state information... 126s Solving dependencies... 126s 0 upgraded, 0 newly installed, 0 to remove and 0 not upgraded. 129s autopkgtest [23:11:40]: testbed running kernel: Linux 6.19.0-3-generic #3-Ubuntu SMP PREEMPT_DYNAMIC Fri Jan 23 19:46:27 UTC 2026 129s autopkgtest [23:11:40]: @@@@@@@@@@@@@@@@@@@@ apt-source r-cran-rrcov 134s Get:1 http://ftpmaster.internal/ubuntu resolute/universe r-cran-rrcov 1.7-6-1 (dsc) [2146 B] 134s Get:2 http://ftpmaster.internal/ubuntu resolute/universe r-cran-rrcov 1.7-6-1 (tar) [1542 kB] 134s Get:3 http://ftpmaster.internal/ubuntu resolute/universe r-cran-rrcov 1.7-6-1 (diff) [3160 B] 134s gpgv: Signature made Fri Sep 6 03:10:50 2024 UTC 134s gpgv: using RSA key 73471499CC60ED9EEE805946C5BD6C8F2295D502 134s gpgv: issuer "plessy@debian.org" 134s gpgv: Can't check signature: No public key 134s dpkg-source: warning: cannot verify inline signature for ./r-cran-rrcov_1.7-6-1.dsc: no acceptable signature found 134s autopkgtest [23:11:45]: testing package r-cran-rrcov version 1.7-6-1 134s autopkgtest [23:11:45]: build not needed 137s autopkgtest [23:11:48]: test run-unit-test: preparing testbed 137s Reading package lists... 137s Building dependency tree... 137s Reading state information... 137s Solving dependencies... 138s The following NEW packages will be installed: 138s fontconfig fontconfig-config fonts-dejavu-core fonts-dejavu-mono libblas3 138s libcairo2 libdatrie1 libdeflate0 libfontconfig1 libgfortran5 libgomp1 138s libgraphite2-3 libharfbuzz0b libice6 libjbig0 libjpeg-turbo8 libjpeg8 138s liblapack3 liblerc4 libpango-1.0-0 libpangocairo-1.0-0 libpangoft2-1.0-0 138s libpaper-utils libpaper2 libpixman-1-0 libsharpyuv0 libsm6 libtcl8.6 138s libthai-data libthai0 libtiff6 libtk8.6 libwebp7 libxcb-render0 libxcb-shm0 138s libxft2 libxrender1 libxss1 libxt6t64 r-base-core r-cran-deoptimr 138s r-cran-lattice r-cran-mass r-cran-mvtnorm r-cran-pcapp r-cran-robustbase 138s r-cran-rrcov unzip x11-common xdg-utils zip 138s 0 upgraded, 51 newly installed, 0 to remove and 0 not upgraded. 138s Need to get 48.0 MB of archives. 138s After this operation, 91.8 MB of additional disk space will be used. 138s Get:1 http://ftpmaster.internal/ubuntu resolute/main arm64 fonts-dejavu-mono all 2.37-8build1 [502 kB] 138s Get:2 http://ftpmaster.internal/ubuntu resolute/main arm64 fonts-dejavu-core all 2.37-8build1 [834 kB] 139s Get:3 http://ftpmaster.internal/ubuntu resolute/main arm64 fontconfig-config arm64 2.17.1-3ubuntu1 [38.5 kB] 139s Get:4 http://ftpmaster.internal/ubuntu resolute/main arm64 libfontconfig1 arm64 2.17.1-3ubuntu1 [144 kB] 139s Get:5 http://ftpmaster.internal/ubuntu resolute/main arm64 fontconfig arm64 2.17.1-3ubuntu1 [181 kB] 139s Get:6 http://ftpmaster.internal/ubuntu resolute/main arm64 libblas3 arm64 3.12.1-7ubuntu1 [181 kB] 139s Get:7 http://ftpmaster.internal/ubuntu resolute/main arm64 libpixman-1-0 arm64 0.46.4-1 [204 kB] 139s Get:8 http://ftpmaster.internal/ubuntu resolute/main arm64 libxcb-render0 arm64 1.17.0-2ubuntu1 [16.4 kB] 139s Get:9 http://ftpmaster.internal/ubuntu resolute/main arm64 libxcb-shm0 arm64 1.17.0-2ubuntu1 [5938 B] 139s Get:10 http://ftpmaster.internal/ubuntu resolute/main arm64 libxrender1 arm64 1:0.9.12-1 [19.5 kB] 139s Get:11 http://ftpmaster.internal/ubuntu resolute/main arm64 libcairo2 arm64 1.18.4-3 [556 kB] 140s Get:12 http://ftpmaster.internal/ubuntu resolute/main arm64 libdatrie1 arm64 0.2.14-1 [19.6 kB] 140s Get:13 http://ftpmaster.internal/ubuntu resolute/main arm64 libdeflate0 arm64 1.23-2build1 [46.8 kB] 140s Get:14 http://ftpmaster.internal/ubuntu resolute/main arm64 libgfortran5 arm64 15.2.0-12ubuntu1 [451 kB] 140s Get:15 http://ftpmaster.internal/ubuntu resolute/main arm64 libgomp1 arm64 15.2.0-12ubuntu1 [147 kB] 140s Get:16 http://ftpmaster.internal/ubuntu resolute/main arm64 libgraphite2-3 arm64 1.3.14-11ubuntu1 [72.1 kB] 140s Get:17 http://ftpmaster.internal/ubuntu resolute/main arm64 libharfbuzz0b arm64 12.3.2-1 [510 kB] 140s Get:18 http://ftpmaster.internal/ubuntu resolute/main arm64 x11-common all 1:7.7+24ubuntu1 [22.4 kB] 140s Get:19 http://ftpmaster.internal/ubuntu resolute/main arm64 libice6 arm64 2:1.1.1-1build1 [43.0 kB] 140s Get:20 http://ftpmaster.internal/ubuntu resolute/main arm64 libjpeg-turbo8 arm64 2.1.5-4ubuntu3 [161 kB] 140s Get:21 http://ftpmaster.internal/ubuntu resolute/main arm64 libjpeg8 arm64 8c-2ubuntu11 [2148 B] 140s Get:22 http://ftpmaster.internal/ubuntu resolute/main arm64 liblapack3 arm64 3.12.1-7ubuntu1 [2299 kB] 143s Get:23 http://ftpmaster.internal/ubuntu resolute/main arm64 liblerc4 arm64 4.0.0+ds-5ubuntu2 [174 kB] 143s Get:24 http://ftpmaster.internal/ubuntu resolute/main arm64 libthai-data all 0.1.30-1 [155 kB] 143s Get:25 http://ftpmaster.internal/ubuntu resolute/main arm64 libthai0 arm64 0.1.30-1 [18.3 kB] 143s Get:26 http://ftpmaster.internal/ubuntu resolute/main arm64 libpango-1.0-0 arm64 1.57.0-1 [238 kB] 143s Get:27 http://ftpmaster.internal/ubuntu resolute/main arm64 libpangoft2-1.0-0 arm64 1.57.0-1 [51.5 kB] 143s Get:28 http://ftpmaster.internal/ubuntu resolute/main arm64 libpangocairo-1.0-0 arm64 1.57.0-1 [27.9 kB] 143s Get:29 http://ftpmaster.internal/ubuntu resolute/main arm64 libpaper2 arm64 2.2.5-0.3build1 [17.3 kB] 143s Get:30 http://ftpmaster.internal/ubuntu resolute/main arm64 libpaper-utils arm64 2.2.5-0.3build1 [15.4 kB] 143s Get:31 http://ftpmaster.internal/ubuntu resolute/main arm64 libsharpyuv0 arm64 1.5.0-0.1build1 [16.7 kB] 143s Get:32 http://ftpmaster.internal/ubuntu resolute/main arm64 libsm6 arm64 2:1.2.6-1build1 [16.8 kB] 143s Get:33 http://ftpmaster.internal/ubuntu resolute/main arm64 libtcl8.6 arm64 8.6.17+dfsg-1build1 [983 kB] 144s Get:34 http://ftpmaster.internal/ubuntu resolute/main arm64 libjbig0 arm64 2.1-6.1ubuntu3 [29.2 kB] 144s Get:35 http://ftpmaster.internal/ubuntu resolute/main arm64 libwebp7 arm64 1.5.0-0.1build1 [205 kB] 144s Get:36 http://ftpmaster.internal/ubuntu resolute/main arm64 libtiff6 arm64 4.7.0-3ubuntu3 [196 kB] 144s Get:37 http://ftpmaster.internal/ubuntu resolute/main arm64 libxft2 arm64 2.3.6-1build2 [43.2 kB] 144s Get:38 http://ftpmaster.internal/ubuntu resolute/main arm64 libxss1 arm64 1:1.2.3-1build4 [7102 B] 144s Get:39 http://ftpmaster.internal/ubuntu resolute/main arm64 libtk8.6 arm64 8.6.17-1 [811 kB] 145s Get:40 http://ftpmaster.internal/ubuntu resolute/main arm64 libxt6t64 arm64 1:1.2.1-1.3 [168 kB] 145s Get:41 http://ftpmaster.internal/ubuntu resolute/main arm64 zip arm64 3.0-15ubuntu3 [170 kB] 145s Get:42 http://ftpmaster.internal/ubuntu resolute/main arm64 unzip arm64 6.0-29ubuntu1 [176 kB] 145s Get:43 http://ftpmaster.internal/ubuntu resolute/main arm64 xdg-utils all 1.2.1-2ubuntu2 [66.1 kB] 145s Get:44 http://ftpmaster.internal/ubuntu resolute/universe arm64 r-base-core arm64 4.5.2-1ubuntu2 [28.6 MB] 184s Get:45 http://ftpmaster.internal/ubuntu resolute/universe arm64 r-cran-deoptimr all 1.1-4-1 [76.7 kB] 184s Get:46 http://ftpmaster.internal/ubuntu resolute-proposed/universe arm64 r-cran-lattice arm64 0.22-9-1 [1399 kB] 186s Get:47 http://ftpmaster.internal/ubuntu resolute/universe arm64 r-cran-mass arm64 7.3-65-1 [1109 kB] 188s Get:48 http://ftpmaster.internal/ubuntu resolute/universe arm64 r-cran-mvtnorm arm64 1.3-3-1build1 [919 kB] 189s Get:49 http://ftpmaster.internal/ubuntu resolute/universe arm64 r-cran-pcapp arm64 2.0-5-1 [366 kB] 190s Get:50 http://ftpmaster.internal/ubuntu resolute/universe arm64 r-cran-robustbase arm64 0.99-7-1 [3068 kB] 194s Get:51 http://ftpmaster.internal/ubuntu resolute/universe arm64 r-cran-rrcov arm64 1.7-6-1 [2406 kB] 197s Preconfiguring packages ... 197s Fetched 48.0 MB in 59s (813 kB/s) 197s Selecting previously unselected package fonts-dejavu-mono. 197s (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 ... 136600 files and directories currently installed.) 197s Preparing to unpack .../00-fonts-dejavu-mono_2.37-8build1_all.deb ... 197s Unpacking fonts-dejavu-mono (2.37-8build1) ... 197s Selecting previously unselected package fonts-dejavu-core. 197s Preparing to unpack .../01-fonts-dejavu-core_2.37-8build1_all.deb ... 197s Unpacking fonts-dejavu-core (2.37-8build1) ... 197s Selecting previously unselected package fontconfig-config. 197s Preparing to unpack .../02-fontconfig-config_2.17.1-3ubuntu1_arm64.deb ... 198s Unpacking fontconfig-config (2.17.1-3ubuntu1) ... 198s Selecting previously unselected package libfontconfig1:arm64. 198s Preparing to unpack .../03-libfontconfig1_2.17.1-3ubuntu1_arm64.deb ... 198s Unpacking libfontconfig1:arm64 (2.17.1-3ubuntu1) ... 198s Selecting previously unselected package fontconfig. 198s Preparing to unpack .../04-fontconfig_2.17.1-3ubuntu1_arm64.deb ... 198s Unpacking fontconfig (2.17.1-3ubuntu1) ... 198s Selecting previously unselected package libblas3:arm64. 198s Preparing to unpack .../05-libblas3_3.12.1-7ubuntu1_arm64.deb ... 198s Unpacking libblas3:arm64 (3.12.1-7ubuntu1) ... 198s Selecting previously unselected package libpixman-1-0:arm64. 198s Preparing to unpack .../06-libpixman-1-0_0.46.4-1_arm64.deb ... 198s Unpacking libpixman-1-0:arm64 (0.46.4-1) ... 198s Selecting previously unselected package libxcb-render0:arm64. 198s Preparing to unpack .../07-libxcb-render0_1.17.0-2ubuntu1_arm64.deb ... 198s Unpacking libxcb-render0:arm64 (1.17.0-2ubuntu1) ... 198s Selecting previously unselected package libxcb-shm0:arm64. 198s Preparing to unpack .../08-libxcb-shm0_1.17.0-2ubuntu1_arm64.deb ... 198s Unpacking libxcb-shm0:arm64 (1.17.0-2ubuntu1) ... 198s Selecting previously unselected package libxrender1:arm64. 198s Preparing to unpack .../09-libxrender1_1%3a0.9.12-1_arm64.deb ... 198s Unpacking libxrender1:arm64 (1:0.9.12-1) ... 198s Selecting previously unselected package libcairo2:arm64. 198s Preparing to unpack .../10-libcairo2_1.18.4-3_arm64.deb ... 198s Unpacking libcairo2:arm64 (1.18.4-3) ... 198s Selecting previously unselected package libdatrie1:arm64. 198s Preparing to unpack .../11-libdatrie1_0.2.14-1_arm64.deb ... 198s Unpacking libdatrie1:arm64 (0.2.14-1) ... 198s Selecting previously unselected package libdeflate0:arm64. 198s Preparing to unpack .../12-libdeflate0_1.23-2build1_arm64.deb ... 198s Unpacking libdeflate0:arm64 (1.23-2build1) ... 198s Selecting previously unselected package libgfortran5:arm64. 198s Preparing to unpack .../13-libgfortran5_15.2.0-12ubuntu1_arm64.deb ... 198s Unpacking libgfortran5:arm64 (15.2.0-12ubuntu1) ... 198s Selecting previously unselected package libgomp1:arm64. 198s Preparing to unpack .../14-libgomp1_15.2.0-12ubuntu1_arm64.deb ... 198s Unpacking libgomp1:arm64 (15.2.0-12ubuntu1) ... 198s Selecting previously unselected package libgraphite2-3:arm64. 198s Preparing to unpack .../15-libgraphite2-3_1.3.14-11ubuntu1_arm64.deb ... 198s Unpacking libgraphite2-3:arm64 (1.3.14-11ubuntu1) ... 198s Selecting previously unselected package libharfbuzz0b:arm64. 198s Preparing to unpack .../16-libharfbuzz0b_12.3.2-1_arm64.deb ... 198s Unpacking libharfbuzz0b:arm64 (12.3.2-1) ... 198s Selecting previously unselected package x11-common. 198s Preparing to unpack .../17-x11-common_1%3a7.7+24ubuntu1_all.deb ... 198s Unpacking x11-common (1:7.7+24ubuntu1) ... 198s Selecting previously unselected package libice6:arm64. 198s Preparing to unpack .../18-libice6_2%3a1.1.1-1build1_arm64.deb ... 198s Unpacking libice6:arm64 (2:1.1.1-1build1) ... 198s Selecting previously unselected package libjpeg-turbo8:arm64. 198s Preparing to unpack .../19-libjpeg-turbo8_2.1.5-4ubuntu3_arm64.deb ... 198s Unpacking libjpeg-turbo8:arm64 (2.1.5-4ubuntu3) ... 198s Selecting previously unselected package libjpeg8:arm64. 198s Preparing to unpack .../20-libjpeg8_8c-2ubuntu11_arm64.deb ... 198s Unpacking libjpeg8:arm64 (8c-2ubuntu11) ... 198s Selecting previously unselected package liblapack3:arm64. 198s Preparing to unpack .../21-liblapack3_3.12.1-7ubuntu1_arm64.deb ... 198s Unpacking liblapack3:arm64 (3.12.1-7ubuntu1) ... 198s Selecting previously unselected package liblerc4:arm64. 198s Preparing to unpack .../22-liblerc4_4.0.0+ds-5ubuntu2_arm64.deb ... 198s Unpacking liblerc4:arm64 (4.0.0+ds-5ubuntu2) ... 199s Selecting previously unselected package libthai-data. 199s Preparing to unpack .../23-libthai-data_0.1.30-1_all.deb ... 199s Unpacking libthai-data (0.1.30-1) ... 199s Selecting previously unselected package libthai0:arm64. 199s Preparing to unpack .../24-libthai0_0.1.30-1_arm64.deb ... 199s Unpacking libthai0:arm64 (0.1.30-1) ... 199s Selecting previously unselected package libpango-1.0-0:arm64. 199s Preparing to unpack .../25-libpango-1.0-0_1.57.0-1_arm64.deb ... 199s Unpacking libpango-1.0-0:arm64 (1.57.0-1) ... 199s Selecting previously unselected package libpangoft2-1.0-0:arm64. 199s Preparing to unpack .../26-libpangoft2-1.0-0_1.57.0-1_arm64.deb ... 199s Unpacking libpangoft2-1.0-0:arm64 (1.57.0-1) ... 199s Selecting previously unselected package libpangocairo-1.0-0:arm64. 199s Preparing to unpack .../27-libpangocairo-1.0-0_1.57.0-1_arm64.deb ... 199s Unpacking libpangocairo-1.0-0:arm64 (1.57.0-1) ... 199s Selecting previously unselected package libpaper2:arm64. 199s Preparing to unpack .../28-libpaper2_2.2.5-0.3build1_arm64.deb ... 199s Unpacking libpaper2:arm64 (2.2.5-0.3build1) ... 199s 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Setting up r-cran-pcapp (2.0-5-1) ... 203s Setting up r-cran-rrcov (1.7-6-1) ... 203s Processing triggers for libc-bin (2.42-2ubuntu4) ... 203s Processing triggers for man-db (2.13.1-1build1) ... 204s Processing triggers for install-info (7.2-5) ... 205s autopkgtest [23:12:56]: test run-unit-test: [----------------------- 205s BEGIN TEST thubert.R 205s 205s R version 4.5.2 (2025-10-31) -- "[Not] Part in a Rumble" 205s Copyright (C) 2025 The R Foundation for Statistical Computing 205s Platform: aarch64-unknown-linux-gnu 205s 205s R is free software and comes with ABSOLUTELY NO WARRANTY. 205s You are welcome to redistribute it under certain conditions. 205s Type 'license()' or 'licence()' for distribution details. 205s 205s R is a collaborative project with many contributors. 205s Type 'contributors()' for more information and 205s 'citation()' on how to cite R or R packages in publications. 205s 205s Type 'demo()' for some demos, 'help()' for on-line help, or 205s 'help.start()' for an HTML browser interface to help. 205s Type 'q()' to quit R. 205s 205s > dodata <- function(nrep=1, time=FALSE, short=FALSE, full=TRUE, 205s + method=c("hubert", "hubert.mcd", "locantore", "cov", "classic", 205s + "grid", "proj")) 205s + { 205s + ## Test the PcaXxx() functions on the literature datasets: 205s + ## 205s + ## Call PcaHubert() and the other functions for all regression 205s + ## data sets available in robustbase/rrcov and print: 205s + ## - execution time (if time == TRUE) 205s + ## - loadings 205s + ## - eigenvalues 205s + ## - scores 205s + ## 205s + 205s + dopca <- function(x, xname, nrep=1){ 205s + 205s + n <- dim(x)[1] 205s + p <- dim(x)[2] 205s + if(method == "hubert.mcd") 205s + pca <- PcaHubert(x, k=p) 205s + else if(method == "hubert") 205s + pca <- PcaHubert(x, mcd=FALSE) 205s + else if(method == "locantore") 205s + pca <- PcaLocantore(x) 205s + else if(method == "cov") 205s + pca <- PcaCov(x) 205s + else if(method == "classic") 205s + pca <- PcaClassic(x) 205s + else if(method == "grid") 205s + pca <- PcaGrid(x) 205s + else if(method == "proj") 205s + pca <- PcaProj(x) 205s + else 205s + stop("Undefined PCA method: ", method) 205s + 205s + 205s + e1 <- getEigenvalues(pca)[1] 205s + e2 <- getEigenvalues(pca)[2] 205s + k <- pca@k 205s + 205s + if(time){ 205s + xtime <- system.time(dorep(x, nrep, method))[1]/nrep 205s + xres <- sprintf("%3d %3d %3d %12.6f %12.6f %10.3f\n", dim(x)[1], dim(x)[2], k, e1, e2, xtime) 205s + } 205s + else{ 205s + xres <- sprintf("%3d %3d %3d %12.6f %12.6f\n", dim(x)[1], dim(x)[2], k, e1, e2) 205s + } 205s + lpad<-lname-nchar(xname) 205s + cat(pad.right(xname, lpad), xres) 205s + 205s + if(!short){ 205s + cat("Scores: \n") 205s + print(getScores(pca)) 205s + 205s + if(full){ 205s + cat("-------------\n") 205s + show(pca) 205s + } 205s + cat("----------------------------------------------------------\n") 205s + } 205s + } 205s + 205s + stopifnot(length(nrep) == 1, nrep >= 1) 205s + method <- match.arg(method) 205s + 205s + options(digits = 5) 205s + set.seed(101) # <<-- sub-sampling algorithm now based on R's RNG and seed 205s + 205s + lname <- 20 205s + 205s + ## VT::15.09.2013 - this will render the output independent 205s + ## from the version of the package 205s + suppressPackageStartupMessages(library(rrcov)) 205s + 205s + data(Animals, package = "MASS") 205s + brain <- Animals[c(1:24, 26:25, 27:28),] 205s + 205s + tmp <- sys.call() 205s + cat("\nCall: ", deparse(substitute(tmp)),"\n") 205s + 205s + cat("Data Set n p k e1 e2\n") 205s + cat("==========================================================\n") 205s + dopca(heart[, 1:2], data(heart), nrep) 205s + dopca(starsCYG, data(starsCYG), nrep) 205s + dopca(data.matrix(subset(phosphor, select = -plant)), data(phosphor), nrep) 205s + dopca(stack.x, data(stackloss), nrep) 205s + ## dopca(data.matrix(subset(coleman, select = -Y)), data(coleman), nrep) # differences between the architectures 205s + dopca(data.matrix(subset(salinity, select = -Y)), data(salinity), nrep) 205s + ## dopca(data.matrix(subset(wood, select = -y)), data(wood), nrep) # differences between the architectures 205s + dopca(data.matrix(subset(hbk, select = -Y)),data(hbk), nrep) 205s + 205s + ## dopca(brain, "Animals", nrep) 205s + dopca(milk, data(milk), nrep) 205s + dopca(bushfire, data(bushfire), nrep) 205s + cat("==========================================================\n") 205s + } 205s > 205s > dogen <- function(nrep=1, eps=0.49, method=c("hubert", "hubert.mcd", "locantore", "cov")){ 205s + 205s + dopca <- function(x, nrep=1){ 205s + gc() 205s + xtime <- system.time(dorep(x, nrep, method))[1]/nrep 205s + cat(sprintf("%6d %3d %10.2f\n", dim(x)[1], dim(x)[2], xtime)) 205s + xtime 205s + } 205s + 205s + set.seed(1234) 205s + 205s + ## VT::15.09.2013 - this will render the output independent 205s + ## from the version of the package 205s + suppressPackageStartupMessages(library(rrcov)) 205s + library(MASS) 205s + 205s + method <- match.arg(method) 205s + 205s + ap <- c(2, 5, 10, 20, 30) 205s + an <- c(100, 500, 1000, 10000, 50000) 205s + 205s + tottime <- 0 205s + cat(" n p Time\n") 205s + cat("=====================\n") 205s + for(i in 1:length(an)) { 205s + for(j in 1:length(ap)) { 205s + n <- an[i] 205s + p <- ap[j] 205s + if(5*p <= n){ 205s + xx <- gendata(n, p, eps) 205s + X <- xx$X 205s + ## print(dimnames(X)) 205s + tottime <- tottime + dopca(X, nrep) 205s + } 205s + } 205s + } 205s + 205s + cat("=====================\n") 205s + cat("Total time: ", tottime*nrep, "\n") 205s + } 205s > 205s > dorep <- function(x, nrep=1, method=c("hubert", "hubert.mcd", "locantore", "cov")){ 205s + 205s + method <- match.arg(method) 205s + for(i in 1:nrep) 205s + if(method == "hubert.mcd") 205s + PcaHubert(x) 205s + else if(method == "hubert") 205s + PcaHubert(x, mcd=FALSE) 205s + else if(method == "locantore") 205s + PcaLocantore(x) 205s + else if(method == "cov") 205s + PcaCov(x) 205s + else 205s + stop("Undefined PCA method: ", method) 205s + } 205s > 205s > #### gendata() #### 205s > # Generates a location contaminated multivariate 205s > # normal sample of n observations in p dimensions 205s > # (1-eps)*Np(0,Ip) + eps*Np(m,Ip) 205s > # where 205s > # m = (b,b,...,b) 205s > # Defaults: eps=0 and b=10 205s > # 205s > gendata <- function(n,p,eps=0,b=10){ 205s + 205s + if(missing(n) || missing(p)) 205s + stop("Please specify (n,p)") 205s + if(eps < 0 || eps >= 0.5) 205s + stop(message="eps must be in [0,0.5)") 205s + X <- mvrnorm(n,rep(0,p),diag(1,nrow=p,ncol=p)) 205s + nbad <- as.integer(eps * n) 205s + xind <- vector("numeric") 205s + if(nbad > 0){ 205s + Xbad <- mvrnorm(nbad,rep(b,p),diag(1,nrow=p,ncol=p)) 205s + xind <- sample(n,nbad) 205s + X[xind,] <- Xbad 205s + } 205s + list(X=X, xind=xind) 205s + } 205s > 205s > pad.right <- function(z, pads) 205s + { 205s + ### Pads spaces to right of text 205s + padding <- paste(rep(" ", pads), collapse = "") 205s + paste(z, padding, sep = "") 205s + } 205s > 205s > whatis <- function(x){ 205s + if(is.data.frame(x)) 205s + cat("Type: data.frame\n") 205s + else if(is.matrix(x)) 205s + cat("Type: matrix\n") 205s + else if(is.vector(x)) 205s + cat("Type: vector\n") 205s + else 205s + cat("Type: don't know\n") 205s + } 205s > 205s > ################################################################# 205s > ## VT::27.08.2010 205s > ## bug report from Stephen Milborrow 205s > ## 205s > test.case.1 <- function() 205s + { 205s + X <- matrix(c( 205s + -0.79984, -1.00103, 0.899794, 0.00000, 205s + 0.34279, 0.52832, -1.303783, -1.17670, 205s + -0.79984, -1.00103, 0.899794, 0.00000, 205s + 0.34279, 0.52832, -1.303783, -1.17670, 205s + 0.34279, 0.52832, -1.303783, -1.17670, 205s + 1.48542, 0.66735, 0.716162, 1.17670, 205s + -0.79984, -1.00103, 0.899794, 0.00000, 205s + 1.69317, 1.91864, -0.018363, 1.76505, 205s + -1.00759, -0.16684, -0.385626, 0.58835, 205s + -0.79984, -1.00103, 0.899794, 0.00000), ncol=4, byrow=TRUE) 205s + 205s + cc1 <- PcaHubert(X, k=3) 205s + 205s + cc2 <- PcaLocantore(X, k=3) 205s + cc3 <- PcaCov(X, k=3, cov.control=CovControlSest()) 205s + 205s + cc4 <- PcaProj(X, k=2) # with k=3 will produce warnings in .distances - too small eignevalues 205s + cc5 <- PcaGrid(X, k=2) # dito 205s + 205s + list(cc1, cc2, cc3, cc4, cc5) 205s + } 205s > 205s > ################################################################# 205s > ## VT::05.08.2016 205s > ## bug report from Matthieu Lesnoff 205s > ## 205s > test.case.2 <- function() 205s + { 205s + do.test.case.2 <- function(z) 205s + { 205s + if(missing(z)) 205s + { 205s + set.seed(12345678) 205s + n <- 5 205s + z <- data.frame(v1 = rnorm(n), v2 = rnorm(n), v3 = rnorm(n)) 205s + z 205s + } 205s + 205s + fm <- PcaLocantore(z, k = 2, scale = TRUE) 205s + fm@scale 205s + apply(z, MARGIN = 2, FUN = mad) 205s + scale(z, center = fm@center, scale = fm@scale) 205s + 205s + T <- fm@scores 205s + P <- fm@loadings 205s + E <- scale(z, center = fm@center, scale = fm@scale) - T %*% t(P) 205s + d2 <- apply(E^2, MARGIN = 1, FUN = sum) 205s + ## print(sqrt(d2)); print(fm@od) 205s + print(ret <- all.equal(sqrt(d2), fm@od)) 205s + 205s + ret 205s + } 205s + do.test.case.2() 205s + do.test.case.2(phosphor) 205s + do.test.case.2(stackloss) 205s + do.test.case.2(salinity) 205s + do.test.case.2(hbk) 205s + do.test.case.2(milk) 205s + do.test.case.2(bushfire) 205s + data(rice); do.test.case.2(rice) 205s + data(un86); do.test.case.2(un86) 205s + } 205s > 205s > ## VT::15.09.2013 - this will render the output independent 205s > ## from the version of the package 205s > suppressPackageStartupMessages(library(rrcov)) 205s > 205s > dodata(method="classic") 205s 205s Call: dodata(method = "classic") 205s Data Set n p k e1 e2 205s ========================================================== 205s heart 12 2 2 812.379735 9.084962 205s Scores: 205s PC1 PC2 205s 1 2.7072 1.46576 205s 2 59.9990 -1.43041 205s 3 -3.5619 -1.54067 205s 4 -7.7696 2.52687 205s 5 14.7660 -0.95822 205s 6 -20.0489 6.91079 205s 7 1.4189 2.25961 205s 8 -34.3308 -4.23717 205s 9 -6.0487 -0.97859 205s 10 -33.0102 -3.73143 205s 11 -18.6372 0.25821 205s 12 44.5163 -0.54476 205s ------------- 205s Call: 205s PcaClassic(x = x) 205s 205s Standard deviations: 205s [1] 28.5023 3.0141 205s ---------------------------------------------------------- 205s starsCYG 47 2 2 0.331279 0.079625 205s Scores: 205s PC1 PC2 205s 1 0.2072999 0.089973 205s 2 0.6855999 0.349644 205s 3 -0.0743007 -0.061028 205s 4 0.6855999 0.349644 205s 5 0.1775161 0.015053 205s 6 0.4223986 0.211351 205s 7 -0.2926077 -0.516156 205s 8 0.2188453 0.293607 205s 9 0.5593696 0.028761 205s 10 0.0983878 0.074540 205s 11 0.8258140 -0.711176 205s 12 0.4167063 0.180244 205s 13 0.3799883 0.225541 205s 14 -0.9105236 -0.432014 205s 15 -0.7418831 -0.125322 205s 16 -0.4432862 0.048287 205s 17 -1.0503005 -0.229623 205s 18 -0.8393302 -0.007831 205s 19 -0.8126742 -0.195952 205s 20 0.9842316 -0.688729 205s 21 -0.6230699 -0.108486 205s 22 -0.7814875 -0.130933 205s 23 -0.6017038 0.025840 205s 24 -0.1857772 0.155474 205s 25 -0.0020261 0.070412 205s 26 -0.3640775 0.059510 205s 27 -0.3458392 -0.069204 205s 28 -0.1208393 0.053577 205s 29 -0.6033482 -0.176391 205s 30 1.1440521 -0.676183 205s 31 -0.5960920 -0.013765 205s 32 0.0519296 0.259855 205s 33 0.1861752 0.167779 205s 34 1.3802755 -0.632611 205s 35 -0.6542566 -0.173505 205s 36 0.5583690 0.392215 205s 37 0.0561384 0.230152 205s 38 0.1861752 0.167779 205s 39 0.1353472 0.241376 205s 40 0.5355195 0.197080 205s 41 -0.3980701 0.014294 205s 42 0.0277576 0.145332 205s 43 0.2979736 0.234120 205s 44 0.3049884 0.184614 205s 45 0.4889809 0.311684 205s 46 -0.0514512 0.134108 205s 47 -0.5224950 0.037063 205s ------------- 205s Call: 205s PcaClassic(x = x) 205s 205s Standard deviations: 205s [1] 0.57557 0.28218 205s ---------------------------------------------------------- 205s phosphor 18 2 2 220.403422 68.346121 205s Scores: 205s PC1 PC2 205s 1 4.04290 -15.3459 205s 2 -22.30489 -1.0004 205s 3 -24.52683 3.2836 205s 4 -12.54839 -6.0848 205s 5 -19.37044 2.2979 205s 6 15.20366 -19.9424 205s 7 0.44222 -3.1379 205s 8 -10.64042 3.6933 205s 9 -11.67967 5.9670 205s 10 14.26805 -7.0221 205s 11 -4.98832 1.5268 205s 12 8.74986 7.9379 205s 13 12.26290 6.0251 205s 14 6.27607 7.5768 205s 15 17.53246 3.1560 205s 16 -10.17024 -5.8994 205s 17 21.05826 5.4492 205s 18 16.39281 11.5191 205s ------------- 205s Call: 205s PcaClassic(x = x) 205s 205s Standard deviations: 205s [1] 14.8460 8.2672 205s ---------------------------------------------------------- 205s stackloss 21 3 3 99.576089 19.581136 205s Scores: 205s PC1 PC2 PC3 205s 1 20.15352 -4.359452 0.324585 205s 2 19.81554 -5.300468 0.308294 205s 3 15.45222 -1.599136 -0.203125 205s 4 2.40370 -0.145282 2.370302 205s 5 1.89538 0.070566 0.448061 205s 6 2.14954 -0.037358 1.409182 205s 7 4.43153 5.500810 2.468051 205s 8 4.43153 5.500810 2.468051 205s 9 -1.47521 1.245404 2.511773 205s 10 -5.11183 -4.802083 -2.407870 205s 11 -2.07009 3.667055 -2.261247 205s 12 -2.66223 2.833964 -3.238659 205s 13 -4.43589 -2.920053 -2.375287 205s 14 -0.46404 7.323193 -1.234961 205s 15 -9.31959 6.232579 -0.056064 205s 16 -10.33350 3.409533 -0.104938 205s 17 -14.81094 -9.872607 0.628103 205s 18 -12.44514 -3.285499 0.742143 205s 19 -11.85300 -2.452408 1.719555 205s 20 -5.73994 -2.494520 0.098250 205s 21 9.98843 1.484952 -3.614198 205s ------------- 205s Call: 205s PcaClassic(x = x) 205s 205s Standard deviations: 205s [1] 9.9788 4.4251 1.8986 205s ---------------------------------------------------------- 205s salinity 28 3 3 11.410736 7.075409 205s Scores: 205s PC1 PC2 PC3 205s 1 -0.937789 -2.40535 0.812909 205s 2 -1.752631 -2.57774 2.004437 205s 3 -6.509364 -0.78762 -1.821906 205s 4 -5.619847 -2.41333 -1.586891 205s 5 -7.268242 1.61012 1.563568 205s 6 -4.316558 -3.20411 0.029376 205s 7 -2.379545 -3.32371 0.703101 205s 8 0.013514 -3.50586 1.260502 205s 9 0.265262 -0.16736 -2.886883 205s 10 1.890755 2.43623 -0.986832 205s 11 0.804196 2.56656 0.387577 205s 12 0.935082 -1.03559 -0.074081 205s 13 1.814839 -1.61087 0.612290 205s 14 3.407535 -0.15880 2.026088 205s 15 1.731273 2.95159 -1.840286 205s 16 -6.129708 7.21368 2.632273 205s 17 -0.645124 1.06260 0.028697 205s 18 -1.307532 -2.54679 -0.280273 205s 19 0.483455 -0.55896 -3.097281 205s 20 2.053267 0.47308 -1.858703 205s 21 3.277664 -1.31002 0.453753 205s 22 4.631644 -0.78005 1.519894 205s 23 1.864403 5.32790 -0.849694 205s 24 0.623899 4.29317 0.056461 205s 25 1.301696 0.37871 -0.646220 205s 26 2.852126 -0.79527 -0.347711 205s 27 4.134051 -0.92756 0.449222 205s 28 4.781679 -0.20467 1.736616 205s ------------- 205s Call: 205s PcaClassic(x = x) 205s 205s Standard deviations: 205s [1] 3.3780 2.6600 1.4836 205s ---------------------------------------------------------- 205s hbk 75 3 3 216.162129 1.981077 205s Scores: 205s PC1 PC2 PC3 205s 1 26.2072 -0.660756 0.503340 205s 2 27.0406 -0.108506 -0.225059 205s 3 28.8351 -1.683721 0.263078 205s 4 29.9221 -0.812174 -0.674480 205s 5 29.3181 -0.909915 -0.121600 205s 6 27.5360 -0.599697 0.916574 205s 7 27.6617 -0.073753 0.676620 205s 8 26.5576 -0.882312 0.159620 205s 9 28.8726 -1.074223 -0.673462 205s 10 27.6643 -1.463829 -0.868593 205s 11 34.2019 -0.664473 -0.567265 205s 12 35.4805 -2.730949 -0.259320 205s 13 34.7544 1.325449 0.749884 205s 14 38.9522 8.171389 0.034382 205s 15 -5.5375 0.390704 1.679172 205s 16 -7.4319 0.803850 1.925633 205s 17 -8.5880 0.957577 -1.010312 205s 18 -6.6022 -0.425109 0.625148 205s 19 -6.5596 1.154721 -0.640680 205s 20 -5.2525 0.812527 1.377832 205s 21 -6.2771 0.067747 0.958907 205s 22 -6.2501 1.325491 -1.104428 205s 23 -7.2419 0.839808 0.728712 205s 24 -7.6489 1.131606 0.154897 205s 25 -9.0763 -0.670721 -0.167577 205s 26 -5.5967 0.999411 -0.810000 205s 27 -5.1460 -0.339018 1.326712 205s 28 -7.1659 -0.993461 0.125933 205s 29 -8.2104 -0.169338 -0.073569 205s 30 -6.2499 -1.689222 -0.877481 205s 31 -7.3180 -0.225795 1.687204 205s 32 -7.9446 1.473868 -0.541790 205s 33 -6.3604 1.237472 0.061800 205s 34 -8.9812 -0.710662 -0.830422 205s 35 -5.1698 -0.435484 1.102817 205s 36 -5.9995 -0.058135 -0.713550 205s 37 -5.8753 0.852882 -1.610556 205s 38 -8.4501 0.334363 0.404813 205s 39 -8.1751 -1.300317 0.633282 205s 40 -7.4495 0.672712 -0.829815 205s 41 -5.6213 -1.106765 1.395315 205s 42 -6.8571 -0.900977 -1.509937 205s 43 -7.0633 1.987372 -1.079934 205s 44 -6.3763 -1.867647 -0.251224 205s 45 -8.6456 -0.866053 0.630132 205s 46 -6.5356 -1.763526 -0.189838 205s 47 -8.2224 -1.183284 1.615150 205s 48 -5.6136 -1.100704 1.079239 205s 49 -5.9907 0.220336 1.443387 205s 50 -5.2675 0.142923 0.194023 205s 51 -7.9324 0.324710 1.113289 205s 52 -7.5544 -1.033884 1.792496 205s 53 -6.7119 -1.712257 -1.711778 205s 54 -7.4679 1.856542 0.046658 205s 55 -7.4666 1.161504 -0.725948 205s 56 -6.7110 1.574868 0.534288 205s 57 -8.2571 -0.399824 0.521995 205s 58 -5.9781 1.312567 0.926790 205s 59 -5.6960 -0.394338 -0.332938 205s 60 -6.1017 -0.797579 -1.679359 205s 61 -5.2628 0.919128 -1.436156 205s 62 -9.1245 -0.516135 -0.229065 205s 63 -7.7140 1.659145 0.068510 205s 64 -4.9886 0.173613 0.865810 205s 65 -6.6157 -1.479786 0.098390 205s 66 -7.9511 0.772770 -0.998321 205s 67 -7.1856 0.459602 0.216588 205s 68 -8.7345 -0.860784 -1.238576 205s 69 -8.5833 -0.313481 0.832074 205s 70 -5.8642 -0.142883 -0.870064 205s 71 -5.8879 0.186456 0.464467 205s 72 -7.1865 0.497156 -0.826767 205s 73 -6.8671 -0.058606 -1.335842 205s 74 -7.1398 0.727642 -1.422331 205s 75 -7.2696 -1.347832 -1.496927 205s ------------- 205s Call: 205s PcaClassic(x = x) 205s 205s Standard deviations: 205s [1] 14.70245 1.40751 0.95725 205s ---------------------------------------------------------- 205s milk 86 8 8 15.940298 2.771345 205s Scores: 205s PC1 PC2 PC3 PC4 PC5 PC6 PC7 205s 1 6.471620 1.031110 0.469432 0.5736412 1.0294362 -0.6054039 -0.2005117 205s 2 7.439545 0.320597 0.081922 -0.6305898 0.7128977 -1.1601053 -0.1170582 205s 3 1.240654 -1.840458 0.520870 -0.1717469 0.2752079 -0.3815506 0.6004089 205s 4 5.952685 -1.856375 1.638710 0.3358626 -0.5834205 -0.0665348 -0.1580799 205s 5 -0.706973 0.261795 0.423736 0.2916399 -0.5307716 -0.3325563 -0.0062349 205s 6 2.524050 0.293380 -0.572997 0.2466367 -0.3497882 0.0386014 -0.1418131 205s 7 3.136085 -0.050202 -0.818165 -0.0451560 -0.5226337 -0.1597194 0.1669050 205s 8 3.260390 0.312365 -0.110776 0.4908006 -0.5225353 -0.1972222 -0.1068433 205s 9 -0.808914 -2.355785 1.344204 -0.4743284 -0.1394914 -0.1390080 -0.2620731 205s 10 -2.511226 -0.995321 -0.087218 -0.5950040 0.4268321 0.2561918 0.0891170 205s 11 -9.204096 -0.598364 1.587275 0.0833647 0.1865626 0.0358228 0.0920394 205s 12 -12.946774 1.951332 -0.179186 0.2560603 0.1300954 -0.1179820 -0.0999494 205s 13 -10.011603 0.726323 -2.102423 -1.3105560 0.3291550 0.0660007 -0.0794410 205s 14 -11.983644 0.768224 -0.532227 -0.5161201 -0.0817164 -0.4358934 -0.1734612 205s 15 -10.465714 -0.704271 2.035437 0.3713778 -0.0564830 -0.2696432 -0.1940091 205s 16 -2.527619 -0.286939 0.354497 0.8571223 0.1585009 0.2272835 0.4386955 205s 17 -0.514527 -2.895087 1.657181 0.2208239 0.1961109 0.1280496 -0.0182491 205s 18 -1.763931 0.854269 -0.686282 0.2848209 -0.4813608 -0.2623962 0.4757030 205s 19 -1.538419 -0.866477 1.103818 0.3874507 0.2086661 0.1267277 0.2354264 205s 20 0.732842 -1.455594 1.097358 -0.2530588 -0.0302385 0.2654274 0.6093330 205s 21 -2.530155 1.932885 -0.873095 0.6202295 -0.4153607 0.0048383 0.0067484 205s 22 -0.772646 0.675846 -0.259539 0.4844670 -0.0893266 -0.2785557 -0.0424662 205s 23 0.185417 1.413719 0.066135 1.1014470 0.0468093 0.0288637 0.2539994 205s 24 -0.280536 0.908864 0.113221 1.3370381 0.3289929 0.2588134 -0.0356289 205s 25 -3.503626 1.971233 0.203620 1.1975494 -0.3175317 0.1149685 0.0584396 205s 26 -0.639313 1.175503 0.403906 0.9082134 -0.2648165 -0.1238813 -0.0174853 205s 27 -2.923327 -0.365168 0.149478 0.8201430 -0.1544609 -0.4856934 -0.0058424 205s 28 2.505633 3.050292 -0.554424 2.1416405 -0.0378764 0.1002280 -0.3888580 205s 29 4.649504 1.054863 -0.081018 1.1454466 0.1502080 0.4967323 0.0879775 205s 30 1.049282 1.355215 -0.142701 0.7805566 -0.2059790 0.0193142 0.0815524 205s 31 1.962583 1.595396 -2.050642 0.3556747 0.1384801 0.1197984 0.1608247 205s 32 1.554846 0.095644 -1.423054 -0.3175620 0.4260008 -0.1612463 -0.0567196 205s 33 2.248977 0.010348 -0.062469 0.6388269 0.2098648 0.1330250 0.0906704 205s 34 0.993109 -0.828812 0.284059 0.3446686 0.1899096 -0.0515571 -0.2281197 205s 35 -0.335103 1.614093 -0.920661 1.2502617 0.2435013 0.1264875 0.0469238 205s 36 4.346795 1.208134 0.368889 1.1429977 -0.1362052 -0.0158169 -0.0183852 205s 37 0.992634 2.013738 -1.350619 0.8714694 0.0057776 -0.2122691 0.1760918 205s 38 2.213341 1.706516 -0.705418 1.2670281 -0.0707149 0.0670467 -0.1863588 205s 39 -1.213255 0.644062 0.163988 1.1213961 0.2945355 0.1093574 0.0019574 205s 40 3.942604 -1.704266 0.660327 0.1618506 0.4259076 0.0070193 0.3462765 205s 41 4.262054 1.687193 0.351875 0.5396477 1.0052810 -0.9331689 0.0056063 205s 42 6.865198 -1.091248 1.153585 1.1248797 0.0873276 0.2565221 0.0333265 205s 43 3.476720 0.555449 -1.030771 -0.3015720 -0.1748109 -0.1584968 0.4079902 205s 44 5.691730 -0.141240 0.565189 0.3174238 0.6478440 1.0579977 -0.5387916 205s 45 0.327134 0.152011 -0.394798 0.4998430 0.1599781 0.3159518 0.1623656 205s 46 0.280225 1.569387 -0.100397 1.2800976 0.0446645 0.0946513 0.0461599 205s 47 3.119928 -0.384834 -3.325600 -1.8865310 -0.1334744 0.1249987 -0.2561273 205s 48 0.501542 0.739816 -1.384556 -0.1244721 0.2948958 0.4836170 -0.1182802 205s 49 -1.953218 0.269986 -1.726474 -0.8510637 0.5047958 0.4860651 0.2318735 205s 50 3.706878 -2.400570 1.361047 -0.4949076 0.2180352 0.4080879 0.1156540 205s 51 -1.060358 -0.521609 -1.387412 -1.2767491 -0.0521356 0.1665452 -0.0044412 205s 52 -4.900528 0.157011 -1.015880 -0.9941168 0.2069608 0.3239762 -0.1921715 205s 53 -0.388496 0.062051 -0.643721 -0.8544141 -0.1857141 0.0063293 0.2664606 205s 54 0.109234 -0.018709 -0.242825 -0.2064701 -0.0585165 0.1720867 0.1117397 205s 55 1.176175 0.644539 -0.373694 0.0038605 -0.3436524 0.0194450 -0.0838883 205s 56 0.407259 -0.606637 0.222915 -0.3622451 -0.0737834 0.0228104 0.0297333 205s 57 -1.022756 -0.071860 0.741957 0.2273628 -0.1388444 -0.2396467 -0.2327738 205s 58 0.245419 1.167059 0.225934 0.8318795 -0.5365166 -0.0090816 -0.1680757 205s 59 -1.300617 -1.110325 -0.262740 -0.8857801 -0.0816954 -0.1186886 -0.0928322 205s 60 -1.110561 -0.832357 -0.212713 -0.4754481 -0.4105982 -0.1886992 -0.0602872 205s 61 0.381831 -1.475116 0.601047 -0.6260156 -0.1854501 -0.1749306 -0.0013904 205s 62 2.734462 -1.887861 0.813453 -0.5856987 0.2310656 0.1117041 -0.0293373 205s 63 3.092464 -0.172602 0.017725 0.4874693 -0.5428206 0.0151218 -0.0683340 205s 64 3.092464 -0.172602 0.017725 0.4874693 -0.5428206 0.0151218 -0.0683340 205s 65 0.004744 -2.712679 1.178987 -0.6677199 0.0208119 0.0621903 -0.0655693 205s 66 -2.014851 -1.060090 -0.099959 -0.7225044 -0.1947648 -0.2282902 -0.0505015 205s 67 0.621739 -1.296106 0.255632 -0.3309504 -0.0880200 0.2524306 0.1465779 205s 68 -0.271385 -1.709161 -1.100349 -2.0937671 0.2166264 0.0191278 0.0114174 205s 69 -0.326350 -0.737232 0.021639 -0.3850383 -0.4338287 0.2156624 0.1597594 205s 70 4.187093 9.708082 4.632803 -4.9751240 -0.0881576 0.2392433 0.0568049 205s 71 -1.868507 -1.600166 0.436353 -0.8078214 -0.1530893 0.0479471 -0.1999893 205s 72 2.768081 -0.556824 -0.148923 -0.3197853 -0.5524427 0.0907804 -0.0694488 205s 73 -1.441846 -2.735114 -0.294134 -1.2172969 0.0109453 -0.0562910 0.1505788 205s 74 -10.995490 0.615992 1.950966 1.1687190 0.2798335 0.2713257 0.0652135 205s 75 0.508992 -2.363945 -0.407064 -0.9522316 0.1040307 0.1088110 -0.7368484 205s 76 -1.015714 -0.307662 -1.088162 -1.0181862 -0.0440888 -0.1362208 0.0271200 205s 77 -8.028891 -0.580763 0.933638 0.4619362 0.3379832 -0.1368644 -0.0669441 205s 78 1.763308 -1.336175 -0.127809 -0.7161775 -0.1904861 -0.0900461 0.0037539 205s 79 0.208944 -0.580698 -0.626297 -0.7620610 -0.0262368 -0.2928202 0.0285908 205s 80 -3.230608 1.251352 0.195280 0.8687004 0.1812011 0.2600692 -0.1516375 205s 81 1.498160 0.669731 -0.266114 0.3772866 -0.2769688 -0.1066593 -0.1608395 205s 82 3.232051 -1.776018 0.485524 0.1170945 0.0557260 0.2219872 0.1187681 205s 83 2.999977 -0.228275 -0.467724 -0.4287672 0.0494902 -0.2337809 -0.0718159 205s 84 1.238083 0.320956 -1.806006 -1.0142266 0.2359630 -0.0857149 0.0593938 205s 85 1.276376 -2.081214 2.540850 0.3745805 -0.2596482 -0.1228412 -0.2199985 205s 86 0.930715 0.836457 -1.385153 -0.6074929 -0.2476354 0.1680713 -0.0117324 205s PC8 205s 1 9.0765e-04 205s 2 2.1811e-04 205s 3 1.1834e-03 205s 4 8.4077e-05 205s 5 9.9209e-04 205s 6 1.6277e-03 205s 7 2.4907e-04 205s 8 6.8383e-04 205s 9 -5.0924e-04 205s 10 3.1215e-04 205s 11 3.0654e-04 205s 12 -1.1951e-03 205s 13 -1.2849e-03 205s 14 -9.0801e-04 205s 15 -1.2686e-03 205s 16 -1.8441e-03 205s 17 -2.1068e-03 205s 18 -5.7816e-04 205s 19 -1.2330e-03 205s 20 3.3857e-05 205s 21 3.8623e-04 205s 22 1.3035e-04 205s 23 -3.8648e-04 205s 24 -1.7400e-04 205s 25 -3.9196e-04 205s 26 -7.6996e-04 205s 27 -4.8042e-04 205s 28 -2.0628e-04 205s 29 -4.5672e-04 205s 30 -1.4716e-04 205s 31 -4.6385e-05 205s 32 -2.0481e-04 205s 33 -3.0020e-04 205s 34 -5.8179e-05 205s 35 1.3870e-04 205s 36 -6.7177e-04 205s 37 -3.0799e-04 205s 38 6.2140e-04 205s 39 4.5912e-04 205s 40 -3.7165e-04 205s 41 -5.4362e-04 205s 42 -1.0155e-03 205s 43 1.3449e-04 205s 44 -5.4761e-04 205s 45 1.0300e-03 205s 46 1.1039e-03 205s 47 -6.4858e-04 205s 48 -7.6886e-05 205s 49 3.2590e-04 205s 50 8.6845e-05 205s 51 4.9423e-04 205s 52 9.2973e-04 205s 53 4.4342e-04 205s 54 4.9888e-04 205s 55 7.2171e-04 205s 56 -3.2133e-05 205s 57 -1.8101e-04 205s 58 -5.4969e-06 205s 59 -8.3841e-04 205s 60 5.9446e-05 205s 61 -6.5683e-05 205s 62 -3.4073e-04 205s 63 -6.5145e-04 205s 64 -6.5145e-04 205s 65 1.4986e-04 205s 66 2.8096e-04 205s 67 -6.5170e-05 205s 68 -1.3775e-04 205s 69 6.8225e-06 205s 70 -1.6290e-04 205s 71 3.9009e-04 205s 72 -1.3981e-04 205s 73 6.2613e-04 205s 74 2.6513e-03 205s 75 3.7088e-04 205s 76 9.9539e-04 205s 77 1.2979e-03 205s 78 5.6500e-04 205s 79 3.0940e-04 205s 80 8.7993e-04 205s 81 -3.1353e-04 205s 82 4.9625e-04 205s 83 -6.3951e-04 205s 84 -4.5582e-04 205s 85 5.9440e-04 205s 86 -3.6234e-04 205s ------------- 205s Call: 205s PcaClassic(x = x) 205s 205s Standard deviations: 205s [1] 3.99253025 1.66473582 1.10660264 0.96987790 0.33004256 0.29263512 0.20843280 205s [8] 0.00074024 205s ---------------------------------------------------------- 205s bushfire 38 5 5 38435.075910 1035.305774 205s Scores: 205s PC1 PC2 PC3 PC4 PC5 205s 1 -111.9345 4.9970 -1.00881 -1.224361 3.180569 205s 2 -113.4128 7.4784 -0.79170 -0.235184 2.385812 205s 3 -105.8364 10.9615 -3.15662 -0.251662 1.017328 205s 4 -89.1684 8.7232 -6.15080 -0.075611 1.431111 205s 5 -58.7216 -1.9543 -12.70661 -0.151328 1.425570 205s 6 -35.0370 -12.8434 -17.06841 -0.525664 3.499743 205s 7 -250.2123 -49.4348 23.31261 -19.070238 0.647348 205s 8 -292.6877 -69.7708 -21.30815 13.093808 -1.288764 205s 9 -294.0765 -70.9903 -23.96326 14.940985 -0.939076 205s 10 -290.0193 -57.3747 3.51346 1.858995 0.083107 205s 11 -289.8168 -43.3207 16.08046 -1.745099 -1.506042 205s 12 -290.8645 6.2503 40.52173 -7.496479 -0.033767 205s 13 -232.6865 41.8090 37.19429 -1.280348 -0.470837 205s 14 9.8483 25.1954 -14.56970 0.538484 1.772046 205s 15 137.1924 11.8521 -37.12452 -5.130459 -0.586695 205s 16 92.9804 10.3923 -24.97267 -7.551314 -1.867125 205s 17 90.4493 10.5630 -21.92735 -5.669651 -1.001362 205s 18 78.6325 5.2211 -19.74718 -6.107880 -1.939986 205s 19 82.1178 3.6913 -21.37810 -4.259855 -1.278838 205s 20 92.9044 7.1961 -21.22900 -4.125571 -0.127089 205s 21 74.9157 10.2991 -16.60924 -5.660751 -0.406343 205s 22 66.7350 12.0460 -16.73298 -4.669080 1.333436 205s 23 -62.1981 22.7394 6.03613 -5.182356 -0.453624 205s 24 -116.5696 32.3182 12.74846 -1.465657 -0.097851 205s 25 -53.8907 22.4278 -2.18861 -2.742014 -0.990071 205s 26 -60.6384 20.2952 -3.05206 -2.953685 -0.629061 205s 27 -74.7621 28.9067 -0.65817 1.473357 -0.443957 205s 28 -50.2202 37.3457 -1.44989 5.530426 -1.073521 205s 29 -38.7483 50.2749 2.34469 10.156457 -0.416262 205s 30 -93.3887 51.7884 20.08872 8.798781 -1.620216 205s 31 35.3096 41.7158 13.46272 14.464358 -0.475973 205s 32 290.8493 3.5924 7.41501 15.244293 2.141354 205s 33 326.7236 -29.8194 15.64898 2.612061 0.064931 205s 34 322.9095 -30.6372 16.21520 1.248005 -0.711322 205s 35 328.5307 -29.9533 16.49656 1.138916 0.974792 205s 36 325.6791 -30.6990 16.83840 -0.050949 -1.211360 205s 37 323.8136 -30.7474 19.55764 -1.545150 -0.267580 205s 38 325.2991 -30.5350 20.31878 -1.928580 -0.120425 205s ------------- 205s Call: 205s PcaClassic(x = x) 205s 205s Standard deviations: 205s [1] 196.0487 32.1762 18.4819 6.9412 1.3510 205s ---------------------------------------------------------- 205s ========================================================== 205s > dodata(method="hubert.mcd") 205s 205s Call: dodata(method = "hubert.mcd") 205s Data Set n p k e1 e2 205s ========================================================== 205s heart 12 2 2 358.175786 4.590630 205s Scores: 205s PC1 PC2 205s 1 -12.2285 0.86283 205s 2 -68.9906 -7.43256 205s 3 -5.7035 -1.53793 205s 4 -1.8988 2.90891 205s 5 -24.0044 -2.68946 205s 6 9.9115 8.43321 205s 7 -11.0210 1.77484 205s 8 25.1826 -1.31573 205s 9 -3.2809 -0.74345 205s 10 23.8200 -0.93701 205s 11 9.1344 1.67701 205s 12 -53.6607 -5.08826 205s ------------- 205s Call: 205s PcaHubert(x = x, k = p) 205s 205s Standard deviations: 205s [1] 18.9255 2.1426 205s ---------------------------------------------------------- 205s starsCYG 47 2 2 0.280653 0.005921 205s Scores: 205s PC1 PC2 205s 1 -0.285731 -0.0899858 205s 2 -0.819689 0.0153191 205s 3 0.028077 -0.1501882 205s 4 -0.819689 0.0153191 205s 5 -0.234971 -0.1526225 205s 6 -0.527231 -0.0382380 205s 7 0.372118 -0.5195605 205s 8 -0.357448 0.1009508 205s 9 -0.603553 -0.2533541 205s 10 -0.177170 -0.0722541 205s 11 -0.637339 -1.0390758 205s 12 -0.512526 -0.0662337 205s 13 -0.490978 -0.0120517 205s 14 0.936868 -0.2550656 205s 15 0.684479 -0.0125787 205s 16 0.347708 0.0641382 205s 17 1.009966 -0.0202111 205s 18 0.742477 0.1286170 205s 19 0.773105 -0.0588983 205s 20 -0.795247 -1.0648673 205s 21 0.566048 -0.0319223 205s 22 0.723956 -0.0061308 205s 23 0.505616 0.0899297 205s 24 0.069956 0.0896997 205s 25 -0.080090 -0.0462652 205s 26 0.268755 0.0512425 205s 27 0.289710 -0.0770574 205s 28 0.038341 -0.0269216 205s 29 0.567463 -0.1026188 205s 30 -0.951542 -1.1005280 205s 31 0.512064 0.0504528 205s 32 -0.188059 0.1184850 205s 33 -0.288758 -0.0094200 205s 34 -1.190016 -1.1293460 205s 35 0.615197 -0.0846898 205s 36 -0.710930 0.0938781 205s 37 -0.183223 0.0888774 205s 38 -0.288758 -0.0094200 205s 39 -0.262177 0.0759816 205s 40 -0.630957 -0.0855773 205s 41 0.314679 0.0182135 205s 42 -0.130850 0.0163715 205s 43 -0.415248 0.0205825 205s 44 -0.407188 -0.0287636 205s 45 -0.620693 0.0376892 205s 46 -0.051896 0.0292672 205s 47 0.426662 0.0770340 205s ------------- 205s Call: 205s PcaHubert(x = x, k = p) 205s 205s Standard deviations: 205s [1] 0.529767 0.076946 205s ---------------------------------------------------------- 205s phosphor 18 2 2 285.985489 32.152099 205s Scores: 205s PC1 PC2 205s 1 -2.89681 -18.08811 205s 2 21.34021 -0.40854 205s 3 22.98065 4.13006 205s 4 12.33544 -6.72947 205s 5 17.99823 2.47611 205s 6 -13.35773 -24.10967 205s 7 -0.92957 -5.51314 205s 8 9.16061 2.71354 205s 9 9.89243 5.10403 205s 10 -14.12600 -11.17832 205s 11 3.84175 -0.17605 205s 12 -10.61905 4.37646 205s 13 -13.85065 2.01919 205s 14 -8.11927 4.34325 205s 15 -18.69805 -1.51673 205s 16 9.95352 -6.85784 205s 17 -22.49433 0.29387 205s 18 -18.66592 6.92359 205s ------------- 205s Call: 205s PcaHubert(x = x, k = p) 205s 205s Standard deviations: 205s [1] 16.9111 5.6703 205s ---------------------------------------------------------- 205s stackloss 21 3 3 78.703690 19.249085 205s Scores: 205s PC1 PC2 PC3 205s 1 -20.323997 10.26124 0.92041 205s 2 -19.761418 11.08797 0.92383 205s 3 -16.469919 6.43190 0.22593 205s 4 -4.171902 1.68262 2.50695 205s 5 -3.756174 1.40774 0.57004 205s 6 -3.964038 1.54518 1.53850 205s 7 -7.547376 -3.27780 2.48643 205s 8 -7.547376 -3.27780 2.48643 205s 9 -0.763294 -0.63699 2.53518 205s 10 4.214079 4.46296 -2.28315 205s 11 -0.849132 -2.97767 -2.31393 205s 12 -0.078689 -2.28838 -3.27896 205s 13 3.088921 2.80948 -2.28999 205s 14 -3.307313 -6.14718 -1.35916 205s 15 5.552354 -7.34201 -0.32057 205s 16 7.240091 -4.86180 -0.31031 205s 17 14.908334 6.84995 0.70603 205s 18 10.970281 1.06279 0.68209 205s 19 10.199838 0.37350 1.64712 205s 20 4.273564 1.99328 0.14526 205s 21 -11.992249 2.19025 -3.37391 205s ------------- 205s Call: 205s PcaHubert(x = x, k = p) 205s 205s Standard deviations: 205s [1] 8.8715 4.3874 2.1990 205s ---------------------------------------------------------- 206s salinity 28 3 3 11.651966 4.107426 206s Scores: 206s PC1 PC2 PC3 206s 1 1.68712 1.62591 0.19812128 206s 2 2.35772 2.37290 1.24965734 206s 3 6.80132 -2.14412 0.68142276 206s 4 6.41982 -0.61348 -0.31907921 206s 5 6.36697 -1.98030 4.87319903 206s 6 5.22050 1.20864 0.10252555 206s 7 3.34007 2.02950 0.00064329 206s 8 1.06220 2.89801 -0.35658064 206s 9 0.34692 -2.20572 -1.71677710 206s 10 -2.21421 -2.74842 0.76862599 206s 11 -1.40111 -2.16163 2.21124383 206s 12 -0.38242 0.32284 -0.23732191 206s 13 -1.12809 1.33152 -0.28800043 206s 14 -3.24998 1.35943 1.17514969 206s 15 -2.11006 -3.70114 0.45102357 206s 16 3.46920 -5.41242 8.56937909 206s 17 0.46682 -1.46753 1.48992481 206s 18 2.21807 0.99168 -0.61894625 206s 19 0.28525 -2.00333 -2.16450483 206s 20 -1.66639 -1.76768 -1.06946404 206s 21 -2.58106 1.23534 -0.65557612 206s 22 -4.15573 1.71244 0.08170141 206s 23 -3.07670 -4.87628 2.53200755 206s 24 -1.70808 -3.71657 2.99305849 206s 25 -1.08172 -1.05713 0.02468813 206s 26 -2.23187 0.27323 -0.85760867 206s 27 -3.50498 1.07657 -0.68503455 206s 28 -4.49819 1.43219 0.53416609 206s ------------- 206s Call: 206s PcaHubert(x = x, k = p) 206s 206s Standard deviations: 206s [1] 3.4135 2.0267 1.0764 206s ---------------------------------------------------------- 206s hbk 75 3 3 1.459908 1.201048 206s Scores: 206s PC1 PC2 PC3 206s 1 -31.105415 4.714217 10.4566165 206s 2 -31.707650 5.748724 10.7682402 206s 3 -33.366131 4.625897 12.1570167 206s 4 -34.173377 6.069657 12.4466895 206s 5 -33.780418 5.508823 11.9872893 206s 6 -32.493478 4.684595 10.5679819 206s 7 -32.592637 5.235522 10.3765493 206s 8 -31.293363 4.865797 10.9379676 206s 9 -33.160964 5.714260 12.3098920 206s 10 -31.919786 5.384537 12.3374332 206s 11 -38.231962 6.810641 13.5994385 206s 12 -39.290479 5.393906 15.2942554 206s 13 -39.418445 7.326461 11.5194898 206s 14 -43.906584 13.214819 8.3282743 206s 15 -1.906326 -0.716061 -0.8635112 206s 16 -0.263255 -0.926016 -1.9009292 206s 17 1.776489 1.072332 -0.5496140 206s 18 -0.464648 -0.702441 0.0482897 206s 19 -0.267826 1.283779 -0.2925812 206s 20 -2.122108 -0.165970 -0.8924686 206s 21 -0.937217 -0.548532 -0.4132196 206s 22 -0.423273 1.781869 -0.0323061 206s 23 -0.047532 -0.018909 -1.1259327 206s 24 0.490041 0.520202 -1.1065753 206s 25 2.143049 -0.720869 -0.0495474 206s 26 -1.094748 1.459175 0.2226246 206s 27 -2.070705 -0.898573 0.0023229 206s 28 0.294998 -0.830258 0.5929001 206s 29 1.242995 -0.300216 -0.2010507 206s 30 -0.147958 -0.439099 2.0003038 206s 31 -0.170818 -1.440946 -0.9755627 206s 32 0.958531 1.199730 -1.0129867 206s 33 -0.697307 0.874343 -0.7260649 206s 34 2.278946 -0.261106 0.4196544 206s 35 -1.962829 -0.809318 0.2033113 206s 36 -0.626631 0.600666 0.8004036 206s 37 -0.550885 1.881448 0.7382776 206s 38 1.249717 -0.336214 -0.9349845 206s 39 1.106696 -1.569418 0.1869576 206s 40 0.684034 0.939963 -0.1034965 206s 41 -1.559314 -1.551408 0.3660323 206s 42 0.538741 0.447358 1.6361099 206s 43 0.252685 2.080564 -0.7765259 206s 44 -0.217012 -1.027281 1.7015154 206s 45 1.497600 -1.349234 -0.2698932 206s 46 -0.100388 -1.026443 1.5390401 206s 47 0.811117 -2.195271 -0.5208141 206s 48 -1.462210 -1.321318 0.5600144 206s 49 -1.383976 -0.740714 -0.7348906 206s 50 -1.636773 0.215464 0.3195369 206s 51 0.530918 -0.759743 -1.2069247 206s 52 0.109566 -2.107455 -0.5315473 206s 53 0.564334 0.060847 2.3910630 206s 54 0.272234 1.122711 -1.5060028 206s 55 0.608660 1.197219 -0.5255609 206s 56 -0.565430 0.710345 -1.3708230 206s 57 1.115629 -0.888816 -0.4186014 206s 58 -1.351288 0.374815 -1.1980618 206s 59 -0.998016 0.151228 0.9007970 206s 60 -0.124017 0.764846 1.9005963 206s 61 -1.189858 1.905264 0.7721322 206s 62 2.190589 -0.579614 -0.1377914 206s 63 0.518278 0.931130 -1.4534768 206s 64 -2.124566 -0.194391 -0.0327092 206s 65 -0.154218 -1.050861 1.1309885 206s 66 1.197852 1.044147 -0.2265269 206s 67 0.114174 0.094763 -0.5168926 206s 68 2.201115 -0.032271 0.8573493 206s 69 1.307843 -1.104815 -0.7741270 206s 70 -0.691449 0.676665 1.0004603 206s 71 -1.150975 -0.050861 -0.0717068 206s 72 0.457293 0.861871 0.1026350 206s 73 0.392258 0.897451 0.9178065 206s 74 0.584658 1.450471 0.3201857 206s 75 0.972517 0.063777 1.8223995 206s ------------- 206s Call: 206s PcaHubert(x = x, k = p) 206s 206s Standard deviations: 206s [1] 1.2083 1.0959 1.0168 206s ---------------------------------------------------------- 206s milk 86 8 8 5.739740 2.405262 206s Scores: 206s PC1 PC2 PC3 PC4 PC5 PC6 PC7 206s 1 -5.710924 -1.346213 0.01332091 -0.3709242 -0.566813 0.7529298 -1.2525433 206s 2 -6.578612 -0.440749 1.16354746 0.2870685 -0.573207 0.7368064 -1.6101427 206s 3 -0.720902 1.777381 -0.21532020 -0.3213950 0.287603 -0.4764464 -0.5638337 206s 4 -5.545889 1.621147 -0.85212883 0.4380154 0.022241 0.0718035 0.1176140 206s 5 1.323210 -0.143897 -0.78611461 0.5966857 0.043139 -0.0512545 -0.1419726 206s 6 -1.760792 -0.662792 0.46402240 0.2149752 0.130000 0.0797221 0.1916948 206s 7 -2.344198 -0.363657 0.92442296 0.3921371 0.241463 -0.2370967 0.0636268 206s 8 -2.556824 -0.680132 0.04339934 0.4635077 0.154136 0.0371259 0.0260340 206s 9 1.203234 2.712342 -1.00693092 0.1251739 0.170679 0.2231851 -0.0118196 206s 10 3.151858 1.255826 -0.01678562 -0.5087398 -0.087933 0.0115055 -0.0097828 206s 11 9.562891 1.580419 -2.65612113 -0.1748178 -0.153031 -0.0880112 -0.1648752 206s 12 13.617821 -0.999033 -1.92168237 0.0326918 -0.038488 0.0870082 -0.1809687 206s 13 10.958032 -0.097916 0.95915085 -0.2348663 0.147875 0.1219202 0.0419067 206s 14 12.675941 0.158747 -1.04153243 0.3117402 0.302036 0.1187749 -0.2310830 206s 15 10.726828 1.775339 -3.36786799 0.1285422 0.151594 0.0998947 -0.2028458 206s 16 3.042705 0.212589 -1.23921907 -0.5596596 0.277061 -0.5037073 0.0612182 206s 17 0.780071 2.990008 -1.58490147 -0.5441119 0.436485 -0.0603833 0.1016610 206s 18 2.523916 -0.923373 -0.03221722 0.3830822 0.208008 -0.5505270 -0.1252648 206s 19 1.990563 1.062648 -1.42038451 -0.3602257 -0.068006 -0.1932744 -0.1197842 206s 20 -0.243938 1.674555 -0.72225359 -0.1475652 -0.397855 -0.5385123 -0.0559660 206s 21 3.354424 -2.001060 -0.22542149 0.3346180 0.032502 -0.0953825 0.1293148 206s 22 1.477177 -0.777534 -0.35362339 0.1224412 0.203208 0.0514382 -0.2166274 206s 23 0.502055 -1.618511 -0.85013853 -0.1298862 -0.144328 -0.1941806 -0.1923681 206s 24 0.900504 -1.227820 -1.07180474 -0.5851197 0.112657 0.0467164 0.0405544 206s 25 4.161393 -1.869015 -1.54507759 0.2003123 -0.152582 -0.1382908 0.0864320 206s 26 1.277795 -1.185179 -1.13445511 0.2771556 -0.101901 0.0070037 -0.1279016 206s 27 3.447256 0.257652 -1.13407954 -0.0077859 0.853002 -0.1376443 -0.1897380 206s 28 -1.695730 -3.781876 -0.72940594 -0.0956421 0.064475 0.3665470 0.0726448 206s 29 -3.923610 -1.654818 -0.16117226 -0.4242302 -0.303749 -0.0209844 0.1723890 206s 30 -0.309616 -1.564739 -0.39909943 0.1657509 -0.178739 -0.0600221 -0.0571706 206s 31 -0.960838 -2.242733 1.50477679 -0.2957897 0.163758 -0.1034399 0.0257903 206s 32 -0.671285 -0.459839 1.39124475 -0.3669914 0.246127 0.2094780 -0.2681284 206s 33 -1.589089 -0.390812 -0.16505762 -0.3992573 0.086870 -0.0402114 -0.0399923 206s 34 -0.421868 0.636139 -0.42563447 -0.2985726 0.311365 0.2398515 -0.0540852 206s 35 1.118429 -2.116328 -0.22329747 -0.4864401 0.289927 -0.0503006 0.0101706 206s 36 -3.660291 -1.630831 -0.57876280 0.1294792 -0.260224 0.0912904 -0.1565668 206s 37 -0.087686 -2.530609 0.50076931 -0.0319873 0.194898 -0.1233526 -0.2494283 206s 38 -1.418620 -2.303011 -0.09405565 -0.0931745 0.169466 0.1581787 0.0850095 206s 39 1.815225 -0.838968 -1.10222194 -0.4897630 0.180933 0.0096330 -0.0600652 206s 40 -3.420975 1.398516 -0.17143314 -0.5852146 0.090464 -0.2066323 -0.2974177 206s 41 -3.462295 -1.795174 -0.17500650 -0.1610267 -0.595086 0.5981680 -1.5930268 206s 42 -6.401429 0.451242 -0.78723149 -0.4285618 0.055395 -0.0212476 0.0808936 206s 43 -2.583017 -0.871790 1.29937081 0.2422349 -0.190002 -0.2822972 -0.2625721 206s 44 -5.027244 -0.167503 -0.02382957 -0.8288929 -0.852207 0.7399343 0.4606076 206s 45 0.364494 -0.440380 -0.07746564 -0.4552133 0.095711 -0.1662998 0.1566706 206s 46 0.420706 -1.880819 -0.82180986 -0.1823454 -0.022661 -0.0304227 -0.0516440 206s 47 -1.932985 -0.120002 4.00934170 0.0930728 0.295428 0.2787446 0.3766231 206s 48 0.395402 -1.021393 1.07953292 -0.4599764 -0.132386 0.1895780 0.2771755 206s 49 2.886100 -0.276587 1.48851137 -0.6314648 -0.203963 -0.0891955 0.1347804 206s 50 -3.255379 2.479232 -0.37933775 -0.3651497 -0.415000 0.0045750 0.0671055 206s 51 1.939333 0.617579 1.57113225 0.0310866 -0.039226 0.0409183 0.1830694 206s 52 5.727154 0.275898 0.58814711 -0.1739820 -0.222791 0.2553797 0.1959402 206s 53 1.207873 0.131451 0.80899235 0.2872465 -0.353544 -0.1697200 -0.0987230 206s 54 0.612921 0.040062 0.17807459 -0.0053074 -0.202244 -0.0671788 0.0530276 206s 55 -0.399075 -0.727144 0.26196635 0.3657576 -0.192705 0.0903564 0.0641289 206s 56 0.240719 0.733792 -0.05030509 0.0967214 -0.186906 0.0310231 -0.0594812 206s 57 1.589641 0.289427 -1.02478822 0.2723190 -0.048378 0.2599262 -0.2040853 206s 58 0.423483 -1.262515 -0.85026016 0.4749963 -0.082647 0.0752412 0.1352259 206s 59 1.983684 1.335122 0.42593757 0.1345894 0.096456 0.1153107 -0.0385994 206s 60 1.770171 0.935428 0.14901569 0.3641973 0.274015 -0.0280119 0.0690244 206s 61 0.182845 1.706453 -0.18364654 0.2517421 -0.035773 0.0357087 -0.1363470 206s 62 -2.191617 1.966324 -0.03573689 -0.2203900 -0.235704 0.1682332 -0.1145174 206s 63 -2.442239 -0.209694 -0.06681921 0.3184048 0.206772 -0.0608468 0.2425649 206s 64 -2.442239 -0.209694 -0.06681921 0.3184048 0.206772 -0.0608468 0.2425649 206s 65 0.407575 2.996346 -0.63021113 -0.1335795 0.087668 0.0627032 0.0486166 206s 66 2.660379 1.322824 0.10122110 0.2420451 0.192938 0.0344019 -0.0771918 206s 67 -0.032273 1.315299 -0.04511689 -0.1293380 -0.025923 -0.1655965 0.1887534 206s 68 1.117637 2.005809 1.97078787 -0.0429209 -0.176568 0.1634287 -0.0916254 206s 69 0.970730 0.837158 0.01621375 0.2347502 -0.071757 -0.2464626 0.2907551 206s 70 -2.688271 -5.335891 -0.64225481 4.1819517 -9.523550 2.0943027 -2.8098426 206s 71 2.428718 1.976051 -0.24749122 0.1308738 0.018276 0.1711292 0.1346284 206s 72 -2.061944 0.405943 0.50472914 0.4393739 -0.056420 -0.0031558 0.2663880 206s 73 2.029606 2.874991 0.68310320 -0.2067254 0.511537 -0.2010371 0.0805608 206s 74 11.293757 0.328931 -3.84783031 -0.4130266 -0.210499 -0.1103148 -0.0381326 206s 75 0.120896 2.287914 0.83639076 -0.2462845 0.551353 0.6629701 0.3789055 206s 76 1.859499 0.422019 1.18435547 0.1546108 0.017266 0.0470615 -0.1071011 206s 77 8.435857 1.147499 -2.19924186 -0.4156770 0.386548 0.0294075 -0.1911399 206s 78 -1.090858 1.311287 0.62897430 0.1727009 0.077341 0.0135972 -0.0096934 206s 79 0.560012 0.623617 0.83727267 0.1680787 0.087477 0.0611949 -0.2588084 206s 80 3.873817 -1.133641 -1.27469019 -0.2717298 -0.165066 0.1696232 0.0635047 206s 81 -0.758664 -0.880260 0.00057124 0.2838720 0.016243 0.1527299 -0.0150514 206s 82 -2.709588 1.464049 -0.12598126 -0.3828567 0.213647 -0.1425385 0.1552827 206s 83 -2.213670 0.059563 0.87565603 0.1255703 -0.082005 0.2189829 -0.2938264 206s 84 -0.242242 -0.483552 2.05089334 -0.0681005 -0.101578 0.1304632 -0.2218093 206s 85 -1.032129 2.375018 -2.19321259 0.2332079 -0.066379 0.1854598 -0.0873859 206s 86 0.015327 -0.948155 1.39530555 0.2701225 -0.268889 0.0578145 0.1608678 206s PC8 206s 1 2.1835e-03 206s 2 1.6801e-03 206s 3 1.6623e-03 206s 4 2.6286e-04 206s 5 9.5884e-04 206s 6 1.4430e-03 206s 7 1.8784e-04 206s 8 6.8473e-04 206s 9 -6.8490e-04 206s 10 1.1565e-04 206s 11 5.6907e-06 206s 12 -1.8395e-03 206s 13 -2.1582e-03 206s 14 -1.6294e-03 206s 15 -1.6964e-03 206s 16 -1.9664e-03 206s 17 -2.2448e-03 206s 18 -6.5884e-04 206s 19 -1.1536e-03 206s 20 2.6887e-04 206s 21 3.3199e-05 206s 22 1.1170e-04 206s 23 -1.7617e-04 206s 24 -2.1577e-04 206s 25 -6.1495e-04 206s 26 -7.2903e-04 206s 27 -6.8773e-04 206s 28 -2.0742e-04 206s 29 -2.6937e-04 206s 30 -6.7472e-05 206s 31 -1.3222e-04 206s 32 -1.6516e-04 206s 33 -1.8836e-04 206s 34 -1.1273e-04 206s 35 3.0703e-05 206s 36 -3.0311e-04 206s 37 -1.9380e-04 206s 38 5.5526e-04 206s 39 4.1987e-04 206s 40 8.4807e-05 206s 41 8.8725e-04 206s 42 -6.5647e-04 206s 43 4.3202e-04 206s 44 -5.3330e-04 206s 45 8.9161e-04 206s 46 1.1588e-03 206s 47 -1.2714e-03 206s 48 -4.0376e-04 206s 49 4.1280e-06 206s 50 3.0116e-04 206s 51 5.8510e-05 206s 52 3.3236e-04 206s 53 4.0982e-04 206s 54 4.0428e-04 206s 55 6.1600e-04 206s 56 -4.0496e-05 206s 57 -1.8342e-04 206s 58 -1.6748e-04 206s 59 -1.0894e-03 206s 60 -2.6876e-04 206s 61 -5.8951e-05 206s 62 -1.5517e-04 206s 63 -7.9933e-04 206s 64 -7.9933e-04 206s 65 2.2592e-05 206s 66 2.4984e-05 206s 67 -2.2714e-04 206s 68 -3.3991e-04 206s 69 -3.0375e-04 206s 70 3.4033e-03 206s 71 2.3288e-05 206s 72 -3.4126e-04 206s 73 2.5528e-04 206s 74 2.2760e-03 206s 75 -2.8985e-04 206s 76 7.9077e-04 206s 77 9.4636e-04 206s 78 4.9099e-04 206s 79 3.0501e-04 206s 80 6.5280e-04 206s 81 -3.6570e-04 206s 82 4.9966e-04 206s 83 -4.3245e-04 206s 84 -4.6152e-04 206s 85 7.4691e-04 206s 86 -6.1103e-04 206s ------------- 206s Call: 206s PcaHubert(x = x, k = p) 206s 206s Standard deviations: 206s [1] 2.39577535 1.55089079 0.92557331 0.33680677 0.19792033 0.17855133 0.16041702 206s [8] 0.00054179 206s ---------------------------------------------------------- 206s bushfire 38 5 5 31248.552973 358.974577 206s Scores: 206s PC1 PC2 PC3 PC4 PC5 206s 1 155.972 1.08098 -23.31135 -1.93015 1.218941 206s 2 157.738 0.35648 -20.95658 -2.42375 0.466415 206s 3 150.667 2.12545 -16.20395 -2.00140 -0.582924 206s 4 133.892 5.25124 -15.88873 -2.78469 -0.275261 206s 5 102.462 13.00611 -21.54096 -4.69409 -0.944176 206s 6 77.694 18.75377 -28.71865 -6.44244 0.446350 206s 7 286.266 -11.36184 -98.67134 10.95233 -3.625338 206s 8 326.627 29.92767 -112.60824 -29.26330 -13.710094 206s 9 327.898 32.39553 -113.34314 -31.65905 -13.830781 206s 10 325.131 5.81628 -105.58927 -13.45695 -8.987971 206s 11 326.458 -7.84562 -94.25242 -6.11547 -8.572845 206s 12 333.171 -37.69907 -50.89207 8.98187 -1.742979 206s 13 279.789 -40.78415 -8.06209 7.65884 0.181748 206s 14 37.714 10.54231 13.46530 -1.55051 2.102662 206s 15 -90.034 34.68964 18.98186 0.69260 0.417573 206s 16 -46.492 23.65086 10.07282 4.36090 -0.748517 206s 17 -43.990 20.36443 9.61049 2.83084 -0.127983 206s 18 -32.938 19.11199 2.64850 2.92879 -1.473988 206s 19 -36.555 20.60142 2.01879 0.63832 -1.235075 206s 20 -46.837 19.89630 6.65142 0.89120 0.271108 206s 21 -28.670 15.29534 6.59311 3.29638 0.402194 206s 22 -20.331 15.06559 7.33721 2.16591 2.006327 206s 23 108.644 -7.92707 -1.45130 6.27388 0.356715 206s 24 163.697 -16.15568 0.61663 4.24231 0.464415 206s 25 100.471 -0.30739 0.87762 2.86452 -0.692735 206s 26 106.922 0.90864 -1.91436 2.54557 -0.565023 206s 27 121.966 -3.29641 4.85626 -0.47676 -0.490047 206s 28 98.650 -4.51455 16.64160 -3.08996 -0.839397 206s 29 88.795 -10.85457 30.46708 -5.37360 0.315657 206s 30 142.981 -27.89100 22.40713 -1.67126 -0.680158 206s 31 14.125 -21.60028 29.80480 -8.25272 -0.019693 206s 32 -244.044 -11.76430 24.53390 -12.52294 2.022312 206s 33 -283.842 -13.21931 -6.23565 -2.63367 -0.080728 206s 34 -280.168 -13.41903 -7.69318 -1.24571 -0.722513 206s 35 -285.666 -13.78452 -6.50318 -1.23756 1.074669 206s 36 -282.938 -13.82281 -7.63902 0.20435 -0.971673 206s 37 -281.129 -16.20408 -8.57154 1.85797 0.234486 206s 38 -282.589 -16.91969 -8.36010 2.35589 0.490630 206s ------------- 206s Call: 206s PcaHubert(x = x, k = p) 206s 206s Standard deviations: 206s [1] 176.77260 18.94662 16.21701 3.95755 0.92761 206s ---------------------------------------------------------- 206s ========================================================== 206s > dodata(method="hubert") 206s 206s Call: dodata(method = "hubert") 206s Data Set n p k e1 e2 206s ========================================================== 206s heart 12 2 1 315.227002 NA 206s Scores: 206s PC1 206s 1 13.2197 206s 2 69.9817 206s 3 6.6946 206s 4 2.8899 206s 5 24.9956 206s 6 -8.9203 206s 7 12.0121 206s 8 -24.1915 206s 9 4.2721 206s 10 -22.8289 206s 11 -8.1433 206s 12 54.6519 206s ------------- 206s Call: 206s PcaHubert(x = x, mcd = FALSE) 206s 206s Standard deviations: 206s [1] 17.755 206s ---------------------------------------------------------- 206s starsCYG 47 2 1 0.308922 NA 206s Scores: 206s PC1 206s 1 0.224695 206s 2 0.758653 206s 3 -0.089113 206s 4 0.758653 206s 5 0.173934 206s 6 0.466195 206s 7 -0.433154 206s 8 0.296411 206s 9 0.542517 206s 10 0.116133 206s 11 0.576303 206s 12 0.451490 206s 13 0.429942 206s 14 -0.997904 206s 15 -0.745515 206s 16 -0.408745 206s 17 -1.071002 206s 18 -0.803514 206s 19 -0.834141 206s 20 0.734210 206s 21 -0.627085 206s 22 -0.784992 206s 23 -0.566652 206s 24 -0.130992 206s 25 0.019053 206s 26 -0.329791 206s 27 -0.350747 206s 28 -0.099378 206s 29 -0.628499 206s 30 0.890506 206s 31 -0.573100 206s 32 0.127022 206s 33 0.227721 206s 34 1.128979 206s 35 -0.676234 206s 36 0.649894 206s 37 0.122186 206s 38 0.227721 206s 39 0.201140 206s 40 0.569920 206s 41 -0.375716 206s 42 0.069814 206s 43 0.354212 206s 44 0.346152 206s 45 0.559656 206s 46 -0.009140 206s 47 -0.487699 206s ------------- 206s Call: 206s PcaHubert(x = x, mcd = FALSE) 206s 206s Standard deviations: 206s [1] 0.55581 206s ---------------------------------------------------------- 206s phosphor 18 2 1 215.172048 NA 206s Scores: 206s PC1 206s 1 1.12634 206s 2 -22.10340 206s 3 -23.49216 206s 4 -13.45927 206s 5 -18.60808 206s 6 11.24086 206s 7 -0.14748 206s 8 -9.77075 206s 9 -10.37022 206s 10 12.71798 206s 11 -4.61857 206s 12 10.07037 206s 13 13.16767 206s 14 7.57254 206s 15 17.81362 206s 16 -11.08799 206s 17 21.70358 206s 18 18.24496 206s ------------- 206s Call: 206s PcaHubert(x = x, mcd = FALSE) 206s 206s Standard deviations: 206s [1] 14.669 206s ---------------------------------------------------------- 206s stackloss 21 3 2 77.038636 18.859777 206s Scores: 206s PC1 PC2 206s 1 -20.334936 10.28081 206s 2 -19.772121 11.10736 206s 3 -16.461573 6.43794 206s 4 -4.258672 1.73213 206s 5 -3.773146 1.41928 206s 6 -4.015909 1.57571 206s 7 -7.635560 -3.22715 206s 8 -7.635560 -3.22715 206s 9 -0.855388 -0.58707 206s 10 4.298129 4.41664 206s 11 -0.767202 -3.02229 206s 12 0.038375 -2.35217 206s 13 3.172500 2.76354 206s 14 -3.261224 -6.17206 206s 15 5.553840 -7.34784 206s 16 7.242284 -4.86820 206s 17 14.878925 6.85989 206s 18 10.939223 1.07406 206s 19 10.133645 0.40394 206s 20 4.267234 1.99501 206s 21 -11.859921 2.12579 206s ------------- 206s Call: 206s PcaHubert(x = x, mcd = FALSE) 206s 206s Standard deviations: 206s [1] 8.7772 4.3428 206s ---------------------------------------------------------- 206s salinity 28 3 2 8.001175 5.858089 206s Scores: 206s PC1 PC2 206s 1 2.858444 1.04359 206s 2 3.807704 1.55974 206s 3 6.220733 -4.32114 206s 4 6.388841 -2.83649 206s 5 6.077450 -3.70092 206s 6 5.974494 -0.67230 206s 7 4.531584 0.78322 206s 8 2.725849 2.41297 206s 9 0.100501 -2.13615 206s 10 -2.358003 -1.49718 206s 11 -1.317688 -1.15391 206s 12 0.434635 0.58230 206s 13 0.116019 1.79022 206s 14 -1.771501 2.71749 206s 15 -2.630757 -2.44003 206s 16 2.289743 -5.51829 206s 17 0.637985 -1.26452 206s 18 3.076147 0.19883 206s 19 0.097381 -1.95868 206s 20 -1.572471 -0.93003 206s 21 -1.284185 2.21858 206s 22 -2.531713 3.30313 206s 23 -3.865359 -3.01230 206s 24 -2.143461 -2.41918 206s 25 -0.714414 -0.41227 206s 26 -1.327781 1.18373 206s 27 -2.201166 2.41566 206s 28 -2.931988 3.20536 206s ------------- 206s Call: 206s PcaHubert(x = x, mcd = FALSE) 206s 206s Standard deviations: 206s [1] 2.8286 2.4203 206s ---------------------------------------------------------- 206s hbk 75 3 3 1.459908 1.201048 206s Scores: 206s PC1 PC2 PC3 206s 1 31.105415 -4.714217 -10.4566165 206s 2 31.707650 -5.748724 -10.7682402 206s 3 33.366131 -4.625897 -12.1570167 206s 4 34.173377 -6.069657 -12.4466895 206s 5 33.780418 -5.508823 -11.9872893 206s 6 32.493478 -4.684595 -10.5679819 206s 7 32.592637 -5.235522 -10.3765493 206s 8 31.293363 -4.865797 -10.9379676 206s 9 33.160964 -5.714260 -12.3098920 206s 10 31.919786 -5.384537 -12.3374332 206s 11 38.231962 -6.810641 -13.5994385 206s 12 39.290479 -5.393906 -15.2942554 206s 13 39.418445 -7.326461 -11.5194898 206s 14 43.906584 -13.214819 -8.3282743 206s 15 1.906326 0.716061 0.8635112 206s 16 0.263255 0.926016 1.9009292 206s 17 -1.776489 -1.072332 0.5496140 206s 18 0.464648 0.702441 -0.0482897 206s 19 0.267826 -1.283779 0.2925812 206s 20 2.122108 0.165970 0.8924686 206s 21 0.937217 0.548532 0.4132196 206s 22 0.423273 -1.781869 0.0323061 206s 23 0.047532 0.018909 1.1259327 206s 24 -0.490041 -0.520202 1.1065753 206s 25 -2.143049 0.720869 0.0495474 206s 26 1.094748 -1.459175 -0.2226246 206s 27 2.070705 0.898573 -0.0023229 206s 28 -0.294998 0.830258 -0.5929001 206s 29 -1.242995 0.300216 0.2010507 206s 30 0.147958 0.439099 -2.0003038 206s 31 0.170818 1.440946 0.9755627 206s 32 -0.958531 -1.199730 1.0129867 206s 33 0.697307 -0.874343 0.7260649 206s 34 -2.278946 0.261106 -0.4196544 206s 35 1.962829 0.809318 -0.2033113 206s 36 0.626631 -0.600666 -0.8004036 206s 37 0.550885 -1.881448 -0.7382776 206s 38 -1.249717 0.336214 0.9349845 206s 39 -1.106696 1.569418 -0.1869576 206s 40 -0.684034 -0.939963 0.1034965 206s 41 1.559314 1.551408 -0.3660323 206s 42 -0.538741 -0.447358 -1.6361099 206s 43 -0.252685 -2.080564 0.7765259 206s 44 0.217012 1.027281 -1.7015154 206s 45 -1.497600 1.349234 0.2698932 206s 46 0.100388 1.026443 -1.5390401 206s 47 -0.811117 2.195271 0.5208141 206s 48 1.462210 1.321318 -0.5600144 206s 49 1.383976 0.740714 0.7348906 206s 50 1.636773 -0.215464 -0.3195369 206s 51 -0.530918 0.759743 1.2069247 206s 52 -0.109566 2.107455 0.5315473 206s 53 -0.564334 -0.060847 -2.3910630 206s 54 -0.272234 -1.122711 1.5060028 206s 55 -0.608660 -1.197219 0.5255609 206s 56 0.565430 -0.710345 1.3708230 206s 57 -1.115629 0.888816 0.4186014 206s 58 1.351288 -0.374815 1.1980618 206s 59 0.998016 -0.151228 -0.9007970 206s 60 0.124017 -0.764846 -1.9005963 206s 61 1.189858 -1.905264 -0.7721322 206s 62 -2.190589 0.579614 0.1377914 206s 63 -0.518278 -0.931130 1.4534768 206s 64 2.124566 0.194391 0.0327092 206s 65 0.154218 1.050861 -1.1309885 206s 66 -1.197852 -1.044147 0.2265269 206s 67 -0.114174 -0.094763 0.5168926 206s 68 -2.201115 0.032271 -0.8573493 206s 69 -1.307843 1.104815 0.7741270 206s 70 0.691449 -0.676665 -1.0004603 206s 71 1.150975 0.050861 0.0717068 206s 72 -0.457293 -0.861871 -0.1026350 206s 73 -0.392258 -0.897451 -0.9178065 206s 74 -0.584658 -1.450471 -0.3201857 206s 75 -0.972517 -0.063777 -1.8223995 206s ------------- 206s Call: 206s PcaHubert(x = x, mcd = FALSE) 206s 206s Standard deviations: 206s [1] 1.2083 1.0959 1.0168 206s ---------------------------------------------------------- 206s milk 86 8 2 6.040806 2.473780 206s Scores: 206s PC1 PC2 206s 1 -5.768003 -0.9174359 206s 2 -6.664422 0.0280812 206s 3 -0.484521 1.7923710 206s 4 -5.211590 2.0747301 206s 5 1.422641 -0.3268437 206s 6 -1.810360 -0.5469828 206s 7 -2.402924 -0.1987041 206s 8 -2.553389 -0.4963662 206s 9 1.583399 2.5410448 206s 10 3.267946 0.9141367 206s 11 9.924771 0.6501301 206s 12 13.628569 -2.3009846 206s 13 10.774550 -1.1628697 206s 14 12.716376 -1.0670330 206s 15 11.176408 0.7403371 206s 16 3.209269 -0.0804317 206s 17 1.256577 2.8931153 206s 18 2.468720 -1.2008647 206s 19 2.253229 0.8379608 206s 20 0.021073 1.6394221 206s 21 3.205298 -2.3518286 206s 22 1.470733 -0.9618655 206s 23 0.475732 -1.7044535 206s 24 0.930144 -1.3288398 206s 25 4.151553 -2.2882554 206s 26 1.314488 -1.3527439 206s 27 3.613405 -0.0813605 206s 28 -1.909178 -3.6473200 206s 29 -3.987263 -1.3255834 206s 30 -0.370601 -1.5855086 206s 31 -1.273254 -2.1892809 206s 32 -0.816634 -0.4514478 206s 33 -1.553394 -0.2792004 206s 34 -0.275027 0.6359374 206s 35 0.980782 -2.2353223 206s 36 -3.678470 -1.3459182 206s 37 -0.327102 -2.5615283 206s 38 -1.563492 -2.2008288 206s 39 1.876146 -1.0292641 206s 40 -3.204182 1.6694332 206s 41 -3.561892 -1.5844770 206s 42 -6.175135 1.0123714 206s 43 -2.736601 -0.7040261 206s 44 -4.981783 0.2434304 206s 45 0.368802 -0.5011413 206s 46 0.369508 -1.9511091 206s 47 -2.306673 -0.0089446 206s 48 0.215195 -1.1000357 206s 49 2.704678 -0.5919929 206s 50 -2.930879 2.7161936 206s 51 1.846250 0.3732500 206s 52 5.661288 -0.3139157 206s 53 1.154929 -0.0575094 206s 54 0.625715 -0.0733934 206s 55 -0.453714 -0.7535924 206s 56 0.343722 0.6460318 206s 57 1.743002 0.0794685 206s 58 0.433705 -1.3500731 206s 59 2.078550 1.0860506 206s 60 1.867913 0.7162287 206s 61 0.392645 1.6184583 206s 62 -1.958732 2.0993596 206s 63 -2.383251 -0.0253919 206s 64 -2.383251 -0.0253919 206s 65 0.780239 2.9018927 206s 66 2.785329 1.0142893 206s 67 0.131210 1.2703167 206s 68 1.110073 1.8140467 206s 69 1.076878 0.6954148 206s 70 -3.260160 -5.6233069 206s 71 2.647036 1.6892084 206s 72 -2.017340 0.5353349 206s 73 2.247524 2.6406249 206s 74 11.649291 -0.7374197 206s 75 0.280544 2.2306959 206s 76 1.791213 0.1796005 206s 77 8.730344 0.3412271 206s 78 -0.987405 1.3467910 206s 79 0.560808 0.5006661 206s 80 3.897879 -1.5270179 206s 81 -0.792759 -0.8649399 206s 82 -2.493611 1.6796838 206s 83 -2.245966 0.1889555 206s 84 -0.468812 -0.5359088 206s 85 -0.538372 2.4105954 206s 86 -0.185347 -1.0176989 206s ------------- 206s Call: 206s PcaHubert(x = x, mcd = FALSE) 206s 206s Standard deviations: 206s [1] 2.4578 1.5728 206s ---------------------------------------------------------- 206s bushfire 38 5 1 38435.075910 NA 206s Scores: 206s PC1 206s 1 -111.9345 206s 2 -113.4128 206s 3 -105.8364 206s 4 -89.1684 206s 5 -58.7216 206s 6 -35.0370 206s 7 -250.2123 206s 8 -292.6877 206s 9 -294.0765 206s 10 -290.0193 206s 11 -289.8168 206s 12 -290.8645 206s 13 -232.6865 206s 14 9.8483 206s 15 137.1924 206s 16 92.9804 206s 17 90.4493 206s 18 78.6325 206s 19 82.1178 206s 20 92.9044 206s 21 74.9157 206s 22 66.7350 206s 23 -62.1981 206s 24 -116.5696 206s 25 -53.8907 206s 26 -60.6384 206s 27 -74.7621 206s 28 -50.2202 206s 29 -38.7483 206s 30 -93.3887 206s 31 35.3096 206s 32 290.8493 206s 33 326.7236 206s 34 322.9095 206s 35 328.5307 206s 36 325.6791 206s 37 323.8136 206s 38 325.2991 206s ------------- 206s Call: 206s PcaHubert(x = x, mcd = FALSE) 206s 206s Standard deviations: 206s [1] 196.05 206s ---------------------------------------------------------- 206s ========================================================== 206s > 206s > dodata(method="locantore") 206s 206s Call: dodata(method = "locantore") 206s Data Set n p k e1 e2 206s ========================================================== 206s heart 12 2 2 1.835912 0.084745 206s Scores: 206s PC1 PC2 206s [1,] 7.3042 1.745289 206s [2,] 64.6474 0.164425 206s [3,] 1.1057 -1.404189 206s [4,] -3.1943 2.565728 206s [5,] 19.4154 -0.401369 206s [6,] -15.5709 6.666752 206s [7,] 5.9980 2.509372 206s [8,] -29.5933 -4.805972 206s [9,] -1.3933 -0.899323 206s [10,] -28.2845 -4.270057 206s [11,] -14.0069 0.048311 206s [12,] 49.1484 0.694598 206s ------------- 206s Call: 206s PcaLocantore(x = x) 206s 206s Standard deviations: 206s [1] 1.35496 0.29111 206s ---------------------------------------------------------- 206s starsCYG 47 2 2 0.779919 0.050341 206s Scores: 206s PC1 PC2 206s [1,] 0.174291 -0.0489127 206s [2,] 0.703776 0.0769650 206s [3,] -0.136954 -0.1212071 206s [4,] 0.703776 0.0769650 206s [5,] 0.125991 -0.1134658 206s [6,] 0.413609 0.0121367 206s [7,] -0.466451 -0.5036094 206s [8,] 0.238569 0.1446547 206s [9,] 0.498194 -0.1998666 206s [10,] 0.065125 -0.0353931 206s [11,] 0.562344 -0.9836936 206s [12,] 0.399997 -0.0164068 206s [13,] 0.376370 0.0369013 206s [14,] -1.041009 -0.2611550 206s [15,] -0.798187 -0.0090880 206s [16,] -0.464636 0.0805967 206s [17,] -1.123135 -0.0293034 206s [18,] -0.861603 0.1297588 206s [19,] -0.884955 -0.0588007 206s [20,] 0.721130 -1.0033585 206s [21,] -0.679097 -0.0238366 206s [22,] -0.837884 -0.0041718 206s [23,] -0.623423 0.1002615 206s [24,] -0.188079 0.1168815 206s [25,] -0.032888 -0.0131784 206s [26,] -0.385242 0.0707643 206s [27,] -0.401220 -0.0582501 206s [28,] -0.151978 0.0015702 206s [29,] -0.677776 -0.0945350 206s [30,] 0.878688 -1.0329475 206s [31,] -0.628339 0.0605648 206s [32,] 0.068629 0.1556245 206s [33,] 0.174199 0.0317098 206s [34,] 1.118098 -1.0525206 206s [35,] -0.726168 -0.0784655 206s [36,] 0.592061 0.1512588 206s [37,] 0.064942 0.1258519 206s [38,] 0.174199 0.0317098 206s [39,] 0.144335 0.1160195 206s [40,] 0.519088 -0.0311555 206s [41,] -0.429855 0.0359837 206s [42,] 0.015412 0.0513747 206s [43,] 0.299435 0.0665821 206s [44,] 0.293289 0.0169612 206s [45,] 0.504064 0.0916219 206s [46,] -0.063981 0.0612071 206s [47,] -0.544029 0.0904291 206s ------------- 206s Call: 206s PcaLocantore(x = x) 206s 206s Standard deviations: 206s [1] 0.88313 0.22437 206s ---------------------------------------------------------- 206s phosphor 18 2 2 0.933905 0.279651 206s Scores: 206s PC1 PC2 206s 1 4.5660 -15.58981 206s 2 -21.2978 -0.38905 206s 3 -23.3783 3.96546 206s 4 -11.7131 -5.79023 206s 5 -18.2569 2.81141 206s 6 15.5702 -20.54935 206s 7 1.3671 -3.27043 206s 8 -9.4859 3.92005 206s 9 -10.4501 6.22662 206s 10 15.0583 -7.60532 206s 11 -3.9078 1.56960 206s 12 10.0330 7.52732 206s 13 13.4815 5.50056 206s 14 7.5487 7.24752 206s 15 18.6543 2.46040 206s 16 -9.3301 -5.68285 206s 17 22.2533 4.63689 206s 18 17.7892 10.85633 206s ------------- 206s Call: 206s PcaLocantore(x = x) 206s 206s Standard deviations: 206s [1] 0.96639 0.52882 206s ---------------------------------------------------------- 206s stackloss 21 3 3 1.137747 0.196704 206s Scores: 206s PC1 PC2 PC3 206s [1,] 19.98046 -6.20875 -3.93576 206s [2,] 19.57014 -7.11509 -4.03666 206s [3,] 15.48729 -3.14247 -3.29600 206s [4,] 3.12341 -1.38969 1.50633 206s [5,] 2.35380 -0.84492 -0.25745 206s [6,] 2.73860 -1.11731 0.62444 206s [7,] 5.58533 4.04837 2.11170 206s [8,] 5.58533 4.04837 2.11170 206s [9,] -0.56851 0.17483 2.46656 206s [10,] -5.36478 -4.80766 -2.64915 206s [11,] -1.67190 3.34943 -1.74110 206s [12,] -2.46702 2.71547 -2.72389 206s [13,] -4.54414 -2.99497 -2.44736 206s [14,] 0.35419 6.70241 -0.45563 206s [15,] -8.28612 5.93369 1.94314 206s [16,] -9.51708 3.21466 1.64046 206s [17,] -14.87676 -9.74652 1.10983 206s [18,] -12.00452 -3.40212 1.81609 206s [19,] -11.20939 -2.76816 2.79887 206s [20,] -5.42808 -2.89367 0.23748 206s [21,] 9.83969 0.74095 -5.30190 206s ------------- 206s Call: 206s PcaLocantore(x = x) 206s 206s Standard deviations: 206s [1] 1.06665 0.44351 0.33935 206s ---------------------------------------------------------- 206s salinity 28 3 3 1.038873 0.621380 206s Scores: 206s PC1 PC2 PC3 206s 1 -2.7215590 -0.98924 0.3594538 206s 2 -3.6251829 -1.03361 1.4973993 206s 3 -6.0588883 4.23861 -1.1012038 206s 4 -6.2741857 2.42372 -1.4875092 206s 5 -5.7274076 5.42190 2.9332011 206s 6 -5.8431892 0.57161 -0.3385363 206s 7 -4.4051377 -0.83292 0.0851817 206s 8 -2.6155827 -2.50739 0.3386166 206s 9 -0.0426575 1.19631 -2.5025726 206s 10 2.5297488 1.65029 -0.0110335 206s 11 1.5528097 1.93255 1.4216262 206s 12 -0.3140451 -0.73269 -0.1961364 206s 13 0.0010783 -1.88658 0.1849912 206s 14 1.9554303 -2.13519 1.8471356 206s 15 2.7897250 2.40211 -0.6327944 206s 16 -1.7665706 8.69449 5.6608836 206s 17 -0.4374125 1.72696 0.7230753 206s 18 -2.9752196 -0.54118 -0.6829760 206s 19 -0.0599346 0.84127 -2.8473543 206s 20 1.6597909 0.34191 -1.4847516 206s 21 1.3857395 -2.43924 0.0039271 206s 22 2.6664754 -3.14291 1.0600254 206s 23 4.1202067 3.81886 1.0608640 206s 24 2.4163743 3.45141 1.6874099 206s 25 0.8493897 0.31424 -0.3073115 206s 26 1.4216265 -1.55310 -0.5455012 206s 27 2.3021676 -2.63392 0.0481451 206s 28 3.0877115 -2.85951 1.4378956 206s ------------- 206s Call: 206s PcaLocantore(x = x) 206s 206s Standard deviations: 206s [1] 1.01925 0.78828 0.36470 206s ---------------------------------------------------------- 206s hbk 75 3 3 1.038833 0.363386 206s Scores: 206s PC1 PC2 PC3 206s 1 32.393698 -3.4318297 0.051248 206s 2 33.103072 -4.4154651 0.294662 206s 3 35.038965 -3.5996035 -0.940929 206s 4 35.955809 -4.9285404 -0.479059 206s 5 35.424918 -4.3076292 -0.366699 206s 6 33.753497 -3.2463136 0.289013 206s 7 33.817375 -3.6819421 0.684167 206s 8 32.717119 -3.7074394 -0.279567 206s 9 34.932190 -4.6939061 -0.738196 206s 10 33.737339 -4.5702346 -1.193206 206s 11 40.202273 -5.4336890 -0.229323 206s 12 41.638189 -4.5304173 -1.996311 206s 13 40.768565 -5.0531048 2.123222 206s 14 44.408749 -8.8448536 8.236462 206s 15 0.977343 1.3057899 0.938694 206s 16 -0.900390 1.6169842 1.382855 206s 17 -2.384467 -0.9835430 0.375495 206s 18 -0.143306 0.7859701 -0.237712 206s 19 -0.344479 -0.9791245 0.733869 206s 20 1.199115 0.8330752 1.216827 206s 21 0.184475 0.8630593 0.351029 206s 22 -0.100389 -1.5084406 0.718236 206s 23 -0.847925 0.4823829 0.958677 206s 24 -1.334366 -0.1021190 1.000300 206s 25 -2.669352 0.4692990 -0.811134 206s 26 0.601538 -1.1984283 0.541627 206s 27 1.373423 1.2098621 0.136249 206s 28 -0.721268 0.6164612 -0.963817 206s 29 -1.832615 0.2543279 -0.297658 206s 30 0.120086 -0.1558590 -1.976558 206s 31 -0.747437 1.7749106 0.342824 206s 32 -1.727558 -0.8325772 1.043088 206s 33 -0.073907 -0.3923823 1.083904 206s 34 -2.646454 -0.1350138 -1.101448 206s 35 1.331096 1.0443905 -0.039328 206s 36 0.281192 -0.6569943 -0.404009 206s 37 0.245349 -1.8406517 0.093656 206s 38 -2.049446 0.5320301 0.347219 206s 39 -1.645547 1.3268749 -1.068792 206s 40 -1.216874 -0.8556007 0.201262 206s 41 0.959445 1.6250030 -0.553881 206s 42 -0.603579 -0.9569812 -1.502730 206s 43 -0.946870 -1.6333180 1.324763 206s 44 0.076217 0.5018427 -1.902369 206s 45 -2.140584 1.2192726 -0.677180 206s 46 -0.081677 0.5389288 -1.785347 206s 47 -1.590461 2.1881067 -0.583771 206s 48 0.931421 1.3321181 -0.669782 206s 49 0.512639 1.2123979 0.683099 206s 50 1.095415 0.0045968 0.143109 206s 51 -1.456417 1.1186245 0.619657 206s 52 -0.917904 2.2084467 -0.366392 206s 53 -0.429654 -0.8524437 -2.326637 206s 54 -1.213858 -0.4996891 1.630709 206s 55 -1.253877 -0.9438354 0.692022 206s 56 -0.390657 -0.0427482 1.571167 206s 57 -1.797537 0.8934866 -0.281980 206s 58 0.396886 0.3227454 1.492494 206s 59 0.646360 -0.2194210 -0.562699 206s 60 0.119900 -1.2480691 -1.459763 206s 61 0.867946 -1.7843458 0.232229 206s 62 -2.733997 0.3604288 -0.692947 206s 63 -1.442683 -0.3732483 1.452800 206s 64 1.444934 0.5727959 0.434633 206s 65 -0.147284 0.7055205 -1.413940 206s 66 -1.739552 -0.9838385 0.220303 206s 67 -0.824644 0.1503195 0.411693 206s 68 -2.437638 -0.4835278 -1.392882 206s 69 -2.091970 1.1865192 -0.088483 206s 70 0.403429 -0.7855276 -0.540161 206s 71 0.507512 0.3152001 0.276885 206s 72 -0.944376 -0.8197825 0.044859 206s 73 -0.648597 -1.1160277 -0.658528 206s 74 -0.979453 -1.4589411 0.029182 206s 75 -0.982282 -0.7226425 -1.917060 206s ------------- 206s Call: 206s PcaLocantore(x = x) 206s 206s Standard deviations: 206s [1] 1.01923 0.60282 0.46137 206s ---------------------------------------------------------- 206s milk 86 8 8 1.175171 0.426506 206s Scores: 206s PC1 PC2 PC3 PC4 PC5 PC6 206s [1,] 6.1907998 0.58762698 0.686510 -0.209679 0.3321757 -1.3424985 206s [2,] 7.0503894 -0.49576086 -0.322697 -0.767415 -0.0165833 -1.4596064 206s [3,] 0.7670594 -1.83556812 0.468814 0.346810 -0.0204610 -0.2115383 206s [4,] 5.4656748 -2.29797862 1.612819 -0.378295 -0.2050232 0.3486957 206s [5,] -1.0291160 0.37303007 0.634604 -0.521527 -0.3299543 0.0859469 206s [6,] 2.2186300 0.39396818 -0.236987 -0.033975 -0.2549238 0.2541221 206s [7,] 2.7938591 -0.01152811 -0.600546 -0.098564 -0.3906602 0.3798516 206s [8,] 2.9544176 0.32646226 0.273051 -0.275073 -0.3982959 0.2377581 206s [9,] -1.3344639 -2.45440308 1.001792 -0.104783 -0.1744718 -0.0887272 206s [10,] -2.9294174 -0.79860558 -0.260533 0.375330 0.3425169 -0.2056682 206s [11,] -9.5810648 -0.09577968 1.565111 -0.112002 0.3143032 -0.3190238 206s [12,] -13.1147240 2.95665890 0.228086 -0.180867 0.0136463 -0.4604390 206s [13,] -10.2989319 1.53220781 -2.244629 0.323950 -0.0398642 -0.3463501 206s [14,] -12.2553418 1.62281167 -0.472862 -0.212983 -0.4124280 -0.4253719 206s [15,] -10.8346894 -0.09781844 2.134079 -0.272304 -0.1090226 -0.3725738 206s [16,] -2.8358474 0.28109809 0.945309 0.603249 0.1615955 0.1762086 206s [17,] -1.0353408 -2.75475311 1.677879 0.598578 0.0078965 0.0228522 206s [18,] -2.0271810 1.25894451 -0.266038 -0.168565 -0.3000200 0.2891774 206s [19,] -1.9279394 -0.68339726 1.264416 0.186749 0.3018226 -0.0869321 206s [20,] 0.2568334 -1.62632029 0.854279 -0.088175 0.5458645 0.2217019 206s [21,] -2.7017404 2.45223507 -0.243639 -0.211402 -0.2102323 0.2140100 206s [22,] -1.0386097 0.99459030 0.188462 -0.033434 -0.2857078 -0.1438517 206s [23,] -0.0198126 1.73285416 0.761979 0.005501 0.1671992 -0.0375468 206s [24,] -0.4909448 1.40982693 0.967440 0.521275 0.1625359 -0.0892501 206s [25,] -3.6632699 2.51414455 0.966410 -0.272694 0.0467958 0.1572715 206s [26,] -0.8733564 1.42247465 0.946038 -0.338985 -0.0804141 -0.0080759 206s [27,] -3.2254798 0.26912538 0.799468 0.372442 -0.6886191 -0.0553515 206s [28,] 2.4675785 3.56128696 0.813964 0.118354 -0.1677073 -0.0303774 206s [29,] 4.4177264 1.13316321 0.613509 0.261488 0.4229929 0.1780620 206s [30,] 0.8240097 1.54163297 0.398148 -0.221825 0.0309586 0.0830110 206s [31,] 1.7735990 2.00615332 -1.399933 0.469158 -0.0740282 0.0692312 206s [32,] 1.2348922 0.28918604 -1.239899 0.470999 -0.1511519 -0.3692504 206s [33,] 1.9407276 0.19123540 0.406623 0.389965 0.0994854 -0.0204286 206s [34,] 0.6225565 -0.65636700 0.565253 0.369897 -0.1612501 -0.1774611 206s [35,] -0.4869219 2.26301333 0.071825 0.588101 -0.0579092 -0.0362009 206s [36,] 4.1117242 1.16638974 0.982790 -0.266009 0.0728797 -0.0018914 206s [37,] 0.8415225 2.46677043 -0.526780 0.167456 -0.2370116 -0.0731483 206s [38,] 2.0528334 2.09648023 0.220912 0.206722 -0.1924842 0.0676382 206s [39,] -1.4493644 1.14916103 0.904194 0.455498 0.0678893 -0.1476540 206s [40,] 3.4867792 -1.82367389 0.730183 0.499859 0.2327704 -0.1518819 206s [41,] 4.0222120 1.34765470 0.580852 -0.453301 0.2482908 -1.5306566 206s [42,] 6.4789035 -1.25599522 1.644194 0.381331 0.1699942 0.1847594 206s [43,] 3.1529354 0.44884526 -0.967114 -0.220364 0.0037036 0.0802727 206s [44,] 5.3344976 -0.47975673 0.642789 0.298705 0.9983145 -0.1310548 206s [45,] 0.0325597 0.49900084 0.076948 0.486521 0.1642679 0.1392696 206s [46,] 0.1014401 1.97657735 0.733879 0.127235 0.0650844 -0.0144271 206s [47,] 2.7217685 -0.37859042 -3.696163 0.355401 -0.4123714 0.2114024 206s [48,] 0.2292225 1.01473918 -1.115726 0.434557 0.2668316 0.0103147 206s [49,] -2.2803784 0.59474034 -1.783003 0.549252 0.4660435 -0.0802352 206s [50,] 3.1560404 -2.84820361 0.913015 0.077151 0.5803961 0.0350246 206s [51,] -1.4680905 -0.43078891 -1.733657 0.074684 0.0026718 0.0819023 206s [52,] -5.2469034 0.48385240 -1.246027 0.081379 0.2380924 -0.1663831 206s [53,] -0.7670982 0.00234561 -0.923030 -0.366820 0.1582141 0.0508747 206s [54,] -0.2428655 0.04714401 -0.217187 -0.059549 0.1762969 0.0806339 206s [55,] 0.8723441 0.66109329 -0.224917 -0.360607 -0.0638127 0.1310131 206s [56,] 0.0019700 -0.67624071 0.081304 -0.182908 0.1045597 -0.0281936 206s [57,] -1.3684663 -0.00045069 0.860560 -0.350684 -0.1443970 -0.2270651 206s [58,] 0.0079047 1.36376727 0.750919 -0.437914 -0.1894910 0.2345556 206s [59,] -1.7430794 -1.06973583 -0.569381 -0.055139 -0.1582790 -0.0873605 206s [60,] -1.5171606 -0.69340281 -0.287048 -0.136559 -0.3871182 0.1606979 206s [61,] -0.0955085 -1.64221260 0.263650 -0.265665 -0.0808644 -0.0476862 206s [62,] 2.2259171 -2.22161516 0.426279 0.027834 0.2924338 -0.1784242 206s [63,] 2.7573525 -0.11785122 0.391113 -0.094032 -0.3184760 0.4251268 206s [64,] 2.7573525 -0.11785122 0.391113 -0.094032 -0.3184760 0.4251268 206s [65,] -0.5520071 -2.86186682 0.746248 0.109945 0.0556927 -0.0135739 206s [66,] -2.4472964 -0.94969715 -0.329042 -0.113895 -0.2728443 -0.0523337 206s [67,] 0.1790969 -1.29190443 0.146657 0.140234 0.1534048 0.2318353 206s [68,] -0.8017055 -1.93331421 -1.968273 0.017854 0.1287513 -0.2306786 206s [69,] -0.7356418 -0.68868398 -0.075215 -0.156944 0.0302876 0.4232626 206s [70,] 3.8821693 5.16959880 0.215490 -8.985938 5.2189361 -2.8089276 206s [71,] -2.3478937 -1.60220695 0.058822 -0.111845 -0.0539018 0.0087982 206s [72,] 2.3676739 -0.70331436 -0.214457 -0.307311 -0.1582719 0.3995413 206s [73,] -1.9906385 -2.60946629 -0.730312 0.485522 -0.2391998 0.1009341 206s [74,] -11.2435515 1.44868683 2.482678 0.026711 0.4922865 -0.2822136 206s [75,] 0.0044207 -2.29768358 -0.692425 0.538923 -0.4110598 -0.0824903 206s [76,] -1.4045239 -0.22649785 -1.343257 -0.067382 -0.1322233 -0.1072330 206s [77,] -8.3637576 0.14167751 1.267616 0.384528 -0.0728561 -0.4017300 206s [78,] 1.3022939 -1.47457541 -0.394623 -0.068014 -0.1502832 0.0757414 206s [79,] -0.1950676 -0.58254701 -0.824931 -0.088174 -0.2071634 -0.1896613 206s [80,] -3.4432989 1.73593273 0.777996 0.094211 0.2377017 -0.1520088 206s [81,] 1.2167258 0.77512068 0.085803 -0.214850 -0.2201173 0.0432435 206s [82,] 2.7778798 -1.80071342 0.583878 0.465898 0.0648352 0.2148470 206s [83,] 2.6218578 -0.39825539 -0.553372 -0.145721 -0.0977092 -0.2485337 206s [84,] 0.8946018 0.33790104 -1.974267 0.091828 0.0051986 -0.2606274 206s [85,] 0.7759316 -2.34860124 2.423325 -0.384149 -0.0167182 -0.0353374 206s [86,] 0.6266756 0.87099609 -1.407948 -0.237762 0.0361644 0.1675792 206s PC7 PC8 206s [1,] -0.1014312 1.5884e-03 206s [2,] -0.3831443 1.0212e-03 206s [3,] -0.7164683 1.2035e-03 206s [4,] 0.0892864 3.5409e-04 206s [5,] -0.0943992 1.0547e-03 206s [6,] 0.1184847 1.5031e-03 206s [7,] -0.2509793 1.6850e-05 206s [8,] -0.0136880 7.0308e-04 206s [9,] 0.2238736 -1.9164e-04 206s [10,] 0.0754413 1.3614e-04 206s [11,] 0.0784380 3.5175e-04 206s [12,] 0.2033489 -1.3174e-03 206s [13,] 0.2139525 -1.7101e-03 206s [14,] 0.1209735 -9.1070e-04 206s [15,] 0.2119647 -9.2843e-04 206s [16,] -0.3011483 -2.1474e-03 206s [17,] 0.0660858 -1.9036e-03 206s [18,] -0.5199396 -9.4385e-04 206s [19,] -0.1232622 -1.2649e-03 206s [20,] -0.3900208 -2.6927e-04 206s [21,] 0.0264834 7.6074e-05 206s [22,] -0.0736288 1.7240e-04 206s [23,] -0.2156005 -5.5661e-04 206s [24,] 0.1143327 -2.5248e-04 206s [25,] 0.0481580 -6.1531e-04 206s [26,] -0.0084802 -7.5928e-04 206s [27,] -0.2173883 -3.0971e-04 206s [28,] 0.3288873 -1.8975e-04 206s [29,] 0.0788974 -7.2436e-04 206s [30,] -0.0598663 -3.0463e-04 206s [31,] -0.1511658 -4.8751e-04 206s [32,] -0.0532375 -2.5207e-04 206s [33,] -0.0635290 -3.9270e-04 206s [34,] 0.1598240 1.3024e-04 206s [35,] -0.0355175 -8.5374e-05 206s [36,] -0.0174096 -6.3294e-04 206s [37,] -0.2883141 -5.2809e-04 206s [38,] 0.1426412 5.3331e-04 206s [39,] 0.0313308 4.2738e-04 206s [40,] -0.3536195 -3.4170e-04 206s [41,] -0.3925168 1.4588e-04 206s [42,] -0.0056267 -9.1925e-04 206s [43,] -0.4447402 -1.8415e-04 206s [44,] 0.9184385 -5.9685e-04 206s [45,] -0.0340987 7.2924e-04 206s [46,] -0.0162866 9.7800e-04 206s [47,] 0.2428769 -1.1208e-03 206s [48,] 0.3026758 -4.5769e-04 206s [49,] 0.0246345 -2.6207e-04 206s [50,] 0.0857698 7.6439e-05 206s [51,] 0.1136658 1.3013e-04 206s [52,] 0.3993357 6.2796e-04 206s [53,] -0.1765161 1.1329e-04 206s [54,] 0.0016144 2.5870e-04 206s [55,] 0.1064371 5.8188e-04 206s [56,] 0.0207478 -8.7595e-05 206s [57,] 0.1560065 6.3987e-05 206s [58,] 0.1684561 -5.0193e-05 206s [59,] 0.0778732 -8.5458e-04 206s [60,] 0.0037585 1.0429e-05 206s [61,] -0.0296083 3.1526e-05 206s [62,] 0.0913974 -2.2794e-04 206s [63,] 0.0358917 -7.3721e-04 206s [64,] 0.0358917 -7.3721e-04 206s [65,] 0.1209159 2.9398e-04 206s [66,] -0.0027574 2.9380e-04 206s [67,] -0.0091059 -2.7494e-04 206s [68,] 0.0555970 -3.3016e-04 206s [69,] -0.0149255 -3.1228e-04 206s [70,] 0.9282997 4.7859e-05 206s [71,] 0.2630142 4.2617e-04 206s [72,] 0.1063248 -3.0070e-04 206s [73,] -0.1462452 4.9607e-04 206s [74,] 0.2027591 2.6399e-03 206s [75,] 0.6934350 6.0284e-04 206s [76,] -0.0430524 8.1271e-04 206s [77,] 0.0789302 1.4655e-03 206s [78,] -0.0318359 5.2799e-04 206s [79,] -0.1269568 2.9497e-04 206s [80,] 0.2903958 7.8932e-04 206s [81,] 0.0979443 -3.1531e-04 206s [82,] -0.0548155 4.2140e-04 206s [83,] -0.0371550 -5.6653e-04 206s [84,] -0.0835149 -7.0682e-04 206s [85,] 0.1864954 1.0604e-03 206s [86,] 0.1074252 -7.4859e-04 206s ------------- 206s Call: 206s PcaLocantore(x = x) 206s 206s Standard deviations: 206s [1] 1.08405293 0.65307452 0.28970076 0.11162824 0.09072195 0.06659711 0.05888048 206s [8] 0.00022877 206s ---------------------------------------------------------- 206s bushfire 38 5 5 1.464779 0.043290 206s Scores: 206s PC1 PC2 PC3 PC4 PC5 206s [1,] -69.9562 -13.0364 0.98678 1.054123 2.411188 206s [2,] -71.5209 -10.5459 0.31081 1.631208 1.663470 206s [3,] -63.9308 -7.4622 -2.43241 0.671038 0.465836 206s [4,] -47.0413 -9.6343 -3.83609 0.758349 0.683983 206s [5,] -15.9088 -20.1737 -5.55893 1.181744 -0.053563 206s [6,] 8.3484 -30.7646 -5.51541 1.877227 1.338037 206s [7,] -207.7458 -66.2492 34.48519 -5.894885 -1.051729 206s [8,] -246.4327 -97.0433 -9.57057 22.286225 -9.234869 206s [9,] -247.5984 -98.8613 -12.13406 23.948770 -9.250401 206s [10,] -245.8121 -79.2634 12.47990 13.046128 -5.125478 206s [11,] -246.8887 -62.5899 21.21764 9.111011 -5.080985 206s [12,] -251.1354 -9.2115 31.77448 0.236379 0.707528 206s [13,] -194.0239 27.1288 21.05023 0.940913 1.781359 206s [14,] 51.7182 8.5038 -11.22109 -2.132458 1.984807 206s [15,] 180.5597 -4.8151 -21.36630 -9.390663 -0.817036 206s [16,] 135.7246 -5.0756 -11.33517 -10.015567 -1.670831 206s [17,] 133.0151 -4.0344 -8.95540 -7.702087 -0.923277 206s [18,] 121.2619 -9.0627 -5.96042 -7.210971 -2.092872 206s [19,] 124.9038 -10.6649 -7.22555 -5.349553 -1.771009 206s [20,] 135.5410 -6.8146 -7.52834 -5.562769 -0.396924 206s [21,] 117.1950 -3.5643 -4.67473 -6.862117 -0.234551 206s [22,] 108.9944 -2.3344 -5.90349 -5.928299 1.455538 206s [23,] -21.4031 8.0668 6.19525 -4.784890 0.671394 206s [24,] -76.3499 16.7804 6.52545 -1.391250 1.219282 206s [25,] -12.5732 6.1109 -1.45259 -3.512072 -0.375837 206s [26,] -19.1800 3.4685 -2.02243 -3.490028 -0.169127 206s [27,] -33.6733 12.0757 -3.53322 0.048666 0.067468 206s [28,] -9.3966 21.5055 -5.91671 2.650895 -0.449672 206s [29,] 1.4123 35.8559 -5.98222 5.982362 0.613667 206s [30,] -54.2683 39.6029 7.82694 6.759994 0.035048 206s [31,] 74.8866 34.9048 10.03986 12.592158 0.149308 206s [32,] 331.4144 9.3079 27.73391 17.334531 1.015536 206s [33,] 367.6915 -19.5135 48.52753 10.213314 -1.268047 206s [34,] 363.8686 -20.4079 49.32855 8.986581 -1.930673 206s [35,] 369.4371 -19.5074 49.66761 9.001542 -0.179566 206s [36,] 366.5850 -20.2555 50.30290 7.745330 -2.259131 206s [37,] 364.5463 -19.8198 53.00407 6.757796 -1.083372 206s [38,] 365.9709 -19.3753 53.80168 6.467284 -0.854384 206s ------------- 206s Call: 206s PcaLocantore(x = x) 206s 206s Standard deviations: 206s [1] 1.210280 0.208063 0.177790 0.062694 0.014423 206s ---------------------------------------------------------- 206s ========================================================== 206s > dodata(method="cov") 206s 206s Call: dodata(method = "cov") 206s Data Set n p k e1 e2 206s ========================================================== 206s heart 12 2 2 685.776266 13.127306 206s Scores: 206s PC1 PC2 206s 1 8.18562 1.17998 206s 2 65.41185 -2.80723 206s 3 1.86039 -1.70646 206s 4 -2.26910 2.44051 206s 5 20.19603 -1.47331 206s 6 -14.46264 7.05759 206s 7 6.91264 1.99823 206s 8 -28.95436 -3.81624 206s 9 -0.61523 -1.09711 206s 10 -27.62427 -3.33575 206s 11 -13.17788 0.37931 206s 12 49.94879 -1.62675 206s ------------- 206s Call: 206s PcaCov(x = x) 206s 206s Standard deviations: 206s [1] 26.1873 3.6232 206s ---------------------------------------------------------- 206s starsCYG 47 2 2 0.280150 0.007389 206s Scores: 206s PC1 PC2 206s 1 0.272263 -0.07964458 206s 2 0.804544 0.03382837 206s 3 -0.040587 -0.14464760 206s 4 0.804544 0.03382837 206s 5 0.222468 -0.14305159 206s 6 0.512941 -0.02420304 206s 7 -0.378928 -0.51924735 206s 8 0.341045 0.11236831 206s 9 0.592550 -0.23812462 206s 10 0.163442 -0.06357822 206s 11 0.638370 -1.02323643 206s 12 0.498667 -0.05242075 206s 13 0.476291 0.00142479 206s 14 -0.947664 -0.26343572 206s 15 -0.699020 -0.01711057 206s 16 -0.363464 0.06475681 206s 17 -1.024352 -0.02972862 206s 18 -0.759174 0.12317995 206s 19 -0.786925 -0.06478250 206s 20 0.796654 -1.04660568 206s 21 -0.580307 -0.03463751 206s 22 -0.738591 -0.01126825 206s 23 -0.521748 0.08812607 206s 24 -0.086135 0.09457052 206s 25 0.065975 -0.03907968 206s 26 -0.284322 0.05307219 206s 27 -0.303309 -0.07553370 206s 28 -0.052738 -0.02155274 206s 29 -0.580638 -0.10534741 206s 30 0.953478 -1.07986770 206s 31 -0.527590 0.04855502 206s 32 0.171408 0.12730538 206s 33 0.274054 0.00095808 206s 34 1.192364 -1.10502882 206s 35 -0.628641 -0.08815176 206s 36 0.694595 0.11071187 206s 37 0.167026 0.09762710 206s 38 0.274054 0.00095808 206s 39 0.246168 0.08594248 206s 40 0.617380 -0.06994769 206s 41 -0.329735 0.01934346 206s 42 0.115770 0.02432733 206s 43 0.400071 0.03289494 206s 44 0.392768 -0.01656886 206s 45 0.605229 0.05314718 206s 46 0.036628 0.03601196 206s 47 -0.442606 0.07644144 206s ------------- 206s Call: 206s PcaCov(x = x) 206s 206s Standard deviations: 206s [1] 0.529292 0.085957 206s ---------------------------------------------------------- 206s phosphor 18 2 2 288.018150 22.020514 206s Scores: 206s PC1 PC2 206s 1 2.7987 -19.015683 206s 2 -20.4311 -0.032022 206s 3 -21.8198 4.589809 206s 4 -11.7869 -6.837833 206s 5 -16.9357 2.664785 206s 6 12.9132 -25.602526 206s 7 1.5249 -6.351664 206s 8 -8.0984 2.416616 206s 9 -8.6979 4.843680 206s 10 14.3903 -12.732868 206s 11 -2.9462 -0.760656 206s 12 11.7427 2.991004 206s 13 14.8400 0.459849 206s 14 9.2449 3.095095 206s 15 19.4860 -3.336883 206s 16 -9.4156 -7.096788 206s 17 23.3759 -1.737460 206s 18 19.9173 5.092467 206s ------------- 206s Call: 206s PcaCov(x = x) 206s 206s Standard deviations: 206s [1] 16.9711 4.6926 206s ---------------------------------------------------------- 206s stackloss 21 3 3 28.153060 8.925048 206s Scores: 206s PC1 PC2 PC3 206s [1,] 10.538448 13.596944 12.84989 206s [2,] 9.674846 14.098881 12.89733 206s [3,] 8.993255 9.221043 9.94062 206s [4,] 1.744427 3.649104 0.17292 206s [5,] 0.980215 2.223126 1.34874 206s [6,] 1.362321 2.936115 0.76083 206s [7,] 6.926040 0.637480 -0.11170 206s [8,] 6.926040 0.637480 -0.11170 206s [9,] 0.046655 0.977727 -2.46930 206s [10,] -7.909092 0.926343 0.80232 206s [11,] -0.136672 -3.591094 0.37539 206s [12,] -1.382381 -3.802146 1.01074 206s [13,] -6.181887 -0.077532 0.70744 206s [14,] 3.699843 -4.885854 -0.40226 206s [15,] -2.768005 -7.507870 -6.08487 206s [16,] -5.358811 -6.002058 -5.94256 206s [17,] -17.067135 1.738055 -5.86637 206s [18,] -11.021920 -1.775507 -6.19842 206s [19,] -9.776212 -1.564455 -6.83377 206s [20,] -6.075508 0.369252 -2.08345 206s [21,] 6.301743 2.706174 8.79509 206s ------------- 206s Call: 206s PcaCov(x = x) 206s 206s Standard deviations: 206s [1] 5.3059 2.9875 1.3020 206s ---------------------------------------------------------- 206s salinity 28 3 3 11.801732 3.961826 206s Scores: 206s PC1 PC2 PC3 206s 1 -1.59888 1.582157 0.135248 206s 2 -2.26975 2.429177 1.107832 206s 3 -6.79543 -2.034636 0.853876 206s 4 -6.36795 -0.602960 -0.267268 206s 5 -6.42044 -1.520259 5.022962 206s 6 -5.13821 1.225470 0.016977 206s 7 -3.24014 1.998671 -0.123418 206s 8 -0.93998 2.789889 -0.515656 206s 9 -0.30856 -2.424345 -1.422752 206s 10 2.20362 -2.800513 1.142127 206s 11 1.38120 -2.076832 2.515630 206s 12 0.44997 0.207439 -0.152835 206s 13 1.21669 1.193701 -0.277116 206s 14 3.31664 1.306627 1.213342 206s 15 2.08484 -3.774814 0.905400 206s 16 -3.64862 -4.677257 9.046484 206s 17 -0.46124 -1.411762 1.706719 206s 18 -2.13038 0.890401 -0.633349 206s 19 -0.23610 -2.262304 -1.885048 206s 20 1.70337 -1.970773 -0.781880 206s 21 2.67273 1.038742 -0.610945 206s 22 4.24561 1.547290 0.108927 206s 23 2.99619 -4.785343 3.094945 206s 24 1.64474 -3.564562 3.432429 206s 25 1.11703 -1.158030 0.237700 206s 26 2.30707 0.069668 -0.735809 206s 27 3.59356 0.860498 -0.611380 206s 28 4.57550 1.300407 0.589307 206s ------------- 206s Call: 206s PcaCov(x = x) 206s 206s Standard deviations: 206s [1] 3.43536 1.99043 0.94546 206s ---------------------------------------------------------- 206s hbk 75 3 3 1.436470 1.181766 206s Scores: 206s PC1 PC2 PC3 206s 1 31.105415 -4.714217 10.4566165 206s 2 31.707650 -5.748724 10.7682402 206s 3 33.366131 -4.625897 12.1570167 206s 4 34.173377 -6.069657 12.4466895 206s 5 33.780418 -5.508823 11.9872893 206s 6 32.493478 -4.684595 10.5679819 206s 7 32.592637 -5.235522 10.3765493 206s 8 31.293363 -4.865797 10.9379676 206s 9 33.160964 -5.714260 12.3098920 206s 10 31.919786 -5.384537 12.3374332 206s 11 38.231962 -6.810641 13.5994385 206s 12 39.290479 -5.393906 15.2942554 206s 13 39.418445 -7.326461 11.5194898 206s 14 43.906584 -13.214819 8.3282743 206s 15 1.906326 0.716061 -0.8635112 206s 16 0.263255 0.926016 -1.9009292 206s 17 -1.776489 -1.072332 -0.5496140 206s 18 0.464648 0.702441 0.0482897 206s 19 0.267826 -1.283779 -0.2925812 206s 20 2.122108 0.165970 -0.8924686 206s 21 0.937217 0.548532 -0.4132196 206s 22 0.423273 -1.781869 -0.0323061 206s 23 0.047532 0.018909 -1.1259327 206s 24 -0.490041 -0.520202 -1.1065753 206s 25 -2.143049 0.720869 -0.0495474 206s 26 1.094748 -1.459175 0.2226246 206s 27 2.070705 0.898573 0.0023229 206s 28 -0.294998 0.830258 0.5929001 206s 29 -1.242995 0.300216 -0.2010507 206s 30 0.147958 0.439099 2.0003038 206s 31 0.170818 1.440946 -0.9755627 206s 32 -0.958531 -1.199730 -1.0129867 206s 33 0.697307 -0.874343 -0.7260649 206s 34 -2.278946 0.261106 0.4196544 206s 35 1.962829 0.809318 0.2033113 206s 36 0.626631 -0.600666 0.8004036 206s 37 0.550885 -1.881448 0.7382776 206s 38 -1.249717 0.336214 -0.9349845 206s 39 -1.106696 1.569418 0.1869576 206s 40 -0.684034 -0.939963 -0.1034965 206s 41 1.559314 1.551408 0.3660323 206s 42 -0.538741 -0.447358 1.6361099 206s 43 -0.252685 -2.080564 -0.7765259 206s 44 0.217012 1.027281 1.7015154 206s 45 -1.497600 1.349234 -0.2698932 206s 46 0.100388 1.026443 1.5390401 206s 47 -0.811117 2.195271 -0.5208141 206s 48 1.462210 1.321318 0.5600144 206s 49 1.383976 0.740714 -0.7348906 206s 50 1.636773 -0.215464 0.3195369 206s 51 -0.530918 0.759743 -1.2069247 206s 52 -0.109566 2.107455 -0.5315473 206s 53 -0.564334 -0.060847 2.3910630 206s 54 -0.272234 -1.122711 -1.5060028 206s 55 -0.608660 -1.197219 -0.5255609 206s 56 0.565430 -0.710345 -1.3708230 206s 57 -1.115629 0.888816 -0.4186014 206s 58 1.351288 -0.374815 -1.1980618 206s 59 0.998016 -0.151228 0.9007970 206s 60 0.124017 -0.764846 1.9005963 206s 61 1.189858 -1.905264 0.7721322 206s 62 -2.190589 0.579614 -0.1377914 206s 63 -0.518278 -0.931130 -1.4534768 206s 64 2.124566 0.194391 -0.0327092 206s 65 0.154218 1.050861 1.1309885 206s 66 -1.197852 -1.044147 -0.2265269 206s 67 -0.114174 -0.094763 -0.5168926 206s 68 -2.201115 0.032271 0.8573493 206s 69 -1.307843 1.104815 -0.7741270 206s 70 0.691449 -0.676665 1.0004603 206s 71 1.150975 0.050861 -0.0717068 206s 72 -0.457293 -0.861871 0.1026350 206s 73 -0.392258 -0.897451 0.9178065 206s 74 -0.584658 -1.450471 0.3201857 206s 75 -0.972517 -0.063777 1.8223995 206s ------------- 206s Call: 206s PcaCov(x = x) 206s 206s Standard deviations: 206s [1] 1.1985 1.0871 1.0086 206s ---------------------------------------------------------- 206s milk 86 8 8 5.758630 2.224809 206s Scores: 206s PC1 PC2 PC3 PC4 PC5 PC6 206s 1 5.7090867 1.388263 0.0055924 0.3510505 -0.7335114 -1.41950731 206s 2 6.5825186 0.480410 -1.1356236 -0.3250838 -0.7343177 -1.71595400 206s 3 0.7433619 -1.749281 0.2510521 0.3450575 0.2996413 -0.34585702 206s 4 5.5733255 -1.588521 0.8934908 -0.3412408 0.0087626 0.07235942 206s 5 -1.3030839 0.142394 0.8487785 -0.5847851 0.0588053 -0.08968553 206s 6 1.7708705 0.674240 -0.4153759 -0.1915734 0.1382138 0.12454293 206s 7 2.3570866 0.381017 -0.8771357 -0.3739365 0.2918453 0.13437364 206s 8 2.5700714 0.695006 0.0061108 -0.4323695 0.1643797 -0.00469369 206s 9 -1.1725766 -2.713291 1.0677483 -0.0647875 0.1183120 -0.10762785 206s 10 -3.1357225 -1.255175 0.0666017 0.5083690 -0.1096080 -0.00647493 206s 11 -9.5333894 -1.608943 2.7307809 0.1690156 -0.1682415 -0.06597478 206s 12 -13.6028505 0.941083 2.0136258 -0.1076520 -0.0475905 -0.15295614 206s 13 -10.9497471 0.048776 -0.8765307 0.1518572 0.1428294 -0.00064406 206s 14 -12.6558378 -0.219444 1.1396273 -0.3734679 0.2875578 -0.23870524 206s 15 -10.6924790 -1.818075 3.4560731 -0.1177943 0.1101199 -0.19708172 206s 16 -3.0258070 -0.203186 1.2835368 0.5799363 0.3237454 0.23168871 206s 17 -0.7498665 -2.977505 1.6310512 0.6305329 0.3994006 0.06594881 206s 18 -2.5093526 0.924459 0.0899818 -0.4026675 0.2963072 0.11324019 206s 19 -1.9689970 -1.051282 1.4659908 0.3870104 -0.0708083 -0.02148354 206s 20 0.2695886 -1.646440 0.7597630 0.1750131 -0.3418142 0.21515143 206s 21 -3.3470252 1.989939 0.2887021 -0.3599779 0.0771965 0.16867095 206s 22 -1.4659204 0.777242 0.4090149 -0.1248050 0.1916768 -0.23160291 206s 23 -0.4944476 1.634130 0.8915509 0.1222296 -0.1231015 -0.08351169 206s 24 -0.8945477 1.239223 1.1117165 0.6018455 0.0912200 -0.01204668 206s 25 -4.1499992 1.860190 1.6062973 -0.2139736 -0.1140169 0.16632426 206s 26 -1.2647012 1.188058 1.1893430 -0.2740862 -0.0971504 -0.09851714 206s 27 -3.4280131 -0.267150 1.1969552 0.0354366 0.8482718 -0.18977667 206s 28 1.6896630 3.793723 0.7706325 0.1007287 0.0317704 -0.11269816 206s 29 3.9258127 1.691428 0.1850999 0.4485202 -0.2969916 0.16594044 206s 30 0.3178322 1.577233 0.4455231 -0.1687197 -0.1587136 -0.00823174 206s 31 0.9562350 2.258138 -1.4672169 0.2675668 0.1910110 0.03177387 206s 32 0.6738452 0.470764 -1.3496896 0.3524049 0.2008218 -0.36957179 206s 33 1.5980690 0.413899 0.1999664 0.4232293 0.0768479 -0.04627841 206s 34 0.4365091 -0.626490 0.4718364 0.3392252 0.2554060 -0.19018602 206s 35 -1.1184804 2.124234 0.2650931 0.4791171 0.2927791 -0.01579964 206s 36 3.6673986 1.659798 0.6138972 -0.1092158 -0.2705583 -0.16494176 206s 37 0.0867143 2.541765 -0.4572593 0.0024263 0.2163300 -0.20116352 206s 38 1.4191839 2.315690 0.1365887 0.1028375 0.1595780 -0.02049460 206s 39 -1.8062960 0.845438 1.1469588 0.5022406 0.1603011 -0.08751261 206s 40 3.4380914 -1.358545 0.1956896 0.6314649 0.0716078 -0.21591535 206s 41 3.4608782 1.828575 0.2012565 0.1064437 -0.7454169 -1.64629924 206s 42 6.4162310 -0.402642 0.8070441 0.5146855 0.0331594 0.04373032 206s 43 2.5906567 0.897993 -1.2612252 -0.2620162 -0.1432569 -0.10279385 206s 44 5.0299750 0.203721 0.0439110 0.8775684 -0.9536011 0.15153452 206s 45 -0.3555392 0.454930 0.1173992 0.4688991 0.1137820 0.18752442 206s 46 -0.4155426 1.892410 0.8649578 0.1827426 -0.0186113 -0.04029205 206s 47 1.9328817 0.121936 -3.9578157 -0.1135807 0.2971001 0.18733657 206s 48 -0.3947656 1.028405 -1.0370498 0.4467257 -0.1445498 0.16878692 206s 49 -2.8829860 0.279064 -1.4443310 0.5889970 -0.1883118 0.16947945 206s 50 3.2797246 -2.443968 0.4100655 0.4278962 -0.4414712 0.08598366 206s 51 -1.9272930 -0.622137 -1.5136862 -0.0483369 -0.0272502 0.16006066 206s 52 -5.7161590 -0.298434 -0.5216578 0.1385780 -0.2435931 0.10628617 206s 53 -1.1933277 -0.125878 -0.7556261 -0.3129372 -0.3166453 0.03078643 206s 54 -0.5994394 -0.031069 -0.1296378 0.0061490 -0.1869578 0.09839221 206s 55 0.4104586 0.733465 -0.2088065 -0.3645266 -0.1830137 0.04705775 206s 56 -0.2227671 -0.724741 0.1007592 -0.0838897 -0.1939960 -0.04223579 206s 57 -1.5706297 -0.292436 1.0849660 -0.2559591 -0.0917278 -0.27423151 206s 58 -0.4102168 1.263831 0.9082556 -0.4592777 -0.0676902 0.11089798 206s 59 -1.9640736 -1.340173 -0.3652736 -0.1267573 0.0775692 -0.07977644 206s 60 -1.7490968 -0.941370 -0.0849901 -0.3453455 0.2858594 0.06413468 206s 61 -0.1583416 -1.699326 0.2385988 -0.2231496 -0.0513883 -0.12227279 206s 62 2.2124878 -1.942366 0.0743514 0.2627321 -0.2844018 -0.15848039 206s 63 2.4578489 0.226019 0.1148050 -0.2715718 0.2322085 0.22346659 206s 64 2.4578489 0.226019 0.1148050 -0.2715718 0.2322085 0.22346659 206s 65 -0.3779208 -2.987354 0.6819006 0.1942611 0.0529259 0.01315140 206s 66 -2.6385498 -1.331204 -0.0367809 -0.2327572 0.1845076 -0.08521680 206s 67 0.0526645 -1.301299 0.0912198 0.1634869 -0.0068236 0.24131589 206s 68 -1.1013065 -2.004809 -1.9168056 0.0260663 -0.2029903 -0.12625268 206s 69 -0.9495853 -0.831697 0.0389476 -0.2123483 -0.0202267 0.38463410 206s 70 2.6935893 5.369312 0.6987368 -4.5754846 -9.6833013 -2.32910628 206s 71 -2.4037611 -1.983509 0.3109848 -0.1015686 -0.0071432 0.06410351 206s 72 2.0795505 -0.392730 -0.4534128 -0.4054224 -0.0312781 0.25408988 206s 73 -2.0038405 -2.874605 -0.6269939 0.2408421 0.5184666 0.11140104 206s 74 -11.2683996 -0.361851 3.9219448 0.4045689 -0.2203308 0.05930132 206s 75 -0.1028287 -2.295813 -0.7769187 0.3071821 0.4537196 0.00522380 206s 76 -1.8466137 -0.425825 -1.1261209 -0.1760585 0.0165729 -0.10698465 206s 77 -8.4124493 -1.174820 2.2700712 0.4213953 0.3446597 -0.20636892 206s 78 1.1103236 -1.299480 -0.5787732 -0.1455945 0.0732148 -0.01806218 206s 79 -0.5451834 -0.620170 -0.7830595 -0.1746479 0.0723052 -0.26017118 206s 80 -3.8647223 1.126328 1.3299567 0.2645241 -0.1881443 0.00485531 206s 81 0.7690939 0.887363 0.0513096 -0.2730980 0.0076447 -0.07590882 206s 82 2.7287618 -1.435327 0.1602865 0.4465859 0.2129425 0.16104418 206s 83 2.2241485 -0.042822 -0.8316486 -0.1230697 -0.1193057 -0.35207561 206s 84 0.2452905 0.491732 -2.0050683 0.0286567 -0.1159415 -0.24887542 206s 85 1.0655845 -2.360746 2.2456131 -0.1479972 -0.1186670 -0.14020891 206s 86 -0.0091659 0.952208 -1.3429189 -0.2944676 -0.2433277 0.15354490 206s PC7 PC8 206s 1 -0.09778744 2.3157e-03 206s 2 0.05189698 1.8077e-03 206s 3 0.70506895 1.2838e-03 206s 4 -0.08541140 3.2781e-04 206s 5 0.11768945 8.3496e-04 206s 6 -0.17886391 1.5222e-03 206s 7 0.14143613 1.3261e-04 206s 8 -0.07724578 7.1241e-04 206s 9 -0.12298048 -7.0110e-04 206s 10 0.07569878 2.3093e-05 206s 11 0.29299858 -3.4542e-04 206s 12 0.07764899 -2.1390e-03 206s 13 -0.08945524 -2.2633e-03 206s 14 0.03597787 -1.8891e-03 206s 15 0.11780498 -2.0279e-03 206s 16 0.46501534 -2.3266e-03 206s 17 0.08603290 -2.4073e-03 206s 18 0.52605757 -9.8822e-04 206s 19 0.31007227 -1.3919e-03 206s 20 0.61582059 -2.3549e-05 206s 21 0.01199350 -6.1649e-05 206s 22 0.03654587 1.3302e-05 206s 23 0.27549986 -3.6759e-04 206s 24 -0.04155354 -2.9882e-04 206s 25 0.11473708 -7.9629e-04 206s 26 0.06673183 -8.3728e-04 206s 27 0.16937729 -9.5775e-04 206s 28 -0.41753592 -7.5544e-05 206s 29 -0.03693100 -2.2481e-04 206s 30 0.08461537 -1.3611e-04 206s 31 0.02476253 -1.4319e-04 206s 32 -0.09756048 -1.2234e-04 206s 33 0.06442434 -2.4915e-04 206s 34 -0.17828409 -9.5882e-05 206s 35 0.00881239 -7.1427e-05 206s 36 -0.01041003 -2.8489e-04 206s 37 0.15994729 -3.1472e-04 206s 38 -0.22386895 6.1384e-04 206s 39 0.03666242 2.8506e-04 206s 40 0.35883231 -8.3062e-05 206s 41 0.18521851 8.5509e-04 206s 42 0.00733985 -6.4477e-04 206s 43 0.35466617 3.2923e-04 206s 44 -0.74952524 -7.6869e-05 206s 45 0.09907237 7.9128e-04 206s 46 0.05119980 1.0606e-03 206s 47 -0.48571583 -9.3780e-04 206s 48 -0.27463442 -2.7037e-04 206s 49 0.06787536 -3.0554e-05 206s 50 0.08499400 3.1181e-04 206s 51 -0.09197457 1.1213e-04 206s 52 -0.24513244 3.9100e-04 206s 53 0.24012780 3.2068e-04 206s 54 0.07999888 3.5689e-04 206s 55 -0.09825475 6.6675e-04 206s 56 0.05133674 -7.2984e-05 206s 57 -0.10302363 -2.0693e-04 206s 58 -0.12323360 -1.6620e-04 206s 59 -0.05119989 -1.1016e-03 206s 60 0.00082131 -3.2951e-04 206s 61 0.08128272 -1.1550e-04 206s 62 -0.01789040 -1.1579e-04 206s 63 -0.07188070 -7.8367e-04 206s 64 -0.07188070 -7.8367e-04 206s 65 0.00917085 -2.6800e-05 206s 66 0.03121573 -5.3492e-05 206s 67 0.12202335 -3.0466e-04 206s 68 -0.04764366 -2.6126e-04 206s 69 0.13828337 -3.9331e-04 206s 70 0.10401069 4.2870e-03 206s 71 -0.14369640 3.7669e-05 206s 72 -0.10334451 -2.6456e-04 206s 73 0.17655402 1.0917e-04 206s 74 0.26779696 1.8685e-03 206s 75 -0.75016549 2.1079e-05 206s 76 0.01802016 7.7555e-04 206s 77 0.13081368 6.4286e-04 206s 78 0.01409131 4.9476e-04 206s 79 0.06643384 2.6590e-04 206s 80 -0.12624376 5.9801e-04 206s 81 -0.14074469 -3.2172e-04 206s 82 0.09228230 4.4064e-04 206s 83 -0.06352151 -3.6274e-04 206s 84 -0.02642452 -3.9742e-04 206s 85 -0.03502188 6.9814e-04 206s 86 -0.11749109 -5.1283e-04 206s ------------- 206s Call: 206s PcaCov(x = x) 206s 206s Standard deviations: 206s [1] 2.39971451 1.49157920 0.93184037 0.33183258 0.19628996 0.16485446 0.12784351 206s [8] 0.00052622 206s ---------------------------------------------------------- 206s bushfire 38 5 5 11393.979994 197.523453 206s Scores: 206s PC1 PC2 PC3 PC4 PC5 206s 1 -91.383 -16.17804 0.56195 -0.252428 1.261840 206s 2 -93.033 -13.93251 -0.67212 0.042287 0.470924 206s 3 -85.400 -10.72512 -3.09832 -1.224797 -0.504718 206s 4 -68.381 -12.12202 -3.31950 -0.676880 -0.228383 206s 5 -36.742 -21.04171 -1.98872 0.397655 -0.932613 206s 6 -12.095 -30.21719 0.59595 2.100702 0.384714 206s 7 -227.949 -71.40450 35.57308 -7.880296 -2.710415 206s 8 -262.815 -111.81228 -11.04574 2.397832 -13.646407 206s 9 -263.767 -114.13702 -13.71407 3.131736 -13.825200 206s 10 -264.312 -90.69643 9.72320 0.967173 -8.800150 206s 11 -266.681 -72.85993 16.55010 0.291092 -8.373583 206s 12 -274.050 -18.41395 20.74273 -2.464589 -1.505967 206s 13 -218.299 19.16040 7.69765 0.069012 0.054846 206s 14 29.646 10.52526 -7.50754 0.855493 1.966680 206s 15 159.575 3.86633 -6.95837 -2.753953 0.616068 206s 16 114.286 2.47164 0.62690 -3.146317 -0.501623 206s 17 111.289 3.45086 1.97182 -0.303064 -0.094416 206s 18 99.626 -1.80416 4.88197 -0.013096 -1.438397 206s 19 103.353 -3.50426 3.58993 1.578169 -1.317194 206s 20 113.769 0.84544 3.28254 2.204926 0.131167 206s 21 95.186 3.50703 4.97153 0.916181 0.351658 206s 22 86.996 4.00938 2.95209 1.281788 1.920404 206s 23 -44.232 8.50898 6.30689 -1.038871 0.400078 206s 24 -99.527 13.81377 1.75130 -0.260669 0.394804 206s 25 -34.855 5.99709 -0.57224 -1.660513 -0.620158 206s 26 -41.265 2.94659 -1.04825 -2.243950 -0.440017 206s 27 -56.148 10.14428 -5.41858 0.321752 -0.608412 206s 28 -32.366 20.27795 -8.60687 3.806572 -1.267249 206s 29 -22.438 34.73585 -11.19123 8.296154 -0.511610 206s 30 -79.035 37.05713 -1.51591 9.892959 -1.618635 206s 31 49.465 39.37414 5.95714 22.874813 -1.883481 206s 32 304.825 30.19205 37.68900 45.175923 -1.293939 206s 33 341.237 7.04985 65.43451 44.553009 -3.148116 206s 34 337.467 6.16879 66.48222 43.278480 -3.688631 206s 35 342.929 7.38548 66.91291 43.941556 -1.937887 206s 36 340.143 6.70203 67.85433 42.479161 -3.873639 206s 37 337.931 7.43184 70.50828 42.333220 -2.645830 206s 38 339.281 8.07267 71.34405 42.400459 -2.392774 206s ------------- 206s Call: 206s PcaCov(x = x) 206s 206s Standard deviations: 206s [1] 106.7426 14.0543 4.9184 1.8263 1.0193 206s ---------------------------------------------------------- 206s ========================================================== 206s > dodata(method="grid") 206s 206s Call: dodata(method = "grid") 206s Data Set n p k e1 e2 206s ========================================================== 206s heart 12 2 2 516.143549 23.932102 206s Scores: 206s PC1 PC2 206s [1,] 6.4694 3.8179 206s [2,] 61.7387 19.1814 206s [3,] 1.4722 -1.0161 206s [4,] -3.8056 1.5127 206s [5,] 18.6760 5.3303 206s [6,] -16.8411 1.7900 206s [7,] 4.9962 4.1638 206s [8,] -26.8665 -13.3010 206s [9,] -1.0648 -1.2690 206s [10,] -25.7734 -12.4037 206s [11,] -13.3987 -4.0751 206s [12,] 46.7700 15.1272 206s ------------- 206s Call: 206s PcaGrid(x = x) 206s 206s Standard deviations: 206s [1] 22.719 4.892 206s ---------------------------------------------------------- 206s starsCYG 47 2 2 0.473800 0.026486 206s Scores: 206s PC1 PC2 206s [1,] 0.181489 -0.0300854 206s [2,] 0.695337 0.1492475 206s [3,] -0.120738 -0.1338110 206s [4,] 0.695337 0.1492475 206s [5,] 0.140039 -0.0992368 206s [6,] 0.413314 0.0551030 206s [7,] -0.409428 -0.5478860 206s [8,] 0.225647 0.1690378 206s [9,] 0.519123 -0.1471454 206s [10,] 0.071513 -0.0277935 206s [11,] 0.663045 -0.9203119 206s [12,] 0.402691 0.0253179 206s [13,] 0.373739 0.0759321 206s [14,] -1.005756 -0.3654219 206s [15,] -0.789968 -0.0898580 206s [16,] -0.467328 0.0334465 206s [17,] -1.111148 -0.1431778 206s [18,] -0.867242 0.0417806 206s [19,] -0.871200 -0.1481782 206s [20,] 0.823011 -0.9236455 206s [21,] -0.669994 -0.0923582 206s [22,] -0.829959 -0.0890246 206s [23,] -0.627294 0.0367802 206s [24,] -0.195929 0.0978059 206s [25,] -0.028257 -0.0157122 206s [26,] -0.387346 0.0317797 206s [27,] -0.390054 -0.0981920 206s [28,] -0.148231 -0.0132120 206s [29,] -0.661454 -0.1625514 206s [30,] 0.982767 -0.9369769 206s [31,] -0.628127 -0.0032112 206s [32,] 0.055476 0.1625819 206s [33,] 0.173158 0.0501056 206s [34,] 1.222924 -0.9319795 206s [35,] -0.711235 -0.1515118 206s [36,] 0.576613 0.2117347 206s [37,] 0.054851 0.1325884 206s [38,] 0.173158 0.0501056 206s [39,] 0.134833 0.1309216 206s [40,] 0.522665 0.0228177 206s [41,] -0.428171 -0.0073782 206s [42,] 0.013192 0.0534392 206s [43,] 0.294173 0.0975945 206s [44,] 0.293132 0.0476054 206s [45,] 0.495172 0.1434167 206s [46,] -0.066790 0.0551060 206s [47,] -0.547311 0.0351134 206s ------------- 206s Call: 206s PcaGrid(x = x) 206s 206s Standard deviations: 206s [1] 0.68833 0.16275 206s ---------------------------------------------------------- 206s phosphor 18 2 2 392.155327 50.657228 206s Scores: 206s PC1 PC2 206s 1 5.6537 -15.2305 206s 2 -21.2150 -1.8862 206s 3 -23.5966 2.3112 206s 4 -11.2742 -6.6000 206s 5 -18.4067 1.5202 206s 6 16.9795 -19.4039 206s 7 1.5964 -3.1666 206s 8 -9.7354 3.2429 206s 9 -10.8594 5.4759 206s 10 15.5585 -6.5279 206s 11 -4.0058 1.2905 206s 12 9.4815 8.2139 206s 13 13.0640 6.4346 206s 14 7.0230 7.7600 206s 15 18.4378 3.7658 206s 16 -8.9047 -6.3253 206s 17 21.8748 6.1900 206s 18 16.9843 12.0801 206s ------------- 206s Call: 206s PcaGrid(x = x) 206s 206s Standard deviations: 206s [1] 19.8029 7.1174 206s ---------------------------------------------------------- 206s stackloss 21 3 3 109.445054 16.741203 206s Scores: 206s PC1 PC2 PC3 206s [1,] 15.136434 14.82909 -2.0387704 206s [2,] 14.393636 15.46816 -1.8391595 206s [3,] 12.351209 10.12290 -2.3458098 206s [4,] 2.510036 2.07589 1.8251581 206s [5,] 1.767140 1.78527 -0.0088651 206s [6,] 2.138588 1.93058 0.9081465 206s [7,] 6.966825 -1.75851 0.6274924 206s [8,] 6.966825 -1.75851 0.6274924 206s [9,] -0.089513 -1.09062 2.2894224 206s [10,] -7.146340 2.65628 -0.8983590 206s [11,] -0.461157 -3.09532 -2.6948576 206s [12,] -1.575403 -2.60157 -3.4122582 206s [13,] -5.660744 1.37815 -1.2975809 206s [14,] 2.881484 -5.50628 -2.5762898 206s [15,] -4.917360 -9.13772 0.0676942 206s [16,] -7.145755 -7.22052 0.6665270 206s [17,] -17.173481 1.87173 4.3780920 206s [18,] -11.973894 -2.60174 2.9808153 206s [19,] -10.859648 -3.09549 3.6982160 206s [20,] -6.031899 0.15817 1.2270803 206s [21,] 8.451640 4.98077 -5.4038839 206s ------------- 206s Call: 206s PcaGrid(x = x) 206s 206s Standard deviations: 206s [1] 10.4616 4.0916 2.8271 206s ---------------------------------------------------------- 206s salinity 28 3 3 14.911546 8.034974 206s Scores: 206s PC1 PC2 PC3 206s 1 -2.72400 0.79288 0.688038 206s 2 -3.45684 0.86162 1.941690 206s 3 -5.73471 -4.79507 0.129202 206s 4 -6.17045 -3.04372 -0.352797 206s 5 -4.72453 -5.59543 4.144851 206s 6 -5.75447 -1.07062 0.579975 206s 7 -4.40759 0.47731 0.680203 206s 8 -2.76360 2.30716 0.540271 206s 9 -0.28782 -1.40644 -2.373399 206s 10 2.64361 -1.43362 -0.266957 206s 11 1.91078 -1.66975 1.312215 206s 12 -0.40661 0.68573 -0.200135 206s 13 -0.14911 1.88993 0.044001 206s 14 1.99005 2.43874 1.373229 206s 15 2.88128 -2.21263 -0.863674 206s 16 -0.12935 -8.28831 6.483875 206s 17 -0.16895 -1.68742 0.905190 206s 18 -3.08054 0.23753 -0.269165 206s 19 -0.38685 -1.08501 -2.736860 206s 20 1.45520 -0.33209 -1.686406 206s 21 1.13834 2.53553 -0.381657 206s 22 2.48522 3.42927 0.417050 206s 23 4.56487 -3.36542 0.711908 206s 24 2.94072 -3.08490 1.556939 206s 25 0.82140 -0.26895 -0.406490 206s 26 1.17794 1.61119 -0.863764 206s 27 2.02965 2.80707 -0.489050 206s 28 2.98039 3.21462 0.747622 206s ------------- 206s Call: 206s PcaGrid(x = x) 206s 206s Standard deviations: 206s [1] 3.86155 2.83460 0.95394 206s ---------------------------------------------------------- 206s hbk 75 3 3 3.714805 3.187126 206s Scores: 206s PC1 PC2 PC3 206s 1 8.423138 24.765818 19.413334 206s 2 7.823138 25.295092 20.356662 206s 3 9.023138 27.411905 20.218454 206s 4 8.223138 28.010236 21.568269 206s 5 8.623138 27.442650 21.123471 206s 6 9.123138 25.601873 20.279943 206s 7 8.823138 25.463855 20.770811 206s 8 8.223138 25.264348 19.451646 206s 9 8.023138 27.373593 20.716984 206s 10 7.623138 26.752275 19.666288 206s 11 9.323138 31.108975 24.313778 206s 12 10.323138 33.179719 23.469966 206s 13 10.323138 29.958667 26.231274 206s 14 9.323138 29.345676 34.207755 206s 15 1.723138 -0.077538 0.754886 206s 16 1.423138 -1.818609 -0.080979 206s 17 -1.676862 -1.872341 -0.686878 206s 18 0.623138 -0.077633 -0.548955 206s 19 -0.876862 -0.576068 0.716574 206s 20 1.423138 -0.016144 1.261078 206s 21 0.923138 -0.223313 0.041619 206s 22 -1.276862 -0.299937 1.038679 206s 23 0.323138 -1.327742 0.057038 206s 24 -0.376862 -1.626860 0.034051 206s 25 -0.676862 -1.550331 -2.266849 206s 26 -0.776862 0.290637 1.184359 206s 27 1.623138 0.750760 0.417361 206s 28 0.123138 -0.016334 -1.346603 206s 29 -0.476862 -1.220468 -1.338846 206s 30 -0.476862 1.387213 -1.339036 206s 31 1.423138 -1.059368 -0.824991 206s 32 -1.176862 -1.833934 0.118433 206s 33 -0.176862 -0.691099 0.908323 206s 34 -1.276862 -1.251213 -2.243862 206s 35 1.423138 0.858128 0.325317 206s 36 -0.576862 0.574335 0.102918 206s 37 -1.576862 0.413330 0.892903 206s 38 -0.176862 -1.841691 -1.085702 206s 39 0.423138 -0.752683 -2.205550 206s 40 -1.176862 -0.905930 -0.211430 206s 41 1.723138 0.819721 -0.479993 206s 42 -1.376862 0.666284 -1.093554 206s 43 -1.576862 -1.304659 1.061761 206s 44 0.123138 1.203126 -1.553772 206s 45 0.223138 -1.358581 -2.151818 206s 46 0.123138 1.003714 -1.569097 206s 47 1.323138 -1.159169 -2.136494 206s 48 1.423138 0.919427 -0.472331 206s 49 1.423138 -0.246300 0.340737 206s 50 0.423138 0.727773 0.716479 206s 51 0.623138 -1.665267 -0.771259 206s 52 1.623138 -0.798657 -1.607314 206s 53 -1.376862 1.310494 -1.645816 206s 54 -0.576862 -1.879908 0.716669 206s 55 -1.176862 -1.235698 0.164407 206s 56 0.123138 -1.296997 0.962055 206s 57 0.123138 -1.304849 -1.545920 206s 58 0.723138 -0.714086 1.207441 206s 59 -0.076862 0.881115 0.026199 206s 60 -1.376862 1.226208 -0.549050 206s 61 -1.276862 0.781504 1.322377 206s 62 -0.776862 -1.657699 -2.174806 206s 63 -0.576862 -1.956627 0.409888 206s 64 1.123138 0.712448 0.915891 206s 65 0.323138 0.689271 -1.392672 206s 66 -1.476862 -1.289430 -0.441492 206s 67 -0.076862 -0.905930 -0.211430 206s 68 -1.576862 -0.852389 -2.213213 206s 69 0.323138 -1.696011 -1.676276 206s 70 -0.676862 0.773747 0.118243 206s 71 0.523138 0.152524 0.371386 206s 72 -1.076862 -0.606812 -0.188443 206s 73 -1.376862 0.114117 -0.433924 206s 74 -1.676862 -0.522431 0.018632 206s 75 -1.376862 0.612552 -1.699453 206s ------------- 206s Call: 206s PcaGrid(x = x) 206s 206s Standard deviations: 206s [1] 1.9274 1.7853 1.6714 206s ---------------------------------------------------------- 206s milk 86 8 8 9.206694 2.910585 206s Scores: 206s PC1 PC2 PC3 PC4 PC5 PC6 206s [1,] 6.090978 0.590424 1.1644466 -0.3835606 1.0342867 -0.4752288 206s [2,] 6.903009 -0.575027 0.8613622 -1.1221795 0.7221616 -1.3097951 206s [3,] 0.622903 -1.594239 1.2122863 -0.0555128 0.3252629 -0.2799581 206s [4,] 5.282665 -1.815742 2.2543268 0.9824543 -0.5345577 -0.7331037 206s [5,] -1.039753 0.663906 0.3353811 0.3070599 -0.3224317 -0.4056666 206s [6,] 2.247786 0.218255 -0.3382923 0.1270005 -0.0271307 -0.2035021 206s [7,] 2.784293 -0.291678 -0.4897587 0.0198481 0.0752345 -0.5986846 206s [8,] 2.942266 0.315608 0.1603961 0.3568462 -0.0647311 -0.5316127 206s [9,] -1.420086 -1.751212 1.7027572 0.0708340 -0.9226517 0.0738411 206s [10,] -2.921113 -0.727554 0.0113966 -0.3915037 -0.0772913 0.6062573 206s [11,] -9.568075 0.792291 1.0217507 0.2554182 -0.6254883 0.8899897 206s [12,] -12.885166 3.423607 -1.2579351 -0.4300397 -0.4094558 1.1727128 206s [13,] -10.038470 1.274931 -2.6913262 -1.6219658 -0.3284974 1.1228303 206s [14,] -12.044003 2.096254 -1.2859668 -0.9602250 -0.7937418 0.8264019 206s [15,] -10.798341 1.159257 1.4870766 0.3248231 -1.0787537 0.8723637 206s [16,] -2.841629 0.500846 0.4771762 0.5975365 0.3197882 0.5804087 206s [17,] -1.150691 -1.978038 2.3229313 0.5275273 -0.5339514 0.5421631 206s [18,] -1.992369 1.131288 -0.8385615 0.1156462 0.2253010 -0.3393814 206s [19,] -1.999699 -0.252876 1.2229972 0.5081648 0.0082612 0.3373454 206s [20,] 0.091385 -1.439422 1.1836134 0.6297789 0.0961407 -0.2126653 206s [21,] -2.571346 2.280701 -1.2845660 0.1463583 0.0949331 0.0902039 206s [22,] -0.990078 1.087033 -0.1638640 -0.0351472 0.0743205 -0.0040605 206s [23,] -0.010631 1.704171 0.0038808 0.5765418 0.6086460 0.0329995 206s [24,] -0.440350 1.500798 0.2769870 0.5556999 0.4751445 0.6516120 206s [25,] -3.578249 2.672783 -0.3534268 0.7398104 0.1108289 0.2704730 206s [26,] -0.854914 1.626684 0.2301131 0.5530224 0.0662862 -0.0999969 206s [27,] -3.175381 0.762609 0.5101987 0.0849002 -0.2137237 0.2729808 206s [28,] 2.599844 3.370137 -0.5174736 0.7409946 0.6853156 0.2430943 206s [29,] 4.395534 0.823611 0.1610152 0.8184845 0.7665555 0.0779724 206s [30,] 0.843794 1.438263 -0.2366601 0.4600650 0.3424806 -0.1768083 206s [31,] 1.890815 1.266935 -1.8218143 -0.3909337 0.8390127 0.1026821 206s [32,] 1.300145 -0.085976 -0.8965312 -0.8855787 0.4156780 0.1478055 206s [33,] 1.923087 0.137638 0.3487435 0.2958367 0.4245932 0.1566678 206s [34,] 0.615762 -0.390711 0.8107376 0.0295536 -0.1169590 0.2940241 206s [35,] -0.372946 2.037079 -0.7663299 0.1907237 0.6959350 0.5366205 206s [36,] 4.068134 1.129044 0.5492962 0.7640964 0.4799859 -0.4080205 206s [37,] 0.937617 2.048258 -1.2326566 -0.0942856 0.7885267 -0.1004018 206s [38,] 2.141223 1.877022 -0.5178216 0.3750868 0.4767003 0.1240656 206s [39,] -1.403505 1.327163 0.3165610 0.3989824 0.3505825 0.5915956 206s [40,] 3.337528 -1.689495 1.4737175 0.2584843 0.4308444 -0.0810597 206s [41,] 3.938506 1.384908 0.8103687 -0.5875595 1.1616535 -0.6492603 206s [42,] 6.327471 -1.061362 1.9861187 1.1016484 0.3512405 -0.1540592 206s [43,] 3.120160 -0.064108 -0.8370717 -0.2229341 0.5623447 -0.7152184 206s [44,] 5.290520 -0.669008 0.8597130 0.5518503 0.2470856 0.6454703 206s [45,] 0.058291 0.356399 -0.1896007 0.2427518 0.3705541 0.3975085 206s [46,] 0.150881 1.942057 -0.1140726 0.5656469 0.5227623 0.2151825 206s [47,] 2.870881 -1.446283 -2.8450062 -1.7292144 -0.0888429 -0.1347003 206s [48,] 0.335593 0.500884 -1.3154520 -0.3874864 0.3449038 0.5387692 206s [49,] -2.179494 -0.021237 -1.7792344 -0.8445930 0.4435338 0.6547961 206s [50,] 2.968304 -2.588546 1.8552104 0.4590101 -0.1755089 -0.0550378 206s [51,] -1.399208 -0.820296 -1.3660014 -0.8890243 -0.2344105 0.1236943 206s [52,] -5.112989 0.318983 -1.3852993 -0.8461529 -0.3467685 0.7349666 206s [53,] -0.773103 -0.267333 -0.8154896 -0.3783062 0.0113880 -0.3304648 206s [54,] -0.244565 -0.066211 -0.2541557 0.0043037 0.0390890 0.0074067 206s [55,] 0.894921 0.516411 -0.4443369 0.0708354 -0.0637890 -0.2799646 206s [56,] -0.038706 -0.588256 0.3166588 -0.0196663 -0.1793472 -0.1179341 206s [57,] -1.377469 0.428939 0.7502430 0.1458375 -0.3818977 -0.0380258 206s [58,] 0.042787 1.488605 0.0252606 0.6377516 -0.1524172 -0.1898723 206s [59,] -1.734357 -0.966494 -0.1026850 -0.5656888 -0.4831402 0.0308069 206s [60,] -1.501991 -0.544918 -0.0837127 -0.2362486 -0.5382026 -0.1351338 206s [61,] -0.175102 -1.339436 0.8403933 -0.0907428 -0.4846145 -0.2795153 206s [62,] 2.100915 -2.004702 1.3031556 -0.0041957 -0.2067776 -0.0793613 206s [63,] 2.735432 -0.102018 0.3215454 0.5331904 -0.1499209 -0.3536272 206s [64,] 2.735432 -0.102018 0.3215454 0.5331904 -0.1499209 -0.3536272 206s [65,] -0.665219 -2.325594 1.6287363 0.0607163 -0.6996720 0.1353325 206s [66,] -2.439244 -0.737375 0.0187770 -0.4561269 -0.5425315 -0.0208332 206s [67,] 0.121564 -1.214385 0.4877707 0.1809998 -0.1943262 0.0662506 206s [68,] -0.804267 -2.238327 -0.8547917 -1.3449926 -0.3577254 -0.0293779 206s [69,] -0.761319 -0.676391 -0.0245494 0.2262894 -0.3396872 -0.1166505 206s [70,] 3.385399 4.360467 -0.7946150 -0.0417895 0.4474362 -4.6626174 206s [71,] -2.364955 -1.257673 0.5226907 -0.2346145 -0.7838777 0.1815821 206s [72,] 2.334511 -0.794530 0.0175620 0.1848925 -0.3437761 -0.4522442 206s [73,] -2.023440 -2.449907 0.2525041 -0.6657474 -0.5509480 0.2118442 206s [74,] -11.180192 2.456516 1.1036540 0.8711496 -0.3833194 1.3548314 206s [75,] 0.058297 -2.094811 0.3075211 -0.8052760 -0.9527729 0.5850255 206s [76,] -1.355742 -0.464355 -1.0183333 -0.8525619 -0.1577144 -0.0767323 206s [77,] -8.296881 0.945092 0.8088967 -0.0071463 -0.4527530 1.0614233 206s [78,] 1.251696 -1.460466 0.2511701 -0.2717606 -0.3158308 -0.2964813 206s [79,] -0.192380 -0.662365 -0.3671703 -0.6722658 -0.1243452 -0.2388225 206s [80,] -3.355201 1.915096 -0.1086672 0.3560062 0.0956865 0.6974817 206s [81,] 1.245305 0.736787 -0.1662155 0.1309822 -0.0122872 -0.2182528 206s [82,] 2.679561 -1.666401 1.1576691 0.3960280 -0.0059146 0.0584136 206s [83,] 2.596651 -0.556654 -0.0807307 -0.4468501 0.0964927 -0.3922894 206s [84,] 0.959377 -0.272038 -1.5879803 -1.1153057 0.3412508 -0.1281556 206s [85,] 0.602737 -1.384591 2.8844745 0.9479144 -0.7946454 -0.2014038 206s [86,] 0.698125 0.335743 -1.5248055 -0.4443037 0.0768256 -0.1999790 206s PC7 PC8 206s [1,] 0.9281777 -0.05158594 206s [2,] 0.8397946 -0.04276628 206s [3,] -0.5189230 0.04913688 206s [4,] -0.0178377 0.01578074 206s [5,] -0.0129237 0.01056305 206s [6,] -0.0764270 0.01469518 206s [7,] -0.3059779 0.04237267 206s [8,] -0.0684673 0.02289928 206s [9,] -0.2549733 -0.00832119 206s [10,] -0.0578118 -0.01894694 206s [11,] 0.0415545 -0.03474479 206s [12,] 0.0869267 -0.04485633 206s [13,] -0.2843977 -0.03100709 206s [14,] -0.3375083 -0.02155574 206s [15,] -0.1718828 -0.02996980 206s [16,] -0.4176728 0.03232381 206s [17,] -0.5923252 0.01765700 206s [18,] -0.3190679 0.04476532 206s [19,] -0.0279426 -0.00236626 206s [20,] 0.1299811 0.00586022 206s [21,] 0.0474059 0.00563264 206s [22,] -0.1240299 0.01123557 206s [23,] 0.2232631 0.00551065 206s [24,] 0.0122404 0.00060079 206s [25,] 0.2627442 -0.00824800 206s [26,] 0.2257329 -0.00440907 206s [27,] -0.8496967 0.05266701 206s [28,] 0.3473502 -0.00500580 206s [29,] 0.4172329 -0.00542705 206s [30,] 0.2773880 -0.00014648 206s [31,] -0.1224270 0.02372808 206s [32,] -0.2224748 0.00757892 206s [33,] -0.0633903 0.01236118 206s [34,] -0.2616599 0.00561781 206s [35,] -0.1671986 0.01988458 206s [36,] 0.4502086 -0.00418541 206s [37,] -0.0773232 0.02768282 206s [38,] 0.0464683 0.01134849 206s [39,] -0.0927182 0.00555823 206s [40,] -0.2162796 0.02467605 206s [41,] 0.9440753 -0.04806541 206s [42,] -0.0078920 0.02022925 206s [43,] 0.1152244 0.02074199 206s [44,] 1.0406693 -0.08815111 206s [45,] -0.1376804 0.01424369 206s [46,] 0.1673461 0.00442877 206s [47,] -0.4125225 0.01038694 206s [48,] 0.1556289 -0.02103354 206s [49,] 0.0434415 -0.01782739 206s [50,] 0.2518610 -0.02154540 206s [51,] -0.1186185 -0.00881133 206s [52,] 0.1507435 -0.04523343 206s [53,] 0.2161208 -0.00967982 206s [54,] 0.1374909 -0.00783970 206s [55,] 0.2417108 -0.00895268 206s [56,] 0.1253846 -0.01188643 206s [57,] 0.1390898 -0.01831232 206s [58,] 0.2219634 -0.00364174 206s [59,] -0.2045636 -0.00589047 206s [60,] -0.3679942 0.01673699 206s [61,] -0.0705611 -0.00273407 206s [62,] 0.1447701 -0.02026768 206s [63,] -0.1854788 0.02686899 206s [64,] -0.1854788 0.02686899 206s [65,] -0.2626650 -0.00376657 206s [66,] -0.3044266 0.00484197 206s [67,] -0.1358811 0.00605789 206s [68,] -0.0551482 -0.02379410 206s [69,] -0.0914891 0.00812122 206s [70,] 10.2524854 -0.64367029 206s [71,] -0.1326972 -0.01666774 206s [72,] 0.0051905 0.00656777 206s [73,] -0.8236843 0.03367265 206s [74,] 0.2140104 -0.04092219 206s [75,] -0.5684260 -0.00987116 206s [76,] -0.1225779 -0.00204629 206s [77,] -0.4235612 -0.00450631 206s [78,] -0.1935155 0.00973901 206s [79,] -0.1615883 0.00518643 206s [80,] 0.2915052 -0.02960159 206s [81,] 0.0908823 0.00038216 206s [82,] -0.3392789 0.02605374 206s [83,] 0.1112141 -0.00629308 206s [84,] 0.0510771 -0.00845572 206s [85,] 0.0748700 -0.01174487 206s [86,] 0.2488127 -0.01446339 206s ------------- 206s Call: 206s PcaGrid(x = x) 206s 206s Standard deviations: 206s [1] 3.034253 1.706044 1.167717 0.670864 0.536071 0.396285 0.266625 0.020768 206s ---------------------------------------------------------- 206s bushfire 38 5 5 38232.614428 1580.825276 206s Scores: 206s PC1 PC2 PC3 PC4 PC5 206s [1,] -67.120 -23.70481 -1.06551 1.129721 1.311630 206s [2,] -69.058 -21.42113 -1.54798 0.983735 0.430774 206s [3,] -61.939 -17.23665 -3.81386 -0.635074 -0.600149 206s [4,] -44.952 -16.53458 -5.16114 0.411753 -0.390518 206s [5,] -12.644 -21.62271 -7.14146 3.519877 -1.211923 206s [6,] 12.820 -27.86930 -7.66114 7.230422 0.040330 206s [7,] -194.634 -100.67730 27.43084 -0.026242 -0.134248 206s [8,] -229.349 -129.75912 -19.46346 25.591651 -18.592601 206s [9,] -230.306 -131.28743 -22.22175 27.251157 -19.214683 206s [10,] -231.118 -115.10815 3.70208 16.303210 -10.573515 206s [11,] -234.540 -100.24984 13.67112 10.325539 -8.727961 206s [12,] -246.507 -51.03515 27.61698 -5.352226 0.514087 206s [13,] -195.712 -5.81324 20.04485 -9.226807 1.721886 206s [14,] 49.881 16.90911 -9.97400 -1.900739 2.190429 206s [15,] 179.545 23.96999 -18.71166 -2.987136 1.332713 206s [16,] 135.356 15.81282 -9.24353 -4.703584 0.971669 206s [17,] 132.350 16.65014 -7.01838 -2.428578 1.346198 206s [18,] 121.499 9.75832 -4.45699 -1.587450 0.131923 206s [19,] 125.222 9.17601 -5.88919 0.582516 -0.061642 206s [20,] 135.112 14.63812 -5.90351 0.411704 1.460488 206s [21,] 116.581 14.47390 -3.04021 -1.842579 2.005998 206s [22,] 108.223 14.62103 -4.47428 -1.196993 3.288463 206s [23,] -22.095 3.26439 6.58391 -6.164581 2.125258 206s [24,] -77.831 3.46616 6.59280 -6.373595 1.545789 206s [25,] -13.092 3.41344 -0.99296 -5.076733 0.299636 206s [26,] -19.206 -0.17007 -1.84209 -4.858675 0.347945 206s [27,] -35.022 6.54155 -3.12767 -3.556587 -0.327873 206s [28,] -12.651 20.14894 -4.61607 -2.025539 -1.214190 206s [29,] -4.404 36.39823 -3.81590 -0.633155 -0.602027 206s [30,] -60.018 30.40980 9.44610 -1.763156 -0.765133 206s [31,] 67.689 47.40087 12.70229 9.791794 -0.671751 206s [32,] 324.134 63.46147 31.52512 30.099817 2.406344 206s [33,] 364.639 38.84260 51.20467 30.648590 3.218678 206s [34,] 361.089 37.09494 52.00522 29.394356 2.861158 206s [35,] 366.403 38.88889 52.31879 29.878844 4.650618 206s [36,] 363.821 37.40859 53.10394 28.286557 2.922632 206s [37,] 361.761 37.21276 55.73012 27.648760 4.477279 206s [38,] 363.106 37.78395 56.56345 27.460078 4.845396 206s ------------- 206s Call: 206s PcaGrid(x = x) 206s 206s Standard deviations: 206s [1] 195.5316 39.7596 11.7329 7.3743 1.7656 206s ---------------------------------------------------------- 206s ========================================================== 206s > 206s > ## IGNORE_RDIFF_BEGIN 206s > dodata(method="proj") 206s 206s Call: dodata(method = "proj") 206s Data Set n p k e1 e2 206s ========================================================== 206s heart 12 2 2 512.772467 29.052346 206s Scores: 206s PC1 PC2 206s [1,] 6.7568 3.2826 206s [2,] 63.0869 14.1293 206s [3,] 1.3852 -1.1318 206s [4,] -3.6709 1.8153 206s [5,] 19.0457 3.8035 206s [6,] -16.6413 3.1452 206s [7,] 5.3163 3.7464 206s [8,] -27.8536 -11.0863 206s [9,] -1.1638 -1.1788 206s [10,] -26.6915 -10.2803 206s [11,] -13.6842 -2.9790 206s [12,] 47.8395 11.2980 206s ------------- 206s Call: 206s PcaProj(x = x) 206s 206s Standard deviations: 206s [1] 22.644 5.390 206s ---------------------------------------------------------- 206s starsCYG 47 2 2 0.470874 0.024681 206s Scores: 206s PC1 PC2 206s [1,] 0.181333 -3.1013e-02 206s [2,] 0.696091 1.4569e-01 206s [3,] -0.121421 -1.3319e-01 206s [4,] 0.696091 1.4569e-01 206s [5,] 0.139530 -9.9951e-02 206s [6,] 0.413590 5.2989e-02 206s [7,] -0.412224 -5.4579e-01 206s [8,] 0.226508 1.6788e-01 206s [9,] 0.518364 -1.4980e-01 206s [10,] 0.071370 -2.8159e-02 206s [11,] 0.658332 -9.2369e-01 206s [12,] 0.402815 2.3259e-02 206s [13,] 0.374123 7.4020e-02 206s [14,] -1.007611 -3.6028e-01 206s [15,] -0.790417 -8.5818e-02 206s [16,] -0.467151 3.5835e-02 206s [17,] -1.111866 -1.3750e-01 206s [18,] -0.867017 4.6214e-02 206s [19,] -0.871946 -1.4372e-01 206s [20,] 0.818278 -9.2784e-01 206s [21,] -0.670457 -8.8932e-02 206s [22,] -0.830403 -8.4781e-02 206s [23,] -0.627097 3.9987e-02 206s [24,] -0.195426 9.8806e-02 206s [25,] -0.028337 -1.5568e-02 206s [26,] -0.387178 3.3760e-02 206s [27,] -0.390551 -9.6197e-02 206s [28,] -0.148297 -1.2454e-02 206s [29,] -0.662277 -1.5917e-01 206s [30,] 0.977965 -9.4199e-01 206s [31,] -0.628135 -7.3179e-16 206s [32,] 0.056306 1.6230e-01 206s [33,] 0.173412 4.9220e-02 206s [34,] 1.218143 -9.3822e-01 206s [35,] -0.712000 -1.4787e-01 206s [36,] 0.577688 2.0878e-01 206s [37,] 0.055528 1.3231e-01 206s [38,] 0.173412 4.9220e-02 206s [39,] 0.135501 1.3023e-01 206s [40,] 0.522775 2.0145e-02 206s [41,] -0.428203 -5.1892e-03 206s [42,] 0.013465 5.3371e-02 206s [43,] 0.294668 9.6089e-02 206s [44,] 0.293371 4.6106e-02 206s [45,] 0.495898 1.4088e-01 206s [46,] -0.066508 5.5447e-02 206s [47,] -0.547124 3.7911e-02 206s ------------- 206s Call: 206s PcaProj(x = x) 206s 206s Standard deviations: 206s [1] 0.6862 0.1571 206s ---------------------------------------------------------- 206s phosphor 18 2 2 388.639033 51.954664 206s Scores: 206s PC1 PC2 206s 1 5.8164 -15.1691 206s 2 -21.1936 -2.1132 206s 3 -23.6199 2.0585 206s 4 -11.2029 -6.7203 206s 5 -18.4220 1.3231 206s 6 17.1862 -19.2211 206s 7 1.6302 -3.1493 206s 8 -9.7695 3.1385 206s 9 -10.9174 5.3594 206s 10 15.6275 -6.3610 206s 11 -4.0194 1.2476 206s 12 9.3931 8.3149 206s 13 12.9944 6.5741 206s 14 6.9396 7.8348 206s 15 18.3964 3.9629 206s 16 -8.8365 -6.4202 206s 17 21.8073 6.4237 206s 18 16.8541 12.2611 206s ------------- 206s Call: 206s PcaProj(x = x) 206s 206s Standard deviations: 206s [1] 19.714 7.208 206s ---------------------------------------------------------- 206s stackloss 21 3 3 97.347030 38.052774 206s Scores: 206s PC1 PC2 PC3 206s [1,] 19.08066 -9.06092 -2.64544 206s [2,] 18.55152 -9.90152 -2.76118 206s [3,] 15.04269 -5.37517 -2.31373 206s [4,] 2.79667 -1.78925 1.70823 206s [5,] 2.21768 -1.17513 -0.10495 206s [6,] 2.50717 -1.48219 0.80164 206s [7,] 5.97151 3.25438 2.40268 206s [8,] 5.97151 3.25438 2.40268 206s [9,] -0.68332 0.30263 2.42495 206s [10,] -5.83478 -4.04630 -2.91819 206s [11,] -1.07253 3.51914 -1.87651 206s [12,] -1.89116 2.98559 -2.89885 206s [13,] -4.77650 -2.36509 -2.68671 206s [14,] 1.33353 6.57450 -0.50696 206s [15,] -7.45351 7.08878 1.37012 206s [16,] -9.04093 4.56697 1.02289 206s [17,] -16.15938 -7.50855 0.30909 206s [18,] -12.45541 -1.62432 1.11929 206s [19,] -11.63677 -1.09077 2.14162 206s [20,] -5.79275 -2.08680 -0.06187 206s [21,] 10.13623 -0.76824 -4.70180 206s ------------- 206s Call: 206s PcaProj(x = x) 206s 206s Standard deviations: 206s [1] 9.8665 6.1687 3.2669 206s ---------------------------------------------------------- 206s salinity 28 3 3 12.120566 8.431549 206s Scores: 206s PC1 PC2 PC3 206s 1 -2.52547 1.45945 -1.1943e-01 206s 2 -3.32298 2.15704 8.7594e-01 206s 3 -6.64947 -3.26398 1.0135e+00 206s 4 -6.64427 -1.81382 -1.6392e-01 206s 5 -6.16898 -2.52222 5.1373e+00 206s 6 -5.87594 0.26440 -3.1956e-15 206s 7 -4.23084 1.46250 -2.8008e-01 206s 8 -2.21502 2.76478 -8.3789e-01 206s 9 -0.40186 -2.17785 -1.6702e+00 206s 10 2.27089 -1.84923 7.3391e-01 206s 11 1.37935 -1.29276 2.1418e+00 206s 12 -0.22635 0.60372 -5.0980e-01 206s 13 0.27224 1.73920 -7.0505e-01 206s 14 2.36592 2.40462 6.4320e-01 206s 15 2.37640 -2.83174 5.2669e-01 206s 16 -2.49175 -4.77664 9.0404e+00 206s 17 -0.61250 -1.11672 1.4398e+00 206s 18 -2.91853 0.63310 -8.3666e-01 206s 19 -0.39732 -2.02029 -2.1396e+00 206s 20 1.47554 -1.23407 -1.1712e+00 206s 21 1.70104 1.92401 -1.1292e+00 206s 22 3.14437 2.81928 -5.2415e-01 206s 23 3.62890 -3.51450 2.6740e+00 206s 24 2.04538 -2.63992 3.0718e+00 206s 25 0.77088 -0.54783 -1.3370e-01 206s 26 1.57254 0.89176 -1.2089e+00 206s 27 2.63610 1.97075 -1.1855e+00 206s 28 3.55112 2.67606 -6.0915e-02 206s ------------- 206s Call: 206s PcaProj(x = x) 206s 206s Standard deviations: 206s [1] 3.4815 2.9037 1.3810 206s ---------------------------------------------------------- 206s hbk 75 3 3 3.801978 3.574192 206s Scores: 206s PC1 PC2 PC3 206s 1 28.747049 15.134042 2.3959241 206s 2 29.021724 16.318941 2.6207988 206s 3 31.271908 15.869319 3.4420860 206s 4 31.586189 17.508798 3.6246706 206s 5 31.299168 16.838093 3.2402573 206s 6 30.037754 15.591930 2.1421166 206s 7 29.888160 16.139376 1.9750096 206s 8 28.994463 15.350167 2.8226275 206s 9 30.758047 16.820526 3.7269602 206s 10 29.759314 16.079531 4.0486097 206s 11 35.301371 19.637962 3.7433562 206s 12 37.193371 18.709303 4.9915250 206s 13 35.634808 20.497713 1.4740727 206s 14 36.816439 27.523024 -2.3006796 206s 15 1.237203 -0.331072 -1.3801401 206s 16 -0.451166 -1.118847 -1.9707479 206s 17 -2.604733 0.067276 0.0130015 206s 18 0.179177 -0.804398 -0.1285240 206s 19 -0.765512 0.982349 -0.2513990 206s 20 1.236727 0.259123 -1.4210070 206s 21 0.428326 -0.503724 -0.6830690 206s 22 -0.724774 1.507943 -0.0022175 206s 23 -0.745349 -0.330094 -1.0982084 206s 24 -1.407850 -0.011831 -0.8987075 206s 25 -2.190427 -1.732051 0.4497793 206s 26 0.058631 1.444044 0.0446166 206s 27 1.680557 -0.429402 -0.6031146 206s 28 -0.315122 -1.179169 0.5822607 206s 29 -1.563355 -1.026914 0.1040012 206s 30 0.329957 -0.633156 1.8533795 206s 31 -0.110108 -1.617131 -1.0958807 206s 32 -2.035875 0.463421 -0.6346632 206s 33 -0.356033 0.740564 -0.8116369 206s 34 -2.342887 -1.340168 0.9724491 206s 35 1.607131 -0.379763 -0.3747630 206s 36 0.084455 0.486671 0.6551654 206s 37 -0.436144 1.659467 0.7145344 206s 38 -1.754819 -1.076076 -0.6037590 206s 39 -0.904375 -2.161949 0.3436723 206s 40 -1.455274 0.331839 0.1499308 206s 41 1.539788 -1.212921 -0.1715110 206s 42 -0.688338 -0.048173 1.7491184 206s 43 -1.635822 1.539067 -0.5208916 206s 44 0.511762 -1.165641 1.5020865 206s 45 -1.454500 -2.099954 0.0219268 206s 46 0.362645 -1.208389 1.3758464 206s 47 -0.615800 -2.658098 -0.4629006 206s 48 1.426278 -1.027667 0.0582638 206s 49 0.809592 -0.533893 -1.1232120 206s 50 0.996105 0.469082 -0.0988805 206s 51 -1.036368 -1.227376 -1.0843166 206s 52 -0.016464 -2.331540 -0.6477169 206s 53 -0.376625 -0.405855 2.4526088 206s 54 -1.524100 0.621590 -1.2927429 206s 55 -1.588523 0.591668 -0.2559428 206s 56 -0.592710 0.529426 -1.4111404 206s 57 -1.306991 -1.538024 -0.1841717 206s 58 0.275991 0.491888 -1.4739863 206s 59 0.598971 0.196673 0.6208960 206s 60 -0.127953 0.485014 1.8571970 206s 61 0.140584 1.905037 0.5838465 206s 62 -2.305069 -1.617811 0.3880825 206s 63 -1.666479 0.357251 -1.1934779 206s 64 1.480143 0.248671 -0.5959984 206s 65 0.309561 -1.219790 0.9671263 206s 66 -1.986789 0.248245 0.1723620 206s 67 -0.765691 -0.269054 -0.4611368 206s 68 -2.232721 -1.090790 1.3915841 206s 69 -1.502453 -1.813763 -0.4936268 206s 70 0.170883 0.584046 0.8369571 206s 71 0.543623 0.043244 -0.3707674 206s 72 -1.168908 0.341335 0.2837393 206s 73 -0.902885 0.411872 1.0546196 206s 74 -1.425273 0.852445 0.5719123 206s 75 -0.898536 -0.555475 2.0107684 206s ------------- 206s Call: 206s PcaProj(x = x) 206s 206s Standard deviations: 206s [1] 1.9499 1.8906 1.2797 206s ---------------------------------------------------------- 206s milk 86 8 8 8.369408 3.530461 206s Scores: 206s PC1 PC2 PC3 PC4 PC5 PC6 206s [1,] 6.337004 -0.245000 0.7704092 -4.9848e-01 -1.6599e-01 1.1763e-01 206s [2,] 7.021899 1.030349 0.2832977 -1.2673e+00 -8.7296e-01 2.0547e-01 206s [3,] 0.600831 1.686247 0.9682032 -3.2663e-02 7.4112e-02 4.7412e-01 206s [4,] 5.206465 2.665956 1.5942253 9.8285e-01 -5.4159e-01 -2.0155e-01 206s [5,] -0.955757 -0.579889 0.3206393 5.1174e-01 -6.1684e-01 -3.8990e-02 206s [6,] 2.198695 0.073770 -0.5712493 1.9440e-01 -1.0237e-01 4.1825e-02 206s [7,] 2.695361 0.644049 -0.8645373 8.1894e-02 -2.6953e-01 1.6884e-01 206s [8,] 2.945361 0.137227 -0.2071463 5.0841e-01 -4.2075e-01 5.8589e-02 206s [9,] -1.539013 1.879894 1.6952390 1.6792e-01 -2.8195e-01 5.0563e-02 206s [10,] -2.977110 0.319666 0.3515636 -5.2496e-01 4.6898e-01 8.5978e-03 206s [11,] -9.375355 -1.638105 1.9026171 4.1237e-01 1.8768e-02 -1.8546e-01 206s [12,] -12.602600 -4.715888 0.0273004 -4.7798e-02 -1.2246e-02 9.6858e-03 206s [13,] -10.114331 -2.487462 -1.6331544 -1.5139e+00 4.1903e-01 2.8313e-01 206s [14,] -11.949336 -3.190157 -0.2146943 -5.0060e-01 -2.9537e-01 3.2160e-01 206s [15,] -10.595396 -1.905517 2.3716887 7.6651e-01 -3.3531e-01 1.9933e-02 206s [16,] -2.735720 -0.748282 0.6750464 7.2415e-01 5.5304e-01 2.2283e-01 206s [17,] -1.248116 2.131195 2.2596886 6.4958e-01 3.5634e-01 2.9021e-01 206s [18,] -1.904210 -1.285804 -0.7746460 3.0198e-01 -2.7407e-01 1.7500e-01 206s [19,] -1.902313 0.095461 1.3824711 5.0369e-01 2.2193e-01 -5.5628e-02 206s [20,] 0.123220 1.399444 1.1517634 3.2546e-01 7.8261e-02 -4.0733e-01 206s [21,] -2.436023 -2.524827 -1.0197416 3.4819e-01 -1.4914e-01 -4.3669e-02 206s [22,] -0.904931 -1.114894 -0.1235807 2.0285e-01 -1.6200e-01 2.5681e-01 206s [23,] 0.220231 -1.767325 0.0482262 6.4418e-01 9.8618e-02 -5.7683e-02 206s [24,] -0.274403 -1.561826 0.3820323 7.0016e-01 5.5220e-01 1.4376e-01 206s [25,] -3.306400 -2.980247 0.0252488 9.4001e-01 -1.0841e-01 -2.5303e-01 206s [26,] -0.658015 -1.625199 0.3021005 7.2702e-01 -3.0299e-01 -1.2339e-01 206s [27,] -3.137066 -0.774218 0.5577497 6.4188e-01 -8.0125e-02 7.7819e-01 206s [28,] 2.867950 -3.099435 -0.6435415 1.0366e+00 1.5908e-01 7.6524e-02 206s [29,] 4.523097 -0.527338 -0.1032516 6.4537e-01 4.7286e-01 -2.7166e-01 206s [30,] 1.002381 -1.376693 -0.2735956 5.0522e-01 -1.2750e-01 -1.6178e-01 206s [31,] 1.894615 -1.296202 -1.9117282 -3.8032e-01 4.6473e-01 3.1085e-01 206s [32,] 1.210291 0.067230 -0.9832930 -8.5379e-01 3.2823e-01 4.9994e-01 206s [33,] 1.964118 0.022175 0.1818518 3.0464e-01 3.5596e-01 1.4985e-01 206s [34,] 0.576738 0.567851 0.6982155 1.8415e-01 1.8695e-01 3.2706e-01 206s [35,] -0.231793 -2.143909 -0.6825523 4.0681e-01 5.4492e-01 3.6259e-01 206s [36,] 4.250883 -0.719760 0.2157706 7.7167e-01 -1.9064e-01 -2.0611e-01 206s [37,] 1.077364 -2.054664 -1.3064867 1.0043e-01 8.6092e-02 3.5416e-01 206s [38,] 2.259260 -1.653588 -0.6730692 5.7300e-01 1.6930e-01 1.6986e-01 206s [39,] -1.251576 -1.451593 0.4671580 5.8957e-01 4.2672e-01 2.2495e-01 206s [40,] 3.304245 1.998193 1.0941231 1.3734e-01 3.7012e-01 2.4142e-01 206s [41,] 4.286315 -1.280951 0.5856744 -6.0980e-01 -4.3090e-01 1.9801e-01 206s [42,] 6.343820 1.801880 1.3481119 1.0355e+00 2.9802e-01 -8.4501e-04 206s [43,] 3.119491 0.214077 -1.1216236 -3.8134e-01 -1.9523e-01 -2.6706e-02 206s [44,] 5.285254 0.938072 0.7440487 1.1539e-02 8.1629e-01 -7.9286e-01 206s [45,] 0.082429 -0.416631 -0.1588203 2.3098e-01 5.1867e-01 9.4503e-02 206s [46,] 0.357862 -1.951997 -0.0731829 7.0393e-01 1.8828e-01 1.5707e-02 206s [47,] 2.428744 1.522538 -3.0467213 -1.9114e+00 2.4638e-01 3.5871e-01 206s [48,] 0.282348 -0.697287 -1.1592508 -5.4929e-01 6.2199e-01 -5.4596e-02 206s [49,] -2.266009 -0.559548 -1.3794914 -1.1300e+00 7.8872e-01 -2.0411e-02 206s [50,] 2.868649 2.860857 1.6128307 6.7382e-02 2.2344e-01 -4.1484e-01 206s [51,] -1.596061 0.546812 -1.1779327 -1.0512e+00 1.3522e-01 -9.4865e-03 206s [52,] -5.186121 -1.000829 -0.7440599 -9.6302e-01 3.0732e-01 -1.7009e-01 206s [53,] -0.800232 0.049087 -0.6946842 -5.8284e-01 -2.1277e-01 -2.7004e-01 206s [54,] -0.246388 -0.030606 -0.1814302 -1.1632e-01 5.7767e-02 -1.8637e-01 206s [55,] 0.914315 -0.428594 -0.4919557 4.5039e-02 -2.7868e-01 -2.2140e-01 206s [56,] -0.061827 0.583572 0.3263056 -1.1589e-01 -1.2973e-01 -1.6518e-01 206s [57,] -1.295979 -0.421943 0.8410805 3.0441e-01 -3.9478e-01 -4.5233e-02 206s [58,] 0.174908 -1.343854 0.0115086 8.0227e-01 -3.9364e-01 -2.2918e-01 206s [59,] -1.869684 0.840823 0.0109543 -5.5536e-01 -1.4155e-01 1.0613e-01 206s [60,] -1.614271 0.557309 -0.0690787 -9.1753e-02 -3.0975e-01 1.6192e-01 206s [61,] -0.258192 1.434984 0.7684636 -1.1998e-01 -3.4662e-01 -4.8808e-02 206s [62,] 2.000275 2.204730 1.1194067 -2.3783e-01 5.9953e-02 -1.5836e-01 206s [63,] 2.694063 0.555482 -0.0340910 6.4470e-01 -2.2417e-01 1.9442e-02 206s [64,] 2.694063 0.555482 -0.0340910 6.4470e-01 -2.2417e-01 1.9442e-02 206s [65,] -0.822201 2.427550 1.5859438 -3.5437e-16 2.2436e-15 -4.7251e-15 206s [66,] -2.545586 0.605953 0.1469837 -3.5318e-01 -2.5871e-01 1.6901e-01 206s [67,] 0.028900 1.253717 0.4474540 5.3595e-02 1.6063e-01 -1.0980e-01 206s [68,] -1.086135 1.968868 -0.7220293 -1.6576e+00 6.2061e-02 -7.0998e-04 206s [69,] -0.836638 0.660453 0.0049966 1.3663e-01 -1.0131e-01 -2.4008e-01 206s [70,] 4.843092 -6.035092 0.8250084 -3.4481e+00 -4.8538e+00 -7.8407e+00 206s [71,] -2.500038 1.146245 0.6967314 -2.4611e-01 -1.4266e-01 -8.2996e-02 206s [72,] 2.220676 1.122951 -0.2444075 1.1066e-01 -3.1540e-01 -2.1344e-01 206s [73,] -2.310518 2.354552 0.2706503 -6.4192e-01 2.0566e-01 4.5520e-01 206s [74,] -10.802799 -3.462655 2.2031446 1.1326e+00 2.8049e-01 -2.9749e-01 206s [75,] -0.301038 2.284366 0.2440764 -6.9450e-01 2.6435e-01 4.3129e-01 206s [76,] -1.477936 0.245154 -0.8869850 -8.9900e-01 -9.8013e-02 1.1983e-01 206s [77,] -8.169236 -1.599780 1.4987144 3.7767e-01 2.4726e-01 3.8246e-01 206s [78,] 1.096654 1.646072 0.0591327 -3.3138e-01 -1.7936e-01 6.2716e-02 206s [79,] -0.289199 0.625796 -0.3974294 -6.6099e-01 -2.0857e-01 2.1190e-01 206s [80,] -3.160557 -2.282579 0.3255355 4.6181e-01 2.7753e-01 -1.5673e-01 206s [81,] 1.284356 -0.548854 -0.2907281 2.4017e-01 -2.5254e-01 -1.4289e-03 206s [82,] 2.562817 2.019485 0.8249162 3.2973e-01 3.3866e-01 1.3889e-01 206s [83,] 2.538825 0.759863 -0.3142506 -5.1028e-01 -2.0539e-01 8.8979e-02 206s [84,] 0.841123 0.110035 -1.5793120 -1.2807e+00 1.2332e-01 1.6224e-01 206s [85,] 0.636271 1.793014 2.6824860 1.0329e+00 -4.8850e-01 -2.3012e-01 206s [86,] 0.633183 -0.426511 -1.4791366 -6.1314e-01 -7.0534e-02 -2.3778e-01 206s PC7 PC8 206s [1,] 1.0196e-01 -1.7180e-03 206s [2,] 2.6131e-01 -8.5191e-03 206s [3,] 6.9637e-01 -8.0573e-03 206s [4,] -1.3548e-01 -1.4969e-03 206s [5,] 3.1443e-02 -2.7307e-03 206s [6,] -2.5079e-01 3.6450e-03 206s [7,] 4.5377e-02 -2.6071e-03 206s [8,] -1.6060e-01 -2.3761e-04 206s [9,] -1.5152e-01 -4.3079e-04 206s [10,] 9.1089e-02 1.9536e-03 206s [11,] 2.5654e-01 -1.4875e-03 206s [12,] -2.3798e-03 -1.0954e-04 206s [13,] -1.3687e-01 2.8402e-03 206s [14,] -6.5248e-02 -1.5114e-03 206s [15,] 3.7695e-02 -2.7827e-03 206s [16,] 3.8131e-01 -3.7990e-03 206s [17,] 4.5661e-02 -1.4965e-03 206s [18,] 3.9910e-01 -7.2703e-03 206s [19,] 2.9353e-01 -3.3342e-03 206s [20,] 6.0915e-01 -6.0837e-03 206s [21,] -1.0079e-01 1.0179e-03 206s [22,] -2.2945e-02 -1.0515e-03 206s [23,] 2.3631e-01 -2.5558e-03 206s [24,] -7.7207e-02 3.4800e-03 206s [25,] 1.4903e-02 -3.2430e-04 206s [26,] 3.8032e-03 -2.1705e-03 206s [27,] 3.7208e-02 -3.0631e-03 206s [28,] -4.8147e-01 6.1089e-03 206s [29,] -4.0388e-02 2.8549e-03 206s [30,] 3.4318e-02 -1.0014e-03 206s [31,] -2.2872e-02 1.8706e-03 206s [32,] -8.4542e-02 1.3368e-03 206s [33,] 4.5274e-02 5.3383e-04 206s [34,] -2.0048e-01 2.4727e-03 206s [35,] -5.6482e-02 2.9923e-03 206s [36,] -2.6046e-02 -1.2910e-03 206s [37,] 9.6038e-02 -1.8897e-03 206s [38,] -2.9035e-01 4.4317e-03 206s [39,] -4.6322e-03 2.4336e-03 206s [40,] 3.8686e-01 -3.9300e-03 206s [41,] 3.7834e-01 -7.8976e-03 206s [42,] -8.2037e-04 -4.3106e-05 206s [43,] 3.3467e-01 -5.2401e-03 206s [44,] -6.2170e-01 1.2840e-02 206s [45,] 5.3557e-02 2.9156e-03 206s [46,] 5.1785e-04 2.0738e-03 206s [47,] -5.2141e-01 5.7206e-03 206s [48,] -2.7669e-01 6.7329e-03 206s [49,] 8.4319e-02 3.8528e-03 206s [50,] 1.4210e-01 1.6961e-04 206s [51,] -1.1871e-01 2.6676e-03 206s [52,] -2.5036e-01 6.4121e-03 206s [53,] 2.2399e-01 -2.8200e-03 206s [54,] 5.6532e-02 4.9304e-04 206s [55,] -1.4343e-01 1.2558e-03 206s [56,] 4.1682e-02 -9.6490e-04 206s [57,] -1.3014e-01 -6.2709e-04 206s [58,] -2.1428e-01 8.2594e-04 206s [59,] -7.9775e-02 -8.9776e-04 206s [60,] -8.6835e-02 -1.0498e-03 206s [61,] 6.2470e-02 -2.7499e-03 206s [62,] 3.3052e-02 -3.2369e-04 206s [63,] -1.7137e-01 -3.1087e-04 206s [64,] -1.7137e-01 -3.1087e-04 206s [65,] -1.4435e-14 -1.8299e-12 206s [66,] -2.2016e-02 -1.2206e-03 206s [67,] 8.5160e-02 -1.4837e-04 206s [68,] -2.2535e-03 1.9054e-04 206s [69,] 5.9976e-02 -8.6961e-04 206s [70,] 1.0448e+00 -2.0167e-02 206s [71,] -1.7609e-01 1.9378e-03 206s [72,] -1.7047e-01 2.6076e-04 206s [73,] 1.1885e-01 -8.1624e-04 206s [74,] 2.0942e-01 3.3164e-03 206s [75,] -7.7528e-01 9.9316e-03 206s [76,] -4.6285e-03 2.5153e-04 206s [77,] 7.0218e-02 1.5708e-03 206s [78,] -1.4859e-02 -6.7049e-04 206s [79,] 5.1054e-02 -2.0198e-03 206s [80,] -1.5770e-01 4.9579e-03 206s [81,] -1.9411e-01 4.4401e-04 206s [82,] 6.0634e-02 8.7960e-04 206s [83,] -4.4635e-02 -1.7048e-03 206s [84,] -2.3612e-03 -2.2242e-04 206s [85,] -5.5171e-02 -1.1222e-03 206s [86,] -1.4972e-01 1.4543e-03 206s ------------- 206s Call: 206s PcaProj(x = x) 206s 206s Standard deviations: 206s [1] 2.8929930 1.8789522 0.9946460 0.7479403 0.3744197 0.2596328 0.1421387 206s [8] 0.0025753 206s ---------------------------------------------------------- 206s bushfire 38 5 5 37473.439646 1742.633018 206s Scores: 206s PC1 PC2 PC3 PC4 PC5 206s [1,] -67.2152 -2.3010e+01 4.4179e+00 1.0892e+00 1.7536e+00 206s [2,] -69.0225 -2.1417e+01 2.5382e+00 1.1092e+00 9.3919e-01 206s [3,] -61.6651 -1.8580e+01 -6.1022e-01 -8.1124e-01 -1.6462e-01 206s [4,] -44.5883 -1.8234e+01 -3.9899e-01 -5.2145e-01 2.0050e-01 206s [5,] -12.2941 -2.2954e+01 3.5970e+00 1.1037e+00 -2.4384e-01 206s [6,] 13.0282 -2.8133e+01 8.7670e+00 3.4751e+00 1.3728e+00 206s [7,] -199.0774 -7.7956e+01 5.4935e+01 6.3134e+00 -1.9919e+00 206s [8,] -228.2849 -1.3258e+02 2.2340e+01 2.1656e+01 -1.2594e+01 206s [9,] -228.9164 -1.3560e+02 2.0463e+01 2.2625e+01 -1.2743e+01 206s [10,] -232.4703 -1.0661e+02 3.5597e+01 1.7915e+01 -7.7659e+00 206s [11,] -236.7410 -8.8072e+01 3.6632e+01 1.5095e+01 -7.4695e+00 206s [12,] -249.4091 -3.6830e+01 2.4010e+01 4.7317e+00 -1.2986e+00 206s [13,] -197.0450 2.3179e-14 2.4481e-14 -1.1772e-13 -5.9580e-13 206s [14,] 50.9487 1.1397e+01 -1.1247e+01 -4.8733e+00 2.4511e+00 206s [15,] 180.7896 1.7571e+01 -8.0454e+00 -1.0582e+01 1.2714e+00 206s [16,] 135.6178 1.4189e+01 -4.9116e-01 -9.2701e+00 1.4021e-01 206s [17,] 132.5344 1.5577e+01 2.2990e-01 -6.4963e+00 7.3370e-01 206s [18,] 121.3422 1.0471e+01 4.5656e+00 -4.9831e+00 -5.2314e-01 206s [19,] 125.2722 9.0272e+00 3.7365e+00 -3.3313e+00 -2.9097e-01 206s [20,] 135.2370 1.4091e+01 2.0639e+00 -3.6800e+00 1.1733e+00 206s [21,] 116.4250 1.5147e+01 2.9085e+00 -4.8084e+00 1.2603e+00 206s [22,] 108.2925 1.4223e+01 7.7165e-01 -4.5065e+00 2.7943e+00 206s [23,] -22.8258 6.4234e+00 2.4654e+00 -3.9627e+00 7.9847e-01 206s [24,] -78.1850 4.6631e+00 -3.6818e+00 -2.7688e+00 5.8508e-01 206s [25,] -13.0417 2.7521e+00 -3.1955e+00 -4.6824e+00 -3.1085e-01 206s [26,] -19.1244 -9.5045e-01 -2.6771e+00 -4.7104e+00 -1.6172e-01 206s [27,] -34.4379 3.2761e+00 -9.2826e+00 -2.9861e+00 -3.3561e-01 206s [28,] -11.5852 1.4506e+01 -1.5649e+01 -1.6260e+00 -8.5347e-01 206s [29,] -2.9366 2.8741e+01 -2.2907e+01 3.9749e-01 3.5861e-02 206s [30,] -59.7518 2.8633e+01 -1.4710e+01 3.5226e+00 -9.9066e-01 206s [31,] 67.8017 4.7241e+01 -9.1255e+00 1.3201e+01 6.9227e-14 206s [32,] 321.9941 7.6188e+01 2.2491e+01 3.1537e+01 3.2368e+00 206s [33,] 359.5155 6.6710e+01 5.6061e+01 3.4541e+01 2.0718e+00 206s [34,] 355.8007 6.5695e+01 5.7430e+01 3.3578e+01 1.4640e+00 206s [35,] 361.1076 6.7577e+01 5.7402e+01 3.3832e+01 3.2618e+00 206s [36,] 358.3592 6.6791e+01 5.8643e+01 3.2720e+01 1.2487e+00 206s [37,] 355.9974 6.8071e+01 6.0927e+01 3.2560e+01 2.4898e+00 206s [38,] 357.2530 6.9073e+01 6.1517e+01 3.2523e+01 2.7558e+00 206s ------------- 206s Call: 206s PcaProj(x = x) 206s 206s Standard deviations: 206s [1] 193.5806 41.7449 16.7665 8.1585 1.6074 206s ---------------------------------------------------------- 206s ========================================================== 206s > ## IGNORE_RDIFF_END 206s > 206s > ## VT::14.11.2018 - commented out - on some platforms PcaHubert will choose only 1 PC 206s > ## and will show difference 206s > ## test.case.1() 206s > 206s > test.case.2() 206s [1] TRUE 206s [1] TRUE 206s [1] TRUE 206s [1] TRUE 206s [1] TRUE 206s [1] TRUE 206s [1] TRUE 206s [1] TRUE 206s [1] TRUE 206s [1] TRUE 206s > 206s BEGIN TEST tlda.R 206s 206s R version 4.5.2 (2025-10-31) -- "[Not] Part in a Rumble" 206s Copyright (C) 2025 The R Foundation for Statistical Computing 206s Platform: aarch64-unknown-linux-gnu 206s 206s R is free software and comes with ABSOLUTELY NO WARRANTY. 206s You are welcome to redistribute it under certain conditions. 206s Type 'license()' or 'licence()' for distribution details. 206s 206s R is a collaborative project with many contributors. 206s Type 'contributors()' for more information and 206s 'citation()' on how to cite R or R packages in publications. 206s 206s Type 'demo()' for some demos, 'help()' for on-line help, or 206s 'help.start()' for an HTML browser interface to help. 206s Type 'q()' to quit R. 206s 207s > ## VT::15.09.2013 - this will render the output independent 207s > ## from the version of the package 207s > suppressPackageStartupMessages(library(rrcov)) 207s > library(MASS) 207s > 207s > ## VT::14.01.2020 207s > ## On some platforms minor differences are shown - use 207s > ## IGNORE_RDIFF_BEGIN 207s > ## IGNORE_RDIFF_END 207s > 207s > dodata <- function(method) { 207s + 207s + options(digits = 5) 207s + set.seed(101) # <<-- sub-sampling algorithm now based on R's RNG and seed 207s + 207s + tmp <- sys.call() 207s + cat("\nCall: ", deparse(substitute(tmp)),"\n") 207s + cat("===================================================\n") 207s + 207s + cat("\nData: ", "hemophilia\n") 207s + data(hemophilia) 207s + show(rlda <- Linda(as.factor(gr)~., data=hemophilia, method=method)) 207s + show(predict(rlda)) 207s + 207s + cat("\nData: ", "anorexia\n") 207s + data(anorexia) 207s + show(rlda <- Linda(Treat~., data=anorexia, method=method)) 207s + show(predict(rlda)) 207s + 207s + cat("\nData: ", "Pima\n") 207s + data(Pima.tr) 207s + show(rlda <- Linda(type~., data=Pima.tr, method=method)) 207s + show(predict(rlda)) 207s + 207s + cat("\nData: ", "Forest soils\n") 207s + data(soil) 207s + soil1983 <- soil[soil$D == 0, -2] # only 1983, remove column D (always 0) 207s + 207s + ## This will not work within the function, of course 207s + ## - comment it out 207s + ## IGNORE_RDIFF_BEGIN 207s + rlda <- Linda(F~., data=soil1983, method=method) 207s + ## show(rlda) 207s + ## IGNORE_RDIFF_END 207s + show(predict(rlda)) 207s + 207s + cat("\nData: ", "Raven and Miller diabetes data\n") 207s + data(diabetes) 207s + show(rlda <- Linda(group~insulin+glucose+sspg, data=diabetes, method=method)) 207s + show(predict(rlda)) 207s + 207s + cat("\nData: ", "iris\n") 207s + data(iris) 207s + if(method != "mcdA") 207s + { 207s + show(rlda <- Linda(Species~., data=iris, method=method, l1med=TRUE)) 207s + show(predict(rlda)) 207s + } 207s + 207s + cat("\nData: ", "crabs\n") 207s + data(crabs) 207s + show(rlda <- Linda(sp~., data=crabs, method=method)) 207s + show(predict(rlda)) 207s + 207s + cat("\nData: ", "fish\n") 207s + data(fish) 207s + fish <- fish[-14,] # remove observation #14 containing missing value 207s + 207s + # The height and width are calculated as percentages 207s + # of the third length variable 207s + fish[,5] <- fish[,5]*fish[,4]/100 207s + fish[,6] <- fish[,6]*fish[,4]/100 207s + 207s + ## There is one class with only 6 observations (p=6). Normally 207s + ## Linda will fail, therefore use l1med=TRUE. 207s + ## This works only for methods mcdB and mcdC 207s + 207s + table(fish$Species) 207s + if(method != "mcdA") 207s + { 207s + ## IGNORE_RDIFF_BEGIN 207s + rlda <- Linda(Species~., data=fish, method=method, l1med=TRUE) 207s + ## show(rlda) 207s + ## IGNORE_RDIFF_END 207s + show(predict(rlda)) 207s + } 207s + 207s + cat("\nData: ", "pottery\n") 207s + data(pottery) 207s + show(rlda <- Linda(origin~., data=pottery, method=method)) 207s + show(predict(rlda)) 207s + 207s + cat("\nData: ", "olitos\n") 207s + data(olitos) 207s + if(method != "mcdA") 207s + { 207s + ## IGNORE_RDIFF_BEGIN 207s + rlda <- Linda(grp~., data=olitos, method=method, l1med=TRUE) 207s + ## show(rlda) 207s + ## IGNORE_RDIFF_END 207s + show(predict(rlda)) 207s + } 207s + 207s + cat("===================================================\n") 207s + } 207s > 207s > 207s > ## -- now do it: 207s > dodata(method="mcdA") 207s 207s Call: dodata(method = "mcdA") 207s =================================================== 207s 207s Data: hemophilia 207s Call: 207s Linda(as.factor(gr) ~ ., data = hemophilia, method = method) 207s 207s Prior Probabilities of Groups: 207s carrier normal 207s 0.6 0.4 207s 207s Group means: 207s AHFactivity AHFantigen 207s carrier -0.30795 -0.0059911 207s normal -0.12920 -0.0603000 207s 207s Within-groups Covariance Matrix: 207s AHFactivity AHFantigen 207s AHFactivity 0.018036 0.011853 207s AHFantigen 0.011853 0.019185 207s 207s Linear Coeficients: 207s AHFactivity AHFantigen 207s carrier -28.4029 17.2368 207s normal -8.5834 2.1602 207s 207s Constants: 207s carrier normal 207s -4.8325 -1.4056 207s 207s Apparent error rate 0.1333 207s 207s Classification table 207s Predicted 207s Actual carrier normal 207s carrier 39 6 207s normal 4 26 207s 207s Confusion matrix 207s Predicted 207s Actual carrier normal 207s carrier 0.867 0.133 207s normal 0.133 0.867 207s 207s Data: anorexia 207s Call: 207s Linda(Treat ~ ., data = anorexia, method = method) 207s 207s Prior Probabilities of Groups: 207s CBT Cont FT 207s 0.40278 0.36111 0.23611 207s 207s Group means: 207s Prewt Postwt 207s CBT 82.633 82.950 207s Cont 81.558 81.108 207s FT 84.331 94.762 207s 207s Within-groups Covariance Matrix: 207s Prewt Postwt 207s Prewt 26.9291 3.3862 207s Postwt 3.3862 18.2368 207s 207s Linear Coeficients: 207s Prewt Postwt 207s CBT 2.5563 4.0738 207s Cont 2.5284 3.9780 207s FT 2.5374 4.7250 207s 207s Constants: 207s CBT Cont FT 207s -275.49 -265.45 -332.31 207s 207s Apparent error rate 0.3889 207s 207s Classification table 207s Predicted 207s Actual CBT Cont FT 207s CBT 16 5 8 207s Cont 11 15 0 207s FT 0 4 13 207s 207s Confusion matrix 207s Predicted 207s Actual CBT Cont FT 207s CBT 0.552 0.172 0.276 207s Cont 0.423 0.577 0.000 207s FT 0.000 0.235 0.765 207s 207s Data: Pima 207s Call: 207s Linda(type ~ ., data = Pima.tr, method = method) 207s 207s Prior Probabilities of Groups: 207s No Yes 207s 0.66 0.34 207s 207s Group means: 207s npreg glu bp skin bmi ped age 207s No 1.8602 107.69 67.344 25.29 30.642 0.40777 24.667 207s Yes 5.3167 145.85 74.283 31.80 34.095 0.49533 37.883 207s 207s Within-groups Covariance Matrix: 207s npreg glu bp skin bmi ped age 207s npreg 8.51105 -5.61029 4.756672 1.52732 0.82066 -0.010070 12.382693 207s glu -5.61029 656.11894 49.855724 16.67486 23.07833 -0.352475 17.724967 207s bp 4.75667 49.85572 119.426757 29.64563 12.90698 -0.049538 21.287178 207s skin 1.52732 16.67486 29.645632 113.19900 44.15972 -0.157594 6.741105 207s bmi 0.82066 23.07833 12.906985 44.15972 35.54164 0.038640 1.481520 207s ped -0.01007 -0.35247 -0.049538 -0.15759 0.03864 0.062664 -0.069636 207s age 12.38269 17.72497 21.287178 6.74110 1.48152 -0.069636 64.887154 207s 207s Linear Coeficients: 207s npreg glu bp skin bmi ped age 207s No -0.45855 0.092789 0.45848 -0.30675 1.0075 6.2670 0.30749 207s Yes -0.22400 0.150013 0.44787 -0.26148 1.0015 8.2935 0.45187 207s 207s Constants: 207s No Yes 207s -37.050 -51.586 207s 207s Apparent error rate 0.22 207s 207s Classification table 207s Predicted 207s Actual No Yes 207s No 107 25 207s Yes 19 49 207s 207s Confusion matrix 207s Predicted 207s Actual No Yes 207s No 0.811 0.189 207s Yes 0.279 0.721 207s 207s Data: Forest soils 207s 207s Apparent error rate 0.3103 207s 207s Classification table 207s Predicted 207s Actual 1 2 3 207s 1 7 2 2 207s 2 3 13 7 207s 3 1 3 20 207s 207s Confusion matrix 207s Predicted 207s Actual 1 2 3 207s 1 0.636 0.182 0.182 207s 2 0.130 0.565 0.304 207s 3 0.042 0.125 0.833 207s 207s Data: Raven and Miller diabetes data 207s Call: 207s Linda(group ~ insulin + glucose + sspg, data = diabetes, method = method) 207s 207s Prior Probabilities of Groups: 207s normal chemical overt 207s 0.52414 0.24828 0.22759 207s 207s Group means: 207s insulin glucose sspg 207s normal 163.939 345.8 99.076 207s chemical 299.448 476.9 223.621 207s overt 95.958 1026.4 343.000 207s 207s Within-groups Covariance Matrix: 207s insulin glucose sspg 207s insulin 7582.0 -1263.1 1095.8 207s glucose -1263.1 18952.4 4919.3 207s sspg 1095.8 4919.3 3351.2 207s 207s Linear Coeficients: 207s insulin glucose sspg 207s normal 0.027694 0.023859 -0.014514 207s chemical 0.040288 0.022532 0.020479 207s overt 0.017144 0.048768 0.025158 207s 207s Constants: 207s normal chemical overt 207s -6.3223 -15.0879 -31.6445 207s 207s Apparent error rate 0.1862 207s 207s Classification table 207s Predicted 207s Actual normal chemical overt 207s normal 69 7 0 207s chemical 13 23 0 207s overt 2 5 26 207s 207s Confusion matrix 207s Predicted 207s Actual normal chemical overt 207s normal 0.908 0.092 0.000 207s chemical 0.361 0.639 0.000 207s overt 0.061 0.152 0.788 207s 207s Data: iris 207s 207s Data: crabs 207s Call: 207s Linda(sp ~ ., data = crabs, method = method) 207s 207s Prior Probabilities of Groups: 207s B O 207s 0.5 0.5 207s 207s Group means: 207s sexM index FL RW CL CW BD 207s B 0.34722 27.333 14.211 12.253 30.397 35.117 12.765 207s O 0.56627 25.554 17.131 13.405 34.247 38.155 15.525 207s 207s Within-groups Covariance Matrix: 207s sexM index FL RW CL CW BD 207s sexM 0.26391 0.76754 0.18606 -0.33763 0.65944 0.59857 0.28932 207s index 0.76754 191.38080 38.42685 26.32923 82.43953 91.89091 38.13688 207s FL 0.18606 38.42685 8.50147 5.68789 18.13749 20.30739 8.30920 207s RW -0.33763 26.32923 5.68789 4.95782 11.90225 13.61117 5.45814 207s CL 0.65944 82.43953 18.13749 11.90225 39.60115 44.10886 18.09504 207s CW 0.59857 91.89091 20.30739 13.61117 44.10886 49.42616 20.17554 207s BD 0.28932 38.13688 8.30920 5.45814 18.09504 20.17554 8.39525 207s 207s Linear Coeficients: 207s sexM index FL RW CL CW BD 207s B 29.104 -2.4938 10.809 15.613 0.8320 -4.2978 -0.46788 207s O 42.470 -3.9361 26.427 22.857 2.8582 -17.1526 12.31048 207s 207s Constants: 207s B O 207s -78.317 -159.259 207s 207s Apparent error rate 0 207s 207s Classification table 207s Predicted 207s Actual B O 207s B 100 0 207s O 0 100 207s 207s Confusion matrix 207s Predicted 207s Actual B O 207s B 1 0 207s O 0 1 207s 207s Data: fish 207s 207s Data: pottery 207s Call: 207s Linda(origin ~ ., data = pottery, method = method) 207s 207s Prior Probabilities of Groups: 207s Attic Eritrean 207s 0.48148 0.51852 207s 207s Group means: 207s SI AL FE MG CA TI 207s Attic 55.36 13.73 9.82 5.45 6.03 0.863 207s Eritrean 52.52 16.23 9.13 3.09 6.26 0.814 207s 207s Within-groups Covariance Matrix: 207s SI AL FE MG CA TI 207s SI 13.5941404 2.986675 -0.651132 0.173577 -0.350984 -0.0051996 207s AL 2.9866747 1.622412 0.485167 0.712400 0.077443 0.0133306 207s FE -0.6511317 0.485167 1.065427 -0.403601 -1.936552 0.0576472 207s MG 0.1735766 0.712400 -0.403601 2.814948 3.262786 -0.0427129 207s CA -0.3509837 0.077443 -1.936552 3.262786 7.720320 -0.1454065 207s TI -0.0051996 0.013331 0.057647 -0.042713 -0.145406 0.0044093 207s 207s Linear Coeficients: 207s SI AL FE MG CA TI 207s Attic 63.235 -196.99 312.92 7.28960 57.082 -1272.23 207s Eritrean 41.554 -123.49 201.47 -0.95431 43.616 -597.91 207s 207s Constants: 207s Attic Eritrean 207s -1578.14 -901.13 207s 207s Apparent error rate 0.1111 207s 207s Classification table 207s Predicted 207s Actual Attic Eritrean 207s Attic 12 1 207s Eritrean 2 12 207s 207s Confusion matrix 207s Predicted 207s Actual Attic Eritrean 207s Attic 0.923 0.077 207s Eritrean 0.143 0.857 207s 207s Data: olitos 207s =================================================== 207s > dodata(method="mcdB") 207s 207s Call: dodata(method = "mcdB") 207s =================================================== 207s 207s Data: hemophilia 207s Call: 207s Linda(as.factor(gr) ~ ., data = hemophilia, method = method) 207s 207s Prior Probabilities of Groups: 207s carrier normal 207s 0.6 0.4 207s 207s Group means: 207s AHFactivity AHFantigen 207s carrier -0.31456 -0.014775 207s normal -0.13582 -0.069084 207s 207s Within-groups Covariance Matrix: 207s AHFactivity AHFantigen 207s AHFactivity 0.0125319 0.0086509 207s AHFantigen 0.0086509 0.0182424 207s 207s Linear Coeficients: 207s AHFactivity AHFantigen 207s carrier -36.486 16.4923 207s normal -12.226 2.0107 207s 207s Constants: 207s carrier normal 207s -6.1276 -1.6771 207s 207s Apparent error rate 0.16 207s 207s Classification table 207s Predicted 207s Actual carrier normal 207s carrier 38 7 207s normal 5 25 207s 207s Confusion matrix 207s Predicted 207s Actual carrier normal 207s carrier 0.844 0.156 207s normal 0.167 0.833 207s 207s Data: anorexia 207s Call: 207s Linda(Treat ~ ., data = anorexia, method = method) 207s 207s Prior Probabilities of Groups: 207s CBT Cont FT 207s 0.40278 0.36111 0.23611 207s 207s Group means: 207s Prewt Postwt 207s CBT 83.254 82.381 207s Cont 82.178 80.539 207s FT 84.951 94.193 207s 207s Within-groups Covariance Matrix: 207s Prewt Postwt 207s Prewt 19.1751 8.8546 207s Postwt 8.8546 25.2326 207s 207s Linear Coeficients: 207s Prewt Postwt 207s CBT 3.3822 2.0780 207s Cont 3.3555 2.0144 207s FT 3.2299 2.5996 207s 207s Constants: 207s CBT Cont FT 207s -227.29 -220.01 -261.06 207s 207s Apparent error rate 0.4444 207s 207s Classification table 207s Predicted 207s Actual CBT Cont FT 207s CBT 16 5 8 207s Cont 12 11 3 207s FT 0 4 13 207s 207s Confusion matrix 207s Predicted 207s Actual CBT Cont FT 207s CBT 0.552 0.172 0.276 207s Cont 0.462 0.423 0.115 207s FT 0.000 0.235 0.765 207s 207s Data: Pima 207s Call: 207s Linda(type ~ ., data = Pima.tr, method = method) 207s 207s Prior Probabilities of Groups: 207s No Yes 207s 0.66 0.34 207s 207s Group means: 207s npreg glu bp skin bmi ped age 207s No 2.0767 109.45 67.790 26.158 30.930 0.41455 24.695 207s Yes 5.5938 145.40 74.748 33.754 34.501 0.49898 37.821 207s 207s Within-groups Covariance Matrix: 207s npreg glu bp skin bmi ped age 207s npreg 6.601330 9.54054 7.33480 3.5803 1.66539 -0.019992 10.661763 207s glu 9.540535 573.03642 60.57124 28.3698 30.28444 -0.436611 28.318034 207s bp 7.334803 60.57124 112.03792 27.7566 13.54085 -0.040510 24.692240 207s skin 3.580339 28.36976 27.75661 112.0036 47.22411 0.100399 13.408195 207s bmi 1.665393 30.28444 13.54085 47.2241 38.37753 0.175891 6.640765 207s ped -0.019992 -0.43661 -0.04051 0.1004 0.17589 0.062551 -0.070673 207s age 10.661763 28.31803 24.69224 13.4082 6.64077 -0.070673 40.492363 207s 207s Linear Coeficients: 207s npreg glu bp skin bmi ped age 207s No -1.3073 0.10851 0.48404 -0.30638 0.86002 5.9796 0.55388 207s Yes -1.3136 0.16260 0.44480 -0.25518 0.79826 8.1199 0.86269 207s 207s Constants: 207s No Yes 207s -38.774 -53.654 207s 207s Apparent error rate 0.25 207s 207s Classification table 207s Predicted 207s Actual No Yes 207s No 104 28 207s Yes 22 46 207s 207s Confusion matrix 207s Predicted 207s Actual No Yes 207s No 0.788 0.212 207s Yes 0.324 0.676 207s 207s Data: Forest soils 207s 207s Apparent error rate 0.3448 207s 207s Classification table 207s Predicted 207s Actual 1 2 3 207s 1 4 3 4 207s 2 2 14 7 207s 3 2 2 20 207s 207s Confusion matrix 207s Predicted 207s Actual 1 2 3 207s 1 0.364 0.273 0.364 207s 2 0.087 0.609 0.304 207s 3 0.083 0.083 0.833 207s 207s Data: Raven and Miller diabetes data 207s Call: 207s Linda(group ~ insulin + glucose + sspg, data = diabetes, method = method) 207s 207s Prior Probabilities of Groups: 207s normal chemical overt 207s 0.52414 0.24828 0.22759 207s 207s Group means: 207s insulin glucose sspg 207s normal 152.405 346.55 99.387 207s chemical 288.244 478.80 226.226 207s overt 84.754 1028.28 345.605 207s 207s Within-groups Covariance Matrix: 207s insulin glucose sspg 207s insulin 5061.46 289.69 2071.71 207s glucose 289.69 1983.07 385.31 207s sspg 2071.71 385.31 3000.17 207s 207s Linear Coeficients: 207s insulin glucose sspg 207s normal 0.021952 0.17236 -0.0041671 207s chemical 0.034852 0.23217 0.0215200 207s overt -0.045700 0.50940 0.0813292 207s 207s Constants: 207s normal chemical overt 207s -31.976 -64.433 -275.502 207s 207s Apparent error rate 0.0966 207s 207s Classification table 207s Predicted 207s Actual normal chemical overt 207s normal 73 3 0 207s chemical 4 32 0 207s overt 0 7 26 207s 207s Confusion matrix 207s Predicted 207s Actual normal chemical overt 207s normal 0.961 0.039 0.000 207s chemical 0.111 0.889 0.000 207s overt 0.000 0.212 0.788 207s 207s Data: iris 207s Call: 207s Linda(Species ~ ., data = iris, method = method, l1med = TRUE) 207s 207s Prior Probabilities of Groups: 207s setosa versicolor virginica 207s 0.33333 0.33333 0.33333 207s 207s Group means: 207s Sepal.Length Sepal.Width Petal.Length Petal.Width 207s setosa 4.9834 3.4153 1.4532 0.22474 207s versicolor 5.8947 2.8149 4.2263 1.35024 207s virginica 6.5255 3.0017 5.4485 2.06756 207s 207s Within-groups Covariance Matrix: 207s Sepal.Length Sepal.Width Petal.Length Petal.Width 207s Sepal.Length 0.201176 0.084299 0.102984 0.037019 207s Sepal.Width 0.084299 0.108394 0.050253 0.031757 207s Petal.Length 0.102984 0.050253 0.120215 0.045016 207s Petal.Width 0.037019 0.031757 0.045016 0.032825 207s 207s Linear Coeficients: 207s Sepal.Length Sepal.Width Petal.Length Petal.Width 207s setosa 22.536 27.422168 -3.6855 -40.0445 207s versicolor 17.559 6.374082 24.1965 -18.0178 207s virginica 16.488 0.015576 29.9586 3.2926 207s 207s Constants: 207s setosa versicolor virginica 207s -96.901 -100.790 -139.937 207s 207s Apparent error rate 0.0267 207s 207s Classification table 207s Predicted 207s Actual setosa versicolor virginica 207s setosa 50 0 0 207s versicolor 0 48 2 207s virginica 0 2 48 207s 207s Confusion matrix 207s Predicted 207s Actual setosa versicolor virginica 207s setosa 1 0.00 0.00 207s versicolor 0 0.96 0.04 207s virginica 0 0.04 0.96 207s 207s Data: crabs 208s Call: 208s Linda(sp ~ ., data = crabs, method = method) 208s 208s Prior Probabilities of Groups: 208s B O 208s 0.5 0.5 208s 208s Group means: 208s sexM index FL RW CL CW BD 208s B 0.41060 25.420 13.947 11.922 29.783 34.404 12.470 208s O 0.60279 23.202 16.782 13.086 33.401 37.230 15.131 208s 208s Within-groups Covariance Matrix: 208s sexM index FL RW CL CW BD 208s sexM 0.27470 0.24656 0.12787 -0.34713 0.48937 0.41525 0.20253 208s index 0.24656 204.06823 42.17347 28.25816 89.28109 100.21077 40.74069 208s FL 0.12787 42.17347 9.45366 6.24808 19.97936 22.49310 9.03804 208s RW -0.34713 28.25816 6.24808 5.12921 13.01576 14.90535 5.89729 208s CL 0.48937 89.28109 19.97936 13.01576 43.06030 48.30814 19.44568 208s CW 0.41525 100.21077 22.49310 14.90535 48.30814 54.45265 21.82356 208s BD 0.20253 40.74069 9.03804 5.89729 19.44568 21.82356 8.89498 208s 208s Linear Coeficients: 208s sexM index FL RW CL CW BD 208s B 12.295 -2.3199 7.2512 9.4085 2.2846 -2.6196 -0.42557 208s O 13.138 -3.7530 21.1374 11.5680 5.0125 -13.9120 12.61928 208s 208s Constants: 208s B O 208s -66.688 -134.375 208s 208s Apparent error rate 0 208s 208s Classification table 208s Predicted 208s Actual B O 208s B 100 0 208s O 0 100 208s 208s Confusion matrix 208s Predicted 208s Actual B O 208s B 1 0 208s O 0 1 208s 208s Data: fish 208s 208s Apparent error rate 0.0949 208s 208s Classification table 208s Predicted 208s Actual 1 2 3 4 5 6 7 208s 1 34 0 0 0 0 0 0 208s 2 0 6 0 0 0 0 0 208s 3 0 0 20 0 0 0 0 208s 4 0 0 0 11 0 0 0 208s 5 0 0 0 0 13 0 1 208s 6 0 0 0 0 0 17 0 208s 7 0 13 0 0 1 0 42 208s 208s Confusion matrix 208s Predicted 208s Actual 1 2 3 4 5 6 7 208s 1 1 0.000 0 0 0.000 0 0.000 208s 2 0 1.000 0 0 0.000 0 0.000 208s 3 0 0.000 1 0 0.000 0 0.000 208s 4 0 0.000 0 1 0.000 0 0.000 208s 5 0 0.000 0 0 0.929 0 0.071 208s 6 0 0.000 0 0 0.000 1 0.000 208s 7 0 0.232 0 0 0.018 0 0.750 208s 208s Data: pottery 208s Call: 208s Linda(origin ~ ., data = pottery, method = method) 208s 208s Prior Probabilities of Groups: 208s Attic Eritrean 208s 0.48148 0.51852 208s 208s Group means: 208s SI AL FE MG CA TI 208s Attic 55.362 13.847 10.0065 5.3141 5.5371 0.87124 208s Eritrean 52.522 16.347 9.3165 2.9541 5.7671 0.82224 208s 208s Within-groups Covariance Matrix: 208s SI AL FE MG CA TI 208s SI 9.708953 2.3634831 -0.112005 0.514666 -0.591122 0.0253885 208s AL 2.363483 0.8510105 0.044491 0.485132 0.241384 0.0023349 208s FE -0.112005 0.0444910 0.247768 -0.263894 -0.503218 0.0163218 208s MG 0.514666 0.4851316 -0.263894 1.608899 1.516228 -0.0292787 208s CA -0.591122 0.2413842 -0.503218 1.516228 2.455516 -0.0531548 208s TI 0.025389 0.0023349 0.016322 -0.029279 -0.053155 0.0017412 208s 208s Linear Coeficients: 208s SI AL FE MG CA TI 208s Attic 112.705 -368.69 530.54 7.5837 149.60 -927.45 208s Eritrean 77.198 -244.65 366.95 -3.7987 116.88 -260.83 208s 208s Constants: 208s Attic Eritrean 208s -3252.6 -1961.9 208s 208s Apparent error rate 0.1111 208s 208s Classification table 208s Predicted 208s Actual Attic Eritrean 208s Attic 12 1 208s Eritrean 2 12 208s 208s Confusion matrix 208s Predicted 208s Actual Attic Eritrean 208s Attic 0.923 0.077 208s Eritrean 0.143 0.857 208s 208s Data: olitos 208s 208s Apparent error rate 0.15 208s 208s Classification table 208s Predicted 208s Actual 1 2 3 4 208s 1 44 1 4 1 208s 2 2 23 0 0 208s 3 6 1 26 1 208s 4 1 1 0 9 208s 208s Confusion matrix 208s Predicted 208s Actual 1 2 3 4 208s 1 0.880 0.020 0.080 0.020 208s 2 0.080 0.920 0.000 0.000 208s 3 0.176 0.029 0.765 0.029 208s 4 0.091 0.091 0.000 0.818 208s =================================================== 208s > dodata(method="mcdC") 208s 208s Call: dodata(method = "mcdC") 208s =================================================== 208s 208s Data: hemophilia 208s Call: 208s Linda(as.factor(gr) ~ ., data = hemophilia, method = method) 208s 208s Prior Probabilities of Groups: 208s carrier normal 208s 0.6 0.4 208s 208s Group means: 208s AHFactivity AHFantigen 208s carrier -0.32583 -0.011545 208s normal -0.12783 -0.071377 208s 208s Within-groups Covariance Matrix: 208s AHFactivity AHFantigen 208s AHFactivity 0.0120964 0.0075536 208s AHFantigen 0.0075536 0.0164883 208s 208s Linear Coeficients: 208s AHFactivity AHFantigen 208s carrier -37.117 16.30377 208s normal -11.015 0.71742 208s 208s Constants: 208s carrier normal 208s -6.4636 -1.5947 208s 208s Apparent error rate 0.16 208s 208s Classification table 208s Predicted 208s Actual carrier normal 208s carrier 38 7 208s normal 5 25 208s 208s Confusion matrix 208s Predicted 208s Actual carrier normal 208s carrier 0.844 0.156 208s normal 0.167 0.833 208s 208s Data: anorexia 208s Call: 208s Linda(Treat ~ ., data = anorexia, method = method) 208s 208s Prior Probabilities of Groups: 208s CBT Cont FT 208s 0.40278 0.36111 0.23611 208s 208s Group means: 208s Prewt Postwt 208s CBT 82.477 82.073 208s Cont 82.039 80.835 208s FT 85.242 94.750 208s 208s Within-groups Covariance Matrix: 208s Prewt Postwt 208s Prewt 19.6589 8.3891 208s Postwt 8.3891 22.8805 208s 208s Linear Coeficients: 208s Prewt Postwt 208s CBT 3.1590 2.4288 208s Cont 3.1599 2.3743 208s FT 3.0454 3.0245 208s 208s Constants: 208s CBT Cont FT 208s -230.85 -226.60 -274.53 208s 208s Apparent error rate 0.4583 208s 208s Classification table 208s Predicted 208s Actual CBT Cont FT 208s CBT 16 5 8 208s Cont 14 10 2 208s FT 0 4 13 208s 208s Confusion matrix 208s Predicted 208s Actual CBT Cont FT 208s CBT 0.552 0.172 0.276 208s Cont 0.538 0.385 0.077 208s FT 0.000 0.235 0.765 208s 208s Data: Pima 208s Call: 208s Linda(type ~ ., data = Pima.tr, method = method) 208s 208s Prior Probabilities of Groups: 208s No Yes 208s 0.66 0.34 208s 208s Group means: 208s npreg glu bp skin bmi ped age 208s No 2.3056 110.63 67.991 26.444 31.010 0.41653 25.806 208s Yes 5.0444 142.58 74.267 33.067 34.309 0.49422 35.156 208s 208s Within-groups Covariance Matrix: 208s npreg glu bp skin bmi ped age 208s npreg 6.164422 8.43753 6.879286 3.252980 1.54269 -0.020158 9.543745 208s glu 8.437528 542.79578 57.156929 26.218837 28.63494 -0.421819 23.809124 208s bp 6.879286 57.15693 106.687356 26.315526 12.86691 -0.039577 22.992973 208s skin 3.252980 26.21884 26.315526 106.552759 44.95420 0.094311 12.005740 208s bmi 1.542689 28.63494 12.866911 44.954202 36.56262 0.167258 6.112925 208s ped -0.020158 -0.42182 -0.039577 0.094311 0.16726 0.059609 -0.072712 208s age 9.543745 23.80912 22.992973 12.005740 6.11292 -0.072712 35.594886 208s 208s Linear Coeficients: 208s npreg glu bp skin bmi ped age 208s No -1.4165 0.11776 0.49336 -0.31564 0.88761 6.5013 0.67462 208s Yes -1.3784 0.17062 0.46662 -0.26771 0.83745 8.5204 0.90557 208s 208s Constants: 208s No Yes 208s -41.716 -55.056 208s 208s Apparent error rate 0.235 208s 208s Classification table 208s Predicted 208s Actual No Yes 208s No 107 25 208s Yes 22 46 208s 208s Confusion matrix 208s Predicted 208s Actual No Yes 208s No 0.811 0.189 208s Yes 0.324 0.676 208s 208s Data: Forest soils 208s 208s Apparent error rate 0.3276 208s 208s Classification table 208s Predicted 208s Actual 1 2 3 208s 1 5 2 4 208s 2 2 13 8 208s 3 1 2 21 208s 208s Confusion matrix 208s Predicted 208s Actual 1 2 3 208s 1 0.455 0.182 0.364 208s 2 0.087 0.565 0.348 208s 3 0.042 0.083 0.875 208s 208s Data: Raven and Miller diabetes data 208s Call: 208s Linda(group ~ insulin + glucose + sspg, data = diabetes, method = method) 208s 208s Prior Probabilities of Groups: 208s normal chemical overt 208s 0.52414 0.24828 0.22759 208s 208s Group means: 208s insulin glucose sspg 208s normal 167.31 348.69 106.44 208s chemical 247.18 478.18 213.36 208s overt 101.83 932.92 322.42 208s 208s Within-groups Covariance Matrix: 208s insulin glucose sspg 208s insulin 4070.84 118.89 1701.54 208s glucose 118.89 2195.95 426.95 208s sspg 1701.54 426.95 2664.49 208s 208s Linear Coeficients: 208s insulin glucose sspg 208s normal 0.041471 0.15888 -0.011992 208s chemical 0.048103 0.21216 0.015359 208s overt -0.013579 0.41323 0.063462 208s 208s Constants: 208s normal chemical overt 208s -31.177 -59.703 -203.775 208s 208s Apparent error rate 0.0828 208s 208s Classification table 208s Predicted 208s Actual normal chemical overt 208s normal 72 4 0 208s chemical 2 34 0 208s overt 0 6 27 208s 208s Confusion matrix 208s Predicted 208s Actual normal chemical overt 208s normal 0.947 0.053 0.000 208s chemical 0.056 0.944 0.000 208s overt 0.000 0.182 0.818 208s 208s Data: iris 208s Call: 208s Linda(Species ~ ., data = iris, method = method, l1med = TRUE) 208s 208s Prior Probabilities of Groups: 208s setosa versicolor virginica 208s 0.33333 0.33333 0.33333 208s 208s Group means: 208s Sepal.Length Sepal.Width Petal.Length Petal.Width 208s setosa 5.0163 3.4510 1.4653 0.2449 208s versicolor 5.9435 2.7891 4.2543 1.3239 208s virginica 6.3867 3.0033 5.3767 2.0700 208s 208s Within-groups Covariance Matrix: 208s Sepal.Length Sepal.Width Petal.Length Petal.Width 208s Sepal.Length 0.186186 0.082478 0.094998 0.035445 208s Sepal.Width 0.082478 0.100137 0.049723 0.030678 208s Petal.Length 0.094998 0.049723 0.113105 0.043078 208s Petal.Width 0.035445 0.030678 0.043078 0.030885 208s 208s Linear Coeficients: 208s Sepal.Length Sepal.Width Petal.Length Petal.Width 208s setosa 23.678 30.2896 -3.1124 -44.9900 208s versicolor 20.342 4.6372 27.3265 -23.2006 208s virginica 18.377 -2.0004 31.4235 4.0906 208s 208s Constants: 208s setosa versicolor virginica 208s -104.96 -110.79 -145.49 208s 208s Apparent error rate 0.0333 208s 208s Classification table 208s Predicted 208s Actual setosa versicolor virginica 208s setosa 50 0 0 208s versicolor 0 48 2 208s virginica 0 3 47 208s 208s Confusion matrix 208s Predicted 208s Actual setosa versicolor virginica 208s setosa 1 0.00 0.00 208s versicolor 0 0.96 0.04 208s virginica 0 0.06 0.94 208s 208s Data: crabs 208s Call: 208s Linda(sp ~ ., data = crabs, method = method) 208s 208s Prior Probabilities of Groups: 208s B O 208s 0.5 0.5 208s 208s Group means: 208s sexM index FL RW CL CW BD 208s B 0.50000 23.956 13.790 11.649 29.390 33.934 12.274 208s O 0.51087 24.478 16.903 13.330 33.707 37.595 15.276 208s 208s Within-groups Covariance Matrix: 208s sexM index FL RW CL CW BD 208s sexM 0.25272 0.39179 0.14054 -0.30017 0.51191 0.45114 0.21708 208s index 0.39179 192.47099 39.97343 26.56698 84.63152 94.99987 38.67917 208s FL 0.14054 39.97343 8.97950 5.91408 18.98672 21.38046 8.60313 208s RW -0.30017 26.56698 5.91408 4.81389 12.31798 14.10613 5.58933 208s CL 0.51191 84.63152 18.98672 12.31798 40.94109 45.94330 18.52367 208s CW 0.45114 94.99987 21.38046 14.10613 45.94330 51.80106 20.79704 208s BD 0.21708 38.67917 8.60313 5.58933 18.52367 20.79704 8.49355 208s 208s Linear Coeficients: 208s sexM index FL RW CL CW BD 208s B 13.993 -2.5515 9.152 9.9187 2.2321 -2.9774 -0.66797 208s O 14.362 -4.0280 23.369 12.1556 5.3672 -14.9236 12.94057 208s 208s Constants: 208s B O 208s -72.687 -142.365 208s 208s Apparent error rate 0 208s 208s Classification table 208s Predicted 208s Actual B O 208s B 100 0 208s O 0 100 208s 208s Confusion matrix 208s Predicted 208s Actual B O 208s B 1 0 208s O 0 1 208s 208s Data: fish 208s 208s Apparent error rate 0.0316 208s 208s Classification table 208s Predicted 208s Actual 1 2 3 4 5 6 7 208s 1 34 0 0 0 0 0 0 208s 2 0 5 0 0 1 0 0 208s 3 0 0 20 0 0 0 0 208s 4 0 0 0 11 0 0 0 208s 5 0 0 0 0 13 0 1 208s 6 0 0 0 0 0 17 0 208s 7 0 0 0 0 3 0 53 208s 208s Confusion matrix 208s Predicted 208s Actual 1 2 3 4 5 6 7 208s 1 1 0.000 0 0 0.000 0 0.000 208s 2 0 0.833 0 0 0.167 0 0.000 208s 3 0 0.000 1 0 0.000 0 0.000 208s 4 0 0.000 0 1 0.000 0 0.000 208s 5 0 0.000 0 0 0.929 0 0.071 208s 6 0 0.000 0 0 0.000 1 0.000 208s 7 0 0.000 0 0 0.054 0 0.946 208s 208s Data: pottery 208s Call: 208s Linda(origin ~ ., data = pottery, method = method) 208s 208s Prior Probabilities of Groups: 208s Attic Eritrean 208s 0.48148 0.51852 208s 208s Group means: 208s SI AL FE MG CA TI 208s Attic 55.450 13.738 10.0000 5.0750 5.0750 0.87375 208s Eritrean 52.444 16.444 9.3222 3.1667 6.1778 0.82000 208s 208s Within-groups Covariance Matrix: 208s SI AL FE MG CA TI 208s SI 6.565481 1.6098148 -0.075259 0.369556 -0.359407 0.0169667 208s AL 1.609815 0.5640648 0.029407 0.302056 0.112426 0.0018583 208s FE -0.075259 0.0294074 0.167704 -0.180222 -0.343704 0.0110667 208s MG 0.369556 0.3020556 -0.180222 1.031667 0.915222 -0.0192167 208s CA -0.359407 0.1124259 -0.343704 0.915222 1.447370 -0.0348167 208s TI 0.016967 0.0018583 0.011067 -0.019217 -0.034817 0.0011725 208s 208s Linear Coeficients: 208s SI AL FE MG CA TI 208s Attic 190.17 -622.48 922.21 1.5045 293.30 -990.323 208s Eritrean 135.34 -431.40 666.59 -14.3288 237.68 -44.025 208s 208s Constants: 208s Attic Eritrean 208s -5924.2 -3802.9 208s 208s Apparent error rate 0.1111 208s 208s Classification table 208s Predicted 208s Actual Attic Eritrean 208s Attic 12 1 208s Eritrean 2 12 208s 208s Confusion matrix 208s Predicted 208s Actual Attic Eritrean 208s Attic 0.923 0.077 208s Eritrean 0.143 0.857 208s 208s Data: olitos 208s 208s Apparent error rate 0.1667 208s 208s Classification table 208s Predicted 208s Actual 1 2 3 4 208s 1 44 1 2 3 208s 2 2 22 0 1 208s 3 5 2 25 2 208s 4 1 1 0 9 208s 208s Confusion matrix 208s Predicted 208s Actual 1 2 3 4 208s 1 0.880 0.020 0.040 0.060 208s 2 0.080 0.880 0.000 0.040 208s 3 0.147 0.059 0.735 0.059 208s 4 0.091 0.091 0.000 0.818 208s =================================================== 208s > dodata(method="mrcd") 208s 208s Call: dodata(method = "mrcd") 208s =================================================== 208s 208s Data: hemophilia 208s Call: 208s Linda(as.factor(gr) ~ ., data = hemophilia, method = method) 208s 208s Prior Probabilities of Groups: 208s carrier normal 208s 0.6 0.4 208s 208s Group means: 208s AHFactivity AHFantigen 208s carrier -0.34048 -0.055943 208s normal -0.13566 -0.081191 208s 208s Within-groups Covariance Matrix: 208s AHFactivity AHFantigen 208s AHFactivity 0.0133676 0.0088055 208s AHFantigen 0.0088055 0.0221225 208s 208s Linear Coeficients: 208s AHFactivity AHFantigen 208s carrier -32.264 10.31334 208s normal -10.478 0.50044 208s 208s Constants: 208s carrier normal 208s -5.7149 -1.6067 208s 208s Apparent error rate 0.16 208s 208s Classification table 208s Predicted 208s Actual carrier normal 208s carrier 38 7 208s normal 5 25 208s 208s Confusion matrix 208s Predicted 208s Actual carrier normal 208s carrier 0.844 0.156 208s normal 0.167 0.833 208s 208s Data: anorexia 209s Call: 209s Linda(Treat ~ ., data = anorexia, method = method) 209s 209s Prior Probabilities of Groups: 209s CBT Cont FT 209s 0.40278 0.36111 0.23611 209s 209s Group means: 209s Prewt Postwt 209s CBT 83.114 84.009 209s Cont 80.327 80.125 209s FT 85.161 94.371 209s 209s Within-groups Covariance Matrix: 209s Prewt Postwt 209s Prewt 22.498 11.860 209s Postwt 11.860 20.426 209s 209s Linear Coeficients: 209s Prewt Postwt 209s CBT 2.1994 2.8357 209s Cont 2.1653 2.6654 209s FT 1.9451 3.4907 209s 209s Constants: 209s CBT Cont FT 209s -211.42 -194.77 -248.97 209s 209s Apparent error rate 0.3889 209s 209s Classification table 209s Predicted 209s Actual CBT Cont FT 209s CBT 15 6 8 209s Cont 6 16 4 209s FT 0 4 13 209s 209s Confusion matrix 209s Predicted 209s Actual CBT Cont FT 209s CBT 0.517 0.207 0.276 209s Cont 0.231 0.615 0.154 209s FT 0.000 0.235 0.765 209s 209s Data: Pima 209s Call: 209s Linda(type ~ ., data = Pima.tr, method = method) 209s 209s Prior Probabilities of Groups: 209s No Yes 209s 0.66 0.34 209s 209s Group means: 209s npreg glu bp skin bmi ped age 209s No 1.9925 108.32 66.240 24.856 30.310 0.37382 24.747 209s Yes 5.8855 145.88 75.715 32.541 33.915 0.39281 38.857 209s 209s Within-groups Covariance Matrix: 209s npreg glu bp skin bmi ped age 209s npreg 4.090330 7.9547 3.818380 3.35899 2.470242 0.032557 9.5929 209s glu 7.954730 770.4187 76.377665 53.32216 54.100400 -1.139087 28.5677 209s bp 3.818380 76.3777 108.201622 42.61184 18.574983 -0.089151 20.3558 209s skin 3.358992 53.3222 42.611844 146.81170 65.210794 -0.277335 15.0162 209s bmi 2.470242 54.1004 18.574983 65.21079 52.871847 0.062145 9.0741 209s ped 0.032557 -1.1391 -0.089151 -0.27733 0.062145 0.063490 0.1762 209s age 9.592948 28.5677 20.355803 15.01616 9.074109 0.176201 53.5163 209s 209s Linear Coeficients: 209s npreg glu bp skin bmi ped age 209s No -1.30832 0.065773 0.54772 -0.32738 0.70207 5.2556 0.40900 209s Yes -0.76566 0.106435 0.55777 -0.28044 0.61709 5.9199 0.54892 209s 209s Constants: 209s No Yes 209s -33.429 -45.434 209s 209s Apparent error rate 0.28 209s 209s Classification table 209s Predicted 209s Actual No Yes 209s No 105 27 209s Yes 29 39 209s 209s Confusion matrix 209s Predicted 209s Actual No Yes 209s No 0.795 0.205 209s Yes 0.426 0.574 209s 209s Data: Forest soils 209s 209s Apparent error rate 0.3448 209s 209s Classification table 209s Predicted 209s Actual 1 2 3 209s 1 7 2 2 209s 2 4 14 5 209s 3 3 4 17 209s 209s Confusion matrix 209s Predicted 209s Actual 1 2 3 209s 1 0.636 0.182 0.182 209s 2 0.174 0.609 0.217 209s 3 0.125 0.167 0.708 209s 209s Data: Raven and Miller diabetes data 209s Call: 209s Linda(group ~ insulin + glucose + sspg, data = diabetes, method = method) 209s 209s Prior Probabilities of Groups: 209s normal chemical overt 209s 0.52414 0.24828 0.22759 209s 209s Group means: 209s insulin glucose sspg 209s normal 154.014 346.07 91.606 209s chemical 248.841 451.10 221.936 209s overt 89.766 1064.16 335.100 209s 209s Within-groups Covariance Matrix: 209s insulin glucose sspg 209s insulin 4948.1 1007.61 1471.12 209s glucose 1007.6 2597.38 358.57 209s sspg 1471.1 358.57 3180.04 209s 209s Linear Coeficients: 209s insulin glucose sspg 209s normal 0.00027839 0.13121 0.013882 209s chemical 0.00148074 0.16615 0.050371 209s overt -0.10102404 0.43466 0.103100 209s 209s Constants: 209s normal chemical overt 209s -24.008 -44.642 -245.497 209s 209s Apparent error rate 0.0966 209s 209s Classification table 209s Predicted 209s Actual normal chemical overt 209s normal 71 5 0 209s chemical 2 34 0 209s overt 0 7 26 209s 209s Confusion matrix 209s Predicted 209s Actual normal chemical overt 209s normal 0.934 0.066 0.000 209s chemical 0.056 0.944 0.000 209s overt 0.000 0.212 0.788 209s 209s Data: iris 209s Call: 209s Linda(Species ~ ., data = iris, method = method, l1med = TRUE) 209s 209s Prior Probabilities of Groups: 209s setosa versicolor virginica 209s 0.33333 0.33333 0.33333 209s 209s Group means: 209s Sepal.Length Sepal.Width Petal.Length Petal.Width 209s setosa 4.9755 3.3826 1.4608 0.22053 209s versicolor 5.8868 2.7823 4.2339 1.34603 209s virginica 6.5176 2.9691 5.4560 2.06335 209s 209s Within-groups Covariance Matrix: 209s Sepal.Length Sepal.Width Petal.Length Petal.Width 209s Sepal.Length 0.238417 0.136325 0.086377 0.036955 209s Sepal.Width 0.136325 0.148452 0.067500 0.034804 209s Petal.Length 0.086377 0.067500 0.100934 0.035968 209s Petal.Width 0.036955 0.034804 0.035968 0.023856 209s 209s Linear Coeficients: 209s Sepal.Length Sepal.Width Petal.Length Petal.Width 209s setosa 17.106 15.693 7.8806 -52.031 209s versicolor 21.744 -15.813 38.0139 -11.505 209s virginica 23.032 -26.567 43.6391 23.777 209s 209s Constants: 209s setosa versicolor virginica 209s -70.214 -115.832 -180.294 209s 209s Apparent error rate 0.02 209s 209s Classification table 209s Predicted 209s Actual setosa versicolor virginica 209s setosa 50 0 0 209s versicolor 0 49 1 209s virginica 0 2 48 209s 209s Confusion matrix 209s Predicted 209s Actual setosa versicolor virginica 209s setosa 1 0.00 0.00 209s versicolor 0 0.98 0.02 209s virginica 0 0.04 0.96 209s 209s Data: crabs 209s Call: 209s Linda(sp ~ ., data = crabs, method = method) 209s 209s Prior Probabilities of Groups: 209s B O 209s 0.5 0.5 209s 209s Group means: 209s sexM index FL RW CL CW BD 209s B 0 25.5 13.270 12.138 28.102 32.624 11.816 209s O 1 25.5 16.626 12.262 33.688 37.188 15.324 209s 209s Within-groups Covariance Matrix: 209s sexM index FL RW CL CW BD 209s sexM 1.5255e-07 0.000 0.0000 0.0000 0.000 0.000 0.000 209s index 0.0000e+00 337.501 62.8107 46.5073 137.713 154.451 63.514 209s FL 0.0000e+00 62.811 15.3164 9.8612 29.911 33.479 13.805 209s RW 0.0000e+00 46.507 9.8612 8.6949 21.878 24.604 10.092 209s CL 0.0000e+00 137.713 29.9112 21.8779 73.888 73.891 30.486 209s CW 0.0000e+00 154.451 33.4788 24.6038 73.891 92.801 34.122 209s BD 0.0000e+00 63.514 13.8053 10.0923 30.486 34.122 15.854 209s 209s Linear Coeficients: 209s sexM index FL RW CL CW BD 209s B 0 -0.64890 0.95529 2.7299 0.20747 0.28549 -0.23815 209s O 6555120 -0.83294 1.67920 1.8896 0.32330 0.23479 0.51136 209s 209s Constants: 209s B O 209s -2.1491e+01 -3.2776e+06 209s 209s Apparent error rate 0.5 209s 209s Classification table 209s Predicted 209s Actual B O 209s B 50 50 209s O 50 50 209s 209s Confusion matrix 209s Predicted 209s Actual B O 209s B 0.5 0.5 209s O 0.5 0.5 209s 209s Data: fish 209s 209s Apparent error rate 0.2532 209s 209s Classification table 209s Predicted 209s Actual 1 2 3 4 5 6 7 209s 1 33 0 0 1 0 0 0 209s 2 0 3 0 0 0 0 3 209s 3 0 2 5 0 0 0 13 209s 4 0 0 0 11 0 0 0 209s 5 0 0 0 0 14 0 0 209s 6 0 0 0 0 0 17 0 209s 7 0 19 0 0 2 0 35 209s 209s Confusion matrix 209s Predicted 209s Actual 1 2 3 4 5 6 7 209s 1 0.971 0.000 0.00 0.029 0.000 0 0.000 209s 2 0.000 0.500 0.00 0.000 0.000 0 0.500 209s 3 0.000 0.100 0.25 0.000 0.000 0 0.650 209s 4 0.000 0.000 0.00 1.000 0.000 0 0.000 209s 5 0.000 0.000 0.00 0.000 1.000 0 0.000 209s 6 0.000 0.000 0.00 0.000 0.000 1 0.000 209s 7 0.000 0.339 0.00 0.000 0.036 0 0.625 209s 209s Data: pottery 209s Call: 209s Linda(origin ~ ., data = pottery, method = method) 209s 209s Prior Probabilities of Groups: 209s Attic Eritrean 209s 0.48148 0.51852 209s 209s Group means: 209s SI AL FE MG CA TI 209s Attic 55.872 13.986 10.113 5.0235 4.7316 0.88531 209s Eritrean 52.487 16.286 9.499 2.4520 5.3745 0.83959 209s 209s Within-groups Covariance Matrix: 209s SI AL FE MG CA TI 209s SI 12.795913 3.2987125 -0.35496855 0.9399999 -0.0143514 0.01132392 209s AL 3.298713 1.0829436 -0.03394751 0.2838724 0.0501000 0.00117721 209s FE -0.354969 -0.0339475 0.08078156 0.0341568 -0.0457411 0.00043177 209s MG 0.940000 0.2838724 0.03415675 0.4350013 0.1417876 0.00396576 209s CA -0.014351 0.0501000 -0.04574114 0.1417876 0.4196628 -0.00104893 209s TI 0.011324 0.0011772 0.00043177 0.0039658 -0.0010489 0.00026205 209s 209s Linear Coeficients: 209s SI AL FE MG CA TI 209s Attic 36.451 -63.784 352.90 -124.07 110.08 3826.6 209s Eritrean 29.763 -41.039 325.12 -128.32 107.36 3938.1 209s 209s Constants: 209s Attic Eritrean 209s -4000.1 -3776.1 209s 209s Apparent error rate 0.1111 209s 209s Classification table 209s Predicted 209s Actual Attic Eritrean 209s Attic 12 1 209s Eritrean 2 12 209s 209s Confusion matrix 209s Predicted 209s Actual Attic Eritrean 209s Attic 0.923 0.077 209s Eritrean 0.143 0.857 209s 209s Data: olitos 209s 209s Apparent error rate 0.125 209s 209s Classification table 209s Predicted 209s Actual 1 2 3 4 209s 1 44 2 3 1 209s 2 1 23 1 0 209s 3 4 1 27 2 209s 4 0 0 0 11 209s 209s Confusion matrix 209s Predicted 209s Actual 1 2 3 4 209s 1 0.880 0.040 0.060 0.020 209s 2 0.040 0.920 0.040 0.000 209s 3 0.118 0.029 0.794 0.059 209s 4 0.000 0.000 0.000 1.000 209s =================================================== 209s > dodata(method="ogk") 209s 209s Call: dodata(method = "ogk") 209s =================================================== 209s 209s Data: hemophilia 209s Call: 209s Linda(as.factor(gr) ~ ., data = hemophilia, method = method) 209s 209s Prior Probabilities of Groups: 209s carrier normal 209s 0.6 0.4 209s 209s Group means: 209s AHFactivity AHFantigen 209s carrier -0.29043 -0.00052902 209s normal -0.12463 -0.06715037 209s 209s Within-groups Covariance Matrix: 209s AHFactivity AHFantigen 209s AHFactivity 0.015688 0.010544 209s AHFantigen 0.010544 0.016633 209s 209s Linear Coeficients: 209s AHFactivity AHFantigen 209s carrier -32.2203 20.3935 209s normal -9.1149 1.7409 209s 209s Constants: 209s carrier normal 209s -5.1843 -1.4259 209s 209s Apparent error rate 0.1467 209s 209s Classification table 209s Predicted 209s Actual carrier normal 209s carrier 38 7 209s normal 4 26 209s 209s Confusion matrix 209s Predicted 209s Actual carrier normal 209s carrier 0.844 0.156 209s normal 0.133 0.867 209s 209s Data: anorexia 209s Call: 209s Linda(Treat ~ ., data = anorexia, method = method) 209s 209s Prior Probabilities of Groups: 209s CBT Cont FT 209s 0.40278 0.36111 0.23611 209s 209s Group means: 209s Prewt Postwt 209s CBT 82.634 82.060 209s Cont 81.605 80.459 209s FT 85.157 93.822 209s 209s Within-groups Covariance Matrix: 209s Prewt Postwt 209s Prewt 15.8294 4.4663 209s Postwt 4.4663 19.6356 209s 209s Linear Coeficients: 209s Prewt Postwt 209s CBT 4.3183 3.1970 209s Cont 4.2734 3.1256 209s FT 4.3080 3.7983 209s 209s Constants: 209s CBT Cont FT 209s -310.50 -301.12 -363.05 209s 209s Apparent error rate 0.4583 209s 209s Classification table 209s Predicted 209s Actual CBT Cont FT 209s CBT 15 5 9 209s Cont 14 11 1 209s FT 0 4 13 209s 209s Confusion matrix 209s Predicted 209s Actual CBT Cont FT 209s CBT 0.517 0.172 0.310 209s Cont 0.538 0.423 0.038 209s FT 0.000 0.235 0.765 209s 209s Data: Pima 209s Call: 209s Linda(type ~ ., data = Pima.tr, method = method) 209s 209s Prior Probabilities of Groups: 209s No Yes 209s 0.66 0.34 209s 209s Group means: 209s npreg glu bp skin bmi ped age 209s No 2.4175 109.93 67.332 26.324 30.344 0.38740 26.267 209s Yes 5.1853 142.29 75.194 33.151 34.878 0.47977 37.626 209s 209s Within-groups Covariance Matrix: 209s npreg glu bp skin bmi ped age 209s npreg 7.218576 7.52457 6.96595 4.86613 0.45567 -0.054245 14.42648 209s glu 7.524571 517.38370 58.53812 31.57321 22.68396 -0.200222 22.88780 209s bp 6.965950 58.53812 101.50317 27.86784 10.89215 -0.152784 25.41819 209s skin 4.866127 31.57321 27.86784 95.16949 37.45066 -0.117375 14.60676 209s bmi 0.455675 22.68396 10.89215 37.45066 30.89491 0.043400 4.05584 209s ped -0.054245 -0.20022 -0.15278 -0.11737 0.04340 0.051268 -0.18131 209s age 14.426479 22.88780 25.41819 14.60676 4.05584 -0.181311 57.89570 209s 209s Linear Coeficients: 209s npreg glu bp skin bmi ped age 209s No -0.99043 0.12339 0.54101 -0.35335 1.0721 8.4945 0.45482 209s Yes -1.01369 0.17577 0.53898 -0.35554 1.1563 11.0474 0.63966 209s 209s Constants: 209s No Yes 209s -43.449 -60.176 209s 209s Apparent error rate 0.23 209s 209s Classification table 209s Predicted 209s Actual No Yes 209s No 108 24 209s Yes 22 46 209s 209s Confusion matrix 209s Predicted 209s Actual No Yes 209s No 0.818 0.182 209s Yes 0.324 0.676 209s 209s Data: Forest soils 209s 209s Apparent error rate 0.3621 209s 209s Classification table 209s Predicted 209s Actual 1 2 3 209s 1 7 3 1 209s 2 4 13 6 209s 3 3 4 17 209s 209s Confusion matrix 209s Predicted 209s Actual 1 2 3 209s 1 0.636 0.273 0.091 209s 2 0.174 0.565 0.261 209s 3 0.125 0.167 0.708 209s 209s Data: Raven and Miller diabetes data 209s Call: 209s Linda(group ~ insulin + glucose + sspg, data = diabetes, method = method) 209s 209s Prior Probabilities of Groups: 209s normal chemical overt 209s 0.52414 0.24828 0.22759 209s 209s Group means: 209s insulin glucose sspg 209s normal 159.540 344.06 99.486 209s chemical 252.992 478.16 219.442 209s overt 79.635 1094.96 338.517 209s 209s Within-groups Covariance Matrix: 209s insulin glucose sspg 209s insulin 3844.877 67.238 1456.55 209s glucose 67.238 2228.396 324.21 209s sspg 1456.548 324.205 2181.73 209s 209s Linear Coeficients: 209s insulin glucose sspg 209s normal 0.040407 0.15379 -0.0042303 209s chemical 0.047858 0.20764 0.0377766 209s overt -0.026158 0.47736 0.1016873 209s 209s Constants: 209s normal chemical overt 209s -30.115 -61.233 -278.996 209s 209s Apparent error rate 0.0966 209s 209s Classification table 209s Predicted 209s Actual normal chemical overt 209s normal 71 5 0 209s chemical 2 34 0 209s overt 0 7 26 209s 209s Confusion matrix 209s Predicted 209s Actual normal chemical overt 209s normal 0.934 0.066 0.000 209s chemical 0.056 0.944 0.000 209s overt 0.000 0.212 0.788 209s 209s Data: iris 209s Call: 209s Linda(Species ~ ., data = iris, method = method, l1med = TRUE) 209s 209s Prior Probabilities of Groups: 209s setosa versicolor virginica 209s 0.33333 0.33333 0.33333 209s 209s Group means: 209s Sepal.Length Sepal.Width Petal.Length Petal.Width 209s setosa 4.9654 3.3913 1.4507 0.21639 209s versicolor 5.8767 2.7909 4.2238 1.34189 209s virginica 6.5075 2.9777 5.4459 2.05921 209s 209s Within-groups Covariance Matrix: 209s Sepal.Length Sepal.Width Petal.Length Petal.Width 209s Sepal.Length 0.180280 0.068876 0.101512 0.036096 209s Sepal.Width 0.068876 0.079556 0.047722 0.029409 209s Petal.Length 0.101512 0.047722 0.111492 0.038658 209s Petal.Width 0.036096 0.029409 0.038658 0.029965 209s 209s Linear Coeficients: 209s Sepal.Length Sepal.Width Petal.Length Petal.Width 209s setosa 28.582 46.5236 -13.859 -54.9877 209s versicolor 19.837 11.9601 20.865 -17.7704 209s virginica 16.999 1.9046 29.808 7.9189 209s 209s Constants: 209s setosa versicolor virginica 209s -134.94 -108.22 -148.56 209s 209s Apparent error rate 0.0133 209s 209s Classification table 209s Predicted 209s Actual setosa versicolor virginica 209s setosa 50 0 0 209s versicolor 0 49 1 209s virginica 0 1 49 209s 209s Confusion matrix 209s Predicted 209s Actual setosa versicolor virginica 209s setosa 1 0.00 0.00 209s versicolor 0 0.98 0.02 209s virginica 0 0.02 0.98 209s 209s Data: crabs 209s Call: 209s Linda(sp ~ ., data = crabs, method = method) 209s 209s Prior Probabilities of Groups: 209s B O 209s 0.5 0.5 209s 209s Group means: 209s sexM index FL RW CL CW BD 209s B 0.48948 24.060 13.801 11.738 29.491 34.062 12.329 209s O 0.56236 24.043 16.825 13.158 33.574 37.418 15.223 209s 209s Within-groups Covariance Matrix: 209s sexM index FL RW CL CW BD 209s sexM 0.24961 0.50421 0.16645 -0.28574 0.54159 0.48449 0.22563 209s index 0.50421 186.86616 38.46284 25.26749 82.29121 92.11253 37.67723 209s FL 0.16645 38.46284 8.58830 5.56769 18.33015 20.58235 8.32030 209s RW -0.28574 25.26749 5.56769 4.52038 11.70881 13.37643 5.32779 209s CL 0.54159 82.29121 18.33015 11.70881 39.78186 44.52112 18.01179 209s CW 0.48449 92.11253 20.58235 13.37643 44.52112 50.06150 20.16852 209s BD 0.22563 37.67723 8.32030 5.32779 18.01179 20.16852 8.25884 209s 209s Linear Coeficients: 209s sexM index FL RW CL CW BD 209s B 16.497 -2.5896 8.3966 11.518 1.7536 -2.5325 -0.67361 209s O 17.010 -4.0452 23.5400 13.702 4.7871 -14.8264 13.04556 209s 209s Constants: 209s B O 209s -77.695 -147.287 209s 209s Apparent error rate 0 209s 209s Classification table 209s Predicted 209s Actual B O 209s B 100 0 209s O 0 100 209s 209s Confusion matrix 209s Predicted 209s Actual B O 209s B 1 0 209s O 0 1 209s 209s Data: fish 209s 209s Apparent error rate 0.0063 209s 209s Classification table 209s Predicted 209s Actual 1 2 3 4 5 6 7 209s 1 34 0 0 0 0 0 0 209s 2 0 6 0 0 0 0 0 209s 3 0 0 20 0 0 0 0 209s 4 0 0 0 11 0 0 0 209s 5 0 0 0 0 14 0 0 209s 6 0 0 0 0 0 17 0 209s 7 0 0 0 0 1 0 55 209s 209s Confusion matrix 209s Predicted 209s Actual 1 2 3 4 5 6 7 209s 1 1 0 0 0 0.000 0 0.000 209s 2 0 1 0 0 0.000 0 0.000 209s 3 0 0 1 0 0.000 0 0.000 209s 4 0 0 0 1 0.000 0 0.000 209s 5 0 0 0 0 1.000 0 0.000 209s 6 0 0 0 0 0.000 1 0.000 209s 7 0 0 0 0 0.018 0 0.982 209s 209s Data: pottery 209s Call: 209s Linda(origin ~ ., data = pottery, method = method) 209s 209s Prior Probabilities of Groups: 209s Attic Eritrean 209s 0.48148 0.51852 209s 209s Group means: 209s SI AL FE MG CA TI 209s Attic 55.381 14.088 10.1316 4.9588 4.7684 0.88444 209s Eritrean 53.559 16.251 9.1145 2.6213 5.8980 0.82501 209s 209s Within-groups Covariance Matrix: 209s SI AL FE MG CA TI 209s SI 7.878378 1.9064112 -0.545403 0.4167407 -0.11589 0.01850748 209s AL 1.906411 0.6678763 -0.037744 0.1120891 -0.10733 0.00805556 209s FE -0.545403 -0.0377438 0.213914 -0.0192356 -0.23121 0.00582800 209s MG 0.416741 0.1120891 -0.019236 0.2336721 0.17284 -0.00183128 209s CA -0.115888 -0.1073297 -0.231213 0.1728385 0.71388 -0.01895968 209s TI 0.018507 0.0080556 0.005828 -0.0018313 -0.01896 0.00081815 209s 209s Linear Coeficients: 209s SI AL FE MG CA TI 209s Attic 57.784 -107.297 319.31 -152.94 241.66 3813.6 209s Eritrean 52.523 -86.545 306.58 -165.71 242.36 3734.1 209s 209s Constants: 209s Attic Eritrean 209s -4346 -4139 209s 209s Apparent error rate 0.1111 209s 209s Classification table 209s Predicted 209s Actual Attic Eritrean 209s Attic 12 1 209s Eritrean 2 12 209s 209s Confusion matrix 209s Predicted 209s Actual Attic Eritrean 209s Attic 0.923 0.077 209s Eritrean 0.143 0.857 209s 209s Data: olitos 209s 209s Apparent error rate 0.1 209s 209s Classification table 209s Predicted 209s Actual 1 2 3 4 209s 1 45 2 2 1 209s 2 0 25 0 0 209s 3 4 1 27 2 209s 4 0 0 0 11 209s 209s Confusion matrix 209s Predicted 209s Actual 1 2 3 4 209s 1 0.900 0.040 0.040 0.020 209s 2 0.000 1.000 0.000 0.000 209s 3 0.118 0.029 0.794 0.059 209s 4 0.000 0.000 0.000 1.000 209s =================================================== 209s > #dodata(method="fsa") 209s > 209s BEGIN TEST tldapp.R 209s 209s R version 4.5.2 (2025-10-31) -- "[Not] Part in a Rumble" 209s Copyright (C) 2025 The R Foundation for Statistical Computing 209s Platform: aarch64-unknown-linux-gnu 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)) 210s > library(MASS) 210s > 210s > dodata <- function(method) { 210s + 210s + options(digits = 5) 210s + set.seed(101) 210s + 210s + tmp <- sys.call() 210s + cat("\nCall: ", deparse(substitute(tmp)),"\n") 210s + cat("===================================================\n") 210s + 210s + data(pottery); show(lda <- LdaPP(origin~., data=pottery, method=method)); show(predict(lda)) 210s + data(hemophilia); show(lda <- LdaPP(as.factor(gr)~., data=hemophilia, method=method)); show(predict(lda)) 210s + data(anorexia); show(lda <- LdaPP(Treat~., data=anorexia, method=method)); show(predict(lda)) 210s + data(Pima.tr); show(lda <- LdaPP(type~., data=Pima.tr, method=method)); show(predict(lda)) 210s + data(crabs); show(lda <- LdaPP(sp~., data=crabs, method=method)); show(predict(lda)) 210s + 210s + cat("===================================================\n") 210s + } 210s > 210s > 210s > ## -- now do it: 210s > 210s > ## Commented out - still to slow 210s > ##dodata(method="huber") 210s > ##dodata(method="sest") 210s > 210s > ## VT::14.11.2018 - Commented out: too slow 210s > ## dodata(method="mad") 210s > ## dodata(method="class") 210s > 210s BEGIN TEST tmcd4.R 210s 210s R version 4.5.2 (2025-10-31) -- "[Not] Part in a Rumble" 210s Copyright (C) 2025 The R Foundation for Statistical Computing 210s Platform: aarch64-unknown-linux-gnu 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 > ## Test the exact fit property of CovMcd 210s > doexactfit <- function(){ 210s + exact <-function(seed=1234){ 210s + 210s + set.seed(seed) 210s + 210s + n1 <- 45 210s + p <- 2 210s + x1 <- matrix(rnorm(p*n1),nrow=n1, ncol=p) 210s + x1[,p] <- x1[,p] + 3 210s + n2 <- 55 210s + m1 <- 0 210s + m2 <- 3 210s + x2 <- cbind(rnorm(n2),rep(m2,n2)) 210s + x<-rbind(x1,x2) 210s + colnames(x) <- c("X1","X2") 210s + x 210s + } 210s + print(CovMcd(exact())) 210s + } 210s > 210s > dodata <- function(nrep=1, time=FALSE, short=FALSE, full=TRUE, method = c("FASTMCD","MASS", "deterministic", "exact", "MRCD")){ 210s + ##@bdescr 210s + ## Test the function covMcd() on the literature datasets: 210s + ## 210s + ## Call CovMcd() for all regression datasets available in rrcov and print: 210s + ## - execution time (if time == TRUE) 210s + ## - objective fucntion 210s + ## - best subsample found (if short == false) 210s + ## - outliers identified (with cutoff 0.975) (if short == false) 210s + ## - estimated center and covarinance matrix if full == TRUE) 210s + ## 210s + ##@edescr 210s + ## 210s + ##@in nrep : [integer] number of repetitions to use for estimating the 210s + ## (average) execution time 210s + ##@in time : [boolean] whether to evaluate the execution time 210s + ##@in short : [boolean] whether to do short output (i.e. only the 210s + ## objective function value). If short == FALSE, 210s + ## the best subsample and the identified outliers are 210s + ## printed. See also the parameter full below 210s + ##@in full : [boolean] whether to print the estimated cente and covariance matrix 210s + ##@in method : [character] select a method: one of (FASTMCD, MASS) 210s + 210s + doest <- function(x, xname, nrep=1){ 210s + n <- dim(x)[1] 210s + p <- dim(x)[2] 210s + if(method == "MASS"){ 210s + mcd<-cov.mcd(x) 210s + quan <- as.integer(floor((n + p + 1)/2)) #default: floor((n+p+1)/2) 210s + } 210s + else{ 210s + mcd <- if(method=="deterministic") CovMcd(x, nsamp="deterministic", trace=FALSE) 210s + else if(method=="exact") CovMcd(x, nsamp="exact", trace=FALSE) 210s + else if(method=="MRCD") CovMrcd(x, trace=FALSE) 210s + else CovMcd(x, trace=FALSE) 210s + quan <- as.integer(mcd@quan) 210s + } 210s + 210s + crit <- mcd@crit 210s + 210s + if(time){ 210s + xtime <- system.time(dorep(x, nrep, method))[1]/nrep 210s + xres <- sprintf("%3d %3d %3d %12.6f %10.3f\n", dim(x)[1], dim(x)[2], quan, crit, xtime) 210s + } 210s + else{ 210s + xres <- sprintf("%3d %3d %3d %12.6f\n", dim(x)[1], dim(x)[2], quan, crit) 210s + } 210s + lpad<-lname-nchar(xname) 210s + cat(pad.right(xname,lpad), xres) 210s + 210s + if(!short){ 210s + cat("Best subsample: \n") 210s + if(length(mcd@best) > 150) 210s + cat("Too long... \n") 210s + else 210s + print(mcd@best) 210s + 210s + ibad <- which(mcd@wt==0) 210s + names(ibad) <- NULL 210s + nbad <- length(ibad) 210s + cat("Outliers: ",nbad,"\n") 210s + if(nbad > 0 & nbad < 150) 210s + print(ibad) 210s + else 210s + cat("Too many to print ... \n") 210s + if(full){ 210s + cat("-------------\n") 210s + show(mcd) 210s + } 210s + cat("--------------------------------------------------------\n") 210s + } 210s + } 210s + 210s + options(digits = 5) 210s + set.seed(101) # <<-- sub-sampling algorithm now based on R's RNG and seed 210s + 210s + lname <- 20 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 + method <- match.arg(method) 210s + if(method == "MASS") 210s + library(MASS) 210s + 210s + data(Animals, package = "MASS") 210s + brain <- Animals[c(1:24, 26:25, 27:28),] 210s + 210s + data(fish) 210s + data(pottery) 210s + data(rice) 210s + data(un86) 210s + data(wages) 210s + 210s + tmp <- sys.call() 210s + cat("\nCall: ", deparse(substitute(tmp)),"\n") 210s + 210s + cat("Data Set n p Half LOG(obj) Time\n") 210s + cat("========================================================\n") 210s + 210s + if(method=="exact") 210s + { 210s + ## only small data sets 210s + doest(heart[, 1:2], data(heart), nrep) 210s + doest(starsCYG, data(starsCYG), nrep) 210s + doest(data.matrix(subset(phosphor, select = -plant)), data(phosphor), nrep) 210s + doest(data.matrix(subset(coleman, select = -Y)), data(coleman), nrep) 210s + doest(data.matrix(subset(salinity, select = -Y)), data(salinity), nrep) 210s + doest(data.matrix(subset(wood, select = -y)), data(wood), nrep) 210s + doest(brain, "Animals", nrep) 210s + doest(lactic, data(lactic), nrep) 210s + doest(pension, data(pension), nrep) 210s + doest(data.matrix(subset(vaso, select = -Y)), data(vaso), nrep) 210s + doest(stack.x, data(stackloss), nrep) 210s + doest(pilot, data(pilot), nrep) 210s + } else 210s + { 210s + doest(heart[, 1:2], data(heart), nrep) 210s + doest(starsCYG, data(starsCYG), nrep) 210s + doest(data.matrix(subset(phosphor, select = -plant)), data(phosphor), nrep) 210s + doest(stack.x, data(stackloss), nrep) 210s + doest(data.matrix(subset(coleman, select = -Y)), data(coleman), nrep) 210s + doest(data.matrix(subset(salinity, select = -Y)), data(salinity), nrep) 210s + doest(data.matrix(subset(wood, select = -y)), data(wood), nrep) 210s + doest(data.matrix(subset(hbk, select = -Y)),data(hbk), nrep) 210s + 210s + doest(brain, "Animals", nrep) 210s + ## doest(milk, data(milk), nrep) # difference between 386 and x64 210s + doest(bushfire, data(bushfire), nrep) 210s + 210s + doest(lactic, data(lactic), nrep) 210s + doest(pension, data(pension), nrep) 210s + ## doest(pilot, data(pilot), nrep) # difference between 386 and x64 210s + 210s + if(method != "MRCD") # these two are quite slow for MRCD, especially the second one 210s + { 210s + doest(radarImage, data(radarImage), nrep) 210s + doest(NOxEmissions, data(NOxEmissions), nrep) 210s + } 210s + 210s + doest(data.matrix(subset(vaso, select = -Y)), data(vaso), nrep) 210s + doest(data.matrix(subset(wagnerGrowth, select = -Period)), data(wagnerGrowth), nrep) 210s + 210s + doest(data.matrix(subset(fish, select = -Species)), data(fish), nrep) 210s + doest(data.matrix(subset(pottery, select = -origin)), data(pottery), nrep) 210s + doest(rice, data(rice), nrep) 210s + doest(un86, data(un86), nrep) 210s + 210s + doest(wages, data(wages), nrep) 210s + 210s + ## from package 'datasets' 210s + doest(airquality[,1:4], data(airquality), nrep) 210s + doest(attitude, data(attitude), nrep) 210s + doest(attenu, data(attenu), nrep) 210s + doest(USJudgeRatings, data(USJudgeRatings), nrep) 210s + doest(USArrests, data(USArrests), nrep) 210s + doest(longley, data(longley), nrep) 210s + doest(Loblolly, data(Loblolly), nrep) 210s + doest(quakes[,1:4], data(quakes), nrep) 210s + } 210s + cat("========================================================\n") 210s + } 210s > 210s > dogen <- function(nrep=1, eps=0.49, method=c("FASTMCD", "MASS")){ 210s + 210s + doest <- function(x, nrep=1){ 210s + gc() 210s + xtime <- system.time(dorep(x, nrep, method))[1]/nrep 210s + cat(sprintf("%6d %3d %10.2f\n", dim(x)[1], dim(x)[2], xtime)) 210s + xtime 210s + } 210s + 210s + set.seed(1234) 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 + library(MASS) 210s + method <- match.arg(method) 210s + 210s + ap <- c(2, 5, 10, 20, 30) 210s + an <- c(100, 500, 1000, 10000, 50000) 210s + 210s + tottime <- 0 210s + cat(" n p Time\n") 210s + 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 + doest(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 + mcd <- CovMcd(xx$X) 210s + check(mcd, xx$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("FASTMCD","MASS", "deterministic", "exact", "MRCD")){ 210s + 210s + method <- match.arg(method) 210s + for(i in 1:nrep) 210s + if(method == "MASS") 210s + cov.mcd(x) 210s + else 210s + { 210s + if(method=="deterministic") CovMcd(x, nsamp="deterministic", trace=FALSE) 210s + else if(method=="exact") CovMcd(x, nsamp="exact", trace=FALSE) 210s + else if(method=="MRCD") CovMrcd(x, trace=FALSE) 210s + else CovMcd(x, trace=FALSE) 210s + } 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 5.678742 210s Best subsample: 210s [1] 1 3 4 5 7 9 11 210s Outliers: 0 210s Too many to print ... 210s ------------- 210s 210s Call: 210s CovMcd(x = x, trace = FALSE) 210s -> Method: Fast MCD(alpha=0.5 ==> h=7); nsamp = 500; (n,k)mini = (300,5) 210s 210s Robust Estimate of Location: 210s height weight 210s 38.3 33.1 210s 210s Robust Estimate of Covariance: 210s height weight 210s height 135 259 210s weight 259 564 210s -------------------------------------------------------- 210s starsCYG 47 2 25 -8.031215 210s Best subsample: 210s [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 210s Outliers: 7 210s [1] 7 9 11 14 20 30 34 210s ------------- 210s 210s Call: 210s CovMcd(x = x, trace = FALSE) 210s -> Method: Fast MCD(alpha=0.5 ==> h=25); nsamp = 500; (n,k)mini = (300,5) 210s 210s Robust Estimate of Location: 210s log.Te log.light 210s 4.41 4.95 210s 210s Robust Estimate of Covariance: 210s log.Te log.light 210s log.Te 0.0132 0.0394 210s log.light 0.0394 0.2743 210s -------------------------------------------------------- 210s phosphor 18 2 10 6.878847 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 CovMcd(x = x, trace = FALSE) 210s -> Method: Fast MCD(alpha=0.5 ==> h=10); nsamp = 500; (n,k)mini = (300,5) 210s 210s Robust Estimate of Location: 210s inorg organic 210s 13.4 38.8 210s 210s Robust Estimate of Covariance: 210s inorg organic 210s inorg 129 130 210s organic 130 182 210s -------------------------------------------------------- 210s stackloss 21 3 12 5.472581 210s Best subsample: 210s [1] 4 5 6 7 8 9 10 11 12 13 14 20 210s Outliers: 9 210s [1] 1 2 3 15 16 17 18 19 21 210s ------------- 210s 210s Call: 210s CovMcd(x = x, trace = FALSE) 210s -> Method: Fast MCD(alpha=0.5 ==> h=12); nsamp = 500; (n,k)mini = (300,5) 210s 210s Robust Estimate of Location: 210s Air.Flow Water.Temp Acid.Conc. 210s 59.5 20.8 87.3 210s 210s Robust Estimate of Covariance: 210s Air.Flow Water.Temp Acid.Conc. 210s Air.Flow 6.29 5.85 5.74 210s Water.Temp 5.85 9.23 6.14 210s Acid.Conc. 5.74 6.14 23.25 210s -------------------------------------------------------- 210s coleman 20 5 13 1.286808 210s Best subsample: 210s [1] 2 3 4 5 7 8 12 13 14 16 17 19 20 210s Outliers: 7 210s [1] 1 6 9 10 11 15 18 210s ------------- 210s 210s Call: 210s CovMcd(x = x, trace = FALSE) 210s -> Method: Fast MCD(alpha=0.5 ==> h=13); nsamp = 500; (n,k)mini = (300,5) 210s 210s Robust Estimate of Location: 210s salaryP fatherWc sstatus teacherSc motherLev 210s 2.76 48.38 6.12 25.00 6.40 210s 210s Robust Estimate of Covariance: 210s salaryP fatherWc sstatus teacherSc motherLev 210s salaryP 0.253 1.786 -0.266 0.151 0.075 210s fatherWc 1.786 1303.382 330.496 12.604 34.503 210s sstatus -0.266 330.496 119.888 3.833 10.131 210s teacherSc 0.151 12.604 3.833 0.785 0.555 210s motherLev 0.075 34.503 10.131 0.555 1.043 210s -------------------------------------------------------- 210s salinity 28 3 16 1.326364 210s Best subsample: 210s [1] 1 2 6 7 8 12 13 14 18 20 21 22 25 26 27 28 210s Outliers: 4 210s [1] 5 16 23 24 210s ------------- 210s 210s Call: 210s CovMcd(x = x, trace = FALSE) 210s -> Method: Fast MCD(alpha=0.5 ==> h=16); nsamp = 500; (n,k)mini = (300,5) 210s 210s Robust Estimate of Location: 210s X1 X2 X3 210s 10.08 2.78 22.78 210s 210s Robust Estimate of Covariance: 210s X1 X2 X3 210s X1 10.44 1.01 -3.19 210s X2 1.01 3.83 -1.44 210s X3 -3.19 -1.44 2.39 210s -------------------------------------------------------- 210s wood 20 5 13 -36.270094 210s Best subsample: 210s [1] 1 2 3 5 9 10 12 13 14 15 17 18 20 210s Outliers: 7 210s [1] 4 6 7 8 11 16 19 210s ------------- 210s 210s Call: 210s CovMcd(x = x, trace = FALSE) 210s -> Method: Fast MCD(alpha=0.5 ==> h=13); nsamp = 500; (n,k)mini = (300,5) 210s 210s Robust Estimate of Location: 210s x1 x2 x3 x4 x5 210s 0.587 0.122 0.531 0.538 0.892 210s 210s Robust Estimate of Covariance: 210s x1 x2 x3 x4 x5 210s x1 1.00e-02 1.88e-03 3.15e-03 -5.86e-04 -1.63e-03 210s x2 1.88e-03 4.85e-04 1.27e-03 -5.20e-05 2.36e-05 210s x3 3.15e-03 1.27e-03 6.63e-03 -8.71e-04 3.52e-04 210s x4 -5.86e-04 -5.20e-05 -8.71e-04 2.85e-03 1.83e-03 210s x5 -1.63e-03 2.36e-05 3.52e-04 1.83e-03 2.77e-03 210s -------------------------------------------------------- 210s hbk 75 3 39 -1.047858 210s Best subsample: 210s [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 210s [26] 55 56 58 59 61 63 64 66 67 70 71 72 73 74 210s Outliers: 14 210s [1] 1 2 3 4 5 6 7 8 9 10 11 12 13 14 210s ------------- 210s 210s Call: 210s CovMcd(x = x, trace = FALSE) 210s -> Method: Fast MCD(alpha=0.5 ==> h=39); nsamp = 500; (n,k)mini = (300,5) 210s 210s Robust Estimate of Location: 210s X1 X2 X3 210s 1.54 1.78 1.69 210s 210s Robust Estimate of Covariance: 210s X1 X2 X3 210s X1 1.227 0.055 0.127 210s X2 0.055 1.249 0.153 210s X3 0.127 0.153 1.160 210s -------------------------------------------------------- 210s Animals 28 2 15 14.555543 210s Best subsample: 210s [1] 1 3 4 5 10 11 17 18 19 20 21 22 23 26 27 210s Outliers: 14 210s [1] 2 6 7 8 9 12 13 14 15 16 23 24 25 28 210s ------------- 210s 210s Call: 210s CovMcd(x = x, trace = FALSE) 210s -> Method: Fast MCD(alpha=0.5 ==> h=15); nsamp = 500; (n,k)mini = (300,5) 210s 210s Robust Estimate of Location: 210s body brain 210s 18.7 64.9 210s 210s Robust Estimate of Covariance: 210s body brain 210s body 929 1576 210s brain 1576 5646 210s -------------------------------------------------------- 210s bushfire 38 5 22 18.135810 210s Best subsample: 210s [1] 1 2 3 4 5 6 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 210s Outliers: 16 210s [1] 7 8 9 10 11 12 29 30 31 32 33 34 35 36 37 38 210s ------------- 210s 210s Call: 210s CovMcd(x = x, trace = FALSE) 210s -> Method: Fast MCD(alpha=0.5 ==> h=22); nsamp = 500; (n,k)mini = (300,5) 210s 210s Robust Estimate of Location: 210s V1 V2 V3 V4 V5 210s 105 147 274 218 279 210s 210s Robust Estimate of Covariance: 210s V1 V2 V3 V4 V5 210s V1 346 268 -1692 -381 -311 210s V2 268 236 -1125 -230 -194 210s V3 -1692 -1125 9993 2455 1951 210s V4 -381 -230 2455 647 505 210s V5 -311 -194 1951 505 398 210s -------------------------------------------------------- 210s lactic 20 2 11 0.359580 210s Best subsample: 210s [1] 1 2 3 4 5 7 8 9 10 11 12 210s Outliers: 4 210s [1] 17 18 19 20 210s ------------- 210s 210s Call: 210s CovMcd(x = x, trace = FALSE) 210s -> Method: Fast MCD(alpha=0.5 ==> h=11); nsamp = 500; (n,k)mini = (300,5) 210s 210s Robust Estimate of Location: 210s X Y 210s 3.86 5.01 210s 210s Robust Estimate of Covariance: 210s X Y 210s X 10.6 14.6 210s Y 14.6 21.3 210s -------------------------------------------------------- 210s pension 18 2 10 16.675508 210s Best subsample: 210s [1] 1 2 3 4 5 6 8 9 11 12 210s Outliers: 5 210s [1] 14 15 16 17 18 210s ------------- 210s 210s Call: 210s CovMcd(x = x, trace = FALSE) 210s -> Method: Fast MCD(alpha=0.5 ==> h=10); nsamp = 500; (n,k)mini = (300,5) 210s 210s Robust Estimate of Location: 210s Income Reserves 210s 52.3 560.9 210s 210s Robust Estimate of Covariance: 210s Income Reserves 210s Income 1420 11932 210s Reserves 11932 208643 210s -------------------------------------------------------- 211s radarImage 1573 5 789 36.694425 211s Best subsample: 211s Too long... 211s Outliers: 117 211s [1] 164 237 238 242 261 262 351 450 451 462 480 481 509 516 535 211s [16] 542 572 597 620 643 654 669 697 737 802 803 804 818 832 833 211s [31] 834 862 863 864 892 900 939 989 1029 1064 1123 1132 1145 1202 1223 211s [46] 1224 1232 1233 1249 1250 1258 1259 1267 1303 1347 1357 1368 1375 1376 1393 211s [61] 1394 1402 1403 1411 1417 1419 1420 1428 1436 1443 1444 1453 1470 1479 1487 211s [76] 1492 1504 1510 1511 1512 1517 1518 1519 1520 1521 1522 1525 1526 1527 1528 211s [91] 1530 1532 1534 1543 1544 1546 1547 1548 1549 1550 1551 1552 1553 1554 1555 211s [106] 1557 1558 1561 1562 1564 1565 1566 1567 1569 1570 1571 1573 211s ------------- 211s 211s Call: 211s CovMcd(x = x, trace = FALSE) 211s -> Method: Fast MCD(alpha=0.5 ==> h=789); nsamp = 500; (n,k)mini = (300,5) 211s 211s Robust Estimate of Location: 211s X.coord Y.coord Band.1 Band.2 Band.3 211s 52.80 35.12 6.77 18.44 8.90 211s 211s Robust Estimate of Covariance: 211s X.coord Y.coord Band.1 Band.2 Band.3 211s X.coord 123.6 23.0 -361.9 -197.1 -22.5 211s Y.coord 23.0 400.6 34.3 -191.1 -39.1 211s Band.1 -361.9 34.3 27167.9 8178.8 473.7 211s Band.2 -197.1 -191.1 8178.8 26021.8 952.4 211s Band.3 -22.5 -39.1 473.7 952.4 4458.4 211s -------------------------------------------------------- 211s NOxEmissions 8088 4 4046 2.474539 211s Best subsample: 211s Too long... 211s Outliers: 2156 211s Too many to print ... 211s ------------- 211s 211s Call: 211s CovMcd(x = x, trace = FALSE) 211s -> Method: Fast MCD(alpha=0.5 ==> h=4046); nsamp = 500; (n,k)mini = (300,5) 211s 211s Robust Estimate of Location: 211s julday LNOx LNOxEm sqrtWS 211s 168.19 4.73 7.91 1.37 211s 211s Robust Estimate of Covariance: 211s julday LNOx LNOxEm sqrtWS 211s julday 9180.6297 12.0306 0.7219 -10.1273 211s LNOx 12.0306 0.4721 0.1418 -0.1526 211s LNOxEm 0.7219 0.1418 0.2516 0.0438 211s sqrtWS -10.1273 -0.1526 0.0438 0.2073 211s -------------------------------------------------------- 211s vaso 39 2 21 -3.972244 211s Best subsample: 211s [1] 3 4 8 14 18 19 20 21 22 23 24 25 26 27 28 33 34 35 37 38 39 211s Outliers: 4 211s [1] 1 2 17 31 211s ------------- 211s 211s Call: 211s CovMcd(x = x, trace = FALSE) 211s -> Method: Fast MCD(alpha=0.5 ==> h=21); nsamp = 500; (n,k)mini = (300,5) 211s 211s Robust Estimate of Location: 211s Volume Rate 211s 1.16 1.72 211s 211s Robust Estimate of Covariance: 211s Volume Rate 211s Volume 0.313 -0.167 211s Rate -0.167 0.728 211s -------------------------------------------------------- 211s wagnerGrowth 63 6 35 6.572208 211s Best subsample: 211s [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 211s [26] 48 51 52 53 54 55 56 57 60 62 211s Outliers: 13 211s [1] 1 8 15 21 22 28 29 33 42 43 46 50 63 211s ------------- 211s 211s Call: 211s CovMcd(x = x, trace = FALSE) 211s -> Method: Fast MCD(alpha=0.5 ==> h=35); nsamp = 500; (n,k)mini = (300,5) 211s 211s Robust Estimate of Location: 211s Region PA GPA HS GHS y 211s 11.00 33.66 -2.00 2.48 0.31 7.48 211s 211s Robust Estimate of Covariance: 211s Region PA GPA HS GHS y 211s Region 35.5615 17.9337 -0.5337 -0.9545 -0.3093 -14.0090 211s PA 17.9337 27.7333 -4.9017 -1.4174 0.0343 -28.7040 211s GPA -0.5337 -4.9017 5.3410 0.2690 -0.1484 4.0006 211s HS -0.9545 -1.4174 0.2690 0.8662 -0.0454 2.9024 211s GHS -0.3093 0.0343 -0.1484 -0.0454 0.1772 0.7457 211s y -14.0090 -28.7040 4.0006 2.9024 0.7457 82.6877 211s -------------------------------------------------------- 211s fish 159 6 82 8.879005 211s Best subsample: 211s [1] 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 211s [20] 20 21 22 23 24 25 26 27 28 30 32 35 36 37 42 43 44 45 46 211s [39] 47 48 49 50 51 52 53 54 55 56 57 58 59 60 107 109 110 111 113 211s [58] 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 211s [77] 134 135 136 137 138 139 211s Outliers: 63 211s [1] 30 39 40 41 42 62 63 64 65 66 68 69 70 73 74 75 76 77 78 211s [20] 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 211s [39] 98 99 100 101 102 103 104 105 141 143 144 145 147 148 149 150 151 152 153 211s [58] 154 155 156 157 158 159 211s ------------- 211s 211s Call: 211s CovMcd(x = x, trace = FALSE) 211s -> Method: Fast MCD(alpha=0.5 ==> h=82); nsamp = 500; (n,k)mini = (300,5) 211s 211s Robust Estimate of Location: 211s Weight Length1 Length2 Length3 Height Width 211s 329.9 24.5 26.6 29.7 31.1 14.7 211s 211s Robust Estimate of Covariance: 211s Weight Length1 Length2 Length3 Height Width 211s Weight 69082.99 1477.81 1613.64 1992.62 1439.32 -62.12 211s Length1 1477.81 34.68 37.61 45.51 28.82 -1.31 211s Length2 1613.64 37.61 40.88 49.52 31.81 -1.40 211s Length3 1992.62 45.51 49.52 61.16 42.65 -2.25 211s Height 1439.32 28.82 31.81 42.65 46.74 -2.82 211s Width -62.12 -1.31 -1.40 -2.25 -2.82 1.01 211s -------------------------------------------------------- 211s pottery 27 6 17 -10.586933 211s Best subsample: 211s [1] 1 2 4 5 6 9 10 11 13 14 15 19 20 21 22 26 27 211s Outliers: 9 211s [1] 3 8 12 16 17 18 23 24 25 211s ------------- 211s 211s Call: 211s CovMcd(x = x, trace = FALSE) 211s -> Method: Fast MCD(alpha=0.5 ==> h=17); nsamp = 500; (n,k)mini = (300,5) 211s 211s Robust Estimate of Location: 211s SI AL FE MG CA TI 211s 54.983 15.206 9.700 3.817 5.211 0.859 211s 211s Robust Estimate of Covariance: 211s SI AL FE MG CA TI 211s SI 20.58227 2.28743 -0.02039 2.12648 -1.80227 0.08821 211s AL 2.28743 4.03605 -0.63021 -2.49966 0.20842 -0.02038 211s FE -0.02039 -0.63021 0.27803 0.53382 -0.35125 0.01427 211s MG 2.12648 -2.49966 0.53382 2.79561 -0.15786 0.02847 211s CA -1.80227 0.20842 -0.35125 -0.15786 1.23240 -0.03465 211s TI 0.08821 -0.02038 0.01427 0.02847 -0.03465 0.00175 211s -------------------------------------------------------- 211s rice 105 6 56 -14.463986 211s Best subsample: 211s [1] 2 4 6 8 10 12 15 18 21 22 24 29 30 31 32 33 34 36 37 211s [20] 38 41 44 45 47 51 52 53 54 55 59 61 65 67 68 69 70 72 76 211s [39] 78 79 80 81 82 83 84 85 86 92 93 94 95 97 98 99 102 105 211s Outliers: 13 211s [1] 9 14 19 28 40 42 49 58 62 71 75 77 89 211s ------------- 211s 211s Call: 211s CovMcd(x = x, trace = FALSE) 211s -> Method: Fast MCD(alpha=0.5 ==> h=56); nsamp = 500; (n,k)mini = (300,5) 211s 211s Robust Estimate of Location: 211s Favor Appearance Taste Stickiness 211s -0.2731 0.0600 -0.1468 0.0646 211s Toughness Overall_evaluation 211s 0.0894 -0.2192 211s 211s Robust Estimate of Covariance: 211s Favor Appearance Taste Stickiness Toughness 211s Favor 0.388 0.323 0.393 0.389 -0.195 211s Appearance 0.323 0.503 0.494 0.494 -0.270 211s Taste 0.393 0.494 0.640 0.629 -0.361 211s Stickiness 0.389 0.494 0.629 0.815 -0.486 211s Toughness -0.195 -0.270 -0.361 -0.486 0.451 211s Overall_evaluation 0.471 0.575 0.723 0.772 -0.457 211s Overall_evaluation 211s Favor 0.471 211s Appearance 0.575 211s Taste 0.723 211s Stickiness 0.772 211s Toughness -0.457 211s Overall_evaluation 0.882 211s -------------------------------------------------------- 211s un86 73 7 40 17.009322 211s Best subsample: 211s [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 211s [26] 51 52 55 56 60 61 62 63 64 65 67 70 71 72 73 211s Outliers: 30 211s [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 211s [26] 58 59 66 68 69 211s ------------- 211s 211s Call: 211s CovMcd(x = x, trace = FALSE) 211s -> Method: Fast MCD(alpha=0.5 ==> h=40); nsamp = 500; (n,k)mini = (300,5) 211s 211s Robust Estimate of Location: 211s POP MOR CAR DR GNP DEN TB 211s 20.740 71.023 6.435 0.817 1.146 56.754 0.441 211s 211s Robust Estimate of Covariance: 211s POP MOR CAR DR GNP DEN 211s POP 582.4034 224.9343 -12.6722 -1.6729 -3.3664 226.1952 211s MOR 224.9343 2351.3907 -286.9504 -32.0743 -35.5649 -527.4684 211s CAR -12.6722 -286.9504 58.1190 5.7393 6.6365 83.6180 211s DR -1.6729 -32.0743 5.7393 0.8339 0.5977 12.1938 211s GNP -3.3664 -35.5649 6.6365 0.5977 1.4175 13.0709 211s DEN 226.1952 -527.4684 83.6180 12.1938 13.0709 2041.5809 211s TB 0.4002 -1.1807 0.2701 0.0191 0.0058 -0.9346 211s TB 211s POP 0.4002 211s MOR -1.1807 211s CAR 0.2701 211s DR 0.0191 211s GNP 0.0058 211s DEN -0.9346 211s TB 0.0184 211s -------------------------------------------------------- 211s wages 39 10 19 22.994272 211s Best subsample: 211s [1] 1 2 6 7 8 9 10 11 12 13 14 15 17 18 19 25 26 27 28 211s Outliers: 9 211s [1] 4 5 6 24 28 30 32 33 34 211s ------------- 211s 211s Call: 211s CovMcd(x = x, trace = FALSE) 211s -> Method: Fast MCD(alpha=0.5 ==> h=19); nsamp = 500; (n,k)mini = (300,5) 211s 211s Robust Estimate of Location: 211s HRS RATE ERSP ERNO NEIN ASSET AGE DEP 211s 2153.37 2.87 1129.16 297.53 360.58 6876.58 39.48 2.36 211s RACE SCHOOL 211s 38.88 10.17 211s 211s Robust Estimate of Covariance: 211s HRS RATE ERSP ERNO NEIN ASSET 211s HRS 6.12e+03 1.73e+01 -1.67e+03 -2.06e+03 9.10e+03 2.02e+05 211s RATE 1.73e+01 2.52e-01 2.14e+01 -3.54e+00 5.85e+01 1.37e+03 211s ERSP -1.67e+03 2.14e+01 1.97e+04 7.76e+01 -1.71e+03 -1.41e+04 211s ERNO -2.06e+03 -3.54e+00 7.76e+01 2.06e+03 -2.02e+03 -4.83e+04 211s NEIN 9.10e+03 5.85e+01 -1.71e+03 -2.02e+03 2.02e+04 4.54e+05 211s ASSET 2.02e+05 1.37e+03 -1.41e+04 -4.83e+04 4.54e+05 1.03e+07 211s AGE -6.29e+01 -2.61e-01 4.83e+00 2.44e+01 -1.08e+02 -2.46e+03 211s DEP -6.17e+00 -7.05e-02 -2.13e+01 2.29e+00 -1.30e+01 -3.16e+02 211s RACE -2.17e+03 -9.46e+00 7.19e+02 5.59e+02 -3.95e+03 -8.77e+04 211s SCHOOL 7.12e+01 5.87e-01 5.39e+01 -2.14e+01 1.63e+02 3.79e+03 211s AGE DEP RACE SCHOOL 211s HRS -6.29e+01 -6.17e+00 -2.17e+03 7.12e+01 211s RATE -2.61e-01 -7.05e-02 -9.46e+00 5.87e-01 211s ERSP 4.83e+00 -2.13e+01 7.19e+02 5.39e+01 211s ERNO 2.44e+01 2.29e+00 5.59e+02 -2.14e+01 211s NEIN -1.08e+02 -1.30e+01 -3.95e+03 1.63e+02 211s ASSET -2.46e+03 -3.16e+02 -8.77e+04 3.79e+03 211s AGE 1.01e+00 7.03e-02 2.39e+01 -9.52e-01 211s DEP 7.03e-02 4.62e-02 2.72e+00 -1.94e-01 211s RACE 2.39e+01 2.72e+00 8.74e+02 -3.09e+01 211s SCHOOL -9.52e-01 -1.94e-01 -3.09e+01 1.62e+00 211s -------------------------------------------------------- 211s airquality 153 4 58 18.213499 211s Best subsample: 211s [1] 3 22 24 25 28 29 32 33 35 36 37 38 39 40 41 42 43 44 46 211s [20] 47 48 49 50 52 56 57 58 59 60 64 66 67 68 69 71 72 73 74 211s [39] 76 78 80 82 83 84 86 87 89 90 91 92 93 94 95 97 98 105 109 211s [58] 110 211s Outliers: 14 211s [1] 8 9 15 18 20 21 23 24 28 30 48 62 117 148 211s ------------- 211s 211s Call: 211s CovMcd(x = x, trace = FALSE) 211s -> Method: Fast MCD(alpha=0.5 ==> h=58); nsamp = 500; (n,k)mini = (300,5) 211s 211s Robust Estimate of Location: 211s Ozone Solar.R Wind Temp 211s 43.2 192.9 9.6 80.5 211s 211s Robust Estimate of Covariance: 211s Ozone Solar.R Wind Temp 211s Ozone 959.69 771.68 -60.92 198.38 211s Solar.R 771.68 7089.72 -1.72 95.75 211s Wind -60.92 -1.72 10.71 -11.96 211s Temp 198.38 95.75 -11.96 62.78 211s -------------------------------------------------------- 211s attitude 30 7 19 24.442803 211s Best subsample: 211s [1] 2 3 4 5 7 8 10 12 15 17 19 20 22 23 25 27 28 29 30 211s Outliers: 10 211s [1] 1 6 9 13 14 16 18 21 24 26 211s ------------- 211s 211s Call: 211s CovMcd(x = x, trace = FALSE) 211s -> Method: Fast MCD(alpha=0.5 ==> h=19); nsamp = 500; (n,k)mini = (300,5) 211s 211s Robust Estimate of Location: 211s rating complaints privileges learning raises critical 211s 67.1 68.0 52.4 57.6 67.2 77.4 211s advance 211s 43.4 211s 211s Robust Estimate of Covariance: 211s rating complaints privileges learning raises critical advance 211s rating 169.34 127.83 40.48 110.26 91.71 -3.59 53.84 211s complaints 127.83 156.80 52.65 110.97 96.56 7.27 76.03 211s privileges 40.48 52.65 136.91 92.38 69.00 9.53 87.98 211s learning 110.26 110.97 92.38 157.77 112.92 6.74 75.51 211s raises 91.71 96.56 69.00 112.92 112.79 4.91 70.22 211s critical -3.59 7.27 9.53 6.74 4.91 52.25 15.00 211s advance 53.84 76.03 87.98 75.51 70.22 15.00 93.11 211s -------------------------------------------------------- 211s attenu 182 5 86 6.440834 211s Best subsample: 211s [1] 68 69 70 71 72 73 74 75 76 77 79 82 83 84 85 86 87 88 89 211s [20] 90 91 92 101 102 103 104 106 107 109 110 111 112 113 114 115 116 117 118 211s [39] 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 211s [58] 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 211s [77] 157 158 159 160 161 162 163 164 165 166 211s Outliers: 61 211s [1] 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 211s [20] 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 36 37 38 39 211s [39] 40 45 46 47 54 55 56 57 58 59 60 61 64 65 82 97 98 100 101 211s [58] 102 103 104 105 211s ------------- 211s 211s Call: 211s CovMcd(x = x, trace = FALSE) 211s -> Method: Fast MCD(alpha=0.5 ==> h=86); nsamp = 500; (n,k)mini = (300,5) 211s 211s Robust Estimate of Location: 211s event mag station dist accel 211s 18.624 5.752 67.861 22.770 0.141 211s 211s Robust Estimate of Covariance: 211s event mag station dist accel 211s event 1.64e+01 -1.22e+00 5.59e+01 9.98e+00 -8.37e-02 211s mag -1.22e+00 4.13e-01 -3.19e+00 1.35e+00 1.22e-02 211s station 5.59e+01 -3.19e+00 1.03e+03 7.00e+01 5.56e-01 211s dist 9.98e+00 1.35e+00 7.00e+01 2.21e+02 -9.24e-01 211s accel -8.37e-02 1.22e-02 5.56e-01 -9.24e-01 9.62e-03 211s -------------------------------------------------------- 211s USJudgeRatings 43 12 28 -47.889993 211s Best subsample: 211s [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 211s [26] 38 41 43 211s Outliers: 14 211s [1] 5 7 8 12 13 14 20 21 23 30 31 35 40 42 211s ------------- 211s 211s Call: 211s CovMcd(x = x, trace = FALSE) 211s -> Method: Fast MCD(alpha=0.5 ==> h=28); nsamp = 500; (n,k)mini = (300,5) 211s 211s Robust Estimate of Location: 211s CONT INTG DMNR DILG CFMG DECI PREP FAMI ORAL WRIT PHYS RTEN 211s 7.40 8.19 7.80 7.96 7.74 7.82 7.74 7.73 7.57 7.63 8.25 7.94 211s 211s Robust Estimate of Covariance: 211s CONT INTG DMNR DILG CFMG DECI PREP FAMI ORAL 211s CONT 0.852 -0.266 -0.422 -0.155 -0.049 -0.074 -0.117 -0.119 -0.177 211s INTG -0.266 0.397 0.537 0.406 0.340 0.325 0.404 0.409 0.430 211s DMNR -0.422 0.537 0.824 0.524 0.458 0.437 0.520 0.504 0.569 211s DILG -0.155 0.406 0.524 0.486 0.426 0.409 0.506 0.515 0.511 211s CFMG -0.049 0.340 0.458 0.426 0.427 0.403 0.466 0.476 0.478 211s DECI -0.074 0.325 0.437 0.409 0.403 0.396 0.449 0.462 0.460 211s PREP -0.117 0.404 0.520 0.506 0.466 0.449 0.552 0.565 0.551 211s FAMI -0.119 0.409 0.504 0.515 0.476 0.462 0.565 0.594 0.571 211s ORAL -0.177 0.430 0.569 0.511 0.478 0.460 0.551 0.571 0.575 211s WRIT -0.159 0.427 0.549 0.515 0.480 0.461 0.556 0.580 0.574 211s PHYS -0.184 0.269 0.362 0.308 0.298 0.307 0.335 0.358 0.369 211s RTEN -0.260 0.472 0.642 0.519 0.467 0.455 0.539 0.554 0.573 211s WRIT PHYS RTEN 211s CONT -0.159 -0.184 -0.260 211s INTG 0.427 0.269 0.472 211s DMNR 0.549 0.362 0.642 211s DILG 0.515 0.308 0.519 211s CFMG 0.480 0.298 0.467 211s DECI 0.461 0.307 0.455 211s PREP 0.556 0.335 0.539 211s FAMI 0.580 0.358 0.554 211s ORAL 0.574 0.369 0.573 211s WRIT 0.580 0.365 0.567 211s PHYS 0.365 0.300 0.378 211s RTEN 0.567 0.378 0.615 211s -------------------------------------------------------- 211s USArrests 50 4 27 15.391648 211s Best subsample: 211s [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 211s [26] 49 50 211s Outliers: 11 211s [1] 2 3 5 6 10 18 24 28 33 37 47 211s ------------- 211s 211s Call: 211s CovMcd(x = x, trace = FALSE) 211s -> Method: Fast MCD(alpha=0.5 ==> h=27); nsamp = 500; (n,k)mini = (300,5) 211s 211s Robust Estimate of Location: 211s Murder Assault UrbanPop Rape 211s 6.71 145.42 65.06 17.88 211s 211s Robust Estimate of Covariance: 211s Murder Assault UrbanPop Rape 211s Murder 16.1 269.3 20.3 25.2 211s Assault 269.3 6613.0 567.8 453.7 211s UrbanPop 20.3 567.8 225.4 47.7 211s Rape 25.2 453.7 47.7 50.9 211s -------------------------------------------------------- 211s longley 16 7 12 12.747678 211s Best subsample: 211s [1] 5 6 7 8 9 10 11 12 13 14 15 16 211s Outliers: 4 211s [1] 1 2 3 4 211s ------------- 211s 211s Call: 211s CovMcd(x = x, trace = FALSE) 211s -> Method: Fast MCD(alpha=0.5 ==> h=12); nsamp = 500; (n,k)mini = (300,5) 211s 211s Robust Estimate of Location: 211s GNP.deflator GNP Unemployed Armed.Forces Population 211s 106.5 430.6 328.2 295.0 120.2 211s Year Employed 211s 1956.5 66.9 211s 211s Robust Estimate of Covariance: 211s GNP.deflator GNP Unemployed Armed.Forces Population 211s GNP.deflator 108.5 1039.9 1231.9 -465.6 81.4 211s GNP 1039.9 10300.0 11161.6 -4277.6 803.4 211s Unemployed 1231.9 11161.6 19799.4 -5805.6 929.1 211s Armed.Forces -465.6 -4277.6 -5805.6 2805.5 -327.4 211s Population 81.4 803.4 929.1 -327.4 63.5 211s Year 51.6 504.3 595.6 -216.7 39.7 211s Employed 34.2 344.1 323.6 -149.5 26.2 211s Year Employed 211s GNP.deflator 51.6 34.2 211s GNP 504.3 344.1 211s Unemployed 595.6 323.6 211s Armed.Forces -216.7 -149.5 211s Population 39.7 26.2 211s Year 25.1 16.7 211s Employed 16.7 12.4 211s -------------------------------------------------------- 211s Loblolly 84 3 44 4.898174 211s Best subsample: 211s [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 211s [26] 46 49 50 51 55 56 58 61 62 64 67 68 69 73 74 75 79 80 81 211s Outliers: 31 211s [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 211s [26] 72 76 77 78 83 84 211s ------------- 211s 211s Call: 211s CovMcd(x = x, trace = FALSE) 211s -> Method: Fast MCD(alpha=0.5 ==> h=44); nsamp = 500; (n,k)mini = (300,5) 211s 211s Robust Estimate of Location: 211s height age Seed 211s 20.44 8.19 7.72 211s 211s Robust Estimate of Covariance: 211s height age Seed 211s height 247.8 79.5 11.9 211s age 79.5 25.7 3.0 211s Seed 11.9 3.0 17.1 211s -------------------------------------------------------- 211s quakes 1000 4 502 8.274369 211s Best subsample: 211s Too long... 211s Outliers: 265 211s Too many to print ... 211s ------------- 211s 211s Call: 211s CovMcd(x = x, trace = FALSE) 211s -> Method: Fast MCD(alpha=0.5 ==> h=502); nsamp = 500; (n,k)mini = (300,5) 211s 211s Robust Estimate of Location: 211s lat long depth mag 211s -21.31 182.48 361.35 4.54 211s 211s Robust Estimate of Covariance: 211s lat long depth mag 211s lat 1.47e+01 3.53e+00 1.34e+02 -2.52e-01 211s long 3.53e+00 4.55e+00 -3.63e+02 4.36e-02 211s depth 1.34e+02 -3.63e+02 4.84e+04 -1.29e+01 211s mag -2.52e-01 4.36e-02 -1.29e+01 1.38e-01 211s -------------------------------------------------------- 211s ======================================================== 211s > dodata(method="deterministic") 211s 211s Call: dodata(method = "deterministic") 211s Data Set n p Half LOG(obj) Time 211s ======================================================== 211s heart 12 2 7 5.678742 211s Best subsample: 211s [1] 1 3 4 5 7 9 11 211s Outliers: 0 211s Too many to print ... 211s ------------- 211s 211s Call: 211s CovMcd(x = x, nsamp = "deterministic", trace = FALSE) 211s -> Method: Deterministic MCD(alpha=0.5 ==> h=7) 211s 211s Robust Estimate of Location: 211s height weight 211s 38.3 33.1 211s 211s Robust Estimate of Covariance: 211s height weight 211s height 135 259 211s weight 259 564 211s -------------------------------------------------------- 211s starsCYG 47 2 25 -8.028718 211s Best subsample: 211s [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 211s Outliers: 7 211s [1] 7 9 11 14 20 30 34 211s ------------- 211s 211s Call: 211s CovMcd(x = x, nsamp = "deterministic", trace = FALSE) 211s -> Method: Deterministic MCD(alpha=0.5 ==> h=25) 211s 211s Robust Estimate of Location: 211s log.Te log.light 211s 4.41 4.95 211s 211s Robust Estimate of Covariance: 211s log.Te log.light 211s log.Te 0.0132 0.0394 211s log.light 0.0394 0.2743 211s -------------------------------------------------------- 211s phosphor 18 2 10 7.732906 211s Best subsample: 211s [1] 2 4 5 7 8 9 11 12 14 16 211s Outliers: 1 211s [1] 6 211s ------------- 211s 211s Call: 211s CovMcd(x = x, nsamp = "deterministic", trace = FALSE) 211s -> Method: Deterministic MCD(alpha=0.5 ==> h=10) 211s 211s Robust Estimate of Location: 211s inorg organic 211s 12.5 40.8 211s 211s Robust Estimate of Covariance: 211s inorg organic 211s inorg 124 101 211s organic 101 197 211s -------------------------------------------------------- 211s stackloss 21 3 12 6.577286 211s Best subsample: 211s [1] 4 5 6 7 8 9 11 13 16 18 19 20 211s Outliers: 2 211s [1] 1 2 211s ------------- 211s 211s Call: 211s CovMcd(x = x, nsamp = "deterministic", trace = FALSE) 211s -> Method: Deterministic MCD(alpha=0.5 ==> h=12) 211s 211s Robust Estimate of Location: 211s Air.Flow Water.Temp Acid.Conc. 211s 58.4 20.5 86.1 211s 211s Robust Estimate of Covariance: 211s Air.Flow Water.Temp Acid.Conc. 211s Air.Flow 56.28 13.33 26.68 211s Water.Temp 13.33 8.28 6.98 211s Acid.Conc. 26.68 6.98 37.97 211s -------------------------------------------------------- 211s coleman 20 5 13 2.149184 211s Best subsample: 211s [1] 3 4 5 7 8 12 13 14 16 17 18 19 20 211s Outliers: 2 211s [1] 6 10 211s ------------- 211s 211s Call: 211s CovMcd(x = x, nsamp = "deterministic", trace = FALSE) 211s -> Method: Deterministic MCD(alpha=0.5 ==> h=13) 211s 211s Robust Estimate of Location: 211s salaryP fatherWc sstatus teacherSc motherLev 211s 2.76 41.08 2.76 25.01 6.27 211s 211s Robust Estimate of Covariance: 211s salaryP fatherWc sstatus teacherSc motherLev 211s salaryP 0.391 2.956 2.146 0.447 0.110 211s fatherWc 2.956 1358.640 442.724 12.235 32.842 211s sstatus 2.146 442.724 205.590 6.464 11.382 211s teacherSc 0.447 12.235 6.464 1.179 0.510 211s motherLev 0.110 32.842 11.382 0.510 0.919 211s -------------------------------------------------------- 211s salinity 28 3 16 1.940763 211s Best subsample: 211s [1] 1 8 10 12 13 14 15 17 18 20 21 22 25 26 27 28 211s Outliers: 2 211s [1] 5 16 211s ------------- 211s 211s Call: 211s CovMcd(x = x, nsamp = "deterministic", trace = FALSE) 211s -> Method: Deterministic MCD(alpha=0.5 ==> h=16) 211s 211s Robust Estimate of Location: 211s X1 X2 X3 211s 10.50 2.58 23.12 211s 211s Robust Estimate of Covariance: 211s X1 X2 X3 211s X1 10.90243 -0.00457 -1.46156 211s X2 -0.00457 3.85051 -1.94604 211s X3 -1.46156 -1.94604 3.21424 211s -------------------------------------------------------- 211s wood 20 5 13 -35.240819 211s Best subsample: 211s [1] 1 2 3 5 9 11 12 13 14 15 17 18 20 211s Outliers: 4 211s [1] 4 6 8 19 211s ------------- 211s 211s Call: 211s CovMcd(x = x, nsamp = "deterministic", trace = FALSE) 211s -> Method: Deterministic MCD(alpha=0.5 ==> h=13) 211s 211s Robust Estimate of Location: 211s x1 x2 x3 x4 x5 211s 0.582 0.125 0.530 0.534 0.888 211s 211s Robust Estimate of Covariance: 211s x1 x2 x3 x4 x5 211s x1 1.05e-02 1.81e-03 2.08e-03 -6.41e-04 -9.61e-04 211s x2 1.81e-03 5.55e-04 8.76e-04 -2.03e-04 -4.70e-05 211s x3 2.08e-03 8.76e-04 5.60e-03 -1.11e-03 -1.26e-05 211s x4 -6.41e-04 -2.03e-04 -1.11e-03 4.27e-03 2.60e-03 211s x5 -9.61e-04 -4.70e-05 -1.26e-05 2.60e-03 2.95e-03 211s -------------------------------------------------------- 211s hbk 75 3 39 -1.045501 211s Best subsample: 211s [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 211s [26] 54 55 56 58 59 63 64 66 67 70 71 72 73 74 211s Outliers: 14 211s [1] 1 2 3 4 5 6 7 8 9 10 11 12 13 14 211s ------------- 211s 211s Call: 211s CovMcd(x = x, nsamp = "deterministic", trace = FALSE) 211s -> Method: Deterministic MCD(alpha=0.5 ==> h=39) 211s 211s Robust Estimate of Location: 211s X1 X2 X3 211s 1.54 1.78 1.69 211s 211s Robust Estimate of Covariance: 211s X1 X2 X3 211s X1 1.227 0.055 0.127 211s X2 0.055 1.249 0.153 211s X3 0.127 0.153 1.160 211s -------------------------------------------------------- 211s Animals 28 2 15 14.555543 211s Best subsample: 211s [1] 1 3 4 5 10 11 17 18 19 20 21 22 23 26 27 211s Outliers: 14 211s [1] 2 6 7 8 9 12 13 14 15 16 23 24 25 28 211s ------------- 211s 211s Call: 211s CovMcd(x = x, nsamp = "deterministic", trace = FALSE) 211s -> Method: Deterministic MCD(alpha=0.5 ==> h=15) 211s 211s Robust Estimate of Location: 211s body brain 211s 18.7 64.9 211s 211s Robust Estimate of Covariance: 211s body brain 211s body 929 1576 211s brain 1576 5646 211s -------------------------------------------------------- 211s bushfire 38 5 22 18.135810 211s Best subsample: 211s [1] 1 2 3 4 5 6 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 211s Outliers: 16 211s [1] 7 8 9 10 11 12 29 30 31 32 33 34 35 36 37 38 211s ------------- 211s 211s Call: 211s CovMcd(x = x, nsamp = "deterministic", trace = FALSE) 211s -> Method: Deterministic MCD(alpha=0.5 ==> h=22) 211s 211s Robust Estimate of Location: 211s V1 V2 V3 V4 V5 211s 105 147 274 218 279 211s 211s Robust Estimate of Covariance: 211s V1 V2 V3 V4 V5 211s V1 346 268 -1692 -381 -311 211s V2 268 236 -1125 -230 -194 211s V3 -1692 -1125 9993 2455 1951 211s V4 -381 -230 2455 647 505 211s V5 -311 -194 1951 505 398 211s -------------------------------------------------------- 211s lactic 20 2 11 0.359580 211s Best subsample: 211s [1] 1 2 3 4 5 7 8 9 10 11 12 211s Outliers: 4 211s [1] 17 18 19 20 211s ------------- 211s 211s Call: 211s CovMcd(x = x, nsamp = "deterministic", trace = FALSE) 211s -> Method: Deterministic MCD(alpha=0.5 ==> h=11) 211s 211s Robust Estimate of Location: 211s X Y 211s 3.86 5.01 211s 211s Robust Estimate of Covariance: 211s X Y 211s X 10.6 14.6 211s Y 14.6 21.3 211s -------------------------------------------------------- 211s pension 18 2 10 16.675508 211s Best subsample: 211s [1] 1 2 3 4 5 6 8 9 11 12 211s Outliers: 5 211s [1] 14 15 16 17 18 211s ------------- 211s 211s Call: 211s CovMcd(x = x, nsamp = "deterministic", trace = FALSE) 211s -> Method: Deterministic MCD(alpha=0.5 ==> h=10) 211s 211s Robust Estimate of Location: 211s Income Reserves 211s 52.3 560.9 211s 211s Robust Estimate of Covariance: 211s Income Reserves 211s Income 1420 11932 211s Reserves 11932 208643 211s -------------------------------------------------------- 211s radarImage 1573 5 789 36.694865 211s Best subsample: 211s Too long... 211s Outliers: 114 211s [1] 164 237 238 242 261 262 351 450 451 462 463 480 481 509 516 211s [16] 535 542 572 597 620 643 654 669 679 697 737 802 803 804 818 211s [31] 832 833 834 862 863 864 892 900 939 989 1029 1064 1123 1132 1145 211s [46] 1202 1223 1224 1232 1233 1249 1250 1258 1259 1267 1303 1347 1357 1368 1375 211s [61] 1376 1393 1394 1402 1411 1417 1419 1420 1428 1436 1443 1444 1453 1470 1504 211s [76] 1510 1511 1512 1518 1519 1520 1521 1522 1525 1526 1527 1528 1530 1532 1534 211s [91] 1543 1544 1546 1547 1548 1549 1550 1551 1552 1553 1554 1555 1557 1558 1561 211s [106] 1562 1564 1565 1566 1567 1569 1570 1571 1573 211s ------------- 211s 211s Call: 211s CovMcd(x = x, nsamp = "deterministic", trace = FALSE) 211s -> Method: Deterministic MCD(alpha=0.5 ==> h=789) 211s 211s Robust Estimate of Location: 211s X.coord Y.coord Band.1 Band.2 Band.3 211s 52.78 35.37 7.12 18.81 9.09 211s 211s Robust Estimate of Covariance: 211s X.coord Y.coord Band.1 Band.2 Band.3 211s X.coord 123.2 21.5 -363.9 -200.1 -24.3 211s Y.coord 21.5 410.7 46.5 -177.3 -33.4 211s Band.1 -363.9 46.5 27051.1 8138.9 469.3 211s Band.2 -200.1 -177.3 8138.9 25938.0 946.2 211s Band.3 -24.3 -33.4 469.3 946.2 4470.1 211s -------------------------------------------------------- 212s NOxEmissions 8088 4 4046 2.474536 212s Best subsample: 212s Too long... 212s Outliers: 2152 212s Too many to print ... 212s ------------- 212s 212s Call: 212s CovMcd(x = x, nsamp = "deterministic", trace = FALSE) 212s -> Method: Deterministic MCD(alpha=0.5 ==> h=4046) 212s 212s Robust Estimate of Location: 212s julday LNOx LNOxEm sqrtWS 212s 168.20 4.73 7.91 1.37 212s 212s Robust Estimate of Covariance: 212s julday LNOx LNOxEm sqrtWS 212s julday 9176.2934 12.0355 0.7022 -10.1387 212s LNOx 12.0355 0.4736 0.1430 -0.1528 212s LNOxEm 0.7022 0.1430 0.2527 0.0436 212s sqrtWS -10.1387 -0.1528 0.0436 0.2074 212s -------------------------------------------------------- 212s vaso 39 2 21 -3.972244 212s Best subsample: 212s [1] 3 4 8 14 18 19 20 21 22 23 24 25 26 27 28 33 34 35 37 38 39 212s Outliers: 4 212s [1] 1 2 17 31 212s ------------- 212s 212s Call: 212s CovMcd(x = x, nsamp = "deterministic", trace = FALSE) 212s -> Method: Deterministic MCD(alpha=0.5 ==> h=21) 212s 212s Robust Estimate of Location: 212s Volume Rate 212s 1.16 1.72 212s 212s Robust Estimate of Covariance: 212s Volume Rate 212s Volume 0.313 -0.167 212s Rate -0.167 0.728 212s -------------------------------------------------------- 212s wagnerGrowth 63 6 35 6.511864 212s Best subsample: 212s [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 212s [26] 48 51 52 53 54 55 56 57 60 62 212s Outliers: 15 212s [1] 1 8 15 21 22 28 29 33 39 42 43 46 49 50 63 212s ------------- 212s 212s Call: 212s CovMcd(x = x, nsamp = "deterministic", trace = FALSE) 212s -> Method: Deterministic MCD(alpha=0.5 ==> h=35) 212s 212s Robust Estimate of Location: 212s Region PA GPA HS GHS y 212s 10.91 33.65 -2.05 2.43 0.31 6.98 212s 212s Robust Estimate of Covariance: 212s Region PA GPA HS GHS y 212s Region 35.1365 17.7291 -1.4003 -0.6554 -0.4728 -14.9305 212s PA 17.7291 28.4297 -5.5245 -1.2444 -0.0452 -29.6181 212s GPA -1.4003 -5.5245 5.2170 0.3954 -0.2152 3.8252 212s HS -0.6554 -1.2444 0.3954 0.7273 -0.0107 2.1514 212s GHS -0.4728 -0.0452 -0.2152 -0.0107 0.1728 0.8440 212s y -14.9305 -29.6181 3.8252 2.1514 0.8440 79.0511 212s -------------------------------------------------------- 212s fish 159 6 82 8.880459 212s Best subsample: 212s [1] 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 212s [20] 20 21 22 23 24 25 26 27 35 36 37 42 43 44 45 46 47 48 49 212s [39] 50 51 52 53 54 55 56 57 58 59 60 106 107 108 109 110 111 112 113 212s [58] 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 212s [77] 134 135 136 137 138 139 212s Outliers: 64 212s [1] 30 39 40 41 62 63 64 65 66 68 69 70 73 74 75 76 77 78 79 212s [20] 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 212s [39] 99 100 101 102 103 104 105 141 142 143 144 145 146 147 148 149 150 151 152 212s [58] 153 154 155 156 157 158 159 212s ------------- 212s 212s Call: 212s CovMcd(x = x, nsamp = "deterministic", trace = FALSE) 212s -> Method: Deterministic MCD(alpha=0.5 ==> h=82) 212s 212s Robust Estimate of Location: 212s Weight Length1 Length2 Length3 Height Width 212s 316.3 24.1 26.3 29.3 31.0 14.7 212s 212s Robust Estimate of Covariance: 212s Weight Length1 Length2 Length3 Height Width 212s Weight 64662.19 1412.34 1541.95 1917.21 1420.83 -61.15 212s Length1 1412.34 34.14 37.04 45.07 29.25 -1.26 212s Length2 1541.95 37.04 40.26 49.04 32.21 -1.34 212s Length3 1917.21 45.07 49.04 60.82 43.03 -2.15 212s Height 1420.83 29.25 32.21 43.03 46.50 -2.66 212s Width -61.15 -1.26 -1.34 -2.15 -2.66 1.02 212s -------------------------------------------------------- 212s pottery 27 6 17 -10.586933 212s Best subsample: 212s [1] 1 2 4 5 6 9 10 11 13 14 15 19 20 21 22 26 27 212s Outliers: 9 212s [1] 3 8 12 16 17 18 23 24 25 212s ------------- 212s 212s Call: 212s CovMcd(x = x, nsamp = "deterministic", trace = FALSE) 212s -> Method: Deterministic MCD(alpha=0.5 ==> h=17) 212s 212s Robust Estimate of Location: 212s SI AL FE MG CA TI 212s 54.983 15.206 9.700 3.817 5.211 0.859 212s 212s Robust Estimate of Covariance: 212s SI AL FE MG CA TI 212s SI 20.58227 2.28743 -0.02039 2.12648 -1.80227 0.08821 212s AL 2.28743 4.03605 -0.63021 -2.49966 0.20842 -0.02038 212s FE -0.02039 -0.63021 0.27803 0.53382 -0.35125 0.01427 212s MG 2.12648 -2.49966 0.53382 2.79561 -0.15786 0.02847 212s CA -1.80227 0.20842 -0.35125 -0.15786 1.23240 -0.03465 212s TI 0.08821 -0.02038 0.01427 0.02847 -0.03465 0.00175 212s -------------------------------------------------------- 212s rice 105 6 56 -14.423048 212s Best subsample: 212s [1] 4 6 8 10 13 15 16 17 18 25 27 29 30 31 32 33 34 36 37 212s [20] 38 44 45 47 51 52 53 55 59 60 65 66 67 70 72 74 76 78 79 212s [39] 80 81 82 83 84 85 86 90 92 93 94 95 97 98 99 100 101 105 212s Outliers: 13 212s [1] 9 19 28 40 42 43 49 58 62 64 71 75 77 212s ------------- 212s 212s Call: 212s CovMcd(x = x, nsamp = "deterministic", trace = FALSE) 212s -> Method: Deterministic MCD(alpha=0.5 ==> h=56) 212s 212s Robust Estimate of Location: 212s Favor Appearance Taste Stickiness 212s -0.2950 0.0799 -0.1555 0.0363 212s Toughness Overall_evaluation 212s 0.0530 -0.2284 212s 212s Robust Estimate of Covariance: 212s Favor Appearance Taste Stickiness Toughness 212s Favor 0.466 0.389 0.471 0.447 -0.198 212s Appearance 0.389 0.610 0.592 0.570 -0.293 212s Taste 0.471 0.592 0.760 0.718 -0.356 212s Stickiness 0.447 0.570 0.718 0.820 -0.419 212s Toughness -0.198 -0.293 -0.356 -0.419 0.400 212s Overall_evaluation 0.557 0.669 0.838 0.846 -0.425 212s Overall_evaluation 212s Favor 0.557 212s Appearance 0.669 212s Taste 0.838 212s Stickiness 0.846 212s Toughness -0.425 212s Overall_evaluation 0.987 212s -------------------------------------------------------- 212s un86 73 7 40 17.117142 212s Best subsample: 212s [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 212s [26] 52 55 56 57 60 61 62 63 64 65 67 70 71 72 73 212s Outliers: 30 212s [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 212s [26] 58 59 66 68 69 212s ------------- 212s 212s Call: 212s CovMcd(x = x, nsamp = "deterministic", trace = FALSE) 212s -> Method: Deterministic MCD(alpha=0.5 ==> h=40) 212s 212s Robust Estimate of Location: 212s POP MOR CAR DR GNP DEN TB 212s 17.036 68.512 6.444 0.877 1.134 64.140 0.433 212s 212s Robust Estimate of Covariance: 212s POP MOR CAR DR GNP DEN 212s POP 3.61e+02 1.95e+02 -6.28e+00 -1.91e-02 -2.07e+00 5.79e+01 212s MOR 1.95e+02 2.39e+03 -2.79e+02 -3.37e+01 -3.39e+01 -9.21e+02 212s CAR -6.28e+00 -2.79e+02 5.76e+01 5.77e+00 6.59e+00 7.81e+01 212s DR -1.91e-02 -3.37e+01 5.77e+00 9.07e-01 5.66e-01 1.69e+01 212s GNP -2.07e+00 -3.39e+01 6.59e+00 5.66e-01 1.42e+00 9.28e+00 212s DEN 5.79e+01 -9.21e+02 7.81e+01 1.69e+01 9.28e+00 3.53e+03 212s TB -6.09e-02 -9.93e-01 2.50e-01 1.98e-02 6.82e-03 -9.75e-01 212s TB 212s POP -6.09e-02 212s MOR -9.93e-01 212s CAR 2.50e-01 212s DR 1.98e-02 212s GNP 6.82e-03 212s DEN -9.75e-01 212s TB 1.64e-02 212s -------------------------------------------------------- 212s wages 39 10 19 23.119456 212s Best subsample: 212s [1] 1 2 5 6 7 9 10 11 12 13 14 15 19 21 23 25 26 27 28 212s Outliers: 9 212s [1] 4 5 9 24 25 26 28 32 34 212s ------------- 212s 212s Call: 212s CovMcd(x = x, nsamp = "deterministic", trace = FALSE) 212s -> Method: Deterministic MCD(alpha=0.5 ==> h=19) 212s 212s Robust Estimate of Location: 212s HRS RATE ERSP ERNO NEIN ASSET AGE DEP 212s 2161.89 2.95 1114.21 297.68 374.00 7269.37 39.13 2.43 212s RACE SCHOOL 212s 36.13 10.39 212s 212s Robust Estimate of Covariance: 212s HRS RATE ERSP ERNO NEIN ASSET 212s HRS 3.53e+03 8.31e+00 -5.96e+03 -6.43e+02 5.15e+03 1.12e+05 212s RATE 8.31e+00 1.78e-01 8.19e+00 2.70e+00 3.90e+01 8.94e+02 212s ERSP -5.96e+03 8.19e+00 1.90e+04 1.13e+03 -4.73e+03 -9.49e+04 212s ERNO -6.43e+02 2.70e+00 1.13e+03 1.80e+03 -3.56e+02 -7.33e+03 212s NEIN 5.15e+03 3.90e+01 -4.73e+03 -3.56e+02 1.38e+04 3.00e+05 212s ASSET 1.12e+05 8.94e+02 -9.49e+04 -7.33e+03 3.00e+05 6.62e+06 212s AGE -3.33e+01 -6.55e-02 8.33e+01 1.50e+00 -3.28e+01 -7.55e+02 212s DEP 4.50e+00 -4.01e-02 -2.77e+01 1.31e+00 -8.09e+00 -1.61e+02 212s RACE -1.30e+03 -6.06e+00 1.80e+03 1.48e+02 -2.58e+03 -5.59e+04 212s SCHOOL 3.01e+01 3.58e-01 -5.57e+00 2.84e+00 9.26e+01 2.10e+03 212s AGE DEP RACE SCHOOL 212s HRS -3.33e+01 4.50e+00 -1.30e+03 3.01e+01 212s RATE -6.55e-02 -4.01e-02 -6.06e+00 3.58e-01 212s ERSP 8.33e+01 -2.77e+01 1.80e+03 -5.57e+00 212s ERNO 1.50e+00 1.31e+00 1.48e+02 2.84e+00 212s NEIN -3.28e+01 -8.09e+00 -2.58e+03 9.26e+01 212s ASSET -7.55e+02 -1.61e+02 -5.59e+04 2.10e+03 212s AGE 6.57e-01 -1.64e-01 1.13e+01 -2.67e-01 212s DEP -1.64e-01 9.20e-02 2.38e-01 -6.01e-02 212s RACE 1.13e+01 2.38e-01 5.73e+02 -1.67e+01 212s SCHOOL -2.67e-01 -6.01e-02 -1.67e+01 7.95e-01 212s -------------------------------------------------------- 212s airquality 153 4 58 18.316848 212s Best subsample: 212s [1] 2 3 8 10 24 25 28 32 33 35 36 37 38 39 40 41 42 43 46 212s [20] 47 48 49 50 52 54 56 57 58 59 60 66 67 69 71 72 73 76 78 212s [39] 81 82 84 86 87 89 90 91 92 95 97 98 100 101 105 106 108 109 110 212s [58] 111 212s Outliers: 10 212s [1] 8 9 15 18 24 30 48 62 117 148 212s ------------- 212s 212s Call: 212s CovMcd(x = x, nsamp = "deterministic", trace = FALSE) 212s -> Method: Deterministic MCD(alpha=0.5 ==> h=58) 212s 212s Robust Estimate of Location: 212s Ozone Solar.R Wind Temp 212s 40.80 189.37 9.66 78.81 212s 212s Robust Estimate of Covariance: 212s Ozone Solar.R Wind Temp 212s Ozone 935.54 857.76 -56.30 220.48 212s Solar.R 857.76 8507.83 1.36 155.13 212s Wind -56.30 1.36 9.90 -11.61 212s Temp 220.48 155.13 -11.61 84.00 212s -------------------------------------------------------- 212s attitude 30 7 19 24.464288 212s Best subsample: 212s [1] 2 3 4 5 7 8 10 11 12 15 17 19 21 22 23 25 27 28 29 212s Outliers: 8 212s [1] 6 9 13 14 16 18 24 26 212s ------------- 212s 212s Call: 212s CovMcd(x = x, nsamp = "deterministic", trace = FALSE) 212s -> Method: Deterministic MCD(alpha=0.5 ==> h=19) 212s 212s Robust Estimate of Location: 212s rating complaints privileges learning raises critical 212s 64.4 65.2 51.0 55.5 65.9 77.4 212s advance 212s 43.2 212s 212s Robust Estimate of Covariance: 212s rating complaints privileges learning raises critical advance 212s rating 199.95 162.36 115.83 160.44 128.87 -13.55 66.20 212s complaints 162.36 204.84 130.33 170.66 150.19 16.28 96.66 212s privileges 115.83 130.33 181.31 152.63 106.56 4.52 91.44 212s learning 160.44 170.66 152.63 213.06 156.57 9.92 88.31 212s raises 128.87 150.19 106.56 156.57 152.05 23.10 84.00 212s critical -13.55 16.28 4.52 9.92 23.10 80.22 27.15 212s advance 66.20 96.66 91.44 88.31 84.00 27.15 95.51 212s -------------------------------------------------------- 212s attenu 182 5 86 6.593068 212s Best subsample: 212s [1] 41 42 43 44 48 49 51 68 70 72 73 74 75 76 77 82 83 84 85 212s [20] 86 87 88 89 90 91 92 101 102 103 104 106 107 109 110 111 112 113 114 212s [39] 115 116 117 119 120 121 122 124 125 126 127 128 129 130 131 132 133 134 135 212s [58] 136 137 138 139 140 141 144 145 146 147 148 149 150 151 152 153 154 155 156 212s [77] 157 158 159 160 161 162 163 164 165 166 212s Outliers: 49 212s [1] 1 2 4 5 6 7 8 9 10 11 12 13 14 15 16 19 20 21 22 212s [20] 23 24 25 27 28 29 30 31 32 33 40 45 47 59 60 61 64 65 78 212s [39] 82 83 97 98 100 101 102 103 104 105 117 212s ------------- 212s 212s Call: 212s CovMcd(x = x, nsamp = "deterministic", trace = FALSE) 212s -> Method: Deterministic MCD(alpha=0.5 ==> h=86) 212s 212s Robust Estimate of Location: 212s event mag station dist accel 212s 17.122 5.798 63.461 25.015 0.131 212s 212s Robust Estimate of Covariance: 212s event mag station dist accel 212s event 2.98e+01 -1.58e+00 9.49e+01 -8.36e+00 -3.59e-02 212s mag -1.58e+00 4.26e-01 -3.88e+00 3.13e+00 5.30e-03 212s station 9.49e+01 -3.88e+00 1.10e+03 2.60e+01 5.38e-01 212s dist -8.36e+00 3.13e+00 2.60e+01 2.66e+02 -9.23e-01 212s accel -3.59e-02 5.30e-03 5.38e-01 -9.23e-01 7.78e-03 212s -------------------------------------------------------- 212s USJudgeRatings 43 12 28 -47.886937 212s Best subsample: 212s [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 212s [26] 40 41 43 212s Outliers: 14 212s [1] 1 5 7 8 12 13 14 17 20 21 23 31 35 42 212s ------------- 212s 212s Call: 212s CovMcd(x = x, nsamp = "deterministic", trace = FALSE) 212s -> Method: Deterministic MCD(alpha=0.5 ==> h=28) 212s 212s Robust Estimate of Location: 212s CONT INTG DMNR DILG CFMG DECI PREP FAMI ORAL WRIT PHYS RTEN 212s 7.46 8.26 7.88 8.06 7.85 7.92 7.84 7.83 7.67 7.74 8.31 8.03 212s 212s Robust Estimate of Covariance: 212s CONT INTG DMNR DILG CFMG DECI PREP FAMI 212s CONT 0.7363 -0.2916 -0.4193 -0.1943 -0.0555 -0.0690 -0.1703 -0.1727 212s INTG -0.2916 0.4179 0.5511 0.4167 0.3176 0.3102 0.4247 0.4279 212s DMNR -0.4193 0.5511 0.8141 0.5256 0.4092 0.3934 0.5294 0.5094 212s DILG -0.1943 0.4167 0.5256 0.4820 0.3904 0.3819 0.5054 0.5104 212s CFMG -0.0555 0.3176 0.4092 0.3904 0.3595 0.3368 0.4180 0.4206 212s DECI -0.0690 0.3102 0.3934 0.3819 0.3368 0.3310 0.4135 0.4194 212s PREP -0.1703 0.4247 0.5294 0.5054 0.4180 0.4135 0.5647 0.5752 212s FAMI -0.1727 0.4279 0.5094 0.5104 0.4206 0.4194 0.5752 0.6019 212s ORAL -0.2109 0.4453 0.5646 0.5054 0.4200 0.4121 0.5575 0.5735 212s WRIT -0.2033 0.4411 0.5466 0.5087 0.4222 0.4147 0.5592 0.5787 212s PHYS -0.1624 0.2578 0.3163 0.2833 0.2268 0.2362 0.3108 0.3284 212s RTEN -0.2622 0.4872 0.6324 0.5203 0.4145 0.4081 0.5488 0.5595 212s ORAL WRIT PHYS RTEN 212s CONT -0.2109 -0.2033 -0.1624 -0.2622 212s INTG 0.4453 0.4411 0.2578 0.4872 212s DMNR 0.5646 0.5466 0.3163 0.6324 212s DILG 0.5054 0.5087 0.2833 0.5203 212s CFMG 0.4200 0.4222 0.2268 0.4145 212s DECI 0.4121 0.4147 0.2362 0.4081 212s PREP 0.5575 0.5592 0.3108 0.5488 212s FAMI 0.5735 0.5787 0.3284 0.5595 212s ORAL 0.5701 0.5677 0.3283 0.5688 212s WRIT 0.5677 0.5715 0.3268 0.5645 212s PHYS 0.3283 0.3268 0.2302 0.3308 212s RTEN 0.5688 0.5645 0.3308 0.6057 212s -------------------------------------------------------- 212s USArrests 50 4 27 15.438912 212s Best subsample: 212s [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 212s [26] 49 50 212s Outliers: 7 212s [1] 2 5 6 10 24 28 33 212s ------------- 212s 212s Call: 212s CovMcd(x = x, nsamp = "deterministic", trace = FALSE) 212s -> Method: Deterministic MCD(alpha=0.5 ==> h=27) 212s 212s Robust Estimate of Location: 212s Murder Assault UrbanPop Rape 212s 6.91 150.10 65.88 18.75 212s 212s Robust Estimate of Covariance: 212s Murder Assault UrbanPop Rape 212s Murder 17.9 285.4 17.6 25.0 212s Assault 285.4 6572.8 524.9 465.0 212s UrbanPop 17.6 524.9 211.9 50.5 212s Rape 25.0 465.0 50.5 56.4 212s -------------------------------------------------------- 212s longley 16 7 12 12.747678 212s Best subsample: 212s [1] 5 6 7 8 9 10 11 12 13 14 15 16 212s Outliers: 4 212s [1] 1 2 3 4 212s ------------- 212s 212s Call: 212s CovMcd(x = x, nsamp = "deterministic", trace = FALSE) 212s -> Method: Deterministic MCD(alpha=0.5 ==> h=12) 212s 212s Robust Estimate of Location: 212s GNP.deflator GNP Unemployed Armed.Forces Population 212s 106.5 430.6 328.2 295.0 120.2 212s Year Employed 212s 1956.5 66.9 212s 212s Robust Estimate of Covariance: 212s GNP.deflator GNP Unemployed Armed.Forces Population 212s GNP.deflator 108.5 1039.9 1231.9 -465.6 81.4 212s GNP 1039.9 10300.0 11161.6 -4277.6 803.4 212s Unemployed 1231.9 11161.6 19799.4 -5805.6 929.1 212s Armed.Forces -465.6 -4277.6 -5805.6 2805.5 -327.4 212s Population 81.4 803.4 929.1 -327.4 63.5 212s Year 51.6 504.3 595.6 -216.7 39.7 212s Employed 34.2 344.1 323.6 -149.5 26.2 212s Year Employed 212s GNP.deflator 51.6 34.2 212s GNP 504.3 344.1 212s Unemployed 595.6 323.6 212s Armed.Forces -216.7 -149.5 212s Population 39.7 26.2 212s Year 25.1 16.7 212s Employed 16.7 12.4 212s -------------------------------------------------------- 212s Loblolly 84 3 44 4.898174 212s Best subsample: 212s [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 212s [26] 46 49 50 51 55 56 58 61 62 64 67 68 69 73 74 75 79 80 81 212s Outliers: 31 212s [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 212s [26] 72 76 77 78 83 84 212s ------------- 212s 212s Call: 212s CovMcd(x = x, nsamp = "deterministic", trace = FALSE) 212s -> Method: Deterministic MCD(alpha=0.5 ==> h=44) 212s 212s Robust Estimate of Location: 212s height age Seed 212s 20.44 8.19 7.72 212s 212s Robust Estimate of Covariance: 212s height age Seed 212s height 247.8 79.5 11.9 212s age 79.5 25.7 3.0 212s Seed 11.9 3.0 17.1 212s -------------------------------------------------------- 212s quakes 1000 4 502 8.274209 212s Best subsample: 212s Too long... 212s Outliers: 266 212s Too many to print ... 212s ------------- 212s 212s Call: 212s CovMcd(x = x, nsamp = "deterministic", trace = FALSE) 212s -> Method: Deterministic MCD(alpha=0.5 ==> h=502) 212s 212s Robust Estimate of Location: 212s lat long depth mag 212s -21.34 182.47 360.58 4.54 212s 212s Robust Estimate of Covariance: 212s lat long depth mag 212s lat 1.50e+01 3.58e+00 1.37e+02 -2.66e-01 212s long 3.58e+00 4.55e+00 -3.61e+02 4.64e-02 212s depth 1.37e+02 -3.61e+02 4.84e+04 -1.36e+01 212s mag -2.66e-01 4.64e-02 -1.36e+01 1.34e-01 212s -------------------------------------------------------- 212s ======================================================== 212s > dodata(method="exact") 212s 212s Call: dodata(method = "exact") 212s Data Set n p Half LOG(obj) Time 212s ======================================================== 212s heart 12 2 7 5.678742 212s Best subsample: 212s [1] 1 3 4 5 7 9 11 212s Outliers: 0 212s Too many to print ... 212s ------------- 212s 212s Call: 212s CovMcd(x = x, nsamp = "exact", trace = FALSE) 212s -> Method: Fast MCD(alpha=0.5 ==> h=7); nsamp = exact; (n,k)mini = (300,5) 212s 212s Robust Estimate of Location: 212s height weight 212s 38.3 33.1 212s 212s Robust Estimate of Covariance: 212s height weight 212s height 135 259 212s weight 259 564 212s -------------------------------------------------------- 212s starsCYG 47 2 25 -8.031215 212s Best subsample: 212s [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 212s Outliers: 7 212s [1] 7 9 11 14 20 30 34 212s ------------- 212s 212s Call: 212s CovMcd(x = x, nsamp = "exact", trace = FALSE) 212s -> Method: Fast MCD(alpha=0.5 ==> h=25); nsamp = exact; (n,k)mini = (300,5) 212s 212s Robust Estimate of Location: 212s log.Te log.light 212s 4.41 4.95 212s 212s Robust Estimate of Covariance: 212s log.Te log.light 212s log.Te 0.0132 0.0394 212s log.light 0.0394 0.2743 212s -------------------------------------------------------- 212s phosphor 18 2 10 6.878847 212s Best subsample: 212s [1] 3 5 8 9 11 12 13 14 15 17 212s Outliers: 3 212s [1] 1 6 10 212s ------------- 212s 212s Call: 212s CovMcd(x = x, nsamp = "exact", trace = FALSE) 212s -> Method: Fast MCD(alpha=0.5 ==> h=10); nsamp = exact; (n,k)mini = (300,5) 212s 212s Robust Estimate of Location: 212s inorg organic 212s 13.4 38.8 212s 212s Robust Estimate of Covariance: 212s inorg organic 212s inorg 129 130 212s organic 130 182 212s -------------------------------------------------------- 212s coleman 20 5 13 1.286808 212s Best subsample: 212s [1] 2 3 4 5 7 8 12 13 14 16 17 19 20 212s Outliers: 7 212s [1] 1 6 9 10 11 15 18 212s ------------- 212s 212s Call: 212s CovMcd(x = x, nsamp = "exact", trace = FALSE) 212s -> Method: Fast MCD(alpha=0.5 ==> h=13); nsamp = exact; (n,k)mini = (300,5) 212s 212s Robust Estimate of Location: 212s salaryP fatherWc sstatus teacherSc motherLev 212s 2.76 48.38 6.12 25.00 6.40 212s 212s Robust Estimate of Covariance: 212s salaryP fatherWc sstatus teacherSc motherLev 212s salaryP 0.253 1.786 -0.266 0.151 0.075 212s fatherWc 1.786 1303.382 330.496 12.604 34.503 212s sstatus -0.266 330.496 119.888 3.833 10.131 212s teacherSc 0.151 12.604 3.833 0.785 0.555 212s motherLev 0.075 34.503 10.131 0.555 1.043 212s -------------------------------------------------------- 213s salinity 28 3 16 1.326364 213s Best subsample: 213s [1] 1 2 6 7 8 12 13 14 18 20 21 22 25 26 27 28 213s Outliers: 4 213s [1] 5 16 23 24 213s ------------- 213s 213s Call: 213s CovMcd(x = x, nsamp = "exact", trace = FALSE) 213s -> Method: Fast MCD(alpha=0.5 ==> h=16); nsamp = exact; (n,k)mini = (300,5) 213s 213s Robust Estimate of Location: 213s X1 X2 X3 213s 10.08 2.78 22.78 213s 213s Robust Estimate of Covariance: 213s X1 X2 X3 213s X1 10.44 1.01 -3.19 213s X2 1.01 3.83 -1.44 213s X3 -3.19 -1.44 2.39 213s -------------------------------------------------------- 213s wood 20 5 13 -36.270094 213s Best subsample: 213s [1] 1 2 3 5 9 10 12 13 14 15 17 18 20 213s Outliers: 7 213s [1] 4 6 7 8 11 16 19 213s ------------- 213s 213s Call: 213s CovMcd(x = x, nsamp = "exact", trace = FALSE) 213s -> Method: Fast MCD(alpha=0.5 ==> h=13); nsamp = exact; (n,k)mini = (300,5) 213s 213s Robust Estimate of Location: 213s x1 x2 x3 x4 x5 213s 0.587 0.122 0.531 0.538 0.892 213s 213s Robust Estimate of Covariance: 213s x1 x2 x3 x4 x5 213s x1 1.00e-02 1.88e-03 3.15e-03 -5.86e-04 -1.63e-03 213s x2 1.88e-03 4.85e-04 1.27e-03 -5.20e-05 2.36e-05 213s x3 3.15e-03 1.27e-03 6.63e-03 -8.71e-04 3.52e-04 213s x4 -5.86e-04 -5.20e-05 -8.71e-04 2.85e-03 1.83e-03 213s x5 -1.63e-03 2.36e-05 3.52e-04 1.83e-03 2.77e-03 213s -------------------------------------------------------- 213s Animals 28 2 15 14.555543 213s Best subsample: 213s [1] 1 3 4 5 10 11 17 18 19 20 21 22 23 26 27 213s Outliers: 14 213s [1] 2 6 7 8 9 12 13 14 15 16 23 24 25 28 213s ------------- 213s 213s Call: 213s CovMcd(x = x, nsamp = "exact", trace = FALSE) 213s -> Method: Fast MCD(alpha=0.5 ==> h=15); nsamp = exact; (n,k)mini = (300,5) 213s 213s Robust Estimate of Location: 213s body brain 213s 18.7 64.9 213s 213s Robust Estimate of Covariance: 213s body brain 213s body 929 1576 213s brain 1576 5646 213s -------------------------------------------------------- 213s lactic 20 2 11 0.359580 213s Best subsample: 213s [1] 1 2 3 4 5 7 8 9 10 11 12 213s Outliers: 4 213s [1] 17 18 19 20 213s ------------- 213s 213s Call: 213s CovMcd(x = x, nsamp = "exact", trace = FALSE) 213s -> Method: Fast MCD(alpha=0.5 ==> h=11); nsamp = exact; (n,k)mini = (300,5) 213s 213s Robust Estimate of Location: 213s X Y 213s 3.86 5.01 213s 213s Robust Estimate of Covariance: 213s X Y 213s X 10.6 14.6 213s Y 14.6 21.3 213s -------------------------------------------------------- 213s pension 18 2 10 16.675508 213s Best subsample: 213s [1] 1 2 3 4 5 6 8 9 11 12 213s Outliers: 5 213s [1] 14 15 16 17 18 213s ------------- 213s 213s Call: 213s CovMcd(x = x, nsamp = "exact", trace = FALSE) 213s -> Method: Fast MCD(alpha=0.5 ==> h=10); nsamp = exact; (n,k)mini = (300,5) 213s 213s Robust Estimate of Location: 213s Income Reserves 213s 52.3 560.9 213s 213s Robust Estimate of Covariance: 213s Income Reserves 213s Income 1420 11932 213s Reserves 11932 208643 213s -------------------------------------------------------- 213s vaso 39 2 21 -3.972244 213s Best subsample: 213s [1] 3 4 8 14 18 19 20 21 22 23 24 25 26 27 28 33 34 35 37 38 39 213s Outliers: 4 213s [1] 1 2 17 31 213s ------------- 213s 213s Call: 213s CovMcd(x = x, nsamp = "exact", trace = FALSE) 213s -> Method: Fast MCD(alpha=0.5 ==> h=21); nsamp = exact; (n,k)mini = (300,5) 213s 213s Robust Estimate of Location: 213s Volume Rate 213s 1.16 1.72 213s 213s Robust Estimate of Covariance: 213s Volume Rate 213s Volume 0.313 -0.167 213s Rate -0.167 0.728 213s -------------------------------------------------------- 213s stackloss 21 3 12 5.472581 213s Best subsample: 213s [1] 4 5 6 7 8 9 10 11 12 13 14 20 213s Outliers: 9 213s [1] 1 2 3 15 16 17 18 19 21 213s ------------- 213s 213s Call: 213s CovMcd(x = x, nsamp = "exact", trace = FALSE) 213s -> Method: Fast MCD(alpha=0.5 ==> h=12); nsamp = exact; (n,k)mini = (300,5) 213s 213s Robust Estimate of Location: 213s Air.Flow Water.Temp Acid.Conc. 213s 59.5 20.8 87.3 213s 213s Robust Estimate of Covariance: 213s Air.Flow Water.Temp Acid.Conc. 213s Air.Flow 6.29 5.85 5.74 213s Water.Temp 5.85 9.23 6.14 213s Acid.Conc. 5.74 6.14 23.25 213s -------------------------------------------------------- 213s pilot 20 2 11 6.487287 213s Best subsample: 213s [1] 2 3 6 7 9 12 15 16 17 18 20 213s Outliers: 0 213s Too many to print ... 213s ------------- 213s 213s Call: 213s CovMcd(x = x, nsamp = "exact", trace = FALSE) 213s -> Method: Fast MCD(alpha=0.5 ==> h=11); nsamp = exact; (n,k)mini = (300,5) 213s 213s Robust Estimate of Location: 213s X Y 213s 101.1 67.7 213s 213s Robust Estimate of Covariance: 213s X Y 213s X 3344 1070 213s Y 1070 343 213s -------------------------------------------------------- 213s ======================================================== 213s > dodata(method="MRCD") 213s 213s Call: dodata(method = "MRCD") 213s Data Set n p Half LOG(obj) Time 213s ======================================================== 213s heart 12 2 6 7.446266 213s Best subsample: 213s [1] 1 3 4 7 9 11 213s Outliers: 0 213s Too many to print ... 213s ------------- 213s 213s Call: 213s CovMrcd(x = x, trace = FALSE) 213s -> Method: Minimum Regularized Covariance Determinant MRCD(alpha=0.5 ==> h=6) 213s 213s Robust Estimate of Location: 213s height weight 213s 38.8 33.0 213s 213s Robust Estimate of Covariance: 213s height weight 213s height 47.4 75.2 213s weight 75.2 155.4 213s -------------------------------------------------------- 213s starsCYG 47 2 24 -5.862050 213s Best subsample: 213s [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 213s Outliers: 0 213s Too many to print ... 213s ------------- 213s 213s Call: 213s CovMrcd(x = x, trace = FALSE) 213s -> Method: Minimum Regularized Covariance Determinant MRCD(alpha=0.5 ==> h=24) 213s 213s Robust Estimate of Location: 213s log.Te log.light 213s 4.44 5.05 213s 213s Robust Estimate of Covariance: 213s log.Te log.light 213s log.Te 0.00867 0.02686 213s log.light 0.02686 0.41127 213s -------------------------------------------------------- 213s phosphor 18 2 9 9.954788 213s Best subsample: 213s [1] 4 7 8 9 11 12 13 14 16 213s Outliers: 0 213s Too many to print ... 213s ------------- 213s 213s Call: 213s CovMrcd(x = x, trace = FALSE) 213s -> Method: Minimum Regularized Covariance Determinant MRCD(alpha=0.5 ==> h=9) 213s 213s Robust Estimate of Location: 213s inorg organic 213s 12.5 39.0 213s 213s Robust Estimate of Covariance: 213s inorg organic 213s inorg 236 140 213s organic 140 172 213s -------------------------------------------------------- 213s stackloss 21 3 11 7.991165 213s Best subsample: 213s [1] 4 5 6 7 8 9 10 13 18 19 20 213s Outliers: 0 213s Too many to print ... 213s ------------- 213s 213s Call: 213s CovMrcd(x = x, trace = FALSE) 213s -> Method: Minimum Regularized Covariance Determinant MRCD(alpha=0.5 ==> h=11) 213s 213s Robust Estimate of Location: 213s Air.Flow Water.Temp Acid.Conc. 213s 58.2 21.4 85.2 213s 213s Robust Estimate of Covariance: 213s Air.Flow Water.Temp Acid.Conc. 213s Air.Flow 49.8 17.2 42.7 213s Water.Temp 17.2 13.8 25.2 213s Acid.Conc. 42.7 25.2 58.2 213s -------------------------------------------------------- 213s coleman 20 5 10 5.212156 213s Best subsample: 213s [1] 3 4 5 7 8 9 14 16 19 20 213s Outliers: 0 213s Too many to print ... 213s ------------- 213s 213s Call: 213s CovMrcd(x = x, trace = FALSE) 213s -> Method: Minimum Regularized Covariance Determinant MRCD(alpha=0.5 ==> h=10) 213s 213s Robust Estimate of Location: 213s salaryP fatherWc sstatus teacherSc motherLev 213s 2.78 59.44 9.28 25.41 6.70 213s 213s Robust Estimate of Covariance: 213s salaryP fatherWc sstatus teacherSc motherLev 213s salaryP 0.1582 -0.2826 0.4112 0.1754 0.0153 213s fatherWc -0.2826 902.9210 201.5815 -2.1236 18.8736 213s sstatus 0.4112 201.5815 65.4580 -0.3876 4.7794 213s teacherSc 0.1754 -2.1236 -0.3876 0.7233 -0.0322 213s motherLev 0.0153 18.8736 4.7794 -0.0322 0.5417 213s -------------------------------------------------------- 213s salinity 28 3 14 3.586919 213s Best subsample: 213s [1] 1 7 8 12 13 14 18 20 21 22 25 26 27 28 213s Outliers: 0 213s Too many to print ... 213s ------------- 213s 213s Call: 213s CovMrcd(x = x, trace = FALSE) 213s -> Method: Minimum Regularized Covariance Determinant MRCD(alpha=0.5 ==> h=14) 213s 213s Robust Estimate of Location: 213s X1 X2 X3 213s 10.95 3.71 21.99 213s 213s Robust Estimate of Covariance: 213s X1 X2 X3 213s X1 14.153 0.718 -3.359 213s X2 0.718 3.565 -0.722 213s X3 -3.359 -0.722 1.607 213s -------------------------------------------------------- 213s wood 20 5 10 -33.100492 213s Best subsample: 213s [1] 1 2 3 5 11 14 15 17 18 20 213s Outliers: 0 213s Too many to print ... 213s ------------- 213s 213s Call: 213s CovMrcd(x = x, trace = FALSE) 213s -> Method: Minimum Regularized Covariance Determinant MRCD(alpha=0.5 ==> h=10) 213s 213s Robust Estimate of Location: 213s x1 x2 x3 x4 x5 213s 0.572 0.120 0.504 0.545 0.899 213s 213s Robust Estimate of Covariance: 213s x1 x2 x3 x4 x5 213s x1 0.007543 0.001720 0.000412 -0.001230 -0.001222 213s x2 0.001720 0.000568 0.000355 -0.000533 -0.000132 213s x3 0.000412 0.000355 0.002478 0.000190 0.000811 213s x4 -0.001230 -0.000533 0.000190 0.002327 0.000967 213s x5 -0.001222 -0.000132 0.000811 0.000967 0.001894 213s -------------------------------------------------------- 213s hbk 75 3 38 1.539545 213s Best subsample: 213s [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 213s [26] 55 56 58 59 63 64 66 67 70 71 72 73 74 213s Outliers: 0 213s Too many to print ... 213s ------------- 213s 213s Call: 213s CovMrcd(x = x, trace = FALSE) 213s -> Method: Minimum Regularized Covariance Determinant MRCD(alpha=0.5 ==> h=38) 213s 213s Robust Estimate of Location: 213s X1 X2 X3 213s 1.60 2.37 1.64 213s 213s Robust Estimate of Covariance: 213s X1 X2 X3 213s X1 2.810 0.124 1.248 213s X2 0.124 1.017 0.208 213s X3 1.248 0.208 2.218 213s -------------------------------------------------------- 213s Animals 28 2 14 16.278395 213s Best subsample: 213s [1] 1 3 4 5 10 11 18 19 20 21 22 23 26 27 213s Outliers: 0 213s Too many to print ... 213s ------------- 213s 213s Call: 213s CovMrcd(x = x, trace = FALSE) 213s -> Method: Minimum Regularized Covariance Determinant MRCD(alpha=0.5 ==> h=14) 213s 213s Robust Estimate of Location: 213s body brain 213s 19.5 56.8 213s 213s Robust Estimate of Covariance: 213s body brain 213s body 2802 5179 213s brain 5179 13761 213s -------------------------------------------------------- 213s bushfire 38 5 19 28.483413 213s Best subsample: 213s [1] 1 2 3 4 5 14 15 16 17 18 19 20 21 22 23 24 25 26 27 213s Outliers: 0 213s Too many to print ... 213s ------------- 213s 213s Call: 213s CovMrcd(x = x, trace = FALSE) 213s -> Method: Minimum Regularized Covariance Determinant MRCD(alpha=0.5 ==> h=19) 213s 213s Robust Estimate of Location: 213s V1 V2 V3 V4 V5 213s 103 145 287 221 281 213s 213s Robust Estimate of Covariance: 213s V1 V2 V3 V4 V5 213s V1 366 249 -1993 -503 -396 213s V2 249 252 -1223 -291 -233 213s V3 -1993 -1223 14246 3479 2718 213s V4 -503 -291 3479 1083 748 213s V5 -396 -233 2718 748 660 213s -------------------------------------------------------- 213s lactic 20 2 10 2.593141 213s Best subsample: 213s [1] 1 2 3 4 5 7 8 9 10 11 213s Outliers: 0 213s Too many to print ... 213s ------------- 213s 213s Call: 213s CovMrcd(x = x, trace = FALSE) 213s -> Method: Minimum Regularized Covariance Determinant MRCD(alpha=0.5 ==> h=10) 213s 213s Robust Estimate of Location: 213s X Y 213s 2.60 3.63 213s 213s Robust Estimate of Covariance: 213s X Y 213s X 8.13 13.54 213s Y 13.54 24.17 213s -------------------------------------------------------- 213s pension 18 2 9 18.931204 213s Best subsample: 213s [1] 2 3 4 5 6 8 9 11 12 213s Outliers: 0 213s Too many to print ... 213s ------------- 213s 213s Call: 213s CovMrcd(x = x, trace = FALSE) 213s -> Method: Minimum Regularized Covariance Determinant MRCD(alpha=0.5 ==> h=9) 213s 213s Robust Estimate of Location: 213s Income Reserves 213s 45.7 466.9 213s 213s Robust Estimate of Covariance: 213s Income Reserves 213s Income 2127 23960 213s Reserves 23960 348275 213s -------------------------------------------------------- 213s vaso 39 2 20 -1.864710 213s Best subsample: 213s [1] 3 4 8 14 18 20 21 22 23 24 25 26 27 28 33 34 35 37 38 39 213s Outliers: 0 213s Too many to print ... 213s ------------- 213s 213s Call: 213s CovMrcd(x = x, trace = FALSE) 213s -> Method: Minimum Regularized Covariance Determinant MRCD(alpha=0.5 ==> h=20) 213s 213s Robust Estimate of Location: 213s Volume Rate 213s 1.14 1.77 213s 213s Robust Estimate of Covariance: 213s Volume Rate 213s Volume 0.44943 -0.00465 213s Rate -0.00465 0.34480 213s -------------------------------------------------------- 213s wagnerGrowth 63 6 32 9.287760 213s Best subsample: 213s [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 213s [26] 53 54 55 56 57 60 62 213s Outliers: 0 213s Too many to print ... 213s ------------- 213s 213s Call: 213s CovMrcd(x = x, trace = FALSE) 213s -> Method: Minimum Regularized Covariance Determinant MRCD(alpha=0.5 ==> h=32) 213s 213s Robust Estimate of Location: 213s Region PA GPA HS GHS y 213s 10.719 33.816 -2.144 2.487 0.293 4.918 213s 213s Robust Estimate of Covariance: 213s Region PA GPA HS GHS y 213s Region 56.7128 17.4919 -2.9710 -0.6491 -0.4545 -10.4287 213s PA 17.4919 29.9968 -7.6846 -1.3141 0.5418 -35.6434 213s GPA -2.9710 -7.6846 6.3238 1.1257 -0.4757 12.4707 213s HS -0.6491 -1.3141 1.1257 1.1330 -0.0915 3.3617 213s GHS -0.4545 0.5418 -0.4757 -0.0915 0.1468 -1.1228 213s y -10.4287 -35.6434 12.4707 3.3617 -1.1228 67.4215 213s -------------------------------------------------------- 213s fish 159 6 79 22.142828 213s Best subsample: 213s [1] 2 3 4 5 6 7 8 9 10 11 12 14 15 16 17 18 19 20 21 213s [20] 22 23 24 25 26 27 35 36 37 42 43 44 45 46 47 48 49 50 51 213s [39] 52 53 54 55 56 57 58 59 60 71 105 106 107 109 110 111 113 114 115 213s [58] 116 117 118 119 120 122 123 124 125 126 127 128 129 130 131 132 134 135 136 213s [77] 137 138 139 213s Outliers: 0 213s Too many to print ... 213s ------------- 213s 213s Call: 213s CovMrcd(x = x, trace = FALSE) 213s -> Method: Minimum Regularized Covariance Determinant MRCD(alpha=0.5 ==> h=79) 213s 213s Robust Estimate of Location: 213s Weight Length1 Length2 Length3 Height Width 213s 291.7 23.8 25.9 28.9 30.4 14.7 213s 213s Robust Estimate of Covariance: 213s Weight Length1 Length2 Length3 Height Width 213s Weight 77155.07 1567.55 1713.74 2213.16 1912.62 -103.97 213s Length1 1567.55 45.66 41.57 52.14 38.66 -2.39 213s Length2 1713.74 41.57 54.26 56.77 42.72 -2.55 213s Length3 2213.16 52.14 56.77 82.57 58.84 -3.65 213s Height 1912.62 38.66 42.72 58.84 70.51 -3.80 213s Width -103.97 -2.39 -2.55 -3.65 -3.80 1.19 213s -------------------------------------------------------- 213s pottery 27 6 14 -6.897459 213s Best subsample: 213s [1] 1 2 4 5 6 10 11 13 14 15 19 21 22 26 213s Outliers: 0 213s Too many to print ... 213s ------------- 213s 213s Call: 213s CovMrcd(x = x, trace = FALSE) 213s -> Method: Minimum Regularized Covariance Determinant MRCD(alpha=0.5 ==> h=14) 213s 213s Robust Estimate of Location: 213s SI AL FE MG CA TI 213s 54.39 14.93 9.78 3.82 5.11 0.86 213s 213s Robust Estimate of Covariance: 213s SI AL FE MG CA TI 213s SI 17.47469 -0.16656 0.39943 4.48192 -0.71153 0.06515 213s AL -0.16656 3.93154 -0.35738 -2.29899 0.14770 -0.02050 213s FE 0.39943 -0.35738 0.20434 0.37562 -0.22460 0.00943 213s MG 4.48192 -2.29899 0.37562 2.82339 -0.16027 0.02943 213s CA -0.71153 0.14770 -0.22460 -0.16027 0.88443 -0.01711 213s TI 0.06515 -0.02050 0.00943 0.02943 -0.01711 0.00114 213s -------------------------------------------------------- 213s rice 105 6 53 -8.916472 213s Best subsample: 213s [1] 4 6 8 10 13 15 16 17 18 25 27 29 30 31 32 33 34 36 37 213s [20] 38 44 45 47 51 52 53 54 55 59 60 65 67 70 72 76 79 80 81 213s [39] 82 83 84 85 86 90 92 93 94 95 97 98 99 101 105 213s Outliers: 0 213s Too many to print ... 213s ------------- 213s 213s Call: 213s CovMrcd(x = x, trace = FALSE) 213s -> Method: Minimum Regularized Covariance Determinant MRCD(alpha=0.5 ==> h=53) 213s 213s Robust Estimate of Location: 213s Favor Appearance Taste Stickiness 213s -0.1741 0.0774 -0.0472 0.1868 213s Toughness Overall_evaluation 213s -0.0346 -0.0683 213s 213s Robust Estimate of Covariance: 213s Favor Appearance Taste Stickiness Toughness 213s Favor 0.402 0.306 0.378 0.364 -0.134 213s Appearance 0.306 0.508 0.474 0.407 -0.146 213s Taste 0.378 0.474 0.708 0.611 -0.258 213s Stickiness 0.364 0.407 0.611 0.795 -0.320 213s Toughness -0.134 -0.146 -0.258 -0.320 0.302 213s Overall_evaluation 0.453 0.536 0.746 0.745 -0.327 213s Overall_evaluation 213s Favor 0.453 213s Appearance 0.536 213s Taste 0.746 213s Stickiness 0.745 213s Toughness -0.327 213s Overall_evaluation 0.963 213s -------------------------------------------------------- 213s un86 73 7 37 19.832993 213s Best subsample: 213s [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 213s [26] 56 57 60 62 63 64 65 67 70 71 72 73 213s Outliers: 0 213s Too many to print ... 213s ------------- 213s 213s Call: 213s CovMrcd(x = x, trace = FALSE) 213s -> Method: Minimum Regularized Covariance Determinant MRCD(alpha=0.5 ==> h=37) 213s 213s Robust Estimate of Location: 213s POP MOR CAR DR GNP DEN TB 213s 14.462 66.892 6.670 0.858 1.251 55.518 0.429 213s 213s Robust Estimate of Covariance: 213s POP MOR CAR DR GNP DEN 213s POP 3.00e+02 1.58e+02 9.83e+00 2.74e+00 5.51e-01 6.87e+01 213s MOR 1.58e+02 2.96e+03 -4.24e+02 -4.72e+01 -5.40e+01 -1.01e+03 213s CAR 9.83e+00 -4.24e+02 9.12e+01 8.71e+00 1.13e+01 1.96e+02 213s DR 2.74e+00 -4.72e+01 8.71e+00 1.25e+00 1.03e+00 2.74e+01 213s GNP 5.51e-01 -5.40e+01 1.13e+01 1.03e+00 2.31e+00 2.36e+01 213s DEN 6.87e+01 -1.01e+03 1.96e+02 2.74e+01 2.36e+01 3.12e+03 213s TB 2.04e-02 -1.81e+00 3.42e-01 2.57e-02 2.09e-02 -6.88e-01 213s TB 213s POP 2.04e-02 213s MOR -1.81e+00 213s CAR 3.42e-01 213s DR 2.57e-02 213s GNP 2.09e-02 213s DEN -6.88e-01 213s TB 2.59e-02 213s -------------------------------------------------------- 213s wages 39 10 14 35.698016 213s Best subsample: 213s [1] 1 2 5 6 9 10 11 13 15 19 23 25 26 28 213s Outliers: 0 213s Too many to print ... 213s ------------- 213s 213s Call: 213s CovMrcd(x = x, trace = FALSE) 213s -> Method: Minimum Regularized Covariance Determinant MRCD(alpha=0.5 ==> h=14) 213s 213s Robust Estimate of Location: 213s HRS RATE ERSP ERNO NEIN ASSET AGE DEP 213s 2167.71 2.96 1113.50 300.43 382.29 7438.00 39.06 2.41 213s RACE SCHOOL 213s 33.00 10.45 213s 213s Robust Estimate of Covariance: 213s HRS RATE ERSP ERNO NEIN ASSET 213s HRS 1.97e+03 -4.14e-01 -4.71e+03 -6.58e+02 1.81e+03 3.84e+04 213s RATE -4.14e-01 1.14e-01 1.79e+01 3.08e+00 1.40e+01 3.57e+02 213s ERSP -4.71e+03 1.79e+01 1.87e+04 2.33e+03 -2.06e+03 -3.57e+04 213s ERNO -6.58e+02 3.08e+00 2.33e+03 5.36e+02 -3.42e+02 -5.56e+03 213s NEIN 1.81e+03 1.40e+01 -2.06e+03 -3.42e+02 5.77e+03 1.10e+05 213s ASSET 3.84e+04 3.57e+02 -3.57e+04 -5.56e+03 1.10e+05 2.86e+06 213s AGE -1.83e+01 1.09e-02 6.69e+01 8.78e+00 -5.07e+00 -1.51e+02 213s DEP 4.82e+00 -3.14e-02 -2.52e+01 -2.96e+00 -5.33e+00 -1.03e+02 213s RACE -5.67e+02 -1.33e+00 1.21e+03 1.81e+02 -9.13e+02 -1.96e+04 213s SCHOOL 5.33e+00 1.87e-01 1.86e+01 3.12e+00 3.20e+01 7.89e+02 213s AGE DEP RACE SCHOOL 213s HRS -1.83e+01 4.82e+00 -5.67e+02 5.33e+00 213s RATE 1.09e-02 -3.14e-02 -1.33e+00 1.87e-01 213s ERSP 6.69e+01 -2.52e+01 1.21e+03 1.86e+01 213s ERNO 8.78e+00 -2.96e+00 1.81e+02 3.12e+00 213s NEIN -5.07e+00 -5.33e+00 -9.13e+02 3.20e+01 213s ASSET -1.51e+02 -1.03e+02 -1.96e+04 7.89e+02 213s AGE 5.71e-01 -1.56e-01 4.58e+00 -5.00e-02 213s DEP -1.56e-01 8.08e-02 -3.02e-01 -4.47e-02 213s RACE 4.58e+00 -3.02e-01 2.36e+02 -4.54e+00 213s SCHOOL -5.00e-02 -4.47e-02 -4.54e+00 4.23e-01 213s -------------------------------------------------------- 213s airquality 153 4 56 21.136376 213s Best subsample: 213s [1] 2 3 8 10 24 25 28 32 33 35 36 37 38 39 40 41 42 43 46 213s [20] 47 48 49 52 54 56 57 58 59 60 66 67 69 71 72 73 76 78 81 213s [39] 82 84 86 87 89 90 91 92 96 97 98 100 101 105 106 109 110 111 213s Outliers: 0 213s Too many to print ... 213s ------------- 213s 213s Call: 213s CovMrcd(x = x, trace = FALSE) 213s -> Method: Minimum Regularized Covariance Determinant MRCD(alpha=0.5 ==> h=56) 213s 213s Robust Estimate of Location: 213s Ozone Solar.R Wind Temp 213s 41.84 197.21 8.93 80.39 213s 213s Robust Estimate of Covariance: 213s Ozone Solar.R Wind Temp 213s Ozone 1480.7 1562.8 -99.9 347.3 213s Solar.R 1562.8 11401.2 -35.2 276.8 213s Wind -99.9 -35.2 11.4 -23.5 213s Temp 347.3 276.8 -23.5 107.7 213s -------------------------------------------------------- 213s attitude 30 7 15 27.040805 213s Best subsample: 213s [1] 2 3 4 5 7 8 10 12 15 19 22 23 25 27 28 213s Outliers: 0 213s Too many to print ... 213s ------------- 213s 213s Call: 213s CovMrcd(x = x, trace = FALSE) 213s -> Method: Minimum Regularized Covariance Determinant MRCD(alpha=0.5 ==> h=15) 213s 213s Robust Estimate of Location: 213s rating complaints privileges learning raises critical 213s 65.8 66.5 50.1 56.1 66.7 78.1 213s advance 213s 41.7 213s 213s Robust Estimate of Covariance: 213s rating complaints privileges learning raises critical advance 213s rating 138.77 80.02 59.22 107.33 95.83 -1.24 54.36 213s complaints 80.02 97.23 50.59 99.50 79.15 -2.71 42.81 213s privileges 59.22 50.59 84.92 90.03 60.88 22.39 44.93 213s learning 107.33 99.50 90.03 187.67 128.71 15.48 63.67 213s raises 95.83 79.15 60.88 128.71 123.94 -1.46 49.98 213s critical -1.24 -2.71 22.39 15.48 -1.46 61.23 12.88 213s advance 54.36 42.81 44.93 63.67 49.98 12.88 48.61 213s -------------------------------------------------------- 213s attenu 182 5 83 9.710111 213s Best subsample: 213s [1] 41 42 43 44 48 49 51 68 70 72 73 74 75 76 77 82 83 84 85 213s [20] 86 87 88 89 90 91 92 101 102 103 104 106 107 109 110 111 112 113 114 213s [39] 115 116 117 121 122 124 125 126 127 128 129 130 131 132 133 134 135 136 137 213s [58] 138 139 140 141 144 145 146 147 148 149 150 151 152 153 155 156 157 158 159 213s [77] 160 161 162 163 164 165 166 213s Outliers: 0 213s Too many to print ... 213s ------------- 213s 213s Call: 213s CovMrcd(x = x, trace = FALSE) 213s -> Method: Minimum Regularized Covariance Determinant MRCD(alpha=0.5 ==> h=83) 213s 213s Robust Estimate of Location: 213s event mag station dist accel 213s 18.940 5.741 67.988 23.365 0.124 213s 213s Robust Estimate of Covariance: 213s event mag station dist accel 213s event 2.86e+01 -2.31e+00 1.02e+02 2.68e+01 -1.99e-01 213s mag -2.31e+00 6.17e-01 -7.03e+00 4.67e-01 2.59e-02 213s station 1.02e+02 -7.03e+00 1.66e+03 1.62e+02 7.96e-02 213s dist 2.68e+01 4.67e-01 1.62e+02 3.61e+02 -1.23e+00 213s accel -1.99e-01 2.59e-02 7.96e-02 -1.23e+00 9.42e-03 213s -------------------------------------------------------- 213s USJudgeRatings 43 12 22 -23.463708 213s Best subsample: 213s [1] 2 3 4 6 9 11 15 16 18 19 24 25 26 27 28 29 32 33 34 36 37 38 213s Outliers: 0 213s Too many to print ... 213s ------------- 213s 213s Call: 213s CovMrcd(x = x, trace = FALSE) 213s -> Method: Minimum Regularized Covariance Determinant MRCD(alpha=0.5 ==> h=22) 213s 213s Robust Estimate of Location: 213s CONT INTG DMNR DILG CFMG DECI PREP FAMI ORAL WRIT PHYS RTEN 213s 7.24 8.42 8.10 8.19 7.95 8.00 7.96 7.96 7.81 7.89 8.40 8.20 213s 213s Robust Estimate of Covariance: 213s CONT INTG DMNR DILG CFMG DECI PREP 213s CONT 0.61805 -0.05601 -0.09540 0.00694 0.09853 0.06261 0.03939 213s INTG -0.05601 0.23560 0.27537 0.20758 0.16603 0.17281 0.21128 213s DMNR -0.09540 0.27537 0.55349 0.28872 0.24014 0.24293 0.28886 213s DILG 0.00694 0.20758 0.28872 0.34099 0.23502 0.23917 0.29672 213s CFMG 0.09853 0.16603 0.24014 0.23502 0.31649 0.23291 0.27651 213s DECI 0.06261 0.17281 0.24293 0.23917 0.23291 0.30681 0.27737 213s PREP 0.03939 0.21128 0.28886 0.29672 0.27651 0.27737 0.42020 213s FAMI 0.04588 0.20388 0.26072 0.29037 0.27179 0.27737 0.34857 213s ORAL 0.03000 0.21379 0.29606 0.28764 0.27338 0.27424 0.33503 213s WRIT 0.03261 0.20258 0.26931 0.27962 0.26382 0.26610 0.32677 213s PHYS -0.04485 0.13598 0.17659 0.16834 0.14554 0.16467 0.18948 213s RTEN 0.01543 0.22654 0.32117 0.27307 0.23826 0.24669 0.29450 213s FAMI ORAL WRIT PHYS RTEN 213s CONT 0.04588 0.03000 0.03261 -0.04485 0.01543 213s INTG 0.20388 0.21379 0.20258 0.13598 0.22654 213s DMNR 0.26072 0.29606 0.26931 0.17659 0.32117 213s DILG 0.29037 0.28764 0.27962 0.16834 0.27307 213s CFMG 0.27179 0.27338 0.26382 0.14554 0.23826 213s DECI 0.27737 0.27424 0.26610 0.16467 0.24669 213s PREP 0.34857 0.33503 0.32677 0.18948 0.29450 213s FAMI 0.47232 0.33762 0.33420 0.19759 0.29015 213s ORAL 0.33762 0.40361 0.32208 0.19794 0.29544 213s WRIT 0.33420 0.32208 0.38733 0.19276 0.28184 213s PHYS 0.19759 0.19794 0.19276 0.20284 0.18097 213s RTEN 0.29015 0.29544 0.28184 0.18097 0.36877 213s -------------------------------------------------------- 213s USArrests 50 4 25 17.834643 213s Best subsample: 213s [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 213s Outliers: 0 213s Too many to print ... 213s ------------- 213s 213s Call: 213s CovMrcd(x = x, trace = FALSE) 213s -> Method: Minimum Regularized Covariance Determinant MRCD(alpha=0.5 ==> h=25) 213s 213s Robust Estimate of Location: 213s Murder Assault UrbanPop Rape 213s 5.38 121.68 63.80 16.33 213s 213s Robust Estimate of Covariance: 213s Murder Assault UrbanPop Rape 213s Murder 17.8 316.3 48.5 31.1 213s Assault 316.3 6863.0 1040.0 548.9 213s UrbanPop 48.5 1040.0 424.8 93.6 213s Rape 31.1 548.9 93.6 63.8 213s -------------------------------------------------------- 213s longley 16 7 8 31.147844 213s Best subsample: 213s [1] 5 6 7 9 10 11 13 14 213s Outliers: 0 213s Too many to print ... 213s ------------- 213s 213s Call: 213s CovMrcd(x = x, trace = FALSE) 213s -> Method: Minimum Regularized Covariance Determinant MRCD(alpha=0.5 ==> h=8) 213s 213s Robust Estimate of Location: 213s GNP.deflator GNP Unemployed Armed.Forces Population 213s 104.3 410.8 278.8 300.1 118.2 213s Year Employed 213s 1955.4 66.5 213s 213s Robust Estimate of Covariance: 213s GNP.deflator GNP Unemployed Armed.Forces Population 213s GNP.deflator 85.0 652.3 784.4 -370.7 48.7 213s GNP 652.3 7502.9 7328.6 -3414.2 453.9 213s Unemployed 784.4 7328.6 10760.3 -4646.7 548.1 213s Armed.Forces -370.7 -3414.2 -4646.7 2824.3 -253.9 213s Population 48.7 453.9 548.1 -253.9 40.2 213s Year 33.5 312.7 378.8 -176.1 23.4 213s Employed 23.9 224.8 263.6 -128.3 16.8 213s Year Employed 213s GNP.deflator 33.5 23.9 213s GNP 312.7 224.8 213s Unemployed 378.8 263.6 213s Armed.Forces -176.1 -128.3 213s Population 23.4 16.8 213s Year 18.9 11.7 213s Employed 11.7 10.3 213s -------------------------------------------------------- 213s Loblolly 84 3 42 11.163448 213s Best subsample: 213s [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 213s [26] 53 54 57 58 59 63 64 65 66 70 71 76 77 81 82 83 84 213s Outliers: 0 213s Too many to print ... 213s ------------- 213s 213s Call: 213s CovMrcd(x = x, trace = FALSE) 213s -> Method: Minimum Regularized Covariance Determinant MRCD(alpha=0.5 ==> h=42) 213s 213s Robust Estimate of Location: 213s height age Seed 213s 44.20 17.26 6.76 213s 213s Robust Estimate of Covariance: 213s height age Seed 213s height 326.74 139.18 3.50 213s age 139.18 68.48 -2.72 213s Seed 3.50 -2.72 25.43 213s -------------------------------------------------------- 214s quakes 1000 4 500 11.802478 214s Best subsample: 214s Too long... 214s Outliers: 0 214s Too many to print ... 214s ------------- 214s 214s Call: 214s CovMrcd(x = x, trace = FALSE) 214s -> Method: Minimum Regularized Covariance Determinant MRCD(alpha=0.5 ==> h=500) 214s 214s Robust Estimate of Location: 214s lat long depth mag 214s -20.59 182.13 432.46 4.42 214s 214s Robust Estimate of Covariance: 214s lat long depth mag 214s lat 15.841 5.702 -106.720 -0.441 214s long 5.702 7.426 -577.189 -0.136 214s depth -106.720 -577.189 66701.479 3.992 214s mag -0.441 -0.136 3.992 0.144 214s -------------------------------------------------------- 214s ======================================================== 214s > ##doexactfit() 214s > 214s BEGIN TEST tmest4.R 214s 214s R version 4.5.2 (2025-10-31) -- "[Not] Part in a Rumble" 214s Copyright (C) 2025 The R Foundation for Statistical Computing 214s Platform: aarch64-unknown-linux-gnu 214s 214s R is free software and comes with ABSOLUTELY NO WARRANTY. 214s You are welcome to redistribute it under certain conditions. 214s Type 'license()' or 'licence()' for distribution details. 214s 214s R is a collaborative project with many contributors. 214s Type 'contributors()' for more information and 214s 'citation()' on how to cite R or R packages in publications. 214s 214s Type 'demo()' for some demos, 'help()' for on-line help, or 214s 'help.start()' for an HTML browser interface to help. 214s Type 'q()' to quit R. 214s 214s > ## VT::15.09.2013 - this will render the output independent 214s > ## from the version of the package 214s > suppressPackageStartupMessages(library(rrcov)) 214s > 214s > library(MASS) 214s > dodata <- function(nrep = 1, time = FALSE, full = TRUE) { 214s + domest <- function(x, xname, nrep = 1) { 214s + n <- dim(x)[1] 214s + p <- dim(x)[2] 214s + mm <- CovMest(x) 214s + crit <- log(mm@crit) 214s + ## c1 <- mm@psi@c1 214s + ## M <- mm$psi@M 214s + 214s + xres <- sprintf("%3d %3d %12.6f\n", dim(x)[1], dim(x)[2], crit) 214s + lpad <- lname-nchar(xname) 214s + cat(pad.right(xname,lpad), xres) 214s + 214s + dist <- getDistance(mm) 214s + quantiel <- qchisq(0.975, p) 214s + ibad <- which(dist >= quantiel) 214s + names(ibad) <- NULL 214s + nbad <- length(ibad) 214s + cat("Outliers: ",nbad,"\n") 214s + if(nbad > 0) 214s + print(ibad) 214s + cat("-------------\n") 214s + show(mm) 214s + cat("--------------------------------------------------------\n") 214s + } 214s + 214s + options(digits = 5) 214s + set.seed(101) # <<-- sub-sampling algorithm now based on R's RNG and seed 214s + 214s + lname <- 20 214s + 214s + data(heart) 214s + data(starsCYG) 214s + data(phosphor) 214s + data(stackloss) 214s + data(coleman) 214s + data(salinity) 214s + data(wood) 214s + data(hbk) 214s + 214s + data(Animals, package = "MASS") 214s + brain <- Animals[c(1:24, 26:25, 27:28),] 214s + data(milk) 214s + data(bushfire) 214s + 214s + tmp <- sys.call() 214s + cat("\nCall: ", deparse(substitute(tmp)),"\n") 214s + 214s + cat("Data Set n p c1 M LOG(det) Time\n") 214s + cat("======================================================================\n") 214s + domest(heart[, 1:2], data(heart), nrep) 214s + domest(starsCYG, data(starsCYG), nrep) 214s + domest(data.matrix(subset(phosphor, select = -plant)), data(phosphor), nrep) 214s + domest(stack.x, data(stackloss), nrep) 214s + domest(data.matrix(subset(coleman, select = -Y)), data(coleman), nrep) 214s + domest(data.matrix(subset(salinity, select = -Y)), data(salinity), nrep) 214s + domest(data.matrix(subset(wood, select = -y)), data(wood), nrep) 214s + domest(data.matrix(subset(hbk, select = -Y)), data(hbk), nrep) 214s + 214s + 214s + domest(brain, "Animals", nrep) 214s + domest(milk, data(milk), nrep) 214s + domest(bushfire, data(bushfire), nrep) 214s + cat("======================================================================\n") 214s + } 214s > 214s > # generate contaminated data using the function gendata with different 214s > # number of outliers and check if the M-estimate breaks - i.e. the 214s > # largest eigenvalue is larger than e.g. 5. 214s > # For n=50 and p=10 and d=5 the M-estimate can break for number of 214s > # outliers grater than 20. 214s > dogen <- function(){ 214s + eig <- vector("numeric",26) 214s + for(i in 0:25) { 214s + gg <- gendata(eps=i) 214s + mm <- CovMest(gg$x, t0=gg$tgood, S0=gg$sgood, arp=0.001) 214s + eig[i+1] <- ev <- getEvals(mm)[1] 214s + # cat(i, ev, "\n") 214s + 214s + stopifnot(ev < 5 || i > 20) 214s + } 214s + # plot(0:25, eig, type="l", xlab="Number of outliers", ylab="Largest Eigenvalue") 214s + } 214s > 214s > # 214s > # generate data 50x10 as multivariate normal N(0,I) and add 214s > # eps % outliers by adding d=5.0 to each component. 214s > # - if eps <0 and eps <=0.5, the number of outliers is eps*n 214s > # - if eps >= 1, it is the number of outliers 214s > # - use the center and cov of the good data as good start 214s > # - use the center and the cov of all data as a bad start 214s > # If using a good start, the M-estimate must iterate to 214s > # the good solution: the largest eigenvalue is less then e.g. 5 214s > # 214s > gendata <- function(n=50, p=10, eps=0, d=5.0){ 214s + 214s + if(eps < 0 || eps > 0.5 && eps < 1.0 || eps > 0.5*n) 214s + stop("eps is out of range") 214s + 214s + library(MASS) 214s + 214s + x <- mvrnorm(n, rep(0,p), diag(p)) 214s + bad <- vector("numeric") 214s + nbad = if(eps < 1) eps*n else eps 214s + if(nbad > 0){ 214s + bad <- sample(n, nbad) 214s + x[bad,] <- x[bad,] + d 214s + } 214s + cov1 <- cov.wt(x) 214s + cov2 <- if(nbad <= 0) cov1 else cov.wt(x[-bad,]) 214s + 214s + list(x=x, bad=sort(bad), tgood=cov2$center, sgood=cov2$cov, tbad=cov1$center, sbad=cov1$cov) 214s + } 214s > 214s > pad.right <- function(z, pads) 214s + { 214s + ## Pads spaces to right of text 214s + padding <- paste(rep(" ", pads), collapse = "") 214s + paste(z, padding, sep = "") 214s + } 214s > 214s > 214s > ## -- now do it: 214s > dodata() 214s 214s Call: dodata() 214s Data Set n p c1 M LOG(det) Time 214s ====================================================================== 214s heart 12 2 7.160341 214s Outliers: 3 214s [1] 2 6 12 214s ------------- 214s 214s Call: 214s CovMest(x = x) 214s -> Method: M-Estimates 214s 214s Robust Estimate of Location: 214s height weight 214s 34.9 27.0 214s 214s Robust Estimate of Covariance: 214s height weight 214s height 102 155 214s weight 155 250 214s -------------------------------------------------------- 214s starsCYG 47 2 -5.994588 214s Outliers: 7 214s [1] 7 9 11 14 20 30 34 214s ------------- 214s 214s Call: 214s CovMest(x = x) 214s -> Method: M-Estimates 214s 214s Robust Estimate of Location: 214s log.Te log.light 214s 4.42 4.95 214s 214s Robust Estimate of Covariance: 214s log.Te log.light 214s log.Te 0.0169 0.0587 214s log.light 0.0587 0.3523 214s -------------------------------------------------------- 214s phosphor 18 2 8.867522 214s Outliers: 3 214s [1] 1 6 10 214s ------------- 214s 214s Call: 214s CovMest(x = x) 214s -> Method: M-Estimates 214s 214s Robust Estimate of Location: 214s inorg organic 214s 15.4 39.1 214s 214s Robust Estimate of Covariance: 214s inorg organic 214s inorg 169 213 214s organic 213 308 214s -------------------------------------------------------- 214s stackloss 21 3 7.241400 214s Outliers: 9 214s [1] 1 2 3 15 16 17 18 19 21 214s ------------- 214s 214s Call: 214s CovMest(x = x) 214s -> Method: M-Estimates 214s 214s Robust Estimate of Location: 214s Air.Flow Water.Temp Acid.Conc. 214s 59.5 20.8 87.3 214s 214s Robust Estimate of Covariance: 214s Air.Flow Water.Temp Acid.Conc. 214s Air.Flow 9.34 8.69 8.52 214s Water.Temp 8.69 13.72 9.13 214s Acid.Conc. 8.52 9.13 34.54 214s -------------------------------------------------------- 214s coleman 20 5 2.574752 214s Outliers: 7 214s [1] 2 6 9 10 12 13 15 214s ------------- 214s 214s Call: 214s CovMest(x = x) 214s -> Method: M-Estimates 214s 214s Robust Estimate of Location: 214s salaryP fatherWc sstatus teacherSc motherLev 214s 2.82 48.44 5.30 25.19 6.51 214s 214s Robust Estimate of Covariance: 214s salaryP fatherWc sstatus teacherSc motherLev 214s salaryP 0.2850 0.1045 1.7585 0.3074 0.0355 214s fatherWc 0.1045 824.8305 260.7062 3.7507 17.7959 214s sstatus 1.7585 260.7062 105.6135 4.1140 5.7714 214s teacherSc 0.3074 3.7507 4.1140 0.6753 0.1563 214s motherLev 0.0355 17.7959 5.7714 0.1563 0.4147 214s -------------------------------------------------------- 214s salinity 28 3 3.875096 214s Outliers: 9 214s [1] 3 5 10 11 15 16 17 23 24 214s ------------- 214s 214s Call: 214s CovMest(x = x) 214s -> Method: M-Estimates 214s 214s Robust Estimate of Location: 214s X1 X2 X3 214s 10.02 3.21 22.36 214s 214s Robust Estimate of Covariance: 214s X1 X2 X3 214s X1 15.353 1.990 -5.075 214s X2 1.990 5.210 -0.769 214s X3 -5.075 -0.769 2.314 214s -------------------------------------------------------- 214s wood 20 5 -35.156305 214s Outliers: 7 214s [1] 4 6 7 8 11 16 19 214s ------------- 214s 214s Call: 214s CovMest(x = x) 214s -> Method: M-Estimates 214s 214s Robust Estimate of Location: 214s x1 x2 x3 x4 x5 214s 0.587 0.122 0.531 0.538 0.892 214s 214s Robust Estimate of Covariance: 214s x1 x2 x3 x4 x5 214s x1 6.45e-03 1.21e-03 2.03e-03 -3.77e-04 -1.05e-03 214s x2 1.21e-03 3.12e-04 8.16e-04 -3.34e-05 1.52e-05 214s x3 2.03e-03 8.16e-04 4.27e-03 -5.60e-04 2.27e-04 214s x4 -3.77e-04 -3.34e-05 -5.60e-04 1.83e-03 1.18e-03 214s x5 -1.05e-03 1.52e-05 2.27e-04 1.18e-03 1.78e-03 214s -------------------------------------------------------- 214s hbk 75 3 1.432485 214s Outliers: 14 214s [1] 1 2 3 4 5 6 7 8 9 10 11 12 13 14 214s ------------- 214s 214s Call: 214s CovMest(x = x) 214s -> Method: M-Estimates 214s 214s Robust Estimate of Location: 214s X1 X2 X3 214s 1.54 1.78 1.69 214s 214s Robust Estimate of Covariance: 214s X1 X2 X3 214s X1 1.6485 0.0739 0.1709 214s X2 0.0739 1.6780 0.2049 214s X3 0.1709 0.2049 1.5584 214s -------------------------------------------------------- 214s Animals 28 2 18.194822 214s Outliers: 10 214s [1] 2 6 7 9 12 14 15 16 25 28 214s ------------- 214s 214s Call: 214s CovMest(x = x) 214s -> Method: M-Estimates 214s 214s Robust Estimate of Location: 214s body brain 214s 18.7 64.9 214s 214s Robust Estimate of Covariance: 214s body brain 214s body 4993 8466 214s brain 8466 30335 214s -------------------------------------------------------- 214s milk 86 8 -25.041802 214s Outliers: 20 214s [1] 1 2 3 11 12 13 14 15 16 17 18 20 27 41 44 47 70 74 75 77 214s ------------- 214s 214s Call: 214s CovMest(x = x) 214s -> Method: M-Estimates 214s 214s Robust Estimate of Location: 214s X1 X2 X3 X4 X5 X6 X7 X8 214s 1.03 35.88 33.04 26.11 25.09 25.02 123.12 14.39 214s 214s Robust Estimate of Covariance: 214s X1 X2 X3 X4 X5 X6 X7 214s X1 4.89e-07 9.64e-05 1.83e-04 1.76e-04 1.57e-04 1.48e-04 6.53e-04 214s X2 9.64e-05 2.05e+00 3.38e-01 2.37e-01 1.70e-01 2.71e-01 1.91e+00 214s X3 1.83e-04 3.38e-01 1.16e+00 8.56e-01 8.48e-01 8.31e-01 8.85e-01 214s X4 1.76e-04 2.37e-01 8.56e-01 6.83e-01 6.55e-01 6.40e-01 6.91e-01 214s X5 1.57e-04 1.70e-01 8.48e-01 6.55e-01 6.93e-01 6.52e-01 6.90e-01 214s X6 1.48e-04 2.71e-01 8.31e-01 6.40e-01 6.52e-01 6.61e-01 6.95e-01 214s X7 6.53e-04 1.91e+00 8.85e-01 6.91e-01 6.90e-01 6.95e-01 4.40e+00 214s X8 5.56e-06 2.60e-01 1.98e-01 1.29e-01 1.12e-01 1.19e-01 4.12e-01 214s X8 214s X1 5.56e-06 214s X2 2.60e-01 214s X3 1.98e-01 214s X4 1.29e-01 214s X5 1.12e-01 214s X6 1.19e-01 214s X7 4.12e-01 214s X8 1.65e-01 214s -------------------------------------------------------- 214s bushfire 38 5 23.457490 214s Outliers: 15 214s [1] 7 8 9 10 11 29 30 31 32 33 34 35 36 37 38 214s ------------- 214s 214s Call: 214s CovMest(x = x) 214s -> Method: M-Estimates 214s 214s Robust Estimate of Location: 214s V1 V2 V3 V4 V5 214s 107 147 263 215 277 214s 214s Robust Estimate of Covariance: 214s V1 V2 V3 V4 V5 214s V1 775 560 -4179 -925 -759 214s V2 560 478 -2494 -510 -431 214s V3 -4179 -2494 27433 6441 5196 214s V4 -925 -510 6441 1607 1276 214s V5 -759 -431 5196 1276 1020 214s -------------------------------------------------------- 214s ====================================================================== 214s > dogen() 215s > #cat('Time elapsed: ', proc.time(),'\n') # for ``statistical reasons'' 215s > 215s BEGIN TEST tmve4.R 215s 215s R version 4.5.2 (2025-10-31) -- "[Not] Part in a Rumble" 215s Copyright (C) 2025 The R Foundation for Statistical Computing 215s Platform: aarch64-unknown-linux-gnu 215s 215s R is free software and comes with ABSOLUTELY NO WARRANTY. 215s You are welcome to redistribute it under certain conditions. 215s Type 'license()' or 'licence()' for distribution details. 215s 215s R is a collaborative project with many contributors. 215s Type 'contributors()' for more information and 215s 'citation()' on how to cite R or R packages in publications. 215s 215s Type 'demo()' for some demos, 'help()' for on-line help, or 215s 'help.start()' for an HTML browser interface to help. 215s Type 'q()' to quit R. 215s 215s > dodata <- function(nrep=1, time=FALSE, short=FALSE, full=TRUE, method = c("FASTMVE","MASS")){ 215s + ##@bdescr 215s + ## Test the function covMve() on the literature datasets: 215s + ## 215s + ## Call covMve() for all regression datasets available in rrco/robustbasev and print: 215s + ## - execution time (if time == TRUE) 215s + ## - objective fucntion 215s + ## - best subsample found (if short == false) 215s + ## - outliers identified (with cutoff 0.975) (if short == false) 215s + ## - estimated center and covarinance matrix if full == TRUE) 215s + ## 215s + ##@edescr 215s + ## 215s + ##@in nrep : [integer] number of repetitions to use for estimating the 215s + ## (average) execution time 215s + ##@in time : [boolean] whether to evaluate the execution time 215s + ##@in short : [boolean] whether to do short output (i.e. only the 215s + ## objective function value). If short == FALSE, 215s + ## the best subsample and the identified outliers are 215s + ## printed. See also the parameter full below 215s + ##@in full : [boolean] whether to print the estimated cente and covariance matrix 215s + ##@in method : [character] select a method: one of (FASTMCD, MASS) 215s + 215s + domve <- function(x, xname, nrep=1){ 215s + n <- dim(x)[1] 215s + p <- dim(x)[2] 215s + alpha <- 0.5 215s + h <- h.alpha.n(alpha, n, p) 215s + if(method == "MASS"){ 215s + mve <- cov.mve(x, quantile.used=h) 215s + quan <- h #default: floor((n+p+1)/2) 215s + crit <- mve$crit 215s + best <- mve$best 215s + mah <- mahalanobis(x, mve$center, mve$cov) 215s + quantiel <- qchisq(0.975, p) 215s + wt <- as.numeric(mah < quantiel) 215s + } 215s + else{ 215s + mve <- CovMve(x, trace=FALSE) 215s + quan <- as.integer(mve@quan) 215s + crit <- log(mve@crit) 215s + best <- mve@best 215s + wt <- mve@wt 215s + } 215s + 215s + 215s + if(time){ 215s + xtime <- system.time(dorep(x, nrep, method))[1]/nrep 215s + xres <- sprintf("%3d %3d %3d %12.6f %10.3f\n", dim(x)[1], dim(x)[2], quan, crit, xtime) 215s + } 215s + else{ 215s + xres <- sprintf("%3d %3d %3d %12.6f\n", dim(x)[1], dim(x)[2], quan, crit) 215s + } 215s + 215s + lpad<-lname-nchar(xname) 215s + cat(pad.right(xname,lpad), xres) 215s + 215s + if(!short){ 215s + cat("Best subsample: \n") 215s + print(best) 215s + 215s + ibad <- which(wt == 0) 215s + names(ibad) <- NULL 215s + nbad <- length(ibad) 215s + cat("Outliers: ", nbad, "\n") 215s + if(nbad > 0) 215s + print(ibad) 215s + if(full){ 215s + cat("-------------\n") 215s + show(mve) 215s + } 215s + cat("--------------------------------------------------------\n") 215s + } 215s + } 215s + 215s + options(digits = 5) 215s + set.seed(101) # <<-- sub-sampling algorithm now based on R's RNG and seed 215s + 215s + lname <- 20 215s + 215s + ## VT::15.09.2013 - this will render the output independent 215s + ## from the version of the package 215s + suppressPackageStartupMessages(library(rrcov)) 215s + 215s + method <- match.arg(method) 215s + if(method == "MASS") 215s + library(MASS) 215s + 215s + 215s + data(heart) 215s + data(starsCYG) 215s + data(phosphor) 215s + data(stackloss) 215s + data(coleman) 215s + data(salinity) 215s + data(wood) 215s + 215s + data(hbk) 215s + 215s + data(Animals, package = "MASS") 215s + brain <- Animals[c(1:24, 26:25, 27:28),] 215s + data(milk) 215s + data(bushfire) 215s + 215s + tmp <- sys.call() 215s + cat("\nCall: ", deparse(substitute(tmp)),"\n") 215s + 215s + cat("Data Set n p Half LOG(obj) Time\n") 215s + cat("========================================================\n") 215s + domve(heart[, 1:2], data(heart), nrep) 215s + domve(starsCYG, data(starsCYG), nrep) 215s + domve(data.matrix(subset(phosphor, select = -plant)), data(phosphor), nrep) 215s + domve(stack.x, data(stackloss), nrep) 215s + domve(data.matrix(subset(coleman, select = -Y)), data(coleman), nrep) 215s + domve(data.matrix(subset(salinity, select = -Y)), data(salinity), nrep) 215s + domve(data.matrix(subset(wood, select = -y)), data(wood), nrep) 215s + domve(data.matrix(subset(hbk, select = -Y)),data(hbk), nrep) 215s + 215s + domve(brain, "Animals", nrep) 215s + domve(milk, data(milk), nrep) 215s + domve(bushfire, data(bushfire), nrep) 215s + cat("========================================================\n") 215s + } 215s > 215s > dogen <- function(nrep=1, eps=0.49, method=c("FASTMVE", "MASS")){ 215s + 215s + domve <- function(x, nrep=1){ 215s + gc() 215s + xtime <- system.time(dorep(x, nrep, method))[1]/nrep 215s + cat(sprintf("%6d %3d %10.2f\n", dim(x)[1], dim(x)[2], xtime)) 215s + xtime 215s + } 215s + 215s + set.seed(1234) 215s + 215s + ## VT::15.09.2013 - this will render the output independent 215s + ## from the version of the package 215s + suppressPackageStartupMessages(library(rrcov)) 215s + library(MASS) 215s + 215s + method <- match.arg(method) 215s + 215s + ap <- c(2, 5, 10, 20, 30) 215s + an <- c(100, 500, 1000, 10000, 50000) 215s + 215s + tottime <- 0 215s + cat(" n p Time\n") 215s + cat("=====================\n") 215s + for(i in 1:length(an)) { 215s + for(j in 1:length(ap)) { 215s + n <- an[i] 215s + p <- ap[j] 215s + if(5*p <= n){ 215s + xx <- gendata(n, p, eps) 215s + X <- xx$X 215s + tottime <- tottime + domve(X, nrep) 215s + } 215s + } 215s + } 215s + 215s + cat("=====================\n") 215s + cat("Total time: ", tottime*nrep, "\n") 215s + } 215s > 215s > docheck <- function(n, p, eps){ 215s + xx <- gendata(n,p,eps) 215s + mve <- CovMve(xx$X) 215s + check(mve, xx$xind) 215s + } 215s > 215s > check <- function(mcd, xind){ 215s + ## check if mcd is robust w.r.t xind, i.e. check how many of xind 215s + ## did not get zero weight 215s + mymatch <- xind %in% which(mcd@wt == 0) 215s + length(xind) - length(which(mymatch)) 215s + } 215s > 215s > dorep <- function(x, nrep=1, method=c("FASTMVE","MASS")){ 215s + 215s + method <- match.arg(method) 215s + for(i in 1:nrep) 215s + if(method == "MASS") 215s + cov.mve(x) 215s + else 215s + CovMve(x) 215s + } 215s > 215s > #### gendata() #### 215s > # Generates a location contaminated multivariate 215s > # normal sample of n observations in p dimensions 215s > # (1-eps)*Np(0,Ip) + eps*Np(m,Ip) 215s > # where 215s > # m = (b,b,...,b) 215s > # Defaults: eps=0 and b=10 215s > # 215s > gendata <- function(n,p,eps=0,b=10){ 215s + 215s + if(missing(n) || missing(p)) 215s + stop("Please specify (n,p)") 215s + if(eps < 0 || eps >= 0.5) 215s + stop(message="eps must be in [0,0.5)") 215s + X <- mvrnorm(n,rep(0,p),diag(1,nrow=p,ncol=p)) 215s + nbad <- as.integer(eps * n) 215s + if(nbad > 0){ 215s + Xbad <- mvrnorm(nbad,rep(b,p),diag(1,nrow=p,ncol=p)) 215s + xind <- sample(n,nbad) 215s + X[xind,] <- Xbad 215s + } 215s + list(X=X, xind=xind) 215s + } 215s > 215s > pad.right <- function(z, pads) 215s + { 215s + ### Pads spaces to right of text 215s + padding <- paste(rep(" ", pads), collapse = "") 215s + paste(z, padding, sep = "") 215s + } 215s > 215s > whatis<-function(x){ 215s + if(is.data.frame(x)) 215s + cat("Type: data.frame\n") 215s + else if(is.matrix(x)) 215s + cat("Type: matrix\n") 215s + else if(is.vector(x)) 215s + cat("Type: vector\n") 215s + else 215s + cat("Type: don't know\n") 215s + } 215s > 215s > ## VT::15.09.2013 - this will render the output independent 215s > ## from the version of the package 215s > suppressPackageStartupMessages(library(rrcov)) 215s > 215s > dodata() 215s 215s Call: dodata() 215s Data Set n p Half LOG(obj) Time 215s ======================================================== 215s heart 12 2 7 3.827606 215s Best subsample: 215s [1] 1 4 7 8 9 10 11 215s Outliers: 3 215s [1] 2 6 12 215s ------------- 215s 215s Call: 215s CovMve(x = x, trace = FALSE) 215s -> Method: Minimum volume ellipsoid estimator 215s 215s Robust Estimate of Location: 215s height weight 215s 34.9 27.0 215s 215s Robust Estimate of Covariance: 215s height weight 215s height 142 217 215s weight 217 350 215s -------------------------------------------------------- 215s starsCYG 47 2 25 -2.742997 215s Best subsample: 215s [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 215s Outliers: 7 215s [1] 7 9 11 14 20 30 34 215s ------------- 215s 215s Call: 215s CovMve(x = x, trace = FALSE) 215s -> Method: Minimum volume ellipsoid estimator 215s 215s Robust Estimate of Location: 215s log.Te log.light 215s 4.41 4.93 215s 215s Robust Estimate of Covariance: 215s log.Te log.light 215s log.Te 0.0173 0.0578 215s log.light 0.0578 0.3615 215s -------------------------------------------------------- 215s phosphor 18 2 10 4.443101 215s Best subsample: 215s [1] 3 5 8 9 11 12 13 14 15 17 215s Outliers: 3 215s [1] 1 6 10 215s ------------- 215s 215s Call: 215s CovMve(x = x, trace = FALSE) 215s -> Method: Minimum volume ellipsoid estimator 215s 215s Robust Estimate of Location: 215s inorg organic 215s 15.2 39.4 215s 215s Robust Estimate of Covariance: 215s inorg organic 215s inorg 188 230 215s organic 230 339 215s -------------------------------------------------------- 215s stackloss 21 3 12 3.327582 215s Best subsample: 215s [1] 4 5 6 7 8 9 10 11 12 13 14 20 215s Outliers: 3 215s [1] 1 2 3 215s ------------- 215s 215s Call: 215s CovMve(x = x, trace = FALSE) 215s -> Method: Minimum volume ellipsoid estimator 215s 215s Robust Estimate of Location: 215s Air.Flow Water.Temp Acid.Conc. 215s 56.7 20.2 85.5 215s 215s Robust Estimate of Covariance: 215s Air.Flow Water.Temp Acid.Conc. 215s Air.Flow 34.31 11.07 23.54 215s Water.Temp 11.07 9.23 7.85 215s Acid.Conc. 23.54 7.85 47.35 215s -------------------------------------------------------- 215s coleman 20 5 13 2.065143 215s Best subsample: 215s [1] 1 3 4 5 7 8 11 14 16 17 18 19 20 215s Outliers: 5 215s [1] 2 6 9 10 13 215s ------------- 215s 215s Call: 215s CovMve(x = x, trace = FALSE) 215s -> Method: Minimum volume ellipsoid estimator 215s 215s Robust Estimate of Location: 215s salaryP fatherWc sstatus teacherSc motherLev 215s 2.79 44.26 3.59 25.08 6.38 215s 215s Robust Estimate of Covariance: 215s salaryP fatherWc sstatus teacherSc motherLev 215s salaryP 0.2920 1.1188 2.0421 0.3487 0.0748 215s fatherWc 1.1188 996.7540 338.6587 7.1673 23.1783 215s sstatus 2.0421 338.6587 148.2501 4.4894 7.8135 215s teacherSc 0.3487 7.1673 4.4894 0.9082 0.3204 215s motherLev 0.0748 23.1783 7.8135 0.3204 0.6024 215s -------------------------------------------------------- 215s salinity 28 3 16 2.002555 215s Best subsample: 215s [1] 1 7 8 9 12 13 14 18 19 20 21 22 25 26 27 28 215s Outliers: 5 215s [1] 5 11 16 23 24 215s ------------- 215s 215s Call: 215s CovMve(x = x, trace = FALSE) 215s -> Method: Minimum volume ellipsoid estimator 215s 215s Robust Estimate of Location: 215s X1 X2 X3 215s 10.2 3.1 22.4 215s 215s Robust Estimate of Covariance: 215s X1 X2 X3 215s X1 14.387 1.153 -4.072 215s X2 1.153 5.005 -0.954 215s X3 -4.072 -0.954 2.222 215s -------------------------------------------------------- 215s wood 20 5 13 -5.471407 215s Best subsample: 215s [1] 1 2 3 5 9 10 12 13 14 15 17 18 20 215s Outliers: 5 215s [1] 4 6 8 11 19 215s ------------- 215s 215s Call: 215s CovMve(x = x, trace = FALSE) 215s -> Method: Minimum volume ellipsoid estimator 215s 215s Robust Estimate of Location: 215s x1 x2 x3 x4 x5 215s 0.576 0.123 0.531 0.538 0.889 215s 215s Robust Estimate of Covariance: 215s x1 x2 x3 x4 x5 215s x1 7.45e-03 1.11e-03 1.83e-03 -2.90e-05 -5.65e-04 215s x2 1.11e-03 3.11e-04 7.68e-04 3.37e-05 3.85e-05 215s x3 1.83e-03 7.68e-04 4.30e-03 -9.96e-04 -6.27e-05 215s x4 -2.90e-05 3.37e-05 -9.96e-04 3.02e-03 1.91e-03 215s x5 -5.65e-04 3.85e-05 -6.27e-05 1.91e-03 2.25e-03 215s -------------------------------------------------------- 215s hbk 75 3 39 1.096831 215s Best subsample: 215s [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 215s [26] 55 56 58 59 64 65 66 67 70 71 72 73 74 75 215s Outliers: 14 215s [1] 1 2 3 4 5 6 7 8 9 10 11 12 13 14 215s ------------- 215s 215s Call: 215s CovMve(x = x, trace = FALSE) 215s -> Method: Minimum volume ellipsoid estimator 215s 215s Robust Estimate of Location: 215s X1 X2 X3 215s 1.48 1.86 1.73 215s 215s Robust Estimate of Covariance: 215s X1 X2 X3 215s X1 1.695 0.230 0.265 215s X2 0.230 1.679 0.119 215s X3 0.265 0.119 1.683 215s -------------------------------------------------------- 215s Animals 28 2 15 8.945423 215s Best subsample: 215s [1] 1 3 4 5 10 11 17 18 21 22 23 24 26 27 28 215s Outliers: 9 215s [1] 2 6 7 9 12 14 15 16 25 215s ------------- 215s 215s Call: 215s CovMve(x = x, trace = FALSE) 215s -> Method: Minimum volume ellipsoid estimator 215s 215s Robust Estimate of Location: 215s body brain 215s 48.3 127.3 215s 215s Robust Estimate of Covariance: 215s body brain 215s body 10767 16872 215s brain 16872 46918 215s -------------------------------------------------------- 215s milk 86 8 47 -1.160085 215s Best subsample: 215s [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 215s [26] 46 54 56 57 59 60 61 62 63 64 65 66 67 69 72 76 78 79 81 82 83 85 215s Outliers: 18 215s [1] 1 2 3 12 13 14 15 16 17 18 20 27 41 44 47 70 74 75 215s ------------- 215s 215s Call: 215s CovMve(x = x, trace = FALSE) 215s -> Method: Minimum volume ellipsoid estimator 215s 215s Robust Estimate of Location: 215s X1 X2 X3 X4 X5 X6 X7 X8 215s 1.03 35.91 33.02 26.08 25.06 24.99 122.93 14.38 215s 215s Robust Estimate of Covariance: 215s X1 X2 X3 X4 X5 X6 X7 215s X1 6.00e-07 1.51e-04 3.34e-04 3.09e-04 2.82e-04 2.77e-04 1.09e-03 215s X2 1.51e-04 2.03e+00 3.83e-01 3.04e-01 2.20e-01 3.51e-01 2.18e+00 215s X3 3.34e-04 3.83e-01 1.58e+00 1.21e+00 1.18e+00 1.20e+00 1.60e+00 215s X4 3.09e-04 3.04e-01 1.21e+00 9.82e-01 9.39e-01 9.53e-01 1.36e+00 215s X5 2.82e-04 2.20e-01 1.18e+00 9.39e-01 9.67e-01 9.52e-01 1.34e+00 215s X6 2.77e-04 3.51e-01 1.20e+00 9.53e-01 9.52e-01 9.92e-01 1.38e+00 215s X7 1.09e-03 2.18e+00 1.60e+00 1.36e+00 1.34e+00 1.38e+00 6.73e+00 215s X8 3.33e-05 2.92e-01 2.65e-01 1.83e-01 1.65e-01 1.76e-01 5.64e-01 215s X8 215s X1 3.33e-05 215s X2 2.92e-01 215s X3 2.65e-01 215s X4 1.83e-01 215s X5 1.65e-01 215s X6 1.76e-01 215s X7 5.64e-01 215s X8 1.80e-01 215s -------------------------------------------------------- 215s bushfire 38 5 22 5.644315 215s Best subsample: 215s [1] 1 2 3 4 5 6 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 215s Outliers: 15 215s [1] 7 8 9 10 11 29 30 31 32 33 34 35 36 37 38 215s ------------- 215s 215s Call: 215s CovMve(x = x, trace = FALSE) 215s -> Method: Minimum volume ellipsoid estimator 215s 215s Robust Estimate of Location: 215s V1 V2 V3 V4 V5 215s 107 147 263 215 277 215s 215s Robust Estimate of Covariance: 215s V1 V2 V3 V4 V5 215s V1 519 375 -2799 -619 -509 215s V2 375 320 -1671 -342 -289 215s V3 -2799 -1671 18373 4314 3480 215s V4 -619 -342 4314 1076 854 215s V5 -509 -289 3480 854 683 215s -------------------------------------------------------- 215s ======================================================== 215s > 215s BEGIN TEST togk4.R 215s 215s R version 4.5.2 (2025-10-31) -- "[Not] Part in a Rumble" 215s Copyright (C) 2025 The R Foundation for Statistical Computing 215s Platform: aarch64-unknown-linux-gnu 215s 215s R is free software and comes with ABSOLUTELY NO WARRANTY. 215s You are welcome to redistribute it under certain conditions. 215s Type 'license()' or 'licence()' for distribution details. 215s 215s R is a collaborative project with many contributors. 215s Type 'contributors()' for more information and 215s 'citation()' on how to cite R or R packages in publications. 215s 215s Type 'demo()' for some demos, 'help()' for on-line help, or 215s 'help.start()' for an HTML browser interface to help. 215s Type 'q()' to quit R. 215s 215s > ## VT::15.09.2013 - this will render the output independent 215s > ## from the version of the package 215s > suppressPackageStartupMessages(library(rrcov)) 216s > 216s > ## VT::14.01.2020 216s > ## On some platforms minor differences are shown - use 216s > ## IGNORE_RDIFF_BEGIN 216s > ## IGNORE_RDIFF_END 216s > 216s > dodata <- function(nrep=1, time=FALSE, short=FALSE, full=TRUE, method = c("FASTMCD","MASS")){ 216s + domcd <- function(x, xname, nrep=1){ 216s + n <- dim(x)[1] 216s + p <- dim(x)[2] 216s + 216s + mcd<-CovOgk(x) 216s + 216s + xres <- sprintf("%3d %3d\n", dim(x)[1], dim(x)[2]) 216s + 216s + lpad<-lname-nchar(xname) 216s + cat(pad.right(xname,lpad), xres) 216s + 216s + dist <- getDistance(mcd) 216s + quantiel <- qchisq(0.975, p) 216s + ibad <- which(dist >= quantiel) 216s + names(ibad) <- NULL 216s + nbad <- length(ibad) 216s + cat("Outliers: ",nbad,"\n") 216s + if(nbad > 0) 216s + print(ibad) 216s + cat("-------------\n") 216s + show(mcd) 216s + cat("--------------------------------------------------------\n") 216s + } 216s + 216s + lname <- 20 216s + 216s + ## VT::15.09.2013 - this will render the output independent 216s + ## from the version of the package 216s + suppressPackageStartupMessages(library(rrcov)) 216s + 216s + method <- match.arg(method) 216s + 216s + data(heart) 216s + data(starsCYG) 216s + data(phosphor) 216s + data(stackloss) 216s + data(coleman) 216s + data(salinity) 216s + data(wood) 216s + 216s + data(hbk) 216s + 216s + data(Animals, package = "MASS") 216s + brain <- Animals[c(1:24, 26:25, 27:28),] 216s + data(milk) 216s + data(bushfire) 216s + 216s + tmp <- sys.call() 216s + cat("\nCall: ", deparse(substitute(tmp)),"\n") 216s + 216s + cat("Data Set n p Half LOG(obj) Time\n") 216s + cat("========================================================\n") 216s + domcd(heart[, 1:2], data(heart), nrep) 216s + ## This will not work within the function, of course 216s + ## - comment it out 216s + ## IGNORE_RDIFF_BEGIN 216s + ## domcd(starsCYG,data(starsCYG), nrep) 216s + ## IGNORE_RDIFF_END 216s + domcd(data.matrix(subset(phosphor, select = -plant)), data(phosphor), nrep) 216s + domcd(stack.x,data(stackloss), nrep) 216s + domcd(data.matrix(subset(coleman, select = -Y)), data(coleman), nrep) 216s + domcd(data.matrix(subset(salinity, select = -Y)), data(salinity), nrep) 216s + ## IGNORE_RDIFF_BEGIN 216s + ## domcd(data.matrix(subset(wood, select = -y)), data(wood), nrep) 216s + ## IGNORE_RDIFF_END 216s + domcd(data.matrix(subset(hbk, select = -Y)), data(hbk), nrep) 216s + 216s + domcd(brain, "Animals", nrep) 216s + domcd(milk, data(milk), nrep) 216s + domcd(bushfire, data(bushfire), nrep) 216s + cat("========================================================\n") 216s + } 216s > 216s > pad.right <- function(z, pads) 216s + { 216s + ### Pads spaces to right of text 216s + padding <- paste(rep(" ", pads), collapse = "") 216s + paste(z, padding, sep = "") 216s + } 216s > 216s > dodata() 216s 216s Call: dodata() 216s Data Set n p Half LOG(obj) Time 216s ======================================================== 216s heart 12 2 216s Outliers: 5 216s [1] 2 6 8 10 12 216s ------------- 216s 216s Call: 216s CovOgk(x = x) 216s -> Method: Orthogonalized Gnanadesikan-Kettenring Estimator 216s 216s Robust Estimate of Location: 216s height weight 216s 39.76 35.71 216s 216s Robust Estimate of Covariance: 216s height weight 216s height 15.88 32.07 216s weight 32.07 78.28 216s -------------------------------------------------------- 216s phosphor 18 2 216s Outliers: 2 216s [1] 1 6 216s ------------- 216s 216s Call: 216s CovOgk(x = x) 216s -> Method: Orthogonalized Gnanadesikan-Kettenring Estimator 216s 216s Robust Estimate of Location: 216s inorg organic 216s 13.31 40.00 216s 216s Robust Estimate of Covariance: 216s inorg organic 216s inorg 92.82 93.24 216s organic 93.24 152.62 216s -------------------------------------------------------- 216s stackloss 21 3 216s Outliers: 2 216s [1] 1 2 216s ------------- 216s 216s Call: 216s CovOgk(x = x) 216s -> Method: Orthogonalized Gnanadesikan-Kettenring Estimator 216s 216s Robust Estimate of Location: 216s Air.Flow Water.Temp Acid.Conc. 216s 57.72 20.50 85.78 216s 216s Robust Estimate of Covariance: 216s Air.Flow Water.Temp Acid.Conc. 216s Air.Flow 38.423 11.306 18.605 216s Water.Temp 11.306 6.806 5.889 216s Acid.Conc. 18.605 5.889 29.840 216s -------------------------------------------------------- 216s coleman 20 5 216s Outliers: 3 216s [1] 1 6 10 216s ------------- 216s 216s Call: 216s CovOgk(x = x) 216s -> Method: Orthogonalized Gnanadesikan-Kettenring Estimator 216s 216s Robust Estimate of Location: 216s salaryP fatherWc sstatus teacherSc motherLev 216s 2.723 43.202 2.912 25.010 6.290 216s 216s Robust Estimate of Covariance: 216s salaryP fatherWc sstatus teacherSc motherLev 216s salaryP 0.12867 2.80048 0.92026 0.15118 0.06413 216s fatherWc 2.80048 678.72549 227.36415 9.30826 16.15102 216s sstatus 0.92026 227.36415 101.39094 3.38013 5.63283 216s teacherSc 0.15118 9.30826 3.38013 0.57112 0.27701 216s motherLev 0.06413 16.15102 5.63283 0.27701 0.44801 216s -------------------------------------------------------- 216s salinity 28 3 216s Outliers: 3 216s [1] 3 5 16 216s ------------- 216s 216s Call: 216s CovOgk(x = x) 216s -> Method: Orthogonalized Gnanadesikan-Kettenring Estimator 216s 216s Robust Estimate of Location: 216s X1 X2 X3 216s 10.74 2.68 22.99 216s 216s Robust Estimate of Covariance: 216s X1 X2 X3 216s X1 8.1047 -0.6365 -0.4720 216s X2 -0.6365 3.0976 -1.3520 216s X3 -0.4720 -1.3520 2.3648 216s -------------------------------------------------------- 216s hbk 75 3 216s Outliers: 14 216s [1] 1 2 3 4 5 6 7 8 9 10 11 12 13 14 216s ------------- 216s 216s Call: 216s CovOgk(x = x) 216s -> Method: Orthogonalized Gnanadesikan-Kettenring Estimator 216s 216s Robust Estimate of Location: 216s X1 X2 X3 216s 1.538 1.780 1.687 216s 216s Robust Estimate of Covariance: 216s X1 X2 X3 216s X1 1.11350 0.04992 0.11541 216s X2 0.04992 1.13338 0.13843 216s X3 0.11541 0.13843 1.05261 216s -------------------------------------------------------- 216s Animals 28 2 216s Outliers: 12 216s [1] 2 6 7 9 12 14 15 16 17 24 25 28 216s ------------- 216s 216s Call: 216s CovOgk(x = x) 216s -> Method: Orthogonalized Gnanadesikan-Kettenring Estimator 216s 216s Robust Estimate of Location: 216s body brain 216s 39.65 105.83 216s 216s Robust Estimate of Covariance: 216s body brain 216s body 3981 7558 216s brain 7558 16594 216s -------------------------------------------------------- 216s milk 86 8 216s Outliers: 22 216s [1] 1 2 3 11 12 13 14 15 16 17 18 20 27 41 44 47 50 70 74 75 77 85 216s ------------- 216s 216s Call: 216s CovOgk(x = x) 216s -> Method: Orthogonalized Gnanadesikan-Kettenring Estimator 216s 216s Robust Estimate of Location: 216s X1 X2 X3 X4 X5 X6 X7 X8 216s 1.03 35.80 33.10 26.15 25.13 25.06 123.06 14.39 216s 216s Robust Estimate of Covariance: 216s X1 X2 X3 X4 X5 X6 X7 216s X1 4.074e-07 5.255e-05 1.564e-04 1.506e-04 1.340e-04 1.234e-04 5.308e-04 216s X2 5.255e-05 1.464e+00 3.425e-01 2.465e-01 1.847e-01 2.484e-01 1.459e+00 216s X3 1.564e-04 3.425e-01 1.070e+00 7.834e-01 7.665e-01 7.808e-01 7.632e-01 216s X4 1.506e-04 2.465e-01 7.834e-01 6.178e-01 5.868e-01 5.959e-01 5.923e-01 216s X5 1.340e-04 1.847e-01 7.665e-01 5.868e-01 6.124e-01 5.967e-01 5.868e-01 216s X6 1.234e-04 2.484e-01 7.808e-01 5.959e-01 5.967e-01 6.253e-01 5.819e-01 216s X7 5.308e-04 1.459e+00 7.632e-01 5.923e-01 5.868e-01 5.819e-01 3.535e+00 216s X8 1.990e-07 1.851e-01 1.861e-01 1.210e-01 1.041e-01 1.116e-01 3.046e-01 216s X8 216s X1 1.990e-07 216s X2 1.851e-01 216s X3 1.861e-01 216s X4 1.210e-01 216s X5 1.041e-01 216s X6 1.116e-01 216s X7 3.046e-01 216s X8 1.292e-01 216s -------------------------------------------------------- 216s bushfire 38 5 216s Outliers: 17 216s [1] 7 8 9 10 11 12 28 29 30 31 32 33 34 35 36 37 38 216s ------------- 216s 216s Call: 216s CovOgk(x = x) 216s -> Method: Orthogonalized Gnanadesikan-Kettenring Estimator 216s 216s Robust Estimate of Location: 216s V1 V2 V3 V4 V5 216s 104.5 146.0 275.6 217.8 279.3 216s 216s Robust Estimate of Covariance: 216s V1 V2 V3 V4 V5 216s V1 266.8 203.2 -1380.7 -311.1 -252.2 216s V2 203.2 178.4 -910.9 -185.9 -155.9 216s V3 -1380.7 -910.9 8279.7 2035.5 1615.4 216s V4 -311.1 -185.9 2035.5 536.5 418.6 216s V5 -252.2 -155.9 1615.4 418.6 329.2 216s -------------------------------------------------------- 216s ======================================================== 216s > 216s BEGIN TEST tqda.R 216s 216s R version 4.5.2 (2025-10-31) -- "[Not] Part in a Rumble" 216s Copyright (C) 2025 The R Foundation for Statistical Computing 216s Platform: aarch64-unknown-linux-gnu 216s 216s R is free software and comes with ABSOLUTELY NO WARRANTY. 216s You are welcome to redistribute it under certain conditions. 216s Type 'license()' or 'licence()' for distribution details. 216s 216s R is a collaborative project with many contributors. 216s Type 'contributors()' for more information and 216s 'citation()' on how to cite R or R packages in publications. 216s 216s Type 'demo()' for some demos, 'help()' for on-line help, or 216s 'help.start()' for an HTML browser interface to help. 216s Type 'q()' to quit R. 216s 216s > ## VT::15.09.2013 - this will render the output independent 216s > ## from the version of the package 216s > suppressPackageStartupMessages(library(rrcov)) 216s > 216s > dodata <- function(method) { 216s + 216s + options(digits = 5) 216s + set.seed(101) # <<-- sub-sampling algorithm now based on R's RNG and seed 216s + 216s + tmp <- sys.call() 216s + cat("\nCall: ", deparse(substitute(tmp)),"\n") 216s + cat("===================================================\n") 216s + 216s + data(hemophilia); show(QdaCov(as.factor(gr)~., data=hemophilia, method=method)) 216s + data(anorexia, package="MASS"); show(QdaCov(Treat~., data=anorexia, method=method)) 216s + data(Pima.tr, package="MASS"); show(QdaCov(type~., data=Pima.tr, method=method)) 216s + data(iris); # show(QdaCov(Species~., data=iris, method=method)) 216s + data(crabs, package="MASS"); # show(QdaCov(sp~., data=crabs, method=method)) 216s + 216s + show(QdaClassic(as.factor(gr)~., data=hemophilia)) 216s + show(QdaClassic(Treat~., data=anorexia)) 216s + show(QdaClassic(type~., data=Pima.tr)) 216s + show(QdaClassic(Species~., data=iris)) 216s + ## show(QdaClassic(sp~., data=crabs)) 216s + cat("===================================================\n") 216s + } 216s > 216s > 216s > ## -- now do it: 216s > dodata(method="mcd") 216s 216s Call: dodata(method = "mcd") 216s =================================================== 216s Call: 216s QdaCov(as.factor(gr) ~ ., data = hemophilia, method = method) 216s 216s Prior Probabilities of Groups: 216s carrier normal 216s 0.6 0.4 216s 216s Group means: 216s AHFactivity AHFantigen 216s carrier -0.30795 -0.0059911 216s normal -0.12920 -0.0603000 216s 216s Group: carrier 216s AHFactivity AHFantigen 216s AHFactivity 0.023784 0.015376 216s AHFantigen 0.015376 0.024035 216s 216s Group: normal 216s AHFactivity AHFantigen 216s AHFactivity 0.0057546 0.0042606 216s AHFantigen 0.0042606 0.0084914 216s Call: 216s QdaCov(Treat ~ ., data = anorexia, method = method) 216s 216s Prior Probabilities of Groups: 216s CBT Cont FT 216s 0.40278 0.36111 0.23611 216s 216s Group means: 216s Prewt Postwt 216s CBT 82.633 82.950 216s Cont 81.558 81.108 216s FT 84.331 94.762 216s 216s Group: CBT 216s Prewt Postwt 216s Prewt 9.8671 8.6611 216s Postwt 8.6611 11.8966 216s 216s Group: Cont 216s Prewt Postwt 216s Prewt 32.5705 -4.3705 216s Postwt -4.3705 22.5079 216s 216s Group: FT 216s Prewt Postwt 216s Prewt 33.056 10.814 216s Postwt 10.814 14.265 217s Call: 217s QdaCov(type ~ ., data = Pima.tr, method = method) 217s 217s Prior Probabilities of Groups: 217s No Yes 217s 0.66 0.34 217s 217s Group means: 217s npreg glu bp skin bmi ped age 217s No 1.8602 107.69 67.344 25.29 30.642 0.40777 24.667 217s Yes 5.3167 145.85 74.283 31.80 34.095 0.49533 37.883 217s 217s Group: No 217s npreg glu bp skin bmi ped age 217s npreg 2.221983 -0.18658 1.86507 -0.44427 0.1725348 -0.0683616 2.63439 217s glu -0.186582 471.88789 45.28021 8.95404 30.6551510 -0.6359899 3.50218 217s bp 1.865066 45.28021 110.09787 26.11192 14.4739180 -0.2104074 13.23392 217s skin -0.444272 8.95404 26.11192 118.30521 52.3115719 -0.2995751 8.65861 217s bmi 0.172535 30.65515 14.47392 52.31157 43.3140415 0.0079866 6.75720 217s ped -0.068362 -0.63599 -0.21041 -0.29958 0.0079866 0.0587710 -0.18683 217s age 2.634387 3.50218 13.23392 8.65861 6.7572019 -0.1868284 12.09493 217s 217s Group: Yes 217s npreg glu bp skin bmi ped age 217s npreg 17.875215 -13.740021 9.03580 4.498580 1.787458 0.079504 26.92283 217s glu -13.740021 917.719003 55.30399 27.976265 10.755113 0.092673 38.94970 217s bp 9.035798 55.303991 129.97953 34.130200 10.104275 0.198342 32.95351 217s skin 4.498580 27.976265 34.13020 101.842647 30.297210 0.064739 3.59427 217s bmi 1.787458 10.755113 10.10428 30.297210 22.529467 0.084369 -6.64317 217s ped 0.079504 0.092673 0.19834 0.064739 0.084369 0.066667 0.11199 217s age 26.922828 38.949697 32.95351 3.594266 -6.643165 0.111992 143.69752 217s Call: 217s QdaClassic(as.factor(gr) ~ ., data = hemophilia) 217s 217s Prior Probabilities of Groups: 217s carrier normal 217s 0.6 0.4 217s 217s Group means: 217s AHFactivity AHFantigen 217s carrier -0.30795 -0.0059911 217s normal -0.13487 -0.0778567 217s 217s Group: carrier 217s AHFactivity AHFantigen 217s AHFactivity 0.023784 0.015376 217s AHFantigen 0.015376 0.024035 217s 217s Group: normal 217s AHFactivity AHFantigen 217s AHFactivity 0.020897 0.015515 217s AHFantigen 0.015515 0.017920 217s Call: 217s QdaClassic(Treat ~ ., data = anorexia) 217s 217s Prior Probabilities of Groups: 217s CBT Cont FT 217s 0.40278 0.36111 0.23611 217s 217s Group means: 217s Prewt Postwt 217s CBT 82.690 85.697 217s Cont 81.558 81.108 217s FT 83.229 90.494 217s 217s Group: CBT 217s Prewt Postwt 217s Prewt 23.479 19.910 217s Postwt 19.910 69.755 217s 217s Group: Cont 217s Prewt Postwt 217s Prewt 32.5705 -4.3705 217s Postwt -4.3705 22.5079 217s 217s Group: FT 217s Prewt Postwt 217s Prewt 25.167 22.883 217s Postwt 22.883 71.827 217s Call: 217s QdaClassic(type ~ ., data = Pima.tr) 217s 217s Prior Probabilities of Groups: 217s No Yes 217s 0.66 0.34 217s 217s Group means: 217s npreg glu bp skin bmi ped age 217s No 2.9167 113.11 69.545 27.205 31.074 0.41548 29.235 217s Yes 4.8382 145.06 74.588 33.118 34.709 0.54866 37.691 217s 217s Group: No 217s npreg glu bp skin bmi ped age 217s npreg 7.878499 10.77226 8.190840 2.910305 -0.035751 -0.207341 16.82888 217s glu 10.772265 709.56118 81.430257 13.237682 19.037867 -0.518609 59.01307 217s bp 8.190840 81.43026 122.845246 33.879944 16.612630 -0.077183 46.78695 217s skin 2.910305 13.23768 33.879944 119.446391 50.125920 0.074282 18.47068 217s bmi -0.035751 19.03787 16.612630 50.125920 40.722996 0.145242 6.99999 217s ped -0.207341 -0.51861 -0.077183 0.074282 0.145242 0.071388 -0.53814 217s age 16.828880 59.01307 46.786954 18.470680 6.999988 -0.538138 91.08183 217s 217s Group: Yes 217s npreg glu bp skin bmi ped age 217s npreg 15.77941 -8.199298 6.42493 -0.51800 -1.03288 -0.133011 21.93437 217s glu -8.19930 907.250219 23.71115 87.51536 9.98156 -0.082159 58.12291 217s bp 6.42493 23.711150 134.18613 19.70588 5.15891 -0.795470 26.30378 217s skin -0.51800 87.515364 19.70588 151.32924 28.28551 0.347951 26.67867 217s bmi -1.03288 9.981563 5.15891 28.28551 23.14529 0.457694 -7.91216 217s ped -0.13301 -0.082159 -0.79547 0.34795 0.45769 0.128883 -0.41737 217s age 21.93437 58.122915 26.30378 26.67867 -7.91216 -0.417375 131.79873 217s Call: 217s QdaClassic(Species ~ ., data = iris) 217s 217s Prior Probabilities of Groups: 217s setosa versicolor virginica 217s 0.33333 0.33333 0.33333 217s 217s Group means: 217s Sepal.Length Sepal.Width Petal.Length Petal.Width 217s setosa 5.006 3.428 1.462 0.246 217s versicolor 5.936 2.770 4.260 1.326 217s virginica 6.588 2.974 5.552 2.026 217s 217s Group: setosa 217s Sepal.Length Sepal.Width Petal.Length Petal.Width 217s Sepal.Length 0.124249 0.099216 0.0163551 0.0103306 217s Sepal.Width 0.099216 0.143690 0.0116980 0.0092980 217s Petal.Length 0.016355 0.011698 0.0301592 0.0060694 217s Petal.Width 0.010331 0.009298 0.0060694 0.0111061 217s 217s Group: versicolor 217s Sepal.Length Sepal.Width Petal.Length Petal.Width 217s Sepal.Length 0.266433 0.085184 0.182898 0.055780 217s Sepal.Width 0.085184 0.098469 0.082653 0.041204 217s Petal.Length 0.182898 0.082653 0.220816 0.073102 217s Petal.Width 0.055780 0.041204 0.073102 0.039106 217s 217s Group: virginica 217s Sepal.Length Sepal.Width Petal.Length Petal.Width 217s Sepal.Length 0.404343 0.093763 0.303290 0.049094 217s Sepal.Width 0.093763 0.104004 0.071380 0.047629 217s Petal.Length 0.303290 0.071380 0.304588 0.048824 217s Petal.Width 0.049094 0.047629 0.048824 0.075433 217s =================================================== 217s > dodata(method="m") 217s 217s Call: dodata(method = "m") 217s =================================================== 217s Call: 217s QdaCov(as.factor(gr) ~ ., data = hemophilia, method = method) 217s 217s Prior Probabilities of Groups: 217s carrier normal 217s 0.6 0.4 217s 217s Group means: 217s AHFactivity AHFantigen 217s carrier -0.29810 -0.0028222 217s normal -0.13081 -0.0675283 217s 217s Group: carrier 217s AHFactivity AHFantigen 217s AHFactivity 0.026018 0.017653 217s AHFantigen 0.017653 0.030128 217s 217s Group: normal 217s AHFactivity AHFantigen 217s AHFactivity 0.0081933 0.0065737 217s AHFantigen 0.0065737 0.0118565 217s Call: 217s QdaCov(Treat ~ ., data = anorexia, method = method) 217s 217s Prior Probabilities of Groups: 217s CBT Cont FT 217s 0.40278 0.36111 0.23611 217s 217s Group means: 217s Prewt Postwt 217s CBT 82.436 82.631 217s Cont 81.559 80.272 217s FT 85.120 94.657 217s 217s Group: CBT 217s Prewt Postwt 217s Prewt 23.630 25.128 217s Postwt 25.128 38.142 217s 217s Group: Cont 217s Prewt Postwt 217s Prewt 35.8824 -8.2405 217s Postwt -8.2405 23.7416 217s 217s Group: FT 217s Prewt Postwt 217s Prewt 33.805 18.206 217s Postwt 18.206 24.639 217s Call: 217s QdaCov(type ~ ., data = Pima.tr, method = method) 217s 217s Prior Probabilities of Groups: 217s No Yes 217s 0.66 0.34 217s 217s Group means: 217s npreg glu bp skin bmi ped age 217s No 2.5225 111.26 68.081 26.640 30.801 0.40452 26.306 217s Yes 5.0702 144.32 75.088 31.982 34.267 0.47004 37.140 217s 217s Group: No 217s npreg glu bp skin bmi ped age 217s npreg 5.74219 14.47051 6.63766 4.98559 0.826570 -0.128106 10.71303 217s glu 14.47051 591.08717 68.81219 44.73311 40.658393 -0.545716 38.01918 217s bp 6.63766 68.81219 121.02716 30.46466 16.789801 -0.320065 25.29371 217s skin 4.98559 44.73311 30.46466 136.52176 56.604475 -0.250711 19.73259 217s bmi 0.82657 40.65839 16.78980 56.60447 47.859747 0.046358 6.94523 217s ped -0.12811 -0.54572 -0.32006 -0.25071 0.046358 0.061485 -0.34653 217s age 10.71303 38.01918 25.29371 19.73259 6.945227 -0.346527 35.66101 217s 217s Group: Yes 217s npreg glu bp skin bmi ped age 217s npreg 15.98861 -1.2430 10.48556 9.05947 2.425316 0.162453 30.149872 217s glu -1.24304 867.1076 46.43838 25.92297 5.517382 1.044360 31.152650 217s bp 10.48556 46.4384 130.12536 17.21407 6.343942 -0.235121 41.091494 217s skin 9.05947 25.9230 17.21407 85.96314 26.089017 0.170061 14.562516 217s bmi 2.42532 5.5174 6.34394 26.08902 22.051976 0.097786 -5.297971 217s ped 0.16245 1.0444 -0.23512 0.17006 0.097786 0.057112 0.055286 217s age 30.14987 31.1527 41.09149 14.56252 -5.297971 0.055286 137.440921 217s Call: 217s QdaClassic(as.factor(gr) ~ ., data = hemophilia) 217s 217s Prior Probabilities of Groups: 217s carrier normal 217s 0.6 0.4 217s 217s Group means: 217s AHFactivity AHFantigen 217s carrier -0.30795 -0.0059911 217s normal -0.13487 -0.0778567 217s 217s Group: carrier 217s AHFactivity AHFantigen 217s AHFactivity 0.023784 0.015376 217s AHFantigen 0.015376 0.024035 217s 217s Group: normal 217s AHFactivity AHFantigen 217s AHFactivity 0.020897 0.015515 217s AHFantigen 0.015515 0.017920 217s Call: 217s QdaClassic(Treat ~ ., data = anorexia) 217s 217s Prior Probabilities of Groups: 217s CBT Cont FT 217s 0.40278 0.36111 0.23611 217s 217s Group means: 217s Prewt Postwt 217s CBT 82.690 85.697 217s Cont 81.558 81.108 217s FT 83.229 90.494 217s 217s Group: CBT 217s Prewt Postwt 217s Prewt 23.479 19.910 217s Postwt 19.910 69.755 217s 217s Group: Cont 217s Prewt Postwt 217s Prewt 32.5705 -4.3705 217s Postwt -4.3705 22.5079 217s 217s Group: FT 217s Prewt Postwt 217s Prewt 25.167 22.883 217s Postwt 22.883 71.827 217s Call: 217s QdaClassic(type ~ ., data = Pima.tr) 217s 217s Prior Probabilities of Groups: 217s No Yes 217s 0.66 0.34 217s 217s Group means: 217s npreg glu bp skin bmi ped age 217s No 2.9167 113.11 69.545 27.205 31.074 0.41548 29.235 217s Yes 4.8382 145.06 74.588 33.118 34.709 0.54866 37.691 217s 217s Group: No 217s npreg glu bp skin bmi ped age 217s npreg 7.878499 10.77226 8.190840 2.910305 -0.035751 -0.207341 16.82888 217s glu 10.772265 709.56118 81.430257 13.237682 19.037867 -0.518609 59.01307 217s bp 8.190840 81.43026 122.845246 33.879944 16.612630 -0.077183 46.78695 217s skin 2.910305 13.23768 33.879944 119.446391 50.125920 0.074282 18.47068 217s bmi -0.035751 19.03787 16.612630 50.125920 40.722996 0.145242 6.99999 217s ped -0.207341 -0.51861 -0.077183 0.074282 0.145242 0.071388 -0.53814 217s age 16.828880 59.01307 46.786954 18.470680 6.999988 -0.538138 91.08183 217s 217s Group: Yes 217s npreg glu bp skin bmi ped age 217s npreg 15.77941 -8.199298 6.42493 -0.51800 -1.03288 -0.133011 21.93437 217s glu -8.19930 907.250219 23.71115 87.51536 9.98156 -0.082159 58.12291 217s bp 6.42493 23.711150 134.18613 19.70588 5.15891 -0.795470 26.30378 217s skin -0.51800 87.515364 19.70588 151.32924 28.28551 0.347951 26.67867 217s bmi -1.03288 9.981563 5.15891 28.28551 23.14529 0.457694 -7.91216 217s ped -0.13301 -0.082159 -0.79547 0.34795 0.45769 0.128883 -0.41737 217s age 21.93437 58.122915 26.30378 26.67867 -7.91216 -0.417375 131.79873 217s Call: 217s QdaClassic(Species ~ ., data = iris) 217s 217s Prior Probabilities of Groups: 217s setosa versicolor virginica 217s 0.33333 0.33333 0.33333 217s 217s Group means: 217s Sepal.Length Sepal.Width Petal.Length Petal.Width 217s setosa 5.006 3.428 1.462 0.246 217s versicolor 5.936 2.770 4.260 1.326 217s virginica 6.588 2.974 5.552 2.026 217s 217s Group: setosa 217s Sepal.Length Sepal.Width Petal.Length Petal.Width 217s Sepal.Length 0.124249 0.099216 0.0163551 0.0103306 217s Sepal.Width 0.099216 0.143690 0.0116980 0.0092980 217s Petal.Length 0.016355 0.011698 0.0301592 0.0060694 217s Petal.Width 0.010331 0.009298 0.0060694 0.0111061 217s 217s Group: versicolor 217s Sepal.Length Sepal.Width Petal.Length Petal.Width 217s Sepal.Length 0.266433 0.085184 0.182898 0.055780 217s Sepal.Width 0.085184 0.098469 0.082653 0.041204 217s Petal.Length 0.182898 0.082653 0.220816 0.073102 217s Petal.Width 0.055780 0.041204 0.073102 0.039106 217s 217s Group: virginica 217s Sepal.Length Sepal.Width Petal.Length Petal.Width 217s Sepal.Length 0.404343 0.093763 0.303290 0.049094 217s Sepal.Width 0.093763 0.104004 0.071380 0.047629 217s Petal.Length 0.303290 0.071380 0.304588 0.048824 217s Petal.Width 0.049094 0.047629 0.048824 0.075433 217s =================================================== 217s > dodata(method="ogk") 217s 217s Call: dodata(method = "ogk") 217s =================================================== 217s Call: 217s QdaCov(as.factor(gr) ~ ., data = hemophilia, method = method) 217s 217s Prior Probabilities of Groups: 217s carrier normal 217s 0.6 0.4 217s 217s Group means: 217s AHFactivity AHFantigen 217s carrier -0.29324 0.00033953 217s normal -0.12744 -0.06628182 217s 217s Group: carrier 217s AHFactivity AHFantigen 217s AHFactivity 0.019260 0.013026 217s AHFantigen 0.013026 0.021889 217s 217s Group: normal 217s AHFactivity AHFantigen 217s AHFactivity 0.0049651 0.0039707 217s AHFantigen 0.0039707 0.0066084 217s Call: 217s QdaCov(Treat ~ ., data = anorexia, method = method) 217s 217s Prior Probabilities of Groups: 217s CBT Cont FT 217s 0.40278 0.36111 0.23611 217s 217s Group means: 217s Prewt Postwt 217s CBT 82.587 82.709 217s Cont 81.558 81.108 217s FT 85.110 94.470 217s 217s Group: CBT 217s Prewt Postwt 217s Prewt 10.452 15.115 217s Postwt 15.115 37.085 217s 217s Group: Cont 217s Prewt Postwt 217s Prewt 31.3178 -4.2024 217s Postwt -4.2024 21.6422 217s 217s Group: FT 217s Prewt Postwt 217s Prewt 5.5309 1.4813 217s Postwt 1.4813 7.5501 217s Call: 217s QdaCov(type ~ ., data = Pima.tr, method = method) 217s 217s Prior Probabilities of Groups: 217s No Yes 217s 0.66 0.34 217s 217s Group means: 217s npreg glu bp skin bmi ped age 217s No 2.4286 110.35 67.495 25.905 30.275 0.39587 26.248 217s Yes 5.1964 142.71 75.357 32.732 34.809 0.48823 37.607 217s 217s Group: No 217s npreg glu bp skin bmi ped age 217s npreg 3.97823 8.70612 4.58776 4.16463 0.250612 -0.117238 8.21769 217s glu 8.70612 448.91392 51.71120 38.66213 21.816345 -0.296524 24.29370 217s bp 4.58776 51.71120 99.41188 24.27574 10.491311 -0.290753 20.02975 217s skin 4.16463 38.66213 24.27574 98.61950 41.682404 -0.335213 16.60454 217s bmi 0.25061 21.81634 10.49131 41.68240 35.237101 -0.019774 5.12042 217s ped -0.11724 -0.29652 -0.29075 -0.33521 -0.019774 0.051431 -0.36275 217s age 8.21769 24.29370 20.02975 16.60454 5.120417 -0.362748 31.32916 217s 217s Group: Yes 217s npreg glu bp skin bmi ped age 217s npreg 15.26499 6.30612 3.01913 3.76690 0.94825 0.12076 22.64860 217s glu 6.30612 688.16837 22.22704 12.81633 3.55791 0.68833 32.28061 217s bp 3.01913 22.22704 103.97959 9.95281 2.09860 0.45672 31.17602 217s skin 3.76690 12.81633 9.95281 67.51754 19.51489 0.59831 -2.35523 217s bmi 0.94825 3.55791 2.09860 19.51489 17.20331 0.24347 -6.88221 217s ped 0.12076 0.68833 0.45672 0.59831 0.24347 0.05933 0.43798 217s age 22.64860 32.28061 31.17602 -2.35523 -6.88221 0.43798 111.16709 217s Call: 217s QdaClassic(as.factor(gr) ~ ., data = hemophilia) 217s 217s Prior Probabilities of Groups: 217s carrier normal 217s 0.6 0.4 217s 217s Group means: 217s AHFactivity AHFantigen 217s carrier -0.30795 -0.0059911 217s normal -0.13487 -0.0778567 217s 217s Group: carrier 217s AHFactivity AHFantigen 217s AHFactivity 0.023784 0.015376 217s AHFantigen 0.015376 0.024035 217s 217s Group: normal 217s AHFactivity AHFantigen 217s AHFactivity 0.020897 0.015515 217s AHFantigen 0.015515 0.017920 217s Call: 217s QdaClassic(Treat ~ ., data = anorexia) 217s 217s Prior Probabilities of Groups: 217s CBT Cont FT 217s 0.40278 0.36111 0.23611 217s 217s Group means: 217s Prewt Postwt 217s CBT 82.690 85.697 217s Cont 81.558 81.108 217s FT 83.229 90.494 217s 217s Group: CBT 217s Prewt Postwt 217s Prewt 23.479 19.910 217s Postwt 19.910 69.755 217s 217s Group: Cont 217s Prewt Postwt 217s Prewt 32.5705 -4.3705 217s Postwt -4.3705 22.5079 217s 217s Group: FT 217s Prewt Postwt 217s Prewt 25.167 22.883 217s Postwt 22.883 71.827 217s Call: 217s QdaClassic(type ~ ., data = Pima.tr) 217s 217s Prior Probabilities of Groups: 217s No Yes 217s 0.66 0.34 217s 217s Group means: 217s npreg glu bp skin bmi ped age 217s No 2.9167 113.11 69.545 27.205 31.074 0.41548 29.235 217s Yes 4.8382 145.06 74.588 33.118 34.709 0.54866 37.691 217s 217s Group: No 217s npreg glu bp skin bmi ped age 217s npreg 7.878499 10.77226 8.190840 2.910305 -0.035751 -0.207341 16.82888 217s glu 10.772265 709.56118 81.430257 13.237682 19.037867 -0.518609 59.01307 217s bp 8.190840 81.43026 122.845246 33.879944 16.612630 -0.077183 46.78695 217s skin 2.910305 13.23768 33.879944 119.446391 50.125920 0.074282 18.47068 217s bmi -0.035751 19.03787 16.612630 50.125920 40.722996 0.145242 6.99999 217s ped -0.207341 -0.51861 -0.077183 0.074282 0.145242 0.071388 -0.53814 217s age 16.828880 59.01307 46.786954 18.470680 6.999988 -0.538138 91.08183 217s 217s Group: Yes 217s npreg glu bp skin bmi ped age 217s npreg 15.77941 -8.199298 6.42493 -0.51800 -1.03288 -0.133011 21.93437 217s glu -8.19930 907.250219 23.71115 87.51536 9.98156 -0.082159 58.12291 217s bp 6.42493 23.711150 134.18613 19.70588 5.15891 -0.795470 26.30378 217s skin -0.51800 87.515364 19.70588 151.32924 28.28551 0.347951 26.67867 217s bmi -1.03288 9.981563 5.15891 28.28551 23.14529 0.457694 -7.91216 217s ped -0.13301 -0.082159 -0.79547 0.34795 0.45769 0.128883 -0.41737 217s age 21.93437 58.122915 26.30378 26.67867 -7.91216 -0.417375 131.79873 217s Call: 217s QdaClassic(Species ~ ., data = iris) 217s 217s Prior Probabilities of Groups: 217s setosa versicolor virginica 217s 0.33333 0.33333 0.33333 217s 217s Group means: 217s Sepal.Length Sepal.Width Petal.Length Petal.Width 217s setosa 5.006 3.428 1.462 0.246 217s versicolor 5.936 2.770 4.260 1.326 217s virginica 6.588 2.974 5.552 2.026 217s 217s Group: setosa 217s Sepal.Length Sepal.Width Petal.Length Petal.Width 217s Sepal.Length 0.124249 0.099216 0.0163551 0.0103306 217s Sepal.Width 0.099216 0.143690 0.0116980 0.0092980 217s Petal.Length 0.016355 0.011698 0.0301592 0.0060694 217s Petal.Width 0.010331 0.009298 0.0060694 0.0111061 217s 217s Group: versicolor 217s Sepal.Length Sepal.Width Petal.Length Petal.Width 217s Sepal.Length 0.266433 0.085184 0.182898 0.055780 217s Sepal.Width 0.085184 0.098469 0.082653 0.041204 217s Petal.Length 0.182898 0.082653 0.220816 0.073102 217s Petal.Width 0.055780 0.041204 0.073102 0.039106 217s 217s Group: virginica 217s Sepal.Length Sepal.Width Petal.Length Petal.Width 217s Sepal.Length 0.404343 0.093763 0.303290 0.049094 217s Sepal.Width 0.093763 0.104004 0.071380 0.047629 217s Petal.Length 0.303290 0.071380 0.304588 0.048824 217s Petal.Width 0.049094 0.047629 0.048824 0.075433 217s =================================================== 217s > dodata(method="sde") 217s 217s Call: dodata(method = "sde") 217s =================================================== 217s Call: 217s QdaCov(as.factor(gr) ~ ., data = hemophilia, method = method) 217s 217s Prior Probabilities of Groups: 217s carrier normal 217s 0.6 0.4 217s 217s Group means: 217s AHFactivity AHFantigen 217s carrier -0.29834 -0.0032286 217s normal -0.12944 -0.0676930 217s 217s Group: carrier 217s AHFactivity AHFantigen 217s AHFactivity 0.025398 0.017810 217s AHFantigen 0.017810 0.030639 217s 217s Group: normal 217s AHFactivity AHFantigen 217s AHFactivity 0.0083435 0.0067686 217s AHFantigen 0.0067686 0.0119565 217s Call: 217s QdaCov(Treat ~ ., data = anorexia, method = method) 217s 217s Prior Probabilities of Groups: 217s CBT Cont FT 217s 0.40278 0.36111 0.23611 217s 217s Group means: 217s Prewt Postwt 217s CBT 82.949 83.323 217s Cont 81.484 80.840 217s FT 84.596 93.835 217s 217s Group: CBT 217s Prewt Postwt 217s Prewt 22.283 17.084 217s Postwt 17.084 25.308 217s 217s Group: Cont 217s Prewt Postwt 217s Prewt 37.1864 -8.8896 217s Postwt -8.8896 31.1930 217s 217s Group: FT 217s Prewt Postwt 217s Prewt 20.7108 3.1531 217s Postwt 3.1531 25.7046 217s Call: 217s QdaCov(type ~ ., data = Pima.tr, method = method) 217s 217s Prior Probabilities of Groups: 217s No Yes 217s 0.66 0.34 217s 217s Group means: 217s npreg glu bp skin bmi ped age 217s No 2.2567 109.91 67.538 25.484 30.355 0.38618 25.628 217s Yes 5.2216 141.64 75.048 32.349 34.387 0.47742 37.634 217s 217s Group: No 217s npreg glu bp skin bmi ped age 217s npreg 4.396832 10.20629 5.43346 4.38313 7.9891e-01 -0.09389257 7.45638 217s glu 10.206286 601.12211 56.62047 49.67071 3.3829e+01 -0.31896741 31.64508 217s bp 5.433462 56.62047 120.38052 34.38984 1.4817e+01 -0.21784446 26.44853 217s skin 4.383134 49.67071 34.38984 136.94931 6.1576e+01 -0.47532490 17.74141 217s bmi 0.798908 33.82928 14.81668 61.57578 5.1441e+01 0.00061983 8.56856 217s ped -0.093893 -0.31897 -0.21784 -0.47532 6.1983e-04 0.06012655 -0.26872 217s age 7.456376 31.64508 26.44853 17.74141 8.5686e+00 -0.26872005 29.93856 217s 217s Group: Yes 217s npreg glu bp skin bmi ped age 217s npreg 15.91978 7.7491 7.24229 10.46802 5.40627 0.320434 25.88314 217s glu 7.74907 856.4955 58.59554 29.65331 11.44745 1.388745 38.24430 217s bp 7.24229 58.5955 89.66288 21.36597 6.46859 0.764486 36.30462 217s skin 10.46802 29.6533 21.36597 86.79253 26.22071 0.620654 5.28665 217s bmi 5.40627 11.4475 6.46859 26.22071 20.12351 0.211701 0.71583 217s ped 0.32043 1.3887 0.76449 0.62065 0.21170 0.062727 0.93743 217s age 25.88314 38.2443 36.30462 5.28665 0.71583 0.937430 136.24335 217s Call: 217s QdaClassic(as.factor(gr) ~ ., data = hemophilia) 217s 217s Prior Probabilities of Groups: 217s carrier normal 217s 0.6 0.4 217s 217s Group means: 217s AHFactivity AHFantigen 217s carrier -0.30795 -0.0059911 217s normal -0.13487 -0.0778567 217s 217s Group: carrier 217s AHFactivity AHFantigen 217s AHFactivity 0.023784 0.015376 217s AHFantigen 0.015376 0.024035 217s 217s Group: normal 217s AHFactivity AHFantigen 217s AHFactivity 0.020897 0.015515 217s AHFantigen 0.015515 0.017920 217s Call: 217s QdaClassic(Treat ~ ., data = anorexia) 217s 217s Prior Probabilities of Groups: 217s CBT Cont FT 217s 0.40278 0.36111 0.23611 217s 217s Group means: 217s Prewt Postwt 217s CBT 82.690 85.697 217s Cont 81.558 81.108 217s FT 83.229 90.494 217s 217s Group: CBT 217s Prewt Postwt 217s Prewt 23.479 19.910 217s Postwt 19.910 69.755 217s 217s Group: Cont 217s Prewt Postwt 217s Prewt 32.5705 -4.3705 217s Postwt -4.3705 22.5079 217s 217s Group: FT 217s Prewt Postwt 217s Prewt 25.167 22.883 217s Postwt 22.883 71.827 217s Call: 217s QdaClassic(type ~ ., data = Pima.tr) 217s 217s Prior Probabilities of Groups: 217s No Yes 217s 0.66 0.34 217s 217s Group means: 217s npreg glu bp skin bmi ped age 217s No 2.9167 113.11 69.545 27.205 31.074 0.41548 29.235 217s Yes 4.8382 145.06 74.588 33.118 34.709 0.54866 37.691 217s 217s Group: No 217s npreg glu bp skin bmi ped age 217s npreg 7.878499 10.77226 8.190840 2.910305 -0.035751 -0.207341 16.82888 217s glu 10.772265 709.56118 81.430257 13.237682 19.037867 -0.518609 59.01307 217s bp 8.190840 81.43026 122.845246 33.879944 16.612630 -0.077183 46.78695 217s skin 2.910305 13.23768 33.879944 119.446391 50.125920 0.074282 18.47068 217s bmi -0.035751 19.03787 16.612630 50.125920 40.722996 0.145242 6.99999 217s ped -0.207341 -0.51861 -0.077183 0.074282 0.145242 0.071388 -0.53814 217s age 16.828880 59.01307 46.786954 18.470680 6.999988 -0.538138 91.08183 217s 217s Group: Yes 217s npreg glu bp skin bmi ped age 217s npreg 15.77941 -8.199298 6.42493 -0.51800 -1.03288 -0.133011 21.93437 217s glu -8.19930 907.250219 23.71115 87.51536 9.98156 -0.082159 58.12291 217s bp 6.42493 23.711150 134.18613 19.70588 5.15891 -0.795470 26.30378 217s skin -0.51800 87.515364 19.70588 151.32924 28.28551 0.347951 26.67867 217s bmi -1.03288 9.981563 5.15891 28.28551 23.14529 0.457694 -7.91216 217s ped -0.13301 -0.082159 -0.79547 0.34795 0.45769 0.128883 -0.41737 217s age 21.93437 58.122915 26.30378 26.67867 -7.91216 -0.417375 131.79873 217s Call: 217s QdaClassic(Species ~ ., data = iris) 217s 217s Prior Probabilities of Groups: 217s setosa versicolor virginica 217s 0.33333 0.33333 0.33333 217s 217s Group means: 217s Sepal.Length Sepal.Width Petal.Length Petal.Width 217s setosa 5.006 3.428 1.462 0.246 217s versicolor 5.936 2.770 4.260 1.326 217s virginica 6.588 2.974 5.552 2.026 217s 217s Group: setosa 217s Sepal.Length Sepal.Width Petal.Length Petal.Width 217s Sepal.Length 0.124249 0.099216 0.0163551 0.0103306 217s Sepal.Width 0.099216 0.143690 0.0116980 0.0092980 217s Petal.Length 0.016355 0.011698 0.0301592 0.0060694 217s Petal.Width 0.010331 0.009298 0.0060694 0.0111061 217s 217s Group: versicolor 217s Sepal.Length Sepal.Width Petal.Length Petal.Width 217s Sepal.Length 0.266433 0.085184 0.182898 0.055780 217s Sepal.Width 0.085184 0.098469 0.082653 0.041204 217s Petal.Length 0.182898 0.082653 0.220816 0.073102 217s Petal.Width 0.055780 0.041204 0.073102 0.039106 217s 217s Group: virginica 217s Sepal.Length Sepal.Width Petal.Length Petal.Width 217s Sepal.Length 0.404343 0.093763 0.303290 0.049094 217s Sepal.Width 0.093763 0.104004 0.071380 0.047629 217s Petal.Length 0.303290 0.071380 0.304588 0.048824 217s Petal.Width 0.049094 0.047629 0.048824 0.075433 217s =================================================== 217s > 217s BEGIN TEST tsde.R 217s 217s R version 4.5.2 (2025-10-31) -- "[Not] Part in a Rumble" 217s Copyright (C) 2025 The R Foundation for Statistical Computing 217s Platform: aarch64-unknown-linux-gnu 217s 217s R is free software and comes with ABSOLUTELY NO WARRANTY. 217s You are welcome to redistribute it under certain conditions. 217s Type 'license()' or 'licence()' for distribution details. 217s 217s R is a collaborative project with many contributors. 217s Type 'contributors()' for more information and 217s 'citation()' on how to cite R or R packages in publications. 217s 217s Type 'demo()' for some demos, 'help()' for on-line help, or 217s 'help.start()' for an HTML browser interface to help. 217s Type 'q()' to quit R. 217s 217s > ## Test for singularity 217s > doexact <- function(){ 217s + exact <-function(){ 217s + n1 <- 45 217s + p <- 2 217s + x1 <- matrix(rnorm(p*n1),nrow=n1, ncol=p) 217s + x1[,p] <- x1[,p] + 3 217s + ## library(MASS) 217s + ## x1 <- mvrnorm(n=n1, mu=c(0,3), Sigma=diag(1,nrow=p)) 217s + 217s + n2 <- 55 217s + m1 <- 0 217s + m2 <- 3 217s + x2 <- cbind(rnorm(n2),rep(m2,n2)) 217s + x<-rbind(x1,x2) 217s + colnames(x) <- c("X1","X2") 217s + x 217s + } 217s + print(CovSde(exact())) 217s + } 217s > 217s > dodata <- function(nrep=1, time=FALSE, short=FALSE, full=TRUE){ 217s + 217s + domcd <- function(x, xname, nrep=1){ 217s + n <- dim(x)[1] 217s + p <- dim(x)[2] 217s + 217s + mcd<-CovSde(x) 217s + 217s + if(time){ 217s + xtime <- system.time(dorep(x, nrep))[1]/nrep 217s + xres <- sprintf("%3d %3d %3d\n", dim(x)[1], dim(x)[2], xtime) 217s + } 217s + else{ 217s + xres <- sprintf("%3d %3d\n", dim(x)[1], dim(x)[2]) 217s + } 217s + lpad<-lname-nchar(xname) 217s + cat(pad.right(xname,lpad), xres) 217s + 217s + if(!short){ 217s + 217s + ibad <- which(mcd@wt==0) 217s + names(ibad) <- NULL 217s + nbad <- length(ibad) 217s + cat("Outliers: ",nbad,"\n") 217s + if(nbad > 0) 217s + print(ibad) 217s + if(full){ 217s + cat("-------------\n") 217s + show(mcd) 217s + } 217s + cat("--------------------------------------------------------\n") 217s + } 217s + } 217s + 217s + options(digits = 5) 217s + set.seed(101) # <<-- sub-sampling algorithm now based on R's RNG and seed 217s + 217s + lname <- 20 217s + 217s + ## VT::15.09.2013 - this will render the output independent 217s + ## from the version of the package 217s + suppressPackageStartupMessages(library(rrcov)) 217s + 217s + data(heart) 217s + data(starsCYG) 217s + data(phosphor) 217s + data(stackloss) 217s + data(coleman) 217s + data(salinity) 217s + data(wood) 217s + 217s + data(hbk) 217s + 217s + data(Animals, package = "MASS") 217s + brain <- Animals[c(1:24, 26:25, 27:28),] 217s + data(milk) 217s + data(bushfire) 217s + 217s + tmp <- sys.call() 217s + cat("\nCall: ", deparse(substitute(tmp)),"\n") 217s + 217s + cat("Data Set n p Half LOG(obj) Time\n") 217s + cat("========================================================\n") 217s + domcd(heart[, 1:2], data(heart), nrep) 217s + domcd(starsCYG, data(starsCYG), nrep) 217s + domcd(data.matrix(subset(phosphor, select = -plant)), data(phosphor), nrep) 217s + domcd(stack.x, data(stackloss), nrep) 217s + domcd(data.matrix(subset(coleman, select = -Y)), data(coleman), nrep) 217s + domcd(data.matrix(subset(salinity, select = -Y)), data(salinity), nrep) 217s + domcd(data.matrix(subset(wood, select = -y)), data(wood), nrep) 217s + domcd(data.matrix(subset(hbk, select = -Y)),data(hbk), nrep) 217s + 217s + domcd(brain, "Animals", nrep) 217s + domcd(milk, data(milk), nrep) 217s + domcd(bushfire, data(bushfire), nrep) 217s + ## VT::19.07.2010: test the univariate SDE 217s + for(i in 1:ncol(bushfire)) 217s + domcd(bushfire[i], data(bushfire), nrep) 217s + cat("========================================================\n") 217s + } 217s > 217s > dogen <- function(nrep=1, eps=0.49){ 217s + 217s + library(MASS) 217s + domcd <- function(x, nrep=1){ 217s + gc() 217s + xtime <- system.time(dorep(x, nrep))[1]/nrep 217s + cat(sprintf("%6d %3d %10.2f\n", dim(x)[1], dim(x)[2], xtime)) 217s + xtime 217s + } 217s + 217s + set.seed(1234) 217s + 217s + ## VT::15.09.2013 - this will render the output independent 217s + ## from the version of the package 217s + suppressPackageStartupMessages(library(rrcov)) 217s + 217s + ap <- c(2, 5, 10, 20, 30) 217s + an <- c(100, 500, 1000, 10000, 50000) 217s + 217s + tottime <- 0 217s + cat(" n p Time\n") 217s + cat("=====================\n") 217s + for(i in 1:length(an)) { 217s + for(j in 1:length(ap)) { 217s + n <- an[i] 217s + p <- ap[j] 217s + if(5*p <= n){ 217s + xx <- gendata(n, p, eps) 217s + X <- xx$X 217s + tottime <- tottime + domcd(X, nrep) 217s + } 217s + } 217s + } 217s + 217s + cat("=====================\n") 217s + cat("Total time: ", tottime*nrep, "\n") 217s + } 217s > 217s > docheck <- function(n, p, eps){ 217s + xx <- gendata(n,p,eps) 217s + mcd <- CovSde(xx$X) 217s + check(mcd, xx$xind) 217s + } 217s > 217s > check <- function(mcd, xind){ 217s + ## check if mcd is robust w.r.t xind, i.e. check how many of xind 217s + ## did not get zero weight 217s + mymatch <- xind %in% which(mcd@wt == 0) 217s + length(xind) - length(which(mymatch)) 217s + } 217s > 217s > dorep <- function(x, nrep=1){ 217s + 217s + for(i in 1:nrep) 217s + CovSde(x) 217s + } 217s > 217s > #### gendata() #### 217s > # Generates a location contaminated multivariate 217s > # normal sample of n observations in p dimensions 217s > # (1-eps)*Np(0,Ip) + eps*Np(m,Ip) 217s > # where 217s > # m = (b,b,...,b) 217s > # Defaults: eps=0 and b=10 217s > # 217s > gendata <- function(n,p,eps=0,b=10){ 217s + 217s + if(missing(n) || missing(p)) 217s + stop("Please specify (n,p)") 217s + if(eps < 0 || eps >= 0.5) 217s + stop(message="eps must be in [0,0.5)") 217s + X <- mvrnorm(n,rep(0,p),diag(1,nrow=p,ncol=p)) 217s + nbad <- as.integer(eps * n) 217s + if(nbad > 0){ 217s + Xbad <- mvrnorm(nbad,rep(b,p),diag(1,nrow=p,ncol=p)) 217s + xind <- sample(n,nbad) 217s + X[xind,] <- Xbad 217s + } 217s + list(X=X, xind=xind) 217s + } 217s > 217s > pad.right <- function(z, pads) 217s + { 217s + ### Pads spaces to right of text 217s + padding <- paste(rep(" ", pads), collapse = "") 217s + paste(z, padding, sep = "") 217s + } 217s > 217s > whatis<-function(x){ 217s + if(is.data.frame(x)) 217s + cat("Type: data.frame\n") 217s + else if(is.matrix(x)) 217s + cat("Type: matrix\n") 217s + else if(is.vector(x)) 217s + cat("Type: vector\n") 217s + else 217s + cat("Type: don't know\n") 217s + } 217s > 217s > ## VT::15.09.2013 - this will render the output independent 217s > ## from the version of the package 217s > suppressPackageStartupMessages(library(rrcov)) 217s > 217s > dodata() 217s 217s Call: dodata() 217s Data Set n p Half LOG(obj) Time 217s ======================================================== 217s heart 12 2 217s Outliers: 5 217s [1] 2 6 8 10 12 217s ------------- 217s 217s Call: 217s CovSde(x = x) 217s -> Method: Stahel-Donoho estimator 217s 217s Robust Estimate of Location: 217s height weight 217s 39.8 35.7 217s 217s Robust Estimate of Covariance: 217s height weight 217s height 38.2 77.1 217s weight 77.1 188.1 217s -------------------------------------------------------- 217s starsCYG 47 2 217s Outliers: 7 217s [1] 7 9 11 14 20 30 34 217s ------------- 217s 217s Call: 217s CovSde(x = x) 217s -> Method: Stahel-Donoho estimator 217s 217s Robust Estimate of Location: 217s log.Te log.light 217s 4.42 4.96 217s 217s Robust Estimate of Covariance: 217s log.Te log.light 217s log.Te 0.0163 0.0522 217s log.light 0.0522 0.3243 217s -------------------------------------------------------- 217s phosphor 18 2 217s Outliers: 2 217s [1] 1 6 217s ------------- 217s 217s Call: 217s CovSde(x = x) 217s -> Method: Stahel-Donoho estimator 217s 217s Robust Estimate of Location: 217s inorg organic 217s 13.3 39.7 217s 217s Robust Estimate of Covariance: 217s inorg organic 217s inorg 133 134 217s organic 134 204 217s -------------------------------------------------------- 217s stackloss 21 3 217s Outliers: 6 217s [1] 1 2 3 15 17 21 217s ------------- 217s 217s Call: 217s CovSde(x = x) 217s -> Method: Stahel-Donoho estimator 217s 217s Robust Estimate of Location: 217s Air.Flow Water.Temp Acid.Conc. 217s 57.8 20.7 86.4 217s 217s Robust Estimate of Covariance: 217s Air.Flow Water.Temp Acid.Conc. 217s Air.Flow 39.7 15.6 25.0 217s Water.Temp 15.6 13.0 11.9 217s Acid.Conc. 25.0 11.9 40.3 217s -------------------------------------------------------- 217s coleman 20 5 217s Outliers: 8 217s [1] 1 2 6 10 11 12 15 18 217s ------------- 217s 217s Call: 217s CovSde(x = x) 217s -> Method: Stahel-Donoho estimator 217s 217s Robust Estimate of Location: 217s salaryP fatherWc sstatus teacherSc motherLev 217s 2.78 58.64 9.09 25.37 6.69 217s 217s Robust Estimate of Covariance: 217s salaryP fatherWc sstatus teacherSc motherLev 217s salaryP 0.2556 -1.0144 0.6599 0.2673 0.0339 217s fatherWc -1.0144 1615.9192 382.7846 -4.8287 36.0227 217s sstatus 0.6599 382.7846 108.1781 -0.7904 9.1027 217s teacherSc 0.2673 -4.8287 -0.7904 0.9346 -0.0239 217s motherLev 0.0339 36.0227 9.1027 -0.0239 0.9155 217s -------------------------------------------------------- 217s salinity 28 3 217s Outliers: 9 217s [1] 3 4 5 9 11 16 19 23 24 217s ------------- 217s 217s Call: 217s CovSde(x = x) 217s -> Method: Stahel-Donoho estimator 217s 217s Robust Estimate of Location: 217s X1 X2 X3 217s 10.84 3.35 22.48 217s 217s Robust Estimate of Covariance: 217s X1 X2 X3 217s X1 10.75 -1.62 -2.05 217s X2 -1.62 4.21 -1.43 217s X3 -2.05 -1.43 2.63 217s -------------------------------------------------------- 217s wood 20 5 217s Outliers: 11 217s [1] 4 6 7 8 9 10 12 13 16 19 20 217s ------------- 217s 217s Call: 217s CovSde(x = x) 217s -> Method: Stahel-Donoho estimator 217s 217s Robust Estimate of Location: 217s x1 x2 x3 x4 x5 217s 0.573 0.119 0.517 0.549 0.904 217s 217s Robust Estimate of Covariance: 217s x1 x2 x3 x4 x5 217s x1 0.025185 0.004279 -0.001262 -0.000382 -0.001907 217s x2 0.004279 0.001011 0.000197 -0.000117 0.000247 217s x3 -0.001262 0.000197 0.003042 0.002034 0.001773 217s x4 -0.000382 -0.000117 0.002034 0.007943 0.001137 217s x5 -0.001907 0.000247 0.001773 0.001137 0.005392 217s -------------------------------------------------------- 217s hbk 75 3 217s Outliers: 15 217s [1] 1 2 3 4 5 6 7 8 9 10 11 12 13 14 53 217s ------------- 217s 217s Call: 217s CovSde(x = x) 217s -> Method: Stahel-Donoho estimator 217s 217s Robust Estimate of Location: 217s X1 X2 X3 217s 1.59 1.79 1.67 217s 217s Robust Estimate of Covariance: 217s X1 X2 X3 217s X1 1.6354 0.0793 0.2284 217s X2 0.0793 1.6461 0.3186 217s X3 0.2284 0.3186 1.5673 217s -------------------------------------------------------- 217s Animals 28 2 217s Outliers: 13 217s [1] 2 6 7 8 9 12 13 14 15 16 24 25 28 217s ------------- 217s 217s Call: 217s CovSde(x = x) 217s -> Method: Stahel-Donoho estimator 217s 217s Robust Estimate of Location: 217s body brain 217s 18.7 64.9 217s 217s Robust Estimate of Covariance: 217s body brain 217s body 4702 7973 217s brain 7973 28571 217s -------------------------------------------------------- 217s milk 86 8 217s Outliers: 21 217s [1] 1 2 3 6 11 12 13 14 15 16 17 18 20 27 41 44 47 70 74 75 77 217s ------------- 217s 217s Call: 217s CovSde(x = x) 217s -> Method: Stahel-Donoho estimator 217s 217s Robust Estimate of Location: 217s X1 X2 X3 X4 X5 X6 X7 X8 217s 1.03 35.90 33.04 26.11 25.10 25.02 123.06 14.37 217s 217s Robust Estimate of Covariance: 217s X1 X2 X3 X4 X5 X6 X7 217s X1 4.73e-07 6.57e-05 1.79e-04 1.71e-04 1.62e-04 1.42e-04 6.85e-04 217s X2 6.57e-05 1.57e+00 1.36e-01 9.28e-02 4.18e-02 1.30e-01 1.58e+00 217s X3 1.79e-04 1.36e-01 1.12e+00 8.20e-01 8.27e-01 8.00e-01 6.66e-01 217s X4 1.71e-04 9.28e-02 8.20e-01 6.57e-01 6.41e-01 6.18e-01 5.47e-01 217s X5 1.62e-04 4.18e-02 8.27e-01 6.41e-01 6.93e-01 6.44e-01 5.71e-01 217s X6 1.42e-04 1.30e-01 8.00e-01 6.18e-01 6.44e-01 6.44e-01 5.55e-01 217s X7 6.85e-04 1.58e+00 6.66e-01 5.47e-01 5.71e-01 5.55e-01 4.17e+00 217s X8 1.40e-05 2.33e-01 1.74e-01 1.06e-01 9.44e-02 9.86e-02 3.54e-01 217s X8 217s X1 1.40e-05 217s X2 2.33e-01 217s X3 1.74e-01 217s X4 1.06e-01 217s X5 9.44e-02 217s X6 9.86e-02 217s X7 3.54e-01 217s X8 1.57e-01 217s -------------------------------------------------------- 218s bushfire 38 5 218s Outliers: 23 218s [1] 1 5 6 7 8 9 10 11 12 13 15 16 28 29 30 31 32 33 34 35 36 37 38 218s ------------- 218s 218s Call: 218s CovSde(x = x) 218s -> Method: Stahel-Donoho estimator 218s 218s Robust Estimate of Location: 218s V1 V2 V3 V4 V5 218s 105 148 287 223 283 218s 218s Robust Estimate of Covariance: 218s V1 V2 V3 V4 V5 218s V1 1964 1712 -10230 -2504 -2066 218s V2 1712 1526 -8732 -2145 -1763 218s V3 -10230 -8732 56327 13803 11472 218s V4 -2504 -2145 13803 3509 2894 218s V5 -2066 -1763 11472 2894 2404 218s -------------------------------------------------------- 218s bushfire 38 1 218s Outliers: 2 218s [1] 13 30 218s ------------- 218s 218s Call: 218s CovSde(x = x) 218s -> Method: Stahel-Donoho estimator 218s 218s Robust Estimate of Location: 218s V1 218s 98.5 218s 218s Robust Estimate of Covariance: 218s V1 218s V1 431 218s -------------------------------------------------------- 218s bushfire 38 1 218s Outliers: 6 218s [1] 33 34 35 36 37 38 218s ------------- 218s 218s Call: 218s CovSde(x = x) 218s -> Method: Stahel-Donoho estimator 218s 218s Robust Estimate of Location: 218s V2 218s 141 218s 218s Robust Estimate of Covariance: 218s V2 218s V2 528 218s -------------------------------------------------------- 218s bushfire 38 1 218s Outliers: 0 218s ------------- 218s 218s Call: 218s CovSde(x = x) 218s -> Method: Stahel-Donoho estimator 218s 218s Robust Estimate of Location: 218s V3 218s 238 218s 218s Robust Estimate of Covariance: 218s V3 218s V3 37148 218s -------------------------------------------------------- 218s bushfire 38 1 218s Outliers: 9 218s [1] 8 9 32 33 34 35 36 37 38 218s ------------- 218s 218s Call: 218s CovSde(x = x) 218s -> Method: Stahel-Donoho estimator 218s 218s Robust Estimate of Location: 218s V4 218s 210 218s 218s Robust Estimate of Covariance: 218s V4 218s V4 2543 218s -------------------------------------------------------- 218s bushfire 38 1 218s Outliers: 9 218s [1] 8 9 32 33 34 35 36 37 38 218s ------------- 218s 218s Call: 218s CovSde(x = x) 218s -> Method: Stahel-Donoho estimator 218s 218s Robust Estimate of Location: 218s V5 218s 273 218s 218s Robust Estimate of Covariance: 218s V5 218s V5 1575 218s -------------------------------------------------------- 218s ======================================================== 218s > ##doexact() 218s > 218s BEGIN TEST tsest.R 218s 218s R version 4.5.2 (2025-10-31) -- "[Not] Part in a Rumble" 218s Copyright (C) 2025 The R Foundation for Statistical Computing 218s Platform: aarch64-unknown-linux-gnu 218s 218s R is free software and comes with ABSOLUTELY NO WARRANTY. 218s You are welcome to redistribute it under certain conditions. 218s Type 'license()' or 'licence()' for distribution details. 218s 218s R is a collaborative project with many contributors. 218s Type 'contributors()' for more information and 218s 'citation()' on how to cite R or R packages in publications. 218s 218s Type 'demo()' for some demos, 'help()' for on-line help, or 218s 'help.start()' for an HTML browser interface to help. 218s Type 'q()' to quit R. 218s 218s > ## VT::15.09.2013 - this will render the output independent 218s > ## from the version of the package 218s > suppressPackageStartupMessages(library(rrcov)) 218s > 218s > library(MASS) 218s > 218s > dodata <- function(nrep = 1, time = FALSE, full = TRUE, method) { 218s + doest <- function(x, xname, nrep = 1, method=c("sfast", "surreal", "bisquare", "rocke", "suser", "MM", "sdet")) { 218s + 218s + method <- match.arg(method) 218s + 218s + lname <- 20 218s + n <- dim(x)[1] 218s + p <- dim(x)[2] 218s + 218s + mm <- if(method == "MM") CovMMest(x) else CovSest(x, method=method) 218s + 218s + crit <- log(mm@crit) 218s + 218s + xres <- sprintf("%3d %3d %12.6f\n", dim(x)[1], dim(x)[2], crit) 218s + lpad <- lname-nchar(xname) 218s + cat(pad.right(xname,lpad), xres) 218s + 218s + dist <- getDistance(mm) 218s + quantiel <- qchisq(0.975, p) 218s + ibad <- which(dist >= quantiel) 218s + names(ibad) <- NULL 218s + nbad <- length(ibad) 218s + cat("Outliers: ",nbad,"\n") 218s + if(nbad > 0) 218s + print(ibad) 218s + cat("-------------\n") 218s + show(mm) 218s + cat("--------------------------------------------------------\n") 218s + } 218s + 218s + options(digits = 5) 218s + set.seed(101) # <<-- sub-sampling algorithm now based on R's RNG and seed 218s + 218s + data(heart) 218s + data(starsCYG) 218s + data(phosphor) 218s + data(stackloss) 218s + data(coleman) 218s + data(salinity) 218s + data(wood) 218s + data(hbk) 218s + 218s + data(Animals, package = "MASS") 218s + brain <- Animals[c(1:24, 26:25, 27:28),] 218s + data(milk) 218s + data(bushfire) 218s + ### 218s + data(rice) 218s + data(hemophilia) 218s + data(fish) 218s + 218s + tmp <- sys.call() 218s + cat("\nCall: ", deparse(substitute(tmp)),"\n") 218s + 218s + cat("Data Set n p LOG(det) Time\n") 218s + cat("===================================================\n") 218s + doest(heart[, 1:2], data(heart), nrep, method=method) 218s + doest(starsCYG, data(starsCYG), nrep, method=method) 218s + doest(data.matrix(subset(phosphor, select = -plant)), data(phosphor), nrep, method=method) 218s + doest(stack.x, data(stackloss), nrep, method=method) 218s + doest(data.matrix(subset(coleman, select = -Y)), data(coleman), nrep, method=method) 218s + doest(data.matrix(subset(salinity, select = -Y)), data(salinity), nrep, method=method) 218s + doest(data.matrix(subset(wood, select = -y)), data(wood), nrep, method=method) 218s + doest(data.matrix(subset(hbk, select = -Y)), data(hbk), nrep, method=method) 218s + 218s + 218s + doest(brain, "Animals", nrep, method=method) 218s + doest(milk, data(milk), nrep, method=method) 218s + doest(bushfire, data(bushfire), nrep, method=method) 218s + 218s + doest(data.matrix(subset(rice, select = -Overall_evaluation)), data(rice), nrep, method=method) 218s + doest(data.matrix(subset(hemophilia, select = -gr)), data(hemophilia), nrep, method=method) 218s + doest(data.matrix(subset(fish, select = -Species)), data(fish), nrep, method=method) 218s + 218s + ## from package 'datasets' 218s + doest(airquality[,1:4], data(airquality), nrep, method=method) 218s + doest(attitude, data(attitude), nrep, method=method) 218s + doest(attenu, data(attenu), nrep, method=method) 218s + doest(USJudgeRatings, data(USJudgeRatings), nrep, method=method) 218s + doest(USArrests, data(USArrests), nrep, method=method) 218s + doest(longley, data(longley), nrep, method=method) 218s + doest(Loblolly, data(Loblolly), nrep, method=method) 218s + doest(quakes[,1:4], data(quakes), nrep, method=method) 218s + 218s + cat("===================================================\n") 218s + } 218s > 218s > # generate contaminated data using the function gendata with different 218s > # number of outliers and check if the M-estimate breaks - i.e. the 218s > # largest eigenvalue is larger than e.g. 5. 218s > # For n=50 and p=10 and d=5 the M-estimate can break for number of 218s > # outliers grater than 20. 218s > dogen <- function(){ 218s + eig <- vector("numeric",26) 218s + for(i in 0:25) { 218s + gg <- gendata(eps=i) 218s + mm <- CovSRocke(gg$x, t0=gg$tgood, S0=gg$sgood) 218s + eig[i+1] <- ev <- getEvals(mm)[1] 218s + cat(i, ev, "\n") 218s + 218s + ## stopifnot(ev < 5 || i > 20) 218s + } 218s + plot(0:25, eig, type="l", xlab="Number of outliers", ylab="Largest Eigenvalue") 218s + } 218s > 218s > # 218s > # generate data 50x10 as multivariate normal N(0,I) and add 218s > # eps % outliers by adding d=5.0 to each component. 218s > # - if eps <0 and eps <=0.5, the number of outliers is eps*n 218s > # - if eps >= 1, it is the number of outliers 218s > # - use the center and cov of the good data as good start 218s > # - use the center and the cov of all data as a bad start 218s > # If using a good start, the M-estimate must iterate to 218s > # the good solution: the largest eigenvalue is less then e.g. 5 218s > # 218s > gendata <- function(n=50, p=10, eps=0, d=5.0){ 218s + 218s + if(eps < 0 || eps > 0.5 && eps < 1.0 || eps > 0.5*n) 218s + stop("eps is out of range") 218s + 218s + library(MASS) 218s + 218s + x <- mvrnorm(n, rep(0,p), diag(p)) 218s + bad <- vector("numeric") 218s + nbad = if(eps < 1) eps*n else eps 218s + if(nbad > 0){ 218s + bad <- sample(n, nbad) 218s + x[bad,] <- x[bad,] + d 218s + } 218s + cov1 <- cov.wt(x) 218s + cov2 <- if(nbad <= 0) cov1 else cov.wt(x[-bad,]) 218s + 218s + list(x=x, bad=sort(bad), tgood=cov2$center, sgood=cov2$cov, tbad=cov1$center, sbad=cov1$cov) 218s + } 218s > 218s > pad.right <- function(z, pads) 218s + { 218s + ## Pads spaces to right of text 218s + padding <- paste(rep(" ", pads), collapse = "") 218s + paste(z, padding, sep = "") 218s + } 218s > 218s > 218s > ## -- now do it: 218s > dodata(method="sfast") 218s 218s Call: dodata(method = "sfast") 218s Data Set n p LOG(det) Time 218s =================================================== 218s heart 12 2 2.017701 218s Outliers: 3 218s [1] 2 6 12 218s ------------- 218s 218s Call: 218s CovSest(x = x, method = method) 218s -> Method: S-estimates: S-FAST 218s 218s Robust Estimate of Location: 218s [1] 36.1 29.5 218s 218s Robust Estimate of Covariance: 218s height weight 218s height 129 210 218s weight 210 365 218s -------------------------------------------------------- 218s starsCYG 47 2 -1.450032 218s Outliers: 7 218s [1] 7 9 11 14 20 30 34 218s ------------- 218s 218s Call: 218s CovSest(x = x, method = method) 218s -> Method: S-estimates: S-FAST 218s 218s Robust Estimate of Location: 218s [1] 4.42 4.97 218s 218s Robust Estimate of Covariance: 218s log.Te log.light 218s log.Te 0.0176 0.0617 218s log.light 0.0617 0.3880 218s -------------------------------------------------------- 218s phosphor 18 2 2.320721 218s Outliers: 2 218s [1] 1 6 218s ------------- 218s 218s Call: 218s CovSest(x = x, method = method) 218s -> Method: S-estimates: S-FAST 218s 218s Robust Estimate of Location: 218s [1] 14.1 38.8 218s 218s Robust Estimate of Covariance: 218s inorg organic 218s inorg 174 190 218s organic 190 268 218s -------------------------------------------------------- 218s stackloss 21 3 1.470031 218s Outliers: 3 218s [1] 1 2 3 218s ------------- 218s 218s Call: 218s CovSest(x = x, method = method) 218s -> Method: S-estimates: S-FAST 218s 218s Robust Estimate of Location: 218s [1] 57.5 20.5 86.0 218s 218s Robust Estimate of Covariance: 218s Air.Flow Water.Temp Acid.Conc. 218s Air.Flow 38.94 11.66 22.89 218s Water.Temp 11.66 9.96 7.81 218s Acid.Conc. 22.89 7.81 40.48 218s -------------------------------------------------------- 218s coleman 20 5 0.491419 218s Outliers: 2 218s [1] 6 10 218s ------------- 218s 218s Call: 218s CovSest(x = x, method = method) 218s -> Method: S-estimates: S-FAST 218s 218s Robust Estimate of Location: 218s [1] 2.77 45.58 4.13 25.13 6.39 218s 218s Robust Estimate of Covariance: 218s salaryP fatherWc sstatus teacherSc motherLev 218s salaryP 0.2209 1.9568 1.4389 0.2638 0.0674 218s fatherWc 1.9568 940.7409 307.8297 8.3290 21.9143 218s sstatus 1.4389 307.8297 134.0540 4.1808 7.4799 218s teacherSc 0.2638 8.3290 4.1808 0.7604 0.2917 218s motherLev 0.0674 21.9143 7.4799 0.2917 0.5817 218s -------------------------------------------------------- 218s salinity 28 3 0.734619 218s Outliers: 4 218s [1] 5 16 23 24 218s ------------- 218s 218s Call: 218s CovSest(x = x, method = method) 218s -> Method: S-estimates: S-FAST 218s 218s Robust Estimate of Location: 218s [1] 10.31 3.07 22.60 218s 218s Robust Estimate of Covariance: 218s X1 X2 X3 218s X1 13.200 0.784 -3.611 218s X2 0.784 4.441 -1.658 218s X3 -3.611 -1.658 2.877 218s -------------------------------------------------------- 218s wood 20 5 -3.202636 218s Outliers: 2 218s [1] 7 9 218s ------------- 218s 218s Call: 218s CovSest(x = x, method = method) 218s -> Method: S-estimates: S-FAST 218s 218s Robust Estimate of Location: 218s [1] 0.551 0.135 0.496 0.511 0.916 218s 218s Robust Estimate of Covariance: 218s x1 x2 x3 x4 x5 218s x1 0.011361 -0.000791 0.005473 0.004204 -0.004747 218s x2 -0.000791 0.000701 -0.000534 -0.001452 0.000864 218s x3 0.005473 -0.000534 0.004905 0.002960 -0.001914 218s x4 0.004204 -0.001452 0.002960 0.005154 -0.002187 218s x5 -0.004747 0.000864 -0.001914 -0.002187 0.003214 218s -------------------------------------------------------- 218s hbk 75 3 0.283145 218s Outliers: 14 218s [1] 1 2 3 4 5 6 7 8 9 10 11 12 13 14 218s ------------- 218s 218s Call: 218s CovSest(x = x, method = method) 218s -> Method: S-estimates: S-FAST 218s 218s Robust Estimate of Location: 218s [1] 1.53 1.83 1.66 218s 218s Robust Estimate of Covariance: 218s X1 X2 X3 218s X1 1.8091 0.0479 0.2446 218s X2 0.0479 1.8190 0.2513 218s X3 0.2446 0.2513 1.7288 218s -------------------------------------------------------- 218s Animals 28 2 4.685129 218s Outliers: 10 218s [1] 2 6 7 9 12 14 15 16 24 25 218s ------------- 218s 218s Call: 218s CovSest(x = x, method = method) 218s -> Method: S-estimates: S-FAST 218s 218s Robust Estimate of Location: 218s [1] 30.8 84.2 218s 218s Robust Estimate of Covariance: 218s body brain 218s body 14806 28767 218s brain 28767 65195 218s -------------------------------------------------------- 218s milk 86 8 -1.437863 218s Outliers: 15 218s [1] 1 2 3 12 13 14 15 16 17 41 44 47 70 74 75 218s ------------- 218s 218s Call: 218s CovSest(x = x, method = method) 218s -> Method: S-estimates: S-FAST 218s 218s Robust Estimate of Location: 218s [1] 1.03 35.81 32.97 26.04 25.02 24.94 122.81 14.36 218s 218s Robust Estimate of Covariance: 218s X1 X2 X3 X4 X5 X6 X7 218s X1 8.30e-07 2.53e-04 4.43e-04 4.02e-04 3.92e-04 3.96e-04 1.44e-03 218s X2 2.53e-04 2.24e+00 4.77e-01 3.63e-01 2.91e-01 3.94e-01 2.44e+00 218s X3 4.43e-04 4.77e-01 1.58e+00 1.20e+00 1.18e+00 1.19e+00 1.65e+00 218s X4 4.02e-04 3.63e-01 1.20e+00 9.74e-01 9.37e-01 9.39e-01 1.39e+00 218s X5 3.92e-04 2.91e-01 1.18e+00 9.37e-01 9.78e-01 9.44e-01 1.37e+00 218s X6 3.96e-04 3.94e-01 1.19e+00 9.39e-01 9.44e-01 9.82e-01 1.41e+00 218s X7 1.44e-03 2.44e+00 1.65e+00 1.39e+00 1.37e+00 1.41e+00 6.96e+00 218s X8 7.45e-05 3.33e-01 2.82e-01 2.01e-01 1.80e-01 1.91e-01 6.38e-01 218s X8 218s X1 7.45e-05 218s X2 3.33e-01 218s X3 2.82e-01 218s X4 2.01e-01 218s X5 1.80e-01 218s X6 1.91e-01 218s X7 6.38e-01 218s X8 2.01e-01 218s -------------------------------------------------------- 218s bushfire 38 5 2.443148 218s Outliers: 13 218s [1] 7 8 9 10 11 31 32 33 34 35 36 37 38 218s ------------- 218s 218s Call: 218s CovSest(x = x, method = method) 218s -> Method: S-estimates: S-FAST 218s 218s Robust Estimate of Location: 218s [1] 108 149 266 216 278 218s 218s Robust Estimate of Covariance: 218s V1 V2 V3 V4 V5 218s V1 911 688 -3961 -856 -707 218s V2 688 587 -2493 -492 -420 218s V3 -3961 -2493 24146 5765 4627 218s V4 -856 -492 5765 1477 1164 218s V5 -707 -420 4627 1164 925 218s -------------------------------------------------------- 218s rice 105 5 -0.724874 218s Outliers: 7 218s [1] 9 40 42 49 57 58 71 218s ------------- 218s 218s Call: 218s CovSest(x = x, method = method) 218s -> Method: S-estimates: S-FAST 218s 218s Robust Estimate of Location: 218s [1] -0.2472 0.1211 -0.1207 0.0715 0.0640 218s 218s Robust Estimate of Covariance: 218s Favor Appearance Taste Stickiness Toughness 218s Favor 0.423 0.345 0.427 0.405 -0.202 218s Appearance 0.345 0.592 0.570 0.549 -0.316 218s Taste 0.427 0.570 0.739 0.706 -0.393 218s Stickiness 0.405 0.549 0.706 0.876 -0.497 218s Toughness -0.202 -0.316 -0.393 -0.497 0.467 218s -------------------------------------------------------- 218s hemophilia 75 2 -1.868949 218s Outliers: 2 218s [1] 11 36 218s ------------- 218s 218s Call: 218s CovSest(x = x, method = method) 218s -> Method: S-estimates: S-FAST 218s 218s Robust Estimate of Location: 218s [1] -0.2126 -0.0357 218s 218s Robust Estimate of Covariance: 218s AHFactivity AHFantigen 218s AHFactivity 0.0317 0.0112 218s AHFantigen 0.0112 0.0218 218s -------------------------------------------------------- 218s fish 159 6 1.285876 218s Outliers: 21 218s [1] 61 62 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 218s [20] 103 142 218s ------------- 218s 218s Call: 218s CovSest(x = x, method = method) 218s -> Method: S-estimates: S-FAST 218s 218s Robust Estimate of Location: 218s [1] 358.3 24.7 26.9 29.7 30.0 14.7 218s 218s Robust Estimate of Covariance: 218s Weight Length1 Length2 Length3 Height Width 218s Weight 1.33e+05 3.09e+03 3.34e+03 3.78e+03 1.72e+03 2.24e+02 218s Length1 3.09e+03 7.92e+01 8.54e+01 9.55e+01 4.04e+01 7.43e+00 218s Length2 3.34e+03 8.54e+01 9.22e+01 1.03e+02 4.49e+01 8.07e+00 218s Length3 3.78e+03 9.55e+01 1.03e+02 1.18e+02 5.92e+01 7.65e+00 218s Height 1.72e+03 4.04e+01 4.49e+01 5.92e+01 7.12e+01 8.51e-01 218s Width 2.24e+02 7.43e+00 8.07e+00 7.65e+00 8.51e-01 3.57e+00 218s -------------------------------------------------------- 218s airquality 153 4 2.684374 218s Outliers: 7 218s [1] 7 14 23 30 34 77 107 218s ------------- 218s 218s Call: 218s CovSest(x = x, method = method) 218s -> Method: S-estimates: S-FAST 218s 218s Robust Estimate of Location: 218s [1] 39.34 192.12 9.67 78.71 218s 218s Robust Estimate of Covariance: 218s Ozone Solar.R Wind Temp 218s Ozone 973.104 894.011 -61.856 243.560 218s Solar.R 894.011 9677.269 0.388 179.429 218s Wind -61.856 0.388 11.287 -14.310 218s Temp 243.560 179.429 -14.310 96.714 218s -------------------------------------------------------- 218s attitude 30 7 2.091968 218s Outliers: 4 218s [1] 14 16 18 24 218s ------------- 218s 218s Call: 218s CovSest(x = x, method = method) 218s -> Method: S-estimates: S-FAST 218s 218s Robust Estimate of Location: 218s [1] 65.7 66.8 51.9 56.1 66.4 76.7 43.0 218s 218s Robust Estimate of Covariance: 218s rating complaints privileges learning raises critical advance 218s rating 170.59 136.40 77.41 125.46 99.72 8.01 49.52 218s complaints 136.40 170.94 94.62 136.73 120.76 23.52 78.52 218s privileges 77.41 94.62 150.49 112.77 87.92 6.43 72.33 218s learning 125.46 136.73 112.77 173.77 131.46 25.81 81.38 218s raises 99.72 120.76 87.92 131.46 136.76 29.50 91.70 218s critical 8.01 23.52 6.43 25.81 29.50 84.75 30.59 218s advance 49.52 78.52 72.33 81.38 91.70 30.59 116.28 218s -------------------------------------------------------- 218s attenu 182 5 1.148032 218s Outliers: 31 218s [1] 2 5 6 7 8 9 10 11 15 16 19 20 21 22 23 24 25 27 28 218s [20] 29 30 31 32 64 65 80 94 95 96 97 100 218s ------------- 218s 218s Call: 218s CovSest(x = x, method = method) 218s -> Method: S-estimates: S-FAST 218s 218s Robust Estimate of Location: 218s [1] 16.432 5.849 60.297 27.144 0.134 218s 218s Robust Estimate of Covariance: 218s event mag station dist accel 218s event 54.9236 -3.0733 181.0954 -49.4194 -0.0628 218s mag -3.0733 0.6530 -8.4388 6.7388 0.0161 218s station 181.0954 -8.4388 1689.7161 -114.6319 0.7285 218s dist -49.4194 6.7388 -114.6319 597.3606 -1.7988 218s accel -0.0628 0.0161 0.7285 -1.7988 0.0152 218s -------------------------------------------------------- 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: S-FAST 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 0.8710 -0.3019 -0.4682 -0.1893 -0.0569 -0.0992 -0.1771 -0.1975 218s INTG -0.3019 0.6401 0.8598 0.6955 0.5732 0.5439 0.7091 0.7084 218s DMNR -0.4682 0.8598 1.2412 0.9107 0.7668 0.7305 0.9292 0.9158 218s DILG -0.1893 0.6955 0.9107 0.8554 0.7408 0.7036 0.8865 0.8791 218s CFMG -0.0569 0.5732 0.7668 0.7408 0.6994 0.6545 0.7788 0.7721 218s DECI -0.0992 0.5439 0.7305 0.7036 0.6545 0.6342 0.7492 0.7511 218s PREP -0.1771 0.7091 0.9292 0.8865 0.7788 0.7492 0.9541 0.9556 218s FAMI -0.1975 0.7084 0.9158 0.8791 0.7721 0.7511 0.9556 0.9785 218s ORAL -0.2444 0.7453 0.9939 0.8917 0.7842 0.7551 0.9554 0.9680 218s WRIT -0.2344 0.7319 0.9649 0.8853 0.7781 0.7511 0.9498 0.9668 218s PHYS -0.1983 0.4676 0.6263 0.5629 0.5073 0.5039 0.5990 0.6140 218s RTEN -0.3152 0.8000 1.0798 0.9234 0.7952 0.7663 0.9637 0.9693 218s ORAL WRIT PHYS RTEN 218s CONT -0.2444 -0.2344 -0.1983 -0.3152 218s INTG 0.7453 0.7319 0.4676 0.8000 218s DMNR 0.9939 0.9649 0.6263 1.0798 218s DILG 0.8917 0.8853 0.5629 0.9234 218s CFMG 0.7842 0.7781 0.5073 0.7952 218s DECI 0.7551 0.7511 0.5039 0.7663 218s PREP 0.9554 0.9498 0.5990 0.9637 218s FAMI 0.9680 0.9668 0.6140 0.9693 218s ORAL 0.9853 0.9744 0.6280 1.0032 218s WRIT 0.9744 0.9711 0.6184 0.9870 218s PHYS 0.6280 0.6184 0.4716 0.6520 218s RTEN 1.0032 0.9870 0.6520 1.0622 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: S-FAST 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 1.038316 218s Outliers: 5 218s [1] 1 2 3 4 5 218s ------------- 218s 218s Call: 218s CovSest(x = x, method = method) 218s -> Method: S-estimates: S-FAST 218s 218s Robust Estimate of Location: 218s [1] 107.6 440.8 339.7 292.5 121.0 1957.1 67.2 218s 218s Robust Estimate of Covariance: 218s GNP.deflator GNP Unemployed Armed.Forces Population 218s GNP.deflator 100.6 954.7 1147.1 -507.6 74.2 218s GNP 954.7 9430.9 10115.8 -4616.5 730.1 218s Unemployed 1147.1 10115.8 19838.3 -6376.9 850.6 218s Armed.Forces -507.6 -4616.5 -6376.9 3240.2 -351.3 218s Population 74.2 730.1 850.6 -351.3 57.5 218s Year 46.4 450.8 539.5 -233.0 35.3 218s Employed 30.8 310.5 274.0 -160.8 23.3 218s Year Employed 218s GNP.deflator 46.4 30.8 218s GNP 450.8 310.5 218s Unemployed 539.5 274.0 218s Armed.Forces -233.0 -160.8 218s Population 35.3 23.3 218s Year 21.9 14.6 218s Employed 14.6 11.2 218s -------------------------------------------------------- 218s Loblolly 84 3 1.481317 218s Outliers: 14 218s [1] 6 12 18 24 30 36 42 48 54 60 66 72 78 84 218s ------------- 218s 218s Call: 218s CovSest(x = x, method = method) 218s -> Method: S-estimates: S-FAST 218s 218s Robust Estimate of Location: 218s [1] 24.22 9.65 7.50 218s 218s Robust Estimate of Covariance: 218s height age Seed 218s height 525.08 179.21 14.27 218s age 179.21 61.85 2.94 218s Seed 14.27 2.94 25.86 218s -------------------------------------------------------- 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: S-FAST 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="sdet") 219s 219s Call: dodata(method = "sdet") 219s Data Set n p LOG(det) Time 219s =================================================== 219s heart 12 2 2.017701 219s Outliers: 3 219s [1] 2 6 12 219s ------------- 219s 219s Call: 219s CovSest(x = x, method = method) 219s -> Method: S-estimates: DET-S 219s 219s Robust Estimate of Location: 219s [1] 36.1 29.5 219s 219s Robust Estimate of Covariance: 219s height weight 219s height 129 210 219s weight 210 365 219s -------------------------------------------------------- 219s starsCYG 47 2 -1.450032 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: DET-S 219s 219s Robust Estimate of Location: 219s [1] 4.42 4.97 219s 219s Robust Estimate of Covariance: 219s log.Te log.light 219s log.Te 0.0176 0.0617 219s log.light 0.0617 0.3880 219s -------------------------------------------------------- 219s phosphor 18 2 2.320721 219s Outliers: 2 219s [1] 1 6 219s ------------- 219s 219s Call: 219s CovSest(x = x, method = method) 219s -> Method: S-estimates: DET-S 219s 219s Robust Estimate of Location: 219s [1] 14.1 38.8 219s 219s Robust Estimate of Covariance: 219s inorg organic 219s inorg 174 190 219s organic 190 268 219s -------------------------------------------------------- 219s stackloss 21 3 1.470031 219s Outliers: 3 219s [1] 1 2 3 219s ------------- 219s 219s Call: 219s CovSest(x = x, method = method) 219s -> Method: S-estimates: DET-S 219s 219s Robust Estimate of Location: 219s [1] 57.5 20.5 86.0 219s 219s Robust Estimate of Covariance: 219s Air.Flow Water.Temp Acid.Conc. 219s Air.Flow 38.94 11.66 22.89 219s Water.Temp 11.66 9.96 7.81 219s Acid.Conc. 22.89 7.81 40.48 219s -------------------------------------------------------- 219s coleman 20 5 0.491419 219s Outliers: 2 219s [1] 6 10 219s ------------- 219s 219s Call: 219s CovSest(x = x, method = method) 219s -> Method: S-estimates: DET-S 219s 219s Robust Estimate of Location: 219s [1] 2.77 45.58 4.13 25.13 6.39 219s 219s Robust Estimate of Covariance: 219s salaryP fatherWc sstatus teacherSc motherLev 219s salaryP 0.2209 1.9568 1.4389 0.2638 0.0674 219s fatherWc 1.9568 940.7409 307.8297 8.3290 21.9143 219s sstatus 1.4389 307.8297 134.0540 4.1808 7.4799 219s teacherSc 0.2638 8.3290 4.1808 0.7604 0.2917 219s motherLev 0.0674 21.9143 7.4799 0.2917 0.5817 219s -------------------------------------------------------- 219s salinity 28 3 0.734619 219s Outliers: 4 219s [1] 5 16 23 24 219s ------------- 219s 219s Call: 219s CovSest(x = x, method = method) 219s -> Method: S-estimates: DET-S 219s 219s Robust Estimate of Location: 219s [1] 10.31 3.07 22.60 219s 219s Robust Estimate of Covariance: 219s X1 X2 X3 219s X1 13.200 0.784 -3.611 219s X2 0.784 4.441 -1.658 219s X3 -3.611 -1.658 2.877 219s -------------------------------------------------------- 219s wood 20 5 -3.220754 219s Outliers: 4 219s [1] 4 6 8 19 219s ------------- 219s 219s Call: 219s CovSest(x = x, method = method) 219s -> Method: S-estimates: DET-S 219s 219s Robust Estimate of Location: 219s [1] 0.580 0.123 0.530 0.538 0.890 219s 219s Robust Estimate of Covariance: 219s x1 x2 x3 x4 x5 219s x1 8.16e-03 1.39e-03 1.97e-03 -2.82e-04 -7.61e-04 219s x2 1.39e-03 4.00e-04 8.14e-04 -8.51e-05 -5.07e-06 219s x3 1.97e-03 8.14e-04 4.74e-03 -9.59e-04 2.06e-05 219s x4 -2.82e-04 -8.51e-05 -9.59e-04 3.09e-03 1.87e-03 219s x5 -7.61e-04 -5.07e-06 2.06e-05 1.87e-03 2.28e-03 219s -------------------------------------------------------- 219s hbk 75 3 0.283145 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: DET-S 219s 219s Robust Estimate of Location: 219s [1] 1.53 1.83 1.66 219s 219s Robust Estimate of Covariance: 219s X1 X2 X3 219s X1 1.8091 0.0479 0.2446 219s X2 0.0479 1.8190 0.2513 219s X3 0.2446 0.2513 1.7288 219s -------------------------------------------------------- 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 CovSest(x = x, method = method) 220s -> Method: S-estimates: DET-S 220s 220s Robust Estimate of Location: 220s [1] 30.8 84.2 220s 220s Robust Estimate of Covariance: 220s body brain 220s body 14806 28767 220s brain 28767 65194 220s -------------------------------------------------------- 220s milk 86 8 -1.437863 220s Outliers: 15 220s [1] 1 2 3 12 13 14 15 16 17 41 44 47 70 74 75 220s ------------- 220s 220s Call: 220s CovSest(x = x, method = method) 220s -> Method: S-estimates: DET-S 220s 220s Robust Estimate of Location: 220s [1] 1.03 35.81 32.97 26.04 25.02 24.94 122.81 14.36 220s 220s Robust Estimate of Covariance: 220s X1 X2 X3 X4 X5 X6 X7 220s X1 8.30e-07 2.53e-04 4.43e-04 4.02e-04 3.92e-04 3.96e-04 1.44e-03 220s X2 2.53e-04 2.24e+00 4.77e-01 3.63e-01 2.91e-01 3.94e-01 2.44e+00 220s X3 4.43e-04 4.77e-01 1.58e+00 1.20e+00 1.18e+00 1.19e+00 1.65e+00 220s X4 4.02e-04 3.63e-01 1.20e+00 9.74e-01 9.37e-01 9.39e-01 1.39e+00 220s X5 3.92e-04 2.91e-01 1.18e+00 9.37e-01 9.78e-01 9.44e-01 1.37e+00 220s X6 3.96e-04 3.94e-01 1.19e+00 9.39e-01 9.44e-01 9.82e-01 1.41e+00 220s X7 1.44e-03 2.44e+00 1.65e+00 1.39e+00 1.37e+00 1.41e+00 6.96e+00 220s X8 7.45e-05 3.33e-01 2.82e-01 2.01e-01 1.80e-01 1.91e-01 6.38e-01 220s X8 220s X1 7.45e-05 220s X2 3.33e-01 220s X3 2.82e-01 220s X4 2.01e-01 220s X5 1.80e-01 220s X6 1.91e-01 220s X7 6.38e-01 220s X8 2.01e-01 220s -------------------------------------------------------- 220s bushfire 38 5 2.443148 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: DET-S 220s 220s Robust Estimate of Location: 220s [1] 108 149 266 216 278 220s 220s Robust Estimate of Covariance: 220s V1 V2 V3 V4 V5 220s V1 911 688 -3961 -856 -707 220s V2 688 587 -2493 -492 -420 220s V3 -3961 -2493 24146 5765 4627 220s V4 -856 -492 5765 1477 1164 220s V5 -707 -420 4627 1164 925 220s -------------------------------------------------------- 221s rice 105 5 -0.724874 221s Outliers: 7 221s [1] 9 40 42 49 57 58 71 221s ------------- 221s 221s Call: 221s CovSest(x = x, method = method) 221s -> Method: S-estimates: DET-S 221s 221s Robust Estimate of Location: 221s [1] -0.2472 0.1211 -0.1207 0.0715 0.0640 221s 221s Robust Estimate of Covariance: 221s Favor Appearance Taste Stickiness Toughness 221s Favor 0.423 0.345 0.427 0.405 -0.202 221s Appearance 0.345 0.592 0.570 0.549 -0.316 221s Taste 0.427 0.570 0.739 0.706 -0.393 221s Stickiness 0.405 0.549 0.706 0.876 -0.497 221s Toughness -0.202 -0.316 -0.393 -0.497 0.467 221s -------------------------------------------------------- 221s hemophilia 75 2 -1.868949 221s Outliers: 2 221s [1] 11 36 221s ------------- 221s 221s Call: 221s CovSest(x = x, method = method) 221s -> Method: S-estimates: DET-S 221s 221s Robust Estimate of Location: 221s [1] -0.2126 -0.0357 221s 221s Robust Estimate of Covariance: 221s AHFactivity AHFantigen 221s AHFactivity 0.0317 0.0112 221s AHFantigen 0.0112 0.0218 221s -------------------------------------------------------- 221s fish 159 6 1.267294 221s Outliers: 33 221s [1] 61 72 73 74 75 76 77 78 79 80 81 82 83 85 86 87 88 89 90 221s [20] 91 92 93 94 95 96 97 98 99 100 101 102 103 142 221s ------------- 221s 221s Call: 221s CovSest(x = x, method = method) 221s -> Method: S-estimates: DET-S 221s 221s Robust Estimate of Location: 221s [1] 381.2 25.6 27.8 30.8 31.0 14.9 221s 221s Robust Estimate of Covariance: 221s Weight Length1 Length2 Length3 Height Width 221s Weight 148372.04 3260.48 3508.71 3976.93 1507.43 127.94 221s Length1 3260.48 77.00 82.52 92.18 27.56 3.29 221s Length2 3508.71 82.52 88.57 99.20 30.83 3.43 221s Length3 3976.93 92.18 99.20 113.97 45.50 2.21 221s Height 1507.43 27.56 30.83 45.50 70.54 -4.95 221s Width 127.94 3.29 3.43 2.21 -4.95 2.28 221s -------------------------------------------------------- 221s airquality 153 4 2.684374 221s Outliers: 7 221s [1] 7 14 23 30 34 77 107 221s ------------- 221s 221s Call: 221s CovSest(x = x, method = method) 221s -> Method: S-estimates: DET-S 221s 221s Robust Estimate of Location: 221s [1] 39.34 192.12 9.67 78.71 221s 221s Robust Estimate of Covariance: 221s Ozone Solar.R Wind Temp 221s Ozone 973.104 894.011 -61.856 243.560 221s Solar.R 894.011 9677.269 0.388 179.429 221s Wind -61.856 0.388 11.287 -14.310 221s Temp 243.560 179.429 -14.310 96.714 221s -------------------------------------------------------- 222s attitude 30 7 2.091968 222s Outliers: 4 222s [1] 14 16 18 24 222s ------------- 222s 222s Call: 222s CovSest(x = x, method = method) 222s -> Method: S-estimates: DET-S 222s 222s Robust Estimate of Location: 222s [1] 65.7 66.8 51.9 56.1 66.4 76.7 43.0 222s 222s Robust Estimate of Covariance: 222s rating complaints privileges learning raises critical advance 222s rating 170.59 136.40 77.41 125.46 99.72 8.01 49.52 222s complaints 136.40 170.94 94.62 136.73 120.76 23.52 78.52 222s privileges 77.41 94.62 150.49 112.77 87.92 6.43 72.33 222s learning 125.46 136.73 112.77 173.77 131.46 25.81 81.38 222s raises 99.72 120.76 87.92 131.46 136.76 29.50 91.70 222s critical 8.01 23.52 6.43 25.81 29.50 84.75 30.59 222s advance 49.52 78.52 72.33 81.38 91.70 30.59 116.28 222s -------------------------------------------------------- 222s attenu 182 5 1.148032 222s Outliers: 31 222s [1] 2 5 6 7 8 9 10 11 15 16 19 20 21 22 23 24 25 27 28 222s [20] 29 30 31 32 64 65 80 94 95 96 97 100 222s ------------- 222s 222s Call: 222s CovSest(x = x, method = method) 222s -> Method: S-estimates: DET-S 222s 222s Robust Estimate of Location: 222s [1] 16.432 5.849 60.297 27.144 0.134 222s 222s Robust Estimate of Covariance: 222s event mag station dist accel 222s event 54.9236 -3.0733 181.0954 -49.4195 -0.0628 222s mag -3.0733 0.6530 -8.4388 6.7388 0.0161 222s station 181.0954 -8.4388 1689.7161 -114.6321 0.7285 222s dist -49.4195 6.7388 -114.6321 597.3609 -1.7988 222s accel -0.0628 0.0161 0.7285 -1.7988 0.0152 222s -------------------------------------------------------- 222s USJudgeRatings 43 12 -1.683847 222s Outliers: 7 222s [1] 5 7 12 13 14 23 31 222s ------------- 222s 222s Call: 222s CovSest(x = x, method = method) 222s -> Method: S-estimates: DET-S 222s 222s Robust Estimate of Location: 222s [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 222s 222s Robust Estimate of Covariance: 222s CONT INTG DMNR DILG CFMG DECI PREP FAMI 222s CONT 0.8715 -0.3020 -0.4683 -0.1894 -0.0569 -0.0993 -0.1772 -0.1976 222s INTG -0.3020 0.6403 0.8600 0.6956 0.5733 0.5440 0.7093 0.7086 222s DMNR -0.4683 0.8600 1.2416 0.9109 0.7669 0.7307 0.9295 0.9161 222s DILG -0.1894 0.6956 0.9109 0.8555 0.7410 0.7037 0.8867 0.8793 222s CFMG -0.0569 0.5733 0.7669 0.7410 0.6995 0.6546 0.7789 0.7723 222s DECI -0.0993 0.5440 0.7307 0.7037 0.6546 0.6343 0.7493 0.7513 222s PREP -0.1772 0.7093 0.9295 0.8867 0.7789 0.7493 0.9543 0.9559 222s FAMI -0.1976 0.7086 0.9161 0.8793 0.7723 0.7513 0.9559 0.9788 222s ORAL -0.2445 0.7456 0.9942 0.8919 0.7844 0.7553 0.9557 0.9683 222s WRIT -0.2345 0.7321 0.9652 0.8856 0.7783 0.7513 0.9501 0.9671 222s PHYS -0.1986 0.4676 0.6264 0.5628 0.5072 0.5038 0.5990 0.6140 222s RTEN -0.3154 0.8002 1.0801 0.9236 0.7954 0.7665 0.9639 0.9695 222s ORAL WRIT PHYS RTEN 222s CONT -0.2445 -0.2345 -0.1986 -0.3154 222s INTG 0.7456 0.7321 0.4676 0.8002 222s DMNR 0.9942 0.9652 0.6264 1.0801 222s DILG 0.8919 0.8856 0.5628 0.9236 222s CFMG 0.7844 0.7783 0.5072 0.7954 222s DECI 0.7553 0.7513 0.5038 0.7665 222s PREP 0.9557 0.9501 0.5990 0.9639 222s FAMI 0.9683 0.9671 0.6140 0.9695 222s ORAL 0.9856 0.9748 0.6281 1.0035 222s WRIT 0.9748 0.9714 0.6184 0.9873 222s PHYS 0.6281 0.6184 0.4713 0.6520 222s RTEN 1.0035 0.9873 0.6520 1.0624 222s -------------------------------------------------------- 223s USArrests 50 4 2.411726 223s Outliers: 4 223s [1] 2 28 33 39 223s ------------- 223s 223s Call: 223s CovSest(x = x, method = method) 223s -> Method: S-estimates: DET-S 223s 223s Robust Estimate of Location: 223s [1] 7.05 150.66 64.66 19.37 223s 223s Robust Estimate of Covariance: 223s Murder Assault UrbanPop Rape 223s Murder 23.8 380.8 19.2 29.7 223s Assault 380.8 8436.2 605.6 645.3 223s UrbanPop 19.2 605.6 246.5 78.8 223s Rape 29.7 645.3 78.8 77.3 223s -------------------------------------------------------- 223s longley 16 7 1.143113 223s Outliers: 4 223s [1] 1 2 3 4 223s ------------- 223s 223s Call: 223s CovSest(x = x, method = method) 223s -> Method: S-estimates: DET-S 223s 223s Robust Estimate of Location: 223s [1] 107 435 334 293 120 1957 67 223s 223s Robust Estimate of Covariance: 223s GNP.deflator GNP Unemployed Armed.Forces Population 223s GNP.deflator 89.2 850.1 1007.4 -404.4 66.2 223s GNP 850.1 8384.4 9020.8 -3692.0 650.5 223s Unemployed 1007.4 9020.8 16585.4 -4990.7 752.5 223s Armed.Forces -404.4 -3692.0 -4990.7 2474.2 -280.9 223s Population 66.2 650.5 752.5 -280.9 51.2 223s Year 41.9 407.6 481.9 -186.4 31.9 223s Employed 27.9 279.7 255.6 -128.8 21.1 223s Year Employed 223s GNP.deflator 41.9 27.9 223s GNP 407.6 279.7 223s Unemployed 481.9 255.6 223s Armed.Forces -186.4 -128.8 223s Population 31.9 21.1 223s Year 20.2 13.4 223s Employed 13.4 10.1 223s -------------------------------------------------------- 223s Loblolly 84 3 1.481317 223s Outliers: 14 223s [1] 6 12 18 24 30 36 42 48 54 60 66 72 78 84 223s ------------- 223s 223s Call: 223s CovSest(x = x, method = method) 223s -> Method: S-estimates: DET-S 223s 223s Robust Estimate of Location: 223s [1] 24.22 9.65 7.50 223s 223s Robust Estimate of Covariance: 223s height age Seed 223s height 525.08 179.21 14.27 223s age 179.21 61.85 2.94 223s Seed 14.27 2.94 25.86 223s -------------------------------------------------------- 224s quakes 1000 4 1.576855 224s Outliers: 223 224s [1] 7 12 15 17 22 25 27 28 32 37 40 41 45 48 53 224s [16] 63 64 73 78 87 91 92 94 99 108 110 117 118 119 120 224s [31] 121 122 126 133 136 141 143 145 148 152 154 155 157 159 160 224s [46] 163 170 192 205 222 226 230 239 243 250 251 252 254 258 263 224s [61] 267 268 271 283 292 300 301 305 311 312 318 320 321 325 328 224s [76] 330 334 352 357 360 365 381 382 384 389 400 402 408 413 416 224s [91] 417 419 426 429 437 441 443 453 456 467 474 477 490 492 496 224s [106] 504 507 508 509 517 524 527 528 531 532 534 536 538 539 541 224s [121] 542 543 544 545 546 547 552 553 560 571 581 583 587 593 594 224s [136] 596 597 605 612 613 618 620 625 629 638 642 647 649 653 655 224s [151] 656 672 675 681 686 699 701 702 712 714 716 721 725 726 735 224s [166] 744 754 756 759 765 766 769 779 781 782 785 787 797 804 813 224s [181] 825 827 837 840 844 852 853 857 860 865 866 869 870 872 873 224s [196] 883 884 887 888 890 891 893 908 909 912 915 916 921 927 930 224s [211] 952 962 963 969 974 980 982 986 987 988 992 997 1000 224s ------------- 224s 224s Call: 224s CovSest(x = x, method = method) 224s -> Method: S-estimates: DET-S 224s 224s Robust Estimate of Location: 224s [1] -21.54 182.35 369.21 4.54 224s 224s Robust Estimate of Covariance: 224s lat long depth mag 224s lat 2.81e+01 6.19e+00 3.27e+02 -4.56e-01 224s long 6.19e+00 7.54e+00 -5.95e+02 9.56e-02 224s depth 3.27e+02 -5.95e+02 8.36e+04 -2.70e+01 224s mag -4.56e-01 9.56e-02 -2.70e+01 2.35e-01 224s -------------------------------------------------------- 224s =================================================== 224s > ##dodata(method="suser") 224s > ##dodata(method="surreal") 224s > dodata(method="bisquare") 224s 224s Call: dodata(method = "bisquare") 224s Data Set n p LOG(det) Time 224s =================================================== 224s heart 12 2 7.721793 224s Outliers: 3 224s [1] 2 6 12 224s ------------- 224s 224s Call: 224s CovSest(x = x, method = method) 224s -> Method: S-estimates: bisquare 224s 224s Robust Estimate of Location: 224s height weight 224s 36.1 29.4 224s 224s Robust Estimate of Covariance: 224s height weight 224s height 109 177 224s weight 177 307 224s -------------------------------------------------------- 224s starsCYG 47 2 -5.942108 224s Outliers: 7 224s [1] 7 9 11 14 20 30 34 224s ------------- 224s 224s Call: 224s CovSest(x = x, method = method) 224s -> Method: S-estimates: bisquare 224s 224s Robust Estimate of Location: 224s log.Te log.light 224s 4.42 4.97 224s 224s Robust Estimate of Covariance: 224s log.Te log.light 224s log.Te 0.0164 0.0574 224s log.light 0.0574 0.3613 224s -------------------------------------------------------- 224s phosphor 18 2 9.269096 224s Outliers: 2 224s [1] 1 6 224s ------------- 224s 224s Call: 224s CovSest(x = x, method = method) 224s -> Method: S-estimates: bisquare 224s 224s Robust Estimate of Location: 224s inorg organic 224s 14.1 38.7 224s 224s Robust Estimate of Covariance: 224s inorg organic 224s inorg 173 189 224s organic 189 268 224s -------------------------------------------------------- 224s stackloss 21 3 8.411100 224s Outliers: 3 224s [1] 1 2 3 224s ------------- 224s 224s Call: 224s CovSest(x = x, method = method) 224s -> Method: S-estimates: bisquare 224s 224s Robust Estimate of Location: 224s Air.Flow Water.Temp Acid.Conc. 224s 57.5 20.5 86.0 224s 224s Robust Estimate of Covariance: 224s Air.Flow Water.Temp Acid.Conc. 224s Air.Flow 33.82 10.17 20.02 224s Water.Temp 10.17 8.70 6.84 224s Acid.Conc. 20.02 6.84 35.51 224s -------------------------------------------------------- 224s coleman 20 5 4.722046 224s Outliers: 2 224s [1] 6 10 224s ------------- 224s 224s Call: 224s CovSest(x = x, method = method) 224s -> Method: S-estimates: bisquare 224s 224s Robust Estimate of Location: 224s salaryP fatherWc sstatus teacherSc motherLev 224s 2.77 45.59 4.14 25.13 6.39 224s 224s Robust Estimate of Covariance: 224s salaryP fatherWc sstatus teacherSc motherLev 224s salaryP 0.2135 1.8732 1.3883 0.2547 0.0648 224s fatherWc 1.8732 905.6704 296.1916 7.9820 21.0848 224s sstatus 1.3883 296.1916 128.9536 4.0196 7.1917 224s teacherSc 0.2547 7.9820 4.0196 0.7321 0.2799 224s motherLev 0.0648 21.0848 7.1917 0.2799 0.5592 224s -------------------------------------------------------- 224s salinity 28 3 4.169963 224s Outliers: 4 224s [1] 5 16 23 24 224s ------------- 224s 224s Call: 224s CovSest(x = x, method = method) 224s -> Method: S-estimates: bisquare 224s 224s Robust Estimate of Location: 224s X1 X2 X3 224s 10.30 3.07 22.59 224s 224s Robust Estimate of Covariance: 224s X1 X2 X3 224s X1 12.234 0.748 -3.369 224s X2 0.748 4.115 -1.524 224s X3 -3.369 -1.524 2.655 224s -------------------------------------------------------- 224s wood 20 5 -33.862485 224s Outliers: 5 224s [1] 4 6 8 11 19 224s ------------- 224s 224s Call: 224s CovSest(x = x, method = method) 224s -> Method: S-estimates: bisquare 224s 224s Robust Estimate of Location: 224s x1 x2 x3 x4 x5 224s 0.580 0.123 0.530 0.538 0.890 224s 224s Robust Estimate of Covariance: 224s x1 x2 x3 x4 x5 224s x1 5.88e-03 9.96e-04 1.43e-03 -1.96e-04 -5.46e-04 224s x2 9.96e-04 2.86e-04 5.89e-04 -5.78e-05 -2.24e-06 224s x3 1.43e-03 5.89e-04 3.42e-03 -6.95e-04 1.43e-05 224s x4 -1.96e-04 -5.78e-05 -6.95e-04 2.23e-03 1.35e-03 224s x5 -5.46e-04 -2.24e-06 1.43e-05 1.35e-03 1.65e-03 224s -------------------------------------------------------- 224s hbk 75 3 1.472421 224s Outliers: 14 224s [1] 1 2 3 4 5 6 7 8 9 10 11 12 13 14 224s ------------- 224s 224s Call: 224s CovSest(x = x, method = method) 224s -> Method: S-estimates: bisquare 224s 224s Robust Estimate of Location: 224s X1 X2 X3 224s 1.53 1.83 1.66 224s 224s Robust Estimate of Covariance: 224s X1 X2 X3 224s X1 1.6775 0.0447 0.2268 224s X2 0.0447 1.6865 0.2325 224s X3 0.2268 0.2325 1.6032 224s -------------------------------------------------------- 224s Animals 28 2 18.528307 224s Outliers: 11 224s [1] 2 6 7 9 12 14 15 16 24 25 28 224s ------------- 224s 224s Call: 224s CovSest(x = x, method = method) 224s -> Method: S-estimates: bisquare 224s 224s Robust Estimate of Location: 224s body brain 224s 30.7 84.1 224s 224s Robust Estimate of Covariance: 224s body brain 224s body 13278 25795 224s brain 25795 58499 224s -------------------------------------------------------- 224s milk 86 8 -24.816943 224s Outliers: 19 224s [1] 1 2 3 11 12 13 14 15 16 17 20 27 41 44 47 70 74 75 77 224s ------------- 224s 224s Call: 224s CovSest(x = x, method = method) 224s -> Method: S-estimates: bisquare 224s 224s Robust Estimate of Location: 224s X1 X2 X3 X4 X5 X6 X7 X8 224s 1.03 35.81 32.96 26.04 25.02 24.94 122.79 14.35 224s 224s Robust Estimate of Covariance: 224s X1 X2 X3 X4 X5 X6 X7 224s X1 6.80e-07 2.20e-04 3.70e-04 3.35e-04 3.27e-04 3.30e-04 1.21e-03 224s X2 2.20e-04 1.80e+00 3.96e-01 3.03e-01 2.45e-01 3.27e-01 2.00e+00 224s X3 3.70e-04 3.96e-01 1.27e+00 9.68e-01 9.49e-01 9.56e-01 1.37e+00 224s X4 3.35e-04 3.03e-01 9.68e-01 7.86e-01 7.55e-01 7.57e-01 1.15e+00 224s X5 3.27e-04 2.45e-01 9.49e-01 7.55e-01 7.88e-01 7.61e-01 1.14e+00 224s X6 3.30e-04 3.27e-01 9.56e-01 7.57e-01 7.61e-01 7.90e-01 1.17e+00 224s X7 1.21e-03 2.00e+00 1.37e+00 1.15e+00 1.14e+00 1.17e+00 5.71e+00 224s X8 6.57e-05 2.71e-01 2.30e-01 1.64e-01 1.48e-01 1.57e-01 5.27e-01 224s X8 224s X1 6.57e-05 224s X2 2.71e-01 224s X3 2.30e-01 224s X4 1.64e-01 224s X5 1.48e-01 224s X6 1.57e-01 224s X7 5.27e-01 224s X8 1.62e-01 224s -------------------------------------------------------- 224s bushfire 38 5 21.704243 224s Outliers: 13 224s [1] 7 8 9 10 11 31 32 33 34 35 36 37 38 224s ------------- 224s 224s Call: 224s CovSest(x = x, method = method) 224s -> Method: S-estimates: bisquare 224s 224s Robust Estimate of Location: 224s V1 V2 V3 V4 V5 224s 108 149 266 216 278 224s 224s Robust Estimate of Covariance: 224s V1 V2 V3 V4 V5 224s V1 528 398 -2298 -497 -410 224s V2 398 340 -1445 -285 -244 224s V3 -2298 -1445 14026 3348 2687 224s V4 -497 -285 3348 857 676 224s V5 -410 -244 2687 676 537 224s -------------------------------------------------------- 224s rice 105 5 -7.346939 224s Outliers: 8 224s [1] 9 14 40 42 49 57 58 71 224s ------------- 224s 224s Call: 224s CovSest(x = x, method = method) 224s -> Method: S-estimates: bisquare 224s 224s Robust Estimate of Location: 224s Favor Appearance Taste Stickiness Toughness 224s -0.2480 0.1203 -0.1213 0.0710 0.0644 224s 224s Robust Estimate of Covariance: 224s Favor Appearance Taste Stickiness Toughness 224s Favor 0.415 0.338 0.419 0.398 -0.198 224s Appearance 0.338 0.580 0.559 0.539 -0.310 224s Taste 0.419 0.559 0.725 0.693 -0.386 224s Stickiness 0.398 0.539 0.693 0.859 -0.487 224s Toughness -0.198 -0.310 -0.386 -0.487 0.457 224s -------------------------------------------------------- 224s hemophilia 75 2 -7.465173 224s Outliers: 2 224s [1] 11 36 224s ------------- 224s 224s Call: 224s CovSest(x = x, method = method) 224s -> Method: S-estimates: bisquare 224s 224s Robust Estimate of Location: 224s AHFactivity AHFantigen 224s -0.2128 -0.0366 224s 224s Robust Estimate of Covariance: 224s AHFactivity AHFantigen 224s AHFactivity 0.0321 0.0115 224s AHFantigen 0.0115 0.0220 224s -------------------------------------------------------- 224s fish 159 6 13.465134 224s Outliers: 35 224s [1] 38 61 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 224s [20] 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 142 224s ------------- 224s 224s Call: 224s CovSest(x = x, method = method) 224s -> Method: S-estimates: bisquare 224s 224s Robust Estimate of Location: 224s Weight Length1 Length2 Length3 Height Width 224s 381.4 25.6 27.8 30.8 31.0 14.9 224s 224s Robust Estimate of Covariance: 224s Weight Length1 Length2 Length3 Height Width 224s Weight 111094.92 2440.81 2626.59 2976.92 1129.78 95.85 224s Length1 2440.81 57.63 61.75 68.98 20.67 2.46 224s Length2 2626.59 61.75 66.28 74.24 23.13 2.57 224s Length3 2976.92 68.98 74.24 85.29 34.11 1.65 224s Height 1129.78 20.67 23.13 34.11 52.75 -3.70 224s Width 95.85 2.46 2.57 1.65 -3.70 1.71 224s -------------------------------------------------------- 224s airquality 153 4 21.282926 224s Outliers: 8 224s [1] 7 11 14 23 30 34 77 107 224s ------------- 224s 224s Call: 224s CovSest(x = x, method = method) 224s -> Method: S-estimates: bisquare 224s 224s Robust Estimate of Location: 224s Ozone Solar.R Wind Temp 224s 39.40 192.29 9.66 78.74 224s 224s Robust Estimate of Covariance: 224s Ozone Solar.R Wind Temp 224s Ozone 930.566 849.644 -59.157 232.459 224s Solar.R 849.644 9207.569 0.594 168.122 224s Wind -59.157 0.594 10.783 -13.645 224s Temp 232.459 168.122 -13.645 92.048 224s -------------------------------------------------------- 224s attitude 30 7 28.084183 224s Outliers: 6 224s [1] 6 9 14 16 18 24 224s ------------- 224s 224s Call: 224s CovSest(x = x, method = method) 224s -> Method: S-estimates: bisquare 224s 224s Robust Estimate of Location: 224s rating complaints privileges learning raises critical 224s 65.7 66.8 51.9 56.1 66.4 76.7 224s advance 224s 43.0 224s 224s Robust Estimate of Covariance: 224s rating complaints privileges learning raises critical advance 224s rating 143.88 114.95 64.97 105.69 83.95 6.96 41.78 224s complaints 114.95 143.84 79.28 115.00 101.48 19.69 66.13 224s privileges 64.97 79.28 126.38 94.70 73.87 5.37 61.07 224s learning 105.69 115.00 94.70 146.14 110.50 21.67 68.49 224s raises 83.95 101.48 73.87 110.50 115.01 24.91 77.16 224s critical 6.96 19.69 5.37 21.67 24.91 71.74 25.88 224s advance 41.78 66.13 61.07 68.49 77.16 25.88 97.71 224s -------------------------------------------------------- 224s attenu 182 5 10.109049 224s Outliers: 35 224s [1] 2 4 5 6 7 8 9 10 11 15 16 19 20 21 22 23 24 25 27 224s [20] 28 29 30 31 32 64 65 80 93 94 95 96 97 98 99 100 224s ------------- 224s 224s Call: 224s CovSest(x = x, method = method) 224s -> Method: S-estimates: bisquare 224s 224s Robust Estimate of Location: 224s event mag station dist accel 224s 16.418 5.850 60.243 27.307 0.134 224s 224s Robust Estimate of Covariance: 224s event mag station dist accel 224s event 41.9000 -2.3543 137.8110 -39.0321 -0.0447 224s mag -2.3543 0.4978 -6.4461 5.2644 0.0118 224s station 137.8110 -6.4461 1283.9675 -90.1657 0.5554 224s dist -39.0321 5.2644 -90.1657 462.3898 -1.3672 224s accel -0.0447 0.0118 0.5554 -1.3672 0.0114 224s -------------------------------------------------------- 224s USJudgeRatings 43 12 -43.367499 224s Outliers: 10 224s [1] 5 7 8 12 13 14 20 23 31 35 224s ------------- 224s 224s Call: 224s CovSest(x = x, method = method) 224s -> Method: S-estimates: bisquare 224s 224s Robust Estimate of Location: 224s CONT INTG DMNR DILG CFMG DECI PREP FAMI ORAL WRIT PHYS RTEN 224s 7.43 8.16 7.75 7.89 7.69 7.76 7.68 7.67 7.52 7.59 8.19 7.87 224s 224s Robust Estimate of Covariance: 224s CONT INTG DMNR DILG CFMG DECI PREP FAMI 224s CONT 0.6895 -0.2399 -0.3728 -0.1514 -0.0461 -0.0801 -0.1419 -0.1577 224s INTG -0.2399 0.5021 0.6746 0.5446 0.4479 0.4254 0.5564 0.5558 224s DMNR -0.3728 0.6746 0.9753 0.7128 0.5992 0.5715 0.7289 0.7181 224s DILG -0.1514 0.5446 0.7128 0.6691 0.5789 0.5501 0.6949 0.6892 224s CFMG -0.0461 0.4479 0.5992 0.5789 0.5468 0.5118 0.6100 0.6049 224s DECI -0.0801 0.4254 0.5715 0.5501 0.5118 0.4965 0.5872 0.5890 224s PREP -0.1419 0.5564 0.7289 0.6949 0.6100 0.5872 0.7497 0.7511 224s FAMI -0.1577 0.5558 0.7181 0.6892 0.6049 0.5890 0.7511 0.7696 224s ORAL -0.1950 0.5848 0.7798 0.6990 0.6143 0.5921 0.7508 0.7610 224s WRIT -0.1866 0.5747 0.7575 0.6946 0.6101 0.5895 0.7470 0.7607 224s PHYS -0.1620 0.3640 0.4878 0.4361 0.3927 0.3910 0.4655 0.4779 224s RTEN -0.2522 0.6268 0.8462 0.7220 0.6210 0.5991 0.7553 0.7599 224s ORAL WRIT PHYS RTEN 224s CONT -0.1950 -0.1866 -0.1620 -0.2522 224s INTG 0.5848 0.5747 0.3640 0.6268 224s DMNR 0.7798 0.7575 0.4878 0.8462 224s DILG 0.6990 0.6946 0.4361 0.7220 224s CFMG 0.6143 0.6101 0.3927 0.6210 224s DECI 0.5921 0.5895 0.3910 0.5991 224s PREP 0.7508 0.7470 0.4655 0.7553 224s FAMI 0.7610 0.7607 0.4779 0.7599 224s ORAL 0.7745 0.7665 0.4893 0.7866 224s WRIT 0.7665 0.7645 0.4823 0.7745 224s PHYS 0.4893 0.4823 0.3620 0.5062 224s RTEN 0.7866 0.7745 0.5062 0.8313 224s -------------------------------------------------------- 224s USArrests 50 4 19.266763 224s Outliers: 4 224s [1] 2 28 33 39 224s ------------- 224s 224s Call: 224s CovSest(x = x, method = method) 224s -> Method: S-estimates: bisquare 224s 224s Robust Estimate of Location: 224s Murder Assault UrbanPop Rape 224s 7.04 150.55 64.64 19.34 224s 224s Robust Estimate of Covariance: 224s Murder Assault UrbanPop Rape 224s Murder 23.7 378.9 19.1 29.5 224s Assault 378.9 8388.2 601.3 639.7 224s UrbanPop 19.1 601.3 245.3 77.9 224s Rape 29.5 639.7 77.9 76.3 224s -------------------------------------------------------- 224s longley 16 7 13.789499 224s Outliers: 4 224s [1] 1 2 3 4 224s ------------- 224s 224s Call: 224s CovSest(x = x, method = method) 224s -> Method: S-estimates: bisquare 224s 224s Robust Estimate of Location: 224s GNP.deflator GNP Unemployed Armed.Forces Population 224s 107 435 333 293 120 224s Year Employed 224s 1957 67 224s 224s Robust Estimate of Covariance: 224s GNP.deflator GNP Unemployed Armed.Forces Population 224s GNP.deflator 65.05 619.75 734.33 -294.02 48.27 224s GNP 619.75 6112.14 6578.12 -2684.52 474.26 224s Unemployed 734.33 6578.12 12075.90 -3627.79 548.58 224s Armed.Forces -294.02 -2684.52 -3627.79 1797.05 -204.25 224s Population 48.27 474.26 548.58 -204.25 37.36 224s Year 30.58 297.29 351.44 -135.53 23.29 224s Employed 20.36 203.96 186.62 -93.64 15.42 224s Year Employed 224s GNP.deflator 30.58 20.36 224s GNP 297.29 203.96 224s Unemployed 351.44 186.62 224s Armed.Forces -135.53 -93.64 224s Population 23.29 15.42 224s Year 14.70 9.80 224s Employed 9.80 7.36 224s -------------------------------------------------------- 224s Loblolly 84 3 8.518440 224s Outliers: 14 224s [1] 6 12 18 24 30 36 42 48 54 60 66 72 78 84 224s ------------- 224s 224s Call: 224s CovSest(x = x, method = method) 224s -> Method: S-estimates: bisquare 224s 224s Robust Estimate of Location: 224s height age Seed 224s 24.14 9.62 7.51 224s 224s Robust Estimate of Covariance: 224s height age Seed 224s height 464.64 158.43 12.83 224s age 158.43 54.62 2.67 224s Seed 12.83 2.67 22.98 224s -------------------------------------------------------- 224s quakes 1000 4 11.611413 224s Outliers: 234 224s [1] 7 12 15 17 22 25 27 28 32 37 40 41 45 48 53 224s [16] 63 64 73 78 87 91 92 94 99 108 110 117 118 119 120 224s [31] 121 122 126 133 136 141 143 145 148 152 154 155 157 159 160 224s [46] 163 166 170 174 192 205 222 226 230 239 243 250 251 252 254 224s [61] 258 263 267 268 271 283 292 297 300 301 305 311 312 318 320 224s [76] 321 325 328 330 331 334 352 357 360 365 368 376 381 382 384 224s [91] 389 399 400 402 408 413 416 417 418 419 426 429 437 441 443 224s [106] 453 456 467 474 477 490 492 496 504 507 508 509 517 524 527 224s [121] 528 531 532 534 536 538 539 541 542 543 544 545 546 547 552 224s [136] 553 558 560 570 571 581 583 587 593 594 596 597 605 612 613 224s [151] 618 620 625 629 638 642 647 649 653 655 656 672 675 681 686 224s [166] 699 701 702 712 714 716 721 725 726 735 744 753 754 756 759 224s [181] 765 766 769 779 781 782 785 787 797 804 813 825 827 837 840 224s [196] 844 852 853 857 860 865 866 869 870 872 873 883 884 887 888 224s [211] 890 891 893 908 909 912 915 916 921 927 930 952 962 963 969 224s [226] 974 980 982 986 987 988 992 997 1000 224s ------------- 224s 224s Call: 224s CovSest(x = x, method = method) 224s -> Method: S-estimates: bisquare 224s 224s Robust Estimate of Location: 224s lat long depth mag 224s -21.54 182.35 369.29 4.54 224s 224s Robust Estimate of Covariance: 224s lat long depth mag 224s lat 2.18e+01 4.82e+00 2.53e+02 -3.54e-01 224s long 4.82e+00 5.87e+00 -4.63e+02 7.45e-02 224s depth 2.53e+02 -4.63e+02 6.51e+04 -2.10e+01 224s mag -3.54e-01 7.45e-02 -2.10e+01 1.83e-01 224s -------------------------------------------------------- 224s =================================================== 224s > dodata(method="rocke") 224s 224s Call: dodata(method = "rocke") 224s Data Set n p LOG(det) Time 224s =================================================== 224s heart 12 2 7.285196 224s Outliers: 3 224s [1] 2 6 12 224s ------------- 224s 224s Call: 224s CovSest(x = x, method = method) 224s -> Method: S-estimates: Rocke type 224s 224s Robust Estimate of Location: 224s height weight 224s 34.3 26.1 224s 224s Robust Estimate of Covariance: 224s height weight 224s height 105 159 224s weight 159 256 224s -------------------------------------------------------- 224s starsCYG 47 2 -5.929361 224s Outliers: 7 224s [1] 7 9 11 14 20 30 34 224s ------------- 224s 224s Call: 224s CovSest(x = x, method = method) 224s -> Method: S-estimates: Rocke type 224s 224s Robust Estimate of Location: 224s log.Te log.light 224s 4.42 4.93 224s 224s Robust Estimate of Covariance: 224s log.Te log.light 224s log.Te 0.0193 0.0709 224s log.light 0.0709 0.3987 224s -------------------------------------------------------- 224s phosphor 18 2 8.907518 224s Outliers: 3 224s [1] 1 6 10 224s ------------- 224s 224s Call: 224s CovSest(x = x, method = method) 224s -> Method: S-estimates: Rocke type 224s 224s Robust Estimate of Location: 224s inorg organic 224s 15.8 39.4 224s 224s Robust Estimate of Covariance: 224s inorg organic 224s inorg 196 252 224s organic 252 360 224s -------------------------------------------------------- 224s stackloss 21 3 8.143313 224s Outliers: 4 224s [1] 1 2 3 21 224s ------------- 224s 224s Call: 224s CovSest(x = x, method = method) 224s -> Method: S-estimates: Rocke type 224s 224s Robust Estimate of Location: 224s Air.Flow Water.Temp Acid.Conc. 224s 56.8 20.2 86.4 224s 224s Robust Estimate of Covariance: 224s Air.Flow Water.Temp Acid.Conc. 224s Air.Flow 29.26 9.62 14.78 224s Water.Temp 9.62 8.54 6.25 224s Acid.Conc. 14.78 6.25 29.70 224s -------------------------------------------------------- 224s coleman 20 5 4.001659 224s Outliers: 5 224s [1] 2 6 9 10 13 224s ------------- 224s 224s Call: 224s CovSest(x = x, method = method) 224s -> Method: S-estimates: Rocke type 224s 224s Robust Estimate of Location: 224s salaryP fatherWc sstatus teacherSc motherLev 224s 2.81 40.27 2.11 25.01 6.27 224s 224s Robust Estimate of Covariance: 224s salaryP fatherWc sstatus teacherSc motherLev 224s salaryP 0.2850 1.1473 2.0254 0.3536 0.0737 224s fatherWc 1.1473 798.0714 278.0145 6.4590 18.6357 224s sstatus 2.0254 278.0145 128.7601 4.0666 6.3845 224s teacherSc 0.3536 6.4590 4.0666 0.8749 0.2980 224s motherLev 0.0737 18.6357 6.3845 0.2980 0.4948 224s -------------------------------------------------------- 224s salinity 28 3 3.455146 224s Outliers: 9 224s [1] 3 5 10 11 15 16 17 23 24 224s ------------- 224s 224s Call: 224s CovSest(x = x, method = method) 224s -> Method: S-estimates: Rocke type 224s 224s Robust Estimate of Location: 224s X1 X2 X3 224s 9.89 3.10 22.46 224s 224s Robust Estimate of Covariance: 224s X1 X2 X3 224s X1 12.710 1.868 -4.135 224s X2 1.868 4.710 -0.663 224s X3 -4.135 -0.663 1.907 224s -------------------------------------------------------- 224s wood 20 5 -35.020244 224s Outliers: 7 224s [1] 4 6 7 8 11 16 19 224s ------------- 224s 224s Call: 224s CovSest(x = x, method = method) 224s -> Method: S-estimates: Rocke type 224s 224s Robust Estimate of Location: 224s x1 x2 x3 x4 x5 224s 0.588 0.123 0.534 0.535 0.891 224s 224s Robust Estimate of Covariance: 224s x1 x2 x3 x4 x5 224s x1 6.60e-03 1.25e-03 2.16e-03 -3.73e-04 -1.10e-03 224s x2 1.25e-03 3.30e-04 8.91e-04 -1.23e-05 2.62e-05 224s x3 2.16e-03 8.91e-04 4.55e-03 -4.90e-04 1.93e-04 224s x4 -3.73e-04 -1.23e-05 -4.90e-04 2.01e-03 1.36e-03 224s x5 -1.10e-03 2.62e-05 1.93e-04 1.36e-03 1.95e-03 224s -------------------------------------------------------- 224s hbk 75 3 1.413303 224s Outliers: 14 224s [1] 1 2 3 4 5 6 7 8 9 10 11 12 13 14 224s ------------- 224s 224s Call: 224s CovSest(x = x, method = method) 224s -> Method: S-estimates: Rocke type 224s 224s Robust Estimate of Location: 224s X1 X2 X3 224s 1.56 1.77 1.68 224s 224s Robust Estimate of Covariance: 224s X1 X2 X3 224s X1 1.6483 0.0825 0.2133 224s X2 0.0825 1.6928 0.2334 224s X3 0.2133 0.2334 1.5334 224s -------------------------------------------------------- 224s Animals 28 2 17.787210 224s Outliers: 11 224s [1] 2 6 7 9 12 14 15 16 24 25 28 224s ------------- 224s 224s Call: 224s CovSest(x = x, method = method) 224s -> Method: S-estimates: Rocke type 224s 224s Robust Estimate of Location: 224s body brain 224s 60.6 150.2 224s 224s Robust Estimate of Covariance: 224s body brain 224s body 10670 19646 224s brain 19646 41147 224s -------------------------------------------------------- 224s milk 86 8 -25.169970 224s Outliers: 22 224s [1] 1 2 3 11 12 13 14 15 16 17 18 20 27 28 41 44 47 70 73 74 75 77 224s ------------- 224s 224s Call: 224s CovSest(x = x, method = method) 224s -> Method: S-estimates: Rocke type 224s 224s Robust Estimate of Location: 224s X1 X2 X3 X4 X5 X6 X7 X8 224s 1.03 35.87 33.14 26.19 25.17 25.11 123.16 14.41 224s 224s Robust Estimate of Covariance: 224s X1 X2 X3 X4 X5 X6 X7 224s X1 4.47e-07 1.77e-04 1.94e-04 1.79e-04 1.60e-04 1.45e-04 6.45e-04 224s X2 1.77e-04 2.36e+00 4.03e-01 3.08e-01 2.08e-01 3.45e-01 2.18e+00 224s X3 1.94e-04 4.03e-01 1.13e+00 8.31e-01 8.08e-01 7.79e-01 9.83e-01 224s X4 1.79e-04 3.08e-01 8.31e-01 6.62e-01 6.22e-01 5.95e-01 7.82e-01 224s X5 1.60e-04 2.08e-01 8.08e-01 6.22e-01 6.51e-01 5.93e-01 7.60e-01 224s X6 1.45e-04 3.45e-01 7.79e-01 5.95e-01 5.93e-01 5.88e-01 7.81e-01 224s X7 6.45e-04 2.18e+00 9.83e-01 7.82e-01 7.60e-01 7.81e-01 4.81e+00 224s X8 2.47e-05 2.57e-01 2.00e-01 1.37e-01 1.13e-01 1.28e-01 4.38e-01 224s X8 224s X1 2.47e-05 224s X2 2.57e-01 224s X3 2.00e-01 224s X4 1.37e-01 224s X5 1.13e-01 224s X6 1.28e-01 224s X7 4.38e-01 224s X8 1.61e-01 224s -------------------------------------------------------- 224s bushfire 38 5 21.641566 224s Outliers: 13 224s [1] 7 8 9 10 11 31 32 33 34 35 36 37 38 224s ------------- 224s 224s Call: 224s CovSest(x = x, method = method) 224s -> Method: S-estimates: Rocke type 224s 224s Robust Estimate of Location: 224s V1 V2 V3 V4 V5 224s 111 150 256 214 276 224s 224s Robust Estimate of Covariance: 224s V1 V2 V3 V4 V5 224s V1 554 408 -2321 -464 -393 224s V2 408 343 -1361 -244 -215 224s V3 -2321 -1361 14690 3277 2684 224s V4 -464 -244 3277 783 629 224s V5 -393 -215 2684 629 509 224s -------------------------------------------------------- 224s rice 105 5 -7.208835 224s Outliers: 8 224s [1] 9 14 40 42 49 57 58 71 224s ------------- 224s 224s Call: 224s CovSest(x = x, method = method) 224s -> Method: S-estimates: Rocke type 224s 224s Robust Estimate of Location: 224s Favor Appearance Taste Stickiness Toughness 224s -0.21721 0.20948 -0.04581 0.15355 -0.00254 224s 224s Robust Estimate of Covariance: 224s Favor Appearance Taste Stickiness Toughness 224s Favor 0.432 0.337 0.417 0.382 -0.201 224s Appearance 0.337 0.591 0.553 0.510 -0.295 224s Taste 0.417 0.553 0.735 0.683 -0.385 224s Stickiness 0.382 0.510 0.683 0.834 -0.462 224s Toughness -0.201 -0.295 -0.385 -0.462 0.408 224s -------------------------------------------------------- 224s hemophilia 75 2 -7.453807 224s Outliers: 2 224s [1] 46 53 224s ------------- 224s 224s Call: 224s CovSest(x = x, method = method) 224s -> Method: S-estimates: Rocke type 224s 224s Robust Estimate of Location: 224s AHFactivity AHFantigen 224s -0.2276 -0.0637 224s 224s Robust Estimate of Covariance: 224s AHFactivity AHFantigen 224s AHFactivity 0.0405 0.0221 224s AHFantigen 0.0221 0.0263 224s -------------------------------------------------------- 224s fish 159 6 13.110263 224s Outliers: 47 224s [1] 38 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 224s [20] 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 224s [39] 98 99 100 101 102 103 104 140 142 224s ------------- 224s 224s Call: 224s CovSest(x = x, method = method) 224s -> Method: S-estimates: Rocke type 224s 224s Robust Estimate of Location: 224s Weight Length1 Length2 Length3 Height Width 224s 452.1 27.2 29.5 32.6 30.8 15.0 224s 224s Robust Estimate of Covariance: 224s Weight Length1 Length2 Length3 Height Width 224s Weight 132559.85 2817.97 3035.69 3369.07 1231.68 112.19 224s Length1 2817.97 64.16 68.74 75.36 22.52 2.37 224s Length2 3035.69 68.74 73.77 81.12 25.57 2.47 224s Length3 3369.07 75.36 81.12 91.65 37.39 1.40 224s Height 1231.68 22.52 25.57 37.39 50.91 -3.92 224s Width 112.19 2.37 2.47 1.40 -3.92 1.87 224s -------------------------------------------------------- 225s airquality 153 4 21.181656 225s Outliers: 13 225s [1] 6 7 11 14 17 20 23 30 34 53 63 77 107 225s ------------- 225s 225s Call: 225s CovSest(x = x, method = method) 225s -> Method: S-estimates: Rocke type 225s 225s Robust Estimate of Location: 225s Ozone Solar.R Wind Temp 225s 40.21 198.33 9.76 79.35 225s 225s Robust Estimate of Covariance: 225s Ozone Solar.R Wind Temp 225s Ozone 885.7 581.1 -57.3 226.4 225s Solar.R 581.1 8870.9 26.2 -15.1 225s Wind -57.3 26.2 11.8 -13.4 225s Temp 226.4 -15.1 -13.4 89.4 225s -------------------------------------------------------- 225s attitude 30 7 27.836398 225s Outliers: 8 225s [1] 1 9 13 14 17 18 24 26 225s ------------- 225s 225s Call: 225s CovSest(x = x, method = method) 225s -> Method: S-estimates: Rocke type 225s 225s Robust Estimate of Location: 225s rating complaints privileges learning raises critical 225s 64.0 65.4 50.5 54.9 63.1 72.6 225s advance 225s 40.5 225s 225s Robust Estimate of Covariance: 225s rating complaints privileges learning raises critical advance 225s rating 180.10 153.16 42.04 128.90 90.25 18.75 39.81 225s complaints 153.16 192.38 58.32 142.48 94.29 8.13 45.33 225s privileges 42.04 58.32 113.65 82.31 69.53 23.13 61.96 225s learning 128.90 142.48 82.31 156.99 101.74 13.22 49.64 225s raises 90.25 94.29 69.53 101.74 110.85 47.84 55.76 225s critical 18.75 8.13 23.13 13.22 47.84 123.00 36.97 225s advance 39.81 45.33 61.96 49.64 55.76 36.97 53.59 225s -------------------------------------------------------- 225s attenu 182 5 9.726797 225s Outliers: 44 225s [1] 1 2 4 5 6 7 8 9 10 11 13 15 16 19 20 21 22 23 24 225s [20] 25 27 28 29 30 31 32 40 45 60 61 64 65 78 80 81 93 94 95 225s [39] 96 97 98 99 100 108 225s ------------- 225s 225s Call: 225s CovSest(x = x, method = method) 225s -> Method: S-estimates: Rocke type 225s 225s Robust Estimate of Location: 225s event mag station dist accel 225s 16.39 5.82 60.89 27.97 0.12 225s 225s Robust Estimate of Covariance: 225s event mag station dist accel 225s event 4.20e+01 -1.97e+00 1.44e+02 -3.50e+01 4.05e-02 225s mag -1.97e+00 5.05e-01 -4.78e+00 4.63e+00 4.19e-03 225s station 1.44e+02 -4.78e+00 1.47e+03 -5.74e+01 7.88e-01 225s dist -3.50e+01 4.63e+00 -5.74e+01 3.99e+02 -1.18e+00 225s accel 4.05e-02 4.19e-03 7.88e-01 -1.18e+00 7.71e-03 225s -------------------------------------------------------- 225s USJudgeRatings 43 12 -46.356873 225s Outliers: 15 225s [1] 1 5 7 8 12 13 14 17 20 21 23 30 31 35 42 225s ------------- 225s 225s Call: 225s CovSest(x = x, method = method) 225s -> Method: S-estimates: Rocke type 225s 225s Robust Estimate of Location: 225s CONT INTG DMNR DILG CFMG DECI PREP FAMI ORAL WRIT PHYS RTEN 225s 7.56 8.12 7.70 7.91 7.74 7.82 7.66 7.66 7.50 7.58 8.22 7.86 225s 225s Robust Estimate of Covariance: 225s CONT INTG DMNR DILG CFMG DECI PREP 225s CONT 0.63426 -0.20121 -0.31858 -0.09578 0.00521 -0.00436 -0.07140 225s INTG -0.20121 0.28326 0.37540 0.27103 0.20362 0.19838 0.25706 225s DMNR -0.31858 0.37540 0.58265 0.33615 0.25649 0.24804 0.31696 225s DILG -0.09578 0.27103 0.33615 0.32588 0.27022 0.26302 0.32236 225s CFMG 0.00521 0.20362 0.25649 0.27022 0.25929 0.24217 0.27784 225s DECI -0.00436 0.19838 0.24804 0.26302 0.24217 0.23830 0.27284 225s PREP -0.07140 0.25706 0.31696 0.32236 0.27784 0.27284 0.35071 225s FAMI -0.07118 0.25858 0.29511 0.32582 0.27863 0.27657 0.35941 225s ORAL -0.11149 0.27055 0.33919 0.31768 0.27339 0.26739 0.34200 225s WRIT -0.10050 0.26857 0.32570 0.32327 0.27860 0.27201 0.34399 225s PHYS -0.09693 0.15339 0.18416 0.17089 0.13837 0.14895 0.18472 225s RTEN -0.15643 0.31793 0.40884 0.33863 0.27073 0.26854 0.34049 225s FAMI ORAL WRIT PHYS RTEN 225s CONT -0.07118 -0.11149 -0.10050 -0.09693 -0.15643 225s INTG 0.25858 0.27055 0.26857 0.15339 0.31793 225s DMNR 0.29511 0.33919 0.32570 0.18416 0.40884 225s DILG 0.32582 0.31768 0.32327 0.17089 0.33863 225s CFMG 0.27863 0.27339 0.27860 0.13837 0.27073 225s DECI 0.27657 0.26739 0.27201 0.14895 0.26854 225s PREP 0.35941 0.34200 0.34399 0.18472 0.34049 225s FAMI 0.38378 0.35617 0.36094 0.19998 0.35048 225s ORAL 0.35617 0.34918 0.34808 0.19759 0.35217 225s WRIT 0.36094 0.34808 0.35242 0.19666 0.35090 225s PHYS 0.19998 0.19759 0.19666 0.14770 0.20304 225s RTEN 0.35048 0.35217 0.35090 0.20304 0.39451 225s -------------------------------------------------------- 225s USArrests 50 4 19.206310 225s Outliers: 4 225s [1] 2 28 33 39 225s ------------- 225s 225s Call: 225s CovSest(x = x, method = method) 225s -> Method: S-estimates: Rocke type 225s 225s Robust Estimate of Location: 225s Murder Assault UrbanPop Rape 225s 7.55 160.94 65.10 19.97 225s 225s Robust Estimate of Covariance: 225s Murder Assault UrbanPop Rape 225s Murder 25.6 409.5 23.4 32.1 225s Assault 409.5 8530.9 676.9 669.4 225s UrbanPop 23.4 676.9 269.9 76.6 225s Rape 32.1 669.4 76.6 76.6 225s -------------------------------------------------------- 225s longley 16 7 13.387132 225s Outliers: 4 225s [1] 1 2 3 4 225s ------------- 225s 225s Call: 225s CovSest(x = x, method = method) 225s -> Method: S-estimates: Rocke type 225s 225s Robust Estimate of Location: 225s GNP.deflator GNP Unemployed Armed.Forces Population 225s 105.5 422.4 318.3 299.7 119.5 225s Year Employed 225s 1956.1 66.5 225s 225s Robust Estimate of Covariance: 225s GNP.deflator GNP Unemployed Armed.Forces Population 225s GNP.deflator 59.97 582.66 694.99 -237.75 46.12 225s GNP 582.66 5849.82 6383.68 -2207.26 461.15 225s Unemployed 694.99 6383.68 11155.03 -3104.18 534.25 225s Armed.Forces -237.75 -2207.26 -3104.18 1429.11 -171.28 225s Population 46.12 461.15 534.25 -171.28 36.79 225s Year 29.01 287.48 340.95 -112.61 22.85 225s Employed 18.99 193.66 186.31 -76.88 14.94 225s Year Employed 225s GNP.deflator 29.01 18.99 225s GNP 287.48 193.66 225s Unemployed 340.95 186.31 225s Armed.Forces -112.61 -76.88 225s Population 22.85 14.94 225s Year 14.36 9.45 225s Employed 9.45 6.90 225s -------------------------------------------------------- 225s Loblolly 84 3 7.757906 225s Outliers: 27 225s [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 225s [26] 83 84 225s ------------- 225s 225s Call: 225s CovSest(x = x, method = method) 225s -> Method: S-estimates: Rocke type 225s 225s Robust Estimate of Location: 225s height age Seed 225s 21.72 8.60 7.58 225s 225s Robust Estimate of Covariance: 225s height age Seed 225s height 316.590 102.273 5.939 225s age 102.273 33.465 -0.121 225s Seed 5.939 -0.121 27.203 225s -------------------------------------------------------- 225s quakes 1000 4 11.473431 225s Outliers: 237 225s [1] 7 12 15 17 22 25 27 28 32 37 40 41 45 48 53 225s [16] 63 64 73 78 87 91 92 94 99 108 110 117 118 119 120 225s [31] 121 122 126 133 136 141 143 145 148 152 154 155 157 159 160 225s [46] 163 166 170 174 176 192 205 222 226 230 239 243 244 250 251 225s [61] 252 254 258 263 267 268 271 283 292 297 300 301 305 311 312 225s [76] 318 320 321 325 328 330 331 334 352 357 360 365 368 376 381 225s [91] 382 384 389 399 400 402 408 410 413 416 417 418 419 426 429 225s [106] 437 441 443 453 456 467 474 477 490 492 496 504 507 508 509 225s [121] 517 524 527 528 531 532 534 536 538 539 541 542 543 544 545 225s [136] 546 547 552 553 558 560 570 571 581 583 587 593 594 596 597 225s [151] 605 612 613 618 620 625 629 638 642 647 649 653 655 656 672 225s [166] 675 681 686 699 701 702 712 714 716 721 725 726 735 744 753 225s [181] 754 756 759 765 766 769 779 781 782 785 787 797 804 813 825 225s [196] 827 837 840 844 852 853 857 860 865 866 869 870 872 873 883 225s [211] 884 887 888 890 891 893 908 909 912 915 916 921 927 930 952 225s [226] 962 963 969 974 980 982 986 987 988 992 997 1000 225s ------------- 225s 225s Call: 225s CovSest(x = x, method = method) 225s -> Method: S-estimates: Rocke type 225s 225s Robust Estimate of Location: 225s lat long depth mag 225s -21.45 182.54 351.18 4.55 225s 225s Robust Estimate of Covariance: 225s lat long depth mag 225s lat 2.10e+01 4.66e+00 2.45e+02 -3.38e-01 225s long 4.66e+00 5.88e+00 -4.63e+02 9.36e-02 225s depth 2.45e+02 -4.63e+02 6.38e+04 -2.02e+01 225s mag -3.38e-01 9.36e-02 -2.02e+01 1.78e-01 225s -------------------------------------------------------- 225s =================================================== 225s > dodata(method="MM") 225s 225s Call: dodata(method = "MM") 225s Data Set n p LOG(det) Time 225s =================================================== 225s heart 12 2 2.017701 225s Outliers: 1 225s [1] 6 225s ------------- 225s 225s Call: 225s CovMMest(x = x) 225s -> Method: MM-estimates 225s 225s Robust Estimate of Location: 225s height weight 225s 40.0 37.7 225s 225s Robust Estimate of Covariance: 225s height weight 225s height 99.2 205.7 225s weight 205.7 458.9 225s -------------------------------------------------------- 225s starsCYG 47 2 -1.450032 225s Outliers: 7 225s [1] 7 9 11 14 20 30 34 225s ------------- 225s 225s Call: 225s CovMMest(x = x) 225s -> Method: MM-estimates 225s 225s Robust Estimate of Location: 225s log.Te log.light 225s 4.41 4.94 225s 225s Robust Estimate of Covariance: 225s log.Te log.light 225s log.Te 0.0180 0.0526 225s log.light 0.0526 0.3217 225s -------------------------------------------------------- 225s phosphor 18 2 2.320721 225s Outliers: 1 225s [1] 6 225s ------------- 225s 225s Call: 225s CovMMest(x = x) 225s -> Method: MM-estimates 225s 225s Robust Estimate of Location: 225s inorg organic 225s 12.3 41.4 225s 225s Robust Estimate of Covariance: 225s inorg organic 225s inorg 94.2 67.2 225s organic 67.2 162.1 225s -------------------------------------------------------- 225s stackloss 21 3 1.470031 225s Outliers: 0 225s ------------- 225s 225s Call: 225s CovMMest(x = x) 225s -> Method: MM-estimates 225s 225s Robust Estimate of Location: 225s Air.Flow Water.Temp Acid.Conc. 225s 60.2 21.0 86.4 225s 225s Robust Estimate of Covariance: 225s Air.Flow Water.Temp Acid.Conc. 225s Air.Flow 81.13 21.99 23.15 225s Water.Temp 21.99 10.01 6.43 225s Acid.Conc. 23.15 6.43 27.22 225s -------------------------------------------------------- 225s coleman 20 5 0.491419 225s Outliers: 1 225s [1] 10 225s ------------- 225s 225s Call: 225s CovMMest(x = x) 225s -> Method: MM-estimates 225s 225s Robust Estimate of Location: 225s salaryP fatherWc sstatus teacherSc motherLev 225s 2.74 43.14 3.65 25.07 6.32 225s 225s Robust Estimate of Covariance: 225s salaryP fatherWc sstatus teacherSc motherLev 225s salaryP 0.1878 2.0635 1.0433 0.2721 0.0582 225s fatherWc 2.0635 670.2232 211.0609 4.3625 15.6083 225s sstatus 1.0433 211.0609 92.8743 2.6532 5.1816 225s teacherSc 0.2721 4.3625 2.6532 1.2757 0.1613 225s motherLev 0.0582 15.6083 5.1816 0.1613 0.4192 225s -------------------------------------------------------- 225s salinity 28 3 0.734619 225s Outliers: 2 225s [1] 5 16 225s ------------- 225s 225s Call: 225s CovMMest(x = x) 225s -> Method: MM-estimates 225s 225s Robust Estimate of Location: 225s X1 X2 X3 225s 10.46 2.66 23.15 225s 225s Robust Estimate of Covariance: 225s X1 X2 X3 225s X1 10.079 -0.024 -1.899 225s X2 -0.024 3.466 -1.817 225s X3 -1.899 -1.817 3.665 225s -------------------------------------------------------- 225s wood 20 5 -3.202636 225s Outliers: 0 225s ------------- 225s 225s Call: 225s CovMMest(x = x) 225s -> Method: MM-estimates 225s 225s Robust Estimate of Location: 225s x1 x2 x3 x4 x5 225s 0.550 0.133 0.506 0.511 0.909 225s 225s Robust Estimate of Covariance: 225s x1 x2 x3 x4 x5 225s x1 0.008454 -0.000377 0.003720 0.002874 -0.003065 225s x2 -0.000377 0.000516 -0.000399 -0.000933 0.000645 225s x3 0.003720 -0.000399 0.004186 0.001720 -0.001714 225s x4 0.002874 -0.000933 0.001720 0.003993 -0.001028 225s x5 -0.003065 0.000645 -0.001714 -0.001028 0.002744 225s -------------------------------------------------------- 225s hbk 75 3 0.283145 225s Outliers: 14 225s [1] 1 2 3 4 5 6 7 8 9 10 11 12 13 14 225s ------------- 225s 225s Call: 225s CovMMest(x = x) 225s -> Method: MM-estimates 225s 225s Robust Estimate of Location: 225s X1 X2 X3 225s 1.54 1.79 1.68 225s 225s Robust Estimate of Covariance: 225s X1 X2 X3 225s X1 1.8016 0.0739 0.2000 225s X2 0.0739 1.8301 0.2295 225s X3 0.2000 0.2295 1.7101 225s -------------------------------------------------------- 225s Animals 28 2 4.685129 225s Outliers: 10 225s [1] 2 6 7 9 12 14 15 16 24 25 225s ------------- 225s 225s Call: 225s CovMMest(x = x) 225s -> Method: MM-estimates 225s 225s Robust Estimate of Location: 225s body brain 225s 82 148 225s 225s Robust Estimate of Covariance: 225s body brain 225s body 21050 24534 225s brain 24534 35135 225s -------------------------------------------------------- 225s milk 86 8 -1.437863 225s Outliers: 12 225s [1] 1 2 3 12 13 17 41 44 47 70 74 75 225s ------------- 225s 225s Call: 225s CovMMest(x = x) 225s -> Method: MM-estimates 225s 225s Robust Estimate of Location: 225s X1 X2 X3 X4 X5 X6 X7 X8 225s 1.03 35.73 32.87 25.96 24.94 24.85 122.55 14.33 225s 225s Robust Estimate of Covariance: 225s X1 X2 X3 X4 X5 X6 X7 225s X1 1.08e-06 5.36e-04 6.80e-04 5.96e-04 5.87e-04 5.91e-04 2.22e-03 225s X2 5.36e-04 2.42e+00 7.07e-01 5.51e-01 4.89e-01 5.70e-01 3.08e+00 225s X3 6.80e-04 7.07e-01 1.64e+00 1.28e+00 1.25e+00 1.26e+00 2.38e+00 225s X4 5.96e-04 5.51e-01 1.28e+00 1.05e+00 1.01e+00 1.02e+00 2.01e+00 225s X5 5.87e-04 4.89e-01 1.25e+00 1.01e+00 1.05e+00 1.02e+00 1.96e+00 225s X6 5.91e-04 5.70e-01 1.26e+00 1.02e+00 1.02e+00 1.05e+00 2.01e+00 225s X7 2.22e-03 3.08e+00 2.38e+00 2.01e+00 1.96e+00 2.01e+00 9.22e+00 225s X8 1.68e-04 4.13e-01 3.37e-01 2.53e-01 2.34e-01 2.43e-01 8.81e-01 225s X8 225s X1 1.68e-04 225s X2 4.13e-01 225s X3 3.37e-01 225s X4 2.53e-01 225s X5 2.34e-01 225s X6 2.43e-01 225s X7 8.81e-01 225s X8 2.11e-01 225s -------------------------------------------------------- 225s bushfire 38 5 2.443148 225s Outliers: 12 225s [1] 8 9 10 11 31 32 33 34 35 36 37 38 225s ------------- 225s 225s Call: 225s CovMMest(x = x) 225s -> Method: MM-estimates 225s 225s Robust Estimate of Location: 225s V1 V2 V3 V4 V5 225s 109 149 258 215 276 225s 225s Robust Estimate of Covariance: 225s V1 V2 V3 V4 V5 225s V1 708 538 -2705 -558 -464 225s V2 538 497 -1376 -248 -216 225s V3 -2705 -1376 20521 4833 3914 225s V4 -558 -248 4833 1217 969 225s V5 -464 -216 3914 969 778 225s -------------------------------------------------------- 225s rice 105 5 -0.724874 225s Outliers: 5 225s [1] 9 42 49 58 71 225s ------------- 225s 225s Call: 225s CovMMest(x = x) 225s -> Method: MM-estimates 225s 225s Robust Estimate of Location: 225s Favor Appearance Taste Stickiness Toughness 225s -0.2653 0.0969 -0.1371 0.0483 0.0731 225s 225s Robust Estimate of Covariance: 225s Favor Appearance Taste Stickiness Toughness 225s Favor 0.421 0.349 0.427 0.405 -0.191 225s Appearance 0.349 0.605 0.565 0.553 -0.316 225s Taste 0.427 0.565 0.725 0.701 -0.378 225s Stickiness 0.405 0.553 0.701 0.868 -0.484 225s Toughness -0.191 -0.316 -0.378 -0.484 0.464 225s -------------------------------------------------------- 225s hemophilia 75 2 -1.868949 225s Outliers: 2 225s [1] 11 36 225s ------------- 225s 225s Call: 225s CovMMest(x = x) 225s -> Method: MM-estimates 225s 225s Robust Estimate of Location: 225s AHFactivity AHFantigen 225s -0.2342 -0.0333 225s 225s Robust Estimate of Covariance: 225s AHFactivity AHFantigen 225s AHFactivity 0.0309 0.0122 225s AHFantigen 0.0122 0.0231 225s -------------------------------------------------------- 225s fish 159 6 1.285876 225s Outliers: 20 225s [1] 61 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 225s [20] 142 225s ------------- 225s 225s Call: 225s CovMMest(x = x) 225s -> Method: MM-estimates 225s 225s Robust Estimate of Location: 225s Weight Length1 Length2 Length3 Height Width 225s 352.7 24.3 26.4 29.2 29.7 14.6 225s 225s Robust Estimate of Covariance: 225s Weight Length1 Length2 Length3 Height Width 225s Weight 1.20e+05 2.89e+03 3.12e+03 3.51e+03 1.49e+03 2.83e+02 225s Length1 2.89e+03 7.73e+01 8.35e+01 9.28e+01 3.73e+01 9.26e+00 225s Length2 3.12e+03 8.35e+01 9.04e+01 1.01e+02 4.16e+01 1.01e+01 225s Length3 3.51e+03 9.28e+01 1.01e+02 1.14e+02 5.37e+01 1.01e+01 225s Height 1.49e+03 3.73e+01 4.16e+01 5.37e+01 6.75e+01 3.22e+00 225s Width 2.83e+02 9.26e+00 1.01e+01 1.01e+01 3.22e+00 4.18e+00 225s -------------------------------------------------------- 225s airquality 153 4 2.684374 225s Outliers: 6 225s [1] 7 14 23 30 34 77 225s ------------- 225s 225s Call: 225s CovMMest(x = x) 225s -> Method: MM-estimates 225s 225s Robust Estimate of Location: 225s Ozone Solar.R Wind Temp 225s 40.35 186.21 9.86 78.09 225s 225s Robust Estimate of Covariance: 225s Ozone Solar.R Wind Temp 225s Ozone 951.0 959.9 -62.5 224.6 225s Solar.R 959.9 8629.9 -28.1 244.9 225s Wind -62.5 -28.1 11.6 -15.8 225s Temp 224.6 244.9 -15.8 93.1 225s -------------------------------------------------------- 225s attitude 30 7 2.091968 225s Outliers: 4 225s [1] 14 16 18 24 225s ------------- 225s 225s Call: 225s CovMMest(x = x) 225s -> Method: MM-estimates 225s 225s Robust Estimate of Location: 225s rating complaints privileges learning raises critical 225s 65.0 66.5 52.4 56.2 65.3 75.6 225s advance 225s 42.7 225s 225s Robust Estimate of Covariance: 225s rating complaints privileges learning raises critical advance 225s rating 143.5 123.4 62.4 92.5 79.2 17.7 28.2 225s complaints 123.4 159.8 83.9 99.7 96.0 27.3 44.0 225s privileges 62.4 83.9 133.5 78.6 62.0 13.4 46.4 225s learning 92.5 99.7 78.6 136.0 90.9 18.9 62.6 225s raises 79.2 96.0 62.0 90.9 107.6 34.6 63.3 225s critical 17.7 27.3 13.4 18.9 34.6 84.9 25.9 225s advance 28.2 44.0 46.4 62.6 63.3 25.9 94.4 225s -------------------------------------------------------- 225s attenu 182 5 1.148032 225s Outliers: 21 225s [1] 2 7 8 9 10 11 15 16 24 25 28 29 30 31 32 64 65 94 95 225s [20] 96 100 225s ------------- 225s 225s Call: 225s CovMMest(x = x) 225s -> Method: MM-estimates 225s 225s Robust Estimate of Location: 225s event mag station dist accel 225s 15.36 5.95 58.11 33.56 0.14 225s 225s Robust Estimate of Covariance: 225s event mag station dist accel 225s event 4.88e+01 -2.74e+00 1.53e+02 -1.14e+02 5.95e-02 225s mag -2.74e+00 5.32e-01 -6.29e+00 1.10e+01 9.37e-03 225s station 1.53e+02 -6.29e+00 1.29e+03 -2.95e+02 1.04e+00 225s dist -1.14e+02 1.10e+01 -2.95e+02 1.13e+03 -2.41e+00 225s accel 5.95e-02 9.37e-03 1.04e+00 -2.41e+00 1.70e-02 225s -------------------------------------------------------- 225s USJudgeRatings 43 12 -1.683847 225s Outliers: 7 225s [1] 5 7 12 13 14 23 31 225s ------------- 225s 225s Call: 225s CovMMest(x = x) 225s -> Method: MM-estimates 225s 225s Robust Estimate of Location: 225s CONT INTG DMNR DILG CFMG DECI PREP FAMI ORAL WRIT PHYS RTEN 225s 7.45 8.15 7.74 7.87 7.67 7.74 7.65 7.65 7.50 7.57 8.17 7.85 225s 225s Robust Estimate of Covariance: 225s CONT INTG DMNR DILG CFMG DECI PREP FAMI 225s CONT 0.9403 -0.2500 -0.3953 -0.1418 -0.0176 -0.0620 -0.1304 -0.1517 225s INTG -0.2500 0.6314 0.8479 0.6889 0.5697 0.5386 0.7007 0.6985 225s DMNR -0.3953 0.8479 1.2186 0.9027 0.7613 0.7232 0.9191 0.9055 225s DILG -0.1418 0.6889 0.9027 0.8474 0.7344 0.6949 0.8751 0.8655 225s CFMG -0.0176 0.5697 0.7613 0.7344 0.6904 0.6442 0.7683 0.7594 225s DECI -0.0620 0.5386 0.7232 0.6949 0.6442 0.6219 0.7362 0.7360 225s PREP -0.1304 0.7007 0.9191 0.8751 0.7683 0.7362 0.9370 0.9357 225s FAMI -0.1517 0.6985 0.9055 0.8655 0.7594 0.7360 0.9357 0.9547 225s ORAL -0.1866 0.7375 0.9841 0.8816 0.7747 0.7433 0.9400 0.9496 225s WRIT -0.1881 0.7208 0.9516 0.8711 0.7646 0.7357 0.9302 0.9439 225s PHYS -0.1407 0.4673 0.6261 0.5661 0.5105 0.5039 0.5996 0.6112 225s RTEN -0.2494 0.7921 1.0688 0.9167 0.7902 0.7585 0.9533 0.9561 225s ORAL WRIT PHYS RTEN 225s CONT -0.1866 -0.1881 -0.1407 -0.2494 225s INTG 0.7375 0.7208 0.4673 0.7921 225s DMNR 0.9841 0.9516 0.6261 1.0688 225s DILG 0.8816 0.8711 0.5661 0.9167 225s CFMG 0.7747 0.7646 0.5105 0.7902 225s DECI 0.7433 0.7357 0.5039 0.7585 225s PREP 0.9400 0.9302 0.5996 0.9533 225s FAMI 0.9496 0.9439 0.6112 0.9561 225s ORAL 0.9712 0.9558 0.6271 0.9933 225s WRIT 0.9558 0.9483 0.6135 0.9725 225s PHYS 0.6271 0.6135 0.4816 0.6549 225s RTEN 0.9933 0.9725 0.6549 1.0540 225s -------------------------------------------------------- 225s USArrests 50 4 2.411726 225s Outliers: 3 225s [1] 2 33 39 225s ------------- 225s 225s Call: 225s CovMMest(x = x) 225s -> Method: MM-estimates 225s 225s Robust Estimate of Location: 225s Murder Assault UrbanPop Rape 225s 7.52 163.86 65.66 20.64 225s 225s Robust Estimate of Covariance: 225s Murder Assault UrbanPop Rape 225s Murder 19.05 295.96 8.32 23.40 225s Assault 295.96 6905.03 396.53 523.49 225s UrbanPop 8.32 396.53 202.98 62.81 225s Rape 23.40 523.49 62.81 79.10 225s -------------------------------------------------------- 225s longley 16 7 1.038316 225s Outliers: 5 225s [1] 1 2 3 4 5 225s ------------- 225s 225s Call: 225s CovMMest(x = x) 225s -> Method: MM-estimates 225s 225s Robust Estimate of Location: 225s GNP.deflator GNP Unemployed Armed.Forces Population 225s 107.5 440.4 339.4 293.0 120.9 225s Year Employed 225s 1957.0 67.2 225s 225s Robust Estimate of Covariance: 225s GNP.deflator GNP Unemployed Armed.Forces Population 225s GNP.deflator 100.4 953.8 1140.8 -501.8 74.3 225s GNP 953.8 9434.3 10084.3 -4573.8 731.3 225s Unemployed 1140.8 10084.3 19644.6 -6296.3 848.4 225s Armed.Forces -501.8 -4573.8 -6296.3 3192.3 -348.5 225s Population 74.3 731.3 848.4 -348.5 57.7 225s Year 46.3 450.7 537.0 -230.7 35.3 225s Employed 30.8 310.2 273.8 -159.4 23.3 225s Year Employed 225s GNP.deflator 46.3 30.8 225s GNP 450.7 310.2 225s Unemployed 537.0 273.8 225s Armed.Forces -230.7 -159.4 225s Population 35.3 23.3 225s Year 21.9 14.6 225s Employed 14.6 11.2 225s -------------------------------------------------------- 225s Loblolly 84 3 1.481317 225s Outliers: 0 225s ------------- 225s 225s Call: 225s CovMMest(x = x) 225s -> Method: MM-estimates 225s 225s Robust Estimate of Location: 225s height age Seed 225s 31.93 12.79 7.48 225s 225s Robust Estimate of Covariance: 225s height age Seed 225s height 440.644 165.652 6.958 225s age 165.652 63.500 0.681 225s Seed 6.958 0.681 16.564 225s -------------------------------------------------------- 225s quakes 1000 4 1.576855 225s Outliers: 218 225s [1] 7 12 15 17 22 27 32 37 40 41 45 48 53 63 64 225s [16] 73 78 87 91 92 94 99 108 110 117 118 119 120 121 122 225s [31] 126 133 136 141 143 145 148 152 154 155 157 159 160 163 170 225s [46] 192 205 222 226 230 239 243 250 251 252 254 258 263 267 268 225s [61] 271 283 292 300 301 305 311 312 318 320 321 325 328 330 334 225s [76] 352 357 360 365 381 382 384 389 400 402 408 413 416 417 419 225s [91] 429 437 441 443 453 456 467 474 477 490 492 496 504 507 508 225s [106] 509 517 524 527 528 531 532 534 536 538 539 541 542 543 544 225s [121] 545 546 547 552 553 560 571 581 583 587 593 594 596 597 605 225s [136] 612 613 618 620 625 629 638 642 647 649 653 655 656 672 675 225s [151] 681 686 699 701 702 712 714 716 721 725 726 735 744 754 756 225s [166] 759 765 766 769 779 781 782 785 787 797 804 813 825 827 837 225s [181] 840 844 852 853 857 860 865 866 869 870 872 873 883 884 887 225s [196] 888 890 891 893 908 909 912 915 916 921 927 930 962 963 969 225s [211] 974 980 982 986 987 988 997 1000 225s ------------- 225s 225s Call: 225s CovMMest(x = x) 225s -> Method: MM-estimates 225s 225s Robust Estimate of Location: 225s lat long depth mag 225s -21.74 182.37 356.37 4.56 225s 225s Robust Estimate of Covariance: 225s lat long depth mag 225s lat 2.97e+01 6.53e+00 3.46e+02 -4.66e-01 225s long 6.53e+00 6.92e+00 -5.05e+02 5.62e-02 225s depth 3.46e+02 -5.05e+02 7.39e+04 -2.51e+01 225s mag -4.66e-01 5.62e-02 -2.51e+01 2.32e-01 225s -------------------------------------------------------- 225s =================================================== 225s > ##dogen() 225s > ##cat('Time elapsed: ', proc.time(),'\n') # for ``statistical reasons'' 225s > 226s autopkgtest [23:13:17]: test run-unit-test: -----------------------] 226s run-unit-test PASS 226s autopkgtest [23:13:17]: test run-unit-test: - - - - - - - - - - results - - - - - - - - - - 227s autopkgtest [23:13:18]: test pkg-r-autopkgtest: preparing testbed 227s Reading package lists... 227s Building dependency tree... 227s Reading state information... 227s Solving dependencies... 227s The following NEW packages will be installed: 227s build-essential cpp cpp-15 cpp-15-aarch64-linux-gnu cpp-aarch64-linux-gnu 227s dctrl-tools g++ g++-15 g++-15-aarch64-linux-gnu g++-aarch64-linux-gnu gcc 227s gcc-15 gcc-15-aarch64-linux-gnu gcc-aarch64-linux-gnu gfortran gfortran-15 227s gfortran-15-aarch64-linux-gnu gfortran-aarch64-linux-gnu icu-devtools 227s libasan8 libblas-dev libbz2-dev libc-dev-bin libc6-dev libcc1-0 libcrypt-dev 227s libdeflate-dev libgcc-15-dev libgfortran-15-dev libhwasan0 libicu-dev 227s libisl23 libitm1 libjpeg-dev libjpeg-turbo8-dev libjpeg8-dev liblapack-dev 227s liblsan0 liblzma-dev libmpc3 libncurses-dev libpcre2-16-0 libpcre2-32-0 227s libpcre2-dev libpcre2-posix3 libpkgconf3 libpng-dev libreadline-dev 227s libstdc++-15-dev libtirpc-dev libtsan2 libubsan1 libzstd-dev linux-libc-dev 227s pkg-r-autopkgtest pkgconf pkgconf-bin r-base-dev rpcsvc-proto zlib1g-dev 228s 0 upgraded, 60 newly installed, 0 to remove and 0 not upgraded. 228s Need to get 103 MB of archives. 228s After this operation, 377 MB of additional disk space will be used. 228s Get:1 http://ftpmaster.internal/ubuntu resolute/main arm64 libc-dev-bin arm64 2.42-2ubuntu4 [22.5 kB] 228s Get:2 http://ftpmaster.internal/ubuntu resolute/main arm64 linux-libc-dev arm64 6.19.0-3.3 [1819 kB] 230s Get:3 http://ftpmaster.internal/ubuntu resolute/main arm64 libcrypt-dev arm64 1:4.5.1-1 [123 kB] 230s Get:4 http://ftpmaster.internal/ubuntu resolute/main arm64 rpcsvc-proto arm64 1.4.3-1build1 [65.6 kB] 230s Get:5 http://ftpmaster.internal/ubuntu resolute/main arm64 libc6-dev arm64 2.42-2ubuntu4 [1765 kB] 232s Get:6 http://ftpmaster.internal/ubuntu resolute/main arm64 libisl23 arm64 0.27-1build1 [676 kB] 233s Get:7 http://ftpmaster.internal/ubuntu resolute/main arm64 libmpc3 arm64 1.3.1-2 [55.6 kB] 233s Get:8 http://ftpmaster.internal/ubuntu resolute/main arm64 cpp-15-aarch64-linux-gnu arm64 15.2.0-12ubuntu1 [11.7 MB] 248s Get:9 http://ftpmaster.internal/ubuntu resolute/main arm64 cpp-15 arm64 15.2.0-12ubuntu1 [1030 B] 248s Get:10 http://ftpmaster.internal/ubuntu resolute/main arm64 cpp-aarch64-linux-gnu arm64 4:15.2.0-4ubuntu1 [5736 B] 248s Get:11 http://ftpmaster.internal/ubuntu resolute/main arm64 cpp arm64 4:15.2.0-4ubuntu1 [22.4 kB] 248s Get:12 http://ftpmaster.internal/ubuntu resolute/main arm64 libcc1-0 arm64 15.2.0-12ubuntu1 [49.0 kB] 248s Get:13 http://ftpmaster.internal/ubuntu resolute/main arm64 libitm1 arm64 15.2.0-12ubuntu1 [27.8 kB] 248s Get:14 http://ftpmaster.internal/ubuntu resolute/main arm64 libasan8 arm64 15.2.0-12ubuntu1 [2920 kB] 253s Get:15 http://ftpmaster.internal/ubuntu resolute/main arm64 liblsan0 arm64 15.2.0-12ubuntu1 [1316 kB] 255s Get:16 http://ftpmaster.internal/ubuntu resolute/main arm64 libtsan2 arm64 15.2.0-12ubuntu1 [2688 kB] 259s Get:17 http://ftpmaster.internal/ubuntu resolute/main arm64 libubsan1 arm64 15.2.0-12ubuntu1 [1175 kB] 260s Get:18 http://ftpmaster.internal/ubuntu resolute/main arm64 libhwasan0 arm64 15.2.0-12ubuntu1 [1638 kB] 263s Get:19 http://ftpmaster.internal/ubuntu resolute/main arm64 libgcc-15-dev arm64 15.2.0-12ubuntu1 [2600 kB] 266s Get:20 http://ftpmaster.internal/ubuntu resolute/main arm64 gcc-15-aarch64-linux-gnu arm64 15.2.0-12ubuntu1 [23.1 MB] 295s Get:21 http://ftpmaster.internal/ubuntu resolute/main arm64 gcc-15 arm64 15.2.0-12ubuntu1 [519 kB] 295s Get:22 http://ftpmaster.internal/ubuntu resolute/main arm64 gcc-aarch64-linux-gnu arm64 4:15.2.0-4ubuntu1 [1206 B] 295s Get:23 http://ftpmaster.internal/ubuntu resolute/main arm64 gcc arm64 4:15.2.0-4ubuntu1 [5016 B] 295s Get:24 http://ftpmaster.internal/ubuntu resolute/main arm64 libstdc++-15-dev arm64 15.2.0-12ubuntu1 [2549 kB] 298s Get:25 http://ftpmaster.internal/ubuntu resolute/main arm64 g++-15-aarch64-linux-gnu arm64 15.2.0-12ubuntu1 [13.2 MB] 313s Get:26 http://ftpmaster.internal/ubuntu resolute/main arm64 g++-15 arm64 15.2.0-12ubuntu1 [25.3 kB] 313s Get:27 http://ftpmaster.internal/ubuntu resolute/main arm64 g++-aarch64-linux-gnu arm64 4:15.2.0-4ubuntu1 [956 B] 313s Get:28 http://ftpmaster.internal/ubuntu resolute/main arm64 g++ arm64 4:15.2.0-4ubuntu1 [1080 B] 313s Get:29 http://ftpmaster.internal/ubuntu resolute/main arm64 build-essential arm64 12.12ubuntu2 [5254 B] 313s Get:30 http://ftpmaster.internal/ubuntu resolute/main arm64 dctrl-tools arm64 2.24-3build4 [102 kB] 313s Get:31 http://ftpmaster.internal/ubuntu resolute/main arm64 libgfortran-15-dev arm64 15.2.0-12ubuntu1 [490 kB] 313s Get:32 http://ftpmaster.internal/ubuntu resolute/main arm64 gfortran-15-aarch64-linux-gnu arm64 15.2.0-12ubuntu1 [12.5 MB] 329s Get:33 http://ftpmaster.internal/ubuntu resolute/main arm64 gfortran-15 arm64 15.2.0-12ubuntu1 [18.1 kB] 329s Get:34 http://ftpmaster.internal/ubuntu resolute/main arm64 gfortran-aarch64-linux-gnu arm64 4:15.2.0-4ubuntu1 [1022 B] 329s Get:35 http://ftpmaster.internal/ubuntu resolute/main arm64 gfortran arm64 4:15.2.0-4ubuntu1 [1160 B] 329s Get:36 http://ftpmaster.internal/ubuntu resolute/main arm64 icu-devtools arm64 78.2-1ubuntu1 [207 kB] 329s Get:37 http://ftpmaster.internal/ubuntu resolute/main arm64 libblas-dev arm64 3.12.1-7ubuntu1 [160 kB] 329s Get:38 http://ftpmaster.internal/ubuntu resolute/main arm64 libbz2-dev arm64 1.0.8-6build2 [34.9 kB] 329s Get:39 http://ftpmaster.internal/ubuntu resolute/main arm64 libdeflate-dev arm64 1.23-2build1 [54.3 kB] 329s Get:40 http://ftpmaster.internal/ubuntu resolute/main arm64 libicu-dev arm64 78.2-1ubuntu1 [12.5 MB] 344s Get:41 http://ftpmaster.internal/ubuntu resolute/main arm64 libjpeg-turbo8-dev arm64 2.1.5-4ubuntu3 [301 kB] 344s Get:42 http://ftpmaster.internal/ubuntu resolute/main arm64 libjpeg8-dev arm64 8c-2ubuntu11 [1484 B] 344s Get:43 http://ftpmaster.internal/ubuntu resolute/main arm64 libjpeg-dev arm64 8c-2ubuntu11 [1482 B] 344s Get:44 http://ftpmaster.internal/ubuntu resolute/main arm64 liblapack-dev arm64 3.12.1-7ubuntu1 [4456 kB] 350s Get:45 http://ftpmaster.internal/ubuntu resolute/main arm64 libncurses-dev arm64 6.6+20251231-1 [391 kB] 350s Get:46 http://ftpmaster.internal/ubuntu resolute/main arm64 libpcre2-16-0 arm64 10.46-1 [225 kB] 350s Get:47 http://ftpmaster.internal/ubuntu resolute/main arm64 libpcre2-32-0 arm64 10.46-1 [213 kB] 350s Get:48 http://ftpmaster.internal/ubuntu resolute/main arm64 libpcre2-posix3 arm64 10.46-1 [7300 B] 350s Get:49 http://ftpmaster.internal/ubuntu resolute/main arm64 libpcre2-dev arm64 10.46-1 [772 kB] 351s Get:50 http://ftpmaster.internal/ubuntu resolute/main arm64 libpkgconf3 arm64 1.8.1-4build1 [33.7 kB] 351s Get:51 http://ftpmaster.internal/ubuntu resolute/main arm64 zlib1g-dev arm64 1:1.3.dfsg+really1.3.1-1ubuntu2 [899 kB] 352s Get:52 http://ftpmaster.internal/ubuntu resolute/main arm64 libpng-dev arm64 1.6.54-1 [268 kB] 352s Get:53 http://ftpmaster.internal/ubuntu resolute/main arm64 libreadline-dev arm64 8.3-3 [199 kB] 352s Get:54 http://ftpmaster.internal/ubuntu resolute/main arm64 libzstd-dev arm64 1.5.7+dfsg-3 [349 kB] 352s Get:55 http://ftpmaster.internal/ubuntu resolute/main arm64 liblzma-dev arm64 5.8.2-2 [180 kB] 352s Get:56 http://ftpmaster.internal/ubuntu resolute/main arm64 pkgconf-bin arm64 1.8.1-4build1 [21.7 kB] 352s Get:57 http://ftpmaster.internal/ubuntu resolute/main arm64 pkgconf arm64 1.8.1-4build1 [16.8 kB] 352s Get:58 http://ftpmaster.internal/ubuntu resolute/main arm64 libtirpc-dev arm64 1.3.6+ds-1 [202 kB] 352s Get:59 http://ftpmaster.internal/ubuntu resolute/universe arm64 r-base-dev all 4.5.2-1ubuntu2 [1880 B] 352s Get:60 http://ftpmaster.internal/ubuntu resolute/universe arm64 pkg-r-autopkgtest all 20250812 [6158 B] 352s Fetched 103 MB in 2min 5s (825 kB/s) 352s Selecting previously unselected package libc-dev-bin. 352s (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 ... 139228 files and directories currently installed.) 352s Preparing to unpack .../00-libc-dev-bin_2.42-2ubuntu4_arm64.deb ... 352s Unpacking libc-dev-bin (2.42-2ubuntu4) ... 353s Selecting previously unselected package linux-libc-dev:arm64. 353s Preparing to unpack .../01-linux-libc-dev_6.19.0-3.3_arm64.deb ... 353s Unpacking linux-libc-dev:arm64 (6.19.0-3.3) ... 353s Selecting previously unselected package libcrypt-dev:arm64. 353s Preparing to unpack .../02-libcrypt-dev_1%3a4.5.1-1_arm64.deb ... 353s Unpacking libcrypt-dev:arm64 (1:4.5.1-1) ... 353s Selecting previously unselected package rpcsvc-proto. 353s Preparing to unpack .../03-rpcsvc-proto_1.4.3-1build1_arm64.deb ... 353s Unpacking rpcsvc-proto (1.4.3-1build1) ... 353s Selecting previously unselected package libc6-dev:arm64. 353s Preparing to unpack .../04-libc6-dev_2.42-2ubuntu4_arm64.deb ... 353s Unpacking libc6-dev:arm64 (2.42-2ubuntu4) ... 353s Selecting previously unselected package libisl23:arm64. 353s Preparing to unpack .../05-libisl23_0.27-1build1_arm64.deb ... 353s Unpacking libisl23:arm64 (0.27-1build1) ... 353s Selecting previously unselected package libmpc3:arm64. 353s Preparing to unpack .../06-libmpc3_1.3.1-2_arm64.deb ... 353s Unpacking libmpc3:arm64 (1.3.1-2) ... 353s Selecting previously unselected package cpp-15-aarch64-linux-gnu. 353s Preparing to unpack .../07-cpp-15-aarch64-linux-gnu_15.2.0-12ubuntu1_arm64.deb ... 353s Unpacking cpp-15-aarch64-linux-gnu (15.2.0-12ubuntu1) ... 353s Selecting previously unselected package cpp-15. 353s Preparing to unpack .../08-cpp-15_15.2.0-12ubuntu1_arm64.deb ... 353s Unpacking cpp-15 (15.2.0-12ubuntu1) ... 353s Selecting previously unselected package cpp-aarch64-linux-gnu. 353s Preparing to unpack .../09-cpp-aarch64-linux-gnu_4%3a15.2.0-4ubuntu1_arm64.deb ... 353s Unpacking cpp-aarch64-linux-gnu (4:15.2.0-4ubuntu1) ... 353s Selecting previously unselected package cpp. 353s Preparing to unpack .../10-cpp_4%3a15.2.0-4ubuntu1_arm64.deb ... 353s Unpacking cpp (4:15.2.0-4ubuntu1) ... 353s Selecting previously unselected package libcc1-0:arm64. 353s Preparing to unpack .../11-libcc1-0_15.2.0-12ubuntu1_arm64.deb ... 353s Unpacking libcc1-0:arm64 (15.2.0-12ubuntu1) ... 353s Selecting previously unselected package libitm1:arm64. 353s Preparing to unpack .../12-libitm1_15.2.0-12ubuntu1_arm64.deb ... 353s Unpacking libitm1:arm64 (15.2.0-12ubuntu1) ... 353s Selecting previously unselected package libasan8:arm64. 353s Preparing to unpack .../13-libasan8_15.2.0-12ubuntu1_arm64.deb ... 353s Unpacking libasan8:arm64 (15.2.0-12ubuntu1) ... 353s Selecting previously unselected package liblsan0:arm64. 353s Preparing to unpack .../14-liblsan0_15.2.0-12ubuntu1_arm64.deb ... 353s Unpacking liblsan0:arm64 (15.2.0-12ubuntu1) ... 354s Selecting previously unselected package libtsan2:arm64. 354s Preparing to unpack .../15-libtsan2_15.2.0-12ubuntu1_arm64.deb ... 354s Unpacking libtsan2:arm64 (15.2.0-12ubuntu1) ... 354s Selecting previously unselected package libubsan1:arm64. 354s Preparing to unpack .../16-libubsan1_15.2.0-12ubuntu1_arm64.deb ... 354s Unpacking libubsan1:arm64 (15.2.0-12ubuntu1) ... 354s Selecting previously unselected package libhwasan0:arm64. 354s Preparing to unpack .../17-libhwasan0_15.2.0-12ubuntu1_arm64.deb ... 354s Unpacking libhwasan0:arm64 (15.2.0-12ubuntu1) ... 354s Selecting previously unselected package libgcc-15-dev:arm64. 354s Preparing to unpack .../18-libgcc-15-dev_15.2.0-12ubuntu1_arm64.deb ... 354s Unpacking libgcc-15-dev:arm64 (15.2.0-12ubuntu1) ... 354s Selecting previously unselected package gcc-15-aarch64-linux-gnu. 354s Preparing to unpack .../19-gcc-15-aarch64-linux-gnu_15.2.0-12ubuntu1_arm64.deb ... 354s Unpacking gcc-15-aarch64-linux-gnu (15.2.0-12ubuntu1) ... 354s Selecting previously unselected package gcc-15. 354s Preparing to unpack .../20-gcc-15_15.2.0-12ubuntu1_arm64.deb ... 354s Unpacking gcc-15 (15.2.0-12ubuntu1) ... 354s Selecting previously unselected package gcc-aarch64-linux-gnu. 354s Preparing to unpack .../21-gcc-aarch64-linux-gnu_4%3a15.2.0-4ubuntu1_arm64.deb ... 354s Unpacking gcc-aarch64-linux-gnu (4:15.2.0-4ubuntu1) ... 354s Selecting previously unselected package gcc. 354s Preparing to unpack .../22-gcc_4%3a15.2.0-4ubuntu1_arm64.deb ... 354s Unpacking gcc (4:15.2.0-4ubuntu1) ... 354s Selecting previously unselected package libstdc++-15-dev:arm64. 354s Preparing to unpack .../23-libstdc++-15-dev_15.2.0-12ubuntu1_arm64.deb ... 354s Unpacking libstdc++-15-dev:arm64 (15.2.0-12ubuntu1) ... 355s Selecting previously unselected package g++-15-aarch64-linux-gnu. 355s Preparing to unpack .../24-g++-15-aarch64-linux-gnu_15.2.0-12ubuntu1_arm64.deb ... 355s Unpacking g++-15-aarch64-linux-gnu (15.2.0-12ubuntu1) ... 355s Selecting previously unselected package g++-15. 355s Preparing to unpack .../25-g++-15_15.2.0-12ubuntu1_arm64.deb ... 355s Unpacking g++-15 (15.2.0-12ubuntu1) ... 355s Selecting previously unselected package g++-aarch64-linux-gnu. 355s Preparing to unpack .../26-g++-aarch64-linux-gnu_4%3a15.2.0-4ubuntu1_arm64.deb ... 355s Unpacking g++-aarch64-linux-gnu (4:15.2.0-4ubuntu1) ... 355s Selecting previously unselected package g++. 355s Preparing to unpack .../27-g++_4%3a15.2.0-4ubuntu1_arm64.deb ... 355s Unpacking g++ (4:15.2.0-4ubuntu1) ... 355s Selecting previously unselected package build-essential. 355s Preparing to unpack .../28-build-essential_12.12ubuntu2_arm64.deb ... 355s Unpacking build-essential (12.12ubuntu2) ... 355s Selecting previously unselected package dctrl-tools. 355s Preparing to unpack .../29-dctrl-tools_2.24-3build4_arm64.deb ... 355s Unpacking dctrl-tools (2.24-3build4) ... 355s Selecting previously unselected package libgfortran-15-dev:arm64. 355s Preparing to unpack .../30-libgfortran-15-dev_15.2.0-12ubuntu1_arm64.deb ... 355s Unpacking libgfortran-15-dev:arm64 (15.2.0-12ubuntu1) ... 355s Selecting previously unselected package gfortran-15-aarch64-linux-gnu. 355s Preparing to unpack .../31-gfortran-15-aarch64-linux-gnu_15.2.0-12ubuntu1_arm64.deb ... 355s Unpacking gfortran-15-aarch64-linux-gnu (15.2.0-12ubuntu1) ... 355s Selecting previously unselected package gfortran-15. 355s Preparing to unpack .../32-gfortran-15_15.2.0-12ubuntu1_arm64.deb ... 355s Unpacking gfortran-15 (15.2.0-12ubuntu1) ... 355s Selecting previously unselected package gfortran-aarch64-linux-gnu. 355s Preparing to unpack .../33-gfortran-aarch64-linux-gnu_4%3a15.2.0-4ubuntu1_arm64.deb ... 355s Unpacking gfortran-aarch64-linux-gnu (4:15.2.0-4ubuntu1) ... 355s Selecting previously unselected package gfortran. 355s Preparing to unpack .../34-gfortran_4%3a15.2.0-4ubuntu1_arm64.deb ... 355s Unpacking gfortran (4:15.2.0-4ubuntu1) ... 355s Selecting previously unselected package icu-devtools. 355s Preparing to unpack .../35-icu-devtools_78.2-1ubuntu1_arm64.deb ... 355s Unpacking icu-devtools (78.2-1ubuntu1) ... 355s Selecting previously unselected package libblas-dev:arm64. 355s Preparing to unpack .../36-libblas-dev_3.12.1-7ubuntu1_arm64.deb ... 355s Unpacking libblas-dev:arm64 (3.12.1-7ubuntu1) ... 355s Selecting previously unselected package libbz2-dev:arm64. 355s Preparing to unpack .../37-libbz2-dev_1.0.8-6build2_arm64.deb ... 355s Unpacking libbz2-dev:arm64 (1.0.8-6build2) ... 356s Selecting previously unselected package libdeflate-dev:arm64. 356s Preparing to unpack .../38-libdeflate-dev_1.23-2build1_arm64.deb ... 356s Unpacking libdeflate-dev:arm64 (1.23-2build1) ... 356s Selecting previously unselected package libicu-dev:arm64. 356s Preparing to unpack .../39-libicu-dev_78.2-1ubuntu1_arm64.deb ... 356s Unpacking libicu-dev:arm64 (78.2-1ubuntu1) ... 356s Selecting previously unselected package libjpeg-turbo8-dev:arm64. 356s Preparing to unpack .../40-libjpeg-turbo8-dev_2.1.5-4ubuntu3_arm64.deb ... 356s Unpacking libjpeg-turbo8-dev:arm64 (2.1.5-4ubuntu3) ... 356s Selecting previously unselected package libjpeg8-dev:arm64. 356s Preparing to unpack .../41-libjpeg8-dev_8c-2ubuntu11_arm64.deb ... 356s Unpacking libjpeg8-dev:arm64 (8c-2ubuntu11) ... 356s Selecting previously unselected package libjpeg-dev:arm64. 356s Preparing to unpack .../42-libjpeg-dev_8c-2ubuntu11_arm64.deb ... 356s Unpacking libjpeg-dev:arm64 (8c-2ubuntu11) ... 356s Selecting previously unselected package liblapack-dev:arm64. 356s Preparing to unpack .../43-liblapack-dev_3.12.1-7ubuntu1_arm64.deb ... 356s Unpacking liblapack-dev:arm64 (3.12.1-7ubuntu1) ... 356s Selecting previously unselected package libncurses-dev:arm64. 356s Preparing to unpack .../44-libncurses-dev_6.6+20251231-1_arm64.deb ... 356s Unpacking libncurses-dev:arm64 (6.6+20251231-1) ... 356s Selecting previously unselected package libpcre2-16-0:arm64. 356s Preparing to unpack .../45-libpcre2-16-0_10.46-1_arm64.deb ... 356s Unpacking libpcre2-16-0:arm64 (10.46-1) ... 356s Selecting previously unselected package libpcre2-32-0:arm64. 356s Preparing to unpack .../46-libpcre2-32-0_10.46-1_arm64.deb ... 356s Unpacking libpcre2-32-0:arm64 (10.46-1) ... 356s Selecting previously unselected package libpcre2-posix3:arm64. 356s Preparing to unpack .../47-libpcre2-posix3_10.46-1_arm64.deb ... 356s Unpacking libpcre2-posix3:arm64 (10.46-1) ... 356s Selecting previously unselected package libpcre2-dev:arm64. 356s Preparing to unpack .../48-libpcre2-dev_10.46-1_arm64.deb ... 356s Unpacking libpcre2-dev:arm64 (10.46-1) ... 356s Selecting previously unselected package libpkgconf3:arm64. 356s Preparing to unpack .../49-libpkgconf3_1.8.1-4build1_arm64.deb ... 356s Unpacking libpkgconf3:arm64 (1.8.1-4build1) ... 356s Selecting previously unselected package zlib1g-dev:arm64. 356s Preparing to unpack .../50-zlib1g-dev_1%3a1.3.dfsg+really1.3.1-1ubuntu2_arm64.deb ... 356s Unpacking zlib1g-dev:arm64 (1:1.3.dfsg+really1.3.1-1ubuntu2) ... 356s Selecting previously unselected package libpng-dev:arm64. 356s Preparing to unpack .../51-libpng-dev_1.6.54-1_arm64.deb ... 356s Unpacking libpng-dev:arm64 (1.6.54-1) ... 356s Selecting previously unselected package libreadline-dev:arm64. 356s Preparing to unpack .../52-libreadline-dev_8.3-3_arm64.deb ... 356s Unpacking libreadline-dev:arm64 (8.3-3) ... 357s Selecting previously unselected package libzstd-dev:arm64. 357s Preparing to unpack .../53-libzstd-dev_1.5.7+dfsg-3_arm64.deb ... 357s Unpacking libzstd-dev:arm64 (1.5.7+dfsg-3) ... 357s Selecting previously unselected package liblzma-dev:arm64. 357s Preparing to unpack .../54-liblzma-dev_5.8.2-2_arm64.deb ... 357s Unpacking liblzma-dev:arm64 (5.8.2-2) ... 357s Selecting previously unselected package pkgconf-bin. 357s Preparing to unpack .../55-pkgconf-bin_1.8.1-4build1_arm64.deb ... 357s Unpacking pkgconf-bin (1.8.1-4build1) ... 357s Selecting previously unselected package pkgconf:arm64. 357s Preparing to unpack .../56-pkgconf_1.8.1-4build1_arm64.deb ... 357s Unpacking pkgconf:arm64 (1.8.1-4build1) ... 357s Selecting previously unselected package libtirpc-dev:arm64. 357s Preparing to unpack .../57-libtirpc-dev_1.3.6+ds-1_arm64.deb ... 357s Unpacking libtirpc-dev:arm64 (1.3.6+ds-1) ... 357s Selecting previously unselected package r-base-dev. 357s Preparing to unpack .../58-r-base-dev_4.5.2-1ubuntu2_all.deb ... 357s Unpacking r-base-dev (4.5.2-1ubuntu2) ... 357s Selecting previously unselected package pkg-r-autopkgtest. 357s Preparing to unpack .../59-pkg-r-autopkgtest_20250812_all.deb ... 357s Unpacking pkg-r-autopkgtest (20250812) ... 357s Setting up libzstd-dev:arm64 (1.5.7+dfsg-3) ... 357s Setting up linux-libc-dev:arm64 (6.19.0-3.3) ... 357s Setting up libpcre2-16-0:arm64 (10.46-1) ... 357s Setting up libpcre2-32-0:arm64 (10.46-1) ... 357s Setting up libtirpc-dev:arm64 (1.3.6+ds-1) ... 357s Setting up libpkgconf3:arm64 (1.8.1-4build1) ... 357s Setting up rpcsvc-proto (1.4.3-1build1) ... 357s Setting up libmpc3:arm64 (1.3.1-2) ... 357s Setting up icu-devtools (78.2-1ubuntu1) ... 357s Setting up pkgconf-bin (1.8.1-4build1) ... 357s Setting up liblzma-dev:arm64 (5.8.2-2) ... 357s Setting up libubsan1:arm64 (15.2.0-12ubuntu1) ... 357s Setting up libpcre2-posix3:arm64 (10.46-1) ... 357s Setting up libhwasan0:arm64 (15.2.0-12ubuntu1) ... 357s Setting up libcrypt-dev:arm64 (1:4.5.1-1) ... 357s Setting up libasan8:arm64 (15.2.0-12ubuntu1) ... 357s Setting up libtsan2:arm64 (15.2.0-12ubuntu1) ... 357s Setting up libisl23:arm64 (0.27-1build1) ... 357s Setting up libc-dev-bin (2.42-2ubuntu4) ... 357s Setting up libdeflate-dev:arm64 (1.23-2build1) ... 357s Setting up libcc1-0:arm64 (15.2.0-12ubuntu1) ... 357s Setting up liblsan0:arm64 (15.2.0-12ubuntu1) ... 357s Setting up libblas-dev:arm64 (3.12.1-7ubuntu1) ... 357s 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 357s Setting up dctrl-tools (2.24-3build4) ... 357s Setting up libitm1:arm64 (15.2.0-12ubuntu1) ... 357s Setting up cpp-15-aarch64-linux-gnu (15.2.0-12ubuntu1) ... 357s Setting up libgcc-15-dev:arm64 (15.2.0-12ubuntu1) ... 357s Setting up libgfortran-15-dev:arm64 (15.2.0-12ubuntu1) ... 357s Setting up pkgconf:arm64 (1.8.1-4build1) ... 357s Setting up cpp-aarch64-linux-gnu (4:15.2.0-4ubuntu1) ... 357s Setting up liblapack-dev:arm64 (3.12.1-7ubuntu1) ... 357s 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 357s Setting up cpp-15 (15.2.0-12ubuntu1) ... 357s Setting up cpp (4:15.2.0-4ubuntu1) ... 357s Setting up libc6-dev:arm64 (2.42-2ubuntu4) ... 357s Setting up libicu-dev:arm64 (78.2-1ubuntu1) ... 357s Setting up libbz2-dev:arm64 (1.0.8-6build2) ... 357s Setting up libjpeg-turbo8-dev:arm64 (2.1.5-4ubuntu3) ... 357s Setting up libncurses-dev:arm64 (6.6+20251231-1) ... 357s Setting up gcc-15-aarch64-linux-gnu (15.2.0-12ubuntu1) ... 357s Setting up libpcre2-dev:arm64 (10.46-1) ... 357s Setting up libreadline-dev:arm64 (8.3-3) ... 357s Setting up gcc-15 (15.2.0-12ubuntu1) ... 357s Setting up libstdc++-15-dev:arm64 (15.2.0-12ubuntu1) ... 357s Setting up gfortran-15-aarch64-linux-gnu (15.2.0-12ubuntu1) ... 357s Setting up g++-15-aarch64-linux-gnu (15.2.0-12ubuntu1) ... 357s Setting up zlib1g-dev:arm64 (1:1.3.dfsg+really1.3.1-1ubuntu2) ... 357s Setting up libjpeg8-dev:arm64 (8c-2ubuntu11) ... 357s Setting up g++-15 (15.2.0-12ubuntu1) ... 357s Setting up gfortran-15 (15.2.0-12ubuntu1) ... 357s Setting up gcc-aarch64-linux-gnu (4:15.2.0-4ubuntu1) ... 357s Setting up libpng-dev:arm64 (1.6.54-1) ... 357s Setting up libjpeg-dev:arm64 (8c-2ubuntu11) ... 357s Setting up gcc (4:15.2.0-4ubuntu1) ... 357s Setting up g++-aarch64-linux-gnu (4:15.2.0-4ubuntu1) ... 357s Setting up gfortran-aarch64-linux-gnu (4:15.2.0-4ubuntu1) ... 357s Setting up gfortran (4:15.2.0-4ubuntu1) ... 357s update-alternatives: using /usr/bin/gfortran to provide /usr/bin/f95 (f95) in auto mode 357s 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 357s update-alternatives: using /usr/bin/gfortran to provide /usr/bin/f77 (f77) in auto mode 357s 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 357s Setting up g++ (4:15.2.0-4ubuntu1) ... 357s update-alternatives: using /usr/bin/g++ to provide /usr/bin/c++ (c++) in auto mode 357s Setting up build-essential (12.12ubuntu2) ... 357s Setting up r-base-dev (4.5.2-1ubuntu2) ... 357s Setting up pkg-r-autopkgtest (20250812) ... 357s Processing triggers for libc-bin (2.42-2ubuntu4) ... 357s Processing triggers for man-db (2.13.1-1build1) ... 358s Processing triggers for install-info (7.2-5) ... 359s autopkgtest [23:15:30]: test pkg-r-autopkgtest: /usr/share/dh-r/pkg-r-autopkgtest 359s autopkgtest [23:15:30]: test pkg-r-autopkgtest: [----------------------- 359s Test: Try to load the R library rrcov 359s 359s R version 4.5.2 (2025-10-31) -- "[Not] Part in a Rumble" 359s Copyright (C) 2025 The R Foundation for Statistical Computing 359s Platform: aarch64-unknown-linux-gnu 359s 359s R is free software and comes with ABSOLUTELY NO WARRANTY. 359s You are welcome to redistribute it under certain conditions. 359s Type 'license()' or 'licence()' for distribution details. 359s 359s R is a collaborative project with many contributors. 359s Type 'contributors()' for more information and 359s 'citation()' on how to cite R or R packages in publications. 359s 359s Type 'demo()' for some demos, 'help()' for on-line help, or 359s 'help.start()' for an HTML browser interface to help. 359s Type 'q()' to quit R. 359s 359s Loading required package: robustbase 359s > library('rrcov') 359s Scalable Robust Estimators with High Breakdown Point (version 1.7-6) 359s 359s > 360s autopkgtest [23:15:31]: test pkg-r-autopkgtest: -----------------------] 360s autopkgtest [23:15:31]: test pkg-r-autopkgtest: - - - - - - - - - - results - - - - - - - - - - 360s pkg-r-autopkgtest PASS 361s autopkgtest [23:15:32]: @@@@@@@@@@@@@@@@@@@@ summary 361s run-unit-test PASS 361s pkg-r-autopkgtest PASS