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R : Copyright 2006, The R Foundation for Statistical Computing
Version 2.3.0 Under development (unstable) (2006-03-02 r37458)
ISBN 3-900051-07-0
R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.
R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.
Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.
> ### Regression tests for which the printed output is the issue
> ### May fail, e.g. by needing Recommended packages
>
> postscript("reg-tests-3.ps")
>
> ## str() for character & factors with NA (levels), and for Surv objects:
> ff <- factor(c(2:1, NA), exclude = NULL)
> str(levels(ff))
chr [1:3] "1" "2" NA
> str(ff)
Factor w/ 3 levels "1","2",NA: 2 1 3
> str(ordered(ff, exclude=NULL))
Ord.factor w/ 3 levels "1"<"2"<NA: 2 1 3
> if(require(survival)) {
+ data(aml)
+ (sa <- Surv(aml$time, aml$status))
+ str(sa)
+ detach("package:survival")
+ }
Loading required package: survival
Loading required package: splines
Surv [1:23, 1:2] 9 13 13+ 18 23 28+ 31 34 45+ 48 ...
- attr(*, "dimnames")=List of 2
..$ : NULL
..$ : chr [1:2] "time" "status"
- attr(*, "type")= chr "right"
> ## were different, the last one failed in 1.6.2 (at least)
>
>
> ## lm.influence where hat[1] == 1
> if(require(MASS)) {
+ fit <- lm(formula = 1000/MPG.city ~ Weight + Cylinders + Type + EngineSize + DriveTrain, data = Cars93)
+ print(lm.influence(fit))
+ ## row 57 should have hat = 1 and resid=0.
+ summary(influence.measures(fit))
+ }
Loading required package: MASS
$hat
1 2 3 4 5 6 7
0.09313909 0.07134091 0.19138434 0.08101081 0.24991662 0.10448752 0.12591828
8 9 10 11 12 13 14
0.39348171 0.10008864 0.23497010 0.27831516 0.11499791 0.06684324 0.16777903
15 16 17 18 19 20 21
0.10418769 0.19438856 0.22249600 0.18531791 0.42832529 0.13160780 0.11571055
22 23 24 25 26 27 28
0.13542772 0.05989558 0.09115955 0.07274599 0.16979948 0.10059554 0.36420370
29 30 31 32 33 34 35
0.05892084 0.12226683 0.14266192 0.06389391 0.07851639 0.16317503 0.10514036
36 37 38 39 40 41 42
0.16620182 0.07407892 0.21406715 0.35800879 0.11660151 0.12115515 0.05846839
43 44 45 46 47 48 49
0.07915006 0.05841339 0.07599254 0.14272015 0.10370606 0.22461698 0.07423925
50 51 52 53 54 55 56
0.16054084 0.10007740 0.22613089 0.05679789 0.05802486 0.07274599 0.16620182
57 58 59 60 61 62 63
1.00000000 0.16034032 0.14337335 0.11805892 0.13059078 0.05892084 0.10869261
64 65 66 67 68 69 70
0.07024346 0.07721617 0.25915706 0.08887161 0.06631974 0.10330515 0.19438856
71 72 73 74 75 76 77
0.12591828 0.21538400 0.05645115 0.08933216 0.16777903 0.07190036 0.12435356
78 79 80 81 82 83 84
0.06735745 0.06233173 0.40499233 0.20574068 0.20315406 0.35602282 0.08812076
85 86 87 88 89 90 91
0.13555308 0.09482733 0.24869622 0.06728598 0.57312772 0.08142621 0.15694445
92 93
0.15864447 0.57312772
$coefficients
(Intercept) Weight Cylinders4 Cylinders5 Cylinders6
1 -0.8045874665 2.867170e-04 -3.820998e-03 -0.121186522 -0.085652499
2 -0.1624020957 7.405395e-05 -3.377846e-02 -0.058135639 0.032561909
3 0.0730227014 -1.000408e-04 2.635594e-02 -0.038987943 -0.136284069
4 0.0154995743 8.165607e-06 5.679643e-03 0.005807148 0.050432610
5 2.0624972203 -5.727657e-04 4.651265e-01 1.314202802 1.689003061
6 0.1889725900 -8.408128e-05 3.552355e-02 -0.042386516 -0.038483733
7 0.0288527501 -1.891425e-05 4.221544e-03 0.012091377 0.008077810
8 -0.9237858418 3.777463e-06 -2.504289e-01 -0.282474268 -0.778087752
9 0.0027522480 9.783189e-05 2.129655e-02 -0.007988299 0.014432116
10 0.9903462340 -5.169747e-04 1.630209e-01 0.294911151 0.129970424
11 -0.5182963206 1.916075e-04 -1.215727e-01 -0.226050823 -0.161523754
12 -0.6387428727 2.494952e-04 -1.008869e-01 -0.179703222 -0.143884548
13 -0.3568385025 7.917221e-05 -2.534541e-02 -0.028384831 -0.029395607
14 -0.0077820700 -4.699458e-06 -1.266873e-03 0.041173344 0.053631137
15 -0.2615585508 1.297214e-04 -5.490059e-02 -0.275540505 -0.222909574
16 -0.0195241852 2.061693e-04 6.572061e-02 0.294616782 0.074266087
17 0.0965040227 -1.534149e-04 1.527511e-02 -0.028420127 -0.112348604
18 0.0048862795 -1.111273e-06 1.332650e-03 0.001477077 0.001007189
19 -0.1837125526 1.943923e-04 -1.515756e-02 -0.122275191 0.014588114
20 0.0080448668 -3.212441e-05 -2.747115e-03 0.002147238 -0.048260808
21 0.3062320767 -7.003532e-05 1.382568e-01 0.212411378 0.364192354
22 0.0834715351 -7.391740e-05 1.122255e-02 0.030230238 -0.037744856
23 -0.0076656309 1.396550e-05 -4.020753e-02 -0.044659212 -0.050554976
24 -1.5070278126 3.723597e-04 1.647077e-02 -0.161486560 -0.278755415
25 -0.0239986724 1.966635e-05 -2.200355e-02 -0.039815491 -0.051838322
26 -0.2726502980 7.668984e-05 -7.104259e-02 -0.070135093 -0.138776999
27 -0.0237099021 -1.906594e-05 -1.449196e-02 -0.165127041 -0.182407191
28 0.5989984194 -3.350192e-04 8.982947e-02 0.072939768 0.051948750
29 0.0049978357 1.024575e-05 -4.596944e-02 -0.048846124 -0.057195412
30 -0.0420784682 4.604021e-06 -9.761996e-03 -0.018154729 -0.051613812
31 -0.1226019720 5.936642e-05 -4.859332e-02 -0.071029678 -0.070396498
32 -1.2891791826 3.470986e-04 1.870320e-01 0.029725520 0.047497829
33 0.5677503929 -2.038892e-04 6.741942e-02 0.117380014 0.074644216
34 -0.0732129453 3.754795e-05 -1.228743e-02 -0.110181891 -0.113812479
35 0.0194920033 -7.575835e-06 5.134183e-03 0.017360915 0.015396275
36 1.6888356455 -4.377455e-04 4.524306e-01 0.411034679 0.902823919
37 -0.4890085420 1.725038e-04 -1.049924e-01 -0.186804182 -0.420107392
38 -0.0082739419 -1.137356e-04 -2.907676e-02 0.013409601 -0.082572165
39 -1.0909018362 1.064695e-04 8.658188e-01 0.866130219 0.806474055
40 -0.6733060595 1.783564e-04 -1.305062e-01 0.065871030 -0.125533828
41 0.3690425668 -1.245558e-04 9.024714e-02 0.216243273 0.228933588
42 0.6432124241 -7.951017e-05 -7.008503e-01 -0.653531527 -0.847103140
43 0.2616446485 -1.975002e-04 9.041771e-02 0.187584888 0.139640344
44 0.0454749520 -4.284837e-06 -5.453546e-02 -0.051589176 -0.066116786
45 -2.2631327197 7.379870e-04 1.070445e-01 -0.204329361 -0.128262892
46 -0.0612084384 2.238252e-05 -1.234131e-02 -0.011911444 -0.017360476
47 0.8600843682 -2.923003e-04 1.777695e-01 -0.255446144 -0.114886957
48 0.1775813222 -1.196361e-04 2.413830e-02 0.077055159 -0.014203507
49 -0.1424954874 9.842541e-05 -2.377345e-02 -0.051500781 0.113004619
50 0.2613474511 -1.665525e-05 8.367041e-02 0.117064766 0.300913215
51 -0.5457545031 1.270106e-04 -1.351808e-01 -0.192894338 -0.176826828
52 0.3111798506 -2.896481e-04 2.816237e-02 0.136852358 -0.007250608
53 0.0297317368 1.296449e-05 -6.708602e-02 -0.069529496 -0.075630367
54 0.0989545407 -1.357243e-05 -3.683573e-02 -0.028339562 -0.025145841
55 0.1644148644 -1.347342e-04 1.507463e-01 0.272775865 0.355144259
56 -1.0973102505 2.844224e-04 -2.939639e-01 -0.267067176 -0.586604116
57 0.0000000000 0.000000e+00 0.000000e+00 0.000000000 0.000000000
58 1.1181936467 -1.814925e-04 1.820092e-01 0.230407448 0.281788680
59 -0.1289781075 2.595372e-05 -3.776833e-02 -0.058580136 -0.126069473
60 0.4827651281 -1.458463e-04 9.396412e-02 -0.005593267 0.099263965
61 -0.1929691299 1.326052e-04 -4.434766e-02 -0.106219857 -0.124334762
62 0.0049978357 1.024575e-05 -4.596944e-02 -0.048846124 -0.057195412
63 -0.3935296223 2.040809e-04 -7.524962e-02 -0.146355742 -0.019064641
64 0.4603333737 -1.617410e-04 -5.546499e-02 0.010390154 -0.035282319
65 0.3126987326 -1.960180e-04 1.168042e-01 0.223520593 0.218762880
66 -0.1920212451 8.908026e-05 -4.283525e-02 -0.117606580 -0.033622259
67 -0.8795466532 3.620658e-04 -1.815067e-01 -0.332837224 -0.502419092
68 -0.0331296115 -3.321728e-05 2.875172e-02 0.062289524 0.061442068
69 -0.1135318718 5.034205e-05 -2.126782e-02 0.029790905 0.026695041
70 -0.0195241852 2.061693e-04 6.572061e-02 0.294616782 0.074266087
71 0.0288527501 -1.891425e-05 4.221544e-03 0.012091377 0.008077810
72 -0.2291016407 5.487125e-05 -6.613686e-02 -0.098852165 -0.051549477
73 0.1700259290 7.628143e-06 -2.032259e-01 -0.198173180 -0.224109893
74 0.5968477257 -1.921799e-04 9.263890e-02 0.150229991 0.156628646
75 -0.0077820700 -4.699458e-06 -1.266873e-03 0.041173344 0.053631137
76 -0.0194397858 2.531489e-05 -1.458165e-07 -0.009800589 -0.035894083
77 0.0134907894 -1.033768e-05 1.558189e-03 0.006006815 0.003684406
78 0.9077181399 -1.582828e-04 7.745093e-02 0.077205972 0.141055974
79 0.2164417917 -3.971900e-05 -4.607492e-02 -0.024531503 -0.012649902
80 0.9960541035 4.247826e-06 -7.839184e-01 -0.702085425 -0.798219133
81 0.0007910652 -3.072859e-07 8.023023e-04 0.001256898 0.000758261
82 -0.6435072296 -7.492359e-05 -1.735778e-01 -0.355994454 -0.119101997
83 0.0611662403 1.159480e-05 -1.119647e-01 -0.121657673 -0.117008905
84 -0.5769304812 3.253972e-04 -3.191547e-01 -0.437477397 -0.423951235
85 1.0837148496 -4.307667e-04 2.461529e-01 0.572974426 0.542167217
86 0.0083937926 -1.990781e-06 8.287336e-04 -0.045561514 -0.037803655
87 -0.1545228365 9.611522e-05 -2.127841e-02 -0.171230178 -0.137086764
88 0.2463906019 -2.892912e-04 3.477162e-01 0.438821017 0.357674795
89 -0.6025253492 2.525728e-04 -1.370524e-01 1.172830299 -0.211660377
90 -0.2820706112 3.173532e-04 -1.101740e-01 -0.261059565 -0.118916876
91 1.4258537942 -6.533290e-04 2.630332e-01 0.890368685 1.145291551
92 0.4060610493 -2.135821e-06 5.871214e-02 0.048538680 0.094105407
93 -0.6025253492 2.525728e-04 -1.370524e-01 -1.878927238 -0.211660377
Cylinders8 Cylindersrotary TypeLarge TypeMidsize TypeSmall
1 -0.1124657876 -0.0651605878 -5.802887e-02 -0.0555471473 0.2528314269
2 0.0053388461 0.0047782307 -6.569650e-02 0.0350485943 0.0252041164
3 -0.1679122402 0.0274285066 2.008834e-01 0.1844628894 0.0674315814
4 0.0638568606 -0.0003503783 -9.564934e-03 0.0149006180 -0.0087430921
5 2.5938169745 0.8582948229 -2.399208e-01 -0.5792472372 -0.5285037464
6 -0.0288706903 0.0299679804 1.045061e-01 0.1382939842 -0.0401298599
7 -0.0312731330 0.0246836012 5.564636e-02 0.0035711688 -0.0041697238
8 -1.8340782811 0.0716558396 2.304687e-01 0.0032843291 0.3376172236
9 0.1847255512 -0.2306585282 1.114501e-01 -0.0803119855 -0.0298407737
10 1.1851421958 0.8654297998 4.409688e-01 0.0708134508 -0.2042104727
11 0.3843948456 0.1406061718 -3.010002e-01 0.0273414412 0.0837774246
12 -0.1597129689 -0.1864801897 6.450603e-02 0.0597885728 0.2076322416
13 -0.0586771076 -0.0646598581 1.706543e-01 0.1735883622 0.2361560351
14 -0.0028726461 -0.0993484475 -4.198827e-02 -0.0328695117 0.0082498333
15 -0.2068476225 -0.1445082313 1.225231e-01 0.1673204751 0.0312950406
16 0.2059222894 -0.1200505921 8.218720e-02 0.0002209106 0.0173235673
17 -0.3504899068 0.3446336843 -9.851809e-02 0.0158568288 0.0633581211
18 0.0120965218 -0.0020492335 6.525536e-03 0.0002012250 -0.0008929206
19 -0.0539420147 -0.1374351833 1.576257e-01 0.0201581755 -0.0041475049
20 -0.0070837751 0.0317471863 -1.531881e-01 0.0051020166 0.0109305108
21 0.5602808822 -0.0939068584 2.916889e-01 0.2079842274 0.0719036134
22 0.0126364571 0.0642138666 -1.824736e-01 0.0127807493 0.0009786882
23 -0.0590906405 -0.0349751702 -5.567345e-03 -0.0025732617 -0.0225313251
24 -0.5271125509 0.1602771709 -1.660813e-01 -0.0765130701 0.5564898293
25 -0.0681411476 0.0031024272 -6.907299e-02 -0.0610995775 -0.0429840790
26 -0.1735454433 -0.0706705707 -1.739837e-02 -0.0112946369 0.0452224232
27 -0.2193360665 0.0008241219 1.092126e-01 0.1738553921 0.0047428510
28 0.0830814596 0.1950801461 1.354514e-01 0.1170474131 -0.1299135184
29 -0.0675817916 -0.0375435877 -5.699613e-03 -0.0018561352 -0.0297646003
30 0.0331484828 -0.0113220048 -1.952427e-01 -0.0016275866 0.0158334658
31 -0.0814880252 -0.0547203065 -1.397635e-02 -0.0112820160 0.0077466973
32 -0.0305111798 0.1574388970 -9.111875e-02 -0.0694657561 0.5501978390
33 0.0753789673 0.1710615320 -1.462954e-01 -0.1345579924 -0.2507910840
34 -0.1921551895 -0.4405196059 1.130618e-01 0.0550822506 0.0142852838
35 0.0139101694 0.0258169696 -7.341174e-03 -0.0040191802 -0.0014323289
36 1.1438837591 0.4210260247 1.057460e-01 0.0605827133 -0.2795146003
37 -0.4363174667 -0.2224017015 7.276605e-02 -0.1577658535 0.1089681503
38 -0.5706613637 0.2470506317 -2.448941e-01 0.0200009992 0.0295593111
39 0.7628832511 0.8929585543 -2.839854e-02 -0.0150058474 0.0623044167
40 -0.4269483338 0.6476956209 -3.978519e-01 -0.2049708931 0.2326834589
41 0.2669874618 0.2216701222 -2.713083e-02 -0.0189484276 -0.0596156237
42 -1.0313086539 -0.4717065449 -5.947438e-02 0.0164415576 -0.6187804909
43 0.1137733941 0.1389371633 1.866498e-01 0.1973976445 0.1051395744
44 -0.0802417862 -0.0375174905 -4.849177e-03 0.0009183418 -0.0468179606
45 -0.2250554681 -0.0236009451 -1.620885e-01 -0.1443281442 0.7996413905
46 -0.0298791385 0.0117333041 -1.717830e-02 -0.0101575259 0.0149621883
47 0.0567064443 -0.0207407914 5.592524e-01 0.6766291378 -0.2163209845
48 -0.4128397633 0.1262494802 1.555317e-01 -0.0336491273 -0.0274472024
49 0.1227716704 -0.0185633712 -7.120767e-02 0.0510945769 0.0093727142
50 0.2753274562 -0.2227910135 1.638844e-02 0.0838038858 -0.0528014684
51 -0.3972662514 0.1137542901 -1.850157e-01 0.0563752358 0.1303601054
52 -0.6043582748 0.4122452714 -2.755341e-01 0.0529148176 -0.0181328373
53 -0.0823840936 -0.0629773704 -4.430653e-03 -0.0021608372 -0.0531359038
54 -0.0150792891 -0.0425585103 6.777594e-03 0.0030583353 -0.0591176911
55 0.4668348880 -0.0212547234 4.732189e-01 0.4185931034 0.2944838529
56 -0.7432312183 -0.2735589895 -6.870778e-02 -0.0393632338 0.1816128390
57 0.0000000000 0.0000000000 0.000000e+00 0.0000000000 0.0000000000
58 0.1945880055 -0.5587521455 -2.266734e-01 -0.3613221042 -0.5509923750
59 -0.0900361434 0.0807855154 -8.877433e-04 -0.0437027380 0.0203231292
60 0.2757970992 -0.3494459094 2.397384e-01 0.1279587545 -0.1512732820
61 0.1520532649 0.0495057257 6.424741e-02 -0.1224729549 -0.0152320811
62 -0.0675817916 -0.0375435877 -5.699613e-03 -0.0018561352 -0.0297646003
63 -0.0124737319 -0.1163136988 -6.666660e-02 0.0045716898 0.0573650532
64 -0.0495762572 0.0108982197 2.072756e-02 0.0311491661 -0.1744779053
65 0.2450971786 0.1014330960 2.438442e-01 0.2322886433 0.1145616875
66 -0.0137450945 -0.0933626778 -1.455145e-02 -0.0219051447 0.0210761620
67 -0.5159902331 -0.3502832221 3.148977e-02 -0.1793660556 0.1719234355
68 0.0601331294 0.0072908696 1.448763e-01 0.1417048477 0.1267967674
69 0.0205395611 -0.0166707782 -6.624376e-02 -0.0877281099 0.0244232730
70 0.2059222894 -0.1200505921 8.218720e-02 0.0002209106 0.0173235673
71 -0.0312731330 0.0246836012 5.564636e-02 0.0035711688 -0.0041697238
72 -0.0698149636 -0.0077907772 -5.798951e-02 -0.0404309294 0.0291804508
73 -0.2461674520 -0.1792254003 -8.946335e-03 -0.0005023396 -0.1849210773
74 0.2142676665 0.1219475973 -7.874021e-02 -0.0918428593 -0.2301439149
75 -0.0028726461 -0.0993484475 -4.198827e-02 -0.0328695117 0.0082498333
76 0.0016544356 -0.0670470508 3.751826e-02 -0.0342084452 -0.0003680573
77 -0.0256147452 0.0156400843 4.086022e-02 0.0019511571 -0.0017546993
78 0.2825081053 0.0902228220 -3.983641e-01 -0.4346234712 -0.6043441371
79 0.0159835202 -0.0629476770 1.898330e-02 0.0085089202 -0.1077243741
80 -0.8150304378 -0.7413746212 5.446384e-03 0.0101047426 0.0136845038
81 0.0006315229 0.0011374665 5.007436e-05 0.0001020962 0.0003802979
82 -0.1389697069 -0.2829444232 2.798773e-01 0.2855962270 0.2832007760
83 -0.1199642681 -0.1139380335 -3.874836e-03 -0.0029066043 0.0054537971
84 -0.4681723050 -0.3692610821 -6.915058e-02 -0.0611471408 -0.0286774399
85 0.5868282269 0.6138842050 -4.618245e-02 -0.0093232438 -0.1687348360
86 -0.0335385306 -0.0121341311 3.955944e-02 0.0530269621 -0.0049516790
87 -0.1199323644 -0.0903358174 7.132870e-02 0.0441402079 0.0305846988
88 0.3030076280 0.4897405972 2.110757e-02 0.0520618321 0.1828859889
89 -0.1751107919 -0.2847075342 -1.578805e-02 -0.1009325245 0.0816716468
90 0.0055450581 -0.2720115784 -2.803760e-01 -0.3305994053 -0.2254900027
91 1.1629492149 0.1111057651 -3.399076e-01 -0.2295981894 -0.3032814817
92 0.0465882510 -0.3782722178 -1.398749e-01 -0.2168631833 -0.2674612094
93 -0.1751107919 -0.2847075342 -1.578805e-02 -0.1009325245 0.0816716468
TypeSporty TypeVan EngineSize DriveTrainFront DriveTrainRear
1 0.0588316568 -0.1244451013 -0.0384310410 0.0770280182 0.0308309135
2 -0.0008119071 -0.0929376586 -0.0169359479 0.0241959908 -0.0339336755
3 0.1122278579 0.2291762722 0.0640824206 -0.0374592418 -0.0063680596
4 -0.0076600464 -0.0180881612 -0.0224320460 0.0058289643 -0.0019669209
5 -0.3020816254 -0.2058571702 -0.3622619462 -0.0332177591 -0.4896133013
6 0.0174438088 0.1203009860 0.0149164277 -0.0095259785 -0.0123604155
7 0.0006330938 0.0018693765 0.0107797571 -0.0019362039 -0.0134263631
8 0.0888020681 -0.0981347691 0.5308561510 -0.0605205490 0.0622791836
9 0.0084422208 0.0641063586 -0.1438112041 0.0132369251 0.1231952988
10 -0.0453797315 0.1992829759 0.2094701125 -0.0711059699 -0.5860656544
11 0.0248173290 -0.1726730349 0.0307556826 0.0513955297 -0.2418132557
12 0.1493980797 -0.0158201826 -0.0533221135 0.0282944654 0.0228550025
13 0.1994088698 0.1348657122 -0.0134379474 -0.0212986235 0.0103552709
14 0.0454481137 -0.0247086389 -0.0005370853 0.0136434594 0.0759855468
15 0.0737344548 0.0705529631 -0.0350342542 0.0366749177 0.0023334058
16 -0.0098606591 -0.6464182823 -0.1570311735 -0.3099924798 -0.2432841941
17 -0.0121432263 0.2179211370 0.2426878264 -0.2268810389 -0.3003526507
18 -0.0012645247 0.0023497958 -0.0011648194 -0.0007816983 0.0031588791
19 -0.0601680504 -0.0271883474 -0.1686877849 0.0224897952 0.0378443211
20 -0.0039938145 0.0181201352 0.0439331331 -0.0137111692 0.0000888560
21 0.1294650212 0.2558709492 -0.1869157355 -0.0403252374 0.1039524785
22 -0.0110221099 0.0377992374 0.0616023114 -0.0236300001 -0.0027554274
23 0.0036748958 -0.0109040520 0.0047056340 -0.0027760031 -0.0075815300
24 0.1217218160 -0.2001221968 0.1453646196 0.1092627610 -0.0419265979
25 -0.0473791084 -0.0661671214 0.0174623161 0.0138168014 -0.0113597498
26 0.0343625250 -0.1263789642 0.0185185704 0.0899765460 0.0628671160
27 0.0521314845 0.1121866729 0.0452354145 0.0036741989 -0.0328558430
28 -0.1357733641 0.3598998278 0.0635427842 0.1408150632 0.2289697825
29 0.0032709010 -0.0102098982 0.0072097840 -0.0046929662 -0.0097593036
30 -0.0031503060 0.0096427335 0.0191501496 -0.0072782279 0.0183269440
31 0.0124966732 -0.0309659093 -0.0029315971 0.0080704811 -0.0032291174
32 0.0842166724 -0.1426179532 -0.0047149618 0.1266243473 0.0488025203
33 -0.2007361705 -0.0700394295 0.0650345678 -0.0076553978 -0.0323613407
34 0.1985477388 0.1317049456 -0.0379303148 0.0476640032 0.2557928936
35 -0.0241684660 -0.0063797023 0.0015970165 -0.0082742198 -0.0012845847
36 -0.2213615898 0.8328871713 -0.1490208173 -0.6045260895 -0.4274997860
37 0.0832688361 0.0526955171 0.0412992657 0.0057199017 0.0750539814
38 0.0381452581 -0.0364723376 0.1718996509 -0.0083216767 -0.1711269654
39 0.0126715370 -0.1319040895 0.0157246728 -0.1238552960 -0.1433995801
40 -0.6152814178 -0.4391609078 0.1925710081 -0.1848270831 -0.1257923223
41 -0.2136693396 -0.0102756220 -0.0187378955 -0.0760535877 0.0079050473
42 0.0115250441 -0.0626784733 0.1853115582 -0.1341403576 -0.1937539975
43 0.1223234350 0.2339351557 0.0477222207 -0.0703208756 -0.0131810299
44 0.0012062101 -0.0056275300 0.0138113326 -0.0099328213 -0.0147138005
45 0.1593529911 -0.3154119193 -0.0734215883 0.2186169305 0.0863564493
46 -0.0178306744 -0.0229394143 0.0050172709 -0.0032569785 -0.0040140299
47 0.0870826598 0.5764940782 -0.0661850124 -0.0160346100 0.0058237374
48 0.0351028466 0.0519540796 0.0730561863 -0.0117874040 -0.0875600533
49 -0.0118615751 -0.1170935139 -0.0664392527 0.0351943834 -0.0256500862
50 -0.0881348868 0.0099122018 -0.1427997802 -0.0154102445 0.2834351261
51 0.0341259919 -0.1980471170 0.1301931475 0.0329557292 -0.1390726822
52 0.0198930304 0.0233944834 0.2437424291 -0.0398986993 -0.2216521963
53 0.0026357380 -0.0124859669 0.0032736381 -0.0076038099 -0.0111780184
54 -0.0052948316 0.0043390590 -0.0062558306 -0.0100922249 -0.0036764450
55 0.3245941919 0.4533108376 -0.1196342985 -0.0946588832 0.0778256270
56 0.1438282891 -0.5411631576 0.0968253310 0.3927869929 0.2777652749
57 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
58 -0.5770947483 -0.1184054962 -0.1740228604 -0.0285545091 0.7693037902
59 0.0412280879 -0.0075198458 0.0438882586 0.0121450418 -0.1252262379
60 0.3533541160 0.2760694598 -0.1036620689 0.1001975219 0.0703124944
61 0.0813382295 -0.0073739718 -0.0680618001 0.0531536577 -0.2332865147
62 0.0032709010 -0.0102098982 0.0072097840 -0.0046929662 -0.0097593036
63 0.0180571278 -0.1370722536 -0.0731027259 0.0500357603 -0.0039945662
64 -0.0280219408 0.0596353403 0.0485330769 -0.0523499513 -0.0380625252
65 0.1445564205 0.2773146947 -0.0044527086 -0.0739571632 0.0145722623
66 0.0147554787 0.0493296285 -0.0390174812 0.0705967740 0.0634638159
67 0.1109162662 -0.0476703926 -0.0101172134 0.0463473545 0.0838855959
68 0.1228600624 0.1417644316 -0.0078297996 -0.0320462976 0.0093214403
69 -0.0117468402 -0.0753433644 -0.0087753330 0.0054190284 0.0076171833
70 -0.0098606591 -0.6464182823 -0.1570311735 -0.3099924798 -0.2432841941
71 0.0006330938 0.0018693765 0.0107797571 -0.0019362039 -0.0134263631
72 -0.0675185509 0.0151499809 -0.0006299133 0.1444639061 0.1463776010
73 0.0024427576 -0.0249870886 0.0183259078 -0.0314868930 -0.0391504393
74 -0.1684498617 -0.0211344382 0.0051450670 -0.0108665177 -0.0006733384
75 0.0454481137 -0.0247086389 -0.0005370853 0.0136434594 0.0759855468
76 0.0087561990 0.0294347022 -0.0243866906 0.0001777584 0.0361467380
77 0.0011372964 -0.0003003688 0.0071919929 -0.0007018973 -0.0096901840
78 -0.4998716808 -0.3342094594 -0.0381922269 0.0632770184 0.0098092574
79 -0.0142230621 0.0179025413 -0.0175009156 -0.0191510694 -0.0015333501
80 -0.0247650968 -0.1469466395 0.0130804686 -0.2728976699 -0.2592164502
81 -0.0001483293 -0.0004719821 0.0001778419 -0.0011917350 -0.0011218042
82 0.3679140434 0.7422456267 0.0018768183 0.7508948030 0.7730015531
83 0.0043841507 0.0024787823 0.0002320259 0.0183666140 0.0145190633
84 0.0640691059 -0.1711824885 -0.0312673044 0.0349340607 -0.0192550330
85 -0.4756750417 0.0452676883 0.0298336291 -0.1959168864 -0.0136381614
86 0.0135669048 0.0363260497 -0.0012178976 0.0026468538 -0.0024799878
87 0.0376963721 0.1229412256 -0.0225447495 -0.0488081493 -0.0417831082
88 -0.0360445039 0.1399780291 0.1137882315 -0.0178410448 -0.0105132722
89 0.0609817970 0.1720567027 -0.0724262979 0.1875627215 0.1892070773
90 -0.2273870236 -0.3709143259 -0.1506696521 0.1197628934 0.0586023325
91 0.4164006880 -0.1004183249 0.0323442452 0.1231599812 -0.1040204060
92 -0.2996222296 -0.1090340253 -0.1173564279 0.0035664196 0.4305799574
93 0.0609817970 0.1720567027 -0.0724262979 0.1875627215 0.1892070773
$sigma
1 2 3 4 5 6 7 8
3.591432 3.594883 3.598562 3.600558 3.522694 3.598166 3.600799 3.582363
9 10 11 12 13 14 15 16
3.590729 3.528259 3.589350 3.596037 3.584177 3.600028 3.593696 3.580547
17 18 19 20 21 22 23 24
3.590040 3.601220 3.599441 3.598460 3.584656 3.597078 3.600671 3.553725
25 26 27 28 29 30 31 32
3.599688 3.599193 3.595214 3.598433 3.600406 3.596419 3.601044 3.518649
33 34 35 36 37 38 39 40
3.587115 3.592663 3.601139 3.501762 3.560763 3.588001 3.592963 3.514670
41 42 43 44 45 46 47 48
3.595497 3.334292 3.589110 3.599718 3.471882 3.601133 3.521852 3.594122
49 50 51 52 53 54 55 56
3.588734 3.589710 3.583459 3.581755 3.599157 3.599895 3.528075 3.559578
57 58 59 60 61 62 63 64
3.601231 3.523963 3.598459 3.571771 3.582319 3.600406 3.596626 3.592960
65 66 67 68 69 70 71 72
3.583325 3.600828 3.569987 3.592482 3.599979 3.580547 3.600799 3.599768
73 74 75 76 77 78 79 80
3.579302 3.593475 3.600028 3.598895 3.600991 3.495965 3.597794 3.594229
81 82 83 84 85 86 87 88
3.601231 3.563077 3.601124 3.585986 3.575773 3.600658 3.599786 3.563954
89 90 91 92 93
3.594056 3.566216 3.484273 3.578056 3.594056
$wt.res
1 2 3 4 5
2.218439708 1.807326787 -1.093991760 0.585986462 -5.684589270
6 7 8 9 10
1.233522386 0.457950438 2.515990067 -2.287803728 5.535960625
11 12 13 14 15
2.178905651 -1.596117514 -2.967297860 0.745175851 1.933882824
16 17 18 19 20
-3.035594591 2.195009903 0.072527577 -0.753360641 -1.155059621
21 22 23 24 25
-2.847828869 -1.410703414 -0.540252474 4.877197398 0.890715640
26 27 28 29 30
-0.968642103 1.731771561 -0.993218102 -0.656454198 -1.529950693
31 32 33 34 35
-0.298424469 6.510112647 2.683267748 1.992954455 -0.214079423
36 37 38 39 40
6.735053083 -4.545792145 -2.399183444 -1.714795692 -6.472930954
41 42 43 44 45
-1.671169308 -11.585332803 -2.485888781 -0.888857647 8.068071025
46 47 48 49 50
-0.216046323 6.246829383 -1.747619081 2.530823032 2.314106628
51 52 53 54 55
2.974532942 -2.887230686 -1.041442666 -0.835536301 -6.102291353
56 57 58 59 60
-4.376058028 0.000000000 5.966190371 -1.147443467 3.788198306
61 62 63 64 65
-3.015807719 -0.656454198 1.508247858 -2.064017840 -3.023462268
66 67 68 69 70
0.407243898 -3.964783523 -2.127186213 -0.789242889 -3.035594591
71 72 73 74 75
0.457950438 -0.797900840 -3.382338495 1.978150290 0.745175851
76 77 78 79 80
-1.096455031 0.341748714 7.324729228 -1.336726492 1.519313995
81 82 83 84 85
0.005901292 -4.095330927 0.195481697 -2.773676266 -3.487375439
86 87 88 89 90
0.536312040 0.775871729 4.379791779 1.302710701 4.213228761
91 92 93
7.334576566 3.283113507 -1.302710701
Potentially influential observations of
lm(formula = 1000/MPG.city ~ Weight + Cylinders + Type + EngineSize + DriveTrain, data = Cars93) :
dfb.1_ dfb.Wght dfb.Cyl4 dfb.Cyl5 dfb.Cyl6 dfb.Cyl8 dfb.Cyln dfb.TypL
8 -0.16 0.00 -0.10 -0.07 -0.24 -0.44 0.01 0.12
19 -0.03 0.09 -0.01 -0.03 0.00 -0.01 -0.03 0.08
28 0.11 -0.15 0.04 0.02 0.02 0.02 0.04 0.07
39 -0.19 0.05 0.34 0.21 0.25 0.18 0.18 -0.01
42 0.12 -0.04 -0.30 -0.17 -0.28 -0.26 -0.11 -0.03
57 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
66 -0.03 0.04 -0.02 -0.03 -0.01 0.00 -0.02 -0.01
80 0.18 0.00 -0.31 -0.17 -0.24 -0.19 -0.15 0.00
83 0.01 0.01 -0.04 -0.03 -0.04 -0.03 -0.02 0.00
87 -0.03 0.04 -0.01 -0.04 -0.04 -0.03 -0.02 0.04
89 -0.11 0.11 -0.05 0.28 -0.06 -0.04 -0.06 -0.01
93 -0.11 0.11 -0.05 -0.45 -0.06 -0.04 -0.06 -0.01
dfb.TypM dfb.TypSm dfb.TypSp dfb.TypV dfb.EngS dfb.DrTF dfb.DrTR dffit
8 0.00 0.21 0.06 -0.04 0.47 -0.04 0.03 0.73
19 0.01 0.00 -0.04 -0.01 -0.15 0.01 0.02 -0.24
28 0.08 -0.08 -0.09 0.16 0.06 0.09 0.12 -0.26
39 -0.01 0.04 0.01 -0.06 0.01 -0.08 -0.08 -0.44
42 0.01 -0.42 0.01 -0.03 0.18 -0.10 -0.11 -0.89
57 0.00 0.00 0.00 0.00 0.00 0.00 0.00 NaN
66 -0.02 0.01 0.01 0.02 -0.03 0.05 0.03 0.08
80 0.01 0.01 -0.02 -0.07 0.01 -0.18 -0.14 0.45
83 0.00 0.00 0.00 0.00 0.00 0.01 0.01 0.05
87 0.03 0.02 0.03 0.06 -0.02 -0.03 -0.02 0.14
89 -0.07 0.05 0.04 0.08 -0.06 0.12 0.10 0.64
93 -0.07 0.05 0.04 0.08 -0.06 0.12 0.10 -0.64
cov.r cook.d hat
8 1.71_* 0.04 0.39
19 2.09_* 0.00 0.43
28 1.86_* 0.00 0.36
39 1.76_* 0.01 0.36
42 0.13_* 0.05 0.06
57 NaN NaN 1.00_*
66 1.63_* 0.00 0.26
80 1.92_* 0.01 0.40
83 1.88_* 0.00 0.36
87 1.60_* 0.00 0.25
89 2.68_* 0.03 0.57_*
93 2.68_* 0.03 0.57_*
> ## only last two cols in row 57 should be influential
>
>
> ## PR#6640 Zero weights in plot.lm
> if(require(MASS)) {
+ fm1 <- lm(time~dist, data=hills, weights=c(0,0,rep(1,33)))
+ plot(fm1)
+ }
> ## gave warnings in 1.8.1
>
>
> ## PR#7829 model.tables & replications
> if(require(MASS)) {
+ oats.aov <- aov(Y ~ B + V + N + V:N, data=oats[-1,])
+ model.tables(oats.aov, "means", cterms=c("N", "V:N"))
+ }
Tables of means
Grand mean
103.8732
N
0.0cwt 0.2cwt 0.4cwt 0.6cwt
78.74 98.5 113.8 123
rep 17.00 18.0 18.0 18
V:N
N
V 0.0cwt 0.2cwt 0.4cwt 0.6cwt
Golden.rain 79.53 98.03 114.20 124.37
rep 6.00 6.00 6.00 6.00
Marvellous 86.20 108.03 116.70 126.37
rep 6.00 6.00 6.00 6.00
Victory 69.77 89.20 110.37 118.03
rep 5.00 6.00 6.00 6.00
> ## wrong printed output in 2.1.0
>
>
> ## drop1 on weighted lm() fits
> if(require(MASS)) {
+ hills.lm <- lm(time ~ 0 + dist + climb, data=hills, weights=1/dist^2)
+ print(drop1(hills.lm))
+ print(stats:::drop1.default(hills.lm))
+ hills.lm2 <- lm(time/dist ~ 1 + I(climb/dist), data=hills)
+ drop1(hills.lm2)
+ }
Single term deletions
Model:
time ~ 0 + dist + climb
Df Sum of Sq RSS AIC
<none> 442.22 92.78
dist 1 330.92 773.14 110.33
climb 1 9.73 451.95 91.54
Single term deletions
Model:
time ~ 0 + dist + climb
Df AIC
<none> 92.776
dist 1 110.329
climb 1 91.538
Single term deletions
Model:
time/dist ~ 1 + I(climb/dist)
Df Sum of Sq RSS AIC
<none> 442.22 92.78
I(climb/dist) 1 9.73 451.95 91.54
> ## quoted unweighted RSS etc in 2.2.1
>
>
> ## tests of ISO C99 compliance (Windows fails without a workaround)
> sprintf("%g", 123456789)
[1] "1.23457e+08"
> sprintf("%8g", 123456789)
[1] "1.23457e+08"
> sprintf("%9.7g", 123456789)
[1] "1.234568e+08"
> sprintf("%10.9g", 123456789)
[1] " 123456789"
> sprintf("%g", 12345.6789)
[1] "12345.7"
> sprintf("%10.9g", 12345.6789)
[1] "12345.6789"
> sprintf("%10.7g", 12345.6789)
[1] " 12345.68"
> sprintf("%.7g", 12345.6789)
[1] "12345.68"
> sprintf("%.5g", 12345.6789)
[1] "12346"
> sprintf("%.4g", 12345.6789)
[1] "1.235e+04"
> sprintf("%9.4g", 12345.6789)
[1] "1.235e+04"
> sprintf("%10.4g", 12345.6789)
[1] " 1.235e+04"
> ## Windows used e+008 etc prior to 2.3.0
>
>
> ## weighted glm() fits
> if(require(MASS)) {
+ hills.glm <- glm(time ~ 0 + dist + climb, data=hills, weights=1/dist^2)
+ print(AIC(hills.glm))
+ print(extractAIC(hills.glm))
+ print(drop1(hills.glm))
+ stats:::drop1.default(hills.glm)
+ }
[1] 322.2318
[1] 2.0000 322.2318
Single term deletions
Model:
time ~ 0 + dist + climb
Df Deviance AIC
<none> 442.22 322.23
dist 1 773.14 339.78
climb 1 451.95 320.99
Single term deletions
Model:
time ~ 0 + dist + climb
Df AIC
<none> 322.23
dist 1 339.78
climb 1 320.99
> ## wrong AIC() and drop1 prior to 2.3.0.
>
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