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R : Copyright 2005, The R Foundation for Statistical ComputingVersion 2.2.0 Under development (unstable) (2005-05-04), ISBN 3-900051-07-0R 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 a 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: survivalLoading required package: splinesSurv [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$hat1 2 3 4 5 6 70.09313909 0.07134091 0.19138434 0.08101081 0.24991662 0.10448752 0.125918288 9 10 11 12 13 140.39348171 0.10008864 0.23497010 0.27831516 0.11499791 0.06684324 0.1677790315 16 17 18 19 20 210.10418769 0.19438856 0.22249600 0.18531791 0.42832529 0.13160780 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-0.010513272289 0.0609817970 0.1720567027 -0.0724262979 0.1875627215 0.189207077390 -0.2273870236 -0.3709143259 -0.1506696521 0.1197628934 0.058602332591 0.4164006880 -0.1004183249 0.0323442452 0.1231599812 -0.104020406092 -0.2996222296 -0.1090340253 -0.1173564279 0.0035664196 0.430579957493 0.0609817970 0.1720567027 -0.0724262979 0.1875627215 0.1892070773$sigma1 2 3 4 5 6 7 83.591432 3.594883 3.598562 3.600558 3.522694 3.598166 3.600799 3.5823639 10 11 12 13 14 15 163.590729 3.528259 3.589350 3.596037 3.584177 3.600028 3.593696 3.58054717 18 19 20 21 22 23 243.590040 3.601220 3.599441 3.598460 3.584656 3.597078 3.600671 3.55372525 26 27 28 29 30 31 323.599688 3.599193 3.595214 3.598433 3.600406 3.596419 3.601044 3.51864933 34 35 36 37 38 39 403.587115 3.592663 3.601139 3.501762 3.560763 3.588001 3.592963 3.51467041 42 43 44 45 46 47 483.595497 3.334292 3.589110 3.599718 3.471882 3.601133 3.521852 3.59412249 50 51 52 53 54 55 563.588734 3.589710 3.583459 3.581755 3.599157 3.599895 3.528075 3.55957857 58 59 60 61 62 63 64NaN 3.523963 3.598459 3.571771 3.582319 3.600406 3.596626 3.59296065 66 67 68 69 70 71 723.583325 3.600828 3.569987 3.592482 3.599979 3.580547 3.600799 3.59976873 74 75 76 77 78 79 803.579302 3.593475 3.600028 3.598895 3.600991 3.495965 3.597794 3.59422981 82 83 84 85 86 87 883.601231 3.563077 3.601124 3.585986 3.575773 3.600658 3.599786 3.56395489 90 91 92 933.594056 3.566216 3.484273 3.578056 3.594056$wt.res1 2 3 4 52.218439708 1.807326787 -1.093991760 0.585986462 -5.6845892706 7 8 9 101.233522386 0.457950438 2.515990067 -2.287803728 5.53596062511 12 13 14 152.178905651 -1.596117514 -2.967297860 0.745175851 1.93388282416 17 18 19 20-3.035594591 2.195009903 0.072527577 -0.753360641 -1.15505962121 22 23 24 25-2.847828869 -1.410703414 -0.540252474 4.877197398 0.89071564026 27 28 29 30-0.968642103 1.731771561 -0.993218102 -0.656454198 -1.52995069331 32 33 34 35-0.298424469 6.510112647 2.683267748 1.992954455 -0.21407942336 37 38 39 406.735053083 -4.545792145 -2.399183444 -1.714795692 -6.47293095441 42 43 44 45-1.671169308 -11.585332803 -2.485888781 -0.888857647 8.06807102546 47 48 49 50-0.216046323 6.246829383 -1.747619081 2.530823032 2.31410662851 52 53 54 552.974532942 -2.887230686 -1.041442666 -0.835536301 -6.10229135356 57 58 59 60-4.376058028 0.000000000 5.966190371 -1.147443467 3.78819830661 62 63 64 65-3.015807719 -0.656454198 1.508247858 -2.064017840 -3.02346226866 67 68 69 700.407243898 -3.964783523 -2.127186213 -0.789242889 -3.03559459171 72 73 74 750.457950438 -0.797900840 -3.382338495 1.978150290 0.74517585176 77 78 79 80-1.096455031 0.341748714 7.324729228 -1.336726492 1.51931399581 82 83 84 850.005901292 -4.095330927 0.195481697 -2.773676266 -3.48737543986 87 88 89 900.536312040 0.775871729 4.379791779 1.302710701 4.21322876191 92 937.334576566 3.283113507 -1.302710701Potentially influential observations oflm(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.TypL8 -0.16 0.00 -0.10 -0.07 -0.24 -0.44 0.01 0.1219 -0.03 0.09 -0.01 -0.03 0.00 -0.01 -0.03 0.0828 0.11 -0.15 0.04 0.02 0.02 0.02 0.04 0.0739 -0.19 0.05 0.34 0.21 0.25 0.18 0.18 -0.0142 0.12 -0.04 -0.30 -0.17 -0.28 -0.26 -0.11 -0.0357 NaN NaN NaN NaN NaN NaN NaN NaN66 -0.03 0.04 -0.02 -0.03 -0.01 0.00 -0.02 -0.0180 0.18 0.00 -0.31 -0.17 -0.24 -0.19 -0.15 0.0083 0.01 0.01 -0.04 -0.03 -0.04 -0.03 -0.02 0.0087 -0.03 0.04 -0.01 -0.04 -0.04 -0.03 -0.02 0.0489 -0.11 0.11 -0.05 0.28 -0.06 -0.04 -0.06 -0.0193 -0.11 0.11 -0.05 -0.45 -0.06 -0.04 -0.06 -0.01dfb.TypM dfb.TypSm dfb.TypSp dfb.TypV dfb.EngS dfb.DrTF dfb.DrTR dffit8 0.00 0.21 0.06 -0.04 0.47 -0.04 0.03 0.7319 0.01 0.00 -0.04 -0.01 -0.15 0.01 0.02 -0.2428 0.08 -0.08 -0.09 0.16 0.06 0.09 0.12 -0.2639 -0.01 0.04 0.01 -0.06 0.01 -0.08 -0.08 -0.4442 0.01 -0.42 0.01 -0.03 0.18 -0.10 -0.11 -0.8957 NaN NaN NaN NaN NaN NaN NaN NaN66 -0.02 0.01 0.01 0.02 -0.03 0.05 0.03 0.0880 0.01 0.01 -0.02 -0.07 0.01 -0.18 -0.14 0.4583 0.00 0.00 0.00 0.00 0.00 0.01 0.01 0.0587 0.03 0.02 0.03 0.06 -0.02 -0.03 -0.02 0.1489 -0.07 0.05 0.04 0.08 -0.06 0.12 0.10 0.6493 -0.07 0.05 0.04 0.08 -0.06 0.12 0.10 -0.64cov.r cook.d hat8 1.71_* 0.04 0.3919 2.09_* 0.00 0.4328 1.86_* 0.00 0.3639 1.76_* 0.01 0.3642 0.13_* 0.05 0.0657 NaN Inf_* 1.00_*66 1.63_* 0.00 0.2680 1.92_* 0.01 0.4083 1.88_* 0.00 0.3687 1.60_* 0.00 0.2589 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 meansGrand mean103.8732N0.0cwt 0.2cwt 0.4cwt 0.6cwt78.74 98.5 113.8 123rep 17.00 18.0 18.0 18V:NNV 0.0cwt 0.2cwt 0.4cwt 0.6cwtGolden.rain 79.53 98.03 114.20 124.37rep 6.00 6.00 6.00 6.00Marvellous 86.20 108.03 116.70 126.37rep 6.00 6.00 6.00 6.00Victory 69.77 89.20 110.37 118.03rep 5.00 6.00 6.00 6.00> ## wrong printed output in 2.1.0>