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Data X:
112285 210907 84786 120982 83123 176508 101193 179321 38361 123185 68504 52746 119182 385534 22807 33170 17140 101645 116174 149061 57635 165446 66198 237213 71701 173326 57793 133131 80444 258873 53855 180083 97668 324799 133824 230964 101481 236785 99645 135473 114789 202925 99052 215147 67654 344297 65553 153935 97500 132943 69112 174724 82753 174415 85323 225548 72654 223632 30727 124817 77873 221698 117478 210767 74007 170266 90183 260561 61542 84853 101494 294424 27570 101011 55813 215641 79215 325107 1423 7176 55461 167542 31081 106408 22996 96560 83122 265769 70106 269651 60578 149112 39992 175824 79892 152871 49810 111665 71570 116408 100708 362301 33032 78800 82875 183167 139077 277965 71595 150629 72260 168809 5950 24188 115762 329267 32551 65029 31701 101097 80670 218946 143558 244052 117105 341570 23789 103597 120733 233328 105195 256462 73107 206161 132068 311473 149193 235800 46821 177939 87011 207176 95260 196553 55183 174184 106671 143246 73511 187559 92945 187681 78664 119016 70054 182192 22618 73566 74011 194979 83737 167488 69094 143756 93133 275541 95536 243199 225920 182999 62133 135649 61370 152299 43836 120221 106117 346485 38692 145790 84651 193339 56622 80953 15986 122774 95364 130585 26706 112611 89691 286468 67267 241066 126846 148446 41140 204713 102860 182079 51715 140344 55801 220516 111813 243060 120293 162765 138599 182613 161647 232138 115929 265318 24266 85574 162901 310839 109825 225060 129838 232317 37510 144966 43750 43287 40652 155754 87771 164709 85872 201940 89275 235454 44418 220801 192565 99466 35232 92661 40909 133328 13294 61361 32387 125930 140867 100750 120662 224549 21233 82316 44332 102010 61056 101523 101338 243511 1168 22938 13497 41566 65567 152474 25162 61857 32334 99923 40735 132487 91413 317394 855 21054 97068 209641 44339 22648 14116 31414 10288 46698 65622 131698 16563 91735 76643 244749 110681 184510 29011 79863 92696 128423 94785 97839 8773 38214 83209 151101 93815 272458 86687 172494 34553 108043 105547 328107 103487 250579 213688 351067 71220 158015 23517 98866 56926 85439 91721 229242 115168 351619 111194 84207 51009 120445 135777 324598 51513 131069 74163 204271 51633 165543 75345 141722 33416 116048 83305 250047 98952 299775 102372 195838 37238 173260 103772 254488 123969 104389 27142 136084 135400 199476 21399 92499 130115 224330 24874 135781 34988 74408 45549 81240 6023 14688 64466 181633 54990 271856 1644 7199 6179 46660 3926 17547 32755 133368 34777 95227 73224 152601 27114 98146 20760 79619 37636 59194 65461 139942 30080 118612 24094 72880 69008 65475 54968 99643 46090 71965 27507 77272 10672 49289 34029 135131 46300 108446 24760 89746 18779 44296 21280 77648 40662 181528 28987 134019 22827 124064 18513 92630 30594 121848 24006 52915 27913 81872 42744 58981 12934 53515 22574 60812 41385 56375 18653 65490 18472 80949 30976 76302 63339 104011 25568 98104 33747 67989 4154 30989 19474 135458 35130 73504 39067 63123 13310 61254 65892 74914 4143 31774 28579 81437 51776 87186 21152 50090 38084 65745 27717 56653 32928 158399 11342 46455 19499 73624 16380 38395 36874 91899 48259 139526 16734 52164 28207 51567 30143 70551 41369 84856 45833 102538 29156 86678 35944 85709 36278 34662 45588 150580 45097 99611 3895 19349 28394 99373 18632 86230 2325 30837 25139 31706 27975 89806 14483 62088 13127 40151 5839 27634 24069 76990 3738 37460 18625 54157 36341 49862 24548 84337 21792 64175 26263 59382 23686 119308 49303 76702 25659 103425 28904 70344 2781 43410 29236 104838 19546 62215 22818 69304 32689 53117 5752 19764 22197 86680 20055 84105 25272 77945 82206 89113 32073 91005 5444 40248 20154 64187 36944 50857 8019 56613 30884 62792
Names of X columns:
Totsize Timerfc
Response Variable (column number)
Explanatory Variable (column number)
Include Intercept Term ?
TRUE
TRUE
FALSE
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R Code
cat1 <- as.numeric(par1) cat2<- as.numeric(par2) intercept<-as.logical(par3) x <- t(x) xdf<-data.frame(t(y)) (V1<-dimnames(y)[[1]][cat1]) (V2<-dimnames(y)[[1]][cat2]) xdf <- data.frame(xdf[[cat1]], xdf[[cat2]]) names(xdf)<-c('Y', 'X') if(intercept == FALSE) (lmxdf<-lm(Y~ X - 1, data = xdf) ) else (lmxdf<-lm(Y~ X, data = xdf) ) sumlmxdf<-summary(lmxdf) (aov.xdf<-aov(lmxdf) ) (anova.xdf<-anova(lmxdf) ) load(file='createtable') a<-table.start() nc <- ncol(sumlmxdf$'coefficients') nr <- nrow(sumlmxdf$'coefficients') a<-table.row.start(a) a<-table.element(a,'Linear Regression Model', nc+1,TRUE) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a, lmxdf$call['formula'],nc+1) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a, 'coefficients:',1,TRUE) a<-table.element(a, ' ',nc,TRUE) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a, ' ',1,TRUE) for(i in 1 : nc){ a<-table.element(a, dimnames(sumlmxdf$'coefficients')[[2]][i],1,TRUE) }#end header a<-table.row.end(a) for(i in 1: nr){ a<-table.element(a,dimnames(sumlmxdf$'coefficients')[[1]][i] ,1,TRUE) for(j in 1 : nc){ a<-table.element(a, round(sumlmxdf$coefficients[i, j], digits=3), 1 ,FALSE) } a<-table.row.end(a) } a<-table.row.start(a) a<-table.element(a, '- - - ',1,TRUE) a<-table.element(a, ' ',nc,FALSE) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a, 'Residual Std. Err. ',1,TRUE) a<-table.element(a, paste(round(sumlmxdf$'sigma', digits=3), ' on ', sumlmxdf$'df'[2], 'df') ,nc, FALSE) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a, 'Multiple R-sq. ',1,TRUE) a<-table.element(a, round(sumlmxdf$'r.squared', digits=3) ,nc, FALSE) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a, 'Adjusted R-sq. ',1,TRUE) a<-table.element(a, round(sumlmxdf$'adj.r.squared', digits=3) ,nc, FALSE) a<-table.row.end(a) a<-table.end(a) table.save(a,file='mytable.tab') a<-table.start() a<-table.row.start(a) a<-table.element(a,'ANOVA Statistics', 5+1,TRUE) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a, ' ',1,TRUE) a<-table.element(a, 'Df',1,TRUE) a<-table.element(a, 'Sum Sq',1,TRUE) a<-table.element(a, 'Mean Sq',1,TRUE) a<-table.element(a, 'F value',1,TRUE) a<-table.element(a, 'Pr(>F)',1,TRUE) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a, V2,1,TRUE) a<-table.element(a, anova.xdf$Df[1]) a<-table.element(a, round(anova.xdf$'Sum Sq'[1], digits=3)) a<-table.element(a, round(anova.xdf$'Mean Sq'[1], digits=3)) a<-table.element(a, round(anova.xdf$'F value'[1], digits=3)) a<-table.element(a, round(anova.xdf$'Pr(>F)'[1], digits=3)) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a, 'Residuals',1,TRUE) a<-table.element(a, anova.xdf$Df[2]) a<-table.element(a, round(anova.xdf$'Sum Sq'[2], digits=3)) a<-table.element(a, round(anova.xdf$'Mean Sq'[2], digits=3)) a<-table.element(a, ' ') a<-table.element(a, ' ') a<-table.row.end(a) a<-table.end(a) table.save(a,file='mytable1.tab') bitmap(file='regressionplot.png') plot(Y~ X, data=xdf, xlab=V2, ylab=V1, main='Regression Solution') if(intercept == TRUE) abline(coef(lmxdf), col='red') if(intercept == FALSE) abline(0.0, coef(lmxdf), col='red') dev.off() library(car) bitmap(file='residualsQQplot.png') qq.plot(resid(lmxdf), main='QQplot of Residuals of Fit') dev.off() bitmap(file='residualsplot.png') plot(xdf$X, resid(lmxdf), main='Scatterplot of Residuals of Model Fit') dev.off() bitmap(file='cooksDistanceLmplot.png') plot.lm(lmxdf, which=4) dev.off()
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