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Data X:
1418 210907 869 120982 1530 176508 2172 179321 901 123185 463 52746 3201 385534 371 33170 1192 101645 1583 149061 1439 165446 1764 237213 1495 173326 1373 133131 2187 258873 1491 180083 4041 324799 1706 230964 2152 236785 1036 135473 1882 202925 1929 215147 2242 344297 1220 153935 1289 132943 2515 174724 2147 174415 2352 225548 1638 223632 1222 124817 1812 221698 1677 210767 1579 170266 1731 260561 807 84853 2452 294424 829 101011 1940 215641 2662 325107 186 7176 1499 167542 865 106408 1793 96560 2527 265769 2747 269651 1324 149112 2702 175824 1383 152871 1179 111665 2099 116408 4308 362301 918 78800 1831 183167 3373 277965 1713 150629 1438 168809 496 24188 2253 329267 744 65029 1161 101097 2352 218946 2144 244052 4691 341570 1112 103597 2694 233328 1973 256462 1769 206161 3148 311473 2474 235800 2084 177939 1954 207176 1226 196553 1389 174184 1496 143246 2269 187559 1833 187681 1268 119016 1943 182192 893 73566 1762 194979 1403 167488 1425 143756 1857 275541 1840 243199 1502 182999 1441 135649 1420 152299 1416 120221 2970 346485 1317 145790 1644 193339 870 80953 1654 122774 1054 130585 937 112611 3004 286468 2008 241066 2547 148446 1885 204713 1626 182079 1468 140344 2445 220516 1964 243060 1381 162765 1369 182613 1659 232138 2888 265318 1290 85574 2845 310839 1982 225060 1904 232317 1391 144966 602 43287 1743 155754 1559 164709 2014 201940 2143 235454 2146 220801 874 99466 1590 92661 1590 133328 1210 61361 2072 125930 1281 100750 1401 224549 834 82316 1105 102010 1272 101523 1944 243511 391 22938 761 41566 1605 152474 530 61857 1988 99923 1386 132487 2395 317394 387 21054 1742 209641 620 22648 449 31414 800 46698 1684 131698 1050 91735 2699 244749 1606 184510 1502 79863 1204 128423 1138 97839 568 38214 1459 151101 2158 272458 1111 172494 1421 108043 2833 328107 1955 250579 2922 351067 1002 158015 1060 98866 956 85439 2186 229242 3604 351619 1035 84207 1417 120445 3261 324598 1587 131069 1424 204271 1701 165543 1249 141722 946 116048 1926 250047 3352 299775 1641 195838 2035 173260 2312 254488 1369 104389 1577 136084 2201 199476 961 92499 1900 224330 1254 135781 1335 74408 1597 81240 207 14688 1645 181633 2429 271856 151 7199 474 46660 141 17547 1639 133368 872 95227 1318 152601 1018 98146 1383 79619 1314 59194 1335 139942 1403 118612 910 72880 616 65475 1407 99643 771 71965 766 77272 473 49289 1376 135131 1232 108446 1521 89746 572 44296 1059 77648 1544 181528 1230 134019 1206 124064 1205 92630 1255 121848 613 52915 721 81872 1109 58981 740 53515 1126 60812 728 56375 689 65490 592 80949 995 76302 1613 104011 2048 98104 705 67989 301 30989 1803 135458 799 73504 861 63123 1186 61254 1451 74914 628 31774 1161 81437 1463 87186 742 50090 979 65745 675 56653 1241 158399 676 46455 1049 73624 620 38395 1081 91899 1688 139526 736 52164 617 51567 812 70551 1051 84856 1656 102538 705 86678 945 85709 554 34662 1597 150580 982 99611 222 19349 1212 99373 1143 86230 435 30837 532 31706 882 89806 608 62088 459 40151 578 27634 826 76990 509 37460 717 54157 637 49862 857 84337 830 64175 652 59382 707 119308 954 76702 1461 103425 672 70344 778 43410 1141 104838 680 62215 1090 69304 616 53117 285 19764 1145 86680 733 84105 888 77945 849 89113 1182 91005 528 40248 642 64187 947 50857 819 56613 757 62792 894 72535
Names of X columns:
pageviews time_in_rfc
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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