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Type 'q()' to quit R. > x <- array(list(2 + ,210907 + ,79 + ,94 + ,112285 + ,146283 + ,30 + ,-1 + ,4 + ,179321 + ,108 + ,103 + ,101193 + ,96933 + ,30 + ,3 + ,0 + ,149061 + ,43 + ,93 + ,116174 + ,95757 + ,26 + ,0 + ,0 + ,237213 + ,78 + ,123 + ,66198 + ,143983 + ,38 + ,3 + ,-4 + ,173326 + ,86 + ,148 + ,71701 + ,75851 + ,44 + ,4 + ,4 + ,133131 + ,44 + ,90 + ,57793 + ,59238 + ,30 + ,0 + ,4 + ,258873 + ,104 + ,124 + ,80444 + ,93163 + ,40 + ,0 + ,0 + ,324799 + ,158 + ,168 + ,97668 + ,151511 + ,47 + ,7 + ,-1 + ,230964 + ,102 + ,115 + ,133824 + ,136368 + ,30 + ,1 + ,0 + ,236785 + ,77 + ,71 + ,101481 + ,112642 + ,31 + ,0 + ,1 + ,344297 + ,80 + ,108 + ,67654 + ,127766 + ,30 + ,1 + ,0 + ,174724 + ,123 + ,120 + ,69112 + ,85646 + ,34 + ,4 + ,3 + ,174415 + ,73 + ,114 + ,82753 + ,98579 + ,31 + ,1 + ,-1 + ,223632 + ,105 + ,120 + ,72654 + ,131741 + ,33 + ,5 + ,4 + ,294424 + ,107 + ,124 + ,101494 + ,171975 + ,33 + ,13 + ,3 + ,325107 + ,84 + ,126 + ,79215 + ,159676 + ,36 + ,4 + ,1 + ,106408 + ,33 + ,37 + 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,224330 + ,131 + ,132 + ,130115 + ,139296 + ,39 + ,4 + ,6 + ,181633 + ,47 + ,73 + ,64466 + ,89455 + ,30 + ,0 + ,-3 + ,271856 + ,109 + ,86 + ,54990 + ,147866 + ,37 + ,0 + ,3 + ,95227 + ,37 + ,48 + ,34777 + ,14336 + ,32 + ,0 + ,0 + ,98146 + ,15 + ,48 + ,27114 + ,30059 + ,17 + ,7 + ,-2 + ,118612 + ,54 + ,43 + ,30080 + ,41907 + ,12 + ,3 + ,1 + ,65475 + ,16 + ,46 + ,69008 + ,35885 + ,13 + ,4 + ,0 + ,108446 + ,22 + ,65 + ,46300 + ,55764 + ,17 + ,1 + ,2 + ,121848 + ,37 + ,52 + ,30594 + ,35619 + ,17 + ,0 + ,2 + ,76302 + ,29 + ,68 + ,30976 + ,40557 + ,20 + ,2 + ,-3 + ,98104 + ,55 + ,47 + ,25568 + ,44197 + ,17 + ,0 + ,-2 + ,30989 + ,5 + ,41 + ,4154 + ,4103 + ,17 + ,0 + ,1 + ,31774 + ,0 + ,47 + ,4143 + ,4694 + ,17 + ,0 + ,-4 + ,150580 + ,27 + ,71 + ,45588 + ,62991 + ,22 + ,2 + ,0 + ,54157 + ,37 + ,30 + ,18625 + ,24261 + ,15 + ,1 + ,1 + ,59382 + ,29 + ,24 + ,26263 + ,21425 + ,12 + ,0 + ,0 + ,84105 + ,17 + ,63 + ,20055 + ,27184 + ,17 + ,0) + ,dim=c(8 + ,85) + ,dimnames=list(c('estscore' + ,'time_in_rfc' + ,'blogged_computations' + ,'feedback_messages_p120' + ,'totsize' + ,'totseconds' + ,'compendiums_reviewed' + ,'difference_hyperlinks-blogs') + ,1:85)) > y <- array(NA,dim=c(8,85),dimnames=list(c('estscore','time_in_rfc','blogged_computations','feedback_messages_p120','totsize','totseconds','compendiums_reviewed','difference_hyperlinks-blogs'),1:85)) > for (i in 1:dim(x)[1]) + { + for (j in 1:dim(x)[2]) + { + y[i,j] <- as.numeric(x[i,j]) + } + } > par4 = 'no' > par3 = '6' > par2 = 'none' > par1 = '2' > #'GNU S' R Code compiled by R2WASP v. 1.0.44 () > #Author: Dr. Ian E. Holliday > #To cite this work: Ian E. Holliday, 2009, YOUR SOFTWARE TITLE (vNUMBER) in Free Statistics Software (v$_version), Office for Research Development and Education, URL http://www.wessa.net/rwasp_YOURPAGE.wasp/ > #Source of accompanying publication: > #Technical description: > library(party) Loading required package: survival Loading required package: splines Loading required package: grid Loading required package: modeltools Loading required package: stats4 Loading required package: coin Loading required package: mvtnorm Loading required package: zoo Loading required package: sandwich Loading required package: strucchange Loading required package: vcd Loading required package: MASS Loading required package: colorspace > library(Hmisc) Attaching package: 'Hmisc' The following object(s) are masked from 'package:survival': untangle.specials The following object(s) are masked from 'package:base': format.pval, round.POSIXt, trunc.POSIXt, units > par1 <- as.numeric(par1) > par3 <- as.numeric(par3) > x <- data.frame(t(y)) > is.data.frame(x) [1] TRUE > x <- x[!is.na(x[,par1]),] > k <- length(x[1,]) > n <- length(x[,1]) > colnames(x)[par1] [1] "time_in_rfc" > x[,par1] [1] 210907 179321 149061 237213 173326 133131 258873 324799 230964 236785 [11] 344297 174724 174415 223632 294424 325107 106408 96560 265769 269651 [21] 149112 152871 362301 183167 277965 218946 244052 341570 233328 206161 [31] 311473 207176 196553 143246 182192 194979 167488 143756 275541 152299 [41] 193339 130585 112611 148446 182079 243060 162765 85574 225060 133328 [51] 100750 101523 243511 152474 132487 317394 244749 184510 128423 97839 [61] 172494 229242 351619 324598 195838 254488 199476 92499 224330 181633 [71] 271856 95227 98146 118612 65475 108446 121848 76302 98104 30989 [81] 31774 150580 54157 59382 84105 > if (par2 == 'kmeans') { + cl <- kmeans(x[,par1], par3) + print(cl) + clm <- matrix(cbind(cl$centers,1:par3),ncol=2) + clm <- clm[sort.list(clm[,1]),] + for (i in 1:par3) { + cl$cluster[cl$cluster==clm[i,2]] <- paste('C',i,sep='') + } + cl$cluster <- as.factor(cl$cluster) + print(cl$cluster) + x[,par1] <- cl$cluster + } > if (par2 == 'quantiles') { + x[,par1] <- cut2(x[,par1],g=par3) + } > if (par2 == 'hclust') { + hc <- hclust(dist(x[,par1])^2, 'cen') + print(hc) + memb <- cutree(hc, k = par3) + dum <- c(mean(x[memb==1,par1])) + for (i in 2:par3) { + dum <- c(dum, mean(x[memb==i,par1])) + } + hcm <- matrix(cbind(dum,1:par3),ncol=2) + hcm <- hcm[sort.list(hcm[,1]),] + for (i in 1:par3) { + memb[memb==hcm[i,2]] <- paste('C',i,sep='') + } + memb <- as.factor(memb) + print(memb) + x[,par1] <- memb + } > if (par2=='equal') { + ed <- cut(as.numeric(x[,par1]),par3,labels=paste('C',1:par3,sep='')) + x[,par1] <- as.factor(ed) + } > table(x[,par1]) 30989 31774 54157 59382 65475 76302 84105 85574 92499 95227 96560 1 1 1 1 1 1 1 1 1 1 1 97839 98104 98146 100750 101523 106408 108446 112611 118612 121848 128423 1 1 1 1 1 1 1 1 1 1 1 130585 132487 133131 133328 143246 143756 148446 149061 149112 150580 152299 1 1 1 1 1 1 1 1 1 1 1 152474 152871 162765 167488 172494 173326 174415 174724 179321 181633 182079 1 1 1 1 1 1 1 1 1 1 1 182192 183167 184510 193339 194979 195838 196553 199476 206161 207176 210907 1 1 1 1 1 1 1 1 1 1 1 218946 223632 224330 225060 229242 230964 233328 236785 237213 243060 243511 1 1 1 1 1 1 1 1 1 1 1 244052 244749 254488 258873 265769 269651 271856 275541 277965 294424 311473 1 1 1 1 1 1 1 1 1 1 1 317394 324598 324799 325107 341570 344297 351619 362301 1 1 1 1 1 1 1 1 > colnames(x) [1] "estscore" "time_in_rfc" [3] "blogged_computations" "feedback_messages_p120" [5] "totsize" "totseconds" [7] "compendiums_reviewed" "difference_hyperlinks.blogs" > colnames(x)[par1] [1] "time_in_rfc" > x[,par1] [1] 210907 179321 149061 237213 173326 133131 258873 324799 230964 236785 [11] 344297 174724 174415 223632 294424 325107 106408 96560 265769 269651 [21] 149112 152871 362301 183167 277965 218946 244052 341570 233328 206161 [31] 311473 207176 196553 143246 182192 194979 167488 143756 275541 152299 [41] 193339 130585 112611 148446 182079 243060 162765 85574 225060 133328 [51] 100750 101523 243511 152474 132487 317394 244749 184510 128423 97839 [61] 172494 229242 351619 324598 195838 254488 199476 92499 224330 181633 [71] 271856 95227 98146 118612 65475 108446 121848 76302 98104 30989 [81] 31774 150580 54157 59382 84105 > if (par2 == 'none') { + m <- ctree(as.formula(paste(colnames(x)[par1],' ~ .',sep='')),data = x) + } > > #Note: the /var/wessaorg/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab > load(file="/var/wessaorg/rcomp/createtable") > > if (par2 != 'none') { + m <- ctree(as.formula(paste('as.factor(',colnames(x)[par1],') ~ .',sep='')),data = x) + if (par4=='yes') { + a<-table.start() + a<-table.row.start(a) + a<-table.element(a,'10-Fold Cross Validation',3+2*par3,TRUE) + a<-table.row.end(a) + a<-table.row.start(a) + a<-table.element(a,'',1,TRUE) + a<-table.element(a,'Prediction (training)',par3+1,TRUE) + a<-table.element(a,'Prediction (testing)',par3+1,TRUE) + a<-table.row.end(a) + a<-table.row.start(a) + a<-table.element(a,'Actual',1,TRUE) + for (jjj in 1:par3) a<-table.element(a,paste('C',jjj,sep=''),1,TRUE) + a<-table.element(a,'CV',1,TRUE) + for (jjj in 1:par3) a<-table.element(a,paste('C',jjj,sep=''),1,TRUE) + a<-table.element(a,'CV',1,TRUE) + a<-table.row.end(a) + for (i in 1:10) { + ind <- sample(2, nrow(x), replace=T, prob=c(0.9,0.1)) + m.ct <- ctree(as.formula(paste('as.factor(',colnames(x)[par1],') ~ .',sep='')),data =x[ind==1,]) + if (i==1) { + m.ct.i.pred <- predict(m.ct, newdata=x[ind==1,]) + m.ct.i.actu <- x[ind==1,par1] + m.ct.x.pred <- predict(m.ct, newdata=x[ind==2,]) + m.ct.x.actu <- x[ind==2,par1] + } else { + m.ct.i.pred <- c(m.ct.i.pred,predict(m.ct, newdata=x[ind==1,])) + m.ct.i.actu <- c(m.ct.i.actu,x[ind==1,par1]) + m.ct.x.pred <- c(m.ct.x.pred,predict(m.ct, newdata=x[ind==2,])) + m.ct.x.actu <- c(m.ct.x.actu,x[ind==2,par1]) + } + } + print(m.ct.i.tab <- table(m.ct.i.actu,m.ct.i.pred)) + numer <- 0 + for (i in 1:par3) { + print(m.ct.i.tab[i,i] / sum(m.ct.i.tab[i,])) + numer <- numer + m.ct.i.tab[i,i] + } + print(m.ct.i.cp <- numer / sum(m.ct.i.tab)) + print(m.ct.x.tab <- table(m.ct.x.actu,m.ct.x.pred)) + numer <- 0 + for (i in 1:par3) { + print(m.ct.x.tab[i,i] / sum(m.ct.x.tab[i,])) + numer <- numer + m.ct.x.tab[i,i] + } + print(m.ct.x.cp <- numer / sum(m.ct.x.tab)) + for (i in 1:par3) { + a<-table.row.start(a) + a<-table.element(a,paste('C',i,sep=''),1,TRUE) + for (jjj in 1:par3) a<-table.element(a,m.ct.i.tab[i,jjj]) + a<-table.element(a,round(m.ct.i.tab[i,i]/sum(m.ct.i.tab[i,]),4)) + for (jjj in 1:par3) a<-table.element(a,m.ct.x.tab[i,jjj]) + a<-table.element(a,round(m.ct.x.tab[i,i]/sum(m.ct.x.tab[i,]),4)) + a<-table.row.end(a) + } + a<-table.row.start(a) + a<-table.element(a,'Overall',1,TRUE) + for (jjj in 1:par3) a<-table.element(a,'-') + a<-table.element(a,round(m.ct.i.cp,4)) + for (jjj in 1:par3) a<-table.element(a,'-') + a<-table.element(a,round(m.ct.x.cp,4)) + a<-table.row.end(a) + a<-table.end(a) + table.save(a,file="/var/wessaorg/rcomp/tmp/1zryh1324319836.tab") + } + } > m Conditional inference tree with 5 terminal nodes Response: time_in_rfc Inputs: estscore, blogged_computations, feedback_messages_p120, totsize, totseconds, compendiums_reviewed, difference_hyperlinks.blogs Number of observations: 85 1) totseconds <= 76669; criterion = 1, statistic = 62.226 2) totseconds <= 58391; criterion = 1, statistic = 20.435 3) blogged_computations <= 29; criterion = 0.982, statistic = 9.09 4)* weights = 9 3) blogged_computations > 29 5)* weights = 12 2) totseconds > 58391 6)* weights = 14 1) totseconds > 76669 7) totseconds <= 112494; criterion = 1, statistic = 17.413 8)* weights = 24 7) totseconds > 112494 9)* weights = 26 > postscript(file="/var/wessaorg/rcomp/tmp/2f4wp1324319836.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > plot(m) > dev.off() null device 1 > postscript(file="/var/wessaorg/rcomp/tmp/3qlh41324319836.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > plot(x[,par1] ~ as.factor(where(m)),main='Response by Terminal Node',xlab='Terminal Node',ylab='Response') > dev.off() null device 1 > if (par2 == 'none') { + forec <- predict(m) + result <- as.data.frame(cbind(x[,par1],forec,x[,par1]-forec)) + colnames(result) <- c('Actuals','Forecasts','Residuals') + print(result) + } Actuals Forecasts Residuals 1 210907 269233.0 -58326.0385 2 179321 200812.1 -21491.0833 3 149061 200812.1 -51751.0833 4 237213 269233.0 -32020.0385 5 173326 146219.2 27106.7857 6 133131 146219.2 -13088.2143 7 258873 200812.1 58060.9167 8 324799 269233.0 55565.9615 9 230964 269233.0 -38269.0385 10 236785 269233.0 -32448.0385 11 344297 269233.0 75063.9615 12 174724 200812.1 -26088.0833 13 174415 200812.1 -26397.0833 14 223632 269233.0 -45601.0385 15 294424 269233.0 25190.9615 16 325107 269233.0 55873.9615 17 106408 104294.5 2113.5000 18 96560 104294.5 -7734.5000 19 265769 269233.0 -3464.0385 20 269651 269233.0 417.9615 21 149112 146219.2 2892.7857 22 152871 200812.1 -47941.0833 23 362301 200812.1 161488.9167 24 183167 200812.1 -17645.0833 25 277965 269233.0 8731.9615 26 218946 200812.1 18133.9167 27 244052 269233.0 -25181.0385 28 341570 269233.0 72336.9615 29 233328 269233.0 -35905.0385 30 206161 146219.2 59941.7857 31 311473 269233.0 42239.9615 32 207176 200812.1 6363.9167 33 196553 269233.0 -72680.0385 34 143246 146219.2 -2973.2143 35 182192 200812.1 -18620.0833 36 194979 200812.1 -5833.0833 37 167488 200812.1 -33324.0833 38 143756 146219.2 -2463.2143 39 275541 200812.1 74728.9167 40 152299 146219.2 6079.7857 41 193339 200812.1 -7473.0833 42 130585 146219.2 -15634.2143 43 112611 104294.5 8316.5000 44 148446 146219.2 2226.7857 45 182079 200812.1 -18733.0833 46 243060 269233.0 -26173.0385 47 162765 200812.1 -38047.0833 48 85574 104294.5 -18720.5000 49 225060 200812.1 24247.9167 50 133328 146219.2 -12891.2143 51 100750 146219.2 -45469.2143 52 101523 104294.5 -2771.5000 53 243511 200812.1 42698.9167 54 152474 200812.1 -48338.0833 55 132487 104294.5 28192.5000 56 317394 269233.0 48160.9615 57 244749 269233.0 -24484.0385 58 184510 146219.2 38290.7857 59 128423 104294.5 24128.5000 60 97839 146219.2 -48380.2143 61 172494 200812.1 -28318.0833 62 229242 200812.1 28429.9167 63 351619 269233.0 82385.9615 64 324598 269233.0 55364.9615 65 195838 200812.1 -4974.0833 66 254488 269233.0 -14745.0385 67 199476 269233.0 -69757.0385 68 92499 71902.0 20597.0000 69 224330 269233.0 -44903.0385 70 181633 200812.1 -19179.0833 71 271856 269233.0 2622.9615 72 95227 104294.5 -9067.5000 73 98146 71902.0 26244.0000 74 118612 104294.5 14317.5000 75 65475 71902.0 -6427.0000 76 108446 71902.0 36544.0000 77 121848 104294.5 17553.5000 78 76302 71902.0 4400.0000 79 98104 104294.5 -6190.5000 80 30989 71902.0 -40913.0000 81 31774 71902.0 -40128.0000 82 150580 146219.2 4360.7857 83 54157 104294.5 -50137.5000 84 59382 71902.0 -12520.0000 85 84105 71902.0 12203.0000 > if (par2 != 'none') { + print(cbind(as.factor(x[,par1]),predict(m))) + myt <- table(as.factor(x[,par1]),predict(m)) + print(myt) + } > postscript(file="/var/wessaorg/rcomp/tmp/4w8fh1324319836.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > if(par2=='none') { + op <- par(mfrow=c(2,2)) + plot(density(result$Actuals),main='Kernel Density Plot of Actuals') + plot(density(result$Residuals),main='Kernel Density Plot of Residuals') + plot(result$Forecasts,result$Actuals,main='Actuals versus Predictions',xlab='Predictions',ylab='Actuals') + plot(density(result$Forecasts),main='Kernel Density Plot of Predictions') + par(op) + } > if(par2!='none') { + plot(myt,main='Confusion Matrix',xlab='Actual',ylab='Predicted') + } > dev.off() null device 1 > if (par2 == 'none') { + detcoef <- cor(result$Forecasts,result$Actuals) + a<-table.start() + a<-table.row.start(a) + a<-table.element(a,'Goodness of Fit',2,TRUE) + a<-table.row.end(a) + a<-table.row.start(a) + a<-table.element(a,'Correlation',1,TRUE) + a<-table.element(a,round(detcoef,4)) + a<-table.row.end(a) + a<-table.row.start(a) + a<-table.element(a,'R-squared',1,TRUE) + a<-table.element(a,round(detcoef*detcoef,4)) + a<-table.row.end(a) + a<-table.row.start(a) + a<-table.element(a,'RMSE',1,TRUE) + a<-table.element(a,round(sqrt(mean((result$Residuals)^2)),4)) + a<-table.row.end(a) + a<-table.end(a) + table.save(a,file="/var/wessaorg/rcomp/tmp/5ysaf1324319836.tab") + a<-table.start() + a<-table.row.start(a) + a<-table.element(a,'Actuals, Predictions, and Residuals',4,TRUE) + a<-table.row.end(a) + a<-table.row.start(a) + a<-table.element(a,'#',header=TRUE) + a<-table.element(a,'Actuals',header=TRUE) + a<-table.element(a,'Forecasts',header=TRUE) + a<-table.element(a,'Residuals',header=TRUE) + a<-table.row.end(a) + for (i in 1:length(result$Actuals)) { + a<-table.row.start(a) + a<-table.element(a,i,header=TRUE) + a<-table.element(a,result$Actuals[i]) + a<-table.element(a,result$Forecasts[i]) + a<-table.element(a,result$Residuals[i]) + a<-table.row.end(a) + } + a<-table.end(a) + table.save(a,file="/var/wessaorg/rcomp/tmp/69lm21324319836.tab") + } > if (par2 != 'none') { + a<-table.start() + a<-table.row.start(a) + a<-table.element(a,'Confusion Matrix (predicted in columns / actuals in rows)',par3+1,TRUE) + a<-table.row.end(a) + a<-table.row.start(a) + a<-table.element(a,'',1,TRUE) + for (i in 1:par3) { + a<-table.element(a,paste('C',i,sep=''),1,TRUE) + } + a<-table.row.end(a) + for (i in 1:par3) { + a<-table.row.start(a) + a<-table.element(a,paste('C',i,sep=''),1,TRUE) + for (j in 1:par3) { + a<-table.element(a,myt[i,j]) + } + a<-table.row.end(a) + } + a<-table.end(a) + table.save(a,file="/var/wessaorg/rcomp/tmp/7ndzg1324319836.tab") + } > > try(system("convert tmp/2f4wp1324319836.ps tmp/2f4wp1324319836.png",intern=TRUE)) character(0) > try(system("convert tmp/3qlh41324319836.ps tmp/3qlh41324319836.png",intern=TRUE)) character(0) > try(system("convert tmp/4w8fh1324319836.ps tmp/4w8fh1324319836.png",intern=TRUE)) character(0) > > > proc.time() user system elapsed 3.104 0.343 3.442