R version 2.15.2 (2012-10-26) -- "Trick or Treat" Copyright (C) 2012 The R Foundation for Statistical Computing ISBN 3-900051-07-0 Platform: i686-pc-linux-gnu (32-bit) 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. > x <- array(list(0 + ,24 + ,14 + ,11 + ,12 + ,24 + ,26 + ,0 + ,25 + ,11 + ,7 + ,8 + ,25 + ,23 + ,0 + ,17 + ,6 + ,17 + ,8 + ,30 + ,25 + ,1 + ,18 + ,12 + ,10 + ,8 + ,19 + ,23 + ,1 + ,18 + ,8 + ,12 + ,9 + ,22 + ,19 + ,1 + ,16 + ,10 + ,12 + ,7 + ,22 + ,29 + ,1 + ,20 + ,10 + ,11 + ,4 + ,25 + ,25 + ,1 + ,16 + ,11 + ,11 + ,11 + ,23 + ,21 + ,1 + ,18 + ,16 + ,12 + ,7 + ,17 + ,22 + ,1 + ,17 + ,11 + ,13 + ,7 + ,21 + ,25 + ,0 + ,23 + ,13 + ,14 + ,12 + ,19 + ,24 + ,0 + ,30 + ,12 + ,16 + ,10 + ,19 + ,18 + ,1 + ,23 + ,8 + ,11 + ,10 + ,15 + ,22 + ,1 + ,18 + ,12 + ,10 + ,8 + ,16 + ,15 + ,1 + ,15 + ,11 + ,11 + ,8 + ,23 + ,22 + ,1 + ,12 + ,4 + ,15 + ,4 + ,27 + ,28 + ,0 + ,21 + ,9 + ,9 + ,9 + ,22 + ,20 + ,1 + ,15 + ,8 + ,11 + ,8 + ,14 + ,12 + ,1 + ,20 + ,8 + ,17 + ,7 + ,22 + ,24 + ,0 + ,31 + ,14 + ,17 + ,11 + ,23 + ,20 + ,0 + ,27 + ,15 + ,11 + ,9 + ,23 + ,21 + ,1 + ,34 + ,16 + ,18 + ,11 + ,21 + ,20 + ,1 + ,21 + ,9 + ,14 + ,13 + ,19 + ,21 + ,1 + ,31 + ,14 + ,10 + ,8 + ,18 + ,23 + ,1 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+ ,7 + ,11 + ,9 + ,26 + ,22 + ,1 + ,28 + ,16 + ,16 + ,8 + ,24 + ,24 + ,1 + ,38 + ,11 + ,21 + ,7 + ,29 + ,29 + ,0 + ,22 + ,9 + ,14 + ,6 + ,19 + ,12 + ,1 + ,20 + ,11 + ,20 + ,13 + ,24 + ,20 + ,0 + ,17 + ,9 + ,13 + ,6 + ,19 + ,21 + ,1 + ,28 + ,14 + ,11 + ,8 + ,24 + ,24 + ,1 + ,22 + ,13 + ,15 + ,10 + ,22 + ,22 + ,0 + ,31 + ,16 + ,19 + ,16 + ,17 + ,20) + ,dim=c(7 + ,159) + ,dimnames=list(c('Gender' + ,'ConcMistakes' + ,'DoubtsActions' + ,'ParExp' + ,'ParCrit' + ,'PersonalStandards' + ,'Organisation') + ,1:159)) > y <- array(NA,dim=c(7,159),dimnames=list(c('Gender','ConcMistakes','DoubtsActions','ParExp','ParCrit','PersonalStandards','Organisation'),1:159)) > for (i in 1:dim(x)[1]) + { + for (j in 1:dim(x)[2]) + { + y[i,j] <- as.numeric(x[i,j]) + } + } > par20 = '' > par19 = '' > par18 = '' > par17 = '' > par16 = '' > par15 = '' > par14 = '' > par13 = '' > par12 = '' > par11 = '' > par10 = '' > par9 = '' > par8 = '' > par7 = '' > par6 = '' > par5 = '' > par4 = 'yes' > par3 = '2' > par2 = 'quantiles' > par1 = '2' > 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 Attaching package: 'zoo' The following object(s) are masked from 'package:base': as.Date, as.Date.numeric Loading required package: sandwich Loading required package: strucchange Loading required package: vcd Loading required package: MASS Loading required package: colorspace > library(Hmisc) Hmisc library by Frank E Harrell Jr Type library(help='Hmisc'), ?Overview, or ?Hmisc.Overview') to see overall documentation. NOTE:Hmisc no longer redefines [.factor to drop unused levels when subsetting. To get the old behavior of Hmisc type dropUnusedLevels(). 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] "ConcMistakes" > x[,par1] [1] 24 25 17 18 18 16 20 16 18 17 23 30 23 18 15 12 21 15 20 31 27 34 21 31 19 [26] 16 20 21 22 17 24 25 26 25 17 32 33 13 32 25 29 22 18 17 20 15 20 33 29 23 [51] 26 18 20 11 28 26 22 17 12 14 17 21 19 18 10 29 31 19 9 20 28 19 30 29 26 [76] 23 13 21 19 28 23 18 21 20 23 21 21 15 28 19 26 10 16 22 19 31 31 29 19 22 [101] 23 15 20 18 23 25 21 24 25 17 13 28 21 25 9 16 19 17 25 20 29 14 22 15 19 [126] 20 15 20 18 33 22 16 17 16 21 26 18 18 17 22 30 30 24 21 21 29 31 20 16 22 [151] 20 28 38 22 20 17 28 22 31 > 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]) [ 9,22) [22,38] 89 70 > colnames(x) [1] "Gender" "ConcMistakes" "DoubtsActions" [4] "ParExp" "ParCrit" "PersonalStandards" [7] "Organisation" > colnames(x)[par1] [1] "ConcMistakes" > x[,par1] [1] [22,38] [22,38] [ 9,22) [ 9,22) [ 9,22) [ 9,22) [ 9,22) [ 9,22) [ 9,22) [10] [ 9,22) [22,38] [22,38] [22,38] [ 9,22) [ 9,22) [ 9,22) [ 9,22) [ 9,22) [19] [ 9,22) [22,38] [22,38] [22,38] [ 9,22) [22,38] [ 9,22) [ 9,22) [ 9,22) [28] [ 9,22) [22,38] [ 9,22) [22,38] [22,38] [22,38] [22,38] [ 9,22) [22,38] [37] [22,38] [ 9,22) [22,38] [22,38] [22,38] [22,38] [ 9,22) [ 9,22) [ 9,22) [46] [ 9,22) [ 9,22) [22,38] [22,38] [22,38] [22,38] [ 9,22) [ 9,22) [ 9,22) [55] [22,38] [22,38] [22,38] [ 9,22) [ 9,22) [ 9,22) [ 9,22) [ 9,22) [ 9,22) [64] [ 9,22) [ 9,22) [22,38] [22,38] [ 9,22) [ 9,22) [ 9,22) [22,38] [ 9,22) [73] [22,38] [22,38] [22,38] [22,38] [ 9,22) [ 9,22) [ 9,22) [22,38] [22,38] [82] [ 9,22) [ 9,22) [ 9,22) [22,38] [ 9,22) [ 9,22) [ 9,22) [22,38] [ 9,22) [91] [22,38] [ 9,22) [ 9,22) [22,38] [ 9,22) [22,38] [22,38] [22,38] [ 9,22) [100] [22,38] [22,38] [ 9,22) [ 9,22) [ 9,22) [22,38] [22,38] [ 9,22) [22,38] [109] [22,38] [ 9,22) [ 9,22) [22,38] [ 9,22) [22,38] [ 9,22) [ 9,22) [ 9,22) [118] [ 9,22) [22,38] [ 9,22) [22,38] [ 9,22) [22,38] [ 9,22) [ 9,22) [ 9,22) [127] [ 9,22) [ 9,22) [ 9,22) [22,38] [22,38] [ 9,22) [ 9,22) [ 9,22) [ 9,22) [136] [22,38] [ 9,22) [ 9,22) [ 9,22) [22,38] [22,38] [22,38] [22,38] [ 9,22) [145] [ 9,22) [22,38] [22,38] [ 9,22) [ 9,22) [22,38] [ 9,22) [22,38] [22,38] [154] [22,38] [ 9,22) [ 9,22) [22,38] [22,38] [22,38] Levels: [ 9,22) [22,38] > if (par2 == 'none') { + m <- ctree(as.formula(paste(colnames(x)[par1],' ~ .',sep='')),data = x) + } > > #Note: the /var/fisher/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab > load(file="/var/fisher/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/fisher/rcomp/tmp/1tam61355153828.tab") + } + } m.ct.i.pred m.ct.i.actu 1 2 1 700 100 2 233 385 [1] 0.875 [1] 0.6229773 [1] 0.7651622 m.ct.x.pred m.ct.x.actu 1 2 1 69 21 2 36 46 [1] 0.7666667 [1] 0.5609756 [1] 0.6686047 > m Conditional inference tree with 5 terminal nodes Response: as.factor(ConcMistakes) Inputs: Gender, DoubtsActions, ParExp, ParCrit, PersonalStandards, Organisation Number of observations: 159 1) PersonalStandards <= 24; criterion = 1, statistic = 21.669 2) ParCrit <= 9; criterion = 1, statistic = 17.216 3) DoubtsActions <= 13; criterion = 0.98, statistic = 8.561 4)* weights = 66 3) DoubtsActions > 13 5)* weights = 19 2) ParCrit > 9 6)* weights = 28 1) PersonalStandards > 24 7) DoubtsActions <= 10; criterion = 0.999, statistic = 14.48 8)* weights = 24 7) DoubtsActions > 10 9)* weights = 22 > postscript(file="/var/fisher/rcomp/tmp/2xod11355153828.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/fisher/rcomp/tmp/3wak11355153828.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) + } > if (par2 != 'none') { + print(cbind(as.factor(x[,par1]),predict(m))) + myt <- table(as.factor(x[,par1]),predict(m)) + print(myt) + } [,1] [,2] [1,] 2 2 [2,] 2 2 [3,] 1 1 [4,] 1 1 [5,] 1 1 [6,] 1 1 [7,] 1 1 [8,] 1 2 [9,] 1 2 [10,] 1 1 [11,] 2 2 [12,] 2 2 [13,] 2 2 [14,] 1 1 [15,] 1 1 [16,] 1 1 [17,] 1 1 [18,] 1 1 [19,] 1 1 [20,] 2 2 [21,] 2 2 [22,] 2 2 [23,] 1 2 [24,] 2 2 [25,] 1 1 [26,] 1 1 [27,] 1 1 [28,] 1 1 [29,] 2 1 [30,] 1 1 [31,] 2 1 [32,] 2 2 [33,] 2 2 [34,] 2 1 [35,] 1 1 [36,] 2 2 [37,] 2 2 [38,] 1 2 [39,] 2 2 [40,] 2 2 [41,] 2 2 [42,] 2 1 [43,] 1 1 [44,] 1 1 [45,] 1 1 [46,] 1 1 [47,] 1 2 [48,] 2 2 [49,] 2 1 [50,] 2 2 [51,] 2 2 [52,] 1 1 [53,] 1 1 [54,] 1 1 [55,] 2 1 [56,] 2 1 [57,] 2 1 [58,] 1 1 [59,] 1 1 [60,] 1 2 [61,] 1 1 [62,] 1 1 [63,] 1 1 [64,] 1 1 [65,] 1 1 [66,] 2 2 [67,] 2 1 [68,] 1 1 [69,] 1 1 [70,] 1 2 [71,] 2 1 [72,] 1 1 [73,] 2 1 [74,] 2 2 [75,] 2 1 [76,] 2 1 [77,] 1 2 [78,] 1 1 [79,] 1 1 [80,] 2 2 [81,] 2 2 [82,] 1 1 [83,] 1 1 [84,] 1 1 [85,] 2 2 [86,] 1 1 [87,] 1 1 [88,] 1 2 [89,] 2 2 [90,] 1 1 [91,] 2 2 [92,] 1 1 [93,] 1 1 [94,] 2 1 [95,] 1 2 [96,] 2 1 [97,] 2 2 [98,] 2 2 [99,] 1 1 [100,] 2 1 [101,] 2 2 [102,] 1 1 [103,] 1 2 [104,] 1 2 [105,] 2 2 [106,] 2 2 [107,] 1 1 [108,] 2 2 [109,] 2 2 [110,] 1 2 [111,] 1 1 [112,] 2 2 [113,] 1 2 [114,] 2 1 [115,] 1 1 [116,] 1 1 [117,] 1 1 [118,] 1 1 [119,] 2 2 [120,] 1 1 [121,] 2 2 [122,] 1 1 [123,] 2 2 [124,] 1 1 [125,] 1 2 [126,] 1 1 [127,] 1 1 [128,] 1 1 [129,] 1 1 [130,] 2 2 [131,] 2 2 [132,] 1 1 [133,] 1 1 [134,] 1 1 [135,] 1 1 [136,] 2 2 [137,] 1 1 [138,] 1 1 [139,] 1 1 [140,] 2 2 [141,] 2 2 [142,] 2 2 [143,] 2 2 [144,] 1 2 [145,] 1 2 [146,] 2 2 [147,] 2 1 [148,] 1 1 [149,] 1 1 [150,] 2 2 [151,] 1 1 [152,] 2 2 [153,] 2 2 [154,] 2 1 [155,] 1 2 [156,] 1 1 [157,] 2 2 [158,] 2 2 [159,] 2 2 [ 9,22) [22,38] [ 9,22) 71 18 [22,38] 19 51 > postscript(file="/var/fisher/rcomp/tmp/4db7x1355153828.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$Residuals)^2)),4)) + a<-table.row.end(a) + a<-table.end(a) + table.save(a,file="/var/fisher/rcomp/tmp/5qd6p1355153828.tab") + a<-table.start() + a<-table.row.start(a) + a<-table.element(a,'Actuals, Predictions, and Residuals',4,TRUE) + a<-table.row.end(a) + a<-table.row.start(a) + a<-table.element(a,'#',header=TRUE) + a<-table.element(a,'Actuals',header=TRUE) + a<-table.element(a,'Forecasts',header=TRUE) + a<-table.element(a,'Residuals',header=TRUE) + a<-table.row.end(a) + for (i in 1:length(result$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/fisher/rcomp/tmp/6kqz31355153829.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/fisher/rcomp/tmp/7etvu1355153829.tab") + } > > try(system("convert tmp/2xod11355153828.ps tmp/2xod11355153828.png",intern=TRUE)) character(0) > try(system("convert tmp/3wak11355153828.ps tmp/3wak11355153828.png",intern=TRUE)) character(0) > try(system("convert tmp/4db7x1355153828.ps tmp/4db7x1355153828.png",intern=TRUE)) character(0) > > > proc.time() user system elapsed 4.986 0.612 5.599