R version 2.9.0 (2009-04-17)
Copyright (C) 2009 The R Foundation for Statistical Computing
ISBN 3-900051-07-0

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Type 'demo()' for some demos, 'help()' for on-line help, or
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Type 'q()' to quit R.

> x <- array(list(46
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+ ,33
+ ,48
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+ ,19)
+ ,dim=c(5
+ ,146)
+ ,dimnames=list(c('Carrieremogelijkheden'
+ ,'Geen_Motivatie'
+ ,'Leermogelijkheden'
+ ,'Persoonlijke_redenen'
+ ,'Ouders')
+ ,1:146))
>  y <- array(NA,dim=c(5,146),dimnames=list(c('Carrieremogelijkheden','Geen_Motivatie','Leermogelijkheden','Persoonlijke_redenen','Ouders'),1:146))
>  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 = '3'
> par2 = 'quantiles'
> par1 = '3'
> #'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

Attaching package: 'zoo'


	The following object(s) are masked from package:base :

	 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)

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] "Leermogelijkheden"
> x[,par1]
  [1] 52 39 42 35 32 49 33 47 46 40 33 39 37 56 36 24 56 32 41 24 42 47 25 33 43
 [26] 45 44 46 31 31 42 28 38 59 43 29 38 39 50 44 29 29 36 43 28 39 35 43 28 49
 [51] 33 39 36 24 47 34 33 43 41 40 39 54 43 45 29 45 47 38 52 34 56 26 42 32 39
 [76] 37 37 52 31 34 38 29 52 40 47 34 37 43 37 55 36 28 47 38 37 32 47 40 45 37
[101] 38 37 35 50 32 32 38 31 27 34 43 28 44 43 53 33 36 46 36 24 50 40 40 32 49
[126] 47 28 41 25 46 53 34 40 46 38 51 38 45 41 42 36 41 35 42 35 32
> 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])

[24,37) [37,44) [44,59] 
     55      51      40 
> colnames(x)
[1] "Carrieremogelijkheden" "Geen_Motivatie"        "Leermogelijkheden"    
[4] "Persoonlijke_redenen"  "Ouders"               
> colnames(x)[par1]
[1] "Leermogelijkheden"
> x[,par1]
  [1] [44,59] [37,44) [37,44) [24,37) [24,37) [44,59] [24,37) [44,59] [44,59]
 [10] [37,44) [24,37) [37,44) [37,44) [44,59] [24,37) [24,37) [44,59] [24,37)
 [19] [37,44) [24,37) [37,44) [44,59] [24,37) [24,37) [37,44) [44,59] [44,59]
 [28] [44,59] [24,37) [24,37) [37,44) [24,37) [37,44) [44,59] [37,44) [24,37)
 [37] [37,44) [37,44) [44,59] [44,59] [24,37) [24,37) [24,37) [37,44) [24,37)
 [46] [37,44) [24,37) [37,44) [24,37) [44,59] [24,37) [37,44) [24,37) [24,37)
 [55] [44,59] [24,37) [24,37) [37,44) [37,44) [37,44) [37,44) [44,59] [37,44)
 [64] [44,59] [24,37) [44,59] [44,59] [37,44) [44,59] [24,37) [44,59] [24,37)
 [73] [37,44) [24,37) [37,44) [37,44) [37,44) [44,59] [24,37) [24,37) [37,44)
 [82] [24,37) [44,59] [37,44) [44,59] [24,37) [37,44) [37,44) [37,44) [44,59]
 [91] [24,37) [24,37) [44,59] [37,44) [37,44) [24,37) [44,59] [37,44) [44,59]
[100] [37,44) [37,44) [37,44) [24,37) [44,59] [24,37) [24,37) [37,44) [24,37)
[109] [24,37) [24,37) [37,44) [24,37) [44,59] [37,44) [44,59] [24,37) [24,37)
[118] [44,59] [24,37) [24,37) [44,59] [37,44) [37,44) [24,37) [44,59] [44,59]
[127] [24,37) [37,44) [24,37) [44,59] [44,59] [24,37) [37,44) [44,59] [37,44)
[136] [44,59] [37,44) [44,59] [37,44) [37,44) [24,37) [37,44) [24,37) [37,44)
[145] [24,37) [24,37)
Levels: [24,37) [37,44) [44,59]
> if (par2 == 'none') {
+ m <- ctree(as.formula(paste(colnames(x)[par1],' ~ .',sep='')),data = x)
+ }
> 
> #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/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/www/html/rcomp/tmp/1gj9t1292923665.tab") 
+ }
+ }
> m

	 Conditional inference tree with 3 terminal nodes

Response:  as.factor(Leermogelijkheden) 
Inputs:  Carrieremogelijkheden, Geen_Motivatie, Persoonlijke_redenen, Ouders 
Number of observations:  146 

1) Persoonlijke_redenen <= 32; criterion = 1, statistic = 33.229
  2) Carrieremogelijkheden <= 42; criterion = 0.984, statistic = 11.02
    3)*  weights = 28 
  2) Carrieremogelijkheden > 42
    4)*  weights = 72 
1) Persoonlijke_redenen > 32
  5)*  weights = 46 
> postscript(file="/var/www/html/rcomp/tmp/2gj9t1292923665.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/www/html/rcomp/tmp/3gj9t1292923665.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,]    3    2
  [2,]    2    2
  [3,]    2    1
  [4,]    1    1
  [5,]    1    2
  [6,]    3    3
  [7,]    1    2
  [8,]    3    2
  [9,]    3    2
 [10,]    2    2
 [11,]    1    2
 [12,]    2    2
 [13,]    2    2
 [14,]    3    3
 [15,]    1    2
 [16,]    1    2
 [17,]    3    2
 [18,]    1    3
 [19,]    2    2
 [20,]    1    1
 [21,]    2    2
 [22,]    3    3
 [23,]    1    2
 [24,]    1    1
 [25,]    2    2
 [26,]    3    3
 [27,]    3    2
 [28,]    3    3
 [29,]    1    1
 [30,]    1    2
 [31,]    2    3
 [32,]    1    2
 [33,]    2    2
 [34,]    3    3
 [35,]    2    3
 [36,]    1    2
 [37,]    2    2
 [38,]    2    3
 [39,]    3    3
 [40,]    3    3
 [41,]    1    2
 [42,]    1    1
 [43,]    1    3
 [44,]    2    2
 [45,]    1    2
 [46,]    2    2
 [47,]    1    2
 [48,]    2    3
 [49,]    1    1
 [50,]    3    2
 [51,]    1    2
 [52,]    2    2
 [53,]    1    2
 [54,]    1    3
 [55,]    3    3
 [56,]    1    1
 [57,]    1    2
 [58,]    2    3
 [59,]    2    3
 [60,]    2    1
 [61,]    2    3
 [62,]    3    3
 [63,]    2    2
 [64,]    3    3
 [65,]    1    2
 [66,]    3    2
 [67,]    3    2
 [68,]    2    2
 [69,]    3    3
 [70,]    1    1
 [71,]    3    3
 [72,]    1    1
 [73,]    2    3
 [74,]    1    2
 [75,]    2    2
 [76,]    2    2
 [77,]    2    3
 [78,]    3    3
 [79,]    1    1
 [80,]    1    2
 [81,]    2    2
 [82,]    1    1
 [83,]    3    2
 [84,]    2    2
 [85,]    3    2
 [86,]    1    3
 [87,]    2    2
 [88,]    2    2
 [89,]    2    2
 [90,]    3    3
 [91,]    1    2
 [92,]    1    1
 [93,]    3    3
 [94,]    2    3
 [95,]    2    1
 [96,]    1    1
 [97,]    3    2
 [98,]    2    2
 [99,]    3    3
[100,]    2    3
[101,]    2    3
[102,]    2    1
[103,]    1    1
[104,]    3    3
[105,]    1    2
[106,]    1    3
[107,]    2    2
[108,]    1    1
[109,]    1    2
[110,]    1    1
[111,]    2    3
[112,]    1    2
[113,]    3    3
[114,]    2    2
[115,]    3    3
[116,]    1    2
[117,]    1    1
[118,]    3    3
[119,]    1    2
[120,]    1    1
[121,]    3    3
[122,]    2    2
[123,]    2    3
[124,]    1    2
[125,]    3    3
[126,]    3    3
[127,]    1    2
[128,]    2    2
[129,]    1    2
[130,]    3    1
[131,]    3    2
[132,]    1    1
[133,]    2    2
[134,]    3    2
[135,]    2    2
[136,]    3    3
[137,]    2    3
[138,]    3    2
[139,]    2    1
[140,]    2    2
[141,]    1    3
[142,]    2    2
[143,]    1    1
[144,]    2    1
[145,]    1    1
[146,]    1    2
         
          [24,37) [37,44) [44,59]
  [24,37)      21      28       6
  [37,44)       6      30      15
  [44,59]       1      14      25
> postscript(file="/var/www/html/rcomp/tmp/4118h1292923665.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/www/html/rcomp/tmp/542641292923665.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/www/html/rcomp/tmp/6qkns1292923665.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/www/html/rcomp/tmp/7t4p81292923666.tab") 
+ }
> 
> try(system("convert tmp/2gj9t1292923665.ps tmp/2gj9t1292923665.png",intern=TRUE))
character(0)
> try(system("convert tmp/3gj9t1292923665.ps tmp/3gj9t1292923665.png",intern=TRUE))
character(0)
> try(system("convert tmp/4118h1292923665.ps tmp/4118h1292923665.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  2.113   0.477   9.085