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

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(-5,-6,33,5,15,-1,-3,24,6,17,-2,-4,24,6,13,-5,-7,31,5,12,-4,-7,25,5,13,-6,-7,28,3,10,-2,-3,24,5,14,-2,0,25,5,13,-2,-5,16,5,10,-2,-3,17,3,11,2,3,11,6,12,1,2,12,6,7,-8,-7,39,4,11,-1,-1,19,6,9,1,0,14,5,13,-1,-3,15,4,12,2,4,7,5,5,2,2,12,5,13,1,3,12,4,11,-1,0,14,3,8,-2,-10,9,2,8,-2,-10,8,3,8,-1,-9,4,2,8,-8,-22,7,-1,0,-4,-16,3,0,3,-6,-18,5,-2,0,-3,-14,0,1,-1,-3,-12,-2,-2,-1,-7,-17,6,-2,-4,-9,-23,11,-2,1,-11,-28,9,-6,-1,-13,-31,17,-4,0,-11,-21,21,-2,-1,-9,-19,21,0,6,-17,-22,41,-5,0,-22,-22,57,-4,-3,-25,-25,65,-5,-3,-20,-16,68,-1,4,-24,-22,73,-2,1,-24,-21,71,-4,0,-22,-10,71,-1,-4,-19,-7,70,1,-2,-18,-5,69,1,3,-17,-4,65,-2,2,-11,7,57,1,5,-11,6,57,1,6,-12,3,57,3,6,-10,10,55,3,3,-15,0,65,1,4,-15,-2,65,1,7,-15,-1,64,0,5,-13,2,60,2,6,-8,8,43,2,1,-13,-6,47,-1,3,-9,-4,40,1,6,-7,4,31,0,0,-4,7,27,1,3,-4,3,24,1,4,-2,3,23,3,7,0,8,17,2,6),dim=c(5,60),dimnames=list(c('indicator','vooruitzichten','werkloosheid','financiën','spaarvermogen'),1:60))
>  y <- array(NA,dim=c(5,60),dimnames=list(c('indicator','vooruitzichten','werkloosheid','financiën','spaarvermogen'),1:60))
>  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 = '2'
> 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] "werkloosheid"
> x[,par1]
 [1] 33 24 24 31 25 28 24 25 16 17 11 12 39 19 14 15  7 12 12 14  9  8  4  7  3
[26]  5  0 -2  6 11  9 17 21 21 41 57 65 68 73 71 71 70 69 65 57 57 57 55 65 65
[51] 64 60 43 47 40 31 27 24 23 17
> 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])

[-2,25) [25,73] 
     31      29 
> colnames(x)
[1] "indicator"      "vooruitzichten" "werkloosheid"   "financi..n"    
[5] "spaarvermogen" 
> colnames(x)[par1]
[1] "werkloosheid"
> x[,par1]
 [1] [25,73] [-2,25) [-2,25) [25,73] [25,73] [25,73] [-2,25) [25,73] [-2,25)
[10] [-2,25) [-2,25) [-2,25) [25,73] [-2,25) [-2,25) [-2,25) [-2,25) [-2,25)
[19] [-2,25) [-2,25) [-2,25) [-2,25) [-2,25) [-2,25) [-2,25) [-2,25) [-2,25)
[28] [-2,25) [-2,25) [-2,25) [-2,25) [-2,25) [-2,25) [-2,25) [25,73] [25,73]
[37] [25,73] [25,73] [25,73] [25,73] [25,73] [25,73] [25,73] [25,73] [25,73]
[46] [25,73] [25,73] [25,73] [25,73] [25,73] [25,73] [25,73] [25,73] [25,73]
[55] [25,73] [25,73] [25,73] [-2,25) [-2,25) [-2,25)
Levels: [-2,25) [25,73]
> 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/19tik1293272563.tab") 
+ }
+ }
> m

	 Conditional inference tree with 3 terminal nodes

Response:  as.factor(werkloosheid) 
Inputs:  indicator, vooruitzichten, financi..n, spaarvermogen 
Number of observations:  60 

1) indicator <= -4; criterion = 1, statistic = 26.802
  2) vooruitzichten <= -16; criterion = 0.995, statistic = 10.512
    3)*  weights = 15 
  2) vooruitzichten > -16
    4)*  weights = 23 
1) indicator > -4
  5)*  weights = 22 
> postscript(file="/var/www/html/rcomp/tmp/29tik1293272563.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/39tik1293272563.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,]    1    1
 [3,]    1    1
 [4,]    2    2
 [5,]    2    2
 [6,]    2    2
 [7,]    1    1
 [8,]    2    1
 [9,]    1    1
[10,]    1    1
[11,]    1    1
[12,]    1    1
[13,]    2    2
[14,]    1    1
[15,]    1    1
[16,]    1    1
[17,]    1    1
[18,]    1    1
[19,]    1    1
[20,]    1    1
[21,]    1    1
[22,]    1    1
[23,]    1    1
[24,]    1    1
[25,]    1    1
[26,]    1    1
[27,]    1    1
[28,]    1    1
[29,]    1    1
[30,]    1    1
[31,]    1    1
[32,]    1    1
[33,]    1    1
[34,]    1    1
[35,]    2    1
[36,]    2    1
[37,]    2    1
[38,]    2    1
[39,]    2    1
[40,]    2    1
[41,]    2    2
[42,]    2    2
[43,]    2    2
[44,]    2    2
[45,]    2    2
[46,]    2    2
[47,]    2    2
[48,]    2    2
[49,]    2    2
[50,]    2    2
[51,]    2    2
[52,]    2    2
[53,]    2    2
[54,]    2    2
[55,]    2    2
[56,]    2    2
[57,]    2    2
[58,]    1    2
[59,]    1    1
[60,]    1    1
         
          [-2,25) [25,73]
  [-2,25)      30       1
  [25,73]       7      22
> postscript(file="/var/www/html/rcomp/tmp/4j20n1293272563.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/5ycfe1293272563.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/6qlfg1293272563.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/7u4d41293272563.tab") 
+ }
> 
> try(system("convert tmp/29tik1293272563.ps tmp/29tik1293272563.png",intern=TRUE))
character(0)
> try(system("convert tmp/39tik1293272563.ps tmp/39tik1293272563.png",intern=TRUE))
character(0)
> try(system("convert tmp/4j20n1293272563.ps tmp/4j20n1293272563.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  2.068   0.496  31.994