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(101.82
+ ,107.34
+ ,93.63
+ ,99.85
+ ,101.76
+ ,101.68
+ ,107.34
+ ,93.63
+ ,99.91
+ ,102.37
+ ,101.68
+ ,107.34
+ ,93.63
+ ,99.87
+ ,102.38
+ ,102.45
+ ,107.34
+ ,96.13
+ ,99.86
+ ,102.86
+ ,102.45
+ ,107.34
+ ,96.13
+ ,100.10
+ ,102.87
+ ,102.45
+ ,107.34
+ ,96.13
+ ,100.10
+ ,102.92
+ ,102.45
+ ,107.34
+ ,96.13
+ ,100.12
+ ,102.95
+ ,102.45
+ ,107.34
+ ,96.13
+ ,99.95
+ ,103.02
+ ,102.45
+ ,112.60
+ ,96.13
+ ,99.94
+ ,104.08
+ ,102.52
+ ,112.60
+ ,96.13
+ ,100.18
+ ,104.16
+ ,102.52
+ ,112.60
+ ,96.13
+ ,100.31
+ ,104.24
+ ,102.85
+ ,112.60
+ ,96.13
+ ,100.65
+ ,104.33
+ ,102.85
+ ,112.61
+ ,96.13
+ ,100.65
+ ,104.73
+ ,102.85
+ ,112.61
+ ,96.13
+ ,100.69
+ ,104.86
+ ,103.25
+ ,112.61
+ ,96.13
+ ,101.26
+ ,105.03
+ ,103.25
+ ,112.61
+ ,98.73
+ ,101.26
+ ,105.62
+ ,103.25
+ ,112.61
+ ,98.73
+ ,101.38
+ ,105.63
+ ,103.25
+ ,112.61
+ ,98.73
+ ,101.38
+ ,105.63
+ ,104.45
+ ,112.61
+ ,98.73
+ ,101.38
+ ,105.94
+ ,104.45
+ ,112.61
+ ,98.73
+ ,101.44
+ ,106.61
+ ,104.45
+ ,118.65
+ ,98.73
+ ,101.40
+ ,107.69
+ ,104.80
+ ,118.65
+ ,98.73
+ ,101.40
+ ,107.78
+ ,104.80
+ ,118.65
+ ,98.73
+ ,100.58
+ ,107.93
+ ,105.29
+ ,118.65
+ ,98.73
+ ,100.58
+ ,108.48
+ ,105.29
+ ,114.29
+ ,98.73
+ ,100.58
+ ,108.14
+ ,105.29
+ ,114.29
+ ,98.73
+ ,100.59
+ ,108.48
+ ,105.29
+ ,114.29
+ ,98.73
+ ,100.81
+ ,108.48
+ ,106.04
+ ,114.29
+ ,101.67
+ ,100.75
+ ,108.89
+ ,105.94
+ ,114.29
+ ,101.67
+ ,100.75
+ ,108.93
+ ,105.94
+ ,114.29
+ ,101.67
+ ,100.96
+ ,109.21
+ ,105.94
+ ,114.29
+ ,101.67
+ ,101.31
+ ,109.47
+ ,106.28
+ ,114.29
+ ,101.67
+ ,101.64
+ ,109.80
+ ,106.48
+ ,123.33
+ ,101.67
+ ,101.46
+ ,111.73
+ ,107.19
+ ,123.33
+ ,101.67
+ ,101.73
+ ,111.85
+ ,108.14
+ ,123.33
+ ,101.67
+ ,101.73
+ ,112.12
+ ,108.22
+ ,123.33
+ ,101.67
+ ,101.64
+ ,112.15
+ ,108.22
+ ,123.33
+ ,101.67
+ ,101.77
+ ,112.17
+ ,108.61
+ ,123.33
+ ,101.67
+ ,101.74
+ ,112.67
+ ,108.61
+ ,123.33
+ ,101.67
+ ,101.89
+ ,112.80
+ ,108.61
+ ,123.33
+ ,107.94
+ ,101.89
+ ,113.44
+ ,108.61
+ ,123.33
+ ,107.94
+ ,101.93
+ ,113.53
+ ,109.06
+ ,123.33
+ ,107.94
+ ,101.93
+ ,114.53
+ ,109.06
+ ,123.33
+ ,107.94
+ ,102.32
+ ,114.51
+ ,112.93
+ ,123.33
+ ,107.94
+ ,102.41
+ ,115.05
+ ,115.84
+ ,129.03
+ ,107.94
+ ,103.58
+ ,116.67
+ ,118.57
+ ,128.76
+ ,107.94
+ ,104.12
+ ,117.07
+ ,118.57
+ ,128.76
+ ,107.94
+ ,104.10
+ ,116.92
+ ,118.86
+ ,128.76
+ ,107.94
+ ,104.15
+ ,117.00
+ ,118.98
+ ,128.76
+ ,107.94
+ ,104.15
+ ,117.02
+ ,119.27
+ ,128.76
+ ,107.94
+ ,104.16
+ ,117.35
+ ,119.39
+ ,128.76
+ ,107.94
+ ,102.94
+ ,117.36
+ ,119.49
+ ,128.76
+ ,110.30
+ ,103.07
+ ,117.82
+ ,119.59
+ ,128.76
+ ,110.30
+ ,103.04
+ ,117.88
+ ,120.12
+ ,128.76
+ ,110.30
+ ,103.06
+ ,118.24
+ ,120.14
+ ,128.76
+ ,110.30
+ ,103.05
+ ,118.50
+ ,120.14
+ ,128.76
+ ,110.30
+ ,102.95
+ ,118.80
+ ,120.14
+ ,132.63
+ ,110.30
+ ,102.95
+ ,119.76
+ ,120.14
+ ,132.63
+ ,110.30
+ ,103.05
+ ,120.09)
+ ,dim=c(5
+ ,58)
+ ,dimnames=list(c('bios'
+ ,'schouwburg'
+ ,'eedagsacttractie'
+ ,'huurDVD'
+ ,'vrijetijdsbesteding')
+ ,1:58))
>  y <- array(NA,dim=c(5,58),dimnames=list(c('bios','schouwburg','eedagsacttractie','huurDVD','vrijetijdsbesteding'),1:58))
>  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 = '5'
> #'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] "vrijetijdsbesteding"
> x[,par1]
 [1] 101.76 102.37 102.38 102.86 102.87 102.92 102.95 103.02 104.08 104.16
[11] 104.24 104.33 104.73 104.86 105.03 105.62 105.63 105.63 105.94 106.61
[21] 107.69 107.78 107.93 108.48 108.14 108.48 108.48 108.89 108.93 109.21
[31] 109.47 109.80 111.73 111.85 112.12 112.15 112.17 112.67 112.80 113.44
[41] 113.53 114.53 114.51 115.05 116.67 117.07 116.92 117.00 117.02 117.35
[51] 117.36 117.82 117.88 118.24 118.50 118.80 119.76 120.09
> 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])

[102,109) [109,120] 
       29        29 
> colnames(x)
[1] "bios"                "schouwburg"          "eedagsacttractie"   
[4] "huurDVD"             "vrijetijdsbesteding"
> colnames(x)[par1]
[1] "vrijetijdsbesteding"
> x[,par1]
 [1] [102,109) [102,109) [102,109) [102,109) [102,109) [102,109) [102,109)
 [8] [102,109) [102,109) [102,109) [102,109) [102,109) [102,109) [102,109)
[15] [102,109) [102,109) [102,109) [102,109) [102,109) [102,109) [102,109)
[22] [102,109) [102,109) [102,109) [102,109) [102,109) [102,109) [102,109)
[29] [102,109) [109,120] [109,120] [109,120] [109,120] [109,120] [109,120]
[36] [109,120] [109,120] [109,120] [109,120] [109,120] [109,120] [109,120]
[43] [109,120] [109,120] [109,120] [109,120] [109,120] [109,120] [109,120]
[50] [109,120] [109,120] [109,120] [109,120] [109,120] [109,120] [109,120]
[57] [109,120] [109,120]
Levels: [102,109) [109,120]
> 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/1q9za1291974388.tab") 
+ }
+ }
> m

	 Conditional inference tree with 3 terminal nodes

Response:  as.factor(vrijetijdsbesteding) 
Inputs:  bios, schouwburg, eedagsacttractie, huurDVD 
Number of observations:  58 

1) eedagsacttractie <= 98.73; criterion = 1, statistic = 40.557
  2)*  weights = 27 
1) eedagsacttractie > 98.73
  3) schouwburg <= 123.33; criterion = 0.977, statistic = 7.636
    4)*  weights = 17 
  3) schouwburg > 123.33
    5)*  weights = 14 
> postscript(file="/var/www/html/rcomp/tmp/2jizd1291974388.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/3jizd1291974388.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,]    1    1
 [2,]    1    1
 [3,]    1    1
 [4,]    1    1
 [5,]    1    1
 [6,]    1    1
 [7,]    1    1
 [8,]    1    1
 [9,]    1    1
[10,]    1    1
[11,]    1    1
[12,]    1    1
[13,]    1    1
[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    2
[29,]    1    2
[30,]    2    2
[31,]    2    2
[32,]    2    2
[33,]    2    2
[34,]    2    2
[35,]    2    2
[36,]    2    2
[37,]    2    2
[38,]    2    2
[39,]    2    2
[40,]    2    2
[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,]    2    2
           
            [102,109) [109,120]
  [102,109)        27         2
  [109,120]         0        29
> postscript(file="/var/www/html/rcomp/tmp/4t9yy1291974388.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/5xae41291974388.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/6iavs1291974388.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/7tkuv1291974388.tab") 
+ }
> 
> try(system("convert tmp/2jizd1291974388.ps tmp/2jizd1291974388.png",intern=TRUE))
character(0)
> try(system("convert tmp/3jizd1291974388.ps tmp/3jizd1291974388.png",intern=TRUE))
character(0)
> try(system("convert tmp/4t9yy1291974388.ps tmp/4t9yy1291974388.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  2.053   0.505   4.468