R version 2.12.0 (2010-10-15)
Copyright (C) 2010 The R Foundation for Statistical Computing
ISBN 3-900051-07-0
Platform: i486-pc-linux-gnu (32-bit)

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> x <- array(list(2649.2,31077,2579.4,31293,2504.6,30236,2462.3,30160,2467.4,32436,2446.7,30695,2656.3,27525,2626.2,26434,2482.6,25739,2539.9,25204,2502.7,24977,2466.9,24320,2513.2,22680,2443.3,22052,2293.4,21467,2070.8,21383,2029.6,21777,2052,21928,1864.4,21814,1670.1,22937,1811,23595,1905.4,20830,1862.8,19650,2014.5,19195,2197.8,19644,2962.3,18483,3047,18079,3032.6,19178,3504.4,18391,3801.1,18441,3857.6,18584,3674.4,20108,3721,20148,3844.5,19394,4116.7,17745,4105.2,17696,4435.2,17032,4296.5,16438,4202.5,15683,4562.8,15594,4621.4,15713,4697,15937,4591.3,16171,4357,15928,4502.6,16348,4443.9,15579,4290.9,15305,4199.8,15648,4138.5,14954,3970.1,15137,3862.3,15839,3701.6,16050,3570.12,15168,3801.06,17064,3895.51,16005,3917.96,14886,3813.06,14931,3667.03,14544,3494.17,13812,3364,13031,3295.3,12574,3277.0,11964,3257.2,11451,3161.7,11346,3097.3,11353,3061.3,10702,3119.3,10646,3106.22,10556,3080.58,10463,2981.85,10407),dim=c(2,70),dimnames=list(c('Bel20','Goudprijs'),1:70))
>  y <- array(NA,dim=c(2,70),dimnames=list(c('Bel20','Goudprijs'),1:70))
>  for (i in 1:dim(x)[1])
+  {
+  	for (j in 1:dim(x)[2])
+  	{
+  		y[i,j] <- as.numeric(x[i,j])
+  	}
+  }
> par4 = 'yes'
> par3 = '2'
> par2 = 'quantiles'
> par1 = '1'
> #'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] "Bel20"
> x[,par1]
 [1] 2649.20 2579.40 2504.60 2462.30 2467.40 2446.70 2656.30 2626.20 2482.60
[10] 2539.90 2502.70 2466.90 2513.20 2443.30 2293.40 2070.80 2029.60 2052.00
[19] 1864.40 1670.10 1811.00 1905.40 1862.80 2014.50 2197.80 2962.30 3047.00
[28] 3032.60 3504.40 3801.10 3857.60 3674.40 3721.00 3844.50 4116.70 4105.20
[37] 4435.20 4296.50 4202.50 4562.80 4621.40 4697.00 4591.30 4357.00 4502.60
[46] 4443.90 4290.90 4199.80 4138.50 3970.10 3862.30 3701.60 3570.12 3801.06
[55] 3895.51 3917.96 3813.06 3667.03 3494.17 3364.00 3295.30 3277.00 3257.20
[64] 3161.70 3097.30 3061.30 3119.30 3106.22 3080.58 2981.85
> 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])

[1670,3257) [3257,4697] 
         35          35 
> colnames(x)
[1] "Bel20"     "Goudprijs"
> colnames(x)[par1]
[1] "Bel20"
> x[,par1]
 [1] [1670,3257) [1670,3257) [1670,3257) [1670,3257) [1670,3257) [1670,3257)
 [7] [1670,3257) [1670,3257) [1670,3257) [1670,3257) [1670,3257) [1670,3257)
[13] [1670,3257) [1670,3257) [1670,3257) [1670,3257) [1670,3257) [1670,3257)
[19] [1670,3257) [1670,3257) [1670,3257) [1670,3257) [1670,3257) [1670,3257)
[25] [1670,3257) [1670,3257) [1670,3257) [1670,3257) [3257,4697] [3257,4697]
[31] [3257,4697] [3257,4697] [3257,4697] [3257,4697] [3257,4697] [3257,4697]
[37] [3257,4697] [3257,4697] [3257,4697] [3257,4697] [3257,4697] [3257,4697]
[43] [3257,4697] [3257,4697] [3257,4697] [3257,4697] [3257,4697] [3257,4697]
[49] [3257,4697] [3257,4697] [3257,4697] [3257,4697] [3257,4697] [3257,4697]
[55] [3257,4697] [3257,4697] [3257,4697] [3257,4697] [3257,4697] [3257,4697]
[61] [3257,4697] [3257,4697] [3257,4697] [1670,3257) [1670,3257) [1670,3257)
[67] [1670,3257) [1670,3257) [1670,3257) [1670,3257)
Levels: [1670,3257) [3257,4697]
> if (par2 == 'none') {
+ m <- ctree(as.formula(paste(colnames(x)[par1],' ~ .',sep='')),data = x)
+ }
> 
> #Note: the /var/www/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/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/rcomp/tmp/19xwj1292274358.tab") 
+ }
+ }
           m.ct.i.pred
m.ct.i.actu   1   2
          1 250  66
          2   6 310
[1] 0.7911392
[1] 0.9810127
[1] 0.886076
           m.ct.x.pred
m.ct.x.actu  1  2
          1 22 12
          2  4 30
[1] 0.6470588
[1] 0.882353
[1] 0.7647059
> m

	 Conditional inference tree with 2 terminal nodes

Response:  as.factor(Bel20) 
Input:  Goudprijs 
Number of observations:  70 

1) Goudprijs <= 20148; criterion = 1, statistic = 16.553
  2)*  weights = 48 
1) Goudprijs > 20148
  3)*  weights = 22 
> postscript(file="/var/www/rcomp/tmp/29xwj1292274358.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/rcomp/tmp/39xwj1292274358.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    2
[24,]    1    2
[25,]    1    2
[26,]    1    2
[27,]    1    2
[28,]    1    2
[29,]    2    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
[59,]    2    2
[60,]    2    2
[61,]    2    2
[62,]    2    2
[63,]    2    2
[64,]    1    2
[65,]    1    2
[66,]    1    2
[67,]    1    2
[68,]    1    2
[69,]    1    2
[70,]    1    2
             
              [1670,3257) [3257,4697]
  [1670,3257)          22          13
  [3257,4697]           0          35
> postscript(file="/var/www/rcomp/tmp/4uxc71292274358.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/rcomp/tmp/5n6ts1292274358.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/rcomp/tmp/69pay1292274358.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/rcomp/tmp/7jyrj1292274358.tab") 
+ }
> 
> try(system("convert tmp/29xwj1292274358.ps tmp/29xwj1292274358.png",intern=TRUE))
character(0)
> try(system("convert tmp/39xwj1292274358.ps tmp/39xwj1292274358.png",intern=TRUE))
character(0)
> try(system("convert tmp/4uxc71292274358.ps tmp/4uxc71292274358.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
   2.15    0.71    2.83