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 'license()' or 'licence()' for distribution details.

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Type 'demo()' for some demos, 'help()' for on-line help, or
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> x <- array(list(3.18
+ ,0.22
+ ,6.62
+ ,3.64
+ ,3.14
+ ,0.22
+ ,6.56
+ ,3.62
+ ,3.02
+ ,0.23
+ ,6.59
+ ,3.61
+ ,3.02
+ ,0.24
+ ,6.56
+ ,3.6
+ ,3.03
+ ,0.25
+ ,6.57
+ ,3.6
+ ,3.04
+ ,0.25
+ ,6.62
+ ,3.63
+ ,3.09
+ ,0.24
+ ,6.69
+ ,3.59
+ ,3.06
+ ,0.24
+ ,6.69
+ ,3.55
+ ,3.06
+ ,0.22
+ ,6.64
+ ,3.54
+ ,3.09
+ ,0.21
+ ,6.6
+ ,3.53
+ ,3.11
+ ,0.21
+ ,6.66
+ ,3.53
+ ,3.1
+ ,0.21
+ ,6.62
+ ,3.53
+ ,3.09
+ ,0.2
+ ,6.64
+ ,3.52
+ ,3.19
+ ,0.2
+ ,6.64
+ ,3.52
+ ,3.22
+ ,0.2
+ ,6.73
+ ,3.48
+ ,3.22
+ ,0.2
+ ,6.73
+ ,3.49
+ ,3.25
+ ,0.2
+ ,6.69
+ ,3.47
+ ,3.25
+ ,0.2
+ ,6.78
+ ,3.46
+ ,3.27
+ ,0.2
+ ,6.77
+ ,3.4
+ ,3.28
+ ,0.2
+ ,6.8
+ ,3.36
+ ,3.24
+ ,0.2
+ ,6.8
+ ,3.3
+ ,3.23
+ ,0.2
+ ,6.74
+ ,3.28
+ ,3.2
+ ,0.2
+ ,6.84
+ ,3.28
+ ,3.19
+ ,0.2
+ ,6.83
+ ,3.24
+ ,3.23
+ ,0.2
+ ,6.89
+ ,3.23
+ ,3.19
+ ,0.2
+ ,6.9
+ ,3.2
+ ,3.16
+ ,0.2
+ ,6.86
+ ,3.15
+ ,3.11
+ ,0.2
+ ,6.78
+ ,3.1
+ ,3.11
+ ,0.2
+ ,6.82
+ ,3.07
+ ,3.07
+ ,0.2
+ ,6.81
+ ,3.03
+ ,3.05
+ ,0.21
+ ,6.81
+ ,2.96
+ ,3
+ ,0.2
+ ,6.78
+ ,2.88
+ ,2.95
+ ,0.2
+ ,6.79
+ ,2.83
+ ,2.9
+ ,0.19
+ ,6.83
+ ,2.8
+ ,2.88
+ ,0.18
+ ,6.9
+ ,2.8
+ ,2.9
+ ,0.18
+ ,6.79
+ ,2.79
+ ,2.89
+ ,0.17
+ ,6.88
+ ,2.79
+ ,2.89
+ ,0.17
+ ,6.89
+ ,2.78
+ ,2.91
+ ,0.17
+ ,6.91
+ ,2.79
+ ,2.9
+ ,0.17
+ ,6.93
+ ,2.78
+ ,2.9
+ ,0.17
+ ,6.89
+ ,2.78
+ ,2.88
+ ,0.16
+ ,7
+ ,2.74
+ ,2.83
+ ,0.16
+ ,7.01
+ ,2.71
+ ,2.8
+ ,0.16
+ ,7.15
+ ,2.69
+ ,2.77
+ ,0.16
+ ,7.25
+ ,2.68
+ ,2.78
+ ,0.16
+ ,7.33
+ ,2.68
+ ,2.75
+ ,0.16
+ ,7.39
+ ,2.68
+ ,2.74
+ ,0.15
+ ,7.38
+ ,2.69
+ ,2.73
+ ,0.15
+ ,7.38
+ ,2.68
+ ,2.69
+ ,0.15
+ ,7.35
+ ,2.69
+ ,2.67
+ ,0.15
+ ,7.38
+ ,2.68
+ ,2.66
+ ,0.15
+ ,7.34
+ ,2.68
+ ,2.67
+ ,0.16
+ ,7.25
+ ,2.63
+ ,2.65
+ ,0.15
+ ,7.07
+ ,2.58
+ ,2.64
+ ,0.15
+ ,6.73
+ ,2.52
+ ,2.63
+ ,0.15
+ ,6.56
+ ,2.5)
+ ,dim=c(4
+ ,56)
+ ,dimnames=list(c('Mayonaise'
+ ,'Eieren'
+ ,'Olijfolie'
+ ,'Mosterd')
+ ,1:56))
>  y <- array(NA,dim=c(4,56),dimnames=list(c('Mayonaise','Eieren','Olijfolie','Mosterd'),1:56))
>  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 = '0'
> par2 = 'none'
> 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

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] "Mayonaise"
> x[,par1]
 [1] 3.18 3.14 3.02 3.02 3.03 3.04 3.09 3.06 3.06 3.09 3.11 3.10 3.09 3.19 3.22
[16] 3.22 3.25 3.25 3.27 3.28 3.24 3.23 3.20 3.19 3.23 3.19 3.16 3.11 3.11 3.07
[31] 3.05 3.00 2.95 2.90 2.88 2.90 2.89 2.89 2.91 2.90 2.90 2.88 2.83 2.80 2.77
[46] 2.78 2.75 2.74 2.73 2.69 2.67 2.66 2.67 2.65 2.64 2.63
> 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])

2.63 2.64 2.65 2.66 2.67 2.69 2.73 2.74 2.75 2.77 2.78  2.8 2.83 2.88 2.89  2.9 
   1    1    1    1    2    1    1    1    1    1    1    1    1    2    2    4 
2.91 2.95    3 3.02 3.03 3.04 3.05 3.06 3.07 3.09  3.1 3.11 3.14 3.16 3.18 3.19 
   1    1    1    2    1    1    1    2    1    3    1    3    1    1    1    3 
 3.2 3.22 3.23 3.24 3.25 3.27 3.28 
   1    2    2    1    2    1    1 
> colnames(x)
[1] "Mayonaise" "Eieren"    "Olijfolie" "Mosterd"  
> colnames(x)[par1]
[1] "Mayonaise"
> x[,par1]
 [1] 3.18 3.14 3.02 3.02 3.03 3.04 3.09 3.06 3.06 3.09 3.11 3.10 3.09 3.19 3.22
[16] 3.22 3.25 3.25 3.27 3.28 3.24 3.23 3.20 3.19 3.23 3.19 3.16 3.11 3.11 3.07
[31] 3.05 3.00 2.95 2.90 2.88 2.90 2.89 2.89 2.91 2.90 2.90 2.88 2.83 2.80 2.77
[46] 2.78 2.75 2.74 2.73 2.69 2.67 2.66 2.67 2.65 2.64 2.63
> 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/1ejwe1292347258.tab") 
+ }
+ }
> m

	 Conditional inference tree with 4 terminal nodes

Response:  Mayonaise 
Inputs:  Eieren, Olijfolie, Mosterd 
Number of observations:  56 

1) Mosterd <= 2.83; criterion = 1, statistic = 37.696
  2) Mosterd <= 2.69; criterion = 1, statistic = 18.947
    3)*  weights = 13 
  2) Mosterd > 2.69
    4)*  weights = 11 
1) Mosterd > 2.83
  5) Eieren <= 0.2; criterion = 0.999, statistic = 12.174
    6)*  weights = 19 
  5) Eieren > 0.2
    7)*  weights = 13 
> postscript(file="/var/www/html/rcomp/tmp/2oadz1292347258.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/3oadz1292347258.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)
+ }
   Actuals Forecasts    Residuals
1     3.18  3.076154  0.103846154
2     3.14  3.076154  0.063846154
3     3.02  3.076154 -0.056153846
4     3.02  3.076154 -0.056153846
5     3.03  3.076154 -0.046153846
6     3.04  3.076154 -0.036153846
7     3.09  3.076154  0.013846154
8     3.06  3.076154 -0.016153846
9     3.06  3.076154 -0.016153846
10    3.09  3.076154  0.013846154
11    3.11  3.076154  0.033846154
12    3.10  3.076154  0.023846154
13    3.09  3.184211 -0.094210526
14    3.19  3.184211  0.005789474
15    3.22  3.184211  0.035789474
16    3.22  3.184211  0.035789474
17    3.25  3.184211  0.065789474
18    3.25  3.184211  0.065789474
19    3.27  3.184211  0.085789474
20    3.28  3.184211  0.095789474
21    3.24  3.184211  0.055789474
22    3.23  3.184211  0.045789474
23    3.20  3.184211  0.015789474
24    3.19  3.184211  0.005789474
25    3.23  3.184211  0.045789474
26    3.19  3.184211  0.005789474
27    3.16  3.184211 -0.024210526
28    3.11  3.184211 -0.074210526
29    3.11  3.184211 -0.074210526
30    3.07  3.184211 -0.114210526
31    3.05  3.076154 -0.026153846
32    3.00  3.184211 -0.184210526
33    2.95  2.893636  0.056363636
34    2.90  2.893636  0.006363636
35    2.88  2.893636 -0.013636364
36    2.90  2.893636  0.006363636
37    2.89  2.893636 -0.003636364
38    2.89  2.893636 -0.003636364
39    2.91  2.893636  0.016363636
40    2.90  2.893636  0.006363636
41    2.90  2.893636  0.006363636
42    2.88  2.893636 -0.013636364
43    2.83  2.893636 -0.063636364
44    2.80  2.706154  0.093846154
45    2.77  2.706154  0.063846154
46    2.78  2.706154  0.073846154
47    2.75  2.706154  0.043846154
48    2.74  2.706154  0.033846154
49    2.73  2.706154  0.023846154
50    2.69  2.706154 -0.016153846
51    2.67  2.706154 -0.036153846
52    2.66  2.706154 -0.046153846
53    2.67  2.706154 -0.036153846
54    2.65  2.706154 -0.056153846
55    2.64  2.706154 -0.066153846
56    2.63  2.706154 -0.076153846
> if (par2 != 'none') {
+ print(cbind(as.factor(x[,par1]),predict(m)))
+ myt <- table(as.factor(x[,par1]),predict(m))
+ print(myt)
+ }
> postscript(file="/var/www/html/rcomp/tmp/4h1ck1292347258.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/5dbsa1292347258.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/6o2rd1292347258.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/7938j1292347258.tab") 
+ }
> 
> try(system("convert tmp/2oadz1292347258.ps tmp/2oadz1292347258.png",intern=TRUE))
character(0)
> try(system("convert tmp/3oadz1292347258.ps tmp/3oadz1292347258.png",intern=TRUE))
character(0)
> try(system("convert tmp/4h1ck1292347258.ps tmp/4h1ck1292347258.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  2.247   0.570   5.964