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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You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.

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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(12008.00
+ ,4.00
+ ,9169.00
+ ,5.90
+ ,8788.00
+ ,7.10
+ ,8417.00
+ ,10.50
+ ,8247.00
+ ,15.10
+ ,8197.00
+ ,16.80
+ ,8236.00
+ ,15.30
+ ,8253.00
+ ,18.40
+ ,7733.00
+ ,16.10
+ ,8366.00
+ ,11.30
+ ,8626.00
+ ,7.90
+ ,8863.00
+ ,5.60
+ ,10102.00
+ ,3.40
+ ,8463.00
+ ,4.80
+ ,9114.00
+ ,6.50
+ ,8563.00
+ ,8.50
+ ,8872.00
+ ,15.10
+ ,8301.00
+ ,15.70
+ ,8301.00
+ ,18.70
+ ,8278.00
+ ,19.20
+ ,7736.00
+ ,12.90
+ ,7973.00
+ ,14.40
+ ,8268.00
+ ,6.20
+ ,9476.00
+ ,3.30
+ ,11100.00
+ ,4.60
+ ,8962.00
+ ,7.10
+ ,9173.00
+ ,7.80
+ ,8738.00
+ ,9.90
+ ,8459.00
+ ,13.60
+ ,8078.00
+ ,17.10
+ ,8411.00
+ ,17.80
+ ,8291.00
+ ,18.60
+ ,7810.00
+ ,14.70
+ ,8616.00
+ ,10.50
+ ,8312.00
+ ,8.60
+ ,9692.00
+ ,4.40
+ ,9911.00
+ ,2.30
+ ,8915.00
+ ,2.80
+ ,9452.00
+ ,8.80
+ ,9112.00
+ ,10.70
+ ,8472.00
+ ,13.90
+ ,8230.00
+ ,19.30
+ ,8384.00
+ ,19.50
+ ,8625.00
+ ,20.40
+ ,8221.00
+ ,15.30
+ ,8649.00
+ ,7.90
+ ,8625.00
+ ,8.30
+ ,10443.00
+ ,4.50
+ ,10357.00
+ ,3.20
+ ,8586.00
+ ,5.00
+ ,8892.00
+ ,6.60
+ ,8329.00
+ ,11.10
+ ,8101.00
+ ,12.80
+ ,7922.00
+ ,16.30
+ ,8120.00
+ ,17.40
+ ,7838.00
+ ,18.90
+ ,7735.00
+ ,15.80
+ ,8406.00
+ ,11.70
+ ,8209.00
+ ,6.40
+ ,9451.00
+ ,2.90
+ ,10041.00
+ ,4.70
+ ,9411.00
+ ,2.40
+ ,10405.00
+ ,7.20
+ ,8467.00
+ ,10.70
+ ,8464.00
+ ,13.40
+ ,8102.00
+ ,18.30
+ ,7627.00
+ ,18.40
+ ,7513.00
+ ,16.80
+ ,7510.00
+ ,16.60
+ ,8291.00
+ ,14.10
+ ,8064.00
+ ,6.10
+ ,9383.00
+ ,3.50
+ ,9706.00
+ ,1.70
+ ,8579.00
+ ,2.30
+ ,9474.00
+ ,4.50
+ ,8318.00
+ ,9.30
+ ,8213.00
+ ,14.20
+ ,8059.00
+ ,17.30
+ ,9111.00
+ ,23.00
+ ,7708.00
+ ,16.30
+ ,7680.00
+ ,18.40
+ ,8014.00
+ ,14.20
+ ,8007.00
+ ,9.10
+ ,8718.00
+ ,5.90
+ ,9486.00
+ ,7.20
+ ,9113.00
+ ,6.80
+ ,9025.00
+ ,8.00
+ ,8476.00
+ ,14.30
+ ,7952.00
+ ,14.60
+ ,7759.00
+ ,17.50
+ ,7835.00
+ ,17.20
+ ,7600.00
+ ,17.20
+ ,7651.00
+ ,14.10
+ ,8319.00
+ ,10.40
+ ,8812.00
+ ,6.80
+ ,8630.00
+ ,4.10)
+ ,dim=c(2
+ ,96)
+ ,dimnames=list(c('Sterftecijfers'
+ ,'Temperatuur')
+ ,1:96))
>  y <- array(NA,dim=c(2,96),dimnames=list(c('Sterftecijfers','Temperatuur'),1:96))
>  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 = '4'
> 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

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] "Sterftecijfers"
> x[,par1]
 [1] 12008  9169  8788  8417  8247  8197  8236  8253  7733  8366  8626  8863
[13] 10102  8463  9114  8563  8872  8301  8301  8278  7736  7973  8268  9476
[25] 11100  8962  9173  8738  8459  8078  8411  8291  7810  8616  8312  9692
[37]  9911  8915  9452  9112  8472  8230  8384  8625  8221  8649  8625 10443
[49] 10357  8586  8892  8329  8101  7922  8120  7838  7735  8406  8209  9451
[61] 10041  9411 10405  8467  8464  8102  7627  7513  7510  8291  8064  9383
[73]  9706  8579  9474  8318  8213  8059  9111  7708  7680  8014  8007  8718
[85]  9486  9113  9025  8476  7952  7759  7835  7600  7651  8319  8812  8630
> 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])

[7510, 8120) [8120, 8459) [8459, 9025) [9025,12008] 
          24           24           24           24 
> colnames(x)
[1] "Sterftecijfers" "Temperatuur"   
> colnames(x)[par1]
[1] "Sterftecijfers"
> x[,par1]
 [1] [9025,12008] [9025,12008] [8459, 9025) [8120, 8459) [8120, 8459)
 [6] [8120, 8459) [8120, 8459) [8120, 8459) [7510, 8120) [8120, 8459)
[11] [8459, 9025) [8459, 9025) [9025,12008] [8459, 9025) [9025,12008]
[16] [8459, 9025) [8459, 9025) [8120, 8459) [8120, 8459) [8120, 8459)
[21] [7510, 8120) [7510, 8120) [8120, 8459) [9025,12008] [9025,12008]
[26] [8459, 9025) [9025,12008] [8459, 9025) [8459, 9025) [7510, 8120)
[31] [8120, 8459) [8120, 8459) [7510, 8120) [8459, 9025) [8120, 8459)
[36] [9025,12008] [9025,12008] [8459, 9025) [9025,12008] [9025,12008]
[41] [8459, 9025) [8120, 8459) [8120, 8459) [8459, 9025) [8120, 8459)
[46] [8459, 9025) [8459, 9025) [9025,12008] [9025,12008] [8459, 9025)
[51] [8459, 9025) [8120, 8459) [7510, 8120) [7510, 8120) [8120, 8459)
[56] [7510, 8120) [7510, 8120) [8120, 8459) [8120, 8459) [9025,12008]
[61] [9025,12008] [9025,12008] [9025,12008] [8459, 9025) [8459, 9025)
[66] [7510, 8120) [7510, 8120) [7510, 8120) [7510, 8120) [8120, 8459)
[71] [7510, 8120) [9025,12008] [9025,12008] [8459, 9025) [9025,12008]
[76] [8120, 8459) [8120, 8459) [7510, 8120) [9025,12008] [7510, 8120)
[81] [7510, 8120) [7510, 8120) [7510, 8120) [8459, 9025) [9025,12008]
[86] [9025,12008] [9025,12008] [8459, 9025) [7510, 8120) [7510, 8120)
[91] [7510, 8120) [7510, 8120) [7510, 8120) [8120, 8459) [8459, 9025)
[96] [8459, 9025)
Levels: [7510, 8120) [8120, 8459) [8459, 9025) [9025,12008]
> 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/1j4wk1292187334.tab") 
+ }
+ }
           m.ct.i.pred
m.ct.i.actu   1   2   3   4
          1 182  12  15   1
          2 110  49  48   6
          3  49  14 109  46
          4   4   8  63 143
[1] 0.8666667
[1] 0.2300469
[1] 0.5
[1] 0.6559633
[1] 0.5622817
           m.ct.x.pred
m.ct.x.actu  1  2  3  4
          1 25  2  2  1
          2 15  1 11  0
          3  4  2  8  8
          4  1  1  8 12
[1] 0.8333333
[1] 0.03703704
[1] 0.3636364
[1] 0.5454545
[1] 0.4554455
> m

	 Conditional inference tree with 5 terminal nodes

Response:  as.factor(Sterftecijfers) 
Input:  Temperatuur 
Number of observations:  96 

1) Temperatuur <= 4.7; criterion = 1, statistic = 47.098
  2)*  weights = 17 
1) Temperatuur > 4.7
  3) Temperatuur <= 11.7; criterion = 1, statistic = 24.993
    4)*  weights = 35 
  3) Temperatuur > 11.7
    5) Temperatuur <= 14.3; criterion = 0.993, statistic = 12.082
      6)*  weights = 10 
    5) Temperatuur > 14.3
      7) Temperatuur <= 18.4; criterion = 0.988, statistic = 10.97
        8)*  weights = 26 
      7) Temperatuur > 18.4
        9)*  weights = 8 
> postscript(file="/var/www/html/rcomp/tmp/2cvvn1292187334.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/3cvvn1292187334.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,]    4    4
 [2,]    4    3
 [3,]    3    3
 [4,]    2    3
 [5,]    2    1
 [6,]    2    1
 [7,]    2    1
 [8,]    2    1
 [9,]    1    1
[10,]    2    3
[11,]    3    3
[12,]    3    3
[13,]    4    4
[14,]    3    3
[15,]    4    3
[16,]    3    3
[17,]    3    1
[18,]    2    1
[19,]    2    2
[20,]    2    2
[21,]    1    1
[22,]    1    1
[23,]    2    3
[24,]    4    4
[25,]    4    4
[26,]    3    3
[27,]    4    3
[28,]    3    3
[29,]    3    1
[30,]    1    1
[31,]    2    1
[32,]    2    2
[33,]    1    1
[34,]    3    3
[35,]    2    3
[36,]    4    4
[37,]    4    4
[38,]    3    4
[39,]    4    3
[40,]    4    3
[41,]    3    1
[42,]    2    2
[43,]    2    2
[44,]    3    2
[45,]    2    1
[46,]    3    3
[47,]    3    3
[48,]    4    4
[49,]    4    4
[50,]    3    3
[51,]    3    3
[52,]    2    3
[53,]    1    1
[54,]    1    1
[55,]    2    1
[56,]    1    2
[57,]    1    1
[58,]    2    3
[59,]    2    3
[60,]    4    4
[61,]    4    4
[62,]    4    4
[63,]    4    3
[64,]    3    3
[65,]    3    1
[66,]    1    1
[67,]    1    1
[68,]    1    1
[69,]    1    1
[70,]    2    1
[71,]    1    3
[72,]    4    4
[73,]    4    4
[74,]    3    4
[75,]    4    4
[76,]    2    3
[77,]    2    1
[78,]    1    1
[79,]    4    2
[80,]    1    1
[81,]    1    1
[82,]    1    1
[83,]    1    3
[84,]    3    3
[85,]    4    3
[86,]    4    3
[87,]    4    3
[88,]    3    1
[89,]    1    1
[90,]    1    1
[91,]    1    1
[92,]    1    1
[93,]    1    1
[94,]    2    3
[95,]    3    3
[96,]    3    4
              
               [7510, 8120) [8120, 8459) [8459, 9025) [9025,12008]
  [7510, 8120)           21            1            2            0
  [8120, 8459)           10            5            9            0
  [8459, 9025)            5            1           15            3
  [9025,12008]            0            1            9           14
> postscript(file="/var/www/html/rcomp/tmp/45nd81292187334.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/5qnte1292187334.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/6u6sk1292187334.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/7x6871292187334.tab") 
+ }
> 
> try(system("convert tmp/2cvvn1292187334.ps tmp/2cvvn1292187334.png",intern=TRUE))
character(0)
> try(system("convert tmp/3cvvn1292187334.ps tmp/3cvvn1292187334.png",intern=TRUE))
character(0)
> try(system("convert tmp/45nd81292187334.ps tmp/45nd81292187334.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  2.562   0.489   5.385