R version 2.13.0 (2011-04-13)
Copyright (C) 2011 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(210907
+ ,79
+ ,30
+ ,94
+ ,112285
+ ,144
+ ,145
+ ,120982
+ ,58
+ ,28
+ ,103
+ ,84786
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+ ,101
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+ ,60
+ ,38
+ ,93
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+ ,108
+ ,30
+ ,103
+ ,101193
+ ,135
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+ ,49
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+ ,52746
+ ,0
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+ ,119182
+ ,150
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+ ,33170
+ ,1
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+ ,22807
+ ,5
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+ ,20
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+ ,28
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+ ,149061
+ ,43
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+ ,165446
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+ ,80
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+ ,237213
+ ,78
+ ,38
+ ,123
+ ,66198
+ ,130
+ ,127
+ ,173326
+ ,86
+ ,44
+ ,148
+ ,71701
+ ,82
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+ ,133131
+ ,44
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+ ,60
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+ ,258873
+ ,104
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+ ,180083
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+ ,158
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+ ,102
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+ ,150
+ ,236785
+ ,77
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+ ,91
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+ ,135473
+ ,82
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+ ,344297
+ ,80
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+ ,132943
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+ ,119
+ ,116
+ ,170266
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+ ,74007
+ ,129
+ ,123
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+ ,127
+ ,125
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+ ,109
+ ,61542
+ ,27
+ ,27
+ ,294424
+ ,107
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+ ,101011
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+ ,27570
+ ,35
+ ,32
+ ,215641
+ ,71
+ ,32
+ ,92
+ ,55813
+ ,64
+ ,64
+ ,325107
+ ,84
+ ,36
+ ,126
+ ,79215
+ ,96
+ ,92
+ ,7176
+ ,0
+ ,0
+ ,0
+ ,1423
+ ,0
+ ,0
+ ,167542
+ ,59
+ ,28
+ ,70
+ ,55461
+ ,84
+ ,83
+ ,106408
+ ,33
+ ,14
+ ,37
+ ,31081
+ ,41
+ ,41
+ ,96560
+ ,42
+ ,17
+ ,38
+ ,22996
+ ,47
+ ,47
+ ,265769
+ ,96
+ ,32
+ ,120
+ ,83122
+ ,126
+ ,120
+ ,269651
+ ,106
+ ,30
+ ,93
+ ,70106
+ ,105
+ ,105
+ ,149112
+ ,56
+ ,35
+ ,95
+ ,60578
+ ,80
+ ,79
+ ,175824
+ ,57
+ ,20
+ ,77
+ ,39992
+ ,70
+ ,65
+ ,152871
+ ,59
+ ,28
+ ,90
+ ,79892
+ ,73
+ ,70)
+ ,dim=c(7
+ ,48)
+ ,dimnames=list(c('Y'
+ ,'X1'
+ ,'X2'
+ ,'X3'
+ ,'X4'
+ ,'X5'
+ ,'X6')
+ ,1:48))
>  y <- array(NA,dim=c(7,48),dimnames=list(c('Y','X1','X2','X3','X4','X5','X6'),1:48))
>  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 = '3'
> par2 = 'none'
> par1 = '1'
> 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] "Y"
> x[,par1]
 [1] 210907 120982 176508 179321 123185  52746 385534  33170 101645 149061
[11] 165446 237213 173326 133131 258873 180083 324799 230964 236785 135473
[21] 202925 215147 344297 153935 132943 174724 174415 225548 223632 124817
[31] 221698 210767 170266 260561  84853 294424 101011 215641 325107   7176
[41] 167542 106408  96560 265769 269651 149112 175824 152871
> 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])

  7176  33170  52746  84853  96560 101011 101645 106408 120982 123185 124817 
     1      1      1      1      1      1      1      1      1      1      1 
132943 133131 135473 149061 149112 152871 153935 165446 167542 170266 173326 
     1      1      1      1      1      1      1      1      1      1      1 
174415 174724 175824 176508 179321 180083 202925 210767 210907 215147 215641 
     1      1      1      1      1      1      1      1      1      1      1 
221698 223632 225548 230964 236785 237213 258873 260561 265769 269651 294424 
     1      1      1      1      1      1      1      1      1      1      1 
324799 325107 344297 385534 
     1      1      1      1 
> colnames(x)
[1] "Y"  "X1" "X2" "X3" "X4" "X5" "X6"
> colnames(x)[par1]
[1] "Y"
> x[,par1]
 [1] 210907 120982 176508 179321 123185  52746 385534  33170 101645 149061
[11] 165446 237213 173326 133131 258873 180083 324799 230964 236785 135473
[21] 202925 215147 344297 153935 132943 174724 174415 225548 223632 124817
[31] 221698 210767 170266 260561  84853 294424 101011 215641 325107   7176
[41] 167542 106408  96560 265769 269651 149112 175824 152871
> if (par2 == 'none') {
+ m <- ctree(as.formula(paste(colnames(x)[par1],' ~ .',sep='')),data = x)
+ }
> 
> #Note: the /var/wessaorg/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/wessaorg/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/wessaorg/rcomp/tmp/1ejwz1324631149.tab") 
+ }
+ }
> m

	 Conditional inference tree with 3 terminal nodes

Response:  Y 
Inputs:  X1, X2, X3, X4, X5, X6 
Number of observations:  48 

1) X1 <= 69; criterion = 1, statistic = 30.974
  2) X1 <= 42; criterion = 1, statistic = 17.195
    3)*  weights = 8 
  2) X1 > 42
    4)*  weights = 14 
1) X1 > 69
  5)*  weights = 26 
> postscript(file="/var/wessaorg/rcomp/tmp/2bxc41324631149.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/wessaorg/rcomp/tmp/3khle1324631149.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   210907 235786.31  -24879.3077
2   120982 153054.50  -32072.5000
3   176508 153054.50   23453.5000
4   179321 235786.31  -56465.3077
5   123185 153054.50  -29869.5000
6    52746  72946.12  -20200.1250
7   385534 235786.31  149747.6923
8    33170  72946.12  -39776.1250
9   101645  72946.12   28698.8750
10  149061 153054.50   -3993.5000
11  165446 153054.50   12391.5000
12  237213 235786.31    1426.6923
13  173326 235786.31  -62460.3077
14  133131 153054.50  -19923.5000
15  258873 235786.31   23086.6923
16  180083 153054.50   27028.5000
17  324799 235786.31   89012.6923
18  230964 235786.31   -4822.3077
19  236785 235786.31     998.6923
20  135473 235786.31 -100313.3077
21  202925 235786.31  -32861.3077
22  215147 235786.31  -20639.3077
23  344297 235786.31  108510.6923
24  153935 153054.50     880.5000
25  132943 235786.31 -102843.3077
26  174724 235786.31  -61062.3077
27  174415 235786.31  -61371.3077
28  225548 235786.31  -10238.3077
29  223632 235786.31  -12154.3077
30  124817 153054.50  -28237.5000
31  221698 235786.31  -14088.3077
32  210767 235786.31  -25019.3077
33  170266 153054.50   17211.5000
34  260561 235786.31   24774.6923
35   84853  72946.12   11906.8750
36  294424 235786.31   58637.6923
37  101011  72946.12   28064.8750
38  215641 235786.31  -20145.3077
39  325107 235786.31   89320.6923
40    7176  72946.12  -65770.1250
41  167542 153054.50   14487.5000
42  106408  72946.12   33461.8750
43   96560  72946.12   23613.8750
44  265769 235786.31   29982.6923
45  269651 235786.31   33864.6923
46  149112 153054.50   -3942.5000
47  175824 153054.50   22769.5000
48  152871 153054.50    -183.5000
> if (par2 != 'none') {
+ print(cbind(as.factor(x[,par1]),predict(m)))
+ myt <- table(as.factor(x[,par1]),predict(m))
+ print(myt)
+ }
> postscript(file="/var/wessaorg/rcomp/tmp/46oai1324631149.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/wessaorg/rcomp/tmp/5w5j81324631149.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/wessaorg/rcomp/tmp/6nisu1324631149.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/wessaorg/rcomp/tmp/7i4zo1324631149.tab") 
+ }
> 
> try(system("convert tmp/2bxc41324631149.ps tmp/2bxc41324631149.png",intern=TRUE))
character(0)
> try(system("convert tmp/3khle1324631149.ps tmp/3khle1324631149.png",intern=TRUE))
character(0)
> try(system("convert tmp/46oai1324631149.ps tmp/46oai1324631149.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  2.357   0.215   2.598