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)

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(210907
+ ,79
+ ,30
+ ,94
+ ,112285
+ ,144
+ ,145
+ ,120982
+ ,58
+ ,28
+ ,103
+ ,84786
+ ,103
+ ,101
+ ,176508
+ ,60
+ ,38
+ ,93
+ ,83123
+ ,98
+ ,98
+ ,179321
+ ,108
+ ,30
+ ,103
+ ,101193
+ ,135
+ ,132
+ ,123185
+ ,49
+ ,22
+ ,51
+ ,38361
+ ,61
+ ,60
+ ,52746
+ ,0
+ ,26
+ ,70
+ ,68504
+ ,39
+ ,38
+ ,385534
+ ,121
+ ,25
+ ,91
+ ,119182
+ ,150
+ ,144
+ ,33170
+ ,1
+ ,18
+ ,22
+ ,22807
+ ,5
+ ,5
+ ,101645
+ ,20
+ ,11
+ ,38
+ ,17140
+ ,28
+ ,28
+ ,149061
+ ,43
+ ,26
+ ,93
+ ,116174
+ ,84
+ ,84
+ ,165446
+ ,69
+ ,25
+ ,60
+ ,57635
+ ,80
+ ,79
+ ,237213
+ ,78
+ ,38
+ ,123
+ ,66198
+ ,130
+ ,127
+ ,173326
+ ,86
+ ,44
+ ,148
+ ,71701
+ ,82
+ ,78
+ ,133131
+ ,44
+ ,30
+ ,90
+ ,57793
+ ,60
+ ,60
+ ,258873
+ ,104
+ ,40
+ ,124
+ ,80444
+ ,131
+ ,131
+ ,180083
+ ,63
+ ,34
+ ,70
+ ,53855
+ ,84
+ ,84
+ ,324799
+ ,158
+ ,47
+ ,168
+ ,97668
+ ,140
+ ,133
+ ,230964
+ ,102
+ ,30
+ ,115
+ ,133824
+ ,151
+ ,150
+ ,236785
+ ,77
+ ,31
+ ,71
+ ,101481
+ ,91
+ ,91
+ ,135473
+ ,82
+ ,23
+ ,66
+ ,99645
+ ,138
+ ,132
+ ,202925
+ ,115
+ ,36
+ ,134
+ ,114789
+ ,150
+ ,136
+ ,215147
+ ,101
+ ,36
+ ,117
+ ,99052
+ ,124
+ ,124
+ ,344297
+ ,80
+ ,30
+ ,108
+ ,67654
+ ,119
+ ,118
+ ,153935
+ ,50
+ ,25
+ ,84
+ ,65553
+ ,73
+ ,70
+ ,132943
+ ,83
+ ,39
+ ,156
+ ,97500
+ ,110
+ ,107
+ ,174724
+ ,123
+ ,34
+ ,120
+ ,69112
+ ,123
+ ,119
+ ,174415
+ ,73
+ ,31
+ ,114
+ ,82753
+ ,90
+ ,89
+ ,225548
+ ,81
+ ,31
+ ,94
+ ,85323
+ ,116
+ ,112
+ ,223632
+ ,105
+ ,33
+ ,120
+ ,72654
+ ,113
+ ,108
+ ,124817
+ ,47
+ ,25
+ ,81
+ ,30727
+ ,56
+ ,52
+ ,221698
+ ,105
+ ,33
+ ,110
+ ,77873
+ ,115
+ ,112
+ ,210767
+ ,94
+ ,35
+ ,133
+ ,117478
+ ,119
+ ,116
+ ,170266
+ ,44
+ ,42
+ ,122
+ ,74007
+ ,129
+ ,123
+ ,260561
+ ,114
+ ,43
+ ,158
+ ,90183
+ ,127
+ ,125
+ ,84853
+ ,38
+ ,30
+ ,109
+ ,61542
+ ,27
+ ,27
+ ,294424
+ ,107
+ ,33
+ ,124
+ ,101494
+ ,175
+ ,162
+ ,101011
+ ,30
+ ,13
+ ,39
+ ,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 = '6'
> 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] "X5"
> x[,par1]
 [1] 144 103  98 135  61  39 150   5  28  84  80 130  82  60 131  84 140 151  91
[20] 138 150 124 119  73 110 123  90 116 113  56 115 119 129 127  27 175  35  64
[39]  96   0  84  41  47 126 105  80  70  73
> 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])

  0   5  27  28  35  39  41  47  56  60  61  64  70  73  80  82  84  90  91  96 
  1   1   1   1   1   1   1   1   1   1   1   1   1   2   2   1   3   1   1   1 
 98 103 105 110 113 115 116 119 123 124 126 127 129 130 131 135 138 140 144 150 
  1   1   1   1   1   1   1   2   1   1   1   1   1   1   1   1   1   1   1   2 
151 175 
  1   1 
> colnames(x)
[1] "Y"  "X1" "X2" "X3" "X4" "X5" "X6"
> colnames(x)[par1]
[1] "X5"
> x[,par1]
 [1] 144 103  98 135  61  39 150   5  28  84  80 130  82  60 131  84 140 151  91
[20] 138 150 124 119  73 110 123  90 116 113  56 115 119 129 127  27 175  35  64
[39]  96   0  84  41  47 126 105  80  70  73
> 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/1y8et1324630543.tab") 
+ }
+ }
> m

	 Conditional inference tree with 4 terminal nodes

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

1) X6 <= 91; criterion = 1, statistic = 46.788
  2) X6 <= 47; criterion = 1, statistic = 21.924
    3)*  weights = 8 
  2) X6 > 47
    4)*  weights = 15 
1) X6 > 91
  5) X6 <= 131; criterion = 1, statistic = 23.201
    6)*  weights = 17 
  5) X6 > 131
    7)*  weights = 8 
> postscript(file="/var/www/rcomp/tmp/2ph0u1324630543.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/31rag1324630543.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      144 147.87500  -3.8750000
2      103 116.70588 -13.7058824
3       98 116.70588 -18.7058824
4      135 147.87500 -12.8750000
5       61  75.46667 -14.4666667
6       39  27.75000  11.2500000
7      150 147.87500   2.1250000
8        5  27.75000 -22.7500000
9       28  27.75000   0.2500000
10      84  75.46667   8.5333333
11      80  75.46667   4.5333333
12     130 116.70588  13.2941176
13      82  75.46667   6.5333333
14      60  75.46667 -15.4666667
15     131 116.70588  14.2941176
16      84  75.46667   8.5333333
17     140 147.87500  -7.8750000
18     151 147.87500   3.1250000
19      91  75.46667  15.5333333
20     138 147.87500  -9.8750000
21     150 147.87500   2.1250000
22     124 116.70588   7.2941176
23     119 116.70588   2.2941176
24      73  75.46667  -2.4666667
25     110 116.70588  -6.7058824
26     123 116.70588   6.2941176
27      90  75.46667  14.5333333
28     116 116.70588  -0.7058824
29     113 116.70588  -3.7058824
30      56  75.46667 -19.4666667
31     115 116.70588  -1.7058824
32     119 116.70588   2.2941176
33     129 116.70588  12.2941176
34     127 116.70588  10.2941176
35      27  27.75000  -0.7500000
36     175 147.87500  27.1250000
37      35  27.75000   7.2500000
38      64  75.46667 -11.4666667
39      96 116.70588 -20.7058824
40       0  27.75000 -27.7500000
41      84  75.46667   8.5333333
42      41  27.75000  13.2500000
43      47  27.75000  19.2500000
44     126 116.70588   9.2941176
45     105 116.70588 -11.7058824
46      80  75.46667   4.5333333
47      70  75.46667  -5.4666667
48      73  75.46667  -2.4666667
> 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/rcomp/tmp/4ywuk1324630543.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/5zwpb1324630543.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/6s6vn1324630543.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/7e9t51324630543.tab") 
+ }
> 
> try(system("convert tmp/2ph0u1324630543.ps tmp/2ph0u1324630543.png",intern=TRUE))
character(0)
> try(system("convert tmp/31rag1324630543.ps tmp/31rag1324630543.png",intern=TRUE))
character(0)
> try(system("convert tmp/4ywuk1324630543.ps tmp/4ywuk1324630543.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  2.100   0.140   2.225