R version 2.15.2 (2012-10-26) -- "Trick or Treat"
Copyright (C) 2012 The R Foundation for Statistical Computing
ISBN 3-900051-07-0
Platform: i686-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(6.8
+ ,225
+ ,0.442
+ ,0.672
+ ,9.2
+ ,6.3
+ ,180
+ ,0.435
+ ,0.797
+ ,11.7
+ ,6.4
+ ,190
+ ,0.456
+ ,0.761
+ ,15.8
+ ,6.2
+ ,180
+ ,0.416
+ ,0.651
+ ,8.6
+ ,6.9
+ ,205
+ ,0.449
+ ,0.9
+ ,23.2
+ ,6.4
+ ,225
+ ,0.431
+ ,0.78
+ ,27.4
+ ,6.3
+ ,185
+ ,0.487
+ ,0.771
+ ,9.3
+ ,6.8
+ ,235
+ ,0.469
+ ,0.75
+ ,16
+ ,6.9
+ ,235
+ ,0.435
+ ,0.818
+ ,4.7
+ ,6.7
+ ,210
+ ,0.48
+ ,0.825
+ ,12.5
+ ,6.9
+ ,245
+ ,0.516
+ ,0.632
+ ,20.1
+ ,6.9
+ ,245
+ ,0.493
+ ,0.757
+ ,9.1
+ ,6.3
+ ,185
+ ,0.374
+ ,0.709
+ ,8.1
+ ,6.1
+ ,185
+ ,0.424
+ ,0.782
+ ,8.6
+ ,6.2
+ ,180
+ ,0.441
+ ,0.775
+ ,20.3
+ ,6.8
+ ,220
+ ,0.503
+ ,0.88
+ ,25
+ ,6.5
+ ,194
+ ,0.503
+ ,0.833
+ ,19.2
+ ,7.6
+ ,225
+ ,0.425
+ ,0.571
+ ,3.3
+ ,6.3
+ ,210
+ ,0.371
+ ,0.816
+ ,11.2
+ ,7.1
+ ,240
+ ,0.504
+ ,0.714
+ ,10.5
+ ,6.8
+ ,225
+ ,0.4
+ ,0.765
+ ,10.1
+ ,7.3
+ ,263
+ ,0.482
+ ,0.655
+ ,7.2
+ ,6.4
+ ,210
+ ,0.475
+ ,0.244
+ ,13.6
+ ,6.8
+ ,235
+ ,0.428
+ ,0.728
+ ,9
+ ,7.2
+ ,230
+ ,0.559
+ ,0.721
+ ,24.6
+ ,6.4
+ ,190
+ ,0.441
+ ,0.757
+ ,12.6
+ ,6.6
+ ,220
+ ,0.492
+ ,0.747
+ ,5.6
+ ,6.8
+ ,210
+ ,0.402
+ ,0.739
+ ,8.7
+ ,6.1
+ ,180
+ ,0.415
+ ,0.713
+ ,7.7
+ ,6.5
+ ,235
+ ,0.492
+ ,0.742
+ ,24.1
+ ,6.4
+ ,185
+ ,0.484
+ ,0.861
+ ,11.7
+ ,6
+ ,175
+ ,0.387
+ ,0.721
+ ,7.7
+ ,6
+ ,192
+ ,0.436
+ ,0.785
+ ,9.6
+ ,7.3
+ ,263
+ ,0.482
+ ,0.655
+ ,7.2
+ ,6.1
+ ,180
+ ,0.34
+ ,0.821
+ ,12.3
+ ,6.7
+ ,240
+ ,0.516
+ ,0.728
+ ,8.9
+ ,6.4
+ ,210
+ ,0.475
+ ,0.846
+ ,13.6
+ ,5.8
+ ,160
+ ,0.412
+ ,0.813
+ ,11.2
+ ,6.9
+ ,230
+ ,0.411
+ ,0.595
+ ,2.8
+ ,7
+ ,245
+ ,0.407
+ ,0.573
+ ,3.2
+ ,7.3
+ ,228
+ ,0.445
+ ,0.726
+ ,9.4
+ ,5.9
+ ,155
+ ,0.291
+ ,0.707
+ ,11.9
+ ,6.2
+ ,200
+ ,0.449
+ ,0.804
+ ,15.4
+ ,6.8
+ ,235
+ ,0.546
+ ,0.784
+ ,7.4
+ ,7
+ ,235
+ ,0.48
+ ,0.744
+ ,18.9
+ ,5.9
+ ,105
+ ,0.359
+ ,0.839
+ ,7.9
+ ,6.1
+ ,180
+ ,0.528
+ ,0.79
+ ,12.2
+ ,5.7
+ ,185
+ ,0.352
+ ,0.701
+ ,11
+ ,7.1
+ ,245
+ ,0.414
+ ,0.778
+ ,2.8
+ ,5.8
+ ,180
+ ,0.425
+ ,0.872
+ ,11.8
+ ,7.4
+ ,240
+ ,0.599
+ ,0.713
+ ,17.1
+ ,6.8
+ ,225
+ ,0.482
+ ,0.701
+ ,11.6
+ ,6.8
+ ,215
+ ,0.457
+ ,0.734
+ ,5.8
+ ,7
+ ,230
+ ,0.435
+ ,0.764
+ ,8.3)
+ ,dim=c(5
+ ,54)
+ ,dimnames=list(c('X1'
+ ,'X2'
+ ,'X3'
+ ,'X4'
+ ,'X5')
+ ,1:54))
>  y <- array(NA,dim=c(5,54),dimnames=list(c('X1','X2','X3','X4','X5'),1:54))
>  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 = '4'
> par2 = 'none'
> par1 = '5'
> 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, 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)
Hmisc library by Frank E Harrell Jr

Type library(help='Hmisc'), ?Overview, or ?Hmisc.Overview')
to see overall documentation.

NOTE:Hmisc no longer redefines [.factor to drop unused levels when
subsetting.  To get the old behavior of Hmisc type dropUnusedLevels().


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]  9.2 11.7 15.8  8.6 23.2 27.4  9.3 16.0  4.7 12.5 20.1  9.1  8.1  8.6 20.3
[16] 25.0 19.2  3.3 11.2 10.5 10.1  7.2 13.6  9.0 24.6 12.6  5.6  8.7  7.7 24.1
[31] 11.7  7.7  9.6  7.2 12.3  8.9 13.6 11.2  2.8  3.2  9.4 11.9 15.4  7.4 18.9
[46]  7.9 12.2 11.0  2.8 11.8 17.1 11.6  5.8  8.3
> 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])

 2.8  3.2  3.3  4.7  5.6  5.8  7.2  7.4  7.7  7.9  8.1  8.3  8.6  8.7  8.9    9 
   2    1    1    1    1    1    2    1    2    1    1    1    2    1    1    1 
 9.1  9.2  9.3  9.4  9.6 10.1 10.5   11 11.2 11.6 11.7 11.8 11.9 12.2 12.3 12.5 
   1    1    1    1    1    1    1    1    2    1    2    1    1    1    1    1 
12.6 13.6 15.4 15.8   16 17.1 18.9 19.2 20.1 20.3 23.2 24.1 24.6   25 27.4 
   1    2    1    1    1    1    1    1    1    1    1    1    1    1    1 
> colnames(x)
[1] "X1" "X2" "X3" "X4" "X5"
> colnames(x)[par1]
[1] "X5"
> x[,par1]
 [1]  9.2 11.7 15.8  8.6 23.2 27.4  9.3 16.0  4.7 12.5 20.1  9.1  8.1  8.6 20.3
[16] 25.0 19.2  3.3 11.2 10.5 10.1  7.2 13.6  9.0 24.6 12.6  5.6  8.7  7.7 24.1
[31] 11.7  7.7  9.6  7.2 12.3  8.9 13.6 11.2  2.8  3.2  9.4 11.9 15.4  7.4 18.9
[46]  7.9 12.2 11.0  2.8 11.8 17.1 11.6  5.8  8.3
> if (par2 == 'none') {
+ m <- ctree(as.formula(paste(colnames(x)[par1],' ~ .',sep='')),data = x)
+ }
> 
> #Note: the /var/fisher/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/fisher/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/fisher/rcomp/tmp/1s0xe1355258301.tab") 
+ }
+ }
> m

	 Conditional inference tree with 1 terminal nodes

Response:  X5 
Inputs:  X1, X2, X3, X4 
Number of observations:  54 

1)*  weights = 54 
> postscript(file="/var/fisher/rcomp/tmp/27h2l1355258301.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/fisher/rcomp/tmp/3cna31355258301.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      9.2  11.79074 -2.590740741
2     11.7  11.79074 -0.090740741
3     15.8  11.79074  4.009259259
4      8.6  11.79074 -3.190740741
5     23.2  11.79074 11.409259259
6     27.4  11.79074 15.609259259
7      9.3  11.79074 -2.490740741
8     16.0  11.79074  4.209259259
9      4.7  11.79074 -7.090740741
10    12.5  11.79074  0.709259259
11    20.1  11.79074  8.309259259
12     9.1  11.79074 -2.690740741
13     8.1  11.79074 -3.690740741
14     8.6  11.79074 -3.190740741
15    20.3  11.79074  8.509259259
16    25.0  11.79074 13.209259259
17    19.2  11.79074  7.409259259
18     3.3  11.79074 -8.490740741
19    11.2  11.79074 -0.590740741
20    10.5  11.79074 -1.290740741
21    10.1  11.79074 -1.690740741
22     7.2  11.79074 -4.590740741
23    13.6  11.79074  1.809259259
24     9.0  11.79074 -2.790740741
25    24.6  11.79074 12.809259259
26    12.6  11.79074  0.809259259
27     5.6  11.79074 -6.190740741
28     8.7  11.79074 -3.090740741
29     7.7  11.79074 -4.090740741
30    24.1  11.79074 12.309259259
31    11.7  11.79074 -0.090740741
32     7.7  11.79074 -4.090740741
33     9.6  11.79074 -2.190740741
34     7.2  11.79074 -4.590740741
35    12.3  11.79074  0.509259259
36     8.9  11.79074 -2.890740741
37    13.6  11.79074  1.809259259
38    11.2  11.79074 -0.590740741
39     2.8  11.79074 -8.990740741
40     3.2  11.79074 -8.590740741
41     9.4  11.79074 -2.390740741
42    11.9  11.79074  0.109259259
43    15.4  11.79074  3.609259259
44     7.4  11.79074 -4.390740741
45    18.9  11.79074  7.109259259
46     7.9  11.79074 -3.890740741
47    12.2  11.79074  0.409259259
48    11.0  11.79074 -0.790740741
49     2.8  11.79074 -8.990740741
50    11.8  11.79074  0.009259259
51    17.1  11.79074  5.309259259
52    11.6  11.79074 -0.190740741
53     5.8  11.79074 -5.990740741
54     8.3  11.79074 -3.490740741
> if (par2 != 'none') {
+ print(cbind(as.factor(x[,par1]),predict(m)))
+ myt <- table(as.factor(x[,par1]),predict(m))
+ print(myt)
+ }
> postscript(file="/var/fisher/rcomp/tmp/4fxb71355258301.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/fisher/rcomp/tmp/5glec1355258301.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/fisher/rcomp/tmp/6ddfx1355258301.tab") 
+ }
Warning message:
In cor(result$Forecasts, result$Actuals) : the standard deviation is zero
> 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/fisher/rcomp/tmp/7ge3t1355258301.tab") 
+ }
> 
> try(system("convert tmp/27h2l1355258301.ps tmp/27h2l1355258301.png",intern=TRUE))
character(0)
> try(system("convert tmp/3cna31355258301.ps tmp/3cna31355258301.png",intern=TRUE))
character(0)
> try(system("convert tmp/4fxb71355258301.ps tmp/4fxb71355258301.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  3.487   0.564   4.039