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)

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> x <- array(list(391
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+ ,16
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+ ,121
+ ,25
+ ,91
+ ,119182
+ ,195663
+ ,14)
+ ,dim=c(7
+ ,81)
+ ,dimnames=list(c('Pageviews'
+ ,'Blogged_comp'
+ ,'Reviewed_comp'
+ ,'Fb_messages'
+ ,'Comp_Size'
+ ,'Comp_Time'
+ ,'PLC')
+ ,1:81))
>  y <- array(NA,dim=c(7,81),dimnames=list(c('Pageviews','Blogged_comp','Reviewed_comp','Fb_messages','Comp_Size','Comp_Time','PLC'),1:81))
>  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 = '7'
> 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] "PLC"
> x[,par1]
 [1] 12 10 14  9  8 16 11 19 10 12 11  8 14 13 14 14 17 16 12 14 15 15 14 14 16
[26] 16 13 14 15 12 13 15 17  8 16 10 17 14 16  7 15  9  9 13 16 15 12 16 15  8
[51] 16 13 15 15 17 13 16 16 18 19 14 15 15 17 11 16 16 16 14 17 16 17 13 12 14
[76] 10 20 16 14 16 14
> 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])

 7  8  9 10 11 12 13 14 15 16 17 18 19 20 
 1  4  3  4  3  6  7 14 11 17  7  1  2  1 
> colnames(x)
[1] "Pageviews"     "Blogged_comp"  "Reviewed_comp" "Fb_messages"  
[5] "Comp_Size"     "Comp_Time"     "PLC"          
> colnames(x)[par1]
[1] "PLC"
> x[,par1]
 [1] 12 10 14  9  8 16 11 19 10 12 11  8 14 13 14 14 17 16 12 14 15 15 14 14 16
[26] 16 13 14 15 12 13 15 17  8 16 10 17 14 16  7 15  9  9 13 16 15 12 16 15  8
[51] 16 13 15 15 17 13 16 16 18 19 14 15 15 17 11 16 16 16 14 17 16 17 13 12 14
[76] 10 20 16 14 16 14
> 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/1rynl1323456294.tab") 
+ }
+ }
> m

	 Conditional inference tree with 1 terminal nodes

Response:  PLC 
Inputs:  Pageviews, Blogged_comp, Reviewed_comp, Fb_messages, Comp_Size, Comp_Time 
Number of observations:  81 

1)*  weights = 81 
> postscript(file="/var/www/rcomp/tmp/25hkq1323456294.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/3dfk61323456294.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       12  13.95062 -1.95061728
2       10  13.95062 -3.95061728
3       14  13.95062  0.04938272
4        9  13.95062 -4.95061728
5        8  13.95062 -5.95061728
6       16  13.95062  2.04938272
7       11  13.95062 -2.95061728
8       19  13.95062  5.04938272
9       10  13.95062 -3.95061728
10      12  13.95062 -1.95061728
11      11  13.95062 -2.95061728
12       8  13.95062 -5.95061728
13      14  13.95062  0.04938272
14      13  13.95062 -0.95061728
15      14  13.95062  0.04938272
16      14  13.95062  0.04938272
17      17  13.95062  3.04938272
18      16  13.95062  2.04938272
19      12  13.95062 -1.95061728
20      14  13.95062  0.04938272
21      15  13.95062  1.04938272
22      15  13.95062  1.04938272
23      14  13.95062  0.04938272
24      14  13.95062  0.04938272
25      16  13.95062  2.04938272
26      16  13.95062  2.04938272
27      13  13.95062 -0.95061728
28      14  13.95062  0.04938272
29      15  13.95062  1.04938272
30      12  13.95062 -1.95061728
31      13  13.95062 -0.95061728
32      15  13.95062  1.04938272
33      17  13.95062  3.04938272
34       8  13.95062 -5.95061728
35      16  13.95062  2.04938272
36      10  13.95062 -3.95061728
37      17  13.95062  3.04938272
38      14  13.95062  0.04938272
39      16  13.95062  2.04938272
40       7  13.95062 -6.95061728
41      15  13.95062  1.04938272
42       9  13.95062 -4.95061728
43       9  13.95062 -4.95061728
44      13  13.95062 -0.95061728
45      16  13.95062  2.04938272
46      15  13.95062  1.04938272
47      12  13.95062 -1.95061728
48      16  13.95062  2.04938272
49      15  13.95062  1.04938272
50       8  13.95062 -5.95061728
51      16  13.95062  2.04938272
52      13  13.95062 -0.95061728
53      15  13.95062  1.04938272
54      15  13.95062  1.04938272
55      17  13.95062  3.04938272
56      13  13.95062 -0.95061728
57      16  13.95062  2.04938272
58      16  13.95062  2.04938272
59      18  13.95062  4.04938272
60      19  13.95062  5.04938272
61      14  13.95062  0.04938272
62      15  13.95062  1.04938272
63      15  13.95062  1.04938272
64      17  13.95062  3.04938272
65      11  13.95062 -2.95061728
66      16  13.95062  2.04938272
67      16  13.95062  2.04938272
68      16  13.95062  2.04938272
69      14  13.95062  0.04938272
70      17  13.95062  3.04938272
71      16  13.95062  2.04938272
72      17  13.95062  3.04938272
73      13  13.95062 -0.95061728
74      12  13.95062 -1.95061728
75      14  13.95062  0.04938272
76      10  13.95062 -3.95061728
77      20  13.95062  6.04938272
78      16  13.95062  2.04938272
79      14  13.95062  0.04938272
80      16  13.95062  2.04938272
81      14  13.95062  0.04938272
> 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/4os4m1323456294.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/5hdnj1323456294.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/6ftxr1323456294.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/www/rcomp/tmp/7lfx81323456294.tab") 
+ }
> 
> try(system("convert tmp/25hkq1323456294.ps tmp/25hkq1323456294.png",intern=TRUE))
character(0)
> try(system("convert tmp/3dfk61323456294.ps tmp/3dfk61323456294.png",intern=TRUE))
character(0)
> try(system("convert tmp/4os4m1323456294.ps tmp/4os4m1323456294.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  2.030   0.120   2.146