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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Type 'demo()' for some demos, 'help()' for on-line help, or
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Type 'q()' to quit R.

> x <- array(list(56
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+ ,1.1687
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+ ,21425
+ ,0
+ ,20
+ ,17
+ ,17
+ ,66
+ ,63
+ ,27184
+ ,4.2325)
+ ,dim=c(7
+ ,85)
+ ,dimnames=list(c('login'
+ ,'blog'
+ ,'review'
+ ,'fdb'
+ ,'fdb120'
+ ,'sec'
+ ,'examen')
+ ,1:85))
>  y <- array(NA,dim=c(7,85),dimnames=list(c('login','blog','review','fdb','fdb120','sec','examen'),1:85))
>  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'
> #'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
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] "examen"
> x[,par1]
 [1]  9.5457 15.8949  0.0000  0.0000  0.0000 12.0989 15.8949  2.6529  1.0579
[10]  0.0000  0.0000  0.0000  0.8401  0.0000  4.2325  5.5091  0.0000  2.9596
[19]  0.0000  0.0000  0.0000  4.2325  4.2325  6.9999  0.0000  4.2325 12.7203
[28]  4.2325 12.0989  0.0000  2.1093  6.9999  0.0000  9.5457  9.5531 15.9023
[37]  0.0000 13.9969 15.8949  0.0000 15.8949  0.0000 14.6220 12.7203 10.1745
[46]  0.0000  0.0000  0.0000  4.2325  0.0000 11.4474  4.2325  2.9596  0.0000
[55]  1.0579  1.6867  4.2325  0.0000  4.2325  0.0000  5.6162  6.7857 12.0989
[64] 15.8949  0.0000  1.0579  3.7145  8.2765  2.9596 15.8949  1.6867 10.0674
[73]  2.4416  0.0000  8.7908  0.0000  5.5091  7.5179  0.0000  8.2728  8.2728
[82]  1.1687  0.0000  0.0000  4.2325
> 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  0.8401  1.0579  1.1687  1.6867  2.1093  2.4416  2.6529  2.9596  3.7145 
     30       1       3       1       2       1       1       1       3       1 
 4.2325  5.5091  5.6162  6.7857  6.9999  7.5179  8.2728  8.2765  8.7908  9.5457 
     10       2       1       1       2       1       2       1       1       2 
 9.5531 10.0674 10.1745 11.4474 12.0989 12.7203 13.9969  14.622 15.8949 15.9023 
      1       1       1       1       3       2       1       1       6       1 
> colnames(x)
[1] "login"  "blog"   "review" "fdb"    "fdb120" "sec"    "examen"
> colnames(x)[par1]
[1] "examen"
> x[,par1]
 [1]  9.5457 15.8949  0.0000  0.0000  0.0000 12.0989 15.8949  2.6529  1.0579
[10]  0.0000  0.0000  0.0000  0.8401  0.0000  4.2325  5.5091  0.0000  2.9596
[19]  0.0000  0.0000  0.0000  4.2325  4.2325  6.9999  0.0000  4.2325 12.7203
[28]  4.2325 12.0989  0.0000  2.1093  6.9999  0.0000  9.5457  9.5531 15.9023
[37]  0.0000 13.9969 15.8949  0.0000 15.8949  0.0000 14.6220 12.7203 10.1745
[46]  0.0000  0.0000  0.0000  4.2325  0.0000 11.4474  4.2325  2.9596  0.0000
[55]  1.0579  1.6867  4.2325  0.0000  4.2325  0.0000  5.6162  6.7857 12.0989
[64] 15.8949  0.0000  1.0579  3.7145  8.2765  2.9596 15.8949  1.6867 10.0674
[73]  2.4416  0.0000  8.7908  0.0000  5.5091  7.5179  0.0000  8.2728  8.2728
[82]  1.1687  0.0000  0.0000  4.2325
> 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/1c05r1324325347.tab") 
+ }
+ }
> m

	 Conditional inference tree with 1 terminal nodes

Response:  examen 
Inputs:  login, blog, review, fdb, fdb120, sec 
Number of observations:  85 

1)*  weights = 85 
> postscript(file="/var/wessaorg/rcomp/tmp/24ll61324325347.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/3ehd51324325347.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   9.5457  4.837534  4.7081659
2  15.8949  4.837534 11.0573659
3   0.0000  4.837534 -4.8375341
4   0.0000  4.837534 -4.8375341
5   0.0000  4.837534 -4.8375341
6  12.0989  4.837534  7.2613659
7  15.8949  4.837534 11.0573659
8   2.6529  4.837534 -2.1846341
9   1.0579  4.837534 -3.7796341
10  0.0000  4.837534 -4.8375341
11  0.0000  4.837534 -4.8375341
12  0.0000  4.837534 -4.8375341
13  0.8401  4.837534 -3.9974341
14  0.0000  4.837534 -4.8375341
15  4.2325  4.837534 -0.6050341
16  5.5091  4.837534  0.6715659
17  0.0000  4.837534 -4.8375341
18  2.9596  4.837534 -1.8779341
19  0.0000  4.837534 -4.8375341
20  0.0000  4.837534 -4.8375341
21  0.0000  4.837534 -4.8375341
22  4.2325  4.837534 -0.6050341
23  4.2325  4.837534 -0.6050341
24  6.9999  4.837534  2.1623659
25  0.0000  4.837534 -4.8375341
26  4.2325  4.837534 -0.6050341
27 12.7203  4.837534  7.8827659
28  4.2325  4.837534 -0.6050341
29 12.0989  4.837534  7.2613659
30  0.0000  4.837534 -4.8375341
31  2.1093  4.837534 -2.7282341
32  6.9999  4.837534  2.1623659
33  0.0000  4.837534 -4.8375341
34  9.5457  4.837534  4.7081659
35  9.5531  4.837534  4.7155659
36 15.9023  4.837534 11.0647659
37  0.0000  4.837534 -4.8375341
38 13.9969  4.837534  9.1593659
39 15.8949  4.837534 11.0573659
40  0.0000  4.837534 -4.8375341
41 15.8949  4.837534 11.0573659
42  0.0000  4.837534 -4.8375341
43 14.6220  4.837534  9.7844659
44 12.7203  4.837534  7.8827659
45 10.1745  4.837534  5.3369659
46  0.0000  4.837534 -4.8375341
47  0.0000  4.837534 -4.8375341
48  0.0000  4.837534 -4.8375341
49  4.2325  4.837534 -0.6050341
50  0.0000  4.837534 -4.8375341
51 11.4474  4.837534  6.6098659
52  4.2325  4.837534 -0.6050341
53  2.9596  4.837534 -1.8779341
54  0.0000  4.837534 -4.8375341
55  1.0579  4.837534 -3.7796341
56  1.6867  4.837534 -3.1508341
57  4.2325  4.837534 -0.6050341
58  0.0000  4.837534 -4.8375341
59  4.2325  4.837534 -0.6050341
60  0.0000  4.837534 -4.8375341
61  5.6162  4.837534  0.7786659
62  6.7857  4.837534  1.9481659
63 12.0989  4.837534  7.2613659
64 15.8949  4.837534 11.0573659
65  0.0000  4.837534 -4.8375341
66  1.0579  4.837534 -3.7796341
67  3.7145  4.837534 -1.1230341
68  8.2765  4.837534  3.4389659
69  2.9596  4.837534 -1.8779341
70 15.8949  4.837534 11.0573659
71  1.6867  4.837534 -3.1508341
72 10.0674  4.837534  5.2298659
73  2.4416  4.837534 -2.3959341
74  0.0000  4.837534 -4.8375341
75  8.7908  4.837534  3.9532659
76  0.0000  4.837534 -4.8375341
77  5.5091  4.837534  0.6715659
78  7.5179  4.837534  2.6803659
79  0.0000  4.837534 -4.8375341
80  8.2728  4.837534  3.4352659
81  8.2728  4.837534  3.4352659
82  1.1687  4.837534 -3.6688341
83  0.0000  4.837534 -4.8375341
84  0.0000  4.837534 -4.8375341
85  4.2325  4.837534 -0.6050341
> 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/43wv01324325347.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/51zf81324325347.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/62cko1324325347.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/wessaorg/rcomp/tmp/73w0i1324325347.tab") 
+ }
> 
> try(system("convert tmp/24ll61324325347.ps tmp/24ll61324325347.png",intern=TRUE))
character(0)
> try(system("convert tmp/3ehd51324325347.ps tmp/3ehd51324325347.png",intern=TRUE))
character(0)
> try(system("convert tmp/43wv01324325347.ps tmp/43wv01324325347.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  2.628   0.323   2.946