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)

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.

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Type 'contributors()' for more information and
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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(79
+ ,30
+ ,94
+ ,146283
+ ,0.69
+ ,2
+ ,108
+ ,30
+ ,103
+ ,96933
+ ,0.54
+ ,4
+ ,43
+ ,26
+ ,93
+ ,95757
+ ,0.64
+ ,0
+ ,78
+ ,38
+ ,123
+ ,143983
+ ,0.61
+ ,0
+ ,86
+ ,44
+ ,148
+ ,75851
+ ,0.44
+ ,-4
+ ,44
+ ,30
+ ,90
+ ,59238
+ ,0.44
+ ,4
+ ,104
+ ,40
+ ,124
+ ,93163
+ ,0.36
+ ,4
+ ,158
+ ,47
+ ,168
+ ,151511
+ ,0.47
+ ,0
+ ,102
+ ,30
+ ,115
+ ,136368
+ ,0.59
+ ,-1
+ ,77
+ ,31
+ ,71
+ ,112642
+ ,0.48
+ ,0
+ ,80
+ ,30
+ ,108
+ ,127766
+ ,0.37
+ ,1
+ ,123
+ ,34
+ ,120
+ ,85646
+ ,0.49
+ ,0
+ ,73
+ ,31
+ ,114
+ ,98579
+ ,0.57
+ ,3
+ ,105
+ ,33
+ ,120
+ ,131741
+ ,0.59
+ ,-1
+ ,107
+ ,33
+ ,124
+ ,171975
+ ,0.58
+ ,4
+ ,84
+ ,36
+ ,126
+ ,159676
+ ,0.49
+ ,3
+ ,33
+ ,14
+ ,37
+ ,58391
+ ,0.55
+ ,1
+ ,42
+ ,17
+ ,38
+ ,31580
+ ,0.33
+ ,0
+ ,96
+ ,32
+ ,120
+ ,136815
+ ,0.51
+ ,-2
+ ,106
+ ,30
+ ,93
+ ,120642
+ ,0.45
+ ,-3
+ ,56
+ ,35
+ ,95
+ ,69107
+ ,0.46
+ ,-4
+ ,59
+ ,28
+ ,90
+ ,108016
+ ,0.71
+ ,2
+ ,76
+ ,34
+ ,110
+ ,79336
+ ,0.22
+ ,2
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+ ,138
+ ,93176
+ ,0.51
+ ,-4
+ ,115
+ ,39
+ ,133
+ ,161632
+ ,0.58
+ ,3
+ ,76
+ ,29
+ ,96
+ ,102996
+ ,0.47
+ ,2
+ ,101
+ ,44
+ ,164
+ ,160604
+ ,0.66
+ ,2
+ ,94
+ ,21
+ ,78
+ ,158051
+ ,0.46
+ ,0
+ ,92
+ ,28
+ ,102
+ ,162647
+ ,0.70
+ ,5
+ ,75
+ ,28
+ ,99
+ ,60622
+ ,0.29
+ ,-2
+ ,128
+ ,38
+ ,129
+ ,179566
+ ,0.58
+ ,0
+ ,56
+ ,32
+ ,114
+ ,96144
+ ,0.46
+ ,-2
+ ,41
+ ,29
+ ,99
+ ,129847
+ ,0.66
+ ,-3
+ ,67
+ ,27
+ ,104
+ ,71180
+ ,0.50
+ ,2
+ ,77
+ ,40
+ ,138
+ ,86767
+ ,0.48
+ ,2
+ ,66
+ ,40
+ ,151
+ ,93487
+ ,0.48
+ ,2
+ ,69
+ ,28
+ ,72
+ ,82981
+ ,0.50
+ ,0
+ ,105
+ ,34
+ ,120
+ ,73815
+ ,0.51
+ ,4
+ ,116
+ ,33
+ ,115
+ ,94552
+ ,0.34
+ ,4
+ ,62
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+ ,98
+ ,67808
+ ,0.45
+ ,2
+ ,100
+ ,35
+ ,71
+ ,106175
+ ,0.55
+ ,2
+ ,67
+ ,29
+ ,107
+ ,76669
+ ,0.59
+ ,-4
+ ,46
+ ,20
+ ,73
+ ,57283
+ ,0.51
+ ,3
+ ,135
+ ,37
+ ,129
+ ,72413
+ ,0.49
+ ,3
+ ,124
+ ,33
+ ,118
+ ,96971
+ ,0.53
+ ,2
+ ,58
+ ,29
+ ,104
+ ,120336
+ ,0.50
+ ,-1
+ ,68
+ ,28
+ ,107
+ ,93913
+ ,0.58
+ ,-3
+ ,37
+ ,21
+ ,36
+ ,32036
+ ,0.37
+ ,0
+ ,93
+ ,41
+ ,139
+ ,102255
+ ,0.45
+ ,1
+ ,56
+ ,20
+ ,56
+ ,63506
+ ,0.48
+ ,-3
+ ,83
+ ,30
+ ,93
+ ,68370
+ ,0.68
+ ,3
+ ,59
+ ,22
+ ,87
+ ,50517
+ ,0.50
+ ,0
+ ,133
+ ,42
+ ,110
+ ,103950
+ ,0.43
+ ,0
+ ,106
+ ,32
+ ,83
+ ,84396
+ ,0.55
+ ,0
+ ,71
+ ,36
+ ,98
+ ,55515
+ ,0.42
+ ,3
+ ,116
+ ,31
+ ,82
+ ,209056
+ ,0.66
+ ,-3
+ ,98
+ ,33
+ ,115
+ ,142775
+ ,0.58
+ ,0
+ ,64
+ ,40
+ ,140
+ ,68847
+ ,0.37
+ ,-4
+ ,32
+ ,38
+ ,120
+ ,20112
+ ,0.16
+ ,2
+ ,25
+ ,24
+ ,66
+ ,61023
+ ,0.62
+ ,-1
+ ,46
+ ,43
+ ,139
+ ,112494
+ ,0.65
+ ,3
+ ,63
+ ,31
+ ,119
+ ,78876
+ ,0.34
+ ,2
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+ ,141
+ ,170745
+ ,0.49
+ ,5
+ ,113
+ ,37
+ ,133
+ ,122037
+ ,0.38
+ ,2
+ ,111
+ ,31
+ ,98
+ ,112283
+ ,0.57
+ ,-2
+ ,41
+ ,21
+ ,78
+ ,10901
+ ,0.06
+ ,0
+ ,120
+ ,39
+ ,117
+ ,120691
+ ,0.47
+ ,0
+ ,87
+ ,32
+ ,105
+ ,122422
+ ,0.61
+ ,3
+ ,25
+ ,18
+ ,55
+ ,25899
+ ,0.28
+ ,-2
+ ,131
+ ,39
+ ,132
+ ,139296
+ ,0.62
+ ,0
+ ,47
+ ,30
+ ,73
+ ,89455
+ ,0.49
+ ,6
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+ ,37
+ ,86
+ ,147866
+ ,0.54
+ ,-3
+ ,37
+ ,32
+ ,48
+ ,14336
+ ,0.15
+ ,3
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+ ,17
+ ,48
+ ,30059
+ ,0.31
+ ,0
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+ ,12
+ ,43
+ ,41907
+ ,0.35
+ ,-2
+ ,16
+ ,13
+ ,46
+ ,35885
+ ,0.55
+ ,1
+ ,22
+ ,17
+ ,65
+ ,55764
+ ,0.51
+ ,0
+ ,37
+ ,17
+ ,52
+ ,35619
+ ,0.29
+ ,2
+ ,29
+ ,20
+ ,68
+ ,40557
+ ,0.53
+ ,2
+ ,55
+ ,17
+ ,47
+ ,44197
+ ,0.45
+ ,-3
+ ,5
+ ,17
+ ,41
+ ,4103
+ ,0.13
+ ,-2
+ ,0
+ ,17
+ ,47
+ ,4694
+ ,0.15
+ ,1
+ ,27
+ ,22
+ ,71
+ ,62991
+ ,0.42
+ ,-4
+ ,37
+ ,15
+ ,30
+ ,24261
+ ,0.45
+ ,0
+ ,29
+ ,12
+ ,24
+ ,21425
+ ,0.36
+ ,1
+ ,17
+ ,17
+ ,63
+ ,27184
+ ,0.32
+ ,0)
+ ,dim=c(6
+ ,86)
+ ,dimnames=list(c('blogcomp'
+ ,'review'
+ ,'feedback'
+ ,'sec'
+ ,'prod'
+ ,'score')
+ ,1:86))
>  y <- array(NA,dim=c(6,86),dimnames=list(c('blogcomp','review','feedback','sec','prod','score'),1:86))
>  for (i in 1:dim(x)[1])
+  {
+  	for (j in 1:dim(x)[2])
+  	{
+  		y[i,j] <- as.numeric(x[i,j])
+  	}
+  }
> par4 = 'yes'
> par3 = '2'
> par2 = 'quantiles'
> par1 = '2'
> #'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] "review"
> x[,par1]
 [1] 30 30 26 38 44 30 40 47 30 31 30 34 31 33 33 36 14 17 32 30 35 28 34 39 39
[26] 29 44 21 28 28 38 32 29 27 40 40 28 34 33 33 35 29 20 37 33 29 28 21 41 20
[51] 30 22 42 32 36 31 33 40 38 24 43 31 40 37 31 21 39 32 18 39 30 37 32 17 12
[76] 13 17 17 20 17 17 17 22 15 12 17
> 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])

[12,32) [32,47] 
     47      39 
> colnames(x)
[1] "blogcomp" "review"   "feedback" "sec"      "prod"     "score"   
> colnames(x)[par1]
[1] "review"
> x[,par1]
 [1] [12,32) [12,32) [12,32) [32,47] [32,47] [12,32) [32,47] [32,47] [12,32)
[10] [12,32) [12,32) [32,47] [12,32) [32,47] [32,47] [32,47] [12,32) [12,32)
[19] [32,47] [12,32) [32,47] [12,32) [32,47] [32,47] [32,47] [12,32) [32,47]
[28] [12,32) [12,32) [12,32) [32,47] [32,47] [12,32) [12,32) [32,47] [32,47]
[37] [12,32) [32,47] [32,47] [32,47] [32,47] [12,32) [12,32) [32,47] [32,47]
[46] [12,32) [12,32) [12,32) [32,47] [12,32) [12,32) [12,32) [32,47] [32,47]
[55] [32,47] [12,32) [32,47] [32,47] [32,47] [12,32) [32,47] [12,32) [32,47]
[64] [32,47] [12,32) [12,32) [32,47] [32,47] [12,32) [32,47] [12,32) [32,47]
[73] [32,47] [12,32) [12,32) [12,32) [12,32) [12,32) [12,32) [12,32) [12,32)
[82] [12,32) [12,32) [12,32) [12,32) [12,32)
Levels: [12,32) [32,47]
> 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/1qiek1323543575.tab") 
+ }
+ }
           m.ct.i.pred
m.ct.i.actu   1   2
          1 403  28
          2  75 275
[1] 0.9350348
[1] 0.7857143
[1] 0.8681178
           m.ct.x.pred
m.ct.x.actu  1  2
          1 36  3
          2  5 35
[1] 0.9230769
[1] 0.875
[1] 0.8987342
> m

	 Conditional inference tree with 2 terminal nodes

Response:  as.factor(review) 
Inputs:  blogcomp, feedback, sec, prod, score 
Number of observations:  86 

1) feedback <= 108; criterion = 1, statistic = 37.851
  2)*  weights = 52 
1) feedback > 108
  3)*  weights = 34 
> postscript(file="/var/wessaorg/rcomp/tmp/20x121323543575.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/3v14n1323543575.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)
+ }
> if (par2 != 'none') {
+ print(cbind(as.factor(x[,par1]),predict(m)))
+ myt <- table(as.factor(x[,par1]),predict(m))
+ print(myt)
+ }
      [,1] [,2]
 [1,]    1    1
 [2,]    1    1
 [3,]    1    1
 [4,]    2    2
 [5,]    2    2
 [6,]    1    1
 [7,]    2    2
 [8,]    2    2
 [9,]    1    2
[10,]    1    1
[11,]    1    1
[12,]    2    2
[13,]    1    2
[14,]    2    2
[15,]    2    2
[16,]    2    2
[17,]    1    1
[18,]    1    1
[19,]    2    2
[20,]    1    1
[21,]    2    1
[22,]    1    1
[23,]    2    2
[24,]    2    2
[25,]    2    2
[26,]    1    1
[27,]    2    2
[28,]    1    1
[29,]    1    1
[30,]    1    1
[31,]    2    2
[32,]    2    2
[33,]    1    1
[34,]    1    1
[35,]    2    2
[36,]    2    2
[37,]    1    1
[38,]    2    2
[39,]    2    2
[40,]    2    1
[41,]    2    1
[42,]    1    1
[43,]    1    1
[44,]    2    2
[45,]    2    2
[46,]    1    1
[47,]    1    1
[48,]    1    1
[49,]    2    2
[50,]    1    1
[51,]    1    1
[52,]    1    1
[53,]    2    2
[54,]    2    1
[55,]    2    1
[56,]    1    1
[57,]    2    2
[58,]    2    2
[59,]    2    2
[60,]    1    1
[61,]    2    2
[62,]    1    2
[63,]    2    2
[64,]    2    2
[65,]    1    1
[66,]    1    1
[67,]    2    2
[68,]    2    1
[69,]    1    1
[70,]    2    2
[71,]    1    1
[72,]    2    1
[73,]    2    1
[74,]    1    1
[75,]    1    1
[76,]    1    1
[77,]    1    1
[78,]    1    1
[79,]    1    1
[80,]    1    1
[81,]    1    1
[82,]    1    1
[83,]    1    1
[84,]    1    1
[85,]    1    1
[86,]    1    1
         
          [12,32) [32,47]
  [12,32)      44       3
  [32,47]       8      31
> postscript(file="/var/wessaorg/rcomp/tmp/4an2l1323543575.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/5ztu71323543575.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/6m4821323543575.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/7m4cb1323543575.tab") 
+ }
> 
> try(system("convert tmp/20x121323543575.ps tmp/20x121323543575.png",intern=TRUE))
character(0)
> try(system("convert tmp/3v14n1323543575.ps tmp/3v14n1323543575.png",intern=TRUE))
character(0)
> try(system("convert tmp/4an2l1323543575.ps tmp/4an2l1323543575.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  3.073   0.241   3.335