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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> x <- array(list(1418
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+ ,dim=c(6
+ ,156)
+ ,dimnames=list(c('pageviews'
+ ,'TineInRFC'
+ ,'BloggedComp'
+ ,'LongFBM'
+ ,'Totsize'
+ ,'Totrevision')
+ ,1:156))
>  y <- array(NA,dim=c(6,156),dimnames=list(c('pageviews','TineInRFC','BloggedComp','LongFBM','Totsize','Totrevision'),1:156))
>  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 = 'quantiles'
> par1 = '4'
> 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] "LongFBM"
> x[,par1]
  [1]  94 103  93 103  51  70  91  22  93  60 123 148  90 124  70 168 115  71
 [19]  66 134 117 108  84 156 120 114  94 120  81 110 133 122 158 109 124  92
 [37] 126  70  37 120  93  95  90  80  31 110  66 138 133 113 100   7 140  61
 [55]  41  96 164 102 124  99 129  62  73 114  99  70 104 116  91  74 138  67
 [73] 151  72 120 115 105 104 108  98  69 111  99  71  27  69 107 107  93 129
 [91]  69 118  73 119 104 107  99  90 197  85 139 106  50  64  31  63  92 106
[109]  69  93 114 110   0  83  30  98  82   0  60   9 115 140 120  66  21 124
[127] 152 139 144 120 160 114  78 119 141 101 133  83 116  90  36  97  98  78
[145] 117 148 105 132   0  73  86   0  13   4  48  46
> 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, 84) [ 84,114) [114,197] 
       53        51        52 
> colnames(x)
[1] "pageviews"   "TineInRFC"   "BloggedComp" "LongFBM"     "Totsize"    
[6] "Totrevision"
> colnames(x)[par1]
[1] "LongFBM"
> x[,par1]
  [1] [ 84,114) [ 84,114) [ 84,114) [ 84,114) [  0, 84) [  0, 84) [ 84,114)
  [8] [  0, 84) [ 84,114) [  0, 84) [114,197] [114,197] [ 84,114) [114,197]
 [15] [  0, 84) [114,197] [114,197] [  0, 84) [  0, 84) [114,197] [114,197]
 [22] [ 84,114) [ 84,114) [114,197] [114,197] [114,197] [ 84,114) [114,197]
 [29] [  0, 84) [ 84,114) [114,197] [114,197] [114,197] [ 84,114) [114,197]
 [36] [ 84,114) [114,197] [  0, 84) [  0, 84) [114,197] [ 84,114) [ 84,114)
 [43] [ 84,114) [  0, 84) [  0, 84) [ 84,114) [  0, 84) [114,197] [114,197]
 [50] [ 84,114) [ 84,114) [  0, 84) [114,197] [  0, 84) [  0, 84) [ 84,114)
 [57] [114,197] [ 84,114) [114,197] [ 84,114) [114,197] [  0, 84) [  0, 84)
 [64] [114,197] [ 84,114) [  0, 84) [ 84,114) [114,197] [ 84,114) [  0, 84)
 [71] [114,197] [  0, 84) [114,197] [  0, 84) [114,197] [114,197] [ 84,114)
 [78] [ 84,114) [ 84,114) [ 84,114) [  0, 84) [ 84,114) [ 84,114) [  0, 84)
 [85] [  0, 84) [  0, 84) [ 84,114) [ 84,114) [ 84,114) [114,197] [  0, 84)
 [92] [114,197] [  0, 84) [114,197] [ 84,114) [ 84,114) [ 84,114) [ 84,114)
 [99] [114,197] [ 84,114) [114,197] [ 84,114) [  0, 84) [  0, 84) [  0, 84)
[106] [  0, 84) [ 84,114) [ 84,114) [  0, 84) [ 84,114) [114,197] [ 84,114)
[113] [  0, 84) [  0, 84) [  0, 84) [ 84,114) [  0, 84) [  0, 84) [  0, 84)
[120] [  0, 84) [114,197] [114,197] [114,197] [  0, 84) [  0, 84) [114,197]
[127] [114,197] [114,197] [114,197] [114,197] [114,197] [114,197] [  0, 84)
[134] [114,197] [114,197] [ 84,114) [114,197] [  0, 84) [114,197] [ 84,114)
[141] [  0, 84) [ 84,114) [ 84,114) [  0, 84) [114,197] [114,197] [ 84,114)
[148] [114,197] [  0, 84) [  0, 84) [ 84,114) [  0, 84) [  0, 84) [  0, 84)
[155] [  0, 84) [  0, 84)
Levels: [  0, 84) [ 84,114) [114,197]
> 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/1myxg1324047092.tab") 
+ }
+ }
> m

	 Conditional inference tree with 4 terminal nodes

Response:  as.factor(LongFBM) 
Inputs:  pageviews, TineInRFC, BloggedComp, Totsize, Totrevision 
Number of observations:  156 

1) BloggedComp <= 55; criterion = 1, statistic = 57.215
  2) TineInRFC <= 144966; criterion = 0.991, statistic = 12.591
    3)*  weights = 37 
  2) TineInRFC > 144966
    4)*  weights = 12 
1) BloggedComp > 55
  5) BloggedComp <= 82; criterion = 0.976, statistic = 10.627
    6)*  weights = 44 
  5) BloggedComp > 82
    7)*  weights = 63 
> postscript(file="/var/wessaorg/rcomp/tmp/21qwa1324047092.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/3acr81324047092.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,]    2    2
  [2,]    2    2
  [3,]    2    2
  [4,]    2    3
  [5,]    1    1
  [6,]    1    1
  [7,]    2    3
  [8,]    1    1
  [9,]    2    1
 [10,]    1    2
 [11,]    3    2
 [12,]    3    3
 [13,]    2    1
 [14,]    3    3
 [15,]    1    2
 [16,]    3    3
 [17,]    3    3
 [18,]    1    2
 [19,]    1    2
 [20,]    3    3
 [21,]    3    3
 [22,]    2    2
 [23,]    2    1
 [24,]    3    3
 [25,]    3    3
 [26,]    3    2
 [27,]    2    2
 [28,]    3    3
 [29,]    1    1
 [30,]    2    3
 [31,]    3    3
 [32,]    3    1
 [33,]    3    3
 [34,]    2    1
 [35,]    3    3
 [36,]    2    2
 [37,]    3    3
 [38,]    1    2
 [39,]    1    1
 [40,]    3    3
 [41,]    2    3
 [42,]    2    2
 [43,]    2    2
 [44,]    1    1
 [45,]    1    1
 [46,]    2    2
 [47,]    1    1
 [48,]    3    3
 [49,]    3    3
 [50,]    2    3
 [51,]    2    2
 [52,]    1    1
 [53,]    3    2
 [54,]    1    1
 [55,]    1    1
 [56,]    2    2
 [57,]    3    3
 [58,]    2    3
 [59,]    3    3
 [60,]    2    2
 [61,]    3    3
 [62,]    1    3
 [63,]    1    1
 [64,]    3    2
 [65,]    2    1
 [66,]    1    2
 [67,]    2    2
 [68,]    3    2
 [69,]    2    3
 [70,]    1    3
 [71,]    3    2
 [72,]    1    1
 [73,]    3    2
 [74,]    1    2
 [75,]    3    3
 [76,]    3    3
 [77,]    2    3
 [78,]    2    2
 [79,]    2    3
 [80,]    2    2
 [81,]    1    1
 [82,]    2    3
 [83,]    2    1
 [84,]    1    3
 [85,]    1    1
 [86,]    1    1
 [87,]    2    2
 [88,]    2    2
 [89,]    2    2
 [90,]    3    3
 [91,]    1    2
 [92,]    3    3
 [93,]    1    1
 [94,]    3    3
 [95,]    2    2
 [96,]    2    2
 [97,]    2    2
 [98,]    2    3
 [99,]    3    3
[100,]    2    3
[101,]    3    3
[102,]    2    3
[103,]    1    1
[104,]    1    1
[105,]    1    2
[106,]    1    2
[107,]    2    3
[108,]    2    3
[109,]    1    1
[110,]    2    3
[111,]    3    1
[112,]    2    3
[113,]    1    1
[114,]    1    3
[115,]    1    1
[116,]    2    2
[117,]    1    3
[118,]    1    1
[119,]    1    2
[120,]    1    1
[121,]    3    3
[122,]    3    2
[123,]    3    1
[124,]    1    1
[125,]    1    1
[126,]    3    1
[127,]    3    3
[128,]    3    1
[129,]    3    3
[130,]    3    3
[131,]    3    3
[132,]    3    2
[133,]    1    1
[134,]    3    2
[135,]    3    3
[136,]    2    1
[137,]    3    3
[138,]    1    1
[139,]    3    3
[140,]    2    2
[141,]    1    1
[142,]    2    3
[143,]    2    3
[144,]    1    1
[145,]    3    3
[146,]    3    3
[147,]    2    3
[148,]    3    3
[149,]    1    1
[150,]    1    1
[151,]    2    3
[152,]    1    1
[153,]    1    1
[154,]    1    1
[155,]    1    1
[156,]    1    1
           
            [  0, 84) [ 84,114) [114,197]
  [  0, 84)        37        11         5
  [ 84,114)         7        23        21
  [114,197]         5        10        37
> postscript(file="/var/wessaorg/rcomp/tmp/4wj8g1324047092.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/5cnif1324047092.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/6h13g1324047092.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/7pd6o1324047092.tab") 
+ }
> 
> try(system("convert tmp/21qwa1324047092.ps tmp/21qwa1324047092.png",intern=TRUE))
character(0)
> try(system("convert tmp/3acr81324047092.ps tmp/3acr81324047092.png",intern=TRUE))
character(0)
> try(system("convert tmp/4wj8g1324047092.ps tmp/4wj8g1324047092.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  2.840   0.315   3.417