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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+ ,0
+ ,17
+ ,16
+ ,64
+ ,39
+ ,19540
+ ,6095
+ ,35873
+ ,27
+ ,21
+ ,15)
+ ,dim=c(16
+ ,173)
+ ,dimnames=list(c('pageviews'
+ ,'time_in_rfc'
+ ,'logins'
+ ,'compendium_views_info'
+ ,'compendium_views_pr'
+ ,'shared_compendiums'
+ ,'blogged_computations'
+ ,'compendiums_reviewed'
+ ,'feedback_messages_p1'
+ ,'feedback_messages_p120'
+ ,'totsize'
+ ,'totrevisions'
+ ,'totseconds'
+ ,'tothyperlinks'
+ ,'totblogs'
+ ,'I1')
+ ,1:173))
>  y <- array(NA,dim=c(16,173),dimnames=list(c('pageviews','time_in_rfc','logins','compendium_views_info','compendium_views_pr','shared_compendiums','blogged_computations','compendiums_reviewed','feedback_messages_p1','feedback_messages_p120','totsize','totrevisions','totseconds','tothyperlinks','totblogs','I1'),1:173))
>  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 = '10'
> #'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] "feedback_messages_p120"
> x[,par1]
  [1]  94 103  93  91  93  60 123  90 168 115  71  66 117 108  84 120 114  94
 [19] 120  81 133 122 124 126   0  37  38 120  95  77  90  80 110 138 100   7
 [37] 140  96 164  78  49 124  62  99  70 104 116  91  67  72 120 105 104  98
 [55] 111  71  69 107  73 107 129 118  73 119 104 107  90 197  36  85 139 106
 [73]  50  63  63  69  41  56  25  93  44  87 110   0  83  80  98  82   0  60
 [91]  28   9  33  59 115 120  66 152 139  38 144 160 114 119 101  56 133  83
[109] 116  50  61  97  98  78 117  55 132  44  21  50  73  86  48  48  68  87
[127]  43  67  46  56  60  65  60  54  52  61  61  81  40  40  68  79  47  41
[145]  29  60  79  47  40  42  49  57  40  33  77  45  45  50  71  67  62  54
[163]   4  25  40  59  24  58  42   4  63  54  39
> 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, 77) [77,197] 
      88       85 
> colnames(x)
 [1] "pageviews"              "time_in_rfc"            "logins"                
 [4] "compendium_views_info"  "compendium_views_pr"    "shared_compendiums"    
 [7] "blogged_computations"   "compendiums_reviewed"   "feedback_messages_p1"  
[10] "feedback_messages_p120" "totsize"                "totrevisions"          
[13] "totseconds"             "tothyperlinks"          "totblogs"              
[16] "I1"                    
> colnames(x)[par1]
[1] "feedback_messages_p120"
> x[,par1]
  [1] [77,197] [77,197] [77,197] [77,197] [77,197] [ 0, 77) [77,197] [77,197]
  [9] [77,197] [77,197] [ 0, 77) [ 0, 77) [77,197] [77,197] [77,197] [77,197]
 [17] [77,197] [77,197] [77,197] [77,197] [77,197] [77,197] [77,197] [77,197]
 [25] [ 0, 77) [ 0, 77) [ 0, 77) [77,197] [77,197] [77,197] [77,197] [77,197]
 [33] [77,197] [77,197] [77,197] [ 0, 77) [77,197] [77,197] [77,197] [77,197]
 [41] [ 0, 77) [77,197] [ 0, 77) [77,197] [ 0, 77) [77,197] [77,197] [77,197]
 [49] [ 0, 77) [ 0, 77) [77,197] [77,197] [77,197] [77,197] [77,197] [ 0, 77)
 [57] [ 0, 77) [77,197] [ 0, 77) [77,197] [77,197] [77,197] [ 0, 77) [77,197]
 [65] [77,197] [77,197] [77,197] [77,197] [ 0, 77) [77,197] [77,197] [77,197]
 [73] [ 0, 77) [ 0, 77) [ 0, 77) [ 0, 77) [ 0, 77) [ 0, 77) [ 0, 77) [77,197]
 [81] [ 0, 77) [77,197] [77,197] [ 0, 77) [77,197] [77,197] [77,197] [77,197]
 [89] [ 0, 77) [ 0, 77) [ 0, 77) [ 0, 77) [ 0, 77) [ 0, 77) [77,197] [77,197]
 [97] [ 0, 77) [77,197] [77,197] [ 0, 77) [77,197] [77,197] [77,197] [77,197]
[105] [77,197] [ 0, 77) [77,197] [77,197] [77,197] [ 0, 77) [ 0, 77) [77,197]
[113] [77,197] [77,197] [77,197] [ 0, 77) [77,197] [ 0, 77) [ 0, 77) [ 0, 77)
[121] [ 0, 77) [77,197] [ 0, 77) [ 0, 77) [ 0, 77) [77,197] [ 0, 77) [ 0, 77)
[129] [ 0, 77) [ 0, 77) [ 0, 77) [ 0, 77) [ 0, 77) [ 0, 77) [ 0, 77) [ 0, 77)
[137] [ 0, 77) [77,197] [ 0, 77) [ 0, 77) [ 0, 77) [77,197] [ 0, 77) [ 0, 77)
[145] [ 0, 77) [ 0, 77) [77,197] [ 0, 77) [ 0, 77) [ 0, 77) [ 0, 77) [ 0, 77)
[153] [ 0, 77) [ 0, 77) [77,197] [ 0, 77) [ 0, 77) [ 0, 77) [ 0, 77) [ 0, 77)
[161] [ 0, 77) [ 0, 77) [ 0, 77) [ 0, 77) [ 0, 77) [ 0, 77) [ 0, 77) [ 0, 77)
[169] [ 0, 77) [ 0, 77) [ 0, 77) [ 0, 77) [ 0, 77)
Levels: [ 0, 77) [77,197]
> 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/181oq1323893676.tab") 
+ }
+ }
           m.ct.i.pred
m.ct.i.actu   1   2
          1 694  85
          2  74 697
[1] 0.8908858
[1] 0.9040208
[1] 0.8974194
           m.ct.x.pred
m.ct.x.actu  1  2
          1 93  8
          2 12 67
[1] 0.9207921
[1] 0.8481013
[1] 0.8888889
> m

	 Conditional inference tree with 4 terminal nodes

Response:  as.factor(feedback_messages_p120) 
Inputs:  pageviews, time_in_rfc, logins, compendium_views_info, compendium_views_pr, shared_compendiums, blogged_computations, compendiums_reviewed, feedback_messages_p1, totsize, totrevisions, totseconds, tothyperlinks, totblogs, I1 
Number of observations:  173 

1) feedback_messages_p1 <= 93; criterion = 1, statistic = 99.692
  2) pageviews <= 1926; criterion = 1, statistic = 18.419
    3) totrevisions <= 13539; criterion = 0.987, statistic = 11.105
      4)*  weights = 75 
    3) totrevisions > 13539
      5)*  weights = 10 
  2) pageviews > 1926
    6)*  weights = 7 
1) feedback_messages_p1 > 93
  7)*  weights = 81 
> postscript(file="/var/wessaorg/rcomp/tmp/2e96a1323893676.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/35he21323893676.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    2
  [5,]    2    2
  [6,]    1    1
  [7,]    2    2
  [8,]    2    2
  [9,]    2    2
 [10,]    2    2
 [11,]    1    2
 [12,]    1    1
 [13,]    2    2
 [14,]    2    2
 [15,]    2    1
 [16,]    2    2
 [17,]    2    2
 [18,]    2    2
 [19,]    2    2
 [20,]    2    2
 [21,]    2    2
 [22,]    2    2
 [23,]    2    2
 [24,]    2    2
 [25,]    1    1
 [26,]    1    1
 [27,]    1    1
 [28,]    2    2
 [29,]    2    2
 [30,]    2    2
 [31,]    2    2
 [32,]    2    2
 [33,]    2    2
 [34,]    2    2
 [35,]    2    2
 [36,]    1    1
 [37,]    2    2
 [38,]    2    2
 [39,]    2    2
 [40,]    2    2
 [41,]    1    1
 [42,]    2    2
 [43,]    1    2
 [44,]    2    2
 [45,]    1    2
 [46,]    2    2
 [47,]    2    2
 [48,]    2    2
 [49,]    1    1
 [50,]    1    2
 [51,]    2    2
 [52,]    2    2
 [53,]    2    2
 [54,]    2    2
 [55,]    2    2
 [56,]    1    1
 [57,]    1    1
 [58,]    2    2
 [59,]    1    1
 [60,]    2    2
 [61,]    2    2
 [62,]    2    2
 [63,]    1    1
 [64,]    2    2
 [65,]    2    2
 [66,]    2    2
 [67,]    2    2
 [68,]    2    2
 [69,]    1    1
 [70,]    2    2
 [71,]    2    2
 [72,]    2    2
 [73,]    1    2
 [74,]    1    2
 [75,]    1    2
 [76,]    1    1
 [77,]    1    1
 [78,]    1    1
 [79,]    1    1
 [80,]    2    2
 [81,]    1    1
 [82,]    2    1
 [83,]    2    2
 [84,]    1    1
 [85,]    2    2
 [86,]    2    2
 [87,]    2    2
 [88,]    2    2
 [89,]    1    1
 [90,]    1    1
 [91,]    1    1
 [92,]    1    1
 [93,]    1    1
 [94,]    1    1
 [95,]    2    2
 [96,]    2    2
 [97,]    1    1
 [98,]    2    2
 [99,]    2    2
[100,]    1    1
[101,]    2    2
[102,]    2    2
[103,]    2    2
[104,]    2    2
[105,]    2    2
[106,]    1    1
[107,]    2    2
[108,]    2    2
[109,]    2    2
[110,]    1    1
[111,]    1    1
[112,]    2    2
[113,]    2    2
[114,]    2    2
[115,]    2    2
[116,]    1    1
[117,]    2    2
[118,]    1    1
[119,]    1    1
[120,]    1    1
[121,]    1    2
[122,]    2    2
[123,]    1    2
[124,]    1    1
[125,]    1    1
[126,]    2    1
[127,]    1    1
[128,]    1    1
[129,]    1    1
[130,]    1    1
[131,]    1    1
[132,]    1    1
[133,]    1    1
[134,]    1    1
[135,]    1    1
[136,]    1    1
[137,]    1    1
[138,]    2    1
[139,]    1    1
[140,]    1    1
[141,]    1    1
[142,]    2    1
[143,]    1    2
[144,]    1    1
[145,]    1    1
[146,]    1    1
[147,]    2    1
[148,]    1    1
[149,]    1    1
[150,]    1    1
[151,]    1    1
[152,]    1    1
[153,]    1    1
[154,]    1    1
[155,]    2    1
[156,]    1    1
[157,]    1    1
[158,]    1    1
[159,]    1    1
[160,]    1    1
[161,]    1    1
[162,]    1    1
[163,]    1    1
[164,]    1    1
[165,]    1    1
[166,]    1    1
[167,]    1    1
[168,]    1    1
[169,]    1    1
[170,]    1    1
[171,]    1    1
[172,]    1    1
[173,]    1    1
          
           [ 0, 77) [77,197]
  [ 0, 77)       78       10
  [77,197]        7       78
> postscript(file="/var/wessaorg/rcomp/tmp/4jy1g1323893676.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/5iyy61323893676.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/67t9i1323893676.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/7iodh1323893676.tab") 
+ }
> 
> try(system("convert tmp/2e96a1323893676.ps tmp/2e96a1323893676.png",intern=TRUE))
character(0)
> try(system("convert tmp/35he21323893676.ps tmp/35he21323893676.png",intern=TRUE))
character(0)
> try(system("convert tmp/4jy1g1323893676.ps tmp/4jy1g1323893676.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  5.849   0.267   6.112