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(6282929
+ ,213118
+ ,1081
+ ,162556
+ ,4324047
+ ,81767
+ ,309
+ ,29790
+ ,4108272
+ ,153198
+ ,458
+ ,87550
+ ,-1212617
+ ,-26007
+ ,588
+ ,84738
+ ,1485329
+ ,126942
+ ,299
+ ,54660
+ ,1779876
+ ,157214
+ ,156
+ ,42634
+ ,1367203
+ ,129352
+ ,481
+ ,40949
+ ,2519076
+ ,234817
+ ,323
+ ,42312
+ ,912684
+ ,60448
+ ,452
+ ,37704
+ ,1443586
+ ,47818
+ ,109
+ ,16275
+ ,1220017
+ ,245546
+ ,115
+ ,25830
+ ,984885
+ ,48020
+ ,110
+ ,12679
+ ,1457425
+ ,-1710
+ ,239
+ ,18014
+ ,-572920
+ ,32648
+ ,247
+ ,43556
+ ,929144
+ ,95350
+ ,497
+ ,24524
+ ,1151176
+ ,151352
+ ,103
+ ,6532
+ ,790090
+ ,288170
+ ,109
+ ,7123
+ ,774497
+ ,114337
+ ,502
+ ,20813
+ ,990576
+ ,37884
+ ,248
+ ,37597
+ ,454195
+ ,122844
+ ,373
+ ,17821
+ ,876607
+ ,82340
+ ,119
+ ,12988
+ ,711969
+ ,79801
+ ,84
+ ,22330
+ ,702380
+ ,165548
+ ,102
+ ,13326
+ ,264449
+ ,116384
+ ,295
+ ,16189
+ ,450033
+ ,134028
+ ,105
+ ,7146
+ ,541063
+ ,63838
+ ,64
+ ,15824
+ ,588864
+ ,74996
+ ,267
+ ,26088
+ ,-37216
+ ,31080
+ ,129
+ ,11326
+ ,783310
+ ,32168
+ ,37
+ ,8568
+ ,467359
+ ,49857
+ ,361
+ ,14416
+ ,688779
+ ,87161
+ ,28
+ ,3369
+ ,608419
+ ,106113
+ ,85
+ ,11819
+ ,696348
+ ,80570
+ ,44
+ ,6620
+ ,597793
+ ,102129
+ ,49
+ ,4519
+ ,821730
+ ,301670
+ ,22
+ ,2220
+ ,377934
+ ,102313
+ ,155
+ ,18562
+ ,651939
+ ,88577
+ ,91
+ ,10327
+ ,697458
+ ,112477
+ ,81
+ ,5336
+ ,700368
+ ,191778
+ ,79
+ ,2365
+ ,225986
+ ,79804
+ ,145
+ ,4069
+ ,348695
+ ,128294
+ ,816
+ ,7710
+ ,373683
+ ,96448
+ ,61
+ ,13718
+ ,501709
+ ,93811
+ ,226
+ ,4525
+ ,413743
+ ,117520
+ ,105
+ ,6869
+ ,379825
+ ,69159
+ ,62
+ ,4628
+ ,336260
+ ,101792
+ ,24
+ ,3653
+ ,636765
+ ,210568
+ ,26
+ ,1265
+ ,481231
+ ,136996
+ ,322
+ ,7489
+ ,469107
+ ,121920
+ ,84
+ ,4901
+ ,211928
+ ,76403
+ ,33
+ ,2284)
+ ,dim=c(4
+ ,50)
+ ,dimnames=list(c('Wealth'
+ ,'Dividends'
+ ,'Trades'
+ ,'Costs
')
+ ,1:50))
>  y <- array(NA,dim=c(4,50),dimnames=list(c('Wealth','Dividends','Trades','Costs
'),1:50))
>  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 = ''
> par2 = 'none'
> par1 = '1'
> #'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] "Wealth"
> x[,par1]
 [1]  6282929  4324047  4108272 -1212617  1485329  1779876  1367203  2519076
 [9]   912684  1443586  1220017   984885  1457425  -572920   929144  1151176
[17]   790090   774497   990576   454195   876607   711969   702380   264449
[25]   450033   541063   588864   -37216   783310   467359   688779   608419
[33]   696348   597793   821730   377934   651939   697458   700368   225986
[41]   348695   373683   501709   413743   379825   336260   636765   481231
[49]   469107   211928
> 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])

-1212617  -572920   -37216   211928   225986   264449   336260   348695 
       1        1        1        1        1        1        1        1 
  373683   377934   379825   413743   450033   454195   467359   469107 
       1        1        1        1        1        1        1        1 
  481231   501709   541063   588864   597793   608419   636765   651939 
       1        1        1        1        1        1        1        1 
  688779   696348   697458   700368   702380   711969   774497   783310 
       1        1        1        1        1        1        1        1 
  790090   821730   876607   912684   929144   984885   990576  1151176 
       1        1        1        1        1        1        1        1 
 1220017  1367203  1443586  1457425  1485329  1779876  2519076  4108272 
       1        1        1        1        1        1        1        1 
 4324047  6282929 
       1        1 
> colnames(x)
[1] "Wealth"    "Dividends" "Trades"    "Costs."   
> colnames(x)[par1]
[1] "Wealth"
> x[,par1]
 [1]  6282929  4324047  4108272 -1212617  1485329  1779876  1367203  2519076
 [9]   912684  1443586  1220017   984885  1457425  -572920   929144  1151176
[17]   790090   774497   990576   454195   876607   711969   702380   264449
[25]   450033   541063   588864   -37216   783310   467359   688779   608419
[33]   696348   597793   821730   377934   651939   697458   700368   225986
[41]   348695   373683   501709   413743   379825   336260   636765   481231
[49]   469107   211928
> 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/1f3ov1293188373.tab") 
+ }
+ }
> m

	 Conditional inference tree with 2 terminal nodes

Response:  Wealth 
Inputs:  Dividends, Trades, Costs. 
Number of observations:  50 

1) Costs. <= 26088; criterion = 1, statistic = 20.971
  2)*  weights = 39 
1) Costs. > 26088
  3)*  weights = 11 
> postscript(file="/var/www/rcomp/tmp/2f3ov1293188373.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/3f3ov1293188373.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   6282929 1998586.8  4284342.182
2   4324047 1998586.8  2325460.182
3   4108272 1998586.8  2109685.182
4  -1212617 1998586.8 -3211203.818
5   1485329 1998586.8  -513257.818
6   1779876 1998586.8  -218710.818
7   1367203 1998586.8  -631383.818
8   2519076 1998586.8   520489.182
9    912684 1998586.8 -1085902.818
10  1443586  635218.8   808367.205
11  1220017  635218.8   584798.205
12   984885  635218.8   349666.205
13  1457425  635218.8   822206.205
14  -572920 1998586.8 -2571506.818
15   929144  635218.8   293925.205
16  1151176  635218.8   515957.205
17   790090  635218.8   154871.205
18   774497  635218.8   139278.205
19   990576 1998586.8 -1008010.818
20   454195  635218.8  -181023.795
21   876607  635218.8   241388.205
22   711969  635218.8    76750.205
23   702380  635218.8    67161.205
24   264449  635218.8  -370769.795
25   450033  635218.8  -185185.795
26   541063  635218.8   -94155.795
27   588864  635218.8   -46354.795
28   -37216  635218.8  -672434.795
29   783310  635218.8   148091.205
30   467359  635218.8  -167859.795
31   688779  635218.8    53560.205
32   608419  635218.8   -26799.795
33   696348  635218.8    61129.205
34   597793  635218.8   -37425.795
35   821730  635218.8   186511.205
36   377934  635218.8  -257284.795
37   651939  635218.8    16720.205
38   697458  635218.8    62239.205
39   700368  635218.8    65149.205
40   225986  635218.8  -409232.795
41   348695  635218.8  -286523.795
42   373683  635218.8  -261535.795
43   501709  635218.8  -133509.795
44   413743  635218.8  -221475.795
45   379825  635218.8  -255393.795
46   336260  635218.8  -298958.795
47   636765  635218.8     1546.205
48   481231  635218.8  -153987.795
49   469107  635218.8  -166111.795
50   211928  635218.8  -423290.795
> 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/4qc5y1293188373.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/5m4lp1293188373.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/6fv2a1293188373.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/www/rcomp/tmp/7ie0g1293188373.tab") 
+ }
> 
> try(system("convert tmp/2f3ov1293188373.ps tmp/2f3ov1293188373.png",intern=TRUE))
character(0)
> try(system("convert tmp/3f3ov1293188373.ps tmp/3f3ov1293188373.png",intern=TRUE))
character(0)
> try(system("convert tmp/4qc5y1293188373.ps tmp/4qc5y1293188373.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  1.990   0.660   2.631