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)

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(1606
+ ,6
+ ,3.74
+ ,16
+ ,1391
+ ,1634
+ ,6.81
+ ,4.17
+ ,29
+ ,1621
+ ,2013
+ ,9.75
+ ,4.84
+ ,22
+ ,1837
+ ,1654
+ ,6.96
+ ,4.21
+ ,30
+ ,2132
+ ,1003
+ ,3.94
+ ,3.93
+ ,20
+ ,1489
+ ,1029
+ ,5
+ ,4.9
+ ,39
+ ,1817
+ ,1052
+ ,4.9
+ ,4.7
+ ,18
+ ,1586
+ ,1653
+ ,5.7
+ ,3.5
+ ,9.6
+ ,1565
+ ,1918
+ ,6.5
+ ,3.4
+ ,10.2
+ ,1787
+ ,1926
+ ,7.1
+ ,3.7
+ ,20.2
+ ,1804
+ ,1862
+ ,7.5
+ ,4
+ ,50
+ ,1763
+ ,1816
+ ,7.8
+ ,4.3
+ ,120
+ ,1675
+ ,1712
+ ,7
+ ,4.1
+ ,19.8
+ ,1575
+ ,1646
+ ,7.4
+ ,4.5
+ ,18
+ ,1524
+ ,1555
+ ,8.55
+ ,5.5
+ ,3
+ ,1686
+ ,1402
+ ,7.43
+ ,5.3
+ ,11
+ ,1800
+ ,1047
+ ,4.7
+ ,4.5
+ ,15
+ ,1442
+ ,891
+ ,4.7
+ ,5.3
+ ,27
+ ,1345
+ ,940
+ ,5.3
+ ,5.6
+ ,28
+ ,1500
+ ,1372
+ ,6.2
+ ,4.5
+ ,14
+ ,1556
+ ,2012
+ ,7.4
+ ,3.7
+ ,5.6
+ ,2012
+ ,1879
+ ,7.5
+ ,4
+ ,6.5
+ ,1618
+ ,1667
+ ,7.32
+ ,4.4
+ ,8.5
+ ,1487
+ ,1856
+ ,8.15
+ ,4.4
+ ,87.9
+ ,1607
+ ,1771
+ ,7.24
+ ,4.1
+ ,5.8
+ ,1308
+ ,1721
+ ,7.4
+ ,4.3
+ ,25.2
+ ,1429
+ ,1773
+ ,9.4
+ ,5.3
+ ,7.5
+ ,1596
+ ,1507
+ ,8.9
+ ,5.9
+ ,13.7
+ ,1884
+ ,1033
+ ,4.5
+ ,4.4
+ ,34
+ ,1262
+ ,1011
+ ,4.9
+ ,4.9
+ ,17
+ ,1283
+ ,1111
+ ,5.6
+ ,5.1
+ ,9
+ ,1346
+ ,1736
+ ,6.4
+ ,3.7
+ ,9.2
+ ,1505
+ ,1865
+ ,6
+ ,3.2
+ ,5
+ ,1151
+ ,2078
+ ,6.9
+ ,3.3
+ ,24
+ ,1600
+ ,1947
+ ,6.7
+ ,3.5
+ ,40
+ ,1420
+ ,1428
+ ,5.4
+ ,3.8
+ ,86.5
+ ,1073
+ ,1500
+ ,5.6
+ ,3.8
+ ,0.54
+ ,1076
+ ,1950
+ ,6.9
+ ,3.5
+ ,14
+ ,1510
+ ,1591
+ ,6.9
+ ,4.3
+ ,4.8
+ ,1345
+ ,1613
+ ,7
+ ,4.3
+ ,28
+ ,1631
+ ,1077
+ ,4
+ ,3.7
+ ,16
+ ,1135
+ ,880
+ ,3.7
+ ,4.2
+ ,5.8
+ ,1009
+ ,1128
+ ,4.9
+ ,4.3
+ ,16
+ ,1155
+ ,1320
+ ,5
+ ,3.8
+ ,9.1
+ ,1184
+ ,1692
+ ,5.7
+ ,3.4
+ ,6
+ ,1285
+ ,1575
+ ,6.1
+ ,3.9
+ ,17
+ ,1257
+ ,1478
+ ,5.3
+ ,3.6
+ ,26
+ ,1131
+ ,1500
+ ,5.5
+ ,3.6
+ ,99.6
+ ,1274
+ ,1368
+ ,5.7
+ ,4.2
+ ,41
+ ,235
+ ,1563
+ ,5.21
+ ,3.3
+ ,72
+ ,1299
+ ,1424
+ ,5.4
+ ,3.8
+ ,23
+ ,1460
+ ,1274
+ ,4.5
+ ,3.5
+ ,42
+ ,1455
+ ,1047
+ ,3.7
+ ,3.7
+ ,40
+ ,1113
+ ,1049
+ ,4.1
+ ,3.9
+ ,18
+ ,1263
+ ,1069
+ ,4.8
+ ,4.5
+ ,45
+ ,1401
+ ,981
+ ,4.1
+ ,4.2
+ ,18
+ ,1135
+ ,1540
+ ,5
+ ,3.2
+ ,2
+ ,1137
+ ,1559
+ ,5.2
+ ,3.3
+ ,10
+ ,1140
+ ,1459
+ ,5.5
+ ,3.8
+ ,13.6
+ ,1014
+ ,1559
+ ,5.9
+ ,3.8
+ ,160
+ ,1220)
+ ,dim=c(5
+ ,60)
+ ,dimnames=list(c('aanvoer'
+ ,'aanvoerwaarde'
+ ,'prijzen'
+ ,'interventie'
+ ,'visserijen')
+ ,1:60))
>  y <- array(NA,dim=c(5,60),dimnames=list(c('aanvoer','aanvoerwaarde','prijzen','interventie','visserijen'),1:60))
>  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 = '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] "aanvoer"
> x[,par1]
 [1] 1606 1634 2013 1654 1003 1029 1052 1653 1918 1926 1862 1816 1712 1646 1555
[16] 1402 1047  891  940 1372 2012 1879 1667 1856 1771 1721 1773 1507 1033 1011
[31] 1111 1736 1865 2078 1947 1428 1500 1950 1591 1613 1077  880 1128 1320 1692
[46] 1575 1478 1500 1368 1563 1424 1274 1047 1049 1069  981 1540 1559 1459 1559
> 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])

[ 880,1559) [1559,2078] 
         30          30 
> colnames(x)
[1] "aanvoer"       "aanvoerwaarde" "prijzen"       "interventie"  
[5] "visserijen"   
> colnames(x)[par1]
[1] "aanvoer"
> x[,par1]
 [1] [1559,2078] [1559,2078] [1559,2078] [1559,2078] [ 880,1559) [ 880,1559)
 [7] [ 880,1559) [1559,2078] [1559,2078] [1559,2078] [1559,2078] [1559,2078]
[13] [1559,2078] [1559,2078] [ 880,1559) [ 880,1559) [ 880,1559) [ 880,1559)
[19] [ 880,1559) [ 880,1559) [1559,2078] [1559,2078] [1559,2078] [1559,2078]
[25] [1559,2078] [1559,2078] [1559,2078] [ 880,1559) [ 880,1559) [ 880,1559)
[31] [ 880,1559) [1559,2078] [1559,2078] [1559,2078] [1559,2078] [ 880,1559)
[37] [ 880,1559) [1559,2078] [1559,2078] [1559,2078] [ 880,1559) [ 880,1559)
[43] [ 880,1559) [ 880,1559) [1559,2078] [1559,2078] [ 880,1559) [ 880,1559)
[49] [ 880,1559) [1559,2078] [ 880,1559) [ 880,1559) [ 880,1559) [ 880,1559)
[55] [ 880,1559) [ 880,1559) [ 880,1559) [1559,2078] [ 880,1559) [1559,2078]
Levels: [ 880,1559) [1559,2078]
> 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/1qa2g1292497673.tab") 
+ }
+ }
           m.ct.i.pred
m.ct.i.actu   1   2
          1 238  25
          2  34 231
[1] 0.904943
[1] 0.8716981
[1] 0.8882576
           m.ct.x.pred
m.ct.x.actu  1  2
          1 32  5
          2  3 32
[1] 0.8648649
[1] 0.9142857
[1] 0.8888889
> m

	 Conditional inference tree with 4 terminal nodes

Response:  as.factor(aanvoer) 
Inputs:  aanvoerwaarde, prijzen, interventie, visserijen 
Number of observations:  60 

1) aanvoerwaarde <= 5.6; criterion = 1, statistic = 21.698
  2)*  weights = 27 
1) aanvoerwaarde > 5.6
  3) prijzen <= 4.4; criterion = 0.998, statistic = 12.073
    4) visserijen <= 1345; criterion = 0.999, statistic = 13.797
      5)*  weights = 7 
    4) visserijen > 1345
      6)*  weights = 19 
  3) prijzen > 4.4
    7)*  weights = 7 
> postscript(file="/var/www/rcomp/tmp/2qa2g1292497673.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/3qa2g1292497673.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    1
 [4,]    2    2
 [5,]    1    1
 [6,]    1    1
 [7,]    1    1
 [8,]    2    2
 [9,]    2    2
[10,]    2    2
[11,]    2    2
[12,]    2    2
[13,]    2    2
[14,]    2    1
[15,]    1    1
[16,]    1    1
[17,]    1    1
[18,]    1    1
[19,]    1    1
[20,]    1    1
[21,]    2    2
[22,]    2    2
[23,]    2    2
[24,]    2    2
[25,]    2    2
[26,]    2    2
[27,]    2    1
[28,]    1    1
[29,]    1    1
[30,]    1    1
[31,]    1    1
[32,]    2    2
[33,]    2    2
[34,]    2    2
[35,]    2    2
[36,]    1    1
[37,]    1    1
[38,]    2    2
[39,]    2    2
[40,]    2    2
[41,]    1    1
[42,]    1    1
[43,]    1    1
[44,]    1    1
[45,]    2    2
[46,]    2    2
[47,]    1    1
[48,]    1    1
[49,]    1    2
[50,]    2    1
[51,]    1    1
[52,]    1    1
[53,]    1    1
[54,]    1    1
[55,]    1    1
[56,]    1    1
[57,]    1    1
[58,]    2    1
[59,]    1    1
[60,]    2    2
             
              [ 880,1559) [1559,2078]
  [ 880,1559)          29           1
  [1559,2078]           5          25
> postscript(file="/var/www/rcomp/tmp/40jj11292497673.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/5ebzs1292497673.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/6pkzd1292497673.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/7s3fj1292497673.tab") 
+ }
> try(system("convert tmp/2qa2g1292497673.ps tmp/2qa2g1292497673.png",intern=TRUE))
character(0)
> try(system("convert tmp/3qa2g1292497673.ps tmp/3qa2g1292497673.png",intern=TRUE))
character(0)
> try(system("convert tmp/40jj11292497673.ps tmp/40jj11292497673.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  2.450   0.670   3.143