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 '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(3030.29
+ ,25.64
+ ,2803.47
+ ,27.97
+ ,2767.63
+ ,27.62
+ ,2882.6
+ ,23.31
+ ,2863.36
+ ,29.07
+ ,2897.06
+ ,29.58
+ ,3012.61
+ ,28.63
+ ,3142.95
+ ,29.92
+ ,3032.93
+ ,32.68
+ ,3045.78
+ ,31.54
+ ,3110.52
+ ,32.43
+ ,3013.24
+ ,26.54
+ ,2987.1
+ ,25.85
+ ,2995.55
+ ,27.6
+ ,2833.18
+ ,25.71
+ ,2848.96
+ ,25.38
+ ,2794.83
+ ,28.57
+ ,2845.26
+ ,27.64
+ ,2915.03
+ ,25.36
+ ,2892.63
+ ,25.9
+ ,2604.42
+ ,26.29
+ ,2641.65
+ ,21.74
+ ,2659.81
+ ,19.2
+ ,2638.53
+ ,19.32
+ ,2720.25
+ ,19.82
+ ,2745.88
+ ,20.36
+ ,2735.7
+ ,24.31
+ ,2811.7
+ ,25.97
+ ,2799.43
+ ,25.61
+ ,2555.28
+ ,24.67
+ ,2304.98
+ ,25.59
+ ,2214.95
+ ,26.09
+ ,2065.81
+ ,28.37
+ ,1940.49
+ ,27.34
+ ,2042
+ ,24.46
+ ,1995.37
+ ,27.46
+ ,1946.81
+ ,30.23
+ ,1765.9
+ ,32.33
+ ,1635.25
+ ,29.87
+ ,1833.42
+ ,24.87
+ ,1910.43
+ ,25.48
+ ,1959.67
+ ,27.28
+ ,1969.6
+ ,28.24
+ ,2061.41
+ ,29.58
+ ,2093.48
+ ,26.95
+ ,2120.88
+ ,29.08
+ ,2174.56
+ ,28.76
+ ,2196.72
+ ,29.59
+ ,2350.44
+ ,30.7
+ ,2440.25
+ ,30.52
+ ,2408.64
+ ,32.67
+ ,2472.81
+ ,33.19
+ ,2407.6
+ ,37.13
+ ,2454.62
+ ,35.54
+ ,2448.05
+ ,37.75
+ ,2497.84
+ ,41.84
+ ,2645.64
+ ,42.94
+ ,2756.76
+ ,49.14
+ ,2849.27
+ ,44.61
+ ,2921.44
+ ,40.22
+ ,2981.85
+ ,44.23
+ ,3080.58
+ ,45.85
+ ,3106.22
+ ,53.38
+ ,3119.31
+ ,53.26
+ ,3061.26
+ ,51.8
+ ,3097.31
+ ,55.3
+ ,3161.69
+ ,57.81
+ ,3257.16
+ ,63.96
+ ,3277.01
+ ,63.77
+ ,3295.32
+ ,59.15
+ ,3363.99
+ ,56.12
+ ,3494.17
+ ,57.42
+ ,3667.03
+ ,63.52
+ ,3813.06
+ ,61.71
+ ,3917.96
+ ,63.01
+ ,3895.51
+ ,68.18
+ ,3801.06
+ ,72.03
+ ,3570.12
+ ,69.75
+ ,3701.61
+ ,74.41
+ ,3862.27
+ ,74.33
+ ,3970.1
+ ,64.24
+ ,4138.52
+ ,60.03
+ ,4199.75
+ ,59.44
+ ,4290.89
+ ,62.5
+ ,4443.91
+ ,55.04
+ ,4502.64
+ ,58.34
+ ,4356.98
+ ,61.92
+ ,4591.27
+ ,67.65
+ ,4696.96
+ ,67.68
+ ,4621.4
+ ,70.3
+ ,4562.84
+ ,75.26
+ ,4202.52
+ ,71.44
+ ,4296.49
+ ,76.36
+ ,4435.23
+ ,81.71
+ ,4105.18
+ ,92.6
+ ,4116.68
+ ,90.6
+ ,3844.49
+ ,92.23
+ ,3720.98
+ ,94.09
+ ,3674.4
+ ,102.79
+ ,3857.62
+ ,109.65
+ ,3801.06
+ ,124.05
+ ,3504.37
+ ,132.69
+ ,3032.6
+ ,135.81
+ ,3047.03
+ ,116.07
+ ,2962.34
+ ,101.42
+ ,2197.82
+ ,75.73
+ ,2014.45
+ ,55.48
+ ,1862.83
+ ,43.8
+ ,1905.41
+ ,45.29)
+ ,dim=c(2
+ ,109)
+ ,dimnames=list(c('Aandelenkoers'
+ ,'Olieprijs')
+ ,1:109))
>  y <- array(NA,dim=c(2,109),dimnames=list(c('Aandelenkoers','Olieprijs'),1:109))
>  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] "Aandelenkoers"
> x[,par1]
  [1] 3030.29 2803.47 2767.63 2882.60 2863.36 2897.06 3012.61 3142.95 3032.93
 [10] 3045.78 3110.52 3013.24 2987.10 2995.55 2833.18 2848.96 2794.83 2845.26
 [19] 2915.03 2892.63 2604.42 2641.65 2659.81 2638.53 2720.25 2745.88 2735.70
 [28] 2811.70 2799.43 2555.28 2304.98 2214.95 2065.81 1940.49 2042.00 1995.37
 [37] 1946.81 1765.90 1635.25 1833.42 1910.43 1959.67 1969.60 2061.41 2093.48
 [46] 2120.88 2174.56 2196.72 2350.44 2440.25 2408.64 2472.81 2407.60 2454.62
 [55] 2448.05 2497.84 2645.64 2756.76 2849.27 2921.44 2981.85 3080.58 3106.22
 [64] 3119.31 3061.26 3097.31 3161.69 3257.16 3277.01 3295.32 3363.99 3494.17
 [73] 3667.03 3813.06 3917.96 3895.51 3801.06 3570.12 3701.61 3862.27 3970.10
 [82] 4138.52 4199.75 4290.89 4443.91 4502.64 4356.98 4591.27 4696.96 4621.40
 [91] 4562.84 4202.52 4296.49 4435.23 4105.18 4116.68 3844.49 3720.98 3674.40
[100] 3857.62 3801.06 3504.37 3032.60 3047.03 2962.34 2197.82 2014.45 1862.83
[109] 1905.41
> 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])

[1635,2962) [2962,4697] 
         55          54 
> colnames(x)
[1] "Aandelenkoers" "Olieprijs"    
> colnames(x)[par1]
[1] "Aandelenkoers"
> x[,par1]
  [1] [2962,4697] [1635,2962) [1635,2962) [1635,2962) [1635,2962) [1635,2962)
  [7] [2962,4697] [2962,4697] [2962,4697] [2962,4697] [2962,4697] [2962,4697]
 [13] [2962,4697] [2962,4697] [1635,2962) [1635,2962) [1635,2962) [1635,2962)
 [19] [1635,2962) [1635,2962) [1635,2962) [1635,2962) [1635,2962) [1635,2962)
 [25] [1635,2962) [1635,2962) [1635,2962) [1635,2962) [1635,2962) [1635,2962)
 [31] [1635,2962) [1635,2962) [1635,2962) [1635,2962) [1635,2962) [1635,2962)
 [37] [1635,2962) [1635,2962) [1635,2962) [1635,2962) [1635,2962) [1635,2962)
 [43] [1635,2962) [1635,2962) [1635,2962) [1635,2962) [1635,2962) [1635,2962)
 [49] [1635,2962) [1635,2962) [1635,2962) [1635,2962) [1635,2962) [1635,2962)
 [55] [1635,2962) [1635,2962) [1635,2962) [1635,2962) [1635,2962) [1635,2962)
 [61] [2962,4697] [2962,4697] [2962,4697] [2962,4697] [2962,4697] [2962,4697]
 [67] [2962,4697] [2962,4697] [2962,4697] [2962,4697] [2962,4697] [2962,4697]
 [73] [2962,4697] [2962,4697] [2962,4697] [2962,4697] [2962,4697] [2962,4697]
 [79] [2962,4697] [2962,4697] [2962,4697] [2962,4697] [2962,4697] [2962,4697]
 [85] [2962,4697] [2962,4697] [2962,4697] [2962,4697] [2962,4697] [2962,4697]
 [91] [2962,4697] [2962,4697] [2962,4697] [2962,4697] [2962,4697] [2962,4697]
 [97] [2962,4697] [2962,4697] [2962,4697] [2962,4697] [2962,4697] [2962,4697]
[103] [2962,4697] [2962,4697] [2962,4697] [1635,2962) [1635,2962) [1635,2962)
[109] [1635,2962)
Levels: [1635,2962) [2962,4697]
> 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/1p7qv1291917029.tab") 
+ }
+ }
           m.ct.i.pred
m.ct.i.actu   1   2
          1 472  18
          2 101 398
[1] 0.9632653
[1] 0.7975952
[1] 0.8796764
           m.ct.x.pred
m.ct.x.actu  1  2
          1 58  2
          2  9 32
[1] 0.9666667
[1] 0.7804878
[1] 0.8910891
> m

	 Conditional inference tree with 2 terminal nodes

Response:  as.factor(Aandelenkoers) 
Input:  Olieprijs 
Number of observations:  109 

1) Olieprijs <= 49.14; criterion = 1, statistic = 48.201
  2)*  weights = 64 
1) Olieprijs > 49.14
  3)*  weights = 45 
> postscript(file="/var/www/rcomp/tmp/2p7qv1291917029.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/3p7qv1291917029.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    1
  [2,]    1    1
  [3,]    1    1
  [4,]    1    1
  [5,]    1    1
  [6,]    1    1
  [7,]    2    1
  [8,]    2    1
  [9,]    2    1
 [10,]    2    1
 [11,]    2    1
 [12,]    2    1
 [13,]    2    1
 [14,]    2    1
 [15,]    1    1
 [16,]    1    1
 [17,]    1    1
 [18,]    1    1
 [19,]    1    1
 [20,]    1    1
 [21,]    1    1
 [22,]    1    1
 [23,]    1    1
 [24,]    1    1
 [25,]    1    1
 [26,]    1    1
 [27,]    1    1
 [28,]    1    1
 [29,]    1    1
 [30,]    1    1
 [31,]    1    1
 [32,]    1    1
 [33,]    1    1
 [34,]    1    1
 [35,]    1    1
 [36,]    1    1
 [37,]    1    1
 [38,]    1    1
 [39,]    1    1
 [40,]    1    1
 [41,]    1    1
 [42,]    1    1
 [43,]    1    1
 [44,]    1    1
 [45,]    1    1
 [46,]    1    1
 [47,]    1    1
 [48,]    1    1
 [49,]    1    1
 [50,]    1    1
 [51,]    1    1
 [52,]    1    1
 [53,]    1    1
 [54,]    1    1
 [55,]    1    1
 [56,]    1    1
 [57,]    1    1
 [58,]    1    1
 [59,]    1    1
 [60,]    1    1
 [61,]    2    1
 [62,]    2    1
 [63,]    2    2
 [64,]    2    2
 [65,]    2    2
 [66,]    2    2
 [67,]    2    2
 [68,]    2    2
 [69,]    2    2
 [70,]    2    2
 [71,]    2    2
 [72,]    2    2
 [73,]    2    2
 [74,]    2    2
 [75,]    2    2
 [76,]    2    2
 [77,]    2    2
 [78,]    2    2
 [79,]    2    2
 [80,]    2    2
 [81,]    2    2
 [82,]    2    2
 [83,]    2    2
 [84,]    2    2
 [85,]    2    2
 [86,]    2    2
 [87,]    2    2
 [88,]    2    2
 [89,]    2    2
 [90,]    2    2
 [91,]    2    2
 [92,]    2    2
 [93,]    2    2
 [94,]    2    2
 [95,]    2    2
 [96,]    2    2
 [97,]    2    2
 [98,]    2    2
 [99,]    2    2
[100,]    2    2
[101,]    2    2
[102,]    2    2
[103,]    2    2
[104,]    2    2
[105,]    2    2
[106,]    1    2
[107,]    1    2
[108,]    1    1
[109,]    1    1
             
              [1635,2962) [2962,4697]
  [1635,2962)          53           2
  [2962,4697]          11          43
> postscript(file="/var/www/rcomp/tmp/4hgpx1291917029.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/5d8561291917029.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/6hqlu1291917029.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/7903x1291917029.tab") 
+ }
> 
> try(system("convert tmp/2p7qv1291917029.ps tmp/2p7qv1291917029.png",intern=TRUE))
character(0)
> try(system("convert tmp/3p7qv1291917029.ps tmp/3p7qv1291917029.png",intern=TRUE))
character(0)
> try(system("convert tmp/4hgpx1291917029.ps tmp/4hgpx1291917029.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  2.260   0.600   2.832