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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Type 'demo()' for some demos, 'help()' for on-line help, or
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Type 'q()' to quit R.

> x <- array(list(97.06
+ ,21454
+ ,631923
+ ,130678
+ ,97.73
+ ,23899
+ ,654294
+ ,120877
+ ,98
+ ,24939
+ ,671833
+ ,137114
+ ,97.76
+ ,23580
+ ,586840
+ ,134406
+ ,97.48
+ ,24562
+ ,600969
+ ,120262
+ ,97.77
+ ,24696
+ ,625568
+ ,130846
+ ,97.96
+ ,23785
+ ,558110
+ ,120343
+ ,98.22
+ ,23812
+ ,630577
+ ,98881
+ ,98.51
+ ,21917
+ ,628654
+ ,115678
+ ,98.19
+ ,19713
+ ,603184
+ ,120796
+ ,98.37
+ ,19282
+ ,656255
+ ,94261
+ ,98.31
+ ,18788
+ ,600730
+ ,89151
+ ,98.6
+ ,21453
+ ,670326
+ ,119880
+ ,98.96
+ ,24482
+ ,678423
+ ,131468
+ ,99.11
+ ,27474
+ ,641502
+ ,155089
+ ,99.64
+ ,27264
+ ,625311
+ ,149581
+ ,100.02
+ ,27349
+ ,628177
+ ,122788
+ ,99.98
+ ,30632
+ ,589767
+ ,143900
+ ,100.32
+ ,29429
+ ,582471
+ ,112115
+ ,100.44
+ ,30084
+ ,636248
+ ,109600
+ ,100.51
+ ,26290
+ ,599885
+ ,117446
+ ,101
+ ,24379
+ ,621694
+ ,118456
+ ,100.88
+ ,23335
+ ,637406
+ ,101901
+ ,100.55
+ ,21346
+ ,595994
+ ,89940
+ ,100.82
+ ,21106
+ ,696308
+ ,129143
+ ,101.5
+ ,24514
+ ,674201
+ ,126102
+ ,102.15
+ ,28353
+ ,648861
+ ,143048
+ ,102.39
+ ,30805
+ ,649605
+ ,142258
+ ,102.54
+ ,31348
+ ,672392
+ ,131011
+ ,102.85
+ ,34556
+ ,598396
+ ,146471
+ ,103.47
+ ,33855
+ ,613177
+ ,114073
+ ,103.56
+ ,34787
+ ,638104
+ ,114642
+ ,103.69
+ ,32529
+ ,615632
+ ,118226
+ ,103.49
+ ,29998
+ ,634465
+ ,111338
+ ,103.47
+ ,29257
+ ,638686
+ ,108701
+ ,103.45
+ ,28155
+ ,604243
+ ,80512
+ ,103.48
+ ,30466
+ ,706669
+ ,146865
+ ,103.93
+ ,35704
+ ,677185
+ ,137179
+ ,103.89
+ ,39327
+ ,644328
+ ,166536
+ ,104.4
+ ,39351
+ ,664825
+ ,137070
+ ,104.79
+ ,42234
+ ,605707
+ ,127090
+ ,104.77
+ ,43630
+ ,600136
+ ,139966
+ ,105.13
+ ,43722
+ ,612166
+ ,122243
+ ,105.26
+ ,43121
+ ,599659
+ ,109097
+ ,104.96
+ ,37985
+ ,634210
+ ,116591
+ ,104.75
+ ,37135
+ ,618234
+ ,111964
+ ,105.01
+ ,34646
+ ,613576
+ ,109754
+ ,105.15
+ ,33026
+ ,627200
+ ,77609
+ ,105.2
+ ,35087
+ ,668973
+ ,138445
+ ,105.77
+ ,38846
+ ,651479
+ ,127901
+ ,105.78
+ ,42013
+ ,619661
+ ,156615
+ ,106.26
+ ,43908
+ ,644260
+ ,133264
+ ,106.13
+ ,42868
+ ,579936
+ ,143521
+ ,106.12
+ ,44423
+ ,601752
+ ,152139
+ ,106.57
+ ,44167
+ ,595376
+ ,131523
+ ,106.44
+ ,43636
+ ,588902
+ ,113925
+ ,106.54
+ ,44382
+ ,634341
+ ,86495
+ ,107.1
+ ,42142
+ ,594305
+ ,127877
+ ,108.1
+ ,43452
+ ,606200
+ ,107017
+ ,108.4
+ ,36912
+ ,610926
+ ,78716
+ ,108.84
+ ,42413
+ ,633685
+ ,138278
+ ,109.62
+ ,45344
+ ,639696
+ ,144238
+ ,110.42
+ ,44873
+ ,659451
+ ,143679
+ ,110.67
+ ,47510
+ ,593248
+ ,159932
+ ,111.66
+ ,49554
+ ,606677
+ ,136781
+ ,112.28
+ ,47369
+ ,599434
+ ,148173
+ ,112.87
+ ,45998
+ ,569578
+ ,125673
+ ,112.18
+ ,48140
+ ,629873
+ ,105573
+ ,112.36
+ ,48441
+ ,613438
+ ,122405
+ ,112.16
+ ,44928
+ ,604172
+ ,128045
+ ,111.49
+ ,40454
+ ,658328
+ ,94467
+ ,111.25
+ ,38661
+ ,612633
+ ,85573
+ ,111.36
+ ,37246
+ ,707372
+ ,121501
+ ,111.74
+ ,36843
+ ,739770
+ ,125074
+ ,111.1
+ ,36424
+ ,777535
+ ,144979
+ ,111.33
+ ,37594
+ ,685030
+ ,142120
+ ,111.25
+ ,38144
+ ,730234
+ ,124213
+ ,111.04
+ ,38737
+ ,714154
+ ,144407
+ ,110.97
+ ,34560
+ ,630872
+ ,125170
+ ,111.31
+ ,36080
+ ,719492
+ ,109267
+ ,111.02
+ ,33508
+ ,677023
+ ,122354
+ ,111.07
+ ,35462
+ ,679272
+ ,122589
+ ,111.36
+ ,33374
+ ,718317
+ ,104982
+ ,111.54
+ ,32110
+ ,645672
+ ,90542)
+ ,dim=c(4
+ ,84)
+ ,dimnames=list(c('conusmentenprijsindex'
+ ,'vacatures'
+ ,'werkloosheid'
+ ,'inschrijvingen')
+ ,1:84))
>  y <- array(NA,dim=c(4,84),dimnames=list(c('conusmentenprijsindex','vacatures','werkloosheid','inschrijvingen'),1:84))
>  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 = '3'
> 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] "conusmentenprijsindex"
> x[,par1]
 [1]  97.06  97.73  98.00  97.76  97.48  97.77  97.96  98.22  98.51  98.19
[11]  98.37  98.31  98.60  98.96  99.11  99.64 100.02  99.98 100.32 100.44
[21] 100.51 101.00 100.88 100.55 100.82 101.50 102.15 102.39 102.54 102.85
[31] 103.47 103.56 103.69 103.49 103.47 103.45 103.48 103.93 103.89 104.40
[41] 104.79 104.77 105.13 105.26 104.96 104.75 105.01 105.15 105.20 105.77
[51] 105.78 106.26 106.13 106.12 106.57 106.44 106.54 107.10 108.10 108.40
[61] 108.84 109.62 110.42 110.67 111.66 112.28 112.87 112.18 112.36 112.16
[71] 111.49 111.25 111.36 111.74 111.10 111.33 111.25 111.04 110.97 111.31
[81] 111.02 111.07 111.36 111.54
> 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])

[ 97.1,103) [102.5,107) [106.6,113] 
         28          28          28 
> colnames(x)
[1] "conusmentenprijsindex" "vacatures"             "werkloosheid"         
[4] "inschrijvingen"       
> colnames(x)[par1]
[1] "conusmentenprijsindex"
> x[,par1]
 [1] [ 97.1,103) [ 97.1,103) [ 97.1,103) [ 97.1,103) [ 97.1,103) [ 97.1,103)
 [7] [ 97.1,103) [ 97.1,103) [ 97.1,103) [ 97.1,103) [ 97.1,103) [ 97.1,103)
[13] [ 97.1,103) [ 97.1,103) [ 97.1,103) [ 97.1,103) [ 97.1,103) [ 97.1,103)
[19] [ 97.1,103) [ 97.1,103) [ 97.1,103) [ 97.1,103) [ 97.1,103) [ 97.1,103)
[25] [ 97.1,103) [ 97.1,103) [ 97.1,103) [ 97.1,103) [102.5,107) [102.5,107)
[31] [102.5,107) [102.5,107) [102.5,107) [102.5,107) [102.5,107) [102.5,107)
[37] [102.5,107) [102.5,107) [102.5,107) [102.5,107) [102.5,107) [102.5,107)
[43] [102.5,107) [102.5,107) [102.5,107) [102.5,107) [102.5,107) [102.5,107)
[49] [102.5,107) [102.5,107) [102.5,107) [102.5,107) [102.5,107) [102.5,107)
[55] [106.6,113] [102.5,107) [102.5,107) [106.6,113] [106.6,113] [106.6,113]
[61] [106.6,113] [106.6,113] [106.6,113] [106.6,113] [106.6,113] [106.6,113]
[67] [106.6,113] [106.6,113] [106.6,113] [106.6,113] [106.6,113] [106.6,113]
[73] [106.6,113] [106.6,113] [106.6,113] [106.6,113] [106.6,113] [106.6,113]
[79] [106.6,113] [106.6,113] [106.6,113] [106.6,113] [106.6,113] [106.6,113]
Levels: [ 97.1,103) [102.5,107) [106.6,113]
> 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/1tp111323526001.tab") 
+ }
+ }
           m.ct.i.pred
m.ct.i.actu   1   2   3
          1 250   0   0
          2  36  45 167
          3   0  29 221
[1] 1
[1] 0.1814516
[1] 0.884
[1] 0.6898396
           m.ct.x.pred
m.ct.x.actu  1  2  3
          1 29  1  0
          2  4  3 25
          3  0  9 21
[1] 0.9666667
[1] 0.09375
[1] 0.7
[1] 0.576087
> m

	 Conditional inference tree with 3 terminal nodes

Response:  as.factor(conusmentenprijsindex) 
Inputs:  vacatures, werkloosheid, inschrijvingen 
Number of observations:  84 

1) vacatures <= 30805; criterion = 1, statistic = 57.55
  2) vacatures <= 27474; criterion = 0.968, statistic = 6.526
    3)*  weights = 23 
  2) vacatures > 27474
    4)*  weights = 9 
1) vacatures > 30805
  5)*  weights = 52 
> postscript(file="/var/wessaorg/rcomp/tmp/2all91323526001.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/37jdj1323526001.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,]    1    1
 [2,]    1    1
 [3,]    1    1
 [4,]    1    1
 [5,]    1    1
 [6,]    1    1
 [7,]    1    1
 [8,]    1    1
 [9,]    1    1
[10,]    1    1
[11,]    1    1
[12,]    1    1
[13,]    1    1
[14,]    1    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,]    2    3
[30,]    2    3
[31,]    2    3
[32,]    2    3
[33,]    2    3
[34,]    2    1
[35,]    2    1
[36,]    2    1
[37,]    2    1
[38,]    2    3
[39,]    2    3
[40,]    2    3
[41,]    2    3
[42,]    2    3
[43,]    2    3
[44,]    2    3
[45,]    2    3
[46,]    2    3
[47,]    2    3
[48,]    2    3
[49,]    2    3
[50,]    2    3
[51,]    2    3
[52,]    2    3
[53,]    2    3
[54,]    2    3
[55,]    3    3
[56,]    2    3
[57,]    2    3
[58,]    3    3
[59,]    3    3
[60,]    3    3
[61,]    3    3
[62,]    3    3
[63,]    3    3
[64,]    3    3
[65,]    3    3
[66,]    3    3
[67,]    3    3
[68,]    3    3
[69,]    3    3
[70,]    3    3
[71,]    3    3
[72,]    3    3
[73,]    3    3
[74,]    3    3
[75,]    3    3
[76,]    3    3
[77,]    3    3
[78,]    3    3
[79,]    3    3
[80,]    3    3
[81,]    3    3
[82,]    3    3
[83,]    3    3
[84,]    3    3
             
              [ 97.1,103) [102.5,107) [106.6,113]
  [ 97.1,103)          28           0           0
  [102.5,107)           4           0          24
  [106.6,113]           0           0          28
> postscript(file="/var/wessaorg/rcomp/tmp/44qm41323526001.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/5dvcf1323526001.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/6c0kg1323526001.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/748871323526001.tab") 
+ }
> 
> try(system("convert tmp/2all91323526001.ps tmp/2all91323526001.png",intern=TRUE))
character(0)
> try(system("convert tmp/37jdj1323526001.ps tmp/37jdj1323526001.png",intern=TRUE))
character(0)
> try(system("convert tmp/44qm41323526001.ps tmp/44qm41323526001.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  3.100   0.192   3.333