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(1280
+ ,1024
+ ,1024
+ ,768
+ ,1120
+ ,700
+ ,1024
+ ,768
+ ,1280
+ ,800
+ ,1280
+ ,1024
+ ,1280
+ ,800
+ ,1024
+ ,768
+ ,1280
+ ,800
+ ,1280
+ ,1024
+ ,1280
+ ,800
+ ,1280
+ ,800
+ ,1280
+ ,1024
+ ,1688
+ ,949
+ ,1440
+ ,900
+ ,1600
+ ,1200
+ ,1280
+ ,800
+ ,1280
+ ,800
+ ,1280
+ ,768
+ ,1176
+ ,735
+ ,1280
+ ,800
+ ,1503
+ ,845
+ ,1440
+ ,900
+ ,1366
+ ,768
+ ,1280
+ ,768
+ ,1024
+ ,768
+ ,1280
+ ,800
+ ,2560
+ ,1440
+ ,1280
+ ,768
+ ,1024
+ ,768
+ ,1280
+ ,1024
+ ,1280
+ ,800
+ ,1440
+ ,900
+ ,1280
+ ,800
+ ,1440
+ ,900
+ ,1024
+ ,768
+ ,1440
+ ,900
+ ,1143
+ ,857
+ ,1280
+ ,800
+ ,1440
+ ,900
+ ,1280
+ ,800
+ ,1366
+ ,768
+ ,1024
+ ,768
+ ,1408
+ ,880
+ ,1366
+ ,768
+ ,1176
+ ,735
+ ,1920
+ ,1200
+ ,1257
+ ,785
+ ,1280
+ ,800
+ ,1280
+ ,800
+ ,1440
+ ,900
+ ,1680
+ ,1050
+ ,1440
+ ,900
+ ,1024
+ ,768
+ ,1140
+ ,641
+ ,1280
+ ,1024
+ ,1280
+ ,800
+ ,1280
+ ,800
+ ,1280
+ ,800
+ ,1280
+ ,800
+ ,1440
+ ,900
+ ,1280
+ ,800
+ ,1152
+ ,864
+ ,1280
+ ,1024
+ ,1280
+ ,800
+ ,1440
+ ,900
+ ,1280
+ ,800
+ ,1280
+ ,1024
+ ,1440
+ ,900
+ ,1280
+ ,800
+ ,1280
+ ,800
+ ,1440
+ ,900
+ ,1280
+ ,800
+ ,1280
+ ,1024
+ ,1600
+ ,900
+ ,1024
+ ,768
+ ,1366
+ ,768
+ ,1280
+ ,800
+ ,1280
+ ,800
+ ,1440
+ ,900
+ ,1366
+ ,768
+ ,1280
+ ,800
+ ,1024
+ ,768
+ ,1280
+ ,800
+ ,1440
+ ,900
+ ,1280
+ ,800
+ ,1280
+ ,800
+ ,1408
+ ,880
+ ,1280
+ ,800
+ ,1600
+ ,900
+ ,1600
+ ,900
+ ,1680
+ ,1050
+ ,1440
+ ,900
+ ,1440
+ ,900
+ ,917
+ ,550
+ ,1280
+ ,800
+ ,1760
+ ,990
+ ,1280
+ ,800
+ ,1280
+ ,800
+ ,1280
+ ,800
+ ,1024
+ ,768
+ ,1366
+ ,768
+ ,1440
+ ,900
+ ,1280
+ ,800
+ ,1280
+ ,1024
+ ,1920
+ ,1080
+ ,1024
+ ,768
+ ,1024
+ ,768
+ ,1600
+ ,900
+ ,1117
+ ,698
+ ,1440
+ ,900
+ ,983
+ ,737
+ ,1024
+ ,768
+ ,1024
+ ,640
+ ,1280
+ ,800
+ ,1440
+ ,900
+ ,1280
+ ,800
+ ,1280
+ ,800
+ ,1280
+ ,800
+ ,1440
+ ,900
+ ,1280
+ ,800
+ ,1024
+ ,768
+ ,1024
+ ,768
+ ,1152
+ ,864
+ ,1280
+ ,768
+ ,1024
+ ,768
+ ,1366
+ ,768
+ ,1680
+ ,1050
+ ,1680
+ ,1050
+ ,1280
+ ,800
+ ,1366
+ ,768
+ ,1024
+ ,768
+ ,1440
+ ,900
+ ,1024
+ ,768
+ ,1280
+ ,800
+ ,1280
+ ,800
+ ,1280
+ ,800
+ ,1024
+ ,768
+ ,1280
+ ,800)
+ ,dim=c(2
+ ,139)
+ ,dimnames=list(c('br'
+ ,'gr')
+ ,1:139))
>  y <- array(NA,dim=c(2,139),dimnames=list(c('br','gr'),1:139))
>  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 = '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] "br"
> x[,par1]
  [1] 1280 1024 1120 1024 1280 1280 1280 1024 1280 1280 1280 1280 1280 1688 1440
 [16] 1600 1280 1280 1280 1176 1280 1503 1440 1366 1280 1024 1280 2560 1280 1024
 [31] 1280 1280 1440 1280 1440 1024 1440 1143 1280 1440 1280 1366 1024 1408 1366
 [46] 1176 1920 1257 1280 1280 1440 1680 1440 1024 1140 1280 1280 1280 1280 1280
 [61] 1440 1280 1152 1280 1280 1440 1280 1280 1440 1280 1280 1440 1280 1280 1600
 [76] 1024 1366 1280 1280 1440 1366 1280 1024 1280 1440 1280 1280 1408 1280 1600
 [91] 1600 1680 1440 1440  917 1280 1760 1280 1280 1280 1024 1366 1440 1280 1280
[106] 1920 1024 1024 1600 1117 1440  983 1024 1024 1280 1440 1280 1280 1280 1440
[121] 1280 1024 1024 1152 1280 1024 1366 1680 1680 1280 1366 1024 1440 1024 1280
[136] 1280 1280 1024 1280
> 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])

[ 917,1366) [1366,2560] 
         93          46 
> colnames(x)
[1] "br" "gr"
> colnames(x)[par1]
[1] "br"
> x[,par1]
  [1] [ 917,1366) [ 917,1366) [ 917,1366) [ 917,1366) [ 917,1366) [ 917,1366)
  [7] [ 917,1366) [ 917,1366) [ 917,1366) [ 917,1366) [ 917,1366) [ 917,1366)
 [13] [ 917,1366) [1366,2560] [1366,2560] [1366,2560] [ 917,1366) [ 917,1366)
 [19] [ 917,1366) [ 917,1366) [ 917,1366) [1366,2560] [1366,2560] [1366,2560]
 [25] [ 917,1366) [ 917,1366) [ 917,1366) [1366,2560] [ 917,1366) [ 917,1366)
 [31] [ 917,1366) [ 917,1366) [1366,2560] [ 917,1366) [1366,2560] [ 917,1366)
 [37] [1366,2560] [ 917,1366) [ 917,1366) [1366,2560] [ 917,1366) [1366,2560]
 [43] [ 917,1366) [1366,2560] [1366,2560] [ 917,1366) [1366,2560] [ 917,1366)
 [49] [ 917,1366) [ 917,1366) [1366,2560] [1366,2560] [1366,2560] [ 917,1366)
 [55] [ 917,1366) [ 917,1366) [ 917,1366) [ 917,1366) [ 917,1366) [ 917,1366)
 [61] [1366,2560] [ 917,1366) [ 917,1366) [ 917,1366) [ 917,1366) [1366,2560]
 [67] [ 917,1366) [ 917,1366) [1366,2560] [ 917,1366) [ 917,1366) [1366,2560]
 [73] [ 917,1366) [ 917,1366) [1366,2560] [ 917,1366) [1366,2560] [ 917,1366)
 [79] [ 917,1366) [1366,2560] [1366,2560] [ 917,1366) [ 917,1366) [ 917,1366)
 [85] [1366,2560] [ 917,1366) [ 917,1366) [1366,2560] [ 917,1366) [1366,2560]
 [91] [1366,2560] [1366,2560] [1366,2560] [1366,2560] [ 917,1366) [ 917,1366)
 [97] [1366,2560] [ 917,1366) [ 917,1366) [ 917,1366) [ 917,1366) [1366,2560]
[103] [1366,2560] [ 917,1366) [ 917,1366) [1366,2560] [ 917,1366) [ 917,1366)
[109] [1366,2560] [ 917,1366) [1366,2560] [ 917,1366) [ 917,1366) [ 917,1366)
[115] [ 917,1366) [1366,2560] [ 917,1366) [ 917,1366) [ 917,1366) [1366,2560]
[121] [ 917,1366) [ 917,1366) [ 917,1366) [ 917,1366) [ 917,1366) [ 917,1366)
[127] [1366,2560] [1366,2560] [1366,2560] [ 917,1366) [1366,2560] [ 917,1366)
[133] [1366,2560] [ 917,1366) [ 917,1366) [ 917,1366) [ 917,1366) [ 917,1366)
[139] [ 917,1366)
Levels: [ 917,1366) [1366,2560]
> 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/1no0t1292929301.tab") 
+ }
+ }
> m

	 Conditional inference tree with 2 terminal nodes

Response:  as.factor(br) 
Input:  gr 
Number of observations:  139 

1) gr <= 864; criterion = 1, statistic = 29.866
  2)*  weights = 92 
1) gr > 864
  3)*  weights = 47 
> postscript(file="/var/www/rcomp/tmp/2gfhe1292929301.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/3gfhe1292929301.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    2
  [2,]    1    1
  [3,]    1    1
  [4,]    1    1
  [5,]    1    1
  [6,]    1    2
  [7,]    1    1
  [8,]    1    1
  [9,]    1    1
 [10,]    1    2
 [11,]    1    1
 [12,]    1    1
 [13,]    1    2
 [14,]    2    2
 [15,]    2    2
 [16,]    2    2
 [17,]    1    1
 [18,]    1    1
 [19,]    1    1
 [20,]    1    1
 [21,]    1    1
 [22,]    2    1
 [23,]    2    2
 [24,]    2    1
 [25,]    1    1
 [26,]    1    1
 [27,]    1    1
 [28,]    2    2
 [29,]    1    1
 [30,]    1    1
 [31,]    1    2
 [32,]    1    1
 [33,]    2    2
 [34,]    1    1
 [35,]    2    2
 [36,]    1    1
 [37,]    2    2
 [38,]    1    1
 [39,]    1    1
 [40,]    2    2
 [41,]    1    1
 [42,]    2    1
 [43,]    1    1
 [44,]    2    2
 [45,]    2    1
 [46,]    1    1
 [47,]    2    2
 [48,]    1    1
 [49,]    1    1
 [50,]    1    1
 [51,]    2    2
 [52,]    2    2
 [53,]    2    2
 [54,]    1    1
 [55,]    1    1
 [56,]    1    2
 [57,]    1    1
 [58,]    1    1
 [59,]    1    1
 [60,]    1    1
 [61,]    2    2
 [62,]    1    1
 [63,]    1    1
 [64,]    1    2
 [65,]    1    1
 [66,]    2    2
 [67,]    1    1
 [68,]    1    2
 [69,]    2    2
 [70,]    1    1
 [71,]    1    1
 [72,]    2    2
 [73,]    1    1
 [74,]    1    2
 [75,]    2    2
 [76,]    1    1
 [77,]    2    1
 [78,]    1    1
 [79,]    1    1
 [80,]    2    2
 [81,]    2    1
 [82,]    1    1
 [83,]    1    1
 [84,]    1    1
 [85,]    2    2
 [86,]    1    1
 [87,]    1    1
 [88,]    2    2
 [89,]    1    1
 [90,]    2    2
 [91,]    2    2
 [92,]    2    2
 [93,]    2    2
 [94,]    2    2
 [95,]    1    1
 [96,]    1    1
 [97,]    2    2
 [98,]    1    1
 [99,]    1    1
[100,]    1    1
[101,]    1    1
[102,]    2    1
[103,]    2    2
[104,]    1    1
[105,]    1    2
[106,]    2    2
[107,]    1    1
[108,]    1    1
[109,]    2    2
[110,]    1    1
[111,]    2    2
[112,]    1    1
[113,]    1    1
[114,]    1    1
[115,]    1    1
[116,]    2    2
[117,]    1    1
[118,]    1    1
[119,]    1    1
[120,]    2    2
[121,]    1    1
[122,]    1    1
[123,]    1    1
[124,]    1    1
[125,]    1    1
[126,]    1    1
[127,]    2    1
[128,]    2    2
[129,]    2    2
[130,]    1    1
[131,]    2    1
[132,]    1    1
[133,]    2    2
[134,]    1    1
[135,]    1    1
[136,]    1    1
[137,]    1    1
[138,]    1    1
[139,]    1    1
             
              [ 917,1366) [1366,2560]
  [ 917,1366)          83          10
  [1366,2560]           9          37
> postscript(file="/var/www/rcomp/tmp/486zh1292929301.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/55yfq1292929301.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/6fpet1292929301.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/7qhve1292929301.tab") 
+ }
> 
> try(system("convert tmp/2gfhe1292929301.ps tmp/2gfhe1292929301.png",intern=TRUE))
character(0)
> try(system("convert tmp/3gfhe1292929301.ps tmp/3gfhe1292929301.png",intern=TRUE))
character(0)
> try(system("convert tmp/486zh1292929301.ps tmp/486zh1292929301.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  1.940   0.270   2.206