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Type 'q()' to quit R. > x <- array(list(9506 + ,1775 + ,8704 + ,2197 + ,10079 + ,2920 + ,8993 + ,4240 + ,9957 + ,5415 + ,10240 + ,6136 + ,10098 + ,6719 + ,10090 + ,6234 + ,9867 + ,7152 + ,9736 + ,3646 + ,9040 + ,2165 + ,9232 + ,2803 + ,9520 + ,1615 + ,9217 + ,2350 + ,9868 + ,3350 + ,9455 + ,3536 + ,9984 + ,5834 + ,9556 + ,6767 + ,10190 + ,5993 + ,9906 + ,7276 + ,9824 + ,5641 + ,9972 + ,3477 + ,9185 + ,2247 + ,9765 + ,2466 + ,9838 + ,1567 + ,9084 + ,2237 + ,9643 + ,2598 + ,10051 + ,3729 + ,9987 + ,5715 + ,9827 + ,5776 + ,10491 + ,5852 + ,9722 + ,6878 + ,9472 + ,5488 + ,9728 + ,3583 + ,8510 + ,2054 + ,9511 + ,2282 + ,9492 + ,1552 + ,8638 + ,2261 + ,9792 + ,2446 + ,9605 + ,3519 + ,9237 + ,5161 + ,9533 + ,5085 + ,10293 + ,5711 + ,9938 + ,6057 + ,9984 + ,5224 + ,9563 + ,3363 + ,8871 + ,1899 + ,9301 + ,2115 + ,9215 + ,1491 + ,8834 + ,2061 + ,9998 + ,2419 + ,9604 + ,3430 + ,9507 + ,4778 + ,9718 + ,4862 + ,10095 + ,6176 + ,9583 + ,5664 + ,9883 + ,5529 + ,9365 + ,3418 + ,8919 + ,1941 + ,9449 + ,2402 + ,9769 + ,1579 + ,9321 + ,2146 + ,9939 + ,2462 + ,9336 + ,3695 + ,10195 + ,4831 + ,9464 + ,5134 + ,10010 + ,6250 + ,10213 + ,5760 + ,9563 + ,6249 + ,9890 + ,2917 + ,9305 + ,1741 + ,9391 + ,2359 + ,9743 + ,1511 + ,8587 + ,2059 + ,9731 + ,2635 + ,9563 + ,2867 + ,9998 + ,4403 + ,9437 + ,5720 + ,10038 + ,4502 + ,9918 + ,5749 + ,9252 + ,5627 + ,9737 + ,2846 + ,9035 + ,1762 + ,9133 + ,2429 + ,9487 + ,1169 + ,8700 + ,2154 + ,9627 + ,2249 + ,8947 + ,2687 + ,9283 + ,4359 + ,8829 + ,5382 + ,9947 + ,4459 + ,9628 + ,6398 + ,9318 + ,4596 + ,9605 + ,3024 + ,8640 + ,1887 + ,9214 + ,2070 + ,9676 + ,1351 + ,8642 + ,2218 + ,9402 + ,2461 + ,9610 + ,3028 + ,9294 + ,4784 + ,9448 + ,4975 + ,10319 + ,4607 + ,9548 + ,6249 + ,9801 + ,4809 + ,9596 + ,3157 + ,8923 + ,1910 + ,9746 + ,2228 + ,9829 + ,1594 + ,9125 + ,2467 + ,9782 + ,2222 + ,9441 + ,3607 + ,9162 + ,4685 + ,9915 + ,4962 + ,10444 + ,5770 + ,10209 + ,5480 + ,9985 + ,5000 + ,9842 + ,3228 + ,9429 + ,1993 + ,10132 + ,2288 + ,9849 + ,1588 + ,9172 + ,2105 + ,10313 + ,2191 + ,9819 + ,3591 + ,9955 + ,4668 + ,10048 + ,4885 + ,10082 + ,5822 + ,10541 + ,5599 + ,10208 + ,5340 + ,10233 + ,3082 + ,9439 + ,2010 + ,9963 + ,2301) + ,dim=c(2 + ,132) + ,dimnames=list(c('births' + ,'marriages') + ,1:132)) > y <- array(NA,dim=c(2,132),dimnames=list(c('births','marriages'),1:132)) > 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$_version), Office for Research Development and Education, URL http://www.wessa.net/rwasp_YOURPAGE.wasp/ > #Source of accompanying publication: > #Technical description: > library(party) Loading required package: survival Loading required package: splines Loading required package: grid Loading required package: modeltools Loading required package: stats4 Loading required package: coin Loading required package: mvtnorm Loading required package: zoo Attaching package: 'zoo' The following object(s) are masked from package:base : as.Date.numeric Loading required package: sandwich Loading required package: strucchange Loading required package: vcd Loading required package: MASS Loading required package: colorspace > library(Hmisc) Attaching package: 'Hmisc' The following object(s) are masked from package:survival : untangle.specials The following object(s) are masked from package:base : format.pval, round.POSIXt, trunc.POSIXt, units > par1 <- as.numeric(par1) > par3 <- as.numeric(par3) > x <- data.frame(t(y)) > is.data.frame(x) [1] TRUE > x <- x[!is.na(x[,par1]),] > k <- length(x[1,]) > n <- length(x[,1]) > colnames(x)[par1] [1] "births" > x[,par1] [1] 9506 8704 10079 8993 9957 10240 10098 10090 9867 9736 9040 9232 [13] 9520 9217 9868 9455 9984 9556 10190 9906 9824 9972 9185 9765 [25] 9838 9084 9643 10051 9987 9827 10491 9722 9472 9728 8510 9511 [37] 9492 8638 9792 9605 9237 9533 10293 9938 9984 9563 8871 9301 [49] 9215 8834 9998 9604 9507 9718 10095 9583 9883 9365 8919 9449 [61] 9769 9321 9939 9336 10195 9464 10010 10213 9563 9890 9305 9391 [73] 9743 8587 9731 9563 9998 9437 10038 9918 9252 9737 9035 9133 [85] 9487 8700 9627 8947 9283 8829 9947 9628 9318 9605 8640 9214 [97] 9676 8642 9402 9610 9294 9448 10319 9548 9801 9596 8923 9746 [109] 9829 9125 9782 9441 9162 9915 10444 10209 9985 9842 9429 10132 [121] 9849 9172 10313 9819 9955 10048 10082 10541 10208 10233 9439 9963 > if (par2 == 'kmeans') { + cl <- kmeans(x[,par1], par3) + print(cl) + clm <- matrix(cbind(cl$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]) 8510 8587 8638 8640 8642 8700 8704 8829 8834 8871 8919 8923 8947 1 1 1 1 1 1 1 1 1 1 1 1 1 8993 9035 9040 9084 9125 9133 9162 9172 9185 9214 9215 9217 9232 1 1 1 1 1 1 1 1 1 1 1 1 1 9237 9252 9283 9294 9301 9305 9318 9321 9336 9365 9391 9402 9429 1 1 1 1 1 1 1 1 1 1 1 1 1 9437 9439 9441 9448 9449 9455 9464 9472 9487 9492 9506 9507 9511 1 1 1 1 1 1 1 1 1 1 1 1 1 9520 9533 9548 9556 9563 9583 9596 9604 9605 9610 9627 9628 9643 1 1 1 1 3 1 1 1 2 1 1 1 1 9676 9718 9722 9728 9731 9736 9737 9743 9746 9765 9769 9782 9792 1 1 1 1 1 1 1 1 1 1 1 1 1 9801 9819 9824 9827 9829 9838 9842 9849 9867 9868 9883 9890 9906 1 1 1 1 1 1 1 1 1 1 1 1 1 9915 9918 9938 9939 9947 9955 9957 9963 9972 9984 9985 9987 9998 1 1 1 1 1 1 1 1 1 2 1 1 2 10010 10038 10048 10051 10079 10082 10090 10095 10098 10132 10190 10195 10208 1 1 1 1 1 1 1 1 1 1 1 1 1 10209 10213 10233 10240 10293 10313 10319 10444 10491 10541 1 1 1 1 1 1 1 1 1 1 > colnames(x) [1] "births" "marriages" > colnames(x)[par1] [1] "births" > x[,par1] [1] 9506 8704 10079 8993 9957 10240 10098 10090 9867 9736 9040 9232 [13] 9520 9217 9868 9455 9984 9556 10190 9906 9824 9972 9185 9765 [25] 9838 9084 9643 10051 9987 9827 10491 9722 9472 9728 8510 9511 [37] 9492 8638 9792 9605 9237 9533 10293 9938 9984 9563 8871 9301 [49] 9215 8834 9998 9604 9507 9718 10095 9583 9883 9365 8919 9449 [61] 9769 9321 9939 9336 10195 9464 10010 10213 9563 9890 9305 9391 [73] 9743 8587 9731 9563 9998 9437 10038 9918 9252 9737 9035 9133 [85] 9487 8700 9627 8947 9283 8829 9947 9628 9318 9605 8640 9214 [97] 9676 8642 9402 9610 9294 9448 10319 9548 9801 9596 8923 9746 [109] 9829 9125 9782 9441 9162 9915 10444 10209 9985 9842 9429 10132 [121] 9849 9172 10313 9819 9955 10048 10082 10541 10208 10233 9439 9963 > if (par2 == 'none') { + m <- ctree(as.formula(paste(colnames(x)[par1],' ~ .',sep='')),data = x) + } > > #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab > load(file="/var/www/html/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/html/rcomp/tmp/1orl11293211897.tab") + } + } > m Conditional inference tree with 4 terminal nodes Response: births Input: marriages Number of observations: 132 1) marriages <= 2261; criterion = 1, statistic = 29.15 2) marriages <= 1615; criterion = 0.977, statistic = 5.172 3)* weights = 10 2) marriages > 1615 4)* weights = 27 1) marriages > 2261 5) marriages <= 5382; criterion = 0.997, statistic = 8.944 6)* weights = 63 5) marriages > 5382 7)* weights = 32 > postscript(file="/var/www/html/rcomp/tmp/2orl11293211897.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/html/rcomp/tmp/3orl11293211897.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 9506 9128.407 377.59259 2 8704 9128.407 -424.40741 3 10079 9654.714 424.28571 4 8993 9654.714 -661.71429 5 9957 9932.750 24.25000 6 10240 9932.750 307.25000 7 10098 9932.750 165.25000 8 10090 9932.750 157.25000 9 9867 9932.750 -65.75000 10 9736 9654.714 81.28571 11 9040 9128.407 -88.40741 12 9232 9654.714 -422.71429 13 9520 9641.800 -121.80000 14 9217 9654.714 -437.71429 15 9868 9654.714 213.28571 16 9455 9654.714 -199.71429 17 9984 9932.750 51.25000 18 9556 9932.750 -376.75000 19 10190 9932.750 257.25000 20 9906 9932.750 -26.75000 21 9824 9932.750 -108.75000 22 9972 9654.714 317.28571 23 9185 9128.407 56.59259 24 9765 9654.714 110.28571 25 9838 9641.800 196.20000 26 9084 9128.407 -44.40741 27 9643 9654.714 -11.71429 28 10051 9654.714 396.28571 29 9987 9932.750 54.25000 30 9827 9932.750 -105.75000 31 10491 9932.750 558.25000 32 9722 9932.750 -210.75000 33 9472 9932.750 -460.75000 34 9728 9654.714 73.28571 35 8510 9128.407 -618.40741 36 9511 9654.714 -143.71429 37 9492 9641.800 -149.80000 38 8638 9128.407 -490.40741 39 9792 9654.714 137.28571 40 9605 9654.714 -49.71429 41 9237 9654.714 -417.71429 42 9533 9654.714 -121.71429 43 10293 9932.750 360.25000 44 9938 9932.750 5.25000 45 9984 9654.714 329.28571 46 9563 9654.714 -91.71429 47 8871 9128.407 -257.40741 48 9301 9128.407 172.59259 49 9215 9641.800 -426.80000 50 8834 9128.407 -294.40741 51 9998 9654.714 343.28571 52 9604 9654.714 -50.71429 53 9507 9654.714 -147.71429 54 9718 9654.714 63.28571 55 10095 9932.750 162.25000 56 9583 9932.750 -349.75000 57 9883 9932.750 -49.75000 58 9365 9654.714 -289.71429 59 8919 9128.407 -209.40741 60 9449 9654.714 -205.71429 61 9769 9641.800 127.20000 62 9321 9128.407 192.59259 63 9939 9654.714 284.28571 64 9336 9654.714 -318.71429 65 10195 9654.714 540.28571 66 9464 9654.714 -190.71429 67 10010 9932.750 77.25000 68 10213 9932.750 280.25000 69 9563 9932.750 -369.75000 70 9890 9654.714 235.28571 71 9305 9128.407 176.59259 72 9391 9654.714 -263.71429 73 9743 9641.800 101.20000 74 8587 9128.407 -541.40741 75 9731 9654.714 76.28571 76 9563 9654.714 -91.71429 77 9998 9654.714 343.28571 78 9437 9932.750 -495.75000 79 10038 9654.714 383.28571 80 9918 9932.750 -14.75000 81 9252 9932.750 -680.75000 82 9737 9654.714 82.28571 83 9035 9128.407 -93.40741 84 9133 9654.714 -521.71429 85 9487 9641.800 -154.80000 86 8700 9128.407 -428.40741 87 9627 9128.407 498.59259 88 8947 9654.714 -707.71429 89 9283 9654.714 -371.71429 90 8829 9654.714 -825.71429 91 9947 9654.714 292.28571 92 9628 9932.750 -304.75000 93 9318 9654.714 -336.71429 94 9605 9654.714 -49.71429 95 8640 9128.407 -488.40741 96 9214 9128.407 85.59259 97 9676 9641.800 34.20000 98 8642 9128.407 -486.40741 99 9402 9654.714 -252.71429 100 9610 9654.714 -44.71429 101 9294 9654.714 -360.71429 102 9448 9654.714 -206.71429 103 10319 9654.714 664.28571 104 9548 9932.750 -384.75000 105 9801 9654.714 146.28571 106 9596 9654.714 -58.71429 107 8923 9128.407 -205.40741 108 9746 9128.407 617.59259 109 9829 9641.800 187.20000 110 9125 9654.714 -529.71429 111 9782 9128.407 653.59259 112 9441 9654.714 -213.71429 113 9162 9654.714 -492.71429 114 9915 9654.714 260.28571 115 10444 9932.750 511.25000 116 10209 9932.750 276.25000 117 9985 9654.714 330.28571 118 9842 9654.714 187.28571 119 9429 9128.407 300.59259 120 10132 9654.714 477.28571 121 9849 9641.800 207.20000 122 9172 9128.407 43.59259 123 10313 9128.407 1184.59259 124 9819 9654.714 164.28571 125 9955 9654.714 300.28571 126 10048 9654.714 393.28571 127 10082 9932.750 149.25000 128 10541 9932.750 608.25000 129 10208 9654.714 553.28571 130 10233 9654.714 578.28571 131 9439 9128.407 310.59259 132 9963 9654.714 308.28571 > 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/html/rcomp/tmp/4yilm1293211897.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/html/rcomp/tmp/5usic1293211897.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/html/rcomp/tmp/6510f1293211897.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/html/rcomp/tmp/79kg31293211897.tab") + } > > try(system("convert tmp/2orl11293211897.ps tmp/2orl11293211897.png",intern=TRUE)) character(0) > try(system("convert tmp/3orl11293211897.ps tmp/3orl11293211897.png",intern=TRUE)) character(0) > try(system("convert tmp/4yilm1293211897.ps tmp/4yilm1293211897.png",intern=TRUE)) character(0) > > > proc.time() user system elapsed 2.640 0.608 13.822