R version 2.9.0 (2009-04-17) Copyright (C) 2009 The R Foundation for Statistical Computing ISBN 3-900051-07-0 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. R is a collaborative project with many contributors. Type 'contributors()' for more information and 'citation()' on how to cite R or R packages in publications. 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(33024 + ,31086 + ,19828 + ,18932 + ,32526 + ,30839 + ,19967 + ,18927 + ,31455 + ,30051 + ,19814 + ,19124 + ,31524 + ,29976 + ,20053 + ,19066 + ,31856 + ,30463 + ,20719 + ,19971 + ,32696 + ,31422 + ,21174 + ,20165 + ,32584 + ,31588 + ,20648 + ,19705 + ,33498 + ,31900 + ,20659 + ,19718 + ,34175 + ,32878 + ,20733 + ,19938 + ,34172 + ,33010 + ,21069 + ,20039 + ,34379 + ,32954 + ,20566 + ,19721 + ,34988 + ,33076 + ,20839 + ,19777 + ,36158 + ,35057 + ,21615 + ,20505 + ,37411 + ,35906 + ,22739 + ,21763 + ,38015 + ,36100 + ,23222 + ,22404 + ,37577 + ,35824 + ,23031 + ,22038 + ,36354 + ,34579 + ,23014 + ,22038 + ,36030 + ,34484 + ,22868 + ,21874 + ,35636 + ,33920 + ,22182 + ,21269 + ,35669 + ,34059 + ,22177 + ,21127 + ,34635 + ,33812 + ,21216 + ,20609 + ,35496 + ,34594 + ,21031 + ,20565 + ,36376 + ,36083 + ,20968 + ,19791 + ,37635 + ,36563 + ,21049 + ,20672 + ,38875 + ,37416 + ,21033 + ,20938 + ,38372 + ,37953 + ,21078 + ,20675 + ,38897 + ,37517 + ,20702 + ,19992 + ,38018 + ,37467 + ,20309 + ,19801 + ,37325 + ,36963 + ,20449 + ,20050 + ,36893 + ,36019 + ,20737 + ,20427 + ,36117 + ,35232 + ,20849 + ,20815 + ,37599 + ,36857 + ,21966 + ,21666 + ,39037 + ,37978 + ,23100 + ,22720 + ,40809 + ,40160 + ,23975 + ,23650 + ,42508 + ,42165 + ,24350 + ,24244 + ,44021 + ,43069 + ,24020 + ,23669 + ,44088 + ,43021 + ,24005 + ,23881 + ,44510 + ,43376 + ,23602 + ,23857 + ,45786 + ,43978 + ,24120 + ,23999 + ,47349 + ,45911 + ,24847 + ,24780 + ,48696 + ,47107 + ,25702 + ,25426 + ,50598 + ,49168 + ,26312 + ,26229 + ,50066 + ,48390 + ,25891 + ,25973 + ,49367 + ,47678 + ,25172 + ,25375 + ,48784 + ,47822 + ,25698 + ,25966 + ,47841 + ,46695 + ,25833 + ,25391 + ,48300 + ,47185 + ,25658 + ,26046 + ,47518 + ,45684 + ,25269 + ,25572 + ,46504 + ,44884 + ,24846 + ,24900 + ,45147 + ,44256 + ,24390 + ,24744 + ,44404 + ,43637 + ,23954 + ,24526 + ,43455 + ,42368 + ,23828 + ,24274 + ,42299 + ,40892 + ,23507 + ,23774 + ,42105 + ,40616 + ,23144 + ,23414 + ,40152 + ,39026 + ,22302 + ,23002 + ,39519 + ,38921 + ,23028 + ,23137 + ,39633 + ,38512 + ,22741 + ,22947 + ,39376 + ,38884 + ,23129 + ,23733 + ,38850 + ,38406 + ,22911 + ,23234 + ,39657 + ,38804 + ,22071 + ,22969 + ,34804 + ,34871 + ,16466 + ,17708 + ,34372 + ,34660 + ,16370 + ,17377 + ,32678 + ,33104 + ,15049 + ,16273 + ,28420 + ,28952 + ,13174 + ,14342 + ,25420 + ,26488 + ,12231 + ,13522 + ,27683 + ,29418 + ,13620 + ,15210 + ,29904 + ,32315 + ,14317 + ,16493 + ,30546 + ,32885 + ,14039 + ,16701 + ,29142 + ,31565 + ,13526 + ,15662 + ,27724 + ,30782 + ,12826 + ,15526 + ,27069 + ,30442 + ,12360 + ,15413 + ,26665 + ,30851 + ,12592 + ,15805 + ,26004 + ,30432 + ,12381 + ,15802 + ,25767 + ,31260 + ,12554 + ,16753 + ,24915 + ,30737 + ,12338 + ,16906 + ,23689 + ,30129 + ,11768 + ,16891 + ,20915 + ,27672 + ,10687 + ,15703 + ,19414 + ,26469 + ,9964 + ,15429 + ,17824 + ,24895 + ,9338 + ,14762 + ,16348 + ,24427 + ,8697 + ,14426 + ,15571 + ,23252 + ,8068 + ,14250 + ,13929 + ,21815 + ,7295 + ,13267 + ,12480 + ,20837 + ,6372 + ,12397 + ,10837 + ,18537 + ,5649 + ,11586 + ,9473 + ,17237 + ,4926 + ,10888 + ,8051 + ,15476 + ,4199 + ,9841 + ,5278 + ,10709 + ,2568 + ,6443 + ,3008 + ,6776 + ,1461 + ,4019 + ,2404 + ,5810 + ,1173 + ,3449 + ,2298 + ,5765 + ,1084 + ,3179 + ,2260 + ,5775 + ,978 + ,3341 + ,1938 + ,5589 + ,947 + ,3325 + ,1371 + ,4687 + ,679 + ,2478 + ,1009 + ,3630 + ,457 + ,1982 + ,686 + ,2552 + ,262 + ,1405 + ,493 + ,1928 + ,218 + ,1059 + ,285 + ,1323 + ,132 + ,740 + ,192 + ,1005 + ,70 + ,533 + ,129 + ,678 + ,44 + ,366 + ,60 + ,397 + ,24 + ,224 + ,54 + ,286 + ,20 + ,147 + ,26 + ,166 + ,4 + ,75 + ,11 + ,80 + ,4 + ,54 + ,3 + ,53 + ,1 + ,23 + ,0 + ,32 + ,0 + ,16 + ,2 + ,11 + ,0 + ,6 + ,1 + ,6 + ,0 + ,7 + ,0 + ,4 + ,0 + ,2 + ,0 + ,2 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,1 + ,0 + ,0) + ,dim=c(4 + ,111) + ,dimnames=list(c('MVG' + ,'VVG' + ,'MWG' + ,'VWG') + ,1:111)) > y <- array(NA,dim=c(4,111),dimnames=list(c('MVG','VVG','MWG','VWG'),1:111)) > 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$_version), Office for Research Development and Education, URL http://www.wessa.net/rwasp_YOURPAGE.wasp/ > #Source of accompanying publication: > #Technical description: > library(party) Loading required package: survival Loading required package: splines Loading required package: grid Loading required package: modeltools Loading required package: stats4 Loading required package: coin Loading required package: mvtnorm Loading required package: zoo Attaching package: 'zoo' The following object(s) are masked from package:base : as.Date.numeric Loading required package: sandwich Loading required package: strucchange Loading required package: vcd Loading required package: MASS Loading required package: colorspace > library(Hmisc) Attaching package: 'Hmisc' The following object(s) are masked from package:survival : untangle.specials The following object(s) are masked from package:base : format.pval, round.POSIXt, trunc.POSIXt, units > par1 <- as.numeric(par1) > par3 <- as.numeric(par3) > x <- data.frame(t(y)) > is.data.frame(x) [1] TRUE > x <- x[!is.na(x[,par1]),] > k <- length(x[1,]) > n <- length(x[,1]) > colnames(x)[par1] [1] "MVG" > x[,par1] [1] 33024 32526 31455 31524 31856 32696 32584 33498 34175 34172 34379 34988 [13] 36158 37411 38015 37577 36354 36030 35636 35669 34635 35496 36376 37635 [25] 38875 38372 38897 38018 37325 36893 36117 37599 39037 40809 42508 44021 [37] 44088 44510 45786 47349 48696 50598 50066 49367 48784 47841 48300 47518 [49] 46504 45147 44404 43455 42299 42105 40152 39519 39633 39376 38850 39657 [61] 34804 34372 32678 28420 25420 27683 29904 30546 29142 27724 27069 26665 [73] 26004 25767 24915 23689 20915 19414 17824 16348 15571 13929 12480 10837 [85] 9473 8051 5278 3008 2404 2298 2260 1938 1371 1009 686 493 [97] 285 192 129 60 54 26 11 3 0 2 1 0 [109] 0 0 0 > if (par2 == 'kmeans') { + cl <- kmeans(x[,par1], par3) + print(cl) + clm <- matrix(cbind(cl$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]) [ 0,33498) [33498,50598] 56 55 > colnames(x) [1] "MVG" "VVG" "MWG" "VWG" > colnames(x)[par1] [1] "MVG" > x[,par1] [1] [ 0,33498) [ 0,33498) [ 0,33498) [ 0,33498) [ 0,33498) [6] [ 0,33498) [ 0,33498) [33498,50598] [33498,50598] [33498,50598] [11] [33498,50598] [33498,50598] [33498,50598] [33498,50598] [33498,50598] [16] [33498,50598] [33498,50598] [33498,50598] [33498,50598] [33498,50598] [21] [33498,50598] [33498,50598] [33498,50598] [33498,50598] [33498,50598] [26] [33498,50598] [33498,50598] [33498,50598] [33498,50598] [33498,50598] [31] [33498,50598] [33498,50598] [33498,50598] [33498,50598] [33498,50598] [36] [33498,50598] [33498,50598] [33498,50598] [33498,50598] [33498,50598] [41] [33498,50598] [33498,50598] [33498,50598] [33498,50598] [33498,50598] [46] [33498,50598] [33498,50598] [33498,50598] [33498,50598] [33498,50598] [51] [33498,50598] [33498,50598] [33498,50598] [33498,50598] [33498,50598] [56] [33498,50598] [33498,50598] [33498,50598] [33498,50598] [33498,50598] [61] [33498,50598] [33498,50598] [ 0,33498) [ 0,33498) [ 0,33498) [66] [ 0,33498) [ 0,33498) [ 0,33498) [ 0,33498) [ 0,33498) [71] [ 0,33498) [ 0,33498) [ 0,33498) [ 0,33498) [ 0,33498) [76] [ 0,33498) [ 0,33498) [ 0,33498) [ 0,33498) [ 0,33498) [81] [ 0,33498) [ 0,33498) [ 0,33498) [ 0,33498) [ 0,33498) [86] [ 0,33498) [ 0,33498) [ 0,33498) [ 0,33498) [ 0,33498) [91] [ 0,33498) [ 0,33498) [ 0,33498) [ 0,33498) [ 0,33498) [96] [ 0,33498) [ 0,33498) [ 0,33498) [ 0,33498) [ 0,33498) [101] [ 0,33498) [ 0,33498) [ 0,33498) [ 0,33498) [ 0,33498) [106] [ 0,33498) [ 0,33498) [ 0,33498) [ 0,33498) [ 0,33498) [111] [ 0,33498) Levels: [ 0,33498) [33498,50598] > 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/1x9f61292142974.tab") + } + } > m Conditional inference tree with 3 terminal nodes Response: as.factor(MVG) Inputs: VVG, MWG, VWG Number of observations: 111 1) MWG <= 20053; criterion = 1, statistic = 74.235 2)* weights = 55 1) MWG > 20053 3) VVG <= 33010; criterion = 0.981, statistic = 7.413 4)* weights = 7 3) VVG > 33010 5)* weights = 49 > postscript(file="/var/www/html/rcomp/tmp/2x9f61292142974.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/3x9f61292142974.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 2 [6,] 1 2 [7,] 1 2 [8,] 2 2 [9,] 2 2 [10,] 2 2 [11,] 2 2 [12,] 2 2 [13,] 2 2 [14,] 2 2 [15,] 2 2 [16,] 2 2 [17,] 2 2 [18,] 2 2 [19,] 2 2 [20,] 2 2 [21,] 2 2 [22,] 2 2 [23,] 2 2 [24,] 2 2 [25,] 2 2 [26,] 2 2 [27,] 2 2 [28,] 2 2 [29,] 2 2 [30,] 2 2 [31,] 2 2 [32,] 2 2 [33,] 2 2 [34,] 2 2 [35,] 2 2 [36,] 2 2 [37,] 2 2 [38,] 2 2 [39,] 2 2 [40,] 2 2 [41,] 2 2 [42,] 2 2 [43,] 2 2 [44,] 2 2 [45,] 2 2 [46,] 2 2 [47,] 2 2 [48,] 2 2 [49,] 2 2 [50,] 2 2 [51,] 2 2 [52,] 2 2 [53,] 2 2 [54,] 2 2 [55,] 2 2 [56,] 2 2 [57,] 2 2 [58,] 2 2 [59,] 2 2 [60,] 2 2 [61,] 2 1 [62,] 2 1 [63,] 1 1 [64,] 1 1 [65,] 1 1 [66,] 1 1 [67,] 1 1 [68,] 1 1 [69,] 1 1 [70,] 1 1 [71,] 1 1 [72,] 1 1 [73,] 1 1 [74,] 1 1 [75,] 1 1 [76,] 1 1 [77,] 1 1 [78,] 1 1 [79,] 1 1 [80,] 1 1 [81,] 1 1 [82,] 1 1 [83,] 1 1 [84,] 1 1 [85,] 1 1 [86,] 1 1 [87,] 1 1 [88,] 1 1 [89,] 1 1 [90,] 1 1 [91,] 1 1 [92,] 1 1 [93,] 1 1 [94,] 1 1 [95,] 1 1 [96,] 1 1 [97,] 1 1 [98,] 1 1 [99,] 1 1 [100,] 1 1 [101,] 1 1 [102,] 1 1 [103,] 1 1 [104,] 1 1 [105,] 1 1 [106,] 1 1 [107,] 1 1 [108,] 1 1 [109,] 1 1 [110,] 1 1 [111,] 1 1 [ 0,33498) [33498,50598] [ 0,33498) 53 3 [33498,50598] 2 53 > postscript(file="/var/www/html/rcomp/tmp/471ws1292142974.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/5lst01292142974.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/6pts61292142974.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/7ikr91292142974.tab") + } > > try(system("convert tmp/2x9f61292142974.ps tmp/2x9f61292142974.png",intern=TRUE)) character(0) > try(system("convert tmp/3x9f61292142974.ps tmp/3x9f61292142974.png",intern=TRUE)) character(0) > try(system("convert tmp/471ws1292142974.ps tmp/471ws1292142974.png",intern=TRUE)) character(0) > > > proc.time() user system elapsed 2.021 0.485 4.402