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. 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 <- c(348542 + ,335658 + ,330664 + ,326814 + ,322900 + ,322310 + ,385164 + ,404861 + ,412136 + ,411057 + ,410040 + ,414980 + ,413626 + ,411062 + ,408352 + ,409780 + ,411318 + ,415555 + ,479481 + ,497826 + ,501638 + ,497990 + ,499287 + ,506247 + ,510401 + ,508642 + ,501805 + ,495476 + ,490336 + ,490042 + ,553155 + ,569999 + ,573170 + ,571687 + ,575453 + ,580177 + ,579849 + ,574346 + ,563325 + ,555604 + ,545544 + ,545109 + ,605181 + ,627856 + ,631421 + ,625671 + ,613577 + ,606463 + ,601676 + ,589121 + ,573559 + ,558487 + ,552148 + ,545720 + ,606569 + ,636067 + ,630704 + ,623275 + ,617771 + ,605401 + ,619393 + ,596019 + ,569977 + ,546213 + ,528492 + ,505944 + ,554910 + ,567831 + ,564021 + ,552800 + ,541102 + ,542378 + ,540380 + ,521219 + ,504652 + ,490626 + ,481686 + ,477930 + ,522605 + ,531432 + ,532355 + ,539954 + ,524987 + ,533307 + ,530541 + ,508392 + ,495208 + ,482223 + ,470495 + ,466106 + ,515037 + ,517752 + ,515565 + ,510727 + ,499725 + ,498369 + ,493756 + ,476141 + ,458458 + ,443182 + ,429597 + ,424476 + ,476257 + ,480555 + ,469762 + ,459820 + ,451028 + ,450065 + ,444385 + ,428846 + ,421020 + ,399778 + ,389005 + ,384018 + ,431933 + ,445844 + ,431464 + ,423263 + ,415881 + ,416208 + ,413491 + ,399153 + ,385939 + ,373917 + ,364635 + ,364696 + ,418358 + ,428212 + ,423730 + ,420677 + ,417428 + ,423245 + ,423113 + ,418873 + ,405733 + ,397812 + ,389918 + ,391116 + ,443814 + ,460373 + ,455422 + ,456288 + ,452233 + ,459256 + ,461146 + ,451391 + ,443101 + ,438810 + ,430457 + ,435721 + ,488280 + ,505814 + ,502338 + ,500910 + ,501434 + ,515476 + ,520862 + ,519517 + ,511805 + ,508607 + ,505327 + ,511435 + ,570158 + ,591665 + ,593572 + ,586346 + ,586063 + ,591504 + ,594033 + ,585597 + ,572450 + ,562917 + ,554675 + ,553997 + ,601310 + ,622255 + ,616735 + ,606480 + ,595079 + ,598588 + ,599917 + ,591573 + ,575489 + ,567223 + ,555338 + ,555252 + ,608249 + ,630859 + ,628632 + ,624435 + ,609670 + ,615830 + ,621170 + ,604212 + ,584348 + ,573717 + ,555234 + ,544897 + ,598866 + ,620081 + ,607699 + ,589960 + ,578665 + ,580166 + ,579457 + ,571560 + ,560460 + ,551397 + ,536763 + ,540562 + ,588184 + ,607049 + ,598968 + ,577644 + ,562640 + ,565867 + ,561274 + ,554144 + ,539900 + ,526271 + ,511841 + ,505282 + ,554083 + ,584225 + ,568858 + ,539516 + ,521612 + ,525562 + ,526519 + ,515713 + ,503454 + ,489301 + ,479020 + ,475102 + ,523682 + ,551528 + ,531626 + ,511037 + ,492417 + ,492188 + ,492865 + ,480961 + ,461935 + ,456608 + ,441977 + ,439148 + ,488180 + ,520564 + ,501492 + ,485025 + ,464196 + ,460170 + ,467037 + ,460070 + ,447988 + ,442867 + ,436087 + ,431328 + ,484015 + ,509673 + ,512927 + ,502831 + ,470984 + ,471067 + ,476049 + ,474605 + ,470439 + ,461251 + ,454724 + ,455626 + ,516847 + ,525192 + ,522975 + ,518585 + ,509239 + ,512238 + ,519164 + ,517009 + ,509933 + ,509127 + ,500857 + ,506971 + ,569323 + ,579714 + ,577992 + ,565464 + ,547344 + ,554788 + ,562325 + ,560854 + ,555332 + ,543599 + ,536662 + ,542722 + ,593530 + ,610763 + ,612613 + ,611324 + ,594167 + ,595454 + ,590865 + ,589379 + ,584428 + ,573100 + ,567456 + ,569028 + ,620735 + ,628884 + ,628232 + ,612117 + ,595404 + ,597141) > par9 = '1' > par8 = '1' > par7 = '1' > par6 = '1' > par5 = '12' > par4 = '1' > par3 = '1' > par2 = '1.2' > par1 = 'FALSE' > library(lattice) > if (par1 == 'TRUE') par1 <- TRUE > if (par1 == 'FALSE') par1 <- FALSE > par2 <- as.numeric(par2) #Box-Cox lambda transformation parameter > par3 <- as.numeric(par3) #degree of non-seasonal differencing > par4 <- as.numeric(par4) #degree of seasonal differencing > par5 <- as.numeric(par5) #seasonal period > par6 <- as.numeric(par6) #degree (p) of the non-seasonal AR(p) polynomial > par7 <- as.numeric(par7) #degree (q) of the non-seasonal MA(q) polynomial > par8 <- as.numeric(par8) #degree (P) of the seasonal AR(P) polynomial > par9 <- as.numeric(par9) #degree (Q) of the seasonal MA(Q) polynomial > armaGR <- function(arima.out, names, n){ + try1 <- arima.out$coef + try2 <- sqrt(diag(arima.out$var.coef)) + try.data.frame <- data.frame(matrix(NA,ncol=4,nrow=length(names))) + dimnames(try.data.frame) <- list(names,c('coef','std','tstat','pv')) + try.data.frame[,1] <- try1 + for(i in 1:length(try2)) try.data.frame[which(rownames(try.data.frame)==names(try2)[i]),2] <- try2[i] + try.data.frame[,3] <- try.data.frame[,1] / try.data.frame[,2] + try.data.frame[,4] <- round((1-pt(abs(try.data.frame[,3]),df=n-(length(try2)+1)))*2,5) + vector <- rep(NA,length(names)) + vector[is.na(try.data.frame[,4])] <- 0 + maxi <- which.max(try.data.frame[,4]) + continue <- max(try.data.frame[,4],na.rm=TRUE) > .05 + vector[maxi] <- 0 + list(summary=try.data.frame,next.vector=vector,continue=continue) + } > arimaSelect <- function(series, order=c(13,0,0), seasonal=list(order=c(2,0,0),period=12), include.mean=F){ + nrc <- order[1]+order[3]+seasonal$order[1]+seasonal$order[3] + coeff <- matrix(NA, nrow=nrc*2, ncol=nrc) + pval <- matrix(NA, nrow=nrc*2, ncol=nrc) + mylist <- rep(list(NULL), nrc) + names <- NULL + if(order[1] > 0) names <- paste('ar',1:order[1],sep='') + if(order[3] > 0) names <- c( names , paste('ma',1:order[3],sep='') ) + if(seasonal$order[1] > 0) names <- c(names, paste('sar',1:seasonal$order[1],sep='')) + if(seasonal$order[3] > 0) names <- c(names, paste('sma',1:seasonal$order[3],sep='')) + arima.out <- arima(series, order=order, seasonal=seasonal, include.mean=include.mean, method='ML') + mylist[[1]] <- arima.out + last.arma <- armaGR(arima.out, names, length(series)) + mystop <- FALSE + i <- 1 + coeff[i,] <- last.arma[[1]][,1] + pval [i,] <- last.arma[[1]][,4] + i <- 2 + aic <- arima.out$aic + while(!mystop){ + mylist[[i]] <- arima.out + arima.out <- arima(series, order=order, seasonal=seasonal, include.mean=include.mean, method='ML', fixed=last.arma$next.vector) + aic <- c(aic, arima.out$aic) + last.arma <- armaGR(arima.out, names, length(series)) + mystop <- !last.arma$continue + coeff[i,] <- last.arma[[1]][,1] + pval [i,] <- last.arma[[1]][,4] + i <- i+1 + } + list(coeff, pval, mylist, aic=aic) + } > arimaSelectplot <- function(arimaSelect.out,noms,choix){ + noms <- names(arimaSelect.out[[3]][[1]]$coef) + coeff <- arimaSelect.out[[1]] + k <- min(which(is.na(coeff[,1])))-1 + coeff <- coeff[1:k,] + pval <- arimaSelect.out[[2]][1:k,] + aic <- arimaSelect.out$aic[1:k] + coeff[coeff==0] <- NA + n <- ncol(coeff) + if(missing(choix)) choix <- k + layout(matrix(c(1,1,1,2, + 3,3,3,2, + 3,3,3,4, + 5,6,7,7),nr=4), + widths=c(10,35,45,15), + heights=c(30,30,15,15)) + couleurs <- rainbow(75)[1:50]#(50) + ticks <- pretty(coeff) + par(mar=c(1,1,3,1)) + plot(aic,k:1-.5,type='o',pch=21,bg='blue',cex=2,axes=F,lty=2,xpd=NA) + points(aic[choix],k-choix+.5,pch=21,cex=4,bg=2,xpd=NA) + title('aic',line=2) + par(mar=c(3,0,0,0)) + plot(0,axes=F,xlab='',ylab='',xlim=range(ticks),ylim=c(.1,1)) + rect(xleft = min(ticks) + (0:49)/50*(max(ticks)-min(ticks)), + xright = min(ticks) + (1:50)/50*(max(ticks)-min(ticks)), + ytop = rep(1,50), + ybottom= rep(0,50),col=couleurs,border=NA) + axis(1,ticks) + rect(xleft=min(ticks),xright=max(ticks),ytop=1,ybottom=0) + text(mean(coeff,na.rm=T),.5,'coefficients',cex=2,font=2) + par(mar=c(1,1,3,1)) + image(1:n,1:k,t(coeff[k:1,]),axes=F,col=couleurs,zlim=range(ticks)) + for(i in 1:n) for(j in 1:k) if(!is.na(coeff[j,i])) { + if(pval[j,i]<.01) symb = 'green' + else if( (pval[j,i]<.05) & (pval[j,i]>=.01)) symb = 'orange' + else if( (pval[j,i]<.1) & (pval[j,i]>=.05)) symb = 'red' + else symb = 'black' + polygon(c(i+.5 ,i+.2 ,i+.5 ,i+.5), + c(k-j+0.5,k-j+0.5,k-j+0.8,k-j+0.5), + col=symb) + if(j==choix) { + rect(xleft=i-.5, + xright=i+.5, + ybottom=k-j+1.5, + ytop=k-j+.5, + lwd=4) + text(i, + k-j+1, + round(coeff[j,i],2), + cex=1.2, + font=2) + } + else{ + rect(xleft=i-.5,xright=i+.5,ybottom=k-j+1.5,ytop=k-j+.5) + text(i,k-j+1,round(coeff[j,i],2),cex=1.2,font=1) + } + } + axis(3,1:n,noms) + par(mar=c(0.5,0,0,0.5)) + plot(0,axes=F,xlab='',ylab='',type='n',xlim=c(0,8),ylim=c(-.2,.8)) + cols <- c('green','orange','red','black') + niv <- c('0','0.01','0.05','0.1') + for(i in 0:3){ + polygon(c(1+2*i ,1+2*i ,1+2*i-.5 ,1+2*i), + c(.4 ,.7 , .4 , .4), + col=cols[i+1]) + text(2*i,0.5,niv[i+1],cex=1.5) + } + text(8,.5,1,cex=1.5) + text(4,0,'p-value',cex=2) + box() + residus <- arimaSelect.out[[3]][[choix]]$res + par(mar=c(1,2,4,1)) + acf(residus,main='') + title('acf',line=.5) + par(mar=c(1,2,4,1)) + pacf(residus,main='') + title('pacf',line=.5) + par(mar=c(2,2,4,1)) + qqnorm(residus,main='') + title('qq-norm',line=.5) + qqline(residus) + residus + } > if (par2 == 0) x <- log(x) > if (par2 != 0) x <- x^par2 > (selection <- arimaSelect(x, order=c(par6,par3,par7), seasonal=list(order=c(par8,par4,par9), period=par5))) [[1]] [,1] [,2] [,3] [,4] [1,] 0.9357038 -0.8125308 0.3919882 -0.8776378 [2,] 0.9517643 -0.8287603 0.0000000 -0.5435521 [3,] NA NA NA NA [4,] NA NA NA NA [5,] NA NA NA NA [6,] NA NA NA NA [7,] NA NA NA NA [8,] NA NA NA NA [[2]] [,1] [,2] [,3] [,4] [1,] 0 0 2e-05 0 [2,] 0 0 NA 0 [3,] NA NA NA NA [4,] NA NA NA NA [5,] NA NA NA NA [6,] NA NA NA NA [7,] NA NA NA NA [8,] NA NA NA NA [[3]] [[3]][[1]] Call: arima(x = series, order = order, seasonal = seasonal, include.mean = include.mean, method = "ML") Coefficients: ar1 ma1 sar1 sma1 0.9357 -0.8125 0.3920 -0.8776 s.e. 0.0448 0.0719 0.0892 0.0623 sigma^2 estimated as 8.499e+09: log likelihood = -3846.96, aic = 7703.92 [[3]][[2]] Call: arima(x = series, order = order, seasonal = seasonal, include.mean = include.mean, method = "ML") Coefficients: ar1 ma1 sar1 sma1 0.9357 -0.8125 0.3920 -0.8776 s.e. 0.0448 0.0719 0.0892 0.0623 sigma^2 estimated as 8.499e+09: log likelihood = -3846.96, aic = 7703.92 [[3]][[3]] NULL [[3]][[4]] NULL $aic [1] 7703.916 7713.960 Warning message: In arima(series, order = order, seasonal = seasonal, include.mean = include.mean, : some AR parameters were fixed: setting transform.pars = FALSE > postscript(file="/var/www/rcomp/tmp/1fe7s1322906448.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > resid <- arimaSelectplot(selection) > dev.off() null device 1 > resid Time Series: Start = 1 End = 312 Frequency = 1 [1] 2583.1250 1002.0516 591.5644 389.2308 256.7244 [6] 205.3745 1079.6943 1236.3833 1207.9669 1070.4962 [11] 957.4884 -1519.7879 -13056.4523 136057.6790 8516.1718 [16] 52090.0206 50342.1985 40668.5031 28356.4023 -36182.9423 [21] -67508.2577 -48540.0282 31248.6717 28895.7334 76000.2873 [26] 32471.6834 -78920.1993 -106932.6195 -75196.4933 -33490.5850 [31] 51520.6485 -7763.4700 -11421.1424 33840.8478 59034.7667 [36] -19552.5817 -38337.8113 -19522.1545 -79800.2367 -34156.6745 [41] -79980.4912 18173.9179 16004.7350 115625.1706 960.1281 [46] -60144.2849 -222052.6513 -155903.2944 -21508.1051 -59217.3908 [51] -60473.8628 -90949.3861 80094.4058 -51297.8799 74144.0459 [56] 193501.5980 -139438.9764 -19960.2988 57684.3255 -143136.5485 [61] 319163.8174 -229504.7436 -214214.4140 -168326.1755 -130967.2042 [66] -228626.1211 -98948.0479 -98441.5825 69574.7121 3340.9988 [71] -34358.4226 212042.2875 -107019.4701 26170.4961 90570.0329 [76] 82296.2628 83880.1956 170395.8742 -168953.1548 -114040.2661 [81] 61058.6035 276874.8247 -132673.6526 131280.3089 -57800.5881 [86] -118688.1851 27598.8378 -9972.4748 -51414.7564 9523.4497 [91] -32721.2102 -171482.1914 -22452.6474 -76641.6916 29098.4357 [96] -61167.5170 -22129.9014 41058.9775 -43684.3977 -17676.0247 [101] -22501.7072 27379.5410 -320.6763 -65135.0305 -132313.7338 [106] -46511.7998 53174.0354 28228.6416 -22436.4717 44350.9825 [111] 151500.5959 -115273.0461 29600.4790 16185.7789 -103437.2928 [116] 86970.7410 -131209.9830 8067.3838 35977.8195 25709.3203 [121] 19340.2192 25978.5317 -31871.9814 88602.6114 12839.3614 [126] 75172.0046 1973.5204 -83380.7662 56156.4494 46240.7492 [131] 53287.1967 67041.1987 1135.4273 139555.1091 -41699.8943 [136] 40211.5295 -12569.5708 23504.8154 -57253.6456 51012.0715 [141] -49628.8290 57094.7206 -8022.7147 37958.8162 13603.8859 [146] -36799.2469 53340.9543 68991.5636 -30430.2442 79710.9059 [151] -39791.4841 14832.7127 -20299.8698 -18408.0842 75589.8148 [156] 136009.6777 38167.2433 117529.3191 -15741.7445 25764.8177 [161] 34719.3800 32023.7414 68125.6090 48124.0164 27985.4049 [166] -139781.1611 2279.9317 -79599.1223 -22825.2287 -52919.3495 [171] -74213.6308 -50002.1835 -37370.3037 -37575.8992 -114380.6067 [176] 82013.3247 -72550.6998 -62148.4744 -121645.4241 25403.0609 [181] 34299.9212 48965.6775 -46329.7755 47351.5770 -46879.7408 [186] 36411.1439 74502.2810 87383.2803 26235.6171 43280.9429 [191] -127999.0664 48766.0796 73881.1984 -143532.0019 -97887.6342 [196] -11181.3547 -125729.0353 -131512.4275 72769.1337 69103.7996 [201] -145501.2971 -186945.4238 45150.6813 -7820.4398 -15585.1281 [206] 148365.9284 112264.5125 28737.9303 -8898.1207 169047.6570 [211] -106704.8288 -1953.6864 -5262.9817 -167793.3127 -78736.9384 [216] 38519.1355 -58434.2896 68786.2239 -17643.6847 -51195.9464 [221] -9777.4516 -100268.7510 6266.3972 234743.4529 -156038.4737 [226] -235268.9671 -60717.8438 59570.7156 89526.7623 -2396.8419 [231] 51145.0193 -19644.9998 58702.2558 14311.3111 -33588.8520 [236] 71683.6506 -159970.4763 1656.2892 -65610.0458 -40516.4802 [241] 30898.9436 5943.6010 -77673.3134 146518.6818 -51223.4544 [246] 20008.5856 -23690.0141 153557.5120 -101381.4292 1931.9760 [251] -97973.3103 -75321.7543 129666.9128 81031.4503 67873.1439 [256] 38021.1315 86276.5876 -58436.4116 12321.7337 -33698.1871 [261] 269468.5571 28122.6397 -305872.8300 5749.8088 16845.1788 [266] 115379.5736 124488.5830 -60048.6746 17161.6826 48364.9935 [271] 123467.1938 -298832.0706 6112.1252 112547.4212 193615.6441 [276] -9650.7231 27711.7532 21451.7764 -10883.5279 105949.8544 [281] -40719.6931 78251.8119 70259.4882 -125581.5584 20095.5311 [286] -106679.4435 -127110.8918 83466.7084 44836.0045 52288.9312 [291] 46599.7458 -140432.0445 30111.4578 58043.5829 -115764.2583 [296] 37432.2965 98015.0771 162835.6197 -62213.7780 -86210.5674 [301] -176436.1340 63125.3387 58691.9842 -30900.4111 41860.8906 [306] -23719.7368 4036.1119 -172711.7379 40588.1138 -162255.9704 [311] 10283.1175 22610.9262 > postscript(file="/var/www/rcomp/tmp/2y6vs1322906448.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > acf(resid,length(resid)/2, main='Residual Autocorrelation Function') > dev.off() null device 1 > postscript(file="/var/www/rcomp/tmp/3zdte1322906448.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > pacf(resid,length(resid)/2, main='Residual Partial Autocorrelation Function') > dev.off() null device 1 > postscript(file="/var/www/rcomp/tmp/489iv1322906448.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > cpgram(resid, main='Residual Cumulative Periodogram') > dev.off() null device 1 > postscript(file="/var/www/rcomp/tmp/5n5n01322906448.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > hist(resid, main='Residual Histogram', xlab='values of Residuals') > dev.off() null device 1 > postscript(file="/var/www/rcomp/tmp/68zc51322906448.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > densityplot(~resid,col='black',main='Residual Density Plot', xlab='values of Residuals') > dev.off() null device 1 > postscript(file="/var/www/rcomp/tmp/7x5zy1322906448.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > qqnorm(resid, main='Residual Normal Q-Q Plot') > qqline(resid) > dev.off() null device 1 > ncols <- length(selection[[1]][1,]) > nrows <- length(selection[[2]][,1])-1 > > #Note: the /var/www/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab > load(file="/var/www/rcomp/createtable") > > a<-table.start() > a<-table.row.start(a) > a<-table.element(a,'ARIMA Parameter Estimation and Backward Selection', ncols+1,TRUE) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a,'Iteration', header=TRUE) > for (i in 1:ncols) { + a<-table.element(a,names(selection[[3]][[1]]$coef)[i],header=TRUE) + } > a<-table.row.end(a) > for (j in 1:nrows) { + a<-table.row.start(a) + mydum <- 'Estimates (' + mydum <- paste(mydum,j) + mydum <- paste(mydum,')') + a<-table.element(a,mydum, header=TRUE) + for (i in 1:ncols) { + a<-table.element(a,round(selection[[1]][j,i],4)) + } + a<-table.row.end(a) + a<-table.row.start(a) + a<-table.element(a,'(p-val)', header=TRUE) + for (i in 1:ncols) { + mydum <- '(' + mydum <- paste(mydum,round(selection[[2]][j,i],4),sep='') + mydum <- paste(mydum,')') + a<-table.element(a,mydum) + } + a<-table.row.end(a) + } > a<-table.end(a) > table.save(a,file="/var/www/rcomp/tmp/8nxq21322906448.tab") > a<-table.start() > a<-table.row.start(a) > a<-table.element(a,'Estimated ARIMA Residuals', 1,TRUE) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a,'Value', 1,TRUE) > a<-table.row.end(a) > for (i in (par4*par5+par3):length(resid)) { + a<-table.row.start(a) + a<-table.element(a,resid[i]) + a<-table.row.end(a) + } > a<-table.end(a) > table.save(a,file="/var/www/rcomp/tmp/9cyva1322906448.tab") > > try(system("convert tmp/1fe7s1322906448.ps tmp/1fe7s1322906448.png",intern=TRUE)) character(0) > try(system("convert tmp/2y6vs1322906448.ps tmp/2y6vs1322906448.png",intern=TRUE)) character(0) > try(system("convert tmp/3zdte1322906448.ps tmp/3zdte1322906448.png",intern=TRUE)) character(0) > try(system("convert tmp/489iv1322906448.ps tmp/489iv1322906448.png",intern=TRUE)) character(0) > try(system("convert tmp/5n5n01322906448.ps tmp/5n5n01322906448.png",intern=TRUE)) character(0) > try(system("convert tmp/68zc51322906448.ps tmp/68zc51322906448.png",intern=TRUE)) character(0) > try(system("convert tmp/7x5zy1322906448.ps tmp/7x5zy1322906448.png",intern=TRUE)) character(0) > > > proc.time() user system elapsed 5.070 0.340 5.394