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(1149822 + ,1086979 + ,1276674 + ,1522522 + ,1742117 + ,1737275 + ,1979900 + ,2061036 + ,1867943 + ,1707752 + ,1298756 + ,1281814 + ,1281151 + ,1164976 + ,1454329 + ,1645288 + ,1817743 + ,1895785 + ,2236311 + ,2295951 + ,2087315 + ,1980891 + ,1465446 + ,1445026 + ,1488120 + ,1338333 + ,1715789 + ,1806090 + ,2083316 + ,2092278 + ,2430800 + ,2424894 + ,2299016 + ,2130688 + ,1652221 + ,1608162 + ,1647074 + ,1479691 + ,1884978 + ,2007898 + ,2208954 + ,2217164 + ,2534291 + ,2560312 + ,2429069 + ,2315077 + ,1799608 + ,1772590 + ,1744799 + ,1659093 + ,2099821 + ,2135736 + ,2427894 + ,2468882 + ,2703217 + ,2766841 + ,2655236 + ,2550373 + ,2052097 + ,1998055 + ,1920748 + ,1876694 + ,2380930 + ,2467402 + ,2770771 + ,2781340 + ,3143926 + ,3172235 + ,2952540 + ,2920877 + ,2384552 + ,2248987 + ,2208616 + ,2178756 + ,2632870 + ,2706905 + ,3029745 + ,3015402 + ,3391414 + ,3507805 + ,3177852 + ,3142961 + ,2545815 + ,2414007 + ,2372578 + ,2332664 + ,2825328 + ,2901478 + ,3263955 + ,3226738 + ,3610786 + ,3709274 + ,3467185 + ,3449646 + ,2802951 + ,2462530 + ,2490645 + ,2561520 + ,3067554 + ,3226951 + ,3546493 + ,3492787 + ,3952263 + ,3932072 + ,3720284 + ,3651555 + ,2914972 + ,2713514 + ,2703997 + ,2591373 + ,3163748 + ,3355137 + ,3613702 + ,3686773 + ,4098716 + ,4063517 + ,3551489 + ,3226663 + ,2656842 + ,2597484 + ,2572399 + ,2596631 + ,3165225 + ,3303145 + ,3698247 + ,3668631 + ,4130433 + ,4131400 + ,3864358 + ,3721110 + ,2892532 + ,2843451 + ,2747502 + ,2668775 + ,3018602 + ,3013392 + ,3393657 + ,3544233 + ,4075832 + ,4032923 + ,3734509 + ,3761285 + ,2970090 + ,2847849 + ,2741680 + ,2830639 + ,3257673 + ,3480085 + ,3843271 + ,3796961 + ,4337767 + ,4243630 + ,3927202 + ,3915296 + ,3087396 + ,2963792 + ,2955792 + ,2829925 + ,3281195 + ,3548011 + ,4059648 + ,3941175 + ,4528594 + ,4433151 + ,4145737 + ,4077132 + ,3198519 + ,3078660 + ,3028202 + ,2858642 + ,3398954 + ,3808883 + ,4175961 + ,4227542 + ,4744616 + ,4608012 + ,4295049 + ,4201144 + ,3353276 + ,3286851 + ,3169889 + ,3051720 + ,3695426 + ,3905501 + ,4296458 + ,4246247 + ,4921849 + ,4821446 + ,4425064 + ,4379099 + ,3472889 + ,3359160 + ,3200944 + ,3153170 + ,3741498 + ,3918719 + ,4403449 + ,4400407 + ,4847473 + ,4716136 + ,4297440 + ,4272253 + ,3271834 + ,3168388 + ,2911748 + ,2720999 + ,3199918 + ,3672623 + ,3892013 + ,3850845 + ,4532467 + ,4484739 + ,4014972 + ,3983758 + ,3158459 + ,3100569 + ,2935404 + ,2855719 + ,3465611 + ,3006985 + ,4095110 + ,4104793 + ,4730788 + ,4642726 + ,4246919 + ,4308117) > par9 = '1' > par8 = '2' > par7 = '0' > par6 = '3' > par5 = '12' > par4 = '1' > par3 = '1' > par2 = '0.3' > par1 = 'FALSE' > #'GNU S' R Code compiled by R2WASP v. 1.0.44 () > #Author: Prof. Dr. P. Wessa > #To cite this work: AUTHOR(S), (YEAR), YOUR SOFTWARE TITLE (vNUMBER) in Free Statistics Software (v$_version), Office for Research Development and Education, URL http://www.wessa.net/rwasp_YOURPAGE.wasp/ > #Source of accompanying publication: Office for Research, Development, and Education > #Technical description: Write here your technical program description (don't use hard returns!) > library(lattice) > if (par1 == 'TRUE') par1 <- TRUE > if (par1 == 'FALSE') par1 <- FALSE > par2 <- as.numeric(par2) #Box-Cox lambda transformation parameter > par3 <- as.numeric(par3) #degree of non-seasonal differencing > par4 <- as.numeric(par4) #degree of seasonal differencing > par5 <- as.numeric(par5) #seasonal period > par6 <- as.numeric(par6) #degree (p) of the non-seasonal AR(p) polynomial > par7 <- as.numeric(par7) #degree (q) of the non-seasonal MA(q) polynomial > par8 <- as.numeric(par8) #degree (P) of the seasonal AR(P) polynomial > par9 <- as.numeric(par9) #degree (Q) of the seasonal MA(Q) polynomial > armaGR <- function(arima.out, names, n){ + try1 <- arima.out$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] [,5] [,6] [1,] -0.4037250 -0.2307369 -0.06250571 0.1114452 0.13462765 -0.8145976 [2,] -0.4016471 -0.2320571 -0.05805518 0.0000000 0.08105168 -0.7296921 [3,] -0.4068013 -0.2415236 -0.05802907 0.0000000 0.00000000 -0.6976198 [4,] -0.3941285 -0.2196392 0.00000000 0.0000000 0.00000000 -0.7010084 [5,] NA NA NA NA NA NA [6,] NA NA NA NA NA NA [7,] NA NA NA NA NA NA [8,] NA NA NA NA NA NA [9,] NA NA NA NA NA NA [10,] NA NA NA NA NA NA [11,] NA NA NA NA NA NA [12,] NA NA NA NA NA NA [[2]] [,1] [,2] [,3] [,4] [,5] [,6] [1,] 0 0.00185 0.36984 0.42331 0.27552 0 [2,] 0 0.00174 0.40390 NA 0.44753 0 [3,] 0 0.00095 0.40382 NA NA 0 [4,] 0 0.00126 NA NA NA 0 [5,] NA NA NA NA NA NA [6,] NA NA NA NA NA NA [7,] NA NA NA NA NA NA [8,] NA NA NA NA NA NA [9,] NA NA NA NA NA NA [10,] NA NA NA NA NA NA [11,] NA NA NA NA NA NA [12,] NA NA NA NA NA NA [[3]] [[3]][[1]] Call: arima(x = series, order = order, seasonal = seasonal, include.mean = include.mean, method = "ML") Coefficients: ar1 ar2 ar3 sar1 sar2 sma1 -0.4037 -0.2307 -0.0625 0.1114 0.1346 -0.8146 s.e. 0.0689 0.0732 0.0696 0.1389 0.1232 0.1181 sigma^2 estimated as 0.7057: log likelihood = -269.69, aic = 553.37 [[3]][[2]] Call: arima(x = series, order = order, seasonal = seasonal, include.mean = include.mean, method = "ML") Coefficients: ar1 ar2 ar3 sar1 sar2 sma1 -0.4037 -0.2307 -0.0625 0.1114 0.1346 -0.8146 s.e. 0.0689 0.0732 0.0696 0.1389 0.1232 0.1181 sigma^2 estimated as 0.7057: log likelihood = -269.69, aic = 553.37 [[3]][[3]] Call: arima(x = series, order = order, seasonal = seasonal, include.mean = include.mean, fixed = last.arma$next.vector, method = "ML") Coefficients: ar1 ar2 ar3 sar1 sar2 sma1 -0.4016 -0.2321 -0.0581 0 0.0811 -0.7297 s.e. 0.0689 0.0732 0.0694 0 0.1065 0.0840 sigma^2 estimated as 0.71: log likelihood = -269.96, aic = 551.93 [[3]][[4]] Call: arima(x = series, order = order, seasonal = seasonal, include.mean = include.mean, fixed = last.arma$next.vector, method = "ML") Coefficients: ar1 ar2 ar3 sar1 sar2 sma1 -0.4068 -0.2415 -0.0580 0 0 -0.6976 s.e. 0.0684 0.0721 0.0694 0 0 0.0734 sigma^2 estimated as 0.7126: log likelihood = -270.26, aic = 550.52 [[3]][[5]] NULL [[3]][[6]] NULL $aic [1] 553.3728 551.9294 550.5231 549.2213 Warning messages: 1: In arima(series, order = order, seasonal = seasonal, include.mean = include.mean, : some AR parameters were fixed: setting transform.pars = FALSE 2: In arima(series, order = order, seasonal = seasonal, include.mean = include.mean, : some AR parameters were fixed: setting transform.pars = FALSE 3: 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/1k0g11292018168.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 = 226 Frequency = 1 [1] 0.0379864256 0.0161359174 0.0132666568 0.0131368515 0.0131500893 [6] 0.0108843071 0.0120935755 0.0114573189 0.0080239828 0.0052982729 [11] -0.0007661749 -0.0425484138 -0.2406000262 -0.6133753439 0.8665674840 [16] -0.5469091996 -0.7099483407 0.4551352846 0.8891859196 0.2227696425 [21] 0.1280221067 0.6259020255 -0.4563385249 -0.1195717887 0.4278403277 [26] -0.4695973818 1.1739417088 -1.4425742380 0.2074973735 -0.4450074298 [31] 0.0661568614 -0.7612261276 0.6067690778 -0.0294793997 0.5287815239 [36] -0.0801246492 0.1923588932 -0.4475522302 0.6742216043 -0.6260003120 [41] -0.7548201343 -0.6267694994 -0.5226960598 -0.3684394879 0.4196080780 [46] 0.6608454077 0.5146934190 0.3110780936 -0.6142629585 0.5928833493 [51] 0.7695249469 -1.2094691652 -0.0144470617 -0.0064900885 -1.0578293176 [56] -0.1841349609 0.4515576292 0.7276310549 1.1129875484 0.2333619832 [61] -0.9235806114 0.7314395656 0.8728204401 -0.1356964185 0.1032158269 [66] -0.2608680545 0.0580889470 -0.1897669999 -0.4743577455 0.8506965511 [71] 0.9684649305 -0.4542665515 -0.4101698952 0.7192836202 -0.2240534900 [76] -0.5899601932 -0.2288451132 -0.5032544219 -0.1198582708 0.4754283101 [81] -0.8580079076 0.4179538656 0.2044365721 -0.3849332779 -0.3074695225 [86] 0.4219859105 -0.0276399333 -0.3816240365 0.0649688027 -0.4470427673 [91] -0.1870700793 0.0921852096 0.1140347244 0.7285080709 0.3167210076 [96] -2.1632318538 -0.3095094962 1.2213959502 0.3282730133 0.6398700919 [101] -0.2057760935 -0.4948414328 0.1223212605 -0.7326886696 0.1088085692 [106] 0.0552220947 -0.4706159498 -0.3816688377 -0.1645531319 -0.7672286313 [111] 0.0283595821 0.4424337785 -0.5569668690 0.5049832312 -0.0864975201 [116] -0.5925341073 -2.2558057246 -3.0174783351 -0.7225625554 0.7834202354 [121] 0.3712334869 1.0829289787 0.5525100964 0.1647325609 0.5707509765 [126] -0.1041118093 0.2148968808 -0.1378000067 0.4610668730 0.2978018143 [131] -1.1354908962 0.4522036363 -0.6583674018 -0.5529230025 -2.1125362680 [136] -2.1463036966 -0.5405966747 0.9747304891 1.2503994131 0.1729478779 [141] 0.1467185288 1.3237054101 0.0301002505 0.1128687688 -0.6508434609 [146] 1.0050619588 -0.3746903824 0.9328740047 0.1747696833 -0.5496491460 [151] 0.1422337953 -0.6579306975 -0.2025040657 0.5267727388 -0.2427821323 [156] -0.0225511429 0.4167926336 -0.8865445716 -0.6353822198 0.6521864444 [161] 1.2270264391 -0.3766952152 0.3769893504 -0.4234314894 0.1589495199 [166] 0.0975989500 -0.4818448371 -0.1250531967 -0.1271819620 -1.1407808239 [171] 0.0159951131 1.6529625072 0.2528803757 0.7579193338 -0.0955583472 [176] -0.5727897457 -0.1904603575 -0.2395435961 -0.0374821900 0.5085036119 [181] -0.3434928276 -0.3788750093 0.7128363894 -0.1162206004 -0.1821051139 [186] -0.4763511596 0.5685435860 0.0895364264 -0.3202429966 0.0901688849 [191] -0.2484968989 -0.0646514253 -0.7611373151 0.1060240685 0.1221845737 [196] -0.4169777440 0.3073467863 0.1554710568 -0.8459012447 -0.6417529470 [201] -0.8463738111 -0.0167476121 -1.0764745679 -0.3421287436 -1.6484685825 [206] -1.6908589381 -1.1272543682 1.6136362196 -0.7160350199 -0.3147770881 [211] 0.8552861760 0.6475755906 -0.4202189937 -0.0222285045 0.2220175397 [216] 0.5304328302 0.0461913018 0.3259173341 0.7676201421 -5.7977976966 [221] 3.5801831719 1.1715469178 1.4247684286 0.4685597005 0.0882690632 [226] 0.7765232026 > postscript(file="/var/www/rcomp/tmp/2k0g11292018168.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/3k0g11292018168.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/4d9fm1292018168.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/5d9fm1292018168.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/6d9fm1292018168.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/7d9fm1292018168.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/89jvd1292018168.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/9cjt01292018168.tab") > > try(system("convert tmp/1k0g11292018168.ps tmp/1k0g11292018168.png",intern=TRUE)) character(0) > try(system("convert tmp/2k0g11292018168.ps tmp/2k0g11292018168.png",intern=TRUE)) character(0) > try(system("convert tmp/3k0g11292018168.ps tmp/3k0g11292018168.png",intern=TRUE)) character(0) > try(system("convert tmp/4d9fm1292018168.ps tmp/4d9fm1292018168.png",intern=TRUE)) character(0) > try(system("convert tmp/5d9fm1292018168.ps tmp/5d9fm1292018168.png",intern=TRUE)) character(0) > try(system("convert tmp/6d9fm1292018168.ps tmp/6d9fm1292018168.png",intern=TRUE)) character(0) > try(system("convert tmp/7d9fm1292018168.ps tmp/7d9fm1292018168.png",intern=TRUE)) character(0) > > > proc.time() user system elapsed 6.84 1.43 8.30