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 <- c(255 + ,280.2 + ,299.9 + ,339.2 + ,374.2 + ,393.5 + ,389.2 + ,381.7 + ,375.2 + ,369 + ,357.4 + ,352.1 + ,346.5 + ,342.9 + ,340.3 + ,328.3 + ,322.9 + ,314.3 + ,308.9 + ,294 + ,285.6 + ,281.2 + ,280.3 + ,278.8 + ,274.5 + ,270.4 + ,263.4 + ,259.9 + ,258 + ,262.7 + ,284.7 + ,311.3 + ,322.1 + ,327 + ,331.3 + ,333.3 + ,321.4 + ,327 + ,320 + ,314.7 + ,316.7 + ,314.4 + ,321.3 + ,318.2 + ,307.2 + ,301.3 + ,287.5 + ,277.7 + ,274.4 + ,258.8 + ,253.3 + ,251 + ,248.4 + ,249.5 + ,246.1 + ,244.5 + ,243.6 + ,244 + ,240.8 + ,249.8 + ,248 + ,259.4 + ,260.5 + ,260.8 + ,261.3 + ,259.5 + ,256.6 + ,257.9 + ,256.5 + ,254.2 + ,253.3 + ,253.8 + ,255.5 + ,257.1 + ,257.3 + ,253.2 + ,252.8 + ,252 + ,250.7 + ,252.2 + ,250 + ,251 + ,253.4 + ,251.2 + ,255.6 + ,261.1 + ,258.9 + ,259.9 + ,261.2 + ,264.7 + ,267.1 + ,266.4 + ,267.7 + ,268.6 + ,267.5 + ,268.5 + ,268.5 + ,270.5 + ,270.9 + ,270.1 + ,269.3 + ,269.8 + ,270.1 + ,264.9 + ,263.7 + ,264.8 + ,263.7 + ,255.9 + ,276.2 + ,360.1 + ,380.5 + ,373.7 + ,369.8 + ,366.6 + ,359.3 + ,345.8 + ,326.2 + ,324.5 + ,328.1 + ,327.5 + ,324.4 + ,316.5 + ,310.9 + ,301.5 + ,291.7 + ,290.4 + ,287.4 + ,277.7 + ,281.6 + ,288 + ,276 + ,272.9 + ,283 + ,283.3 + ,276.8 + ,284.5 + ,282.7 + ,281.2 + ,287.4 + ,283.1 + ,284 + ,285.5 + ,289.2 + ,292.5 + ,296.4 + ,305.2 + ,303.9 + ,311.5 + ,316.3 + ,316.7 + ,322.5 + ,317.1 + ,309.8 + ,303.8 + ,290.3 + ,293.7 + ,291.7 + ,296.5 + ,289.1 + ,288.5 + ,293.8 + ,297.7 + ,305.4 + ,302.7 + ,302.5 + ,303 + ,294.5 + ,294.1 + ,294.5 + ,297.1 + ,289.4 + ,292.4 + ,287.9 + ,286.6 + ,280.5 + ,272.4 + ,269.2 + ,270.6 + ,267.3 + ,262.5 + ,266.8 + ,268.8 + ,263.1 + ,261.2 + ,266 + ,262.5 + ,265.2 + ,261.3 + ,253.7 + ,249.2 + ,239.1 + ,236.4 + ,235.2 + ,245.2 + ,246.2 + ,247.7 + ,251.4 + ,253.3 + ,254.8 + ,250 + ,249.3 + ,241.5 + ,243.3 + ,248 + ,253 + ,252.9 + ,251.5 + ,251.6 + ,253.5 + ,259.8 + ,334.1 + ,448 + ,445.8 + ,445 + ,448.2 + ,438.2 + ,439.8 + ,423.4 + ,410.8 + ,408.4 + ,406.7 + ,405.9 + ,402.7 + ,405.1 + ,399.6 + ,386.5 + ,381.4 + ,375.2 + ,357.7 + ,359 + ,355 + ,352.7 + ,344.4 + ,343.8 + ,338 + ,339 + ,333.3 + ,334.4 + ,328.3 + ,330.7 + ,330 + ,331.6 + ,351.2 + ,389.4 + ,410.9 + ,442.8 + ,462.8 + ,466.9 + ,461.7 + ,439.2 + ,430.3 + ,416.1 + ,402.5 + ,397.3 + ,403.3 + ,395.9 + ,387.8 + ,378.6 + ,377.1 + ,370.4 + ,362 + ,350.3 + ,348.2 + ,344.6 + ,343.5 + ,342.8 + ,347.6 + ,346.6 + ,349.5 + ,342.1 + ,342 + ,342.8 + ,339.3 + ,348.2 + ,333.7 + ,334.7 + ,354 + ,367.7 + ,363.3 + ,358.4 + ,353.1 + ,343.1 + ,344.6 + ,344.4 + ,333.9 + ,331.7 + ,324.3 + ,321.2 + ,322.4 + ,321.7 + ,320.5 + ,312.8 + ,309.7 + ,315.6 + ,309.7 + ,304.6 + ,302.5 + ,301.5 + ,298.8 + ,291.3 + ,293.6 + ,294.6 + ,285.9 + ,297.6 + ,301.1 + ,293.8 + ,297.7 + ,292.9 + ,292.1 + ,287.2 + ,288.2 + ,283.8 + ,299.9 + ,292.4 + ,293.3 + ,300.8 + ,293.7 + ,293.1 + ,294.4 + ,292.1 + ,291.9 + ,282.5 + ,277.9 + ,287.5 + ,289.2 + ,285.6 + ,293.2 + ,290.8 + ,283.1 + ,275 + ,287.8 + ,287.8 + ,287.4 + ,284 + ,277.8 + ,277.6 + ,304.9 + ,294 + ,300.9 + ,324 + ,332.9 + ,341.6 + ,333.4 + ,348.2 + ,344.7 + ,344.7 + ,329.3 + ,323.5 + ,323.2 + ,317.4 + ,330.1 + ,329.2 + ,334.9 + ,315.8 + ,315.4 + ,319.6 + ,317.3 + ,313.8) > par9 = '0' > par8 = '0' > par7 = '1' > par6 = '3' > par5 = '1' > par4 = '0' > par3 = '1' > par2 = '1' > 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] [1,] -0.3014570 0.2725371 0.02429231 0.7823631 [2,] -0.3296855 0.2842697 0.00000000 0.8154003 [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,] 0.13803 0.01905 0.70939 8e-05 [2,] 0.02116 0.00192 NA 0e+00 [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 ar2 ar3 ma1 -0.3015 0.2725 0.0243 0.7824 s.e. 0.2028 0.1157 0.0651 0.1962 sigma^2 estimated as 111.5: log likelihood = -1348.13, aic = 2706.27 [[3]][[2]] Call: arima(x = series, order = order, seasonal = seasonal, include.mean = include.mean, method = "ML") Coefficients: ar1 ar2 ar3 ma1 -0.3015 0.2725 0.0243 0.7824 s.e. 0.2028 0.1157 0.0651 0.1962 sigma^2 estimated as 111.5: log likelihood = -1348.13, aic = 2706.27 [[3]][[3]] NULL [[3]][[4]] NULL $aic [1] 2706.269 2704.420 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/html/rcomp/tmp/18ioc1260646569.ps",horizontal=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 = 358 Frequency = 1 [1] 0.25499984 22.42780789 8.48479941 31.33649247 16.43574998 [6] 5.83652278 -13.51349160 -4.34460964 -4.65924721 -2.36686209 [11] -9.66236184 0.60871815 -4.36155805 -0.14983292 -1.91301949 [16] -10.16981784 -0.26507100 -6.68684310 -0.99781119 -13.27219296 [21] -0.82744423 -2.09289554 2.06225770 -1.98152560 -2.84974346 [26] -2.73606260 -4.88703149 -0.56490753 -0.50577884 5.64686017 [31] 19.60179655 16.66156402 -0.32662483 0.62735815 1.69674167 [36] 0.37100856 -12.87829108 11.43862968 -11.06639564 0.01061110 [41] 2.16569851 -1.77695580 7.18054855 -6.05949191 -9.01842752 [46] -1.48309469 -11.34506401 -3.20896366 0.16063200 -13.71438351 [51] 1.66433462 -0.92838470 -0.68910326 1.61578365 -3.56805802 [56] -0.07006781 -0.42760829 0.98188679 -3.56345810 10.73610380 [61] -6.62401624 13.66466486 -5.88218322 2.17040929 -1.68433417 [66] -0.43999327 -3.24194441 3.44057280 -2.86579933 -0.76379473 [71] -0.64581449 1.39479460 1.06064840 1.16825935 -0.70713092 [76] -3.96383172 1.37180664 -0.88129015 -0.64306343 1.83896152 [81] -2.81281801 2.16021389 1.57452853 -2.92745008 5.34874210 [86] 3.18303260 -4.17799353 1.99966233 0.50296888 3.27929588 [91] 0.51090908 -1.36167928 1.41519559 0.31717176 -1.41412571 [96] 1.49789364 -0.59251195 2.21774395 -0.75645924 -0.63266555 [101] -0.70379092 1.01776714 -0.10807141 -5.14184649 1.16130701 [106] 1.23959291 -1.28484447 -7.39702787 24.00886588 73.38843821 [111] -17.06718197 -10.65653773 -5.21050761 1.05851526 -7.86472347 [116] -8.58070839 -14.88918449 7.89677475 2.57905086 -0.59306646 [121] -3.75671745 -5.81932985 -2.56924144 -6.84973070 -5.55660282 [126] 2.79088740 -2.67617035 -7.91827134 8.02002116 4.01760051 [131] -14.04115642 2.42882070 10.38023759 -3.64002592 -6.23905925 [136] 10.29462540 -5.76871241 0.52996955 5.63670174 -6.38838195 [141] 2.94847756 0.48582840 3.63126494 1.14375471 2.95515112 [146] 6.67442739 -5.01206289 8.63629256 0.47488282 -0.56423875 [151] 4.86922284 -7.68666732 -4.50453520 -3.34564955 -10.57053039 [156] 9.41287909 -4.51433081 7.13025190 -11.06897182 4.56957954 [161] 3.44422666 3.14637188 4.98420613 -5.46988354 1.07222547 [166] 0.14963825 -8.34624626 3.43600007 -0.10436346 3.11773244 [171] -9.45470838 7.35748231 -7.31647600 2.43702367 -7.24499162 [176] -3.80706032 -0.96924240 3.54937037 -4.58597012 -2.51073099 [181] 5.68267256 0.23869462 -6.33913809 0.69167142 5.19097013 [186] -5.45794299 4.65297093 -5.88910204 -4.81909340 -2.02348737 [191] -7.70743306 1.69633344 -0.47914281 10.99431768 -4.19434418 [196] 2.38673714 1.76943031 1.19795617 0.09070604 -5.02648150 [201] 1.33057879 -7.78027617 5.84301503 2.81405719 3.91414693 [206] -2.97964929 -0.57583733 0.03426615 2.28731827 5.09001053 [211] 71.69669333 78.44227279 -49.63692803 4.52400303 -2.74789166 [216] -6.61401572 2.90730656 -15.54460273 -5.57550825 2.59445346 [221] -0.62094042 0.13349604 -3.02399342 4.06052490 -7.06175541 [226] -9.80951053 0.06616407 -4.08535183 -14.46463678 9.15472035 [231] -5.85040997 1.14213395 -8.82834635 4.52888340 -7.20617538 [236] 5.25454324 -7.91421321 5.44184150 -8.49672417 7.04731082 [241] -3.85430434 3.89853966 17.16473214 30.26045046 3.96040513 [246] 24.39580598 3.74258799 -2.01513932 -8.61312183 -18.93223631 [251] 0.44669374 -10.97404014 -6.32284901 -0.26682402 8.69263173 [256] -10.64448370 -3.51183338 -7.02325276 3.60864237 -7.27134531 [261] -4.09863510 -9.16318146 3.99395750 -3.96504549 1.77340782 [266] -1.38690424 6.06128587 -4.07763503 4.49756076 -9.88856614 [271] 4.63960183 -0.91367228 -2.33699407 9.45767782 -18.28192445 [276] 8.59141891 16.61543400 6.59852012 -10.71673497 -2.04463270 [281] -4.31113592 -6.78253085 5.35531021 -1.08349146 -9.87849015 [286] 2.38133607 -7.05977719 1.04717784 1.51642733 -0.50002026 [291] -1.27156085 -6.90530100 0.32528251 6.83868040 -8.43981882 [296] -1.80825639 -0.75807377 0.49329288 -2.69117252 -5.88490903 [301] 5.40335021 -0.42441325 -8.51114061 15.40771660 -2.68060112 [306] -7.12503763 6.03563020 -6.44187428 1.90733016 -5.41995241 [311] 4.09786397 -5.94969495 19.27490600 -16.55164581 7.30750820 [316] 3.70710846 -7.80246802 1.29812684 1.85634012 -3.02444016 [321] 1.13313634 -9.75156019 0.30594430 10.54064505 -2.17060572 [326] -3.89393251 8.86470447 -6.10450752 -5.63138498 -5.54596408 [331] 16.85399258 -6.93269043 1.73217428 -5.18671366 -3.05804579 [336] 1.25981148 28.02640233 -24.39192569 15.26205688 15.54705757 [341] 2.08449409 3.28891304 -11.13718033 18.45409691 -11.45277916 [346] 4.07078030 -17.99047473 3.71766804 -0.75994613 -3.34106663 [351] 13.78813292 -6.27081910 7.01442063 -22.93274768 10.25230756 [356] 1.12538212 -1.34133982 -4.27887522 > postscript(file="/var/www/html/rcomp/tmp/2oeod1260646569.ps",horizontal=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/html/rcomp/tmp/36dzh1260646569.ps",horizontal=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/html/rcomp/tmp/4s36j1260646569.ps",horizontal=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/html/rcomp/tmp/59s851260646569.ps",horizontal=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/html/rcomp/tmp/68f811260646569.ps",horizontal=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/html/rcomp/tmp/7g4o91260646569.ps",horizontal=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/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab > load(file="/var/www/html/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/html/rcomp/tmp/8gndd1260646569.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/html/rcomp/tmp/9eeex1260646569.tab") > > try(system("convert tmp/18ioc1260646569.ps tmp/18ioc1260646569.png",intern=TRUE)) character(0) > try(system("convert tmp/2oeod1260646569.ps tmp/2oeod1260646569.png",intern=TRUE)) character(0) > try(system("convert tmp/36dzh1260646569.ps tmp/36dzh1260646569.png",intern=TRUE)) character(0) > try(system("convert tmp/4s36j1260646569.ps tmp/4s36j1260646569.png",intern=TRUE)) character(0) > try(system("convert tmp/59s851260646569.ps tmp/59s851260646569.png",intern=TRUE)) character(0) > try(system("convert tmp/68f811260646569.ps tmp/68f811260646569.png",intern=TRUE)) character(0) > try(system("convert tmp/7g4o91260646569.ps tmp/7g4o91260646569.png",intern=TRUE)) character(0) > > > proc.time() user system elapsed 2.056 1.066 2.845