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 + ,315.8 + ,311.3) > par9 = '0' > par8 = '0' > par7 = '0' > par6 = '3' > par5 = '12' > 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] [1,] 0.4719604 -0.09258698 0.07878786 [2,] 0.4664128 -0.05688659 0.00000000 [3,] 0.4417024 0.00000000 0.00000000 [4,] NA NA NA [5,] NA NA NA [6,] NA NA NA [[2]] [,1] [,2] [,3] [1,] 0 0.11186 0.14168 [2,] 0 0.28340 NA [3,] 0 NA NA [4,] NA NA NA [5,] NA NA NA [6,] NA NA NA [[3]] [[3]][[1]] Call: arima(x = series, order = order, seasonal = seasonal, include.mean = include.mean, method = "ML") Coefficients: ar1 ar2 ar3 0.4720 -0.0926 0.0788 s.e. 0.0528 0.0581 0.0535 sigma^2 estimated as 111.6: log likelihood = -1355.89, aic = 2719.77 [[3]][[2]] Call: arima(x = series, order = order, seasonal = seasonal, include.mean = include.mean, method = "ML") Coefficients: ar1 ar2 ar3 0.4720 -0.0926 0.0788 s.e. 0.0528 0.0581 0.0535 sigma^2 estimated as 111.6: log likelihood = -1355.89, aic = 2719.77 [[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 0.4664 -0.0569 0 s.e. 0.0528 0.0530 0 sigma^2 estimated as 112.3: log likelihood = -1356.97, aic = 2719.93 $aic [1] 2719.771 2719.933 2719.085 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 > postscript(file="/var/www/html/rcomp/tmp/13d531260469735.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 = 360 Frequency = 1 [1] 0.25499984 22.57661854 8.56515338 31.54521031 17.79064365 [6] 5.21119571 -11.31073603 -4.39651392 -3.24651650 -3.59496636 [11] -9.07800360 -0.24230863 -3.78789670 -1.28958736 -1.23947889 [16] -10.99211850 0.04904819 -6.76401006 -1.69603769 -12.87059566 [21] -1.75763720 -1.32974283 0.67436888 -1.33052949 -3.65157876 [26] -2.17975494 -5.33231994 -0.46834557 -0.66576139 5.38708122 [31] 19.69977543 16.60628587 -0.35507493 1.37592524 2.62895254 [36] 0.27316934 -12.58821323 11.26408522 -10.28886194 -1.71654567 [41] 4.07378160 -3.53432447 8.08652256 -6.44908731 -9.16160294 [46] -0.94580788 -11.67391708 -3.69913455 0.48581030 -14.61832639 [51] 1.58831358 -0.62216049 -1.84012685 2.18183407 -4.06095918 [56] 0.04837869 -0.34715395 0.72875296 -3.43776304 10.51527552 [61] -6.17975207 12.75152229 -4.31950151 0.43545304 0.42265141 [66] -2.01614041 -2.03201371 2.55020119 -2.17130771 -1.57306955 [71] 0.09310816 0.78893235 1.41559568 0.83554157 -0.44955324 [76] -4.10226402 1.52366970 -0.84666990 -0.94962441 2.06082734 [81] -2.97357173 2.11143799 1.80843673 -3.26250408 5.56263592 [86] 3.32263329 -4.51496929 2.33898434 0.70843673 2.95054998 [91] 0.84150785 -1.62028761 1.76301675 0.25384278 -1.44581894 [96] 1.56425198 -0.52898802 2.05688659 -0.53282555 -0.87279194 [101] -0.40411514 0.82762095 0.02128434 -5.31148054 1.24241242 [106] 1.36388508 -1.68131796 -7.22437070 23.87544441 73.98810525 [111] -17.57723424 -11.54203595 0.43209327 -1.76781897 -6.02933681 [116] -10.27722381 -13.71869960 6.67372149 3.27792460 -2.37579319 [121] -2.61536062 -6.48825234 -2.09168749 -7.23749249 -5.73428479 [126] 2.73611129 -2.95115195 -8.37471423 8.25354417 4.02919027 [131] -14.76318408 2.86102748 10.86324056 -4.58711747 -6.06536930 [136] 10.74874902 -5.76114120 -0.22243028 6.79722331 -7.27708910 [141] 3.25827178 0.83561617 3.05157876 1.65960261 2.57131821 [146] 7.16871591 -5.18257474 8.70693858 1.18131033 -1.40644326 [151] 5.88649051 -8.08243947 -4.45142880 -2.90237430 -11.11679543 [156] 9.35525296 -4.35377237 5.92623995 -9.75255450 3.12451017 [161] 5.15888692 1.39388033 6.18248908 -6.06952069 1.49734122 [166] 0.43968877 -8.74458371 3.59295190 0.10302912 2.39068025 [171] -8.88991858 6.73928351 -6.33726505 0.96951726 -5.74965303 [176] -5.32883463 0.23093531 2.43173953 -4.13501497 -3.18119661 [181] 6.35105559 -0.27863056 -6.38821323 0.87232600 5.36193073 [186] -5.84686584 4.60550034 -5.35841755 -5.62739638 -1.17712059 [191] -8.43348057 1.75477940 -0.51524004 10.40610155 -3.73239167 [196] 1.60245310 3.05726742 0.25960261 0.82429610 -5.39153465 [201] 1.62411121 -7.74656668 5.39819905 3.41674162 2.91025581 [206] -2.16469692 -1.06892578 0.74728923 1.77371750 5.41950438 [211] 71.46968402 79.60391619 -51.09774181 6.70549043 3.44797973 [216] -11.53803016 6.44616485 -17.71512632 -4.85981192 2.54386095 [221] -1.29738034 -0.14362609 -2.92357698 3.84701162 -6.80142774 [226] -10.39820192 0.69713114 -4.56650914 -14.89836238 9.10952675 [231] -5.60185189 -0.36039633 -7.45479696 3.14038690 -5.99231101 [236] 3.67106215 -6.49635498 3.81543941 -6.93730760 5.30769318 [241] -2.16639885 2.06301675 18.81391895 29.14932812 4.79800905 [246] 24.04519295 6.34449406 -3.41357339 -5.97456063 -19.84141855 [251] 1.29847722 -11.32887451 -7.48322920 0.33542422 7.65168885 [256] -10.49428692 -4.30722593 -5.84301726 2.33021619 -6.52373744 [261] -5.36036428 -8.16327281 2.87918215 -3.28610624 0.45962416 [266] -0.39173766 5.06391370 -3.27860194 3.63946840 -8.80948364 [271] 3.51642565 0.42568053 -3.87881888 10.57795399 -18.85017677 [276] 8.26927589 18.00873170 4.75512000 -9.69194390 -2.06843753 [281] -3.26487838 -7.80675656 5.86262885 -1.46848504 -10.32138756 [286] 2.68595684 -6.97120106 0.22630405 2.22491886 -1.43604375 [291] -0.80524715 -7.18012528 0.42311448 6.90785288 -8.82818380 [296] -2.01253375 -0.05692571 -0.31065477 -2.35304906 -6.29757209 [301] 5.64450204 -0.49939879 -9.03557363 15.81467774 -2.45194280 [306] -8.26687164 7.50391633 -7.03428192 1.66063902 -4.79992540 [311] 3.23991334 -5.14515706 18.20910280 -15.25954669 5.31396988 [316] 6.65357909 -10.54689790 3.13818012 1.17595289 -2.94046856 [321] 0.94670195 -9.43755660 -0.22709722 11.21076485 -3.03924096 [326] -3.84679048 9.37579319 -6.14952882 -6.14827127 -4.64514943 [331] 16.13991677 -6.43086490 0.32814832 -3.21343489 -4.63695119 [336] 2.49834482 27.04058571 -23.64444612 13.53690311 19.26168804 [341] -1.48161769 5.86300646 -11.75150053 19.11949808 -10.86937911 [346] 2.47436621 -15.59910306 1.38275676 1.52914066 -5.99001837 [351] 15.38812813 -7.15338447 6.84223116 -21.80975076 8.83273758 [356] 3.30003129 -4.28168830 -2.18832695 3.50160557 -5.63192861 > postscript(file="/var/www/html/rcomp/tmp/2iudu1260469735.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/3jgkp1260469735.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/49cwz1260469735.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/5z9oz1260469735.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/6vndp1260469735.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/7a40c1260469735.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/8c7no1260469735.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/91vsd1260469735.tab") > > system("convert tmp/13d531260469735.ps tmp/13d531260469735.png") > system("convert tmp/2iudu1260469735.ps tmp/2iudu1260469735.png") > system("convert tmp/3jgkp1260469735.ps tmp/3jgkp1260469735.png") > system("convert tmp/49cwz1260469735.ps tmp/49cwz1260469735.png") > system("convert tmp/5z9oz1260469735.ps tmp/5z9oz1260469735.png") > system("convert tmp/6vndp1260469735.ps tmp/6vndp1260469735.png") > system("convert tmp/7a40c1260469735.ps tmp/7a40c1260469735.png") > > > proc.time() user system elapsed 1.781 1.080 2.395