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) > par9 = '0' > par8 = '0' > par7 = '1' > 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] [,4] [1,] -0.2902605 0.2667876 0.02544153 0.7708516 [2,] -0.3276065 0.2831150 0.00000000 0.8126868 [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,] 0.21630 0.04120 0.70743 0.00085 [2,] 0.02659 0.00252 NA 0.00000 [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 -0.2903 0.2668 0.0254 0.7709 s.e. 0.2343 0.1302 0.0677 0.2290 sigma^2 estimated as 111.2: log likelihood = -1351.51, aic = 2713.02 [[3]][[2]] Call: arima(x = series, order = order, seasonal = seasonal, include.mean = include.mean, method = "ML") Coefficients: ar1 ar2 ar3 ma1 -0.2903 0.2668 0.0254 0.7709 s.e. 0.2343 0.1302 0.0677 0.2290 sigma^2 estimated as 111.2: log likelihood = -1351.51, aic = 2713.02 [[3]][[3]] NULL [[3]][[4]] NULL $aic [1] 2713.025 2711.174 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/1i4li1260449532.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 = 359 Frequency = 1 [1] 0.254999839 22.431959165 8.488423888 31.346385590 16.430753104 [6] 5.838963381 -13.511060081 -4.381911125 -4.643426277 -2.397904526 [11] -9.625286525 0.570943888 -4.325754397 -0.182017814 -1.875748246 [16] -10.205760379 -0.230847340 -6.721834033 -0.968770586 -13.288854577 [21] -0.821710152 -2.092252272 2.055762659 -1.958347484 -2.873743916 [26] -2.709811409 -4.915856774 -0.539200029 -0.528445393 5.667705122 [31] 19.591206466 16.678255642 -0.324432057 0.628639760 1.679638224 [36] 0.371340805 -12.877577627 11.429627625 -11.061199032 0.003463289 [41] 2.183990024 -1.810946475 7.229636839 -6.107451334 -8.974187559 [46] -1.523603816 -11.324532671 -3.222157423 0.171025586 -13.724083863 [51] 1.680894070 -0.946309709 -0.673915407 1.618351265 -3.576058952 [56] -0.057593282 -0.440928919 0.992017595 -3.567778898 10.737576808 [61] -6.621190149 13.661810974 -5.871015234 2.149384606 -1.653278116 [66] -0.488459650 -3.186965217 3.382418596 -2.810525449 -0.812910071 [71] -0.600537523 1.350920368 1.102395451 1.133163151 -0.675343429 [76] -3.991469030 1.392698267 -0.900927210 -0.626701935 1.829362197 [81] -2.807598977 2.158561707 1.575100095 -2.928359419 5.353025773 [86] 3.176630693 -4.170171975 1.996736345 0.498077316 3.282578760 [91] 0.513265328 -1.365856634 1.420354936 0.308147398 -1.405316216 [96] 1.490820911 -0.588372243 2.214745807 -0.752160866 -0.637666511 [101] -0.698260229 1.009300041 -0.099107028 -5.149565596 1.167439229 [106] 1.231427839 -1.277520553 -7.397444266 24.003780447 73.397864304 [111] -17.043348360 -10.640732478 -5.248356133 1.008835886 -7.793022458 [116] -8.658695734 -14.814985256 7.818404376 2.652224401 -0.647340823 [121] -3.692337176 -5.885080527 -2.514227886 -6.900871797 -5.513902271 [126] 2.756123052 -2.648232090 -7.933236764 8.033258031 4.003730051 [131] -14.022303145 2.419326449 10.373875682 -3.632747819 -6.228297962 [136] 10.277404470 -5.760861138 0.529405855 5.640833745 -6.402654524 [141] 2.971455765 0.460132044 3.649986996 1.137286847 2.955904013 [146] 6.678920040 -5.018592289 8.644298775 0.465446667 -0.560051354 [151] 4.873884808 -7.702365353 -4.487570507 -3.366558825 -10.561512352 [156] 9.409290401 -4.511999646 7.133944067 -11.058887838 4.547136410 [161] 3.472784938 3.109718660 5.036175250 -5.522449461 1.119799496 [166] 0.103175300 -8.312352962 3.412070830 -0.091330985 3.109474845 [171] -9.438804749 7.337087591 -7.296907964 2.414197986 -7.214107585 [176] -3.848272023 -0.924185323 3.499748642 -4.531625555 -2.556738552 [181] 5.722396396 0.201539059 -6.299902855 0.658831638 5.210449640 [186] -5.471319956 4.669422609 -5.904091409 -4.812118724 -2.024771049 [191] -7.718566880 1.712138173 -0.494466602 11.010133605 -4.195736860 [196] 2.387205223 1.774006966 1.180844871 0.115962559 -5.055029193 [201] 1.354906688 -7.805196359 5.861486794 2.802884462 3.921842700 [206] -2.971552456 -0.591913070 0.049383555 2.267005380 5.112909625 [211] 71.677906093 78.484226342 -49.621617231 4.534921584 -2.838817405 [216] -6.613458144 2.962022870 -15.632400631 -5.482456007 2.503487128 [221] -0.547677981 0.089588995 -2.986669704 4.030126150 -7.035930570 [226] -9.831651688 0.082603742 -4.109158396 -14.438163232 9.133957067 [231] -5.837067027 1.136873351 -8.809883531 4.497328105 -7.168076600 [236] 5.213249590 -7.865748506 5.389613229 -8.440057849 6.986993393 [241] -3.789891376 3.833164633 17.235307369 30.194190569 4.042968583 [246] 24.334133365 3.793505583 -2.076535756 -8.556566900 -19.016170925 [251] 0.510769492 -11.042029982 -6.263089030 -0.304817715 8.715195075 [256] -10.643258945 -3.511983948 -7.022312864 3.592010976 -7.243776234 [261] -4.126625495 -9.131533419 3.954482956 -3.922743293 1.736834867 [266] -1.344266052 6.018103083 -4.031076984 4.454330418 -9.847204031 [271] 4.594562845 -0.870304656 -2.381969819 9.509347613 -18.333574124 [276] 8.638323729 16.573384832 6.628522087 -10.707479314 -2.069279706 [281] -4.301852576 -6.803088991 5.380204553 -1.109232863 -9.848764225 [286] 2.359395595 -7.050959321 1.041384213 1.527639053 -0.513961679 [291] -1.248270488 -6.929859852 0.344841817 6.819164599 -8.421085775 [296] -1.816307379 -0.756283542 0.484156868 -2.673467923 -5.902641573 [301] 5.418874861 -0.439950392 -8.493402955 15.396583809 -2.676823147 [306] -7.120727967 6.038700556 -6.464422220 1.935111479 -5.442533860 [311] 4.108658834 -5.949293462 19.266752082 -16.530188809 7.282031732 [316] 3.739166759 -7.854686289 1.370143900 1.773046252 -2.948709492 [321] 1.073859362 -9.705300909 0.264771018 10.573593876 -2.197797800 [326] -3.856510706 8.830082116 -6.083518495 -5.643131183 -5.538054646 [331] 16.833232049 -6.903710411 1.712931844 -5.162171989 -3.100902186 [336] 1.307974619 27.974277605 -24.328809889 15.211850499 15.590148877 [341] 2.023804883 3.384926183 -11.246117980 18.541470562 -11.530550117 [346] 4.132595904 -18.028396299 3.716251677 -0.739661045 -3.377741923 [351] 13.847824015 -6.333308628 7.080165526 -22.986270650 10.277236157 [356] 1.112297533 -1.345674045 -4.240615252 4.759730219 > postscript(file="/var/www/html/rcomp/tmp/2zm3r1260449532.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/3psxw1260449532.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/4m9xy1260449532.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/5knlu1260449532.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/653tu1260449532.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/7oxbu1260449532.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/8fc7b1260449532.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/9ql881260449532.tab") > > system("convert tmp/1i4li1260449532.ps tmp/1i4li1260449532.png") > system("convert tmp/2zm3r1260449532.ps tmp/2zm3r1260449532.png") > system("convert tmp/3psxw1260449532.ps tmp/3psxw1260449532.png") > system("convert tmp/4m9xy1260449532.ps tmp/4m9xy1260449532.png") > system("convert tmp/5knlu1260449532.ps tmp/5knlu1260449532.png") > system("convert tmp/653tu1260449532.ps tmp/653tu1260449532.png") > system("convert tmp/7oxbu1260449532.ps tmp/7oxbu1260449532.png") > > > proc.time() user system elapsed 2.180 1.143 2.560