R version 2.15.2 (2012-10-26) -- "Trick or Treat" Copyright (C) 2012 The R Foundation for Statistical Computing ISBN 3-900051-07-0 Platform: i686-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(235.1 + ,280.7 + ,264.6 + ,240.7 + ,201.4 + ,240.8 + ,241.1 + ,223.8 + ,206.1 + ,174.7 + ,203.3 + ,220.5 + ,299.5 + ,347.4 + ,338.3 + ,327.7 + ,351.6 + ,396.6 + ,438.8 + ,395.6 + ,363.5 + ,378.8 + ,357 + ,369 + ,464.8 + ,479.1 + ,431.3 + ,366.5 + ,326.3 + ,355.1 + ,331.6 + ,261.3 + ,249 + ,205.5 + ,235.6 + ,240.9 + ,264.9 + ,253.8 + ,232.3 + ,193.8 + ,177 + ,213.2 + ,207.2 + ,180.6 + ,188.6 + ,175.4 + ,199 + ,179.6 + ,225.8 + ,234 + ,200.2 + ,183.6 + ,178.2 + ,203.2 + ,208.5 + ,191.8 + ,172.8 + ,148 + ,159.4 + ,154.5 + ,213.2 + ,196.4 + ,182.8 + ,176.4 + ,153.6 + ,173.2 + ,171 + ,151.2 + ,161.9 + ,157.2 + ,201.7 + ,236.4 + ,356.1 + ,398.3 + ,403.7 + ,384.6 + ,365.8 + ,368.1 + ,367.9 + ,347 + ,343.3 + ,292.9 + ,311.5 + ,300.9 + ,366.9 + ,356.9 + ,329.7 + ,316.2 + ,269 + ,289.3 + ,266.2 + ,253.6 + ,233.8 + ,228.4 + ,253.6 + ,260.1 + ,306.6 + ,309.2 + ,309.5 + ,271 + ,279.9 + ,317.9 + ,298.4 + ,246.7 + ,227.3 + ,209.1 + ,259.9 + ,266 + ,320.6 + ,308.5 + ,282.2 + ,262.7 + ,263.5 + ,313.1 + ,284.3 + ,252.6 + ,250.3 + ,246.5 + ,312.7 + ,333.2 + ,446.4 + ,511.6 + ,515.5 + ,506.4 + ,483.2 + ,522.3 + ,509.8 + ,460.7 + ,405.8 + ,375 + ,378.5 + ,406.8 + ,467.8 + ,469.8 + ,429.8 + ,355.8 + ,332.7 + ,378 + ,360.5 + ,334.7 + ,319.5 + ,323.1 + ,363.6 + ,352.1 + ,411.9 + ,388.6 + ,416.4 + ,360.7 + ,338 + ,417.2 + ,388.4 + ,371.1 + ,331.5 + ,353.7 + ,396.7 + ,447 + ,533.5 + ,565.4 + ,542.3 + ,488.7 + ,467.1 + ,531.3 + ,496.1 + ,444 + ,403.4 + ,386.3 + ,394.1 + ,404.1 + ,462.1 + ,448.1 + ,432.3 + ,386.3 + ,395.2 + ,421.9 + ,382.9 + ,384.2 + ,345.5 + ,323.4 + ,372.6 + ,376 + ,462.7 + ,487 + ,444.2 + ,399.3 + ,394.9 + ,455.4 + ,414 + ,375.5 + ,347 + ,339.4 + ,385.8 + ,378.8 + ,451.8 + ,446.1 + ,422.5 + ,383.1 + ,352.8 + ,445.3 + ,367.5 + ,355.1 + ,326.2 + ,319.8 + ,331.8 + ,340.9 + ,394.1 + ,417.2 + ,369.9 + ,349.2 + ,321.4 + ,405.7 + ,342.9 + ,316.5 + ,284.2 + ,270.9 + ,288.8 + ,278.8 + ,324.4 + ,310.9 + ,299 + ,273 + ,279.3 + ,359.2 + ,305 + ,282.1 + ,250.3 + ,246.5 + ,257.9 + ,266.5 + ,315.9 + ,318.4 + ,295.4 + ,266.4 + ,245.8 + ,362.8 + ,324.9 + ,294.2 + ,289.5 + ,295.2 + ,290.3 + ,272 + ,307.4 + ,328.7 + ,292.9 + ,249.1 + ,230.4 + ,361.5 + ,321.7 + ,277.2 + ,260.7 + ,251 + ,257.6 + ,241.8 + ,287.5 + ,292.3 + ,274.7 + ,254.2 + ,230 + ,339 + ,318.2 + ,287 + ,295.8 + ,284 + ,271 + ,262.7 + ,340.6 + ,379.4 + ,373.3 + ,355.2 + ,338.4 + ,466.9 + ,451 + ,422 + ,429.2 + ,425.9 + ,460.7 + ,463.6 + ,541.4 + ,544.2 + ,517.5 + ,469.4 + ,439.4 + ,549 + ,533 + ,506.1 + ,484 + ,457 + ,481.5 + ,469.5 + ,544.7 + ,541.2 + ,521.5 + ,469.7 + ,434.4 + ,542.6 + ,517.3 + ,485.7 + ,465.8 + ,447 + ,426.6 + ,411.6 + ,467.5 + ,484.5 + ,451.2 + ,417.4 + ,379.9 + ,484.7 + ,455 + ,420.8 + ,416.5 + ,376.3 + ,405.6 + ,405.8 + ,500.8 + ,514 + ,475.5 + ,430.1 + ,414.4 + ,538 + ,526 + ,488.5 + ,520.2 + ,504.4 + ,568.5 + ,610.6 + ,818 + ,830.9 + ,835.9 + ,782 + ,762.3 + ,856.9 + ,820.9 + ,769.6 + ,752.2 + ,724.4 + ,723.1 + ,719.5 + ,817.4 + ,803.3 + ,752.5 + ,689 + ,630.4 + ,765.5 + ,757.7 + ,732.2 + ,702.6 + ,683.3 + ,709.5 + ,702.2 + ,784.8 + ,810.9 + ,755.6 + ,656.8 + ,615.1 + ,745.3 + ,694.1 + ,675.7 + ,643.7 + ,622.1 + ,634.6 + ,588 + ,689.7 + ,673.9 + ,647.9 + ,568.8 + ,545.7 + ,632.6 + ,643.8 + ,593.1 + ,579.7 + ,546 + ,562.9 + ,572.5) > par9 = '1' > par8 = '2' > par7 = '1' > par6 = '3' > par5 = '12' > par4 = '1' > par3 = '0' > par2 = '0.5' > par1 = 'FALSE' > par9 <- '1' > par8 <- '2' > par7 <- '1' > par6 <- '3' > par5 <- '12' > par4 <- '1' > par3 <- '0' > par2 <- '0.5' > 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,] 1.598876 -0.4558252 -0.1609639 -0.5473846 -0.1093883 -0.07402063 [2,] 1.586684 -0.4356998 -0.1690911 -0.5388330 -0.0396933 0.00000000 [3,] 1.576773 -0.4212529 -0.1741037 -0.5303051 0.0000000 0.00000000 [4,] NA NA NA NA NA NA [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 [13,] NA NA NA NA NA NA [14,] NA NA NA NA NA NA [,7] [1,] -0.6022168 [2,] -0.6720214 [3,] -0.6940853 [4,] NA [5,] NA [6,] NA [7,] NA [8,] NA [9,] NA [10,] NA [11,] NA [12,] NA [13,] NA [14,] NA [[2]] [,1] [,2] [,3] [,4] [,5] [,6] [,7] [1,] 0 0.01622 0.01749 0.00003 0.36445 0.41967 0 [2,] 0 0.02640 0.01312 0.00011 0.62329 NA 0 [3,] 0 0.02776 0.00910 0.00011 NA NA 0 [4,] NA NA NA NA NA NA NA [5,] NA NA NA NA NA NA NA [6,] NA NA NA NA NA NA NA [7,] NA NA NA NA NA NA NA [8,] NA NA NA NA NA NA NA [9,] NA NA NA NA NA NA NA [10,] NA NA NA NA NA NA NA [11,] NA NA NA NA NA NA NA [12,] NA NA NA NA NA NA NA [13,] NA NA NA NA NA NA NA [14,] NA 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 ma1 sar1 sar2 sma1 1.5989 -0.4558 -0.1610 -0.5474 -0.1094 -0.0740 -0.6022 s.e. 0.1336 0.1887 0.0674 0.1298 0.1205 0.0916 0.1136 sigma^2 estimated as 0.2725: log likelihood = -282.24, aic = 580.48 [[3]][[2]] Call: arima(x = series, order = order, seasonal = seasonal, include.mean = include.mean, method = "ML") Coefficients: ar1 ar2 ar3 ma1 sar1 sar2 sma1 1.5989 -0.4558 -0.1610 -0.5474 -0.1094 -0.0740 -0.6022 s.e. 0.1336 0.1887 0.0674 0.1298 0.1205 0.0916 0.1136 sigma^2 estimated as 0.2725: log likelihood = -282.24, aic = 580.48 [[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 ma1 sar1 sar2 sma1 1.5867 -0.4357 -0.1691 -0.5388 -0.0397 0 -0.6720 s.e. 0.1404 0.1954 0.0678 0.1382 0.0807 0 0.0641 sigma^2 estimated as 0.273: log likelihood = -282.55, aic = 579.1 [[3]][[4]] NULL [[3]][[5]] NULL [[3]][[6]] NULL [[3]][[7]] NULL $aic [1] 580.4807 579.1041 577.3434 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/fisher/rcomp/tmp/1xukv1353948266.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 = 372 Frequency = 1 [1] 0.015332797 0.016753580 0.016265665 0.015513346 0.014190141 [6] 0.015516119 0.015525599 0.014958013 0.014354165 0.013215368 [11] 0.014256295 0.014847227 0.413915292 -0.007778796 0.270434584 [16] 0.466878347 1.679484259 -0.130819812 0.707670311 -0.344946938 [21] -0.126632135 1.523998657 -1.031762737 -0.079881201 0.412186932 [26] -0.676868868 -0.373756486 -0.548232268 -0.197905046 0.131589878 [31] -0.587772376 -0.702639795 0.811945262 -0.566603251 0.999502239 [36] 0.001555581 -1.489509865 -1.143452752 0.326195083 -0.011078487 [41] 0.128611273 0.340099793 -0.305162899 0.256882683 0.811388795 [46] 0.061196499 0.081227285 -1.270838636 -0.311378066 -0.190656464 [51] -0.434777607 0.511337981 0.417183320 -0.352147000 0.038031186 [56] 0.511601924 -0.558682716 -0.494374550 -0.230390901 -0.212135449 [61] 0.466618118 -1.028685413 0.239618818 0.753293559 -0.514071280 [66] -0.491013762 -0.181004740 0.204533617 0.765299848 0.419988009 [71] 0.789225252 0.931656324 1.243443124 0.487272332 0.336074617 [76] -0.182621543 -0.195085145 -1.024662152 0.046948085 0.635763238 [81] 0.268255936 -0.684760012 -0.185819375 -0.263013741 -0.200642138 [86] -0.275709317 0.093875360 0.598968396 -0.564515456 0.069636769 [91] -0.445802926 0.617761847 -0.304105888 0.719518425 0.085655868 [96] 0.014189048 -0.853854404 -0.096972824 0.705578774 -0.489825758 [101] 1.062268798 0.492267343 -0.518526460 -1.011764632 -0.306816153 [106] 0.239978832 1.011495644 0.077136278 -0.486146404 -0.533945222 [111] -0.314585465 0.259199761 0.664317859 0.698684691 -0.624975503 [116] -0.182215023 0.334523494 0.513085652 0.862920428 0.265005809 [121] 0.819658968 1.289570908 0.273692851 0.149568590 -0.396163148 [126] -0.189584005 0.307622062 0.015989033 -0.842345536 -0.029221530 [131] -0.840691874 0.849846352 -0.193656237 -0.096506397 -0.283793112 [136] -1.001175415 0.123558615 0.679255559 0.260484543 0.439492765 [141] 0.235892966 0.643871696 0.038064312 -0.827838969 -0.437134069 [146] -0.778063390 1.396298695 -0.284828484 -0.201952963 1.081865261 [151] -0.258941271 0.355767181 -0.509172483 0.930160308 0.143104819 [156] 0.885942368 0.042626455 0.436100239 -0.412472438 -0.148933420 [161] 0.094862798 0.228526274 -0.138373949 -0.304606871 -0.092372073 [166] -0.117074827 -0.596703816 0.029949690 -0.130192298 -0.294382138 [171] 0.100932729 0.234651076 0.882377471 -0.681792311 -0.422777932 [176] 1.030749185 -0.141142937 -0.551114414 0.534674373 -0.307175106 [181] 0.363739931 0.498839015 -0.783693321 -0.025823095 0.267092967 [186] 0.319420731 -0.298725600 -0.370430889 0.171030628 0.167314856 [191] 0.318160208 -0.528639967 -0.051756819 -0.259407125 -0.014510380 [196] 0.231179570 -0.523118301 1.099410948 -1.084290995 0.276315097 [201] 0.159458179 0.080867991 -0.725314082 0.060978476 -0.347167810 [206] 0.494261490 -0.613317404 0.499784088 -0.341852436 0.580039886 [211] -0.519319852 -0.240944280 -0.111271618 -0.151138550 -0.298326360 [216] -0.472291851 -0.342302577 -0.540947347 0.467661794 0.224191603 [221] 0.604868867 0.298874784 -0.445712535 -0.284176216 -0.259037701 [226] 0.071557229 -0.445023615 0.129807986 -0.163717070 -0.093531830 [231] -0.091395255 -0.075568474 -0.404839536 1.373131855 0.255502698 [236] -0.560660008 0.510608630 0.264917005 -0.986808473 -0.797823650 [241] -0.423864968 0.685531916 -0.285967631 -0.510295438 -0.175859083 [246] 1.549949196 0.163346155 -0.868764326 -0.001727529 -0.208825787 [251] -0.231077028 -0.429137854 0.041128227 -0.023204957 0.211630160 [256] 0.331363668 -0.418406696 0.298497801 0.573253192 -0.169575630 [261] 0.662915918 -0.340530860 -0.917843657 -0.081531267 0.955051057 [266] 0.815079530 0.350118550 0.189146894 -0.103078377 0.073123365 [271] 0.577228034 0.144416674 0.427326036 0.086002917 0.663886009 [276] 0.291034201 0.045630580 -0.380367527 0.040665279 -0.112810732 [281] 0.048248416 -0.336579725 0.741482872 0.540193865 -0.184273023 [286] -0.313563872 0.485268798 0.117709172 0.144420582 -0.255175679 [291] 0.283967693 -0.091015288 -0.069568447 -0.227998839 0.343074203 [296] 0.294751653 -0.051749438 -0.007169989 -0.731557284 -0.002317394 [301] -0.068059028 0.390997686 -0.085706745 0.236368923 -0.177461441 [306] -0.165634009 0.032171175 0.023741468 0.290704488 -0.607275331 [311] 0.619942324 0.331912455 0.594087423 -0.056729177 -0.430698591 [316] -0.195803720 0.412169920 0.212272496 0.351414210 -0.105325528 [321] 0.923547702 0.169557765 0.948686297 0.926799186 1.905693465 [326] -0.356986735 0.356613798 -0.106500025 0.244772717 -0.953784230 [331] 0.106443574 0.291262031 0.035120692 0.358792403 -0.280980338 [336] 0.145336959 -0.214902676 -0.119718575 -0.024265732 0.194704728 [341] -0.201690525 0.485846946 0.738463805 0.552815424 -0.414581259 [346] 0.223869827 0.218917844 -0.096939037 -0.603012249 0.574187646 [351] -0.139488248 -0.668183180 0.139311769 0.386889047 -0.305549396 [356] 0.534953144 -0.236399268 0.120758977 -0.069617796 -0.869668056 [361] 0.135438643 -0.250001262 0.360334974 -0.177705722 0.337779059 [366] -0.595237491 0.808724728 -0.347678210 -0.019048495 -0.246825889 [371] -0.039796539 0.491429332 > postscript(file="/var/fisher/rcomp/tmp/2nto81353948266.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/fisher/rcomp/tmp/3gzeu1353948266.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/fisher/rcomp/tmp/4o93y1353948266.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/fisher/rcomp/tmp/5vrzz1353948266.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/fisher/rcomp/tmp/677041353948266.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/fisher/rcomp/tmp/7mnff1353948266.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/fisher/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab > load(file="/var/fisher/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/fisher/rcomp/tmp/8shlx1353948266.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/fisher/rcomp/tmp/9xcbe1353948266.tab") > > try(system("convert tmp/1xukv1353948266.ps tmp/1xukv1353948266.png",intern=TRUE)) character(0) > try(system("convert tmp/2nto81353948266.ps tmp/2nto81353948266.png",intern=TRUE)) character(0) > try(system("convert tmp/3gzeu1353948266.ps tmp/3gzeu1353948266.png",intern=TRUE)) character(0) > try(system("convert tmp/4o93y1353948266.ps tmp/4o93y1353948266.png",intern=TRUE)) character(0) > try(system("convert tmp/5vrzz1353948266.ps tmp/5vrzz1353948266.png",intern=TRUE)) character(0) > try(system("convert tmp/677041353948266.ps tmp/677041353948266.png",intern=TRUE)) character(0) > try(system("convert tmp/7mnff1353948266.ps tmp/7mnff1353948266.png",intern=TRUE)) character(0) > > > proc.time() user system elapsed 27.773 2.437 30.224