R version 2.9.0 (2009-04-17)
Copyright (C) 2009 The R Foundation for Statistical Computing
ISBN 3-900051-07-0

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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(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,] 0.4702851 -0.10223229 0.07045854
[2,] 0.4652308 -0.07134828 0.00000000
[3,] 0.4351177  0.00000000 0.00000000
[4,]        NA          NA         NA
[5,]        NA          NA         NA
[6,]        NA          NA         NA

[[2]]
     [,1]    [,2]   [,3]
[1,]    0 0.08018 0.1897
[2,]    0 0.18268     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
      0.4703  -0.1022  0.0705
s.e.  0.0527   0.0583  0.0536

sigma^2 estimated as 111.1:  log likelihood = -1351.29,  aic = 2710.59

[[3]][[2]]

Call:
arima(x = series, order = order, seasonal = seasonal, include.mean = include.mean, 
    method = "ML")

Coefficients:
         ar1      ar2     ar3
      0.4703  -0.1022  0.0705
s.e.  0.0527   0.0583  0.0536

sigma^2 estimated as 111.1:  log likelihood = -1351.29,  aic = 2710.59

[[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
      0.4652  -0.0713    0
s.e.  0.0527   0.0534    0

sigma^2 estimated as 111.7:  log likelihood = -1352.15,  aic = 2710.31


$aic
[1] 2710.585 2710.307 2710.085

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/13lh81260543364.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]   0.280199826  17.700271050  30.666979654  18.121991580   5.820910296
  [6] -10.781764094  -4.122485769  -3.317566779  -3.711112067  -9.179333016
 [11]  -0.345682324  -3.961916966  -1.372853543  -1.324719586 -11.047253797
 [16]  -0.002736190  -6.943933201  -1.784296034 -13.001349036  -1.853342126
 [21]  -1.555150888   0.547689842  -1.395224749  -3.666367287  -2.206530076
 [26]  -5.399351427  -0.535912511  -0.771130262   5.334219486  19.677853599
 [31]  16.700259797  -0.005476473   1.773371941   2.790930650   0.349114242
 [36] -12.523663937  11.278942838 -10.454336942  -1.643834156   3.966285141
 [41]  -3.608607463   8.112727360  -6.474193428  -9.065481425  -1.003641111
 [46] -11.839969528  -3.800770125   0.274655315 -14.763951613   1.522150815
 [51]  -0.854263946  -1.922384770   2.145498972  -4.097259395   0.060267761
 [56]  -0.398214919   0.704550447  -3.450305767  10.517277806  -6.215391520
 [61]  12.879549958  -4.332057792   0.601616581   0.438913879  -2.011210904
 [66]  -2.026910456   2.520742348  -2.211710036  -1.555924140   0.070143194
 [71]   0.754606648   1.403171155   0.844781818  -0.423077164  -4.078888901
 [76]   1.521715851  -0.906435653  -0.956354690   2.047721386  -2.990598938
 [81]   2.130530140   1.777802996  -3.245205586   5.594743595   3.296018348
 [86]  -4.444836835   2.415923276   0.677802996   2.966548271   0.864445043
 [91]  -1.566834876   1.796897427   0.245256188  -1.425954932   1.575967313
 [96]  -0.543713891   2.071348284  -0.530461558  -0.843395744  -0.399276063
[101]   0.815105996   0.010305983  -5.303895092   1.240604536   1.287265858
[106]  -1.697371798  -7.209763031  23.850316964  73.899298571 -17.184492193
[111] -10.304586863   0.719074291  -1.870768293  -6.089519815 -10.332129822
[116] -13.840226957   6.455321434   2.992465958  -2.396122887  -2.564007710
[121]  -6.500593555  -2.145856526  -7.358359081  -5.826381068   2.588587765
[126]  -3.094413171  -8.397060432   8.198693704   3.893521607 -14.699218678
[131]   2.939398366  10.686036007  -4.620010548  -5.918951565  10.745404549
[136]  -5.846040844  -0.113202811   6.769419257  -7.291453256   3.342851711
[141]   0.774494678   3.066367287   1.685668544   2.628727080   7.221049299
[146]  -5.115772548   8.832664912   1.171493310  -1.290860781   5.956379452
[151]  -8.069799205  -4.373933746  -2.989096047 -11.229457799   9.252525813
[156]  -4.544986483   5.973045724  -9.775804307   3.185179528   5.051161166
[161]   1.391467901   6.263745867  -6.004018691   1.605504890   0.400405789
[166]  -8.746885046   3.590135764  -0.020368102   2.385368375  -8.881060712
[171]   6.767782537  -6.445074124   1.007583358  -5.816267265  -5.354845017
[176]   0.133144778   2.310817392  -4.179637599  -3.164850832   6.297658402
[181]  -0.342964113  -6.323663937   0.894512008   5.277253261  -5.868669479
[186]   4.670779490  -5.405842097  -5.592959595  -1.242504387  -8.548708453
[191]   1.677763590  -0.664494565  10.365636568  -3.737925731   1.748252061
[196]   3.073502115   0.285668544   0.880050171  -5.362284429   1.640130165
[201]  -7.816810218   5.378856277   3.306067982   2.941842250  -2.090816960
[206]  -0.996735502   0.744188262   1.753589324   5.423196348  71.504607832
[211]  79.782847309 -49.888608227   8.350077263   3.415218398 -11.545817120
[216]   6.480622299 -17.857852087  -4.856057970   2.291795958  -1.482434509
[221]  -0.180343557  -2.949107460   3.831659866  -6.844868378 -10.369994834
[226]   0.602107643  -4.761985548 -14.979445419   8.999179272  -5.853394983
[231]  -0.346324115  -7.515362344   3.097314413  -6.113052290   3.655529548
[236]  -6.579050826   3.823163724  -7.018439076   5.316390864  -2.251778402
[241]   2.096897427  18.805686955  29.195633986   5.126610608  24.623042701
[246]   6.693126256  -2.928605320  -5.680480514 -19.788271985   1.196681451
[251] -11.664782457  -7.628722666   0.113992962   7.448863388 -10.562395751
[256]  -4.229202531  -5.959607992   2.202202066  -6.658558044  -5.389976207
[261]  -8.270094959   2.743874529  -3.457790287   0.424999408  -0.445099966
[266]   5.047178433  -3.283051538   3.707702542  -8.820517543   3.549617788
[271]   0.318545776  -3.879319452  10.585386354 -18.890272927   8.380846023
[276]  17.800219103   4.792394249  -9.396639791  -1.875513081  -3.334301633
[281]  -7.883883463   5.774161885  -1.611329009 -10.299931418   2.670653523
[286]  -7.125649268   0.185741540   2.114238113  -1.479456615  -0.788720514
[291]  -7.191666864   0.396659058   6.792833628  -8.866041277  -1.934183528
[296]  -0.148277903  -0.386891613  -2.384600617  -6.315225181   5.596590476
[301]  -0.605142922  -9.001129726  15.818856061  -2.563930185  -8.093532804
[306]   7.545903681  -7.135242511   1.711366047  -4.870287140   3.222552190
[311]  -5.214837371  18.218363712 -15.304147992   5.537938215   6.546180169
[316] -10.525017387   3.238250661   1.072565651  -2.947608983   0.962783561
[321]  -9.471054897  -0.241100334  11.069387714  -3.094417585  -3.705948798
[326]   9.396122887  -6.192607743  -6.041199172  -4.688958883  16.018987523
[331]  -6.532875072   0.513258035  -3.213907688  -4.646754665   2.441846664
[336]  26.950686795 -23.615069924  13.918823645  19.112211329  -1.354527835
[341]   6.207591427 -11.612508050  19.235622459 -10.970471458   2.684262330
[346] -15.649718994   1.364553997   1.299574944  -6.074250814  15.376934033
[351]  -7.222250941   7.024830908 -21.816028896   8.892593098   3.023340087
[356]  -4.282508585  -2.130306415   3.464206673  -5.680180552
> postscript(file="/var/www/html/rcomp/tmp/2juyg1260543364.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/3t0nf1260543364.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/445te1260543364.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/5oib01260543364.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/6zg8y1260543364.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/7ct4z1260543364.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/8vasu1260543364.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/9z9zm1260543364.tab") 
> 
> system("convert tmp/13lh81260543364.ps tmp/13lh81260543364.png")
> system("convert tmp/2juyg1260543364.ps tmp/2juyg1260543364.png")
> system("convert tmp/3t0nf1260543364.ps tmp/3t0nf1260543364.png")
> system("convert tmp/445te1260543364.ps tmp/445te1260543364.png")
> system("convert tmp/5oib01260543364.ps tmp/5oib01260543364.png")
> system("convert tmp/6zg8y1260543364.ps tmp/6zg8y1260543364.png")
> system("convert tmp/7ct4z1260543364.ps tmp/7ct4z1260543364.png")
> 
> 
> proc.time()
   user  system elapsed 
  1.853   1.110  10.213