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(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'
> 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
> par6 <- 3
> par7 <- as.numeric(par7) #degree (q) of the non-seasonal MA(q) polynomial
> par7 <- 3
> 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,] 1.061416 0.2046062 -0.3205838 -0.6149018 -0.5965988 0.2226042
 [2,] 1.209620 0.0000000 -0.2576723 -0.7809027 -0.4701713 0.2408770
 [3,]       NA        NA         NA         NA         NA        NA
 [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

[[2]]
         [,1]    [,2]    [,3]    [,4]    [,5]    [,6]
 [1,] 0.01603 0.72427 0.08311 0.15926 0.10469 0.08796
 [2,] 0.00000      NA 0.00020 0.00000 0.00000 0.03664
 [3,]      NA      NA      NA      NA      NA      NA
 [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

[[3]]
[[3]][[1]]

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

Coefficients:
         ar1     ar2      ar3      ma1      ma2     ma3
      1.0614  0.2046  -0.3206  -0.6149  -0.5966  0.2226
s.e.  0.4386  0.5795   0.1845   0.4359   0.3667  0.1301

sigma^2 estimated as 107.5:  log likelihood = -1346.02,  aic = 2706.04

[[3]][[2]]

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

Coefficients:
         ar1     ar2      ar3      ma1      ma2     ma3
      1.0614  0.2046  -0.3206  -0.6149  -0.5966  0.2226
s.e.  0.4386  0.5795   0.1845   0.4359   0.3667  0.1301

sigma^2 estimated as 107.5:  log likelihood = -1346.02,  aic = 2706.04

[[3]][[3]]
NULL

[[3]][[4]]
NULL

[[3]][[5]]
NULL

[[3]][[6]]
NULL


$aic
[1] 2706.041 2704.180

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 log(s2) : NaNs produced
> postscript(file="/var/www/html/rcomp/tmp/18hfg1260475469.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]   0.254999834  22.066656137   8.363116851  30.803137264  16.198487857
  [6]   6.280569042 -12.547787239  -2.900276612  -1.987498035   0.684278380
 [11]  -6.149768138   3.324529865  -1.390543380   2.181102917   0.412765161
 [16]  -8.360623301   1.443049415  -5.393411013   0.436802945 -12.295459207
 [21]  -0.197796463  -1.688004434   2.270175010  -1.912709869  -3.341006742
 [26]  -3.155642042  -5.686248846  -1.185488022  -1.464974447   4.821357374
 [31]  18.477705545  15.987458589  -0.781124768   0.008934188   1.411374738
 [36]   0.926466858 -11.869313088  12.163339758  -9.701556163   1.138446655
 [41]   3.056508409  -0.890289693   8.224854125  -5.487550640  -8.070060066
 [46]  -1.384008915 -10.676742913  -3.005529164   0.143781118 -13.803512934
 [51]   0.919456239  -2.020360309  -1.652220603   0.149678936  -5.202053648
 [56]  -1.765311957  -2.359055629  -0.744276803  -5.407511984   8.777598199
 [61]  -8.241861686  11.808082452  -7.371468445   0.584241530  -3.040954880
 [66]  -1.909671061  -4.097104983   1.932562115  -3.592079109  -2.140831737
 [71]  -1.633334691  -0.001299000   0.116657944  -0.161455060  -1.711529232
 [76]  -5.255000898   0.220747252  -2.086944580  -1.659471281   0.604223647
 [81]  -3.931801461   0.930284314   0.359964610  -4.001936520   4.114005045
 [86]   2.100706971  -5.005637741   0.889462488  -0.454455805   2.571309985
 [91]  -0.152582223  -2.003148921   0.782195770  -0.248066258  -1.783770642
 [96]   0.983273251  -0.952421252   1.839560954  -1.059453214  -0.973620150
[101]  -1.028589678   0.664247851  -0.312670948  -5.438649705   0.746554931
[106]   0.816738261  -1.531743974  -7.853748437  23.221140880  73.437962322
[111] -14.628358390  -9.442230361  -4.809072961   3.537690589  -3.879377085
[116]  -5.544313488 -11.298669035  10.138083781   5.799881289   1.763067499
[121]  -1.456830633  -4.462567521  -0.773396061  -5.642465645  -4.139943294
[126]   3.491994882  -1.697517598  -7.425380406   8.038867388   4.165900176
[131] -13.687381515   1.867605125   9.947389448  -3.362806064  -6.422419891
[136]   9.607124828  -5.726155552   0.393791875   5.314935584  -6.374318380
[141]   2.880756323   0.196594874   3.801022630   1.165108708   3.059271554
[146]   6.897179874  -4.575766184   9.048566300   1.114598502   0.434026405
[151]   5.745698976  -6.555855402  -3.322519624  -2.517256727  -9.435573959
[156]  10.053284753  -3.660448483   7.744533877 -10.654290572   4.517695249
[161]   3.685349120   3.354443752   5.536485654  -5.387074475   1.586140530
[166]   0.262073642  -7.547176998   3.620070735   0.387908179   3.608918446
[171]  -9.023826256   7.288325802  -6.980852489   2.459432442  -7.111028351
[176]  -4.150549584  -1.111345594   2.921110091  -4.670918977  -3.489701994
[181]   4.936353908  -0.648110373  -6.916869673  -0.617074931   4.261868617
[186]  -6.241398984   3.666663486  -6.927896161  -5.815651184  -3.292812451
[191]  -8.968890364   0.321607613  -2.129983260   9.465494570  -5.757311490
[196]   0.589735127  -0.069767983  -0.423168104  -1.225679042  -6.584123730
[201]   0.012669346  -9.240101026   4.475851753   1.396902825   2.727649359
[206]  -4.277228689  -2.122866705  -1.254292563   0.962623421   4.129518587
[211]  70.640267321  80.022806856 -45.855454991   5.876727236  -0.541398520
[216]  -0.558462105   9.327648697  -9.503763201   1.120362063   7.784377414
[221]   5.736672133   5.377018597   2.222758159   8.711908692  -2.163804144
[226]  -5.406285967   4.145212128  -0.064905279 -10.438094663  12.128771407
[231]  -2.542751724   4.065121403  -6.340531230   6.490567281  -4.899025779
[236]   6.889226046  -5.898531862   6.659666393  -6.738306195   7.964970918
[241]  -2.251919995   4.763253578  18.625340901  31.636690073   6.958405069
[246]  26.551961749   7.421678019   2.091954164  -3.613456156 -14.032699594
[251]   6.110786852  -5.626858787  -0.610353453   4.194852194  13.216576654
[256]  -6.299696367  -0.062318116  -3.903342401   6.514893563  -4.131257571
[261]  -1.715370200  -6.863359418   5.565445559  -1.960868426   3.042238807
[266]  -0.007254099   6.860688660  -2.767340091   5.147861398  -8.747347697
[271]   5.149209280   0.151418877  -1.588727239  10.386167664 -17.568971190
[276]   9.194771515  16.918037227   8.159875826  -9.505783621  -1.588055774
[281]  -3.270592700  -5.624752738   6.571361487  -0.032338306  -8.647615950
[286]   2.667420994  -6.492284350   1.362878111   1.670111632  -0.426574665
[291]  -1.265596605  -7.302634276  -0.056233112   6.271442006  -8.548245961
[296]  -2.540612852  -1.646132880  -0.244019926  -3.410395383  -6.978767958
[301]   4.221020339  -1.581209285  -9.536737637  13.719952753  -3.719376639
[306]  -8.176592751   4.382344184  -7.679305970   0.869322283  -6.840793658
[311]   2.847567189  -7.238989718  17.764988213 -17.396969013   5.668681268
[316]   2.392730730  -8.923276639   0.368911069   0.164546680  -3.525576024
[321]  -0.368844218 -10.666993345  -1.313304054   9.252260376  -3.281812359
[326]  -5.048974518   7.028764558  -7.144887739  -6.937669217  -7.092629092
[331]  15.293679380  -7.680458358   0.364690870  -6.634186431  -4.661314017
[336]   0.042906213  26.412832648 -24.518972423  13.491282784  14.546371437
[341]   1.926358167   3.598622068 -11.725766533  19.084634858 -10.803694143
[346]   5.410894738 -17.305729646   4.415657088   0.193262525  -2.626326605
[351]  14.575559153  -5.936897376   7.827155074 -22.867992056  10.348084967
[356]   1.337484290  -0.712724127  -3.990115771   4.355545062
> postscript(file="/var/www/html/rcomp/tmp/24xbh1260475469.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/3xrjk1260475469.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/4czld1260475469.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/5odxo1260475469.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/634hk1260475469.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/76d121260475469.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/812291260475469.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/9v7ub1260475469.tab") 
> system("convert tmp/18hfg1260475469.ps tmp/18hfg1260475469.png")
> system("convert tmp/24xbh1260475469.ps tmp/24xbh1260475469.png")
> system("convert tmp/3xrjk1260475469.ps tmp/3xrjk1260475469.png")
> system("convert tmp/4czld1260475469.ps tmp/4czld1260475469.png")
> system("convert tmp/5odxo1260475469.ps tmp/5odxo1260475469.png")
> system("convert tmp/634hk1260475469.ps tmp/634hk1260475469.png")
> system("convert tmp/76d121260475469.ps tmp/76d121260475469.png")
> 
> 
> proc.time()
   user  system elapsed 
  2.828   1.116   3.132