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
+ ,311.3)
> 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,] 1.083816 0.1740698 -0.3112640 -0.6378712 -0.5757057 0.2242005
 [2,] 1.209189 0.0000000 -0.2570042 -0.7609484 -0.4633946 0.2341328
 [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,] 0.01311 0.76387 0.09606 0.14029 0.11963 0.07740
 [2,] 0.00000      NA 0.00022 0.00000 0.00000 0.03558
 [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
      1.0838  0.1741  -0.3113  -0.6379  -0.5757  0.2242
s.e.  0.4347  0.5790   0.1865   0.4316   0.3690  0.1266

sigma^2 estimated as 107.3:  log likelihood = -1349.46,  aic = 2712.91

[[3]][[2]]

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

Coefficients:
         ar1     ar2      ar3      ma1      ma2     ma3
      1.0838  0.1741  -0.3113  -0.6379  -0.5757  0.2242
s.e.  0.4347  0.5790   0.1865   0.4316   0.3690  0.1266

sigma^2 estimated as 107.3:  log likelihood = -1349.46,  aic = 2712.91

[[3]][[3]]
NULL

[[3]][[4]]
NULL

[[3]][[5]]
NULL

[[3]][[6]]
NULL


$aic
[1] 2712.911 2711.017

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/16lmd1260442917.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]   0.25499983  22.07011272   8.36433828  30.81172540  16.19153033
  [6]   6.24749029 -12.53673947  -2.99149529  -1.99425306   0.61622656
 [11]  -6.10438313   3.29326413  -1.34475635   2.16220260   0.46646597
 [16]  -8.37988679   1.48370051  -5.40621641   0.45465248 -12.27167174
 [21]  -0.20465507  -1.65007198   2.24999557  -1.85072625  -3.36297237
 [26]  -3.11127084  -5.70999310  -1.15860462  -1.47297866   4.83726639
 [31]  18.48795840  15.99900207  -0.76289946   0.01122210   1.38423730
 [36]   0.89284726 -11.87288078  12.14031936  -9.69272373   1.11326869
 [41]   3.11182514  -0.95107538   8.29914049  -5.52815286  -8.03312291
 [46]  -1.39711503 -10.68403786  -2.99793154   0.15571983 -13.80307382
 [51]   0.94958464  -2.01776250  -1.64806132   0.18889554  -5.21658815
 [56]  -1.73878862  -2.36983813  -0.73875445  -5.40250883   8.77323738
 [61]  -8.23029061  11.79261052  -7.33865453   0.53172062  -2.98289660
 [66]  -1.99268202  -4.03311795   1.86839750  -3.54546655  -2.18041265
 [71]  -1.59791087  -0.03612646   0.14387813  -0.18122371  -1.69529401
 [76]  -5.26940155   0.22377085  -2.09755899  -1.66141903   0.60968697
 [81]  -3.94093126   0.93503237   0.35533541  -4.00754840   4.11896808
 [86]   2.09077239  -5.00724500   0.89261825  -0.47043103   2.56408550
 [91]  -0.14803924  -2.01616690   0.78761278  -0.26597385  -1.78183527
 [96]   0.97597698  -0.95609852   1.83376618  -1.05718359  -0.98371193
[101]  -1.02401673   0.64899904  -0.30739921  -5.44828029   0.74853081
[106]   0.80769216  -1.53518905  -7.84527213  23.20713832  73.44853077
[111] -14.60537929  -9.40777899  -4.81055186   3.35106634  -3.79420508
[116]  -5.64997765 -11.21733253  10.06723006   5.86769464   1.73666086
[121]  -1.37628463  -4.50337406  -0.73399027  -5.66787140  -4.11723361
[126]   3.49163420  -1.68594129  -7.40955191   8.05277141   4.16775701
[131] -13.67572012   1.88698404   9.93119133  -3.36256060  -6.39305062
[136]   9.59704242  -5.72942723   0.39352236   5.33521811  -6.40571283
[141]   2.91412976   0.17677966   3.80299051   1.18051750   3.04672238
[146]   6.91619759  -4.59046692   9.06031876   1.10964029   0.42146178
[151]   5.77114143  -6.58703025  -3.30167234  -2.53145228  -9.44157153
[156]  10.06494478  -3.65388921   7.75207620 -10.61020687   4.47910444
[161]   3.74098874   3.29686806   5.61323212  -5.43529984   1.62707826
[166]   0.23359895  -7.54150887   3.62436152   0.38534463   3.61176537
[171]  -8.99763469   7.27214111  -6.95314475   2.42793696  -7.05701198
[176]  -4.20497877  -1.05124754   2.86965397  -4.61358098  -3.51615529
[181]   4.97047043  -0.67291402  -6.88821953  -0.62514604   4.25994033
[186]  -6.24428719   3.67683013  -6.92687937  -5.83168715  -3.27332677
[191]  -9.00379804   0.34597021  -2.14488921   9.47495807  -5.73945147
[196]   0.57753926  -0.04691673  -0.47075247  -1.19287529  -6.62489307
[201]   0.02696205  -9.26678807   4.47232672   1.39986477   2.70913562
[206]  -4.24544683  -2.16018509  -1.23765432   0.92293106   4.14733818
[211]  70.61704128  80.07078067 -45.82810612   5.92464499  -0.65125709
[216]  -0.74475825   9.45305381  -9.65064897   1.23785322   7.72250526
[221]   5.79004909   5.39857729   2.26065938   8.72910250  -2.13483707
[226]  -5.39529435   4.17531286  -0.06882658 -10.39989571  12.14931531
[231]  -2.51581849   4.08278823  -6.27394098   6.46362676  -4.82536130
[236]   6.85669469  -5.81452602   6.61866901  -6.65161052   7.91667761
[241]  -2.16084181   4.71252508  18.72026795  31.59553193   7.05579926
[246]  26.54029140   7.47932366   2.03048938  -3.54461825 -14.12025996
[251]   6.16523187  -5.65792657  -0.55769416   4.24608662  13.23804766
[256]  -6.21788984  -0.03931037  -3.83771490   6.50104067  -4.04804033
[261]  -1.71971394  -6.78101520   5.54961596  -1.88059376   3.04104820
[266]   0.07797953   6.85138306  -2.68972268   5.14150137  -8.67974032
[271]   5.13086351   0.22209892  -1.61151382  10.47229244 -17.58515904
[276]   9.25035912  16.93833144   8.16622908  -9.41006422  -1.60663060
[281]  -3.23191810  -5.64888680   6.63188674  -0.03221720  -8.59283714
[286]   2.69555633  -6.47031503   1.38620642   1.71798455  -0.41987020
[291]  -1.20463701  -7.29910169  -0.01862014   6.28257562  -8.51846178
[296]  -2.50967574  -1.62241556  -0.24255285  -3.36408702  -6.97477028
[301]   4.25612542  -1.57408379  -9.50849213  13.74542191  -3.70865078
[306]  -8.15829716   4.42384942  -7.71016524   0.90919398  -6.83400441
[311]   2.84880959  -7.20084874  17.74840053 -17.33544605   5.63128760
[316]   2.47409691  -9.01301728   0.48258982   0.08497207  -3.46172200
[321]  -0.38760188 -10.63728148  -1.32523662   9.27709500  -3.29043558
[326]  -5.00613891   7.02646453  -7.14360524  -6.93127413  -7.08020349
[331]  15.26710241  -7.64346423   0.35194486  -6.58094779  -4.72676888
[336]   0.10441210  26.35821208 -24.45035105  13.45441060  14.61273262
[341]   1.81827787   3.73666910 -11.83399927  19.13810179 -10.84825848
[346]   5.41611012 -17.26529554   4.33872988   0.28031218  -2.71121442
[351]  14.69216408  -6.00035779   7.89816144 -22.87832387  10.32758119
[356]   1.37809321  -0.77357954  -3.87828265   4.27286908  -6.10806366
> postscript(file="/var/www/html/rcomp/tmp/2qv0i1260442917.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/3wshf1260442917.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/4kwn01260442917.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/56ybo1260442917.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/68y0e1260442917.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/7n0e71260442917.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/8j15p1260442917.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/9cdjz1260442917.tab") 
> 
> system("convert tmp/16lmd1260442917.ps tmp/16lmd1260442917.png")
> system("convert tmp/2qv0i1260442917.ps tmp/2qv0i1260442917.png")
> system("convert tmp/3wshf1260442917.ps tmp/3wshf1260442917.png")
> system("convert tmp/4kwn01260442917.ps tmp/4kwn01260442917.png")
> system("convert tmp/56ybo1260442917.ps tmp/56ybo1260442917.png")
> system("convert tmp/68y0e1260442917.ps tmp/68y0e1260442917.png")
> system("convert tmp/7n0e71260442917.ps tmp/7n0e71260442917.png")
> 
> 
> proc.time()
   user  system elapsed 
  2.721   1.126   3.224