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 'q()' to quit R.

> x <- c(87.28
+ ,87.28
+ ,87.09
+ ,86.92
+ ,87.59
+ ,90.72
+ ,90.69
+ ,90.3
+ ,89.55
+ ,88.94
+ ,88.41
+ ,87.82
+ ,87.07
+ ,86.82
+ ,86.4
+ ,86.02
+ ,85.66
+ ,85.32
+ ,85
+ ,84.67
+ ,83.94
+ ,82.83
+ ,81.95
+ ,81.19
+ ,80.48
+ ,78.86
+ ,69.47
+ ,68.77
+ ,70.06
+ ,73.95
+ ,75.8
+ ,77.79
+ ,81.57
+ ,83.07
+ ,84.34
+ ,85.1
+ ,85.25
+ ,84.26
+ ,83.63
+ ,86.44
+ ,85.3
+ ,84.1
+ ,83.36
+ ,82.48
+ ,81.58
+ ,80.47
+ ,79.34
+ ,82.13
+ ,81.69
+ ,80.7
+ ,79.88
+ ,79.16
+ ,78.38
+ ,77.42
+ ,76.47
+ ,75.46
+ ,74.48
+ ,78.27
+ ,80.7
+ ,79.91
+ ,78.75
+ ,77.78
+ ,81.14
+ ,81.08
+ ,80.03
+ ,78.91
+ ,78.01
+ ,76.9
+ ,75.97
+ ,81.93
+ ,80.27
+ ,78.67
+ ,77.42
+ ,76.16
+ ,74.7
+ ,76.39
+ ,76.04
+ ,74.65
+ ,73.29
+ ,71.79
+ ,74.39
+ ,74.91
+ ,74.54
+ ,73.08
+ ,72.75
+ ,71.32
+ ,70.38
+ ,70.35
+ ,70.01
+ ,69.36
+ ,67.77
+ ,69.26
+ ,69.8
+ ,68.38
+ ,67.62
+ ,68.39
+ ,66.95
+ ,65.21
+ ,66.64
+ ,63.45
+ ,60.66
+ ,62.34
+ ,60.32
+ ,58.64
+ ,60.46
+ ,58.59
+ ,61.87
+ ,61.85
+ ,67.44
+ ,77.06
+ ,91.74
+ ,93.15
+ ,94.15
+ ,93.11
+ ,91.51
+ ,89.96
+ ,88.16
+ ,86.98
+ ,88.03
+ ,86.24
+ ,84.65
+ ,83.23
+ ,81.7
+ ,80.25
+ ,78.8
+ ,77.51
+ ,76.2
+ ,75.04
+ ,74
+ ,75.49
+ ,77.14
+ ,76.15
+ ,76.27
+ ,78.19
+ ,76.49
+ ,77.31
+ ,76.65
+ ,74.99
+ ,73.51
+ ,72.07
+ ,70.59
+ ,71.96
+ ,76.29
+ ,74.86
+ ,74.93
+ ,71.9
+ ,71.01
+ ,77.47
+ ,75.78
+ ,76.6
+ ,76.07
+ ,74.57
+ ,73.02
+ ,72.65
+ ,73.16
+ ,71.53
+ ,69.78
+ ,67.98
+ ,69.96
+ ,72.16
+ ,70.47
+ ,68.86
+ ,67.37
+ ,65.87
+ ,72.16
+ ,71.34
+ ,69.93
+ ,68.44
+ ,67.16
+ ,66.01
+ ,67.25
+ ,70.91
+ ,69.75
+ ,68.59
+ ,67.48
+ ,66.31
+ ,64.81
+ ,66.58
+ ,65.97
+ ,64.7
+ ,64.7
+ ,60.94
+ ,59.08
+ ,58.42
+ ,57.77
+ ,57.11
+ ,53.31
+ ,49.96
+ ,49.4
+ ,48.84
+ ,48.3
+ ,47.74
+ ,47.24
+ ,46.76
+ ,46.29
+ ,48.9
+ ,49.23
+ ,48.53
+ ,48.03
+ ,54.34
+ ,53.79
+ ,53.24
+ ,52.96
+ ,52.17
+ ,51.7
+ ,58.55
+ ,78.2
+ ,77.03
+ ,76.19
+ ,77.15
+ ,75.87
+ ,95.47
+ ,109.67
+ ,112.28
+ ,112.01
+ ,107.93
+ ,105.96
+ ,105.06
+ ,102.98
+ ,102.2
+ ,105.23
+ ,101.85
+ ,99.89
+ ,96.23
+ ,94.76
+ ,91.51
+ ,91.63
+ ,91.54
+ ,85.23
+ ,87.83
+ ,87.38
+ ,84.44
+ ,85.19
+ ,84.03
+ ,86.73
+ ,102.52
+ ,104.45
+ ,106.98
+ ,107.02
+ ,99.26
+ ,94.45
+ ,113.44
+ ,157.33
+ ,147.38
+ ,171.89
+ ,171.95
+ ,132.71
+ ,126.02
+ ,121.18
+ ,115.45
+ ,110.48
+ ,117.85
+ ,117.63
+ ,124.65
+ ,109.59
+ ,111.27
+ ,99.78
+ ,98.21
+ ,99.2
+ ,97.97
+ ,89.55
+ ,87.91
+ ,93.34
+ ,94.42
+ ,93.2
+ ,90.29
+ ,91.46
+ ,89.98
+ ,88.35
+ ,88.41
+ ,82.44
+ ,79.89
+ ,75.69
+ ,75.66
+ ,84.5
+ ,96.73
+ ,87.48
+ ,82.39
+ ,83.48
+ ,79.31
+ ,78.16
+ ,72.77
+ ,72.45
+ ,68.46
+ ,67.62
+ ,68.76
+ ,70.07
+ ,68.55
+ ,65.3
+ ,58.96
+ ,59.17
+ ,62.37
+ ,66.28
+ ,55.62
+ ,55.23
+ ,55.85
+ ,56.75
+ ,50.89
+ ,53.88
+ ,52.95
+ ,55.08
+ ,53.61
+ ,58.78
+ ,61.85
+ ,55.91
+ ,53.32
+ ,46.41
+ ,44.57
+ ,50
+ ,50
+ ,53.36
+ ,46.23
+ ,50.45
+ ,49.07
+ ,45.85
+ ,48.45
+ ,49.96
+ ,46.53
+ ,50.51
+ ,47.58
+ ,48.05
+ ,46.84
+ ,47.67
+ ,49.16
+ ,55.54
+ ,55.82
+ ,58.22
+ ,56.19
+ ,57.77
+ ,63.19
+ ,54.76
+ ,55.74
+ ,62.54
+ ,61.39
+ ,69.6
+ ,79.23
+ ,80
+ ,93.68
+ ,107.63
+ ,100.18
+ ,97.3
+ ,90.45
+ ,80.64
+ ,80.58
+ ,75.82
+ ,85.59
+ ,89.35
+ ,89.42
+ ,104.73
+ ,95.32
+ ,89.27
+ ,90.44
+ ,86.97
+ ,79.98
+ ,81.22
+ ,87.35
+ ,83.64
+ ,82.22
+ ,94.4)
> 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,] -0.2829357 -0.4571699 -0.3489512 0.4281146 0.5829760 0.6241419
 [2,]  0.0000000 -0.5011534 -0.5530316 0.1593749 0.5506812 0.7546503
 [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,] 0.0544 0.00021 0.01373 0.00064    0    0
 [2,]     NA 0.00000 0.00000 0.00009    0    0
 [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
      -0.2829  -0.4572  -0.3490  0.4281  0.5830  0.6241
s.e.   0.1466   0.1222   0.1409  0.1243  0.0955  0.1202

sigma^2 estimated as 26.72:  log likelihood = -1096.33,  aic = 2206.66

[[3]][[2]]

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

Coefficients:
          ar1      ar2      ar3     ma1     ma2     ma3
      -0.2829  -0.4572  -0.3490  0.4281  0.5830  0.6241
s.e.   0.1466   0.1222   0.1409  0.1243  0.0955  0.1202

sigma^2 estimated as 26.72:  log likelihood = -1096.33,  aic = 2206.66

[[3]][[3]]
NULL

[[3]][[4]]
NULL

[[3]][[5]]
NULL

[[3]][[6]]
NULL


$aic
[1] 2206.656 2206.436

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/10u271260460704.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]  8.727995e-02 -1.314805e-05 -1.832806e-01 -1.390005e-01  6.790666e-01
  [6]  3.018813e+00 -5.143447e-01 -6.365760e-01 -1.059639e+00  1.317967e-01
 [11] -2.324869e-01 -5.968321e-01 -1.057436e+00  2.822302e-02 -6.799233e-02
 [16] -2.038818e-01 -6.359332e-01 -3.277948e-01 -7.599941e-02 -8.200243e-02
 [21] -8.038721e-01 -1.138439e+00 -6.355252e-01 -3.343370e-01 -4.909687e-01
 [26] -1.673277e+00 -9.224390e+00  8.870486e-01  2.273328e+00  4.922837e+00
 [31] -6.905172e-01  7.496899e-01  3.555336e+00  2.596297e+00  4.649710e-01
 [36] -8.072050e-01 -7.670278e-02  5.625944e-02 -5.191353e-02  2.268745e+00
 [41] -1.954553e+00 -9.110893e-01 -5.066350e-01 -6.785369e-02 -1.012981e+00
 [46] -1.235721e+00 -1.000658e+00  3.429774e+00 -6.682844e-01 -1.322106e+00
 [51] -1.512727e+00  2.773340e-01 -1.157277e-01 -9.639707e-01 -1.522391e+00
 [56] -7.038925e-01 -2.445530e-01  4.184710e+00  1.492217e+00 -1.637551e+00
 [61] -1.730787e+00 -4.714455e-02  4.330817e+00 -7.039205e-01 -2.063345e+00
 [66] -1.681363e+00  6.441892e-01 -2.508443e-01 -1.265085e+00  5.161127e+00
 [71] -2.101685e+00 -9.889237e-01 -1.954521e+00 -1.993731e-01 -1.104261e+00
 [76]  2.073569e+00 -1.098516e+00 -1.275214e+00 -1.431418e+00 -6.005319e-01
 [81]  2.956296e+00  7.317420e-02 -9.376182e-01 -1.906084e+00  5.861759e-01
 [86] -8.744912e-01 -7.826100e-01 -5.858691e-01 -2.435931e-02 -2.474914e-01
 [91] -1.453993e+00  1.406290e+00  4.079158e-01 -1.227833e+00 -9.848355e-01
 [96]  9.770439e-01 -1.142908e+00 -1.526230e+00  1.257935e+00 -3.018815e+00
[101] -2.134350e+00  1.819751e+00 -1.583944e+00 -1.507683e+00  1.440503e+00
[106] -1.577135e+00  3.773146e+00 -9.067724e-01  5.604225e+00  8.111425e+00
[111]  1.377665e+01 -2.212475e+00 -6.798389e-01 -2.007566e+00  1.691634e+00
[116] -1.258737e+00 -2.527224e+00 -2.196284e+00  2.551559e+00 -8.951225e-01
[121] -1.761679e+00 -2.638303e+00 -5.680957e-01 -2.060907e-01 -9.891457e-01
[126] -1.998862e+00 -1.282842e+00 -2.945144e-01 -2.957190e-01  1.307276e+00
[131]  9.878861e-01 -1.205351e+00  2.383499e-01  2.061192e+00 -1.716434e+00
[136]  6.430904e-01 -1.096348e+00 -8.993207e-01 -1.342488e+00 -1.064657e+00
[141] -1.343561e+00  1.810253e+00  4.211285e+00 -2.114688e+00 -5.565936e-01
[146] -3.310330e+00  8.472534e-01  6.761904e+00 -2.649121e+00 -3.521170e-01
[151] -1.341652e+00  5.682802e-01 -1.171931e+00 -6.714411e-01 -2.107525e-01
[156] -9.826186e-01 -1.144529e+00 -1.667987e+00  2.096494e+00  2.115848e+00
[161] -1.877428e+00 -2.129708e+00 -1.264786e+00 -2.925220e-01  6.814415e+00
[166] -2.203438e+00 -2.136576e+00 -2.122826e+00  8.973201e-01 -4.984344e-01
[171]  8.247248e-01  2.415881e+00 -1.162833e+00 -8.075840e-01 -1.175571e+00
[176] -7.193047e-01 -1.245955e+00  2.109844e+00 -9.311765e-01 -1.210512e+00
[181] -2.763088e-01 -3.148288e+00 -1.102565e+00 -4.253625e-01 -2.092785e-01
[186] -7.689611e-01 -3.797511e+00 -2.749030e+00  3.953111e-01  2.275887e-01
[191] -7.355515e-01 -1.228722e+00 -2.879334e-01  2.327557e-01 -1.946979e-01
[196]  2.210476e+00 -2.920099e-01 -6.195468e-01 -5.806055e-01  6.755669e+00
[201] -1.404563e+00 -9.700471e-01 -1.467554e+00  7.578539e-01  1.230978e-01
[206]  6.679601e+00  1.769316e+01 -4.188286e+00 -2.487972e+00 -4.918999e-01
[211]  2.474425e+00  2.016388e+01  9.727387e+00 -2.322330e+00 -3.462016e+00
[216] -1.243340e+00  1.662977e+00 -1.243171e+00 -4.320223e+00 -9.310366e-01
[221]  5.237433e+00 -2.608134e+00 -3.158899e+00 -5.098517e+00  1.071105e+00
[226] -1.537743e+00  4.673580e-01 -2.026945e+00 -5.859619e+00  4.213956e+00
[231]  2.465476e-01 -2.985513e+00 -8.759801e-01 -4.872838e-01  4.271428e+00
[236]  1.528747e+01 -1.503667e+00  3.024813e-01 -1.646343e+00 -4.451582e+00
[241] -3.427674e+00  1.918555e+01  4.091915e+01 -1.709220e+01  1.987459e+01
[246] -6.322236e+00 -2.970166e+01 -5.215309e+00 -1.157171e+00 -1.776867e+00
[251] -6.448009e+00  6.173899e+00 -1.814735e-01  9.095738e+00 -1.824421e+01
[256]  3.172834e+00 -1.184944e+01  5.302118e+00 -1.463127e+00 -7.459898e-01
[261] -1.100020e+01  1.818265e+00  6.787437e+00  1.828295e+00 -4.878765e+00
[266] -4.080138e+00  3.615632e+00  9.707093e-01 -2.506120e+00 -2.419184e+00
[271] -5.323822e+00  4.732213e-01 -3.218871e+00 -4.236201e-02  7.620876e+00
[276]  1.202296e+01 -1.132234e+01 -5.949587e+00  1.332431e+00  5.483849e-01
[281] -9.058487e-01 -8.004932e+00 -2.130485e-01 -1.622708e+00  1.819066e+00
[286] -7.332346e-01  1.224456e-01 -1.681617e+00 -1.577181e+00 -5.918180e+00
[291]  9.026655e-01  3.274965e+00  4.464541e+00 -1.240145e+01  1.605630e-01
[296]  1.375125e+00  4.235254e+00 -8.173057e+00  2.131480e+00 -1.240203e+00
[301]  5.578448e+00 -3.244704e+00  4.314398e+00  1.166788e+00 -4.210331e+00
[306] -2.633551e+00 -6.433370e+00 -1.345647e-01  6.298390e+00 -3.187533e-01
[311]  1.749003e+00 -8.778568e+00  6.676314e+00 -1.105315e+00 -2.109073e+00
[316] -8.904299e-02  2.249526e+00 -2.532532e+00  4.435500e+00 -4.671613e+00
[321]  1.258487e+00 -1.611422e+00  2.552045e+00  3.970459e-01  6.106788e+00
[326] -1.382770e+00  2.699963e+00 -3.157913e+00  2.841534e+00  4.715791e+00
[331] -8.586991e+00  7.775586e-01  6.844453e+00  2.563231e-01  6.750157e+00
[336]  6.488844e+00 -2.638882e-02  1.318070e+01  1.185556e+01 -9.723368e+00
[341] -4.812113e+00 -5.873825e+00 -4.275667e+00  1.286024e+00 -6.043983e+00
[346]  9.479004e+00  2.989951e+00  9.056091e-01  1.241100e+01 -1.144163e+01
[351] -4.590942e+00  1.388133e+00  3.485522e-02 -7.506824e+00  4.112422e-01
[356]  6.252847e+00 -2.079239e+00 -2.246321e+00  1.049237e+01
> postscript(file="/var/www/html/rcomp/tmp/2gg3u1260460704.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/3j9on1260460704.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/4ekaj1260460704.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/577ks1260460704.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/6li761260460704.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/7uxda1260460704.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/8bd1n1260460705.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/971fz1260460705.tab") 
> system("convert tmp/10u271260460704.ps tmp/10u271260460704.png")
> system("convert tmp/2gg3u1260460704.ps tmp/2gg3u1260460704.png")
> system("convert tmp/3j9on1260460704.ps tmp/3j9on1260460704.png")
> system("convert tmp/4ekaj1260460704.ps tmp/4ekaj1260460704.png")
> system("convert tmp/577ks1260460704.ps tmp/577ks1260460704.png")
> system("convert tmp/6li761260460704.ps tmp/6li761260460704.png")
> system("convert tmp/7uxda1260460704.ps tmp/7uxda1260460704.png")
> 
> 
> proc.time()
   user  system elapsed 
  2.232   1.130   6.063