R version 2.13.0 (2011-04-13)
Copyright (C) 2011 The R Foundation for Statistical Computing
ISBN 3-900051-07-0
Platform: i486-pc-linux-gnu (32-bit)

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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 = '0'
> par7 = '1'
> par6 = '3'
> par5 = '12'
> par4 = '1'
> par3 = '1'
> par2 = '0.5'
> 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
> 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]
 [1,] 0.5336851 0.1847855 -0.0276559 -0.4470970 -0.7213100
 [2,] 0.4617444 0.1881821  0.0000000 -0.3766776 -0.7209464
 [3,]        NA        NA         NA         NA         NA
 [4,]        NA        NA         NA         NA         NA
 [5,]        NA        NA         NA         NA         NA
 [6,]        NA        NA         NA         NA         NA
 [7,]        NA        NA         NA         NA         NA
 [8,]        NA        NA         NA         NA         NA
 [9,]        NA        NA         NA         NA         NA
[10,]        NA        NA         NA         NA         NA

[[2]]
         [,1]    [,2]    [,3]    [,4] [,5]
 [1,] 0.05795 0.00520 0.76956 0.10481    0
 [2,] 0.00778 0.00444      NA 0.03073    0
 [3,]      NA      NA      NA      NA   NA
 [4,]      NA      NA      NA      NA   NA
 [5,]      NA      NA      NA      NA   NA
 [6,]      NA      NA      NA      NA   NA
 [7,]      NA      NA      NA      NA   NA
 [8,]      NA      NA      NA      NA   NA
 [9,]      NA      NA      NA      NA   NA
[10,]      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     sma1
      0.5337  0.1848  -0.0277  -0.4471  -0.7213
s.e.  0.2806  0.0657   0.0943   0.2750   0.0403

sigma^2 estimated as 0.2825:  log likelihood = -286.97,  aic = 585.93

[[3]][[2]]

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

Coefficients:
         ar1     ar2      ar3      ma1     sma1
      0.5337  0.1848  -0.0277  -0.4471  -0.7213
s.e.  0.2806  0.0657   0.0943   0.2750   0.0403

sigma^2 estimated as 0.2825:  log likelihood = -286.97,  aic = 585.93

[[3]][[3]]
NULL

[[3]][[4]]
NULL

[[3]][[5]]
NULL


$aic
[1] 585.9314 584.0182

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/wessaorg/rcomp/tmp/1decs1322751639.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]  8.852493e-03  5.059755e-03  2.900304e-03  1.498531e-03 -1.255896e-06
  [6]  1.218862e-03  1.052759e-03  3.875786e-04 -2.267320e-04 -1.287178e-03
 [11] -1.752666e-04 -8.140185e-03 -4.471362e-02 -6.886914e-02  1.997200e-01
 [16]  3.698846e-01  1.527003e+00 -3.635251e-01  4.558185e-01 -5.637401e-01
 [21] -3.695884e-01  1.280866e+00 -1.361636e+00 -3.699431e-01  1.811987e-01
 [26] -8.640762e-01 -5.620574e-01 -7.274799e-01 -4.073796e-01 -4.839156e-02
 [31] -7.804690e-01 -8.387342e-01  7.162605e-01 -7.017467e-01  8.908639e-01
 [36] -8.327976e-02 -1.586856e+00 -1.082484e+00  4.239775e-01  3.347785e-02
 [41]  1.570849e-01  3.718344e-01 -2.493014e-01  3.230524e-01  8.725883e-01
 [46]  1.207369e-01  9.336091e-02 -1.196958e+00 -1.816143e-01 -5.970533e-02
 [51] -3.618615e-01  5.918341e-01  4.921828e-01 -3.201195e-01  1.069694e-01
 [56]  5.795636e-01 -4.978583e-01 -4.212370e-01 -1.101804e-01 -1.215030e-01
 [61]  5.157274e-01 -9.953841e-01  3.366626e-01  8.619849e-01 -4.697040e-01
 [66] -4.111046e-01 -6.562532e-02  3.036251e-01  8.712458e-01  4.653300e-01
 [71]  8.238653e-01  9.215936e-01  1.203144e+00  4.177732e-01  2.752497e-01
 [76] -2.176291e-01 -2.453682e-01 -1.108141e+00 -3.820011e-02  5.457673e-01
 [81]  8.789066e-02 -8.881021e-01 -3.270234e-01 -4.102262e-01 -3.421323e-01
 [86] -4.460582e-01 -1.435509e-02  5.196831e-01 -7.001387e-01 -4.849401e-02
 [91] -5.041202e-01  5.797267e-01 -3.304089e-01  6.572443e-01  6.489847e-02
 [96] -4.591506e-02 -8.450229e-01 -1.113056e-01  7.375024e-01 -5.158845e-01
[101]  1.020689e+00  4.187040e-01 -6.093007e-01 -9.877345e-01 -2.458154e-01
[106]  2.493264e-01  9.955942e-01  5.029168e-03 -5.378773e-01 -5.517710e-01
[111] -2.717477e-01  3.044600e-01  6.372070e-01  6.287450e-01 -7.034600e-01
[116] -1.555350e-01  3.701847e-01  5.035189e-01  8.324954e-01  1.896268e-01
[121]  7.240686e-01  1.186600e+00  1.609134e-01  1.103067e-02 -4.944148e-01
[126] -3.199601e-01  1.319724e-01 -1.773777e-01 -1.049909e+00 -1.767593e-01
[131] -9.556737e-01  6.820569e-01 -3.941995e-01 -3.220088e-01 -4.035591e-01
[136] -1.114783e+00  8.061095e-02  6.283290e-01  9.540541e-02  3.273574e-01
[141]  1.624824e-01  6.005376e-01  1.547718e-02 -8.843304e-01 -4.455861e-01
[146] -7.551981e-01  1.405230e+00 -3.453764e-01 -2.842046e-01  1.091497e+00
[151] -3.456826e-01  2.842608e-01 -5.585585e-01  9.168413e-01  1.025670e-01
[156]  8.130372e-01 -5.373668e-02  3.293708e-01 -4.895243e-01 -2.779792e-01
[161]  2.468053e-02  1.504185e-01 -2.855973e-01 -4.231573e-01 -2.145794e-01
[166] -1.837111e-01 -7.009848e-01 -5.532469e-02 -2.262077e-01 -4.006452e-01
[171]  9.083408e-02  1.513308e-01  8.220637e-01 -6.974702e-01 -4.791465e-01
[176]  1.075718e+00 -2.087635e-01 -5.499358e-01  5.618255e-01 -2.924981e-01
[181]  3.238904e-01  4.883966e-01 -8.136406e-01 -5.531071e-02  2.987679e-01
[186]  3.267946e-01 -3.630147e-01 -3.816474e-01  1.564874e-01  1.838233e-01
[191]  2.747783e-01 -5.489895e-01 -7.240367e-02 -2.556438e-01 -1.052351e-02
[196]  2.211220e-01 -5.047864e-01  1.118629e+00 -1.131397e+00  3.038242e-01
[201]  1.924443e-01  6.818242e-02 -7.076785e-01  9.332317e-02 -3.011508e-01
[206]  5.246781e-01 -6.083171e-01  5.191769e-01 -2.699221e-01  6.299068e-01
[211] -5.254818e-01 -1.956875e-01 -4.152413e-02 -9.041249e-02 -2.357256e-01
[216] -4.261787e-01 -2.652852e-01 -4.491606e-01  5.500828e-01  3.128194e-01
[221]  6.618074e-01  4.216341e-01 -4.528878e-01 -1.666690e-01 -1.398663e-01
[226]  1.800114e-01 -3.757026e-01  2.043392e-01 -8.748454e-02 -9.411190e-03
[231] -2.737451e-02  2.878979e-02 -3.216624e-01  1.529712e+00  2.360647e-01
[236] -5.532920e-01  5.970375e-01  3.328554e-01 -9.960555e-01 -7.500458e-01
[241] -3.389613e-01  7.509068e-01 -2.684549e-01 -4.733970e-01 -8.353379e-02
[246]  1.689642e+00  1.091956e-01 -8.959015e-01  8.687837e-02 -1.134520e-01
[251] -2.195096e-01 -3.823052e-01  8.984286e-02  4.098088e-02  2.528235e-01
[256]  3.904290e-01 -3.847953e-01  4.625612e-01  6.093798e-01 -1.841906e-01
[261]  7.129262e-01 -2.985540e-01 -9.591048e-01 -4.009124e-02  9.894857e-01
[266]  8.138473e-01  2.791751e-01  1.463630e-01 -1.377391e-01  1.690124e-01
[271]  5.306944e-01  1.800514e-02  3.517205e-01 -8.738072e-03  4.960073e-01
[276]  1.226758e-01 -1.182465e-01 -5.008926e-01 -9.021973e-02 -2.444330e-01
[281] -1.322242e-01 -4.004646e-01  6.029578e-01  3.312966e-01 -3.562318e-01
[286] -4.819173e-01  3.006002e-01 -5.866630e-02 -7.832431e-04 -3.675180e-01
[291]  1.591097e-01 -2.149353e-01 -2.278868e-01 -2.788037e-01  2.642396e-01
[296]  1.565861e-01 -1.541710e-01 -1.251800e-01 -8.453767e-01 -7.871820e-02
[301] -1.054619e-01  3.203104e-01 -1.543149e-01  1.649967e-01 -2.424240e-01
[306] -1.790828e-01  5.556508e-02 -3.307620e-03  2.746406e-01 -6.581370e-01
[311]  6.016275e-01  3.152095e-01  5.494447e-01 -1.009772e-01 -4.599968e-01
[316] -1.990644e-01  3.918799e-01  1.845766e-01  3.282179e-01 -1.581801e-01
[321]  8.776850e-01  7.175920e-02  8.186648e-01  8.184633e-01  1.756192e+00
[326] -5.586664e-01  1.574628e-01 -2.551388e-01  1.875929e-02 -1.170233e+00
[331] -8.209277e-02  7.704572e-02 -2.273231e-01  5.380392e-02 -5.437935e-01
[336] -9.737086e-02 -4.100908e-01 -3.579598e-01 -2.450618e-01 -1.878684e-02
[341] -4.023510e-01  3.024510e-01  5.938018e-01  3.463257e-01 -5.712669e-01
[346]  5.978963e-02  1.164206e-01 -2.243607e-01 -6.708342e-01  4.454226e-01
[351] -2.737137e-01 -8.308760e-01  5.379441e-02  2.663749e-01 -4.074731e-01
[356]  4.456174e-01 -3.080474e-01  2.063443e-02 -1.235031e-01 -9.182544e-01
[361]  1.497645e-01 -2.839251e-01  3.081177e-01 -2.199713e-01  2.992392e-01
[366] -6.131562e-01  8.444743e-01 -3.251787e-01 -4.537136e-02 -2.159136e-01
[371] -1.523538e-02  5.177328e-01
> postscript(file="/var/wessaorg/rcomp/tmp/2bv901322751639.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/wessaorg/rcomp/tmp/3vuyf1322751639.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/wessaorg/rcomp/tmp/4wb9h1322751639.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/wessaorg/rcomp/tmp/5o5s01322751639.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/wessaorg/rcomp/tmp/64quk1322751639.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/wessaorg/rcomp/tmp/7mw3o1322751639.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/wessaorg/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/wessaorg/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/wessaorg/rcomp/tmp/8hemu1322751639.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/wessaorg/rcomp/tmp/9tyn41322751639.tab") 
> 
> try(system("convert tmp/1decs1322751639.ps tmp/1decs1322751639.png",intern=TRUE))
character(0)
> try(system("convert tmp/2bv901322751639.ps tmp/2bv901322751639.png",intern=TRUE))
character(0)
> try(system("convert tmp/3vuyf1322751639.ps tmp/3vuyf1322751639.png",intern=TRUE))
character(0)
> try(system("convert tmp/4wb9h1322751639.ps tmp/4wb9h1322751639.png",intern=TRUE))
character(0)
> try(system("convert tmp/5o5s01322751639.ps tmp/5o5s01322751639.png",intern=TRUE))
character(0)
> try(system("convert tmp/64quk1322751639.ps tmp/64quk1322751639.png",intern=TRUE))
character(0)
> try(system("convert tmp/7mw3o1322751639.ps tmp/7mw3o1322751639.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  5.350   0.332   5.701