R version 2.8.0 (2008-10-20)
Copyright (C) 2008 The R Foundation for Statistical Computing
ISBN 3-900051-07-0

R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.

R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.

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(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 = '0'
> par5 = '12'
> par4 = '1'
> par3 = '1'
> par2 = '-0.3'
> 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]
[1,] 0.05425046 -0.7201231
[2,] 0.00000000 -0.7276537
[3,]         NA         NA
[4,]         NA         NA

[[2]]
        [,1] [,2]
[1,] 0.24653    0
[2,]      NA    0
[3,]      NA   NA
[4,]      NA   NA

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

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

Coefficients:
         ma1     sma1
      0.0543  -0.7201
s.e.  0.0467   0.0446

sigma^2 estimated as 1.192e-05:  log likelihood = 1521.27,  aic = -3036.54

[[3]][[2]]

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

Coefficients:
         ma1     sma1
      0.0543  -0.7201
s.e.  0.0467   0.0446

sigma^2 estimated as 1.192e-05:  log likelihood = 1521.27,  aic = -3036.54


$aic
[1] -3036.542 -3037.195

> postscript(file="/var/www/html/rcomp/tmp/1e7yu1228820685.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 = 372 
Frequency = 1 
  [1]  1.122182e-04  4.238768e-05  3.053395e-05  2.752464e-05  3.154697e-05
  [6]  1.647395e-05  1.404031e-05  1.637100e-05  1.921544e-05  2.706618e-05
 [11]  1.557250e-05 -1.008091e-04 -7.439601e-04  1.781220e-03 -1.649078e-03
 [16] -2.939473e-03 -1.142821e-02  4.281756e-03 -4.203289e-03  8.215144e-04
 [21] -5.824300e-04 -1.001253e-02  1.066082e-02  2.012353e-03  4.834040e-03
 [26]  6.658713e-03  2.163954e-03  4.184627e-03  2.482256e-03  3.403527e-03
 [31]  5.537554e-03  7.300393e-03 -2.097501e-03  7.077199e-03 -5.214236e-03
 [36]  2.047253e-03  8.075844e-03  7.700757e-03  1.276299e-03  5.366040e-03
 [41]  1.099456e-03 -4.614199e-03  2.133409e-03  4.143703e-04 -6.370182e-03
 [46] -1.711847e-03 -2.759861e-03  8.672194e-03 -3.463029e-03  1.278558e-03
 [51]  5.221339e-03 -2.013057e-03 -2.671243e-03  3.168705e-04 -1.958964e-03
 [56] -2.855787e-03  4.949059e-03  3.800725e-03  7.674508e-04  1.510296e-03
 [61] -8.319643e-03  8.231745e-03 -1.557526e-03 -4.211109e-03  5.313852e-03
 [66]  1.711164e-04  9.896231e-04  7.763911e-04 -7.654961e-03 -4.870326e-03
 [71] -9.838488e-03 -9.792686e-03 -7.353597e-03 -4.683921e-03 -5.643709e-03
 [76] -2.577309e-03 -2.660152e-03  7.930210e-03 -5.079984e-04 -4.393505e-03
 [81] -1.291507e-04  2.757182e-03  5.089242e-03  3.667317e-03  6.160452e-03
 [86]  3.102037e-03  3.995107e-04 -2.286807e-03  4.403863e-03  1.626444e-03
 [91]  4.434212e-03 -3.664837e-03  4.059526e-03 -5.331109e-03  1.311249e-03
 [96] -5.458168e-04  5.920366e-03  2.764759e-04 -3.781616e-03  3.633757e-03
[101] -7.747265e-03 -1.119565e-03  2.093891e-03  5.304621e-03  2.556929e-03
[106] -2.016994e-04 -5.903166e-03  1.085076e-04  3.098363e-03  2.769618e-03
[111]  2.045036e-03 -9.257714e-04 -3.752010e-03 -3.460991e-03  3.482492e-03
[116] -2.923895e-04 -2.179582e-03 -4.024937e-03 -4.514784e-03 -1.964600e-03
[121] -2.162609e-03 -6.248287e-03 -3.283897e-03 -3.579578e-03 -1.829383e-04
[126]  3.229990e-03 -1.926387e-03 -1.844390e-03  4.159176e-03 -1.306769e-04
[131]  9.326251e-03 -2.334260e-03  6.428364e-03  1.292288e-03  1.944325e-03
[136]  5.824861e-03  7.164507e-04 -6.880199e-04  7.510404e-05 -2.308466e-03
[141] -6.610270e-04 -4.443983e-03  1.269865e-03  3.872095e-03  3.179008e-03
[146]  4.105772e-03 -6.473790e-03  2.369485e-03  4.892035e-04 -4.581540e-03
[151]  1.411053e-03 -3.285878e-03  2.993314e-03 -6.168997e-03  1.407433e-03
[156] -4.735230e-03  2.327337e-03 -2.565801e-03  9.486495e-04 -1.009011e-03
[161] -7.357602e-04  1.433245e-03  3.719817e-04  6.260076e-04  8.446845e-04
[166]  1.167609e-03  5.525357e-03  9.434597e-04  3.208714e-03  2.166038e-03
[171]  3.184502e-04  5.403219e-05 -3.843326e-03  3.976509e-03  1.761305e-03
[176] -5.058967e-03  1.647992e-03  2.090637e-03 -2.434823e-03  1.813235e-03
[181] -1.423888e-03 -2.126491e-03  3.066298e-03 -4.560056e-04 -1.048211e-03
[186] -9.636238e-04  1.283908e-03  1.400713e-03 -4.683727e-04 -7.202538e-04
[191] -8.509922e-04  2.640245e-03  4.162155e-04  1.417598e-03  3.135839e-04
[196] -5.837721e-04  2.908426e-03 -5.538987e-03  6.079871e-03 -2.385456e-03
[201]  2.297101e-04 -6.517986e-04  4.012151e-03 -6.894466e-04  1.713138e-03
[206] -2.485983e-03  3.794730e-03 -2.516144e-03  2.356441e-03 -4.336184e-03
[211]  3.420429e-03  7.966862e-04  1.433871e-03  1.070615e-03  1.211907e-03
[216]  2.953617e-03  2.434976e-04  3.348656e-03 -1.456526e-03  4.622095e-04
[221] -4.043954e-03 -4.286050e-03  2.595203e-03  6.034688e-04  1.918846e-03
[226] -1.058878e-03  1.932056e-03 -1.723819e-03 -7.212495e-04 -2.248293e-04
[231]  1.026121e-03  9.313789e-04  2.898204e-03 -1.112526e-02 -5.603107e-04
[236]  1.638846e-03 -4.526256e-03 -2.384433e-03  4.974651e-03  4.014451e-03
[241]  1.800708e-03 -3.436218e-03  3.066833e-03  3.890416e-03  1.862099e-03
[246] -1.157455e-02  1.304852e-04  3.900646e-03 -8.496856e-04  1.372875e-03
[251]  1.022589e-03  3.056119e-03 -1.761206e-03  3.533288e-04 -7.082491e-04
[256] -1.733999e-03  2.846877e-03 -5.193418e-03 -2.820255e-03  4.673120e-04
[261] -5.573554e-03  1.331413e-03  4.795864e-03  1.014354e-04 -5.491355e-03
[266] -4.148235e-03 -2.874377e-03 -2.945490e-03 -1.128079e-03  1.887028e-03
[271] -4.023036e-03 -1.917107e-03 -3.065713e-03 -9.458082e-04 -2.830150e-03
[276] -1.631045e-03  3.019141e-03  1.938883e-03 -8.601034e-04 -1.725844e-04
[281] -2.716975e-04  6.957190e-03 -3.510676e-03 -2.186002e-03  7.440654e-04
[286]  1.501163e-03 -8.443617e-04  2.507904e-04  2.421549e-03  1.909248e-03
[291] -1.251940e-03  2.336963e-04  3.693142e-04  4.956352e-03 -1.686355e-03
[296] -1.071873e-03  4.006917e-04  3.387030e-04  4.169470e-03  4.850290e-04
[301]  2.453556e-03 -6.416111e-04  8.931292e-04 -1.030735e-03  1.272374e-03
[306]  2.087479e-03 -3.199892e-04  3.265110e-05 -1.225968e-03  3.419280e-03
[311] -3.186138e-03 -1.094353e-03 -2.086925e-03  2.281988e-04  8.599170e-04
[316]  2.770567e-04 -2.006588e-03  1.173379e-03 -2.179028e-03 -2.275086e-04
[321] -4.289320e-03 -9.911973e-04 -3.802307e-03 -3.844156e-03 -3.506129e-03
[326]  8.512291e-04 -3.289863e-03 -1.714093e-03 -2.118887e-03  8.522330e-03
[331] -1.306377e-03 -9.920708e-04  8.099683e-04 -7.911917e-04  2.790423e-03
[336]  3.020140e-04  4.350866e-03  1.566150e-03  4.793230e-04 -3.976060e-04
[341]  1.191847e-03  2.517817e-03 -2.033502e-03 -1.853738e-03  1.429511e-03
[346] -9.991873e-04  3.738965e-04  5.319416e-04  3.740764e-03 -9.273923e-04
[351]  6.669342e-04  1.901152e-03 -2.266972e-04  1.901064e-03  1.078468e-03
[356] -1.748532e-03  1.406033e-03 -4.355714e-04  9.741917e-04  3.250760e-03
[361]  2.321237e-04  1.769855e-03 -8.403727e-04  1.273650e-03 -1.130043e-03
[366]  3.027260e-03 -3.039102e-03  1.390395e-03 -1.943391e-04  9.610652e-04
[371]  1.219788e-04 -1.724112e-03
> postscript(file="/var/www/html/rcomp/tmp/2gn8f1228820685.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/37f8e1228820685.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/4lgdl1228820685.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/51j2f1228820685.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/6bk921228820685.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/71lb71228820685.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/80q3q1228820685.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/9bkyi1228820685.tab") 
> 
> system("convert tmp/1e7yu1228820685.ps tmp/1e7yu1228820685.png")
> system("convert tmp/2gn8f1228820685.ps tmp/2gn8f1228820685.png")
> system("convert tmp/37f8e1228820685.ps tmp/37f8e1228820685.png")
> system("convert tmp/4lgdl1228820685.ps tmp/4lgdl1228820685.png")
> system("convert tmp/51j2f1228820685.ps tmp/51j2f1228820685.png")
> system("convert tmp/6bk921228820685.ps tmp/6bk921228820685.png")
> system("convert tmp/71lb71228820685.ps tmp/71lb71228820685.png")
> 
> 
> proc.time()
   user  system elapsed 
  2.373   1.099   3.099