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

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Type 'license()' or 'licence()' for distribution details.

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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 = '0'
> par6 = '2'
> par5 = '12'
> par4 = '1'
> par3 = '1'
> par2 = '0.5'
> 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]       [,3]
[1,] 0.1094252 0.2417225 -0.7239618
[2,] 0.0000000 0.2559547 -0.7335038
[3,]        NA        NA         NA
[4,]        NA        NA         NA
[5,]        NA        NA         NA
[6,]        NA        NA         NA

[[2]]
        [,1] [,2] [,3]
[1,] 0.03483    0    0
[2,]      NA    0    0
[3,]      NA   NA   NA
[4,]      NA   NA   NA
[5,]      NA   NA   NA
[6,]      NA   NA   NA

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

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

Coefficients:
         ar1     ar2     sma1
      0.1094  0.2417  -0.7240
s.e.  0.0517  0.0515   0.0403

sigma^2 estimated as 0.2846:  log likelihood = -288.38,  aic = 584.75

[[3]][[2]]

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

Coefficients:
         ar1     ar2     sma1
      0.1094  0.2417  -0.7240
s.e.  0.0517  0.0515   0.0403

sigma^2 estimated as 0.2846:  log likelihood = -288.38,  aic = 584.75

[[3]][[3]]
NULL


$aic
[1] 584.7512 587.2045

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/18w561228579379.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]  8.852493e-03  5.059755e-03  2.900304e-03  1.498531e-03 -1.254779e-06
  [6]  1.218864e-03  1.052761e-03  3.875821e-04 -2.267282e-04 -1.287175e-03
 [11] -1.752638e-04 -8.140184e-03 -4.471402e-02 -6.879392e-02  2.001557e-01
 [16]  3.697183e-01  1.508627e+00 -3.967318e-01  4.571732e-01 -4.563979e-01
 [21] -3.346043e-01  1.358904e+00 -1.392749e+00 -3.906816e-01  2.671212e-01
 [26] -8.980036e-01 -5.687152e-01 -7.163797e-01 -4.485451e-01 -9.714534e-02
 [31] -8.654798e-01 -9.045002e-01  6.901206e-01 -7.957033e-01  7.813652e-01
 [36] -1.241280e-01 -1.694661e+00 -1.030550e+00  4.653027e-01 -5.618063e-02
 [41]  2.591685e-02  3.154095e-01 -3.064480e-01  3.018874e-01  8.810353e-01
 [46]  7.974092e-02  9.404084e-02 -1.146902e+00 -1.253974e-01  5.332154e-03
 [51] -4.053505e-01  5.721867e-01  4.574099e-01 -3.843168e-01  1.180050e-01
 [56]  6.154438e-01 -5.096760e-01 -4.068355e-01 -4.282914e-02 -1.255549e-01
 [61]  4.888731e-01 -1.025798e+00  3.271607e-01  8.939215e-01 -5.545045e-01
 [66] -4.195509e-01 -3.464946e-03  3.068374e-01  8.467610e-01  4.220367e-01
 [71]  8.054228e-01  9.442304e-01  1.218982e+00  4.645768e-01  3.613060e-01
 [76] -7.440547e-02 -1.197197e-01 -9.882713e-01  5.595086e-02  6.069280e-01
 [81]  3.596761e-02 -9.176888e-01 -2.878783e-01 -3.757598e-01 -3.758963e-01
 [86] -4.733833e-01 -5.361421e-02  4.719401e-01 -7.811610e-01 -9.159821e-02
 [91] -4.898689e-01  5.406346e-01 -3.593557e-01  5.930418e-01  6.316755e-02
 [96] -9.435829e-02 -8.169832e-01 -8.050534e-02  7.684807e-01 -5.760533e-01
[101]  9.866096e-01  4.272570e-01 -6.675325e-01 -9.191069e-01 -1.596832e-01
[106]  2.732721e-01  9.405861e-01 -6.969853e-02 -5.791380e-01 -4.929281e-01
[111] -2.244037e-01  3.081060e-01  5.973993e-01  5.670742e-01 -7.408331e-01
[116] -1.218364e-01  4.434712e-01  4.868156e-01  8.122473e-01  1.766944e-01
[121]  7.396646e-01  1.242247e+00  1.796378e-01  7.647717e-02 -3.622843e-01
[126] -2.139279e-01  2.188437e-01 -1.536026e-01 -1.044555e+00 -1.347437e-01
[131] -9.313198e-01  6.379357e-01 -4.378481e-01 -4.250451e-01 -3.991960e-01
[136] -1.150365e+00  6.802039e-02  5.893216e-01 -3.355886e-02  2.515215e-01
[141]  1.405385e-01  5.817527e-01  1.550416e-02 -8.788471e-01 -3.763165e-01
[146] -6.978917e-01  1.398563e+00 -4.045400e-01 -3.807709e-01  1.153289e+00
[151] -3.819232e-01  2.561474e-01 -4.985587e-01  9.300168e-01  1.275442e-01
[156]  7.702136e-01 -1.954248e-02  3.416865e-01 -4.120707e-01 -2.355665e-01
[161]  9.826494e-02  1.628786e-01 -2.968567e-01 -4.203606e-01 -1.933389e-01
[166] -1.812862e-01 -7.248962e-01 -6.830556e-02 -2.477599e-01 -4.642917e-01
[171]  6.191767e-02  1.042445e-01  7.579253e-01 -7.481540e-01 -4.994507e-01
[176]  1.140051e+00 -2.547064e-01 -6.008502e-01  6.228434e-01 -2.925858e-01
[181]  2.926406e-01  5.094991e-01 -8.429229e-01 -2.754145e-02  3.571524e-01
[186]  2.919611e-01 -3.895581e-01 -3.699296e-01  1.938046e-01  1.776563e-01
[191]  2.429794e-01 -5.641708e-01 -6.158105e-02 -2.229833e-01 -2.972081e-02
[196]  2.124696e-01 -5.361386e-01  1.109869e+00 -1.149612e+00  2.721409e-01
[201]  2.636543e-01  3.895066e-03 -7.055806e-01  1.091410e-01 -2.813438e-01
[206]  4.876003e-01 -6.276710e-01  4.871891e-01 -2.537197e-01  5.899513e-01
[211] -5.208159e-01 -2.122070e-01  1.131286e-02 -1.050876e-01 -2.479125e-01
[216] -4.346165e-01 -2.677106e-01 -4.593821e-01  5.197929e-01  2.666513e-01
[221]  5.836049e-01  4.031200e-01 -4.731243e-01 -1.160970e-01 -7.388039e-02
[226]  1.930483e-01 -3.757648e-01  1.996485e-01 -7.782885e-02 -3.433757e-02
[231] -2.125730e-02  2.254937e-02 -3.239021e-01  1.535359e+00  2.013627e-01
[236] -6.122518e-01  6.936280e-01  3.847513e-01 -1.008027e+00 -6.812796e-01
[241] -2.545304e-01  7.430093e-01 -3.335601e-01 -5.377528e-01 -5.689019e-02
[246]  1.684745e+00  3.045852e-02 -9.635777e-01  1.951520e-01 -5.130611e-02
[251] -2.398529e-01 -3.721772e-01  9.158759e-02  3.055112e-02  2.131530e-01
[256]  3.680269e-01 -4.110060e-01  4.812575e-01  6.318023e-01 -2.209504e-01
[261]  7.378573e-01 -2.578849e-01 -9.499911e-01  5.231953e-02  1.025164e+00
[266]  7.524768e-01  2.199107e-01  1.694755e-01 -7.619040e-02  2.409095e-01
[271]  5.848070e-01  2.904157e-02  3.797191e-01  4.009041e-02  5.199807e-01
[276]  1.617559e-01 -9.782653e-02 -4.398177e-01 -3.424527e-02 -2.071458e-01
[281] -1.391501e-01 -3.941288e-01  5.929464e-01  3.017311e-01 -4.142114e-01
[286] -4.653150e-01  3.370335e-01 -6.577146e-02 -3.600729e-02 -3.635920e-01
[291]  1.580369e-01 -2.147597e-01 -2.551976e-01 -2.693191e-01  2.561659e-01
[296]  1.296354e-01 -1.970747e-01 -1.309628e-01 -8.393697e-01 -6.762704e-02
[301] -9.844118e-02  2.604171e-01 -1.975296e-01  1.223866e-01 -2.495917e-01
[306] -1.949340e-01  6.815677e-02 -2.073380e-02  2.534554e-01 -6.760879e-01
[311]  5.989471e-01  3.256228e-01  4.912511e-01 -9.634476e-02 -4.457602e-01
[316] -1.335823e-01  4.277659e-01  1.729051e-01  3.054013e-01 -1.525459e-01
[321]  8.933649e-01  8.634413e-02  8.086082e-01  8.677223e-01  1.762097e+00
[326] -5.277540e-01  2.366092e-01 -6.493935e-02  9.400075e-02 -1.081646e+00
[331] -1.835843e-02  1.360803e-01 -2.787165e-01  3.033923e-02 -5.584993e-01
[336] -1.124866e-01 -4.052830e-01 -3.961942e-01 -2.610980e-01 -5.895817e-02
[341] -4.516671e-01  2.566944e-01  5.588848e-01  2.717195e-01 -6.034657e-01
[346]  8.593902e-02  1.577315e-01 -2.438124e-01 -6.630349e-01  4.673822e-01
[351] -2.832053e-01 -8.829160e-01  7.993710e-02  2.542138e-01 -4.777425e-01
[356]  4.160237e-01 -3.233907e-01 -2.074145e-02 -1.090275e-01 -9.394848e-01
[361]  1.660266e-01 -2.861008e-01  2.406302e-01 -2.514523e-01  2.508713e-01
[366] -6.223684e-01  8.260429e-01 -3.244734e-01 -9.900675e-02 -1.724403e-01
[371] -2.235651e-02  5.198041e-01
> postscript(file="/var/www/html/rcomp/tmp/2ckqf1228579379.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/3swqv1228579379.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/45ohu1228579379.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/5xmlq1228579379.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/61e341228579379.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/73g7p1228579379.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/8tr921228579379.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/9a6bu1228579379.tab") 
> 
> system("convert tmp/18w561228579379.ps tmp/18w561228579379.png")
> system("convert tmp/2ckqf1228579379.ps tmp/2ckqf1228579379.png")
> system("convert tmp/3swqv1228579379.ps tmp/3swqv1228579379.png")
> system("convert tmp/45ohu1228579379.ps tmp/45ohu1228579379.png")
> system("convert tmp/5xmlq1228579379.ps tmp/5xmlq1228579379.png")
> system("convert tmp/61e341228579379.ps tmp/61e341228579379.png")
> system("convert tmp/73g7p1228579379.ps tmp/73g7p1228579379.png")
> 
> 
> proc.time()
   user  system elapsed 
  2.901   1.133   3.764