R version 2.15.2 (2012-10-26) -- "Trick or Treat"
Copyright (C) 2012 The R Foundation for Statistical Computing
ISBN 3-900051-07-0
Platform: i686-pc-linux-gnu (32-bit)

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.

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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 = '1'
> par7 = '1'
> par6 = '2'
> par5 = '12'
> par4 = '0'
> par3 = '1'
> par2 = '1'
> par1 = 'FALSE'
> par9 <- '1'
> par8 <- '1'
> par7 <- '1'
> par6 <- '2'
> par5 <- '12'
> par4 <- '0'
> par3 <- '1'
> par2 <- '1'
> 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]      [,4]       [,5]
 [1,] 0.1047677 0.2363271 0.03162938 0.9896167 -0.6923466
 [2,] 0.1347581 0.2312974 0.00000000 0.9896168 -0.6918402
 [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,] 0.76964 0.00234 0.93268    0    0
 [2,] 0.00818 0.00001      NA    0    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     ma1    sar1     sma1
      0.1048  0.2363  0.0316  0.9896  -0.6923
s.e.  0.3575  0.0771  0.3742  0.0047   0.0404

sigma^2 estimated as 447.6:  log likelihood = -1672.1,  aic = 3356.2

[[3]][[2]]

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

Coefficients:
         ar1     ar2     ma1    sar1     sma1
      0.1048  0.2363  0.0316  0.9896  -0.6923
s.e.  0.3575  0.0771  0.3742  0.0047   0.0404

sigma^2 estimated as 447.6:  log likelihood = -1672.1,  aic = 3356.2

[[3]][[3]]
NULL

[[3]][[4]]
NULL

[[3]][[5]]
NULL


$aic
[1] 3356.202 3354.206

> postscript(file="/var/wessaorg/rcomp/tmp/1a76q1355668634.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]   0.23509932  19.00614089 -10.21173395 -14.06411728 -13.94131925
  [6]  21.77578102   1.61100816 -11.89674085  -6.79068661 -11.85044264
 [11]  15.56564453   5.20170665  31.10086738   4.31268277  -1.31525546
 [16]   6.27961456  46.88535123   0.88630376  23.01400842 -30.77246703
 [21] -19.25655766  43.59526876 -41.00550652  -5.77674850  34.01463527
 [26] -29.52522060 -35.31494759 -35.28642373 -18.92136831   5.44856358
 [31] -33.05426921 -31.54879502  25.20764296 -28.16894422  28.66170443
 [36]  -3.79162094 -59.77664433 -32.19904004  21.36370476   4.40937577
 [41]   0.99828508   2.28360620 -10.15977892  17.95194572  25.99154694
 [46]  -1.13488307   3.82562060 -32.58808381 -11.17841847  -0.11167243
 [51]  -6.15010926  21.62278026  11.85428242 -15.70211034   3.38267469
 [56]  22.47996420 -13.24962804 -10.85246934  -1.46672609  -3.48375260
 [61]   6.07900461 -29.97279420  16.06936368  27.80687521 -15.41905160
 [66] -15.57638683  -0.31188280  14.08362026  22.44761418   9.03627016
 [71]  22.50167858  28.03086734  52.50861477  20.89252466   7.93410748
 [76]  -9.38200393  -9.03883559 -25.17029154   3.11612082  12.08331804
 [81]   0.75511576 -37.14379757  -0.39316204 -11.60590348  -4.58438644
 [86] -19.92394264  -8.15117936  14.97775276 -28.35132596   3.06215562
 [91] -16.50589541  15.13436661 -11.25307574  18.95773771   4.25507877
 [96]  -2.39582669 -25.51825159  -2.61472021  24.34246569 -21.52381789
[101]  33.19642694  18.46052266 -23.57277423 -32.94517727  -2.89433488
[106]   9.34169967  30.20465364  -2.52244119 -15.09639628 -17.37835119
[111]  -9.75115149  10.79992386  18.47932103  21.34570010 -25.44020608
[116]  -4.88021722  14.53124041  13.77650831  31.10173468   7.36368398
[121]  43.13934749  53.82889080  -0.97018685  -3.88344976 -18.98035093
[126]   5.89681324   5.38902804 -21.14758388 -43.92138206  -6.09183299
[131] -24.71800142  27.45847052  -8.05518539 -20.60743895 -24.09035561
[136] -47.56768154   5.31382396  25.47724586  -2.73467003   7.33109508
[141]   6.85480629  19.19767489   6.36618056 -33.17323221  -9.10620951
[146] -30.03754426  53.98624749 -18.71938302 -14.37167443  48.41749261
[151] -17.98664661   6.89646017 -18.01827915  33.27407100  10.54646866
[156]  33.80869249  12.06866171  16.14220545 -26.61775746 -17.09948096
[161]   2.84676744  18.48769058 -17.39474757 -25.99588731  -7.66434978
[166]  -7.77058184 -22.05045886  -2.56841479  -6.04423566 -21.64503494
[171]   0.96701643   4.62083941  29.31937478 -29.73498001 -18.15901806
[176]  44.19539667 -10.34843416 -23.04467025  26.96623114 -12.73240451
[181]  16.34142228  20.98486410 -38.55438381  -1.10885544  13.58202949
[186]  14.93952694 -16.94968042 -16.80919262   8.96418369   6.18168772
[191]  11.86981555 -22.09736317   0.56102082 -11.08836742  -0.98550669
[196]   8.51815893 -21.79575138  45.48686159 -46.96307883  11.32438009
[201]  10.79541502  -0.74496456 -25.49423208   5.08321201 -12.96161111
[206]  19.69336973 -24.00401698  20.64247468  -9.62860057  19.52871667
[211] -17.70205955  -6.53286052   2.35493388  -3.59364827  -9.92456582
[216] -14.71535488 -14.87737099 -17.30891526  24.74340793  12.40408865
[221]  19.53259375   6.92827276 -11.72076745  -1.31375341  -0.52273705
[226]   6.16234428 -14.47870230   6.99771103  -7.01598187  -1.04668617
[231]   2.88997400   3.19615425 -10.14570729  47.05919769   8.65359645
[236] -20.09027238  24.13753214  12.04704682 -33.76958549 -21.75528036
[241] -10.87015223  26.04056627 -10.66951501 -15.57054857  -0.11222757
[246]  51.06963767   1.11000982 -31.25282684   7.43250750  -2.12857554
[251]  -7.19257727 -10.83825855   0.06030777  -0.15321714  10.20083220
[256]  13.48800461 -13.14620236  10.23010828  23.66846881  -6.57031737
[261]  24.06041704  -9.93931308 -29.95148534   3.18831061  36.22532874
[266]  27.64237839   6.21290037   2.31980593  -4.63472646  26.30743467
[271]  16.61176385  -8.04659492  13.95663740   1.29617106  26.14839578
[276]   4.86470385  13.27638839 -18.78642737 -11.60042017 -17.50144397
[281]  -7.93288781   9.33297266  16.51796591   0.24820612 -19.87228482
[286] -19.26595044  18.19614640  -4.85444904  11.56641517 -15.65083116
[291]  -0.14458252 -15.78829956 -12.13649406   7.99015801   3.27527600
[296]  -3.49568191  -8.91320313  -4.60201997 -33.61931865  -2.21794290
[301]   0.33096336  12.54931749 -12.41165749   3.53073133  -9.99368579
[306]  -0.55213295  -1.35758815  -4.20716737  10.68755984 -26.23536202
[311]  25.56560111  11.88259596  26.21360963  -3.46947181 -22.75231966
[316]  -7.62127618  17.37259463  19.31876337   8.68501347 -13.39455127
[321]  39.95920568   1.88562465  41.16050606  40.04139143 117.84297704
[326] -27.50011304   1.36237744 -19.26630710  -0.93851558 -11.37489020
[331] -13.44108574 -13.77005517 -13.77512672  -1.08486024 -23.36121511
[336]  -6.24331238  -4.64341430 -21.23492190 -26.55182768 -10.43919287
[341] -25.60686033  40.89416943  21.87322290   2.02883990 -31.50683266
[346]   3.48087068  13.24419304 -13.81065864 -23.30247119  28.36672001
[351] -25.59352648 -51.89784959   4.93111669  30.89034153 -31.90239650
[356]  15.10982160 -15.39485527  -1.62515770  -3.22897685 -46.54767364
[361]  12.29281927 -15.67384859  11.76799508 -11.36132192  12.05879322
[366] -27.15121925  41.41753658 -20.60678381  -2.62533763  -7.93889156
[371]  -0.51623958  25.87261855
> postscript(file="/var/wessaorg/rcomp/tmp/2pweq1355668634.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/316by1355668634.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/4vo4w1355668634.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/5ke6p1355668634.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/6236s1355668634.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/7kra01355668634.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/8s8q31355668634.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/9yts01355668634.tab") 
> 
> try(system("convert tmp/1a76q1355668634.ps tmp/1a76q1355668634.png",intern=TRUE))
character(0)
> try(system("convert tmp/2pweq1355668634.ps tmp/2pweq1355668634.png",intern=TRUE))
character(0)
> try(system("convert tmp/316by1355668634.ps tmp/316by1355668634.png",intern=TRUE))
character(0)
> try(system("convert tmp/4vo4w1355668634.ps tmp/4vo4w1355668634.png",intern=TRUE))
character(0)
> try(system("convert tmp/5ke6p1355668634.ps tmp/5ke6p1355668634.png",intern=TRUE))
character(0)
> try(system("convert tmp/6236s1355668634.ps tmp/6236s1355668634.png",intern=TRUE))
character(0)
> try(system("convert tmp/7kra01355668634.ps tmp/7kra01355668634.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  5.413   0.658   6.053