R version 3.0.2 (2013-09-25) -- "Frisbee Sailing"
Copyright (C) 2013 The R Foundation for Statistical Computing
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.

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 = '2'
> par5 = '12'
> par4 = '1'
> par3 = '1'
> par2 = '1'
> par1 = 'FALSE'
> par9 <- '1'
> par8 <- '0'
> par7 <- '1'
> par6 <- '2'
> par5 <- '12'
> par4 <- '1'
> par3 <- '1'
> par2 <- '1'
> par1 <- 'FALSE'
> #'GNU S' R Code compiled by R2WASP v. 1.2.327 ()
> #Author: root
> #To cite this work: Wessa P., (2013), ARIMA Backward Selection (v1.0.5) in Free Statistics Software (v$_version), Office for Research Development and Education, URL http://www.wessa.net/rwasp_arimabackwardselection.wasp/
> #Source of accompanying publication: Office for Research, Development, and Education
> #
> library(lattice)
> if (par1 == 'TRUE') par1 <- TRUE
> if (par1 == 'FALSE') par1 <- FALSE
> par2 <- as.numeric(par2) #Box-Cox lambda transformation parameter
> par3 <- as.numeric(par3) #degree of non-seasonal differencing
> par4 <- as.numeric(par4) #degree of seasonal differencing
> par5 <- as.numeric(par5) #seasonal period
> par6 <- as.numeric(par6) #degree (p) of the non-seasonal AR(p) polynomial
> par7 <- as.numeric(par7) #degree (q) of the non-seasonal MA(q) polynomial
> par8 <- as.numeric(par8) #degree (P) of the seasonal AR(P) polynomial
> par9 <- as.numeric(par9) #degree (Q) of the seasonal MA(Q) polynomial
> armaGR <- function(arima.out, names, n){
+ try1 <- arima.out$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]
[1,] 0.1978422 0.2350068 -0.06682547 -0.6943204
[2,] 0.1350038 0.2464071  0.00000000 -0.6952818
[3,]        NA        NA          NA         NA
[4,]        NA        NA          NA         NA
[5,]        NA        NA          NA         NA
[6,]        NA        NA          NA         NA
[7,]        NA        NA          NA         NA
[8,]        NA        NA          NA         NA

[[2]]
        [,1]    [,2]    [,3] [,4]
[1,] 0.55572 0.00448 0.84953    0
[2,] 0.00886 0.00000      NA    0
[3,]      NA      NA      NA   NA
[4,]      NA      NA      NA   NA
[5,]      NA      NA      NA   NA
[6,]      NA      NA      NA   NA
[7,]      NA      NA      NA   NA
[8,]      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     sma1
      0.1978  0.2350  -0.0668  -0.6943
s.e.  0.3355  0.0822   0.3520   0.0385

sigma^2 estimated as 449.6:  log likelihood = -1609.89,  aic = 3229.77

[[3]][[2]]

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

Coefficients:
         ar1     ar2      ma1     sma1
      0.1978  0.2350  -0.0668  -0.6943
s.e.  0.3355  0.0822   0.3520   0.0385

sigma^2 estimated as 449.6:  log likelihood = -1609.89,  aic = 3229.77

[[3]][[3]]
NULL

[[3]][[4]]
NULL


$aic
[1] 3229.775 3227.810

> postscript(file="/var/wessaorg/rcomp/tmp/1r11l1385133095.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]   0.135735011   0.096024059   0.049255374   0.015634844  -0.023075919
  [6]   0.017042382   0.014873407  -0.003244155  -0.019624935  -0.047524262
 [11]  -0.015865845  -0.128516011  -0.535786078   1.803328556   5.247990770
 [16]   9.686520004  49.056807573  -4.945025608  21.003643832 -27.719204114
 [21] -17.488214184  44.660340093 -42.989743133  -7.793193482  24.594161022
 [26] -30.282408148 -31.572230652 -33.084944042 -17.736781138   2.984073063
 [31] -32.655807548 -27.317428584  27.445210999 -26.616487886  28.072372215
 [36]  -4.652289689 -65.309569324 -33.794147092  25.054578823   8.505471731
 [41]   2.491557389  -0.544447090 -10.398345796  20.841104220  26.953317356
 [46]  -0.610311252   1.791491296 -34.065266314 -15.230129821  -0.514117803
 [51]  -3.105479624  23.834816089  12.680405010 -17.958935947   2.607115294
 [56]  24.593381643 -12.577217808 -10.920005429  -3.050449833  -3.555997658
 [61]   3.471437728 -30.100487350  17.973223680  29.534677662 -14.491801906
 [66] -18.075552150  -0.949562378  16.181157959  23.267202565   9.537663226
 [71]  21.044837630  27.208147058  49.457766730  20.075752460   8.169870816
 [76] -10.204402167  -9.956972155 -27.478801027   2.811928945  13.919274665
 [81]   1.581458363 -36.847091722  -1.849764213 -11.695995888  -6.542240037
 [86] -19.748569999  -6.244090999  16.433385724 -27.123131847   1.927634518
 [91] -16.416119203  16.976201652 -10.758724822  19.905920032   3.227273156
 [96]  -2.581693055 -28.557460206  -2.857926195  25.954704040 -19.969624510
[101]  33.658594223  17.306864215 -23.379935017 -32.981553698  -3.158219762
[106]  10.388164585  30.026159310  -2.386848449 -17.655712992 -18.043731380
[111]  -8.660399620  12.075721813  19.470305207  20.478317496 -25.336631395
[116]  -4.377026190  14.368475308  14.624900785  29.848638653   6.911554878
[121]  40.439303219  53.314778355  -0.471752892  -4.988428454 -20.530880567
[126]   3.741661431   5.731646158 -19.633133011 -44.116390844  -5.966566438
[131] -25.351418396  28.266794848  -9.368775017 -20.195026003 -23.277840699
[136] -46.355135598   6.137161027  25.390016850  -0.747939288   8.886169111
[141]   7.143705571  19.450168591   4.841486504 -34.079791812 -12.113911361
[146] -30.103864904  55.849211508 -16.537701455 -13.847182258  45.935559180
[151] -16.727607110   7.854690672 -18.353101205  33.373900190   9.243141560
[156]  33.665349334   9.306772735  15.677339260 -26.874942963 -16.671031349
[161]   2.685555036  17.003149658 -16.299371820 -24.867891109  -7.379574055
[166]  -7.394137522 -22.814455996  -2.679914208  -7.534151486 -20.840975788
[171]   2.299037013   6.768249206  30.370947250 -31.609570330 -17.766470149
[176]  45.267156842  -8.716529916 -23.298963463  24.888298872 -12.754548965
[181]  14.317315984  21.009031423 -37.354666067  -0.462653499  13.569513320
[186]  13.723416666 -15.913214264 -16.077807755   9.411374310   6.691812705
[191]  10.742663820 -22.546048509  -1.958619154 -11.053724698   0.705426936
[196]  10.210707058 -21.374865314  43.301896113 -45.436057738  12.320161545
[201]  11.094300659   0.096411077 -27.388579529   4.640933776 -14.904674278
[206]  20.353691904 -22.381897465  22.181714828  -9.462403621  17.335497638
[211] -16.362980994  -5.471764975   2.610381737  -3.210612485 -11.171286123
[216] -14.899160367 -16.767315032 -16.904733880  26.812823234  14.529088747
[221]  20.201101796   3.924479792 -10.446440700  -0.905441983  -0.207693044
[226]   6.214363423 -15.689195142   6.778512874  -8.849917206  -0.673648496
[231]   4.197510128   4.560208457 -10.041252336  44.243501477  10.803065929
[236] -19.165623794  23.429606147  11.861615233 -34.937175697 -22.808016531
[241] -12.830774824  26.976937490  -8.480919532 -14.280999456  -0.301613962
[246]  48.367093519   3.544031108 -30.309183967   6.508209808  -2.238788093
[251]  -7.637703700 -10.881514338  -1.474759445   0.102117983  11.910491307
[256]  14.850719485 -12.941241879   6.243919035  25.298643637  -4.783476675
[261]  23.808987155 -10.496355676 -31.030761842   2.596695317  34.976768195
[266]  28.343598167   7.365180503   2.385296625  -5.292416017  22.054014280
[271]  18.052452852  -6.640773776  13.122450359   0.783917042  25.488460640
[276]   4.691577262  10.928960495 -19.825282712 -10.980313793 -16.883543296
[281]  -7.337151529   5.829521882  18.641784396   2.358730838 -20.115039141
[286] -19.805504622  17.611830925  -4.040809271   9.868907946 -15.896697793
[291]   1.091122543 -14.744558283 -11.509309713   4.136960698   5.171860384
[296]  -1.412678144  -8.854704381  -4.540502991 -34.195547115  -1.951850127
[301]  -1.245432031  13.444846015 -10.726507658   4.868137223  -9.546777773
[306]  -4.426448595  -0.107140971  -2.158447804  10.921724200 -25.887191693
[311]  25.005799125  12.298818180  24.460670070  -4.080319869 -21.981084653
[316]  -7.269352736  17.976830879  15.784009758  10.043182641 -12.042476755
[321]  39.371839171   2.203491018  40.222813771  39.347929147 114.974518451
[326] -28.669001348   0.156176267 -21.052571667  -1.129018302 -16.161455187
[331] -12.161710916 -11.876626888 -13.627855256  -0.250400291 -23.678512589
[336]  -6.069567619  -7.491294460 -20.337173643 -24.645431546  -8.486641914
[341] -24.261558030  37.661992534  24.151675380   4.635121499 -32.532817894
[346]   3.134930081  12.466061164 -13.420749354 -26.847259082  28.529498500
[351] -23.119370697 -50.150888040   5.138473901  27.670771423 -29.531526569
[356]  16.962088779 -15.275146615  -0.828382751  -4.226318668 -46.228176114
[361]   8.987671223 -14.788134607  14.736763618  -9.013286195  13.109156006
[366] -31.759507995  42.684878847 -18.469785390  -2.301229925  -8.209349047
[371]  -1.021812867  26.203721654
> postscript(file="/var/wessaorg/rcomp/tmp/2git61385133095.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/3eu5f1385133095.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/4x1io1385133095.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/57obi1385133095.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/6v3si1385133095.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/7d5s21385133095.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/8cf851385133095.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/9zq7s1385133095.tab") 
> 
> try(system("convert tmp/1r11l1385133095.ps tmp/1r11l1385133095.png",intern=TRUE))
character(0)
> try(system("convert tmp/2git61385133095.ps tmp/2git61385133095.png",intern=TRUE))
character(0)
> try(system("convert tmp/3eu5f1385133095.ps tmp/3eu5f1385133095.png",intern=TRUE))
character(0)
> try(system("convert tmp/4x1io1385133095.ps tmp/4x1io1385133095.png",intern=TRUE))
character(0)
> try(system("convert tmp/57obi1385133095.ps tmp/57obi1385133095.png",intern=TRUE))
character(0)
> try(system("convert tmp/6v3si1385133095.ps tmp/6v3si1385133095.png",intern=TRUE))
character(0)
> try(system("convert tmp/7d5s21385133095.ps tmp/7d5s21385133095.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  8.131   1.305   9.447