R version 2.9.0 (2009-04-17)
Copyright (C) 2009 The R Foundation for Statistical Computing
ISBN 3-900051-07-0

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Type 'contributors()' for more information and
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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(255
+ ,280.2
+ ,299.9
+ ,339.2
+ ,374.2
+ ,393.5
+ ,389.2
+ ,381.7
+ ,375.2
+ ,369
+ ,357.4
+ ,352.1
+ ,346.5
+ ,342.9
+ ,340.3
+ ,328.3
+ ,322.9
+ ,314.3
+ ,308.9
+ ,294
+ ,285.6
+ ,281.2
+ ,280.3
+ ,278.8
+ ,274.5
+ ,270.4
+ ,263.4
+ ,259.9
+ ,258
+ ,262.7
+ ,284.7
+ ,311.3
+ ,322.1
+ ,327
+ ,331.3
+ ,333.3
+ ,321.4
+ ,327
+ ,320
+ ,314.7
+ ,316.7
+ ,314.4
+ ,321.3
+ ,318.2
+ ,307.2
+ ,301.3
+ ,287.5
+ ,277.7
+ ,274.4
+ ,258.8
+ ,253.3
+ ,251
+ ,248.4
+ ,249.5
+ ,246.1
+ ,244.5
+ ,243.6
+ ,244
+ ,240.8
+ ,249.8
+ ,248
+ ,259.4
+ ,260.5
+ ,260.8
+ ,261.3
+ ,259.5
+ ,256.6
+ ,257.9
+ ,256.5
+ ,254.2
+ ,253.3
+ ,253.8
+ ,255.5
+ ,257.1
+ ,257.3
+ ,253.2
+ ,252.8
+ ,252
+ ,250.7
+ ,252.2
+ ,250
+ ,251
+ ,253.4
+ ,251.2
+ ,255.6
+ ,261.1
+ ,258.9
+ ,259.9
+ ,261.2
+ ,264.7
+ ,267.1
+ ,266.4
+ ,267.7
+ ,268.6
+ ,267.5
+ ,268.5
+ ,268.5
+ ,270.5
+ ,270.9
+ ,270.1
+ ,269.3
+ ,269.8
+ ,270.1
+ ,264.9
+ ,263.7
+ ,264.8
+ ,263.7
+ ,255.9
+ ,276.2
+ ,360.1
+ ,380.5
+ ,373.7
+ ,369.8
+ ,366.6
+ ,359.3
+ ,345.8
+ ,326.2
+ ,324.5
+ ,328.1
+ ,327.5
+ ,324.4
+ ,316.5
+ ,310.9
+ ,301.5
+ ,291.7
+ ,290.4
+ ,287.4
+ ,277.7
+ ,281.6
+ ,288
+ ,276
+ ,272.9
+ ,283
+ ,283.3
+ ,276.8
+ ,284.5
+ ,282.7
+ ,281.2
+ ,287.4
+ ,283.1
+ ,284
+ ,285.5
+ ,289.2
+ ,292.5
+ ,296.4
+ ,305.2
+ ,303.9
+ ,311.5
+ ,316.3
+ ,316.7
+ ,322.5
+ ,317.1
+ ,309.8
+ ,303.8
+ ,290.3
+ ,293.7
+ ,291.7
+ ,296.5
+ ,289.1
+ ,288.5
+ ,293.8
+ ,297.7
+ ,305.4
+ ,302.7
+ ,302.5
+ ,303
+ ,294.5
+ ,294.1
+ ,294.5
+ ,297.1
+ ,289.4
+ ,292.4
+ ,287.9
+ ,286.6
+ ,280.5
+ ,272.4
+ ,269.2
+ ,270.6
+ ,267.3
+ ,262.5
+ ,266.8
+ ,268.8
+ ,263.1
+ ,261.2
+ ,266
+ ,262.5
+ ,265.2
+ ,261.3
+ ,253.7
+ ,249.2
+ ,239.1
+ ,236.4
+ ,235.2
+ ,245.2
+ ,246.2
+ ,247.7
+ ,251.4
+ ,253.3
+ ,254.8
+ ,250
+ ,249.3
+ ,241.5
+ ,243.3
+ ,248
+ ,253
+ ,252.9
+ ,251.5
+ ,251.6
+ ,253.5
+ ,259.8
+ ,334.1
+ ,448
+ ,445.8
+ ,445
+ ,448.2
+ ,438.2
+ ,439.8
+ ,423.4
+ ,410.8
+ ,408.4
+ ,406.7
+ ,405.9
+ ,402.7
+ ,405.1
+ ,399.6
+ ,386.5
+ ,381.4
+ ,375.2
+ ,357.7
+ ,359
+ ,355
+ ,352.7
+ ,344.4
+ ,343.8
+ ,338
+ ,339
+ ,333.3
+ ,334.4
+ ,328.3
+ ,330.7
+ ,330
+ ,331.6
+ ,351.2
+ ,389.4
+ ,410.9
+ ,442.8
+ ,462.8
+ ,466.9
+ ,461.7
+ ,439.2
+ ,430.3
+ ,416.1
+ ,402.5
+ ,397.3
+ ,403.3
+ ,395.9
+ ,387.8
+ ,378.6
+ ,377.1
+ ,370.4
+ ,362
+ ,350.3
+ ,348.2
+ ,344.6
+ ,343.5
+ ,342.8
+ ,347.6
+ ,346.6
+ ,349.5
+ ,342.1
+ ,342
+ ,342.8
+ ,339.3
+ ,348.2
+ ,333.7
+ ,334.7
+ ,354
+ ,367.7
+ ,363.3
+ ,358.4
+ ,353.1
+ ,343.1
+ ,344.6
+ ,344.4
+ ,333.9
+ ,331.7
+ ,324.3
+ ,321.2
+ ,322.4
+ ,321.7
+ ,320.5
+ ,312.8
+ ,309.7
+ ,315.6
+ ,309.7
+ ,304.6
+ ,302.5
+ ,301.5
+ ,298.8
+ ,291.3
+ ,293.6
+ ,294.6
+ ,285.9
+ ,297.6
+ ,301.1
+ ,293.8
+ ,297.7
+ ,292.9
+ ,292.1
+ ,287.2
+ ,288.2
+ ,283.8
+ ,299.9
+ ,292.4
+ ,293.3
+ ,300.8
+ ,293.7
+ ,293.1
+ ,294.4
+ ,292.1
+ ,291.9
+ ,282.5
+ ,277.9
+ ,287.5
+ ,289.2
+ ,285.6
+ ,293.2
+ ,290.8
+ ,283.1
+ ,275
+ ,287.8
+ ,287.8
+ ,287.4
+ ,284
+ ,277.8
+ ,277.6
+ ,304.9
+ ,294
+ ,300.9
+ ,324
+ ,332.9
+ ,341.6
+ ,333.4
+ ,348.2
+ ,344.7
+ ,344.7
+ ,329.3
+ ,323.5
+ ,323.2
+ ,317.4
+ ,330.1
+ ,329.2
+ ,334.9
+ ,315.8
+ ,315.4
+ ,319.6
+ ,317.3
+ ,313.8
+ ,315.8)
> par9 = '0'
> par8 = '0'
> par7 = '0'
> par6 = '3'
> 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]
[1,] 0.4724421 -0.09315870 0.07870417
[2,] 0.4669039 -0.05750058 0.00000000
[3,] 0.4419165  0.00000000 0.00000000
[4,]        NA          NA         NA
[5,]        NA          NA         NA
[6,]        NA          NA         NA

[[2]]
     [,1]    [,2]   [,3]
[1,]    0 0.11009 0.1425
[2,]    0 0.27884     NA
[3,]    0      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     ar3
      0.4724  -0.0932  0.0787
s.e.  0.0528   0.0582  0.0535

sigma^2 estimated as 111.8:  log likelihood = -1352.47,  aic = 2712.94

[[3]][[2]]

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

Coefficients:
         ar1      ar2     ar3
      0.4724  -0.0932  0.0787
s.e.  0.0528   0.0582  0.0535

sigma^2 estimated as 111.8:  log likelihood = -1352.47,  aic = 2712.94

[[3]][[3]]

Call:
arima(x = series, order = order, seasonal = seasonal, include.mean = include.mean, 
    fixed = last.arma$next.vector, method = "ML")

Coefficients:
         ar1      ar2  ar3
      0.4669  -0.0575    0
s.e.  0.0529   0.0530    0

sigma^2 estimated as 112.5:  log likelihood = -1353.55,  aic = 2713.09


$aic
[1] 2712.938 2713.091 2712.265

Warning messages:
1: In arima(series, order = order, seasonal = seasonal, include.mean = include.mean,  :
  some AR parameters were fixed: setting transform.pars = FALSE
2: 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/173np1260449087.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 = 359 
Frequency = 1 
  [1]   0.25499984  22.57324683   8.55961479  31.55100838  17.78343943
  [6]   5.21813737 -11.29872442  -4.38255224  -3.24547349  -3.59637920
 [11]  -9.07894978  -0.24041873  -3.79241620  -1.29009141  -1.24114931
 [16] -10.99305203   0.05334489  -6.76872605  -1.69512987 -12.87322409
 [21]  -1.75363551  -1.33476612   0.67137216  -1.33278906  -3.65139472
 [26]  -2.17856424  -5.33294663  -0.46742530  -0.66834051   5.38586533
 [31]  19.69630073  16.59836766  -0.35463014   1.38695360   2.63317729
 [36]   0.27406620 -12.58655525  11.27115716 -10.29891852  -1.70966971
 [41]   4.07208645  -3.53856079   8.08888005  -6.45388800  -9.15584403
 [46]  -0.94230926 -11.67777354  -3.69598005   0.48214992 -14.62272290
 [51]   1.59394841  -0.62903774  -1.84237428   2.18169872  -4.06309575
 [56]   0.05072378  -0.34845578   0.72821256  -3.43851207  10.51709260
 [61]  -6.18613664  12.75793215  -4.32620511   0.44191233   0.42317947
 [66]  -2.01620176  -2.03082275   2.55052017  -2.17372670  -1.57158384
 [71]   0.09337808   0.78796215   1.41479755   0.83501372  -0.44929520
 [76]  -4.10137985   1.52580597  -0.84899082  -0.94947714   2.06097456
 [81]  -2.97510655   2.11343937   1.80659486  -3.26306870   5.56518989
 [86]   3.31912172  -4.51496872   2.34344168   0.70659486   2.95052555
 [91]   0.84058722  -1.61931726   1.76483409   0.25277457  -1.44546273
 [96]   1.56534477  -0.53015450   2.05750058  -0.53380773  -0.87176039
[101]  -0.40347668   0.82752263   0.02054761  -5.31132087   1.24515028
[106]   1.36128164  -1.68259495  -7.22315511  23.87859952  73.97334702
[111] -17.60597264 -11.50054045   0.44795806  -1.77007885  -6.03015988
[116] -10.27560362 -13.71655202   6.67505798   3.26672526  -2.37860490
[121]  -2.61285560  -6.48709836  -2.08971125  -7.23959291  -5.73310689
[126]   2.73515246  -2.95653063  -8.37403915   8.25646577   4.02131933
[131] -14.76393249   2.87085008  10.85739506  -4.59398084  -6.05931533
[136]  10.75212530  -5.76891352  -0.21681860   6.79685476  -7.28105483
[141]   3.26419020   0.83253404   3.05139472   1.65870656   2.57196938
[146]   7.16882683  -5.18450177   8.71298010   1.17677987  -1.40413417
[151]   5.88924122  -8.08504219  -4.44521578  -2.90210489 -11.11833102
[156]   9.35819873  -4.36373093   5.92930969  -9.75613971   3.13109138
[161]   5.15463805   1.39090916   6.18382798  -6.07090752   1.50339488
[166]   0.43812922  -8.74495205   3.59743315   0.09800664   2.39023822
[171]  -8.89094982   6.74466127  -6.34346604   0.97356913  -5.75177757
[176]  -5.32663717   0.23116779   2.42833770  -4.13766726  -3.17871643
[181]   6.35138665  -0.28368939  -6.38655525   0.87635319   5.35936406
[186]  -5.85038965   4.61016630  -5.36189246  -5.62382336  -1.17578287
[191]  -8.43593699   1.75697645  -0.52011539  10.40503308  -3.73803935
[196]   1.60810190   3.05714478   0.25870656   0.82563479  -5.39110470
[201]   1.62738942  -7.74917006   5.40159975   3.41106854   2.90905287
[206]  -2.16426662  -1.06580673   0.74791535   1.77280881   5.41863271
[211]  71.46775674  79.57129639 -51.10805746   6.77650423   3.44702182
[216] -11.54009283   6.45304051 -17.72205196  -4.85077567   2.53997925
[221]  -1.30393799  -0.14426481  -2.92422789   3.84809191  -6.80457112
[226] -10.39402735   0.70018747  -4.57204784 -14.89844897   9.11431408
[231]  -5.61323512  -0.35763379  -7.45612342   3.14305076  -5.99711247
[236]   3.67354208  -6.50040721   3.81885261  -6.94134754   5.31136422
[241]  -2.17132280   2.06483409  18.81270341  29.14068515   4.79128363
[246]  24.05808892   6.34202908  -3.40380891  -5.96429431 -19.83634753
[251]   1.30633398 -11.33831858  -7.48172024   0.33338438   7.64589226
[256] -10.50042620  -4.29990793  -5.84358296   2.32976089  -6.52864951
[261]  -5.35799496  -8.16326139   2.87977039  -3.29225863   0.46010271
[266]  -0.39340782   5.06358207  -3.28138896   3.64290664  -8.81152179
[271]   3.52184028   0.42118612  -3.87927315  10.58016399 -18.85669643
[276]   8.28186119  17.99933777   4.74625596  -9.68682183  -2.05786508
[281]  -3.26517360  -7.80716234   5.86428560  -1.47536157 -10.32036836
[286]   2.69099048  -6.97656755   0.22858734   2.22189771  -1.43853643
[291]  -0.80416660  -7.17996576   0.42615908   6.90464754  -8.83298460
[296]  -2.00601379  -0.05804369  -0.31275482  -2.35384735  -6.29686014
[301]   5.64652744  -0.50513322  -9.03465254  15.81956421  -2.46303025
[306]  -8.26140678   7.50965024  -7.04067929   1.66539081  -4.80247968
[311]   3.24182848  -5.14865669  18.21187759 -15.27015478   5.32753828
[316]   6.64853219 -10.55002848   3.14627178   1.17188822  -2.94147537
[321]   0.94862964  -9.43887055  -0.22260378  11.20725236  -3.04677977
[326]  -3.84173103   9.37860490  -6.15547146  -6.14242634  -4.64284162
[331]  16.13916687  -6.44212416   0.33600739  -3.21323845  -4.63552709
[336]   2.49930201  27.03687720 -23.65797566  13.55901789  19.25160704
[341]  -1.48872532   5.87281892 -11.75030850  19.12886672 -10.88168195
[346]   2.48517207 -15.60125202   1.39031954   1.52253354  -5.99343219
[351]  15.39079225  -7.16318244   6.85047081 -21.81310256   8.84561713
[356]   3.28850053  -4.28399647  -2.18461868   3.50191220
> postscript(file="/var/www/html/rcomp/tmp/2v84r1260449087.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/35ilp1260449087.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/4uzmc1260449087.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/5rymg1260449087.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/6xacp1260449087.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/7vbdk1260449087.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/8wztr1260449087.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/9btu51260449087.tab") 
> 
> system("convert tmp/173np1260449087.ps tmp/173np1260449087.png")
> system("convert tmp/2v84r1260449087.ps tmp/2v84r1260449087.png")
> system("convert tmp/35ilp1260449087.ps tmp/35ilp1260449087.png")
> system("convert tmp/4uzmc1260449087.ps tmp/4uzmc1260449087.png")
> system("convert tmp/5rymg1260449087.ps tmp/5rymg1260449087.png")
> system("convert tmp/6xacp1260449087.ps tmp/6xacp1260449087.png")
> system("convert tmp/7vbdk1260449087.ps tmp/7vbdk1260449087.png")
> 
> 
> proc.time()
   user  system elapsed 
  1.836   1.100   3.129