R version 3.0.1 (2013-05-16) -- "Good Sport"
Copyright (C) 2013 The R Foundation for Statistical Computing
Platform: i686-pc-linux-gnu (32-bit)

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> x <- c(20.5,20.2,19.4,19.2,18.8,18.8,22.6,23.3,23,21.4,19.9,18.8,18.6,18.4,18.6,19.9,19.2,18.4,21.1,20.5,19.1,18.1,17,17.1,17.4,16.8,15.3,14.3,13.4,15.3,22.1,23.7,22.2,19.5,16.6,17.3,19.8,21.2,21.5,20.6,19.1,19.6,23.4,24.3,24.1,22.8,22.5,23.8,24.9,25.2,24.3,22.8,20.7,19.8,22.5,22.6,22.5,21.8,21.2,20.6,19.9,18.7,17.6,16.4,15.9,16.8,22.8,24,22.2,17.9,16,16)
> par8 = ''
> par7 = '0.95'
> par6 = 'White Noise'
> par5 = '12'
> par4 = '0'
> par3 = '1'
> par2 = '1'
> par1 = '48'
> if (par1 == 'Default') {
+ par1 = 10*log10(length(x))
+ } else {
+ par1 <- as.numeric(par1)
+ }
> par2 <- as.numeric(par2)
> par3 <- as.numeric(par3)
> par4 <- as.numeric(par4)
> par5 <- as.numeric(par5)
> if (par6 == 'White Noise') par6 <- 'white' else par6 <- 'ma'
> par7 <- as.numeric(par7)
> if (par8 != '') par8 <- as.numeric(par8)
> ox <- x
> if (par8 == '') {
+ if (par2 == 0) {
+ x <- log(x)
+ } else {
+ x <- (x ^ par2 - 1) / par2
+ }
+ } else {
+ x <- log(x,base=par8)
+ }
> if (par3 > 0) x <- diff(x,lag=1,difference=par3)
> if (par4 > 0) x <- diff(x,lag=par5,difference=par4)
> postscript(file="/var/wessaorg/rcomp/tmp/1ykic1369610908.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> op <- par(mfrow=c(2,1))
> plot(ox,type='l',main='Original Time Series',xlab='time',ylab='value')
> if (par8=='') {
+ mytitle <- paste('Working Time Series (lambda=',par2,', d=',par3,', D=',par4,')',sep='')
+ mysub <- paste('(lambda=',par2,', d=',par3,', D=',par4,', CI=', par7, ', CI type=',par6,')',sep='')
+ } else {
+ mytitle <- paste('Working Time Series (base=',par8,', d=',par3,', D=',par4,')',sep='')
+ mysub <- paste('(base=',par8,', d=',par3,', D=',par4,', CI=', par7, ', CI type=',par6,')',sep='')
+ }
> plot(x,type='l', main=mytitle,xlab='time',ylab='value')
> par(op)
> dev.off()
null device 
          1 
> postscript(file="/var/wessaorg/rcomp/tmp/2h4kv1369610908.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> racf <- acf(x, par1, main='Autocorrelation', xlab='time lag', ylab='ACF', ci.type=par6, ci=par7, sub=mysub)
> dev.off()
null device 
          1 
> postscript(file="/var/wessaorg/rcomp/tmp/3x6gz1369610908.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> rpacf <- pacf(x,par1,main='Partial Autocorrelation',xlab='lags',ylab='PACF',sub=mysub)
> dev.off()
null device 
          1 
> (myacf <- c(racf$acf))
 [1]  1.00000000  0.38398752 -0.23271530 -0.49247727 -0.37964439  0.02288293
 [7]  0.28673773  0.17508539 -0.07809389 -0.20426769 -0.17112115  0.13373367
[13]  0.49032010  0.08178772 -0.22239771 -0.26407609 -0.13947579  0.15221181
[19]  0.25410617  0.07313512 -0.18616066 -0.29129867 -0.19373734  0.13472378
[25]  0.44624874  0.10463638 -0.17200817 -0.23570706 -0.11906892  0.12385786
[31]  0.19278581  0.02913766 -0.18797138 -0.25507031 -0.13548046  0.15866679
[37]  0.40470047  0.12850548 -0.11394343 -0.20460987 -0.12089442  0.04632064
[43]  0.09705920  0.05044241 -0.04703827 -0.10540278 -0.08926815  0.01419106
[49]  0.16065608
> (mypacf <- c(rpacf$acf))
 [1]  0.383987525 -0.445909480 -0.281167447 -0.202589474  0.042161376
 [6] -0.010853403 -0.149157622 -0.122982135 -0.062472540 -0.119138953
[11]  0.150156754  0.392101537 -0.442780422  0.193301546  0.146304106
[16] -0.028450105  0.056571069  0.027959444  0.003994588 -0.187247432
[21] -0.116986835  0.032973114 -0.063813766 -0.033080411 -0.095892374
[26] -0.020833023 -0.037919286  0.060795307 -0.052309329 -0.009248723
[31] -0.056821448 -0.091011834 -0.057303399 -0.056996874 -0.012007165
[36]  0.005552280  0.038368217  0.045388097  0.001815203  0.059515602
[41] -0.079447704 -0.047566861  0.102240716  0.037986974 -0.072930776
[46] -0.061409996 -0.139294743 -0.083956302
> lengthx <- length(x)
> sqrtn <- sqrt(lengthx)
> 
> #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,'Autocorrelation Function',4,TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'Time lag k',header=TRUE)
> a<-table.element(a,hyperlink('http://www.xycoon.com/basics.htm','ACF(k)','click here for more information about the Autocorrelation Function'),header=TRUE)
> a<-table.element(a,'T-STAT',header=TRUE)
> a<-table.element(a,'P-value',header=TRUE)
> a<-table.row.end(a)
> for (i in 2:(par1+1)) {
+ a<-table.row.start(a)
+ a<-table.element(a,i-1,header=TRUE)
+ a<-table.element(a,round(myacf[i],6))
+ mytstat <- myacf[i]*sqrtn
+ a<-table.element(a,round(mytstat,4))
+ a<-table.element(a,round(1-pt(abs(mytstat),lengthx),6))
+ a<-table.row.end(a)
+ }
> a<-table.end(a)
> table.save(a,file="/var/wessaorg/rcomp/tmp/47nwh1369610908.tab") 
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,'Partial Autocorrelation Function',4,TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'Time lag k',header=TRUE)
> a<-table.element(a,hyperlink('http://www.xycoon.com/basics.htm','PACF(k)','click here for more information about the Partial Autocorrelation Function'),header=TRUE)
> a<-table.element(a,'T-STAT',header=TRUE)
> a<-table.element(a,'P-value',header=TRUE)
> a<-table.row.end(a)
> for (i in 1:par1) {
+ a<-table.row.start(a)
+ a<-table.element(a,i,header=TRUE)
+ a<-table.element(a,round(mypacf[i],6))
+ mytstat <- mypacf[i]*sqrtn
+ a<-table.element(a,round(mytstat,4))
+ a<-table.element(a,round(1-pt(abs(mytstat),lengthx),6))
+ a<-table.row.end(a)
+ }
> a<-table.end(a)
> table.save(a,file="/var/wessaorg/rcomp/tmp/5u8ub1369610908.tab") 
> 
> try(system("convert tmp/1ykic1369610908.ps tmp/1ykic1369610908.png",intern=TRUE))
character(0)
> try(system("convert tmp/2h4kv1369610908.ps tmp/2h4kv1369610908.png",intern=TRUE))
character(0)
> try(system("convert tmp/3x6gz1369610908.ps tmp/3x6gz1369610908.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  2.294   0.510   2.781