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)

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> x <- c(178421,139871,118159,109763,97415,119190,97903,96953,87888,84637,90549,95680,99371,79984,86752,85733,84906,78356,108895,101768,73285,65724,67457,67203,69273,80807,75129,74991,68157,73858,71349,85634,91624,116014,120033,108651,105378,138939,132974,135277,152741,158417,157460,193997,154089,147570,162924,153629,155907,197675,250708,266652,209842,165826,137152,150581,145973,126532,115437,119526,110856,97243,103876,116370,109616,98365,90440,88899,92358,88394,98219,113546,107168,77540,74944,75641,75910,87384,84615,80420,80784,79933,82118,91420,112426,114528,131025,116460,111258,155318,155078,134794,139985,198778,172436,169585,203702,282392,220658,194472,269246,215340,218319,195724,174614,172085,152347,189615,173804,145683,133550,121156,112040,120767,127019,136295,113425,107815,100298,97048,98750,98235,101254,139589,134921,80355,80396,82183,79709,90781)
> par8 = ''
> par7 = '0.95'
> par6 = 'White Noise'
> par5 = '4'
> par4 = '0'
> par3 = '1'
> par2 = '1'
> par1 = 'Default'
> 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/1hw9y1354564657.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/2tw4c1354564657.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/33loy1354564657.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$acf))
 [1]  1.000000000 -0.044924086 -0.255508007  0.082913775  0.052501502
 [6] -0.068975255 -0.092465571  0.222991855  0.086506794 -0.084349562
[11] -0.002024575 -0.006141110 -0.049895329  0.036293434  0.026542340
[16] -0.055268162 -0.008131226 -0.055853112  0.038861007 -0.025323984
[21] -0.076075816  0.019733997
> (mypacf <- c(rpacf$acf))
 [1] -0.044924086 -0.258046964  0.061061832 -0.006925354 -0.032740217
 [6] -0.096902356  0.203999648  0.069455234  0.041964225  0.005053205
[11] -0.038768341 -0.050045457  0.064977617 -0.024042635 -0.070368703
[16] -0.020257638 -0.100489354  0.050701305 -0.028392418 -0.073703527
[21] -0.029980105
> 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/43q3b1354564657.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/5knmw1354564657.tab") 
> 
> try(system("convert tmp/1hw9y1354564657.ps tmp/1hw9y1354564657.png",intern=TRUE))
character(0)
> try(system("convert tmp/2tw4c1354564657.ps tmp/2tw4c1354564657.png",intern=TRUE))
character(0)
> try(system("convert tmp/33loy1354564657.ps tmp/33loy1354564657.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  1.712   0.360   2.056