R version 2.13.0 (2011-04-13)
Copyright (C) 2011 The R Foundation for Statistical Computing
ISBN 3-900051-07-0
Platform: i486-pc-linux-gnu (32-bit)

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> x <- c(95870,95523,95208,94541,101097,100781,95870,92581,92928,92928,93244,93910,93559,96190,97172,96190,99799,97488,92261,90964,90964,91599,89004,90964,89319,90964,93559,94541,96852,95870,89981,87670,86692,87670,86057,86692,84728,88021,89635,89981,96190,96190,88021,86057,86057,87039,82764,80799,78524,79186,82133,79821,86057,87039,80799,78524,77221,78524,74910,73613,68390,69688,70004,70355,76559,75893,68390,65097,63799,65444,59208,54964,47115,47777,47777,47115,52684,53004,46448,45151,42524,46133,39577,35653,28146,29764,27800,28462,33373,34355,31093,30742,30742,35017,27484,22573,14058,20929,19946,20293,28146,27164,23555,25204,25204,31093,24222,20293,14058,22258,21595,21911,28782,28146,25835,26186,27800,31409,25835,21275)
> par8 = ''
> par7 = '0.95'
> par6 = 'White Noise'
> par5 = '12'
> par4 = '0'
> par3 = '0'
> par2 = '1'
> par1 = '48'
> par8 <- ''
> par7 <- '0.95'
> par6 <- 'White Noise'
> par5 <- '12'
> par4 <- '0'
> par3 <- '0'
> par2 <- '1'
> par1 <- '48'
> #'GNU S' R Code compiled by R2WASP v. 1.2.291 ()
> #Author: root
> #To cite this work: Wessa P., (2012), (Partial) Autocorrelation Function (v1.0.11) in Free Statistics Software (v$_version), Office for Research Development and Education, URL http://www.wessa.net/rwasp_autocorrelation.wasp/
> #Source of accompanying publication: 
> #
> 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/1lftg1344776991.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/2blo11344776991.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/36e9i1344776991.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  0.97755783  0.95635629  0.93892625  0.92222184  0.90223905
 [7]  0.88172667  0.86473680  0.84965403  0.83175535  0.81611035  0.80182494
[13]  0.78238254  0.75241037  0.72263198  0.69637423  0.66955666  0.64049784
[19]  0.61027107  0.58433379  0.56048067  0.53434091  0.51013734  0.48886582
[25]  0.46251190  0.42952611  0.39771733  0.36905831  0.33964630  0.30798905
[31]  0.27475736  0.24579321  0.21890556  0.19199500  0.16634737  0.14436682
[37]  0.12054230  0.09194283  0.06391024  0.03890988  0.01320700 -0.01533187
[43] -0.04593270 -0.07021457 -0.09214140 -0.11484369 -0.13594915 -0.15320058
[49] -0.17051573
> (mypacf <- c(rpacf$acf))
 [1]  0.977557831  0.016605851  0.074922387  0.012155380 -0.074826093
 [6] -0.023515889  0.057612734  0.034289869 -0.054417349  0.049408118
[11]  0.009421869 -0.126688741 -0.246924672 -0.050051110  0.016769347
[16] -0.017790712 -0.020275576 -0.058049562  0.026760455  0.020562523
[21] -0.041023584  0.015408200  0.048923506 -0.078666551 -0.116580194
[26] -0.017615867 -0.001902874 -0.018084635 -0.015035024 -0.074601033
[31] -0.004410207  0.011733929  0.009037106 -0.013162622  0.056995361
[36]  0.006238025 -0.076344514 -0.030971965 -0.002748736 -0.020643411
[41] -0.024778751 -0.071780947  0.036626318  0.011982060 -0.014054890
[46] -0.015049087  0.032006651  0.018682167
> 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/4xkm91344776991.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/5o8do1344776991.tab") 
> 
> try(system("convert tmp/1lftg1344776991.ps tmp/1lftg1344776991.png",intern=TRUE))
character(0)
> try(system("convert tmp/2blo11344776991.ps tmp/2blo11344776991.png",intern=TRUE))
character(0)
> try(system("convert tmp/36e9i1344776991.ps tmp/36e9i1344776991.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  1.220   0.256   1.469