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)

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> x <- c(86.5,86.6,98.8,84.4,91.4,95.7,78.5,81.7,94.3,98.5,95.4,91.7,92.8,90.6,102.2,91.8,95,102,88.9,89.6,97.9,108.6,100.8,95.1,101,100.9,102.5,105.4,98.4,105.3,96.5,88.1,107.9,107.1,92.5,95.7,85.2,85.5,94.7,86.2,88.8,93.4,83.4,82.9,96.7,96.2,92.8,92.8,90.2,95.9,107.5,98,95,108.5,91.8,91.7,108.3,105.1,104.8,103.2,98.6,102.4,121.2,102.6,108.9,105.5,90.8,99.6,111.6,104.7,103.1,101.7,98.8,101.4,114.2,96.9,98.3,104.8,94.4,94.5,102.4,105.5,101.2,99.5)
> par8 = ''
> par7 = '0.95'
> par6 = 'White Noise'
> par5 = '12'
> par4 = '0'
> par3 = '1'
> par2 = '1'
> par1 = '48'
> par8 <- ''
> par7 <- '0.95'
> par6 <- 'White Noise'
> par5 <- '12'
> par4 <- '0'
> par3 <- '1'
> 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/1q2651384333731.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/24jp71384333731.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/3azph1384333731.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 -0.329373182 -0.384067238  0.372065820 -0.225054548
 [6] -0.078706423  0.369778991 -0.162116344 -0.099822751  0.243068671
[11] -0.343421352 -0.124505947  0.614017825 -0.188182015 -0.304257232
[16]  0.215471159 -0.136027536 -0.047432095  0.276318839 -0.147999116
[21] -0.064994998  0.204940001 -0.343927744 -0.013088368  0.456415495
[26] -0.170187840 -0.228770733  0.156619957 -0.110615463  0.013225319
[31]  0.213744188 -0.159752730 -0.002323992  0.135767484 -0.269586989
[36]  0.024484263  0.324257329 -0.130744698 -0.148571991  0.111676667
[41] -0.096604885  0.068371834  0.126290108 -0.125400655 -0.019118336
[46]  0.110306902 -0.177896843 -0.015202378  0.278980646
> (mypacf <- c(rpacf$acf))
 [1] -0.329373182 -0.552491957 -0.010175793 -0.404076297 -0.235168945
 [6]  0.007708082  0.035157556  0.119451831  0.297141722 -0.120714672
[11] -0.392022646  0.161791636  0.199117514  0.077730706 -0.158345936
[16] -0.109907015 -0.096787122 -0.067296649 -0.123399350 -0.103663275
[21]  0.053925776 -0.102290218 -0.037356046 -0.028730564  0.038104468
[26] -0.085964805 -0.071604715 -0.090916094 -0.028768242 -0.014890926
[31] -0.056020570 -0.008558622 -0.032873095  0.040367534 -0.016658274
[36] -0.066161499 -0.100787072 -0.041165592  0.032607460 -0.013796317
[41]  0.061890605 -0.018086473  0.095403304 -0.134675626 -0.047108927
[46] -0.049780757 -0.065712763 -0.020863599
> 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/4xtr01384333731.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/5km3o1384333731.tab") 
> 
> try(system("convert tmp/1q2651384333731.ps tmp/1q2651384333731.png",intern=TRUE))
character(0)
> try(system("convert tmp/24jp71384333731.ps tmp/24jp71384333731.png",intern=TRUE))
character(0)
> try(system("convert tmp/3azph1384333731.ps tmp/3azph1384333731.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  2.206   0.445   2.619