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(102.89,102.64,103.33,103.56,103.6,104.24,105.31,105.4,105.89,105.89,105.54,106.15,106.14,105.85,106.27,106.51,106.82,106.53,107.14,107.39,107.33,107.53,107.42,108.25,108.26,108.93,109.43,109.61,109.74,110.12,110.16,110.44,111.23,112.86,112.77,113.04,112.79,113.87,114.28,115.51,116.76,116.91,116.47,116.94,117.24,116.82,117.48,117.11,117.31,117.77,118.37,117.91,118.12,118.02,117.77,117.85,118.68,118.9,118.6,118.21,118.37,117.43,117.5,116.71,116.98,117.74,117.44,117.85,118.54,118.73,118.68,118.19)
> 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/1zs7z1358204637.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/26pq41358204637.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/3acrk1358204637.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  0.018157447  0.046169937  0.044705831  0.035147803
 [6] -0.085867336  0.108347925  0.134731496  0.081873404  0.046549632
[11]  0.103076289 -0.049051973  0.078013538 -0.025715366 -0.063617925
[16] -0.065372077  0.042285697  0.118075837 -0.039155820  0.023229769
[21] -0.169330325 -0.044864881 -0.210286856 -0.062375602 -0.092002386
[26]  0.048716531 -0.119327815  0.048496832 -0.075958942 -0.034637100
[31] -0.123000698 -0.013977729  0.024033461 -0.014387830  0.005642349
[36]  0.124819552 -0.117249832 -0.004267582 -0.052891561 -0.062589142
[41] -0.076060986  0.082703635  0.047079051 -0.062407687  0.098553381
[46] -0.068829006  0.007605831 -0.025079332 -0.038621080
> (mypacf <- c(rpacf$acf))
 [1]  0.018157447  0.045855363  0.043178325  0.031731365 -0.091341884
 [6]  0.107635381  0.138725139  0.077080148  0.029536604  0.072367584
[11] -0.050232668  0.082279360 -0.046924018 -0.103496852 -0.084336493
[16]  0.004861609  0.136741539 -0.059596399 -0.016800590 -0.200537501
[21]  0.006374043 -0.175667264 -0.058737194 -0.116030962  0.043494936
[26] -0.087554846  0.087296215 -0.018853693 -0.001140172 -0.013005302
[31]  0.020151582  0.174360426 -0.034117884  0.044376418  0.096953516
[36] -0.073087085  0.012807326 -0.060898034 -0.054734732 -0.101268086
[41]  0.059313736 -0.052781948 -0.072272094 -0.050180576 -0.094072636
[46]  0.022752922 -0.006372092 -0.106793059
> 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/4dzkx1358204637.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/51ny41358204637.tab") 
> 
> try(system("convert tmp/1zs7z1358204637.ps tmp/1zs7z1358204637.png",intern=TRUE))
character(0)
> try(system("convert tmp/26pq41358204637.ps tmp/26pq41358204637.png",intern=TRUE))
character(0)
> try(system("convert tmp/3acrk1358204637.ps tmp/3acrk1358204637.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  1.950   0.310   2.277