R version 2.15.3 (2013-03-01) -- "Security Blanket"
Copyright (C) 2013 The R Foundation for Statistical Computing
ISBN 3-900051-07-0
Platform: i686-pc-linux-gnu (32-bit)

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> x <- c(105.28,107,106.29,108.07,105.41,104.4,102.77,102.44,103.43,102.95,103.52,105.2,105.88,104.88,106.59,107.8,106.31,106.53,106.25,105.87,107.83,108.01,107.9,108.55,108.83,109.39,108.65,108.33,109.76,110.07,109.23,108.4,108.9,109.14,109.27,109.38,109.66,109.87,109.98,111.24,110.03,111.43,110.28,109.53,111.97,111.89,112.93,113.11,112.95,114.08,115.27,114.73,114.97,113.78,113.7,113.91,114.22,115.32,113.5,115.35,113.23,113.65,114.82,113.54,113.97,113.79,113.27,114.35,113.68,115.3,113.69,115.31)
> 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/16lr31363704848.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/2eqnu1363704848.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/3xd6e1363704848.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  0.93122100  0.90855998  0.86311439  0.83158659  0.79971393
 [7]  0.75564620  0.71105491  0.66321617  0.62384923  0.57732815  0.53097556
[13]  0.50049483  0.44842159  0.39719848  0.35011342  0.31497158  0.28324898
[19]  0.25038178  0.20729642  0.16845144  0.13801496  0.09816535  0.06473060
[25]  0.03804318  0.00950957 -0.02100995 -0.04920797 -0.08984679 -0.10497399
[31] -0.12123605 -0.15592691 -0.18009129 -0.20896757 -0.22967557 -0.25373611
[37] -0.27481093 -0.30406168 -0.32807649 -0.35406050 -0.37340514 -0.38403433
[43] -0.39412449 -0.41336563 -0.43110325 -0.43199819 -0.43278015 -0.42652748
[49] -0.42744820
> (mypacf <- c(rpacf$acf))
 [1]  0.931220995  0.311587945 -0.079109375  0.012543922  0.035971288
 [6] -0.115946629 -0.094912482 -0.051439669  0.022108635 -0.054847010
[11] -0.060326246  0.122327119 -0.115862481 -0.161515283  0.020617620
[16]  0.110546267  0.016985730 -0.024090388 -0.074338519 -0.021430521
[21]  0.009661129 -0.105551529 -0.010439086  0.072766688 -0.016283983
[26] -0.060406221  0.008326395 -0.141029644  0.068110479  0.080852614
[31] -0.168309999 -0.003656473 -0.006534452 -0.037872374 -0.039158749
[36] -0.033178851 -0.081062709 -0.020618873 -0.074607942  0.095535309
[41]  0.081094867 -0.113660734 -0.086320931  0.025470721  0.121910761
[46]  0.012296214 -0.024682430 -0.043581337
> 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/4xb991363704848.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/578xx1363704848.tab") 
> 
> try(system("convert tmp/16lr31363704848.ps tmp/16lr31363704848.png",intern=TRUE))
character(0)
> try(system("convert tmp/2eqnu1363704848.ps tmp/2eqnu1363704848.png",intern=TRUE))
character(0)
> try(system("convert tmp/3xd6e1363704848.ps tmp/3xd6e1363704848.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  1.797   0.298   2.089