R version 3.0.2 (2013-09-25) -- "Frisbee Sailing"
Copyright (C) 2013 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu (64-bit)

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> x <- c(164.88,164.88,164.57,164.53,165.03,165.92,165.92,165.92,165.92,166.12,166.34,165.48,165.61,165.61,165.94,165.88,166.23,166.32,166.43,166.43,166.2,166.21,168.02,168.68,168.65,168.65,168.75,168.8,168.58,168.98,169,169,168.94,169.96,171.59,172.41,172.65,172.65,172.65,172.38,171.95,171.95,171.87,171.87,171.91,171.99,172.15,172.73,173.2,164.97,164.97,164.43,163.16,162.98,161.69,162.19,162,162.22,164.08,164.58,164.68)
> 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/1hwbi1413639929.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/2lxd81413639929.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/3h68i1413639929.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  0.921861709  0.838986995  0.749218547  0.637136553
 [6]  0.528399858  0.411692627  0.306746688  0.207906689  0.112743733
[11]  0.040841435 -0.027846380 -0.104292704 -0.153543878 -0.208498115
[16] -0.257546620 -0.287271891 -0.301349791 -0.315587810 -0.325182952
[21] -0.330606063 -0.328712439 -0.327341042 -0.317285815 -0.303654442
[26] -0.296994169 -0.297863604 -0.296380086 -0.278229453 -0.266334445
[31] -0.257481930 -0.246910789 -0.234195893 -0.219612991 -0.196541482
[36] -0.167354506 -0.132068783 -0.099769878 -0.066463134 -0.045710797
[41] -0.031366042 -0.016421273 -0.002941826  0.008969558  0.017790138
[46]  0.037609251  0.062537109  0.088607253  0.116158579
> (mypacf <- c(rpacf$acf))
 [1]  0.921861709 -0.072197806 -0.090335051 -0.199642915 -0.040102296
 [6] -0.119064953  0.018822352 -0.044709959 -0.046107550  0.050931759
[11] -0.058695773 -0.153082478  0.073356125 -0.115489629 -0.037048754
[16]  0.033145117  0.071453365 -0.109868745 -0.017698622 -0.067443928
[21] -0.022319304 -0.035986957  0.030955791 -0.059157556 -0.034083846
[26] -0.127550140 -0.043897072  0.083480692 -0.039168934 -0.095507617
[31] -0.025525829 -0.009147462 -0.030616094  0.016741344  0.021849405
[36]  0.013156718 -0.019722668 -0.032278837 -0.132426242 -0.026265999
[41] -0.041144422 -0.004938441  0.024049133  0.004742991  0.023195873
[46]  0.027677532 -0.003616335 -0.013178569
> 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/4fkcd1413639929.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/5r7zz1413639929.tab") 
> 
> try(system("convert tmp/1hwbi1413639929.ps tmp/1hwbi1413639929.png",intern=TRUE))
character(0)
> try(system("convert tmp/2lxd81413639929.ps tmp/2lxd81413639929.png",intern=TRUE))
character(0)
> try(system("convert tmp/3h68i1413639929.ps tmp/3h68i1413639929.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  1.146   0.188   1.349