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(45.3,49.9,53.8,55.1,52.9,53.5,53.8,52,48.2,45.5,45.7,52.5,52.3,54.8,54.7,54.9,54.9,64.2,66.4,69.1,68.3,77.3,89.6,93,96.1,131.3,125.3,126,138.3,163,182.5,164.6,148.8,109.3,93.5,80.2,84,75.5,62.4,64.2,64.7,71,73.7,72.6,68.1,72.3,78.5,81.9,97.8,93.1,94.2,101.1,101,99.7,97.1,91.7,95,98.9,109,121.9,131.5,128.5,128.4,126.4,123.1,123,123.3,123.6,124.9,120.4,114.9,113.4)
> 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/1d0f41354102123.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/273qo1354102123.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/39llw1354102123.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  0.940218620  0.848475322  0.740747812  0.632407670
 [6]  0.522127715  0.408171176  0.296796774  0.184741733  0.087442760
[11]  0.003572767 -0.064387820 -0.129321933 -0.188883718 -0.226830812
[16] -0.251561061 -0.260288972 -0.261145793 -0.257857999 -0.258344254
[21] -0.260484678 -0.261868338 -0.253150135 -0.234096685 -0.221770849
[26] -0.199819694 -0.146691811 -0.091649285 -0.030770401  0.032330221
[31]  0.099904446  0.171832004  0.228217697  0.276109524  0.300277251
[36]  0.306389140  0.295343026  0.284448301  0.257246149  0.213123505
[41]  0.158063566  0.099895475  0.041634099 -0.008113273 -0.052161747
[46] -0.092948348 -0.130193271 -0.166402709 -0.190857944
> (mypacf <- c(rpacf$acf))
 [1]  9.402186e-01 -3.063717e-01 -1.270847e-01 -1.547038e-02 -8.681666e-02
 [6] -1.072504e-01 -3.825728e-02 -1.036009e-01  4.656747e-02 -1.459233e-02
[11]  2.790353e-05 -1.126531e-01 -4.282479e-02  1.095457e-01 -3.789556e-02
[16]  1.340774e-02 -1.648931e-02 -4.766847e-02 -8.308733e-02 -4.444973e-02
[21] -4.861764e-02  6.980881e-02  3.969819e-02 -1.099893e-01  9.836583e-02
[26]  2.953791e-01 -1.443483e-01  4.511453e-02  1.000054e-01  5.568495e-02
[31]  9.844494e-02 -1.513641e-01 -3.408303e-03 -9.751334e-02 -1.908806e-02
[36] -1.486130e-02  3.938029e-02 -1.072061e-01  1.833799e-02 -6.312954e-02
[41]  5.890004e-02 -4.785427e-02  9.482307e-02 -3.952326e-02 -4.556030e-02
[46] -2.651973e-02 -1.124572e-02  1.425132e-02
> 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/4clmx1354102123.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/5kxl41354102123.tab") 
> 
> try(system("convert tmp/1d0f41354102123.ps tmp/1d0f41354102123.png",intern=TRUE))
character(0)
> try(system("convert tmp/273qo1354102123.ps tmp/273qo1354102123.png",intern=TRUE))
character(0)
> try(system("convert tmp/39llw1354102123.ps tmp/39llw1354102123.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  1.785   0.372   2.136