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(82,80,76,73,70,68,67,64,69,69,67,57,67,69,67,66,65,56,57,53,58,59,60,59,65,62,61,62,57,51,45,46,48,49,48,43,51,54,57,60,58,61,62,62,64,68,70,73,79,84,82,78,78,76,73,71,71,70,74,72,80,80,80,79,82,71,75,74,76,82,85,82,92,93,93,99,98,89,96,94,99,108,113,115,126,131,134,134,137,139,139,134,133,135,130,133)
> 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/1r6t61413552201.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/2kswp1413552201.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/3b9ss1413552201.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  0.006277179  0.129214135  0.151837421  0.058609421
 [6] -0.177612063  0.190352370 -0.269808957  0.034533923  0.022240125
[11] -0.051535461  0.041456935  0.380437270 -0.089146321  0.128754892
[16]  0.070431818 -0.090192720 -0.103586795 -0.029663844 -0.203643680
[21] -0.016617097  0.003866423 -0.040456991  0.069677845  0.211915244
[26]  0.047035490  0.095998562  0.009645774 -0.022057886 -0.045184248
[31] -0.104875069 -0.106986744 -0.062291047  0.043223841 -0.032326778
[36]  0.021396056  0.193663120  0.107760170 -0.042694403  0.027058437
[41]  0.092106223 -0.117957842  0.026784055 -0.098741032 -0.012240880
[46] -0.045901939  0.023808348 -0.053572014  0.248545996
> (mypacf <- c(rpacf$acf))
 [1]  0.006277179  0.129179822  0.152877265  0.045022185 -0.224450343
 [6]  0.162518779 -0.261047950  0.081523459  0.045927969 -0.045596288
[11]  0.147637816  0.282657838 -0.036833479 -0.025169540 -0.047853490
[16] -0.114705231 -0.073123590 -0.125454377  0.038198628 -0.014064306
[21]  0.093273214  0.073630102 -0.011048683  0.112479728  0.045684362
[26] -0.048801508 -0.112652685  0.001377520  0.004184737 -0.070047059
[31]  0.048166016 -0.022140965  0.134979339 -0.014400734 -0.068451463
[36]  0.110471768 -0.001159800 -0.118443239 -0.083808082  0.164856128
[41] -0.036376405  0.150025853 -0.054114921  0.105174825 -0.153597319
[46] -0.012313866 -0.035454465  0.020166262
> 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/4cwrr1413552201.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/5g3a11413552201.tab") 
> 
> try(system("convert tmp/1r6t61413552201.ps tmp/1r6t61413552201.png",intern=TRUE))
character(0)
> try(system("convert tmp/2kswp1413552201.ps tmp/2kswp1413552201.png",intern=TRUE))
character(0)
> try(system("convert tmp/3b9ss1413552201.ps tmp/3b9ss1413552201.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  1.169   0.236   1.410