R version 3.0.3 (2014-03-06) -- "Warm Puppy"
Copyright (C) 2014 The R Foundation for Statistical Computing
Platform: i686-pc-linux-gnu (32-bit)

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> x <- c(107.00,116.14,117.18,102.28,109.43,114.28,117.39,116.66,114.29,114.18,114.12,122.62,115.70,127.91,119.55,115.08,116.63,121.38,123.41,120.70,119.40,116.83,116.40,121.67,116.54,129.61,119.93,117.64,121.01,124.20,125.23,123.24,121.58,120.89,117.77,110.91,124.23,127.70,129.45,120.13,122.02,126.59,126.34,125.15,125.02,124.40,127.55,126.63,130.18,136.95,136.81,129.59,133.37,140.02,139.67,139.99,134.57,134.41,134.99,135.70)
> 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/1ct281394703528.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/2b7tx1394703528.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/32kmp1394703528.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  0.738292953  0.632000608  0.602369989  0.583252695
 [6]  0.543286122  0.466507294  0.403469963  0.330978033  0.271661552
[11]  0.178861994  0.207147017  0.274477711  0.149600780  0.087804848
[16]  0.072212850  0.093831285  0.083979104  0.064985819  0.053917784
[21]  0.014962886  0.001792148 -0.079806176 -0.022625982 -0.003751672
[26] -0.026433670 -0.052163963 -0.046852494 -0.066506547 -0.072078208
[31] -0.060322320 -0.066952406 -0.078195309 -0.141178799 -0.150886527
[36] -0.137945341 -0.139071858 -0.186771673 -0.217928897 -0.177809890
[41] -0.188541484 -0.206139098 -0.213198963 -0.248239739 -0.255593942
[46] -0.281823977 -0.309168690 -0.318317613 -0.300328739
> (mypacf <- c(rpacf$acf))
 [1]  0.738292953  0.191074147  0.191312829  0.131973500  0.046403297
 [6] -0.066514135 -0.054679119 -0.102106257 -0.066792074 -0.145310768
[11]  0.171587632  0.260860327 -0.206465813 -0.044854121 -0.011419461
[16]  0.026013605 -0.018891236  0.017414782  0.027680563 -0.088520554
[21]  0.001664205 -0.120230202  0.083331779 -0.034731871  0.092197799
[26]  0.031923360  0.036222039 -0.148646038 -0.021929628 -0.017742689
[31] -0.020016910 -0.023208373 -0.124636955  0.119323419 -0.082746366
[36]  0.005965283 -0.124872422 -0.021119836  0.107721874  0.037634324
[41] -0.024430904 -0.095249928 -0.178270350 -0.093051759  0.051124825
[46] -0.146449976  0.018837994  0.037159326
> 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/4eudn1394703528.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/5p0wo1394703528.tab") 
> 
> try(system("convert tmp/1ct281394703528.ps tmp/1ct281394703528.png",intern=TRUE))
character(0)
> try(system("convert tmp/2b7tx1394703528.ps tmp/2b7tx1394703528.png",intern=TRUE))
character(0)
> try(system("convert tmp/32kmp1394703528.ps tmp/32kmp1394703528.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  2.272   0.452   2.732