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 = '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/1sr4a1394703894.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/29fvd1394703894.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/31yfe1394703894.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 -0.286521594 -0.174483156 -0.175059715  0.067250343
 [6]  0.127799261 -0.013661538  0.059350033 -0.031083668  0.017885111
[11] -0.299015832  0.032502627  0.416552366 -0.045327566 -0.168537695
[16] -0.140215703  0.084142271  0.053648772 -0.005234045  0.072238209
[21] -0.062766417  0.064101877 -0.329165409  0.162626143  0.148435048
[26]  0.078436855 -0.191612729  0.028356287 -0.019001046 -0.030684757
[31]  0.057367711  0.012432409  0.129894696 -0.155095773 -0.163072176
[36]  0.059975817  0.193519585  0.029990174 -0.158954218  0.010342976
[41]  0.019290120 -0.007356124  0.075225915 -0.045649616  0.052154362
[46] -0.041078722 -0.082485524  0.013585294  0.139147588
> (mypacf <- c(rpacf$acf))
 [1] -0.28652159 -0.27952531 -0.37712457 -0.27049158 -0.13690163 -0.14610820
 [7]  0.03195006  0.09184092  0.18051582 -0.23549658 -0.32256051  0.16482463
[13]  0.09375967  0.00479615  0.04806790  0.06311262 -0.04939658 -0.13341039
[19]  0.04221367 -0.09126073  0.02052606 -0.16445368 -0.01991065 -0.12833174
[25] -0.06078868 -0.11154266  0.16002248  0.02304182 -0.06141114 -0.05217666
[31] -0.05546056  0.02729641 -0.10259399 -0.06828667 -0.08028390 -0.05042214
[37] -0.02883415 -0.08271195 -0.10493846 -0.04475348  0.01106525  0.14780623
[43]  0.03070605 -0.18334200  0.04132130  0.02708119  0.05488202 -0.01450239
> 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/40opu1394703894.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/565ak1394703894.tab") 
> 
> try(system("convert tmp/1sr4a1394703894.ps tmp/1sr4a1394703894.png",intern=TRUE))
character(0)
> try(system("convert tmp/29fvd1394703894.ps tmp/29fvd1394703894.png",intern=TRUE))
character(0)
> try(system("convert tmp/31yfe1394703894.ps tmp/31yfe1394703894.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  2.416   0.472   2.886