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(110.48,111.41,115.5,118.32,118.42,117.5,110.23,109.19,118.41,118.3,116.1,114.11,113.41,114.33,116.61,123.64,123.77,123.39,116.03,114.95,123.4,123.53,114.45,114.26,114.35,112.77,115.31,114.93,116.38,115.07,105,103.43,114.52,115.04,117.16,115,116.22,112.92,116.56,114.32,113.22,111.56,103.87,102.85,112.27,112.76,118.55,122.73,115.44,116.97,119.84,116.37,117.23,115.58,109.82,108.46,116.54,117.49,122.87,127.1,119.81,120.03,128.58,120.4,121.54,118.71,111.57,109.97,120.29,120.61,130.15,136.12)
> 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/1zb531416063377.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/2ev4f1416063377.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/3qk081416063377.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  0.013479773 -0.253130561  0.043065452 -0.237863775
 [6] -0.126281642  0.330092779 -0.151064039 -0.133030896  0.019158192
[11] -0.297353367  0.029728656  0.628872247  0.079106137 -0.209533918
[16]  0.035330144 -0.230570242 -0.060969714  0.291434798 -0.097852993
[21] -0.097271763  0.038387567 -0.290460396  0.044299769  0.424130789
[26]  0.003695199  0.003097812 -0.067923563 -0.256405141 -0.022113125
[31]  0.233895446 -0.061812114  0.014515854 -0.023129725 -0.181814398
[36]  0.007836151  0.247066796 -0.021599576  0.019563899 -0.014409765
[41] -0.282119676  0.022189243  0.172652767 -0.011690733  0.068803131
[46] -0.002703830 -0.170559950  0.034777867  0.072883477
> (mypacf <- c(rpacf$acf))
 [1]  0.013479773 -0.253358301  0.054248778 -0.326169824 -0.095490013
 [6]  0.208252004 -0.262746720 -0.028670014 -0.196142598 -0.306197403
[11] -0.010690028  0.439934148  0.166644659 -0.167000424  0.028472263
[16] -0.027591185  0.054584154  0.032481490 -0.041412438  0.022261106
[21] -0.014630300  0.012025708  0.058352172 -0.045545222 -0.083304749
[26]  0.220392900 -0.150512363 -0.040339107 -0.100472811  0.050761439
[31]  0.011231733  0.001942874 -0.008863916  0.051490680 -0.047763184
[36] -0.037691141 -0.063412745 -0.130233671  0.075326552 -0.062026951
[41]  0.038780497 -0.090185379  0.048690474  0.035137310 -0.003344502
[46]  0.027902315 -0.102596699 -0.016198867
> 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/4vvcr1416063377.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/55i1u1416063377.tab") 
> 
> try(system("convert tmp/1zb531416063377.ps tmp/1zb531416063377.png",intern=TRUE))
character(0)
> try(system("convert tmp/2ev4f1416063377.ps tmp/2ev4f1416063377.png",intern=TRUE))
character(0)
> try(system("convert tmp/3qk081416063377.ps tmp/3qk081416063377.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  1.208   0.249   1.470