R version 3.2.3 (2015-12-10) -- "Wooden Christmas-Tree"
Copyright (C) 2015 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu (64-bit)

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> x <- c(100.57,100.27,100.27,100.18,100.16,100.18,100.18,100.59,100.69,101.06,101.15,101.16,101.16,100.81,100.94,101.13,101.29,101.34,101.35,101.7,102.05,102.48,102.66,102.72,102.73,102.18,102.22,102.37,102.53,102.61,102.62,103,103.17,103.52,103.69,103.73,99.57,99.09,99.14,99.36,99.6,99.65,99.8,100.15,100.45,100.89,101.13,101.17,101.21,101.1,101.17,101.11,101.2,101.15,100.92,101.1,101.22,101.25,101.39,101.43,101.95,101.92,102.05,102.07,102.1,102.16,101.63,101.43,101.4,101.6,101.72,101.73)
> 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. 1.2.327 (Mon, 30 Nov 2015 06:58:35 +0000)
> #Author: root
> #To cite this work: Wessa P., (2015), (Partial) Autocorrelation Function (v1.0.12) 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)
> x <- na.omit(x)
> 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/1ax971457431160.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/2z4na1457431160.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/3j51z1457431160.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]  1.00000000  0.86301596  0.68375205  0.50585179  0.35691445  0.23146663
 [7]  0.12248163  0.02973699 -0.03828029 -0.07691057 -0.08082944 -0.07581643
[13] -0.10614813 -0.15812035 -0.22940313 -0.29461359 -0.34224511 -0.36486302
[19] -0.37696098 -0.39735602 -0.40502300 -0.39183721 -0.36090982 -0.31684062
[25] -0.29031267 -0.25337846 -0.23128917 -0.20242574 -0.15170225 -0.09142173
[31] -0.01397348  0.03735044  0.08047788  0.12633485  0.18543819  0.25164799
[37]  0.30296881  0.28363733  0.25585835  0.22533996  0.19635869  0.16897796
[43]  0.13576784  0.10417343  0.07584364  0.05458968  0.04284988  0.03556225
[49]  0.03133970
> (mypacf <- c(rpacf$acf))
 [1]  0.863015959 -0.239199317 -0.078774122 -0.002520964 -0.044460179
 [6] -0.057872394 -0.042081403 -0.002912754  0.017052511  0.053563704
[11] -0.029879257 -0.172865360 -0.085896639 -0.122811607 -0.062782375
[16] -0.040234371 -0.010466719 -0.061655491 -0.131677799 -0.044671644
[21] -0.051956577 -0.055156800 -0.020577603 -0.124303531  0.033686119
[26] -0.117239771 -0.032168797  0.012111178 -0.026550010  0.074598977
[31] -0.122127114  0.002051100  0.006815813  0.045112631  0.066389016
[36] -0.028444721 -0.195018053  0.034795452 -0.031003101 -0.064122074
[41] -0.055142616 -0.028532969 -0.033708228 -0.020213856 -0.051763837
[46] -0.073300165 -0.029818488  0.014793612
> 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/4tehe1457431160.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/583qj1457431160.tab") 
> 
> try(system("convert tmp/1ax971457431160.ps tmp/1ax971457431160.png",intern=TRUE))
character(0)
> try(system("convert tmp/2z4na1457431160.ps tmp/2z4na1457431160.png",intern=TRUE))
character(0)
> try(system("convert tmp/3j51z1457431160.ps tmp/3j51z1457431160.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  1.162   0.222   1.395