R version 3.3.1 (2016-06-21) -- "Bug in Your Hair"
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Platform: x86_64-pc-linux-gnu (64-bit)

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> x <- c(98.98,98.97,98.91,98.98,98.95,98.96,98.96,99.04,99.33,100.04,100.14,100.21,100.21,100.27,100.44,100.57,100.51,100.47,100.47,100.49,101,101.61,101.65,101.74,101.74,101.73,101.77,101.82,101.97,102.09,102.09,102.08,102.42,102.78,103.04,103.08,99.16,99.19,99.23,99.31,99.46,99.49,99.95,100.14,100.43,101.1,101.26,101.28,101.04,101.12,101.07,100.97,101.01,100.99,101.19,101.25,101.33,101.79,102.06,102.09,102.27,102.26,102.46,102.46,102.51,102.56,102.59,102.26,102.33,102.84,102.93,102.95)
> 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. 1.2.327 (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/1zfay1476909821.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/20wne1476909821.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/3c1e31476909821.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  0.060467637 -0.036816592 -0.071771017 -0.091808558
 [6]  0.013934054 -0.082761931 -0.052532515 -0.079732893 -0.140382856
[11] -0.025413573  0.062862386  0.155580390  0.030446567  0.034654741
[16] -0.079024090 -0.101782574  0.024284756 -0.024347585  0.020783894
[21]  0.023618637 -0.105272152 -0.071147812  0.026213590  0.043529223
[26]  0.046132210 -0.034006281 -0.135943485 -0.058345085 -0.005203025
[31]  0.014694452  0.093594302  0.011648739 -0.092725433  0.025168881
[36]  0.034137586  0.044990207  0.033078937 -0.004517533 -0.015269114
[41] -0.007769158 -0.007014059 -0.004807086 -0.004790504 -0.006184142
[46]  0.001373049 -0.006907890 -0.004504582  0.030345049
> (mypacf <- c(rpacf$acf))
 [1]  0.060467637 -0.040621453 -0.067355099 -0.085595470  0.019310977
 [6] -0.097526892 -0.054409573 -0.089596772 -0.151502012 -0.049244331
[11]  0.030948696  0.108475587 -0.015974304  0.035742475 -0.093218592
[16] -0.104649538  0.007329920 -0.039820664  0.009499294  0.049825492
[21] -0.082610332 -0.092270104  0.005591340 -0.033203151 -0.017146036
[26] -0.043933559 -0.133865819 -0.064577843 -0.032337784 -0.051452810
[31]  0.016809115 -0.018081770 -0.117261233  0.003815114 -0.004024491
[36] -0.040083830 -0.032073454  0.006015819 -0.011888169  0.008207189
[41]  0.003378446 -0.069552249 -0.070945885 -0.015779077 -0.013335864
[46] -0.021952969  0.002625788 -0.041225814
> 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/4fmjj1476909821.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/5xnta1476909821.tab") 
> 
> try(system("convert tmp/1zfay1476909821.ps tmp/1zfay1476909821.png",intern=TRUE))
character(0)
> try(system("convert tmp/20wne1476909821.ps tmp/20wne1476909821.png",intern=TRUE))
character(0)
> try(system("convert tmp/3c1e31476909821.ps tmp/3c1e31476909821.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  1.219   0.112   1.347