R version 3.3.3 (2017-03-06) -- "Another Canoe"
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Platform: x86_64-pc-linux-gnu (64-bit)

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> x <- c(97.96,98.36,98.36,98.51,98.77,98.78,98.89,98.87,99.05,99.09,99.1,99.12,99.37,99.46,99.6,99.87,99.88,100.01,100.02,100.19,100.2,100.35,100.47,100.57,101.41,101.67,101.82,101.86,101.98,102.06,102.17,102.2,102.35,102.47,102.55,102.62,102.81,102.88,102.94,102.95,102.94,103.05,103.09,103.1,103.14,103.19,103.36,103.43,103.62,103.79,103.9,103.92,103.94,103.98,104.04,104.09,104.16,104.22,104.28,104.32)
> 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/1c9841495045252.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/2124s1495045252.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/3nq161495045252.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  0.073422744  0.101262487  0.030428948 -0.044609459
 [6] -0.005632837 -0.153058258 -0.004528549 -0.062716922  0.135570094
[11] -0.036557804  0.118999194  0.150405614 -0.011103148 -0.072200233
[16] -0.161534114 -0.032378439 -0.107397071 -0.034243985 -0.211094495
[21]  0.090004156  0.040182374 -0.003216152  0.169039871  0.164171888
[26]  0.046813342 -0.039446436 -0.084389205 -0.094587429 -0.036211606
[31] -0.088719182 -0.041798433 -0.012434223 -0.008056530 -0.026540448
[36] -0.011529239 -0.014169846 -0.002603069 -0.023091445 -0.080762075
[41] -0.006113286 -0.024926187 -0.009790934 -0.026155340 -0.017596149
[46]  0.047925613  0.003056551  0.017192271  0.027491656
> (mypacf <- c(rpacf$acf))
 [1]  7.342274e-02  9.639122e-02  1.688033e-02 -5.833553e-02 -3.645051e-03
 [6] -1.453336e-01  1.915410e-02 -3.828876e-02  1.553596e-01 -6.569126e-02
[11]  1.132310e-01  1.092881e-01 -3.239496e-02 -1.336729e-01 -1.107656e-01
[16] -6.759840e-03 -3.495076e-02 -5.266978e-03 -2.030849e-01  1.018002e-01
[21] -6.257584e-03 -7.457741e-04  1.178367e-01  2.017793e-01 -5.457833e-02
[26]  1.410708e-02 -9.213565e-02 -2.291314e-02 -5.790452e-02 -1.496301e-02
[31] -7.348255e-05 -9.036617e-02 -1.012160e-01 -9.726850e-02 -4.514644e-02
[36] -7.280677e-02  8.370249e-02  2.464656e-02  6.816337e-02 -1.783491e-03
[41]  3.730230e-03  2.920352e-02  3.801799e-02 -8.227979e-02  6.549167e-02
[46] -6.691720e-02 -9.715735e-02 -5.135334e-02
> 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/4ye3a1495045252.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/5dul01495045252.tab") 
> 
> try(system("convert tmp/1c9841495045252.ps tmp/1c9841495045252.png",intern=TRUE))
character(0)
> try(system("convert tmp/2124s1495045252.ps tmp/2124s1495045252.png",intern=TRUE))
character(0)
> try(system("convert tmp/3nq161495045252.ps tmp/3nq161495045252.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  2.279   0.345   2.746