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(99.13,100.46,101.83,100.82,100.99,99.11,98.99,99.8,100.3,101.56,98.83,101.29,98.24,98.37,99.68,97.8,98.34,98.06,97.19,99.44,99.04,100.81,98.49,101.03,98.59,101.07,99.28,101.65,100.59,101.84,100.27,100.04,97.78,97.59,97.68,100.56,98.9,100.08,101.7,100.9,100.67,100.51,100.01,99.8,97.7,98.14,101.77,99.82,100.03,101.83,98.25,99.88,98.96,98.37,97.52,99.59,97.99,100.68,100.39,99.31,96.93,102.06,97.9,102.29,100.55,100.77,100.68,100.75,100.21,99.85,100.59,101.45)
> 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/1gkva1457596451.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/2x8nw1457596451.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/386st1457596451.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 -0.629145959  0.338370021 -0.194324714  0.083270565
 [6] -0.244904052  0.268340227 -0.242030391  0.182887957 -0.106060877
[11]  0.144110699 -0.186311571  0.267511614 -0.271589361  0.096253178
[16] -0.027813355 -0.011300788 -0.011288528  0.073299210 -0.037356067
[21]  0.062043325 -0.026416073  0.002516689 -0.053998623  0.065945385
[26] -0.172866600  0.212617058 -0.122206547  0.149724695 -0.127416403
[31]  0.118019845 -0.231592730  0.209353447 -0.190548718  0.131494343
[36] -0.092317295  0.134864258 -0.150601804  0.256570075 -0.241085218
[41]  0.171562721 -0.156228439  0.115913901 -0.135868659  0.135210083
[46] -0.052809303 -0.032226127  0.076876966 -0.030546234
> (mypacf <- c(rpacf$acf))
 [1] -0.629145959 -0.095095930 -0.035117720 -0.055174560 -0.371479277
 [6] -0.087700919 -0.091294757 -0.087387247 -0.112920553  0.024801251
[11] -0.093969710  0.105000085 -0.011861429 -0.210617859 -0.069102974
[16] -0.064078231 -0.043421021 -0.119504440 -0.029013992  0.052451418
[21]  0.028367524 -0.019649079 -0.051957616  0.030632580 -0.167505995
[26]  0.049072194  0.026587615  0.148217358 -0.002029840  0.009996406
[31] -0.175430204 -0.039618579  0.001432208 -0.081471029 -0.103400895
[36] -0.053759140 -0.001912984  0.073244803 -0.018418169 -0.021371542
[41]  0.011688368  0.073641739  0.048049326 -0.041766356  0.099435806
[46] -0.081769560 -0.033697167 -0.007117888
> 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/4s4pl1457596451.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/5t5st1457596451.tab") 
> 
> try(system("convert tmp/1gkva1457596451.ps tmp/1gkva1457596451.png",intern=TRUE))
character(0)
> try(system("convert tmp/2x8nw1457596451.ps tmp/2x8nw1457596451.png",intern=TRUE))
character(0)
> try(system("convert tmp/386st1457596451.ps tmp/386st1457596451.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  1.169   0.165   1.343