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(92.76,93.12,93.6,93.24,93.4,93.32,93.13,93.19,93.84,94.01,93.78,93.47,93.6,92.85,92.91,92.29,92.5,93.1,92.86,93.19,93.73,93.88,93.85,93.45,93.43,93.59,95.28,94.95,94.49,94.45,94.35,95.52,96.89,97.54,97.65,97.35,98.2,99.46,100.35,99.72,99.69,99.62,99.77,100.19,100.82,100.36,101.08,100.73,101.51,102.12,102.88,103.47,103.53,103.67,103.68,103.76,103.67,103.01,103.39,103.43,103.4,104.8)
> 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/1og7a1489839817.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/2q0t81489839817.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/3m58n1489839817.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  0.954574458  0.916808352  0.879789224  0.842500122
 [6]  0.808770733  0.765060441  0.713751648  0.661273650  0.612239816
[11]  0.566376092  0.516940177  0.467060677  0.415400097  0.364024920
[16]  0.317971292  0.264299647  0.215863652  0.161601128  0.106279046
[21]  0.055895486  0.008569731 -0.036969922 -0.082800950 -0.135549108
[26] -0.186384864 -0.228936430 -0.257309496 -0.289541383 -0.323866010
[31] -0.357786292 -0.385506080 -0.398599974 -0.408244683 -0.414006611
[36] -0.423072574 -0.437720854 -0.437622479 -0.429920905 -0.417406330
[41] -0.410239342 -0.403114005 -0.396426963 -0.387261608 -0.373389798
[46] -0.360070628 -0.344254157 -0.323422199 -0.308976725
> (mypacf <- c(rpacf$acf))
 [1]  0.954574458  0.063026330 -0.004270916 -0.020787439  0.019819657
 [6] -0.125198039 -0.129043463 -0.064011610  0.001812365  0.003798092
[11] -0.058947209 -0.024752060 -0.039130847 -0.037156795  0.007823638
[16] -0.115905497  0.009836697 -0.095175653 -0.064794466 -0.015350428
[21]  0.007352961 -0.018823062 -0.036269926 -0.119362132 -0.056231933
[26]  0.027186413  0.112758748 -0.059607922 -0.053422356 -0.039777738
[31]  0.031733675  0.076662775  0.016026407  0.038618209 -0.038776250
[36] -0.112116600  0.074950393  0.056833840  0.057023501 -0.077562088
[41] -0.003849362 -0.061214892 -0.021833650 -0.025520371 -0.008428785
[46]  0.044362398  0.057857970 -0.090948763
> 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/43n0m1489839817.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/535451489839817.tab") 
> 
> try(system("convert tmp/1og7a1489839817.ps tmp/1og7a1489839817.png",intern=TRUE))
character(0)
> try(system("convert tmp/2q0t81489839817.ps tmp/2q0t81489839817.png",intern=TRUE))
character(0)
> try(system("convert tmp/3m58n1489839817.ps tmp/3m58n1489839817.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  1.546   0.152   1.732