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(92.8,92.9,93.06,93.28,93.41,93.49,93.49,93.5,93.56,94.12,94.3,94.36,94.36,94.5,94.85,95.16,95.73,95.76,95.76,95.81,96.09,96.48,96.71,96.69,96.69,96.66,96.73,96.84,97.87,98,97.98,98.03,98.11,98.18,98.32,98.34,98.28,98.52,98.56,99.6,100.16,100.46,100.46,100.68,100.83,100.64,100.9,100.92,100.75,100.96,101.05,101.33,101.38,101.44,101.51,101.4,101.26,100.83,100.75,100.81,100.82,100.85,100.79,100.84,101.04,101.11,101.15,101.11,101.28,101.62,102.07,102.14)
> 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/1csxc1457428774.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/2xjxw1457428774.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/3et0e1457428774.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  0.96029906  0.91839400  0.87861636  0.84186722  0.80602174
 [7]  0.76857030  0.72915621  0.68776820  0.64717966  0.61081953  0.57417359
[13]  0.53530978  0.49292090  0.45022988  0.40910858  0.36695525  0.32868454
[19]  0.28950513  0.24906069  0.20695291  0.16663603  0.13042761  0.09602517
[25]  0.06073853  0.02233955 -0.01851306 -0.05868147 -0.10002362 -0.13224173
[31] -0.16276395 -0.19603357 -0.22898198 -0.25857194 -0.28161417 -0.30362230
[37] -0.32473404 -0.34765263 -0.36943124 -0.39076210 -0.40284854 -0.41014344
[43] -0.41497209 -0.42080157 -0.42419310 -0.42000100 -0.41690522 -0.41106768
[49] -0.40534966
> (mypacf <- c(rpacf$acf))
 [1]  0.960299055 -0.048573653  0.006311055  0.016302193 -0.009783472
 [6] -0.039283801 -0.043472730 -0.047151164 -0.015281293  0.026281803
[11] -0.030641983 -0.048349350 -0.064751890 -0.029884874 -0.014304704
[16] -0.049589208  0.019115591 -0.039618799 -0.039389751 -0.050470936
[21] -0.013632990  0.010792292 -0.011455159 -0.039224613 -0.067451437
[26] -0.061185356 -0.036283357 -0.067988747  0.067802662 -0.018489748
[31] -0.060613204 -0.026587989  0.001745914  0.031044172 -0.031461806
[36] -0.021257986 -0.051882862 -0.005692229 -0.038426063  0.070236219
[41]  0.013017787  0.008733193 -0.017764109  0.004112536  0.075840223
[46] -0.054944111  0.009551985 -0.025192516
> 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/41bx41457428774.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/5qg9k1457428774.tab") 
> 
> try(system("convert tmp/1csxc1457428774.ps tmp/1csxc1457428774.png",intern=TRUE))
character(0)
> try(system("convert tmp/2xjxw1457428774.ps tmp/2xjxw1457428774.png",intern=TRUE))
character(0)
> try(system("convert tmp/3et0e1457428774.ps tmp/3et0e1457428774.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  1.182   0.192   1.387