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(92.94,92.97,93.37,92.6,92.84,92.55,92.93,92.44,93.36,93.24,92.65,92.06,92.88,91.69,91.66,90.26,91.11,92.33,91.82,92.24,93.35,93.53,93.34,92.59,92.42,92.64,94.44,93.59,93.39,93.33,93.72,95.43,97.06,97.7,97.59,96.97,97.75,99.27,100.63,99.8,99.5,99.72,99.77,100.18,101.11,100.67,101.13,100.46,101.6,102.3,103.26,104.56,104.61,104.62,105.03,104.93,104.73,104.33,104.6,104.41,104.63,105.55,106.12,106.62,106.72,106.52,106.79,106.95,106.92,106.74,108.13,107.86)
> 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/12u831457785227.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/2pow91457785227.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/37yh91457785227.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  0.96583263  0.92861649  0.89752042  0.86583064  0.83337047
 [7]  0.79811904  0.76062490  0.72059758  0.68239598  0.64757581  0.61188483
[13]  0.57702521  0.53795411  0.49423111  0.45005836  0.40075662  0.35192162
[19]  0.30331884  0.25190325  0.20104345  0.14994399  0.10545429  0.06391095
[25]  0.02525851 -0.01211599 -0.05268923 -0.08780306 -0.12550323 -0.15969025
[31] -0.19426527 -0.22986754 -0.26027033 -0.29147918 -0.32388474 -0.35224108
[37] -0.37510642 -0.39324947 -0.41014984 -0.42449023 -0.43757249 -0.44459898
[43] -0.44379294 -0.44291454 -0.44057654 -0.43889876 -0.44147359 -0.43591414
[49] -0.43036517
> (mypacf <- c(rpacf$acf))
 [1]  0.965832628 -0.062771259  0.074138387 -0.033987682 -0.019073418
 [6] -0.061381316 -0.050225245 -0.064077514  0.003366731  0.019845756
[11] -0.030744144  0.002396251 -0.087427239 -0.087208642 -0.046958922
[16] -0.124162710 -0.026536322 -0.043526717 -0.070863092 -0.022440853
[21] -0.047129331  0.055324089 -0.003611831  0.018253817 -0.021074610
[26] -0.070418943  0.041352569 -0.096755146  0.035805037 -0.067544300
[31] -0.021501390  0.038805681 -0.054622486 -0.051292735 -0.004247742
[36]  0.027536398  0.007032637 -0.008775493 -0.004455706 -0.029580674
[41]  0.075306777  0.048846216  0.001775755  0.015339687 -0.039955094
[46] -0.070329158  0.068493682 -0.049350443
> 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/4rzpi1457785227.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/5xwvl1457785227.tab") 
> 
> try(system("convert tmp/12u831457785227.ps tmp/12u831457785227.png",intern=TRUE))
character(0)
> try(system("convert tmp/2pow91457785227.ps tmp/2pow91457785227.png",intern=TRUE))
character(0)
> try(system("convert tmp/37yh91457785227.ps tmp/37yh91457785227.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  1.192   0.215   1.418