R version 3.3.1 (2016-06-21) -- "Bug in Your Hair"
Copyright (C) 2016 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu (64-bit)

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> x <- c(92.1,93.91,95.46,94.54,95.63,96.32,96.42,96.95,96.52,96.82,96.4,96.69,96.72,98.57,98.6,96.44,97.09,97.36,97.74,96.78,96.45,97.66,98.69,98.21,97.33,99.05,100.09,98.1,97.68,97.44,99.19,98.32,97.83,97.71,97.51,97.62,96.49,98.92,99.69,97.06,97.63,97.97,99.01,97.89,97.23,96.93,96.97,97.68,97.73,99.03,100.35,99.38,99.3,99.77,101.11,101.15,101.59,100.95,99.23,100.41)
> 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/1qpol1476818638.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/2c7f41476818638.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/35x921476818638.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 -0.108930875 -0.371156315 -0.029844083  0.193783605
 [6]  0.177726183 -0.316949157  0.069921426  0.090129048  0.056215164
[11] -0.253554831 -0.192224452  0.579115895 -0.065776058 -0.248271515
[16] -0.080849754  0.154260302  0.116175032 -0.234576906  0.128820911
[21]  0.015594960  0.038720217 -0.179992686 -0.181381590  0.396765514
[26]  0.009518008 -0.141883714 -0.148406739  0.085398437  0.132952907
[31] -0.096004212  0.022691241 -0.111093479  0.071640263 -0.054903868
[36] -0.093431589  0.152071790 -0.018862397 -0.048676867 -0.065010885
[41]  0.011340379  0.017424729 -0.033557005  0.079934254 -0.086400971
[46] -0.010540451  0.019512519 -0.005385618  0.087789382
> (mypacf <- c(rpacf$acf))
 [1] -0.108930875 -0.387621745 -0.152644134  0.022493713  0.187130244
 [6] -0.209953031  0.167035114 -0.067546327  0.109202042 -0.293834077
[11] -0.171097388  0.398734473 -0.088268718  0.061915564 -0.013155109
[16] -0.026851274 -0.134735365  0.019304821  0.114733088 -0.033528759
[21] -0.002649386 -0.061578458 -0.106840794 -0.002751155  0.070131589
[26]  0.056396311 -0.034139965 -0.076806453 -0.001759463  0.086760679
[31] -0.144975937 -0.079645085 -0.041006582 -0.035772946  0.069721041
[36] -0.066680669 -0.032292037 -0.129089767  0.081797535 -0.096657281
[41] -0.049436448 -0.087422009  0.032298972 -0.026929000 -0.083395987
[46]  0.081329016 -0.004963993  0.047570462
> 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/4z9sb1476818638.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/5mhiy1476818638.tab") 
> 
> try(system("convert tmp/1qpol1476818638.ps tmp/1qpol1476818638.png",intern=TRUE))
character(0)
> try(system("convert tmp/2c7f41476818638.ps tmp/2c7f41476818638.png",intern=TRUE))
character(0)
> try(system("convert tmp/35x921476818638.ps tmp/35x921476818638.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  1.215   0.082   1.317