R version 3.1.0 (2014-04-10) -- "Spring Dance"
Copyright (C) 2014 The R Foundation for Statistical Computing
Platform: i686-pc-linux-gnu (32-bit)

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> x <- c(0.978,0.973,0.96,0.978,0.985,1.035,1.015,1.05,1.022,1.042,1.058,1.056,1.098,1.097,1.139,1.182,1.189,1.191,1.168,1.168,1.177,1.184,1.2,1.251,1.288,1.313,1.363,1.377,1.342,1.334,1.348,1.327,1.349,1.361,1.393,1.38,1.421,1.432,1.457,1.453,1.428,1.383,1.408,1.458,1.474,1.491,1.476,1.446,1.451,1.472,1.449,1.415,1.39,1.394,1.418,1.426,1.437,1.406,1.387,1.404)
> 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. 1.2.291 ()
> #Author: root
> #To cite this work: Wessa P., (2012), (Partial) Autocorrelation Function (v1.0.11) 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)
> 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/1rmoz1399754065.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/2535j1399754065.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/3kfvq1399754065.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  0.144879049  0.059681489 -0.197642232 -0.145275044
 [6] -0.042287880  0.048109230  0.048601113 -0.167896011  0.056826535
[11]  0.310976013  0.318837520  0.179673713 -0.042687501 -0.246827586
[16] -0.230795220 -0.036409707  0.038987918  0.013500845  0.093564530
[21]  0.089883602 -0.022508133  0.127871634  0.029256046 -0.128421593
[26] -0.173482532 -0.197768711 -0.026662888 -0.062807603  0.145960951
[31] -0.004617801  0.013482109 -0.096557974  0.077759467 -0.073103871
[36] -0.106445225 -0.143039261 -0.095610782  0.011327637  0.097689931
[41]  0.043214742 -0.060938809 -0.060817461 -0.091910301  0.037003296
[46] -0.015281634 -0.042501052 -0.031710125 -0.042521932
> (mypacf <- c(rpacf$acf))
 [1]  0.144879049  0.039521095 -0.216549376 -0.095384824  0.018579950
 [6]  0.030378569 -0.008517200 -0.215789014  0.129433622  0.392730929
[11]  0.210335813  0.034125658 -0.006850833 -0.078971148 -0.079696380
[16] -0.056938551 -0.064910442 -0.012022540  0.124913107  0.028303582
[21] -0.263049554 -0.037079421  0.048494600 -0.066906404 -0.047900222
[26] -0.116699470  0.118574016 -0.053553375 -0.121977687 -0.156805381
[31]  0.070190612 -0.061739806  0.126112324 -0.061343235 -0.088991761
[36] -0.015029201  0.087204074  0.021409397  0.002792650 -0.040569415
[41] -0.002057933  0.001157474 -0.153350923  0.012183274  0.061244226
[46]  0.027971320  0.072244375 -0.035014043
> 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/41dbp1399754065.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/51wap1399754065.tab") 
> 
> try(system("convert tmp/1rmoz1399754065.ps tmp/1rmoz1399754065.png",intern=TRUE))
character(0)
> try(system("convert tmp/2535j1399754065.ps tmp/2535j1399754065.png",intern=TRUE))
character(0)
> try(system("convert tmp/3kfvq1399754065.ps tmp/3kfvq1399754065.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  1.542   0.305   1.867