R version 2.15.2 (2012-10-26) -- "Trick or Treat"
Copyright (C) 2012 The R Foundation for Statistical Computing
ISBN 3-900051-07-0
Platform: i686-pc-linux-gnu (32-bit)

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> x <- c(1.44,1.45,1.45,1.47,1.49,1.5,1.5,1.5,1.5,1.5,1.5,1.51,1.52,1.51,1.51,1.51,1.52,1.52,1.52,1.52,1.52,1.53,1.53,1.53,1.53,1.54,1.54,1.55,1.56,1.55,1.56,1.56,1.56,1.56,1.57,1.56,1.57,1.58,1.58,1.58,1.6,1.61,1.61,1.61,1.6,1.59,1.56,1.57,1.55,1.59,1.62,1.63,1.62,1.56,1.56,1.54,1.54,1.52,1.56,1.59,1.61,1.56,1.51,1.48,1.49,1.48,1.47,1.47,1.46,1.45,1.45,1.45)
> 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/1gwz81353058724.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/21iif1353058724.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/3lv2a1353058724.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]  1.0000000000  0.2631746809  0.0526332276 -0.3492412895 -0.1529893744
 [6] -0.1433529062 -0.0716460781  0.0957609791  0.2154527109  0.4162200593
[11]  0.1431364844 -0.0198244325 -0.2349487137 -0.0673394729 -0.0909959013
[16]  0.0859137844  0.0429151266  0.0810594799  0.0571334734  0.0088780425
[21]  0.0040246873 -0.0628316333  0.0474248646 -0.0192966669  0.0714828125
[26] -0.0767187028 -0.0147166867 -0.0434277047 -0.0195035966 -0.0195719403
[31] -0.0003654492  0.0044860076 -0.0336602443  0.0620390357 -0.0288097367
[36] -0.0240256745 -0.0430318805 -0.0047527380  0.0240237760  0.0288078383
[41] -0.0093384136 -0.1145422203 -0.0522706260 -0.0284139125  0.0050802185
[46] -0.0379858339  0.0479412396  0.0289350336  0.0383693182
> (mypacf <- c(rpacf$acf))
 [1]  0.263174681 -0.017865034 -0.385449976  0.044313830 -0.079779495
 [6] -0.181415139  0.169588883  0.136712804  0.292621643  0.026855122
[11] -0.005803665  0.028362397  0.104633402 -0.063445712  0.102163007
[16] -0.033653721 -0.125275128 -0.037191811 -0.045684329  0.022486320
[21]  0.016059872  0.045929812 -0.010826715  0.027614399 -0.085951910
[26]  0.014040202  0.049038723 -0.111146820 -0.028689418 -0.005590474
[31] -0.131713960 -0.038001383  0.117290271 -0.037458853 -0.038518895
[36]  0.097193150 -0.034917349  0.090771379  0.057537481 -0.037807424
[41] -0.084645527 -0.061835902 -0.045703473 -0.041299505 -0.081350377
[46]  0.037996278  0.014499797 -0.046891507
> 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/48xws1353058724.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/5gchb1353058724.tab") 
> 
> try(system("convert tmp/1gwz81353058724.ps tmp/1gwz81353058724.png",intern=TRUE))
character(0)
> try(system("convert tmp/21iif1353058724.ps tmp/21iif1353058724.png",intern=TRUE))
character(0)
> try(system("convert tmp/3lv2a1353058724.ps tmp/3lv2a1353058724.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  1.811   0.312   2.121