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(1.01,1.02,1.04,1.06,1.06,1.06,1.06,1.06,1.02,0.98,0.99,0.99,0.94,0.96,0.98,1.01,1.01,1.02,1.04,1.03,1.05,1.08,1.17,1.11,1.11,1.11,1.2,1.21,1.31,1.37,1.37,1.26,1.23,1.17,1.06,0.95,0.92,0.92,0.9,0.93,0.93,0.97,0.96,0.99,0.98,0.96,1,0.99,1.03,1.02,1.07,1.13,1.15,1.16,1.14,1.15,1.15,1.16,1.17,1.22,1.26,1.29,1.36,1.38,1.37,1.37,1.37,1.36,1.38,1.4,1.44,1.42)
> 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/1u1t21353097090.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/29s6d1353097090.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/31fxl1353097090.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  0.353630903  0.286503610  0.070401725  0.153625496
 [6] -0.226453254 -0.234821644 -0.040558322 -0.067654297 -0.129061026
[11] -0.065145736  0.153982464 -0.022567973 -0.108006121 -0.104062040
[16] -0.046700773 -0.228113059 -0.202271720 -0.105737852  0.006934825
[21] -0.088125993 -0.021899747  0.183198550  0.118306444  0.071662053
[26] -0.010745333  0.059345135 -0.084927685 -0.141535707 -0.021513432
[31]  0.009947445  0.007817375 -0.021829492  0.110808331  0.023981084
[36] -0.009807824  0.012788074  0.018449587 -0.029823839 -0.085472119
[41]  0.070477317  0.039656030  0.001182068 -0.049149750  0.030525503
[46] -0.019604265  0.011035781 -0.005919769  0.055924500
> (mypacf <- c(rpacf$acf))
 [1]  0.353630903  0.184524468 -0.091667302  0.124226397 -0.357417154
 [6] -0.154884191  0.291994434 -0.119653959 -0.077016142  0.070431762
[11]  0.054490377 -0.113656889 -0.102227636 -0.084566937 -0.054563216
[16] -0.087160060 -0.015806022 -0.068883806  0.052830647 -0.039999562
[21] -0.096840933  0.195852193 -0.053751703 -0.022571984 -0.049344401
[26] -0.136083178  0.038014548 -0.059303859  0.065946012 -0.038650145
[31] -0.024975693  0.026526427 -0.083387150 -0.063338700  0.027232517
[36]  0.050223952 -0.054237288  0.004116446 -0.013732528  0.109126899
[41] -0.039556811 -0.080231349 -0.062561300 -0.038839369  0.050576378
[46]  0.070354285 -0.048523851 -0.017752060
> 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/4314p1353097090.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/5xqd01353097090.tab") 
> 
> try(system("convert tmp/1u1t21353097090.ps tmp/1u1t21353097090.png",intern=TRUE))
character(0)
> try(system("convert tmp/29s6d1353097090.ps tmp/29s6d1353097090.png",intern=TRUE))
character(0)
> try(system("convert tmp/31fxl1353097090.ps tmp/31fxl1353097090.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  2.100   0.322   2.425