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(79.49,79.69,79.86,79.87,79.83,79.83,79.83,79.37,79.53,79.78,79.94,79.97,79.97,79.98,80.25,80.38,80.13,80.15,80.15,80.18,80.47,80.83,80.62,80.66,80.66,80.67,80.8,81.04,81.24,81.26,81.26,81.47,81.94,82.83,82.29,82.32,82.32,82.3,82.54,82.54,82.62,82.63,82.63,82.63,82.71,83.25,83.14,83.34,83.34,83.37,83.33,83.26,83.66,83.64,83.64,83.71,83.87,84.17,84.35,84.44,84.44,84.45,84.67,84.95,84.89,84.93,84.93,84.93,85.45,85.77,85.79,85.9)
> 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/1dme11352717888.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/2ii2j1352717888.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/3pyfm1352717888.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 -0.035807784 -0.171672639 -0.140000328 -0.133342524
 [6]  0.142126180  0.080788451  0.057731824 -0.166351203 -0.060283723
[11] -0.050456113 -0.045294605  0.408453542 -0.027055173 -0.083479560
[16] -0.101178862 -0.067212801 -0.016690291  0.059562718  0.134125545
[21] -0.101265696 -0.086745305 -0.110766594  0.020454970  0.200476018
[26] -0.005433740 -0.149668997  0.033132181 -0.107391630 -0.072197472
[31]  0.167283880  0.095448252  0.003857787 -0.090473746 -0.152888561
[36]  0.090246595  0.164064370  0.076920875 -0.053477565 -0.022462177
[41] -0.079925539 -0.019379125  0.067595680  0.065145174  0.026326217
[46] -0.078771414 -0.064276748  0.017543192  0.105194450
> (mypacf <- c(rpacf$acf))
 [1] -0.035807784 -0.173176883 -0.158359374 -0.190165013  0.068796250
 [6]  0.016719333  0.066263399 -0.143326792 -0.013862732 -0.105713520
[11] -0.113604914  0.341670881 -0.008182918  0.036287284 -0.018110241
[16]  0.010283821 -0.162685246 -0.010746636  0.067969286 -0.001424842
[21] -0.071141246 -0.089005093  0.040743448 -0.045917480 -0.041680626
[26] -0.151547628  0.169998338 -0.197412622 -0.072379377  0.110945575
[31]  0.034600521  0.021452176 -0.024183256 -0.034524803  0.073887566
[36]  0.044208330  0.034997052  0.180789534 -0.043841256  0.050696468
[41]  0.053807311 -0.098813738 -0.027333938  0.044915228  0.015356613
[46] -0.014248468 -0.007929602  0.041017744
> 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/4xbd01352717888.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/5v94t1352717888.tab") 
> 
> try(system("convert tmp/1dme11352717888.ps tmp/1dme11352717888.png",intern=TRUE))
character(0)
> try(system("convert tmp/2ii2j1352717888.ps tmp/2ii2j1352717888.png",intern=TRUE))
character(0)
> try(system("convert tmp/3pyfm1352717888.ps tmp/3pyfm1352717888.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  2.199   0.346   2.521