R version 2.13.0 (2011-04-13)
Copyright (C) 2011 The R Foundation for Statistical Computing
ISBN 3-900051-07-0
Platform: i486-pc-linux-gnu (32-bit)

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> x <- c(78.7,75.7,77.1,86.1,86.8,86.3,91.5,90.7,78.2,73,73.7,77.3,67.5,72.7,76.6,82.4,82.3,86.3,93,88.8,96.9,103.9,115.7,112.8,114.7,118,129.3,137,156,166.2,167.8,144.3,126,90.4,67.5,52.4,54.6,52.9,59.1,63.3,73.8,87.6,81.8,90.7,86.3,93.6,98,94.3,97.6,94.2,100.2,106.7,95.7,94.6,94.7,96.2,96.3,103.3,106.8,113.7,117.4,123.6,137.6,147.4,137.2,133.8,136.7,127.3,128.7,127,133.7,132)
> par8 = ''
> par7 = '0.95'
> par6 = 'White Noise'
> par5 = '12'
> par4 = '0'
> par3 = '1'
> par2 = '1'
> par1 = '60'
> #'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/1erlm1334051427.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/2lbf61334051427.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/3nhd01334051427.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  0.483139598  0.357995223  0.081245996 -0.047515804
 [6] -0.269853526 -0.324768241 -0.217364470 -0.155132734 -0.181008123
[11] -0.122726366 -0.030293519 -0.042722514 -0.089924726 -0.056917524
[16]  0.026858323 -0.059624217 -0.032548067 -0.017977495  0.068011869
[21] -0.006009411  0.091855730  0.095686111  0.134461268 -0.027078812
[26]  0.079610897 -0.073388524 -0.112164698 -0.192367593 -0.140554992
[31] -0.058615837 -0.048197712  0.044993373  0.132978056  0.142685920
[36]  0.069225596  0.040989394  0.005826128 -0.023659181 -0.058479663
[41]  0.052910374  0.027219117  0.014027463 -0.014401311  0.042038136
[46]  0.008540219 -0.012389085 -0.021856654  0.043724424 -0.048379109
[51] -0.044292453 -0.033511750  0.008963685 -0.022847108 -0.048661136
[56]  0.019493765  0.033333733  0.025048985 -0.013448060  0.045278050
[61]  0.015709148
> (mypacf <- c(rpacf$acf))
 [1]  0.483139598  0.162503563 -0.190425347 -0.106582894 -0.237115660
 [6] -0.125899425  0.126782531  0.004641765 -0.203362520 -0.086233589
[11]  0.029287648 -0.073956574 -0.117143337 -0.045918589  0.030026992
[16] -0.154327012 -0.035250652 -0.043442418  0.009286745 -0.077358528
[21]  0.081808505 -0.040954277 -0.009453648 -0.152982284  0.130733571
[26] -0.191878113 -0.125358477 -0.041094014 -0.063109284  0.017613692
[31] -0.012603250 -0.040722738 -0.004354347 -0.028019810 -0.055101324
[36] -0.089098982 -0.063134434 -0.004158765  0.018448209  0.033454468
[41] -0.060846449 -0.131769563  0.007506118  0.006862019  0.010218655
[46] -0.054307210 -0.038924642  0.019711234 -0.049607307 -0.046473580
[51]  0.024170590 -0.004368256 -0.036238559 -0.071601314 -0.067982454
[56]  0.028939677  0.034926737 -0.081875799 -0.012301909 -0.001630829
> 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/4058m1334051427.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/5paas1334051427.tab") 
> 
> try(system("convert tmp/1erlm1334051427.ps tmp/1erlm1334051427.png",intern=TRUE))
character(0)
> try(system("convert tmp/2lbf61334051427.ps tmp/2lbf61334051427.png",intern=TRUE))
character(0)
> try(system("convert tmp/3nhd01334051427.ps tmp/3nhd01334051427.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  0.985   0.199   1.196