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(103.48,103.93,103.89,104.4,104.79,104.77,105.13,105.26,104.96,104.75,105.01,105.1,103.48,103.93,103.89,104.4,104.79,106.12,106.57,106.44,106.54,107.1,108.1,108.4,108.84,109.62,110.42,110.67,111.66,112.28,112.87,112.18,112.36,112.16,111.49,111.25,111.36,111.74,111.1,111.33,111.25,111.04,110.97,111.31,111.02,111.07,111.36,111.54,112.05,112.52,112.94,113.33,113.78,113.77,113.82,113.89,114.25,114.41,114.55,115,115.66,116.33,116.91,117.2,117.59,117.95,118.09,117.99,118.31,118.49,118.96,119.01)
> par8 = ''
> par7 = '0.95'
> par6 = 'White Noise'
> par5 = '12'
> par4 = '0'
> par3 = '0'
> par2 = '1'
> par1 = '48'
> par8 <- ''
> par7 <- '0.95'
> par6 <- 'White Noise'
> par5 <- '12'
> par4 <- '0'
> par3 <- '0'
> 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/1g6lr1352710463.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/2dwwj1352710463.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/3xlau1352710463.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  0.954385648  0.907223706  0.858685956  0.810105734
 [6]  0.761018206  0.710374587  0.660944160  0.610915838  0.560200624
[11]  0.509309877  0.462076108  0.416799175  0.366066759  0.319083639
[16]  0.272657735  0.228556503  0.189418124  0.157854511  0.129185040
[21]  0.097931648  0.068615533  0.043115359  0.022041177  0.003318896
[26] -0.011833443 -0.022986038 -0.030939417 -0.037950707 -0.042157248
[31] -0.042677987 -0.041579077 -0.045876341 -0.051629608 -0.059291991
[36] -0.075374232 -0.092334007 -0.109768246 -0.127526787 -0.153293017
[41] -0.180504592 -0.208417237 -0.242471956 -0.275502631 -0.305246721
[46] -0.332597899 -0.360081839 -0.383302469 -0.402467104
> (mypacf <- c(rpacf$acf))
 [1]  0.954385648 -0.040699253 -0.039905889 -0.026113647 -0.032328813
 [6] -0.045246038 -0.015258029 -0.036455367 -0.039009677 -0.033918822
[11]  0.008149467 -0.011717992 -0.095237474  0.007108329 -0.029250833
[16] -0.013127347  0.020790466  0.052389849 -0.004534815 -0.060540564
[21] -0.007615053  0.012839633  0.012820023 -0.001173184  0.019150192
[26]  0.012897537  0.016186578 -0.005593644  0.011554774  0.013307318
[31]  0.002782125 -0.067368114 -0.029055134 -0.032377526 -0.110114154
[36] -0.028775289 -0.029228793 -0.028098866 -0.109651639 -0.032187307
[41] -0.036718752 -0.108991472 -0.022815686  0.016447194 -0.020240729
[46] -0.037772738  0.036692362  0.007182008
> 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/4ev4o1352710463.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/56rhh1352710463.tab") 
> 
> try(system("convert tmp/1g6lr1352710463.ps tmp/1g6lr1352710463.png",intern=TRUE))
character(0)
> try(system("convert tmp/2dwwj1352710463.ps tmp/2dwwj1352710463.png",intern=TRUE))
character(0)
> try(system("convert tmp/3xlau1352710463.ps tmp/3xlau1352710463.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  2.100   0.444   2.523