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(98.68,99.21,99.36,100.72,102.27,102.62,102.97,102.88,102.9,103.01,103.02,103.73,104.18,103.73,103.78,103.61,103.84,103.86,104.14,104.05,104.01,104.49,104.83,104.78,104.95,105.28,105.28,105.91,106.81,106.39,107.02,106.92,107.01,106.79,107.41,107.13,107.54,108.48,108.5,108.27,109.42,110.09,109.98,109.99,109.54,108.85,106.76,107.56,106.24,108.85,111.11,111.85,110.68,106.96,106.74,105.73,105.66,104.01,106.86,108.84,110.66,106.93,103.74,101.64,102.17,101.13,100.64,100.43,99.77,99.79,99.47,99.63)
> 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/fisher/rcomp/tmp/1tjzk1357845354.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/fisher/rcomp/tmp/2e1ry1357845354.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/fisher/rcomp/tmp/3bpiv1357845354.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  0.889647484  0.747803181  0.604357536  0.517447280
 [6]  0.462310205  0.429030270  0.411651119  0.397304540  0.352995965
[11]  0.273500957  0.195457701  0.151746950  0.129071304  0.093810112
[16]  0.049997120  0.006269003 -0.033460943 -0.077456491 -0.119256348
[21] -0.140848612 -0.155358295 -0.165692986 -0.197546386 -0.249397841
[26] -0.294357815 -0.330764729 -0.349991782 -0.352821223 -0.344515843
[31] -0.337853259 -0.327715721 -0.322789383 -0.326631583 -0.332700542
[36] -0.328647063 -0.326925756 -0.322986585 -0.309997118 -0.304987700
[41] -0.301596224 -0.285542756 -0.254285701 -0.220484966 -0.178925945
[46] -0.145485063 -0.119993073 -0.120584342 -0.121549789
> (mypacf <- c(rpacf$acf))
 [1]  0.889647484 -0.209418402 -0.069902234  0.194451612  0.026429806
 [6]  0.021966785  0.084845964  0.016293821 -0.140906445 -0.126764282
[11]  0.038608661  0.085747467 -0.046423976 -0.139129033 -0.021707484
[16] -0.008432651 -0.045401590 -0.042992782 -0.003315943  0.021301856
[21] -0.089218045 -0.004264700 -0.060069668 -0.124801648 -0.013880141
[26] -0.039134910 -0.005005811  0.003161324 -0.031857997 -0.046933794
[31]  0.050396014  0.002738148 -0.070916852 -0.030259106  0.012416034
[36] -0.080461865 -0.034785921  0.050366138 -0.094475256 -0.072359167
[41]  0.079975057  0.044631298 -0.053922174  0.045164058 -0.008625211
[46] -0.021533106 -0.116864552  0.024898341
> lengthx <- length(x)
> sqrtn <- sqrt(lengthx)
> 
> #Note: the /var/fisher/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/fisher/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/fisher/rcomp/tmp/45nin1357845354.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/fisher/rcomp/tmp/52m5f1357845354.tab") 
> 
> try(system("convert tmp/1tjzk1357845354.ps tmp/1tjzk1357845354.png",intern=TRUE))
character(0)
> try(system("convert tmp/2e1ry1357845354.ps tmp/2e1ry1357845354.png",intern=TRUE))
character(0)
> try(system("convert tmp/3bpiv1357845354.ps tmp/3bpiv1357845354.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  1.893   0.557   2.444