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(0.98,0.99,0.99,0.99,1,1,1,1,1,1.01,1.02,1.02,1.01,1.03,1.03,1.03,1.03,1.03,1.03,1.03,1.04,1.06,1.07,1.08,1.08,1.09,1.09,1.09,1.1,1.1,1.1,1.1,1.1,1.11,1.12,1.13,1.13,1.13,1.13,1.13,1.14,1.14,1.14,1.14,1.14,1.14,1.15,1.15,1.15,1.15,1.15,1.15,1.16,1.15,1.16,1.16,1.16,1.17,1.17,1.17,1.18,1.19,1.2,1.21,1.21,1.21,1.21,1.22,1.22,1.22,1.23,1.22)
> 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/1c8f31352710563.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/2cxhb1352710563.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/3is4m1352710563.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  0.956956364  0.912728947  0.869626122  0.824126139
 [6]  0.780964125  0.738660353  0.693959423  0.647394035  0.598964191
[11]  0.555595015  0.517286508  0.480635296  0.439840847  0.403988688
[16]  0.367071126  0.331278156  0.294686133  0.257028707  0.220762224
[21]  0.180174937  0.144381967  0.113531288  0.085018579  0.059110190
[26]  0.031070994  0.005636119 -0.018141462 -0.044049850 -0.066821216
[31] -0.091190688 -0.116625563 -0.142859492 -0.167169774 -0.189674789
[36] -0.209841834 -0.227670909 -0.246831739 -0.264068922 -0.278849758
[41] -0.292772352 -0.303824274 -0.316740653 -0.331255138 -0.345769623
[46] -0.358094111 -0.371217652 -0.381204170 -0.389533393
> (mypacf <- c(rpacf$acf))
 [1]  0.956956364 -0.036048604 -0.009569897 -0.051916052  0.003865919
 [6] -0.015568350 -0.051649869 -0.049179968 -0.050537357  0.032439057
[11]  0.030522697 -0.006024305 -0.078556262  0.033407067 -0.036597174
[16] -0.008729117 -0.049407597 -0.044614175 -0.011110902 -0.077075468
[21]  0.032607364  0.016021868  0.005567218  0.001537240 -0.048756006
[26]  0.002613478 -0.008875975 -0.056785986 -0.001588222 -0.055340980
[31] -0.032941153 -0.028902060 -0.012824150 -0.005957981 -0.004625435
[36]  0.002785216 -0.040881249 -0.015245909  0.001677764 -0.024615587
[41] -0.009982503 -0.047137731 -0.049529024 -0.019092512 -0.004475100
[46] -0.043487442  0.010260211 -0.016140665
> 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/4v4d71352710563.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/57q651352710563.tab") 
> 
> try(system("convert tmp/1c8f31352710563.ps tmp/1c8f31352710563.png",intern=TRUE))
character(0)
> try(system("convert tmp/2cxhb1352710563.ps tmp/2cxhb1352710563.png",intern=TRUE))
character(0)
> try(system("convert tmp/3is4m1352710563.ps tmp/3is4m1352710563.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  2.516   0.536   3.030