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(20.89,21.04,21.07,21.12,21.25,21.24,21.24,21.22,21.29,21.25,21.15,21.16,21.16,21.52,21.59,21.6,21.68,21.67,21.67,21.65,21.74,21.72,21.84,21.94,21.94,21.95,21.96,22.1,22.13,22.18,22.18,22.27,22.3,22.04,22.05,22.06,22.06,22.06,21.97,22.03,22.08,22.13,22.13,22.4,22.4,22.12,22.22,22.14,22.14,22.19,22.29,22.24,22.26,22.29,22.29,22.29,22.29,22.35,22.39,22.43,22.43,22.11,22.12,22.05,22.05,22.08,22.08,22.09,22.09,22.24,22.25,22.24)
> 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/1e3z61352710763.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/2qejo1352710763.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/3igrb1352710763.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 -0.025753677 -0.069325404  0.043990063 -0.088558759
 [6] -0.038130912 -0.138035795  0.125747320 -0.156270311  0.158064014
[11] -0.038114484 -0.081616576  0.205048415 -0.098484490  0.143670192
[16]  0.003024037  0.199336627 -0.088893819 -0.098104651  0.081782604
[21] -0.208639193  0.046150028 -0.104149384  0.149841202 -0.073821661
[26] -0.125414558  0.159383324  0.083639875  0.214209778 -0.075913891
[31]  0.166408352 -0.069982622 -0.246334514 -0.004789144 -0.151850494
[36]  0.073461039 -0.042975808  0.023350753 -0.022819259 -0.016738512
[41]  0.020280098 -0.105485766  0.102691018 -0.040190010 -0.034768627
[46]  0.003048618  0.029824243 -0.041699715 -0.197380666
> (mypacf <- c(rpacf$acf))
 [1] -0.025753677 -0.070035107  0.040501364 -0.091867156 -0.036971803
 [6] -0.157097228  0.124685903 -0.190873343  0.203725171 -0.144359555
[11]  0.012722296  0.121691805 -0.051009189  0.143454984  0.030881955
[16]  0.217902063 -0.092681754  0.013289394 -0.012607726 -0.061795825
[21] -0.046430742 -0.041349602  0.109085088 -0.152480446 -0.102478927
[26]  0.055516154  0.205548439  0.079976331  0.052729033  0.129206614
[31] -0.073771221 -0.201768976 -0.010749312 -0.024434318 -0.040409969
[36]  0.029271903 -0.087681401 -0.041737853 -0.141287454 -0.030870843
[41]  0.031760581 -0.153487543 -0.019385370 -0.116530261 -0.003512990
[46]  0.042368550  0.060787751  0.001622448
> 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/4f48y1352710763.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/59b791352710763.tab") 
> 
> try(system("convert tmp/1e3z61352710763.ps tmp/1e3z61352710763.png",intern=TRUE))
character(0)
> try(system("convert tmp/2qejo1352710763.ps tmp/2qejo1352710763.png",intern=TRUE))
character(0)
> try(system("convert tmp/3igrb1352710763.ps tmp/3igrb1352710763.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  1.932   0.439   2.357