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(123.06,123.39,124.02,124.05,123.99,124.46,124.46,124.6,124.84,124.84,124.99,125.02,128.27,128.38,128.47,128.52,128.71,128.92,128.92,128.82,128.97,129.04,128.95,129.39,129.39,129.48,130.16,129.89,129.85,129.9,129.9,129.57,129.54,129.57,128.97,129.01,129.01,128.72,128.32,128.39,128.33,128.44,128.44,128.6,128.3,128.56,128.01,128.01,128.01,128.26,128.38,128.36,128.48,128.46,128.46,129.56,129.66,129.47,129.41,129.48,129.48,130.17,129.77,129.87,129.97,130.05,130.05,129.89,130.33,130.6,131.46,131.73)
> 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. 1.0.44 ()
> #Author: Dr. Ian E. Holliday
> #To cite this work: Ian E. Holliday, 2009, YOUR SOFTWARE TITLE (vNUMBER) in Free Statistics Software (v$_version), Office for Research Development and Education, URL http://www.wessa.net/rwasp_YOURPAGE.wasp/
> #Source of accompanying publication: 
> #Technical description: 
> 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/1ea9g1322084550.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/28d581322084550.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/3dcuu1322084550.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  0.900302713  0.807564943  0.732268087  0.656573920
 [6]  0.578691600  0.502893654  0.421905558  0.339379257  0.262619751
[11]  0.183882729  0.093610499  0.005774834 -0.021670403 -0.049122431
[16] -0.083821508 -0.119630689 -0.153888046 -0.168002893 -0.181691414
[21] -0.195382699 -0.204313829 -0.211354919 -0.211068075 -0.198588614
[26] -0.184218403 -0.165181354 -0.133957689 -0.103936181 -0.077296930
[31] -0.050107167 -0.021065733  0.002244197  0.029350787  0.057175775
[36]  0.076906470  0.092102962  0.111324673  0.124081402  0.119064093
[41]  0.117083954  0.111129875  0.104083614  0.096309759  0.079108241
[46]  0.052785935  0.028362117  0.002118129 -0.027041567
> (mypacf <- c(rpacf$acf))
 [1]  0.900302713 -0.015729493  0.041921689 -0.040315548 -0.049956281
 [6] -0.038553375 -0.078828829 -0.065029110 -0.035493961 -0.071901575
[11] -0.124777382 -0.074223169  0.237087811 -0.019397315 -0.035805853
[16] -0.055689117 -0.046091774  0.067683887 -0.052967642 -0.035453619
[21] -0.003017565 -0.038274158 -0.024716248  0.028999845  0.088060697
[26]  0.031699070  0.046698824 -0.025592478 -0.017452213  0.056570106
[31] -0.002732362 -0.034699067  0.024705127 -0.003773861 -0.016231934
[36]  0.005579194  0.054671891  0.007345553 -0.062177523 -0.005937342
[41] -0.028071851  0.030418105 -0.002178846 -0.067064776 -0.040989226
[46] -0.009204562 -0.031376790 -0.022366032
> 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/4bihz1322084550.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/5ut851322084550.tab") 
> 
> try(system("convert tmp/1ea9g1322084550.ps tmp/1ea9g1322084550.png",intern=TRUE))
character(0)
> try(system("convert tmp/28d581322084550.ps tmp/28d581322084550.png",intern=TRUE))
character(0)
> try(system("convert tmp/3dcuu1322084550.ps tmp/3dcuu1322084550.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  0.920   0.164   1.078