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(125326,122716,116615,113719,110737,112093,143565,149946,149147,134339,122683,115614,116566,111272,104609,101802,94542,93051,124129,130374,123946,114971,105531,104919,104782,101281,94545,93248,84031,87486,115867,120327,117008,108811,104519,106758,109337,109078,108293,106534,99197,103493,130676,137448,134704,123725,118277,121225,120528,118240,112514,107304,100001,102082,130455,135574,132540,119920,112454,109415,109843,106365,102304,97968,92462,92286,120092,126656,124144,114045,108120,105698)
> 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. 1.0.44 ()
> #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/15fec1333199734.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/288d11333199734.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/3y2251333199734.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  0.307423218 -0.211632386 -0.379093103 -0.272502931
 [6] -0.003647709  0.156254856  0.027228989 -0.208680770 -0.317394721
[11] -0.207676830  0.249725547  0.792939520  0.238560989 -0.198483344
[16] -0.302009538 -0.225662103  0.018227722  0.112674462  0.029582923
[21] -0.168290008 -0.263661611 -0.177772967  0.198026002  0.607724427
[26]  0.175650970 -0.151752649 -0.245534780 -0.167265923  0.017642843
[31]  0.091499439  0.021138560 -0.128339148 -0.200437667 -0.124841776
[36]  0.158075152  0.472334200  0.148501000 -0.099356949 -0.178500749
[41] -0.133757317  0.002013035  0.058924661  0.003180365 -0.103898835
[46] -0.145433244 -0.070086566  0.115908876  0.342384252
> (mypacf <- c(rpacf$acf))
 [1]  3.074232e-01 -3.380944e-01 -2.345398e-01 -1.657934e-01 -2.381354e-02
 [6] -2.373636e-02 -1.765038e-01 -2.685878e-01 -3.272952e-01 -3.773100e-01
[11] -4.306823e-02  6.069247e-01 -3.211078e-01 -8.788772e-05  1.922983e-01
[16] -8.735336e-03  1.351062e-02 -1.290238e-01  6.192512e-02 -3.007100e-02
[21] -6.794699e-02  1.186855e-02 -9.988049e-02 -9.077447e-02 -3.157230e-02
[26]  2.763206e-02 -1.622641e-01 -4.315355e-03 -8.881995e-02 -1.801840e-04
[31] -1.121353e-01 -6.554729e-02  3.710220e-02 -5.901064e-02 -6.518476e-02
[36]  1.414971e-02  4.428618e-02 -7.125490e-03  3.988347e-02 -1.883348e-02
[41]  1.604814e-03  9.868863e-03 -5.289388e-02  2.161788e-02 -6.423775e-02
[46]  5.401455e-02 -8.372054e-02 -7.679151e-02
> 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/4jr901333199734.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/5thb81333199734.tab") 
> 
> try(system("convert tmp/15fec1333199734.ps tmp/15fec1333199734.png",intern=TRUE))
character(0)
> try(system("convert tmp/288d11333199734.ps tmp/288d11333199734.png",intern=TRUE))
character(0)
> try(system("convert tmp/3y2251333199734.ps tmp/3y2251333199734.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  0.999   0.230   1.305