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 = '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/1207o1333199492.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/20hte1333199492.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/3a6s51333199492.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  0.734949854  0.314713932  0.011974058 -0.086999637
 [6] -0.041300886  0.001530479 -0.079380327 -0.180731797 -0.171771781
[11]  0.014941078  0.320371455  0.504802054  0.279285258 -0.063083251
[16] -0.293095827 -0.357372131 -0.296816056 -0.246683227 -0.297311454
[21] -0.370296859 -0.347443624 -0.178386376  0.093583474  0.265485895
[26]  0.124858520 -0.104862003 -0.247194443 -0.254950305 -0.166323901
[31] -0.092845054 -0.106155405 -0.137126207 -0.095371091  0.057354319
[36]  0.278363455  0.416033806  0.306377305  0.118825493 -0.014608038
[41] -0.049896896 -0.008021908  0.026702507 -0.008931334 -0.055125828
[46] -0.041278182  0.056615976  0.198440794  0.279475893
> (mypacf <- c(rpacf$acf))
 [1]  0.7349498545 -0.4902424446  0.0789687831  0.0659368847  0.0392594344
 [6] -0.1008412071 -0.2179126397  0.0630093804  0.1060676010  0.2454199580
[11]  0.2892233321 -0.0234440177 -0.6391238715  0.2132106671 -0.0460119160
[16] -0.2257936099 -0.0820204683 -0.0895997756  0.0280677937 -0.1073943160
[21] -0.0072694497 -0.0748217789 -0.0521161147 -0.0062944293  0.0067035081
[26] -0.0379024287 -0.1000281492  0.0758675549 -0.0579403836  0.0118902478
[31] -0.0096850045  0.0613237789 -0.0078806432  0.0014274764 -0.0020274289
[36]  0.0592602632 -0.0241734488 -0.0422189563 -0.0238067333 -0.0688342552
[41]  0.0140234869 -0.0178023320 -0.0712972234 -0.0229821346 -0.0080185006
[46] -0.0278363387 -0.0832000207  0.0004109005
> 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/4m5qp1333199492.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/50es71333199492.tab") 
> 
> try(system("convert tmp/1207o1333199492.ps tmp/1207o1333199492.png",intern=TRUE))
character(0)
> try(system("convert tmp/20hte1333199492.ps tmp/20hte1333199492.png",intern=TRUE))
character(0)
> try(system("convert tmp/3a6s51333199492.ps tmp/3a6s51333199492.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  1.027   0.223   1.284