R version 2.12.0 (2010-10-15)
Copyright (C) 2010 The R Foundation for Statistical Computing
ISBN 3-900051-07-0
Platform: i486-pc-linux-gnu (32-bit)

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> x <- c(26548,26752,26967,27034,27056,27476,28497,29085,28720,29067,29249,29672,29761,30066,30315,30571,30757,30742,31310,31381,31470,31226,31081,31061,31114,30828,30418,30195,29877,29192,29876,29409,28458,28340,28164,28438,28053,27599,27226,27119,26625,26541,27023,26631,26154,26029,26008,26632,27010,27041,27244,26976,26715,27017,27714,27655,27103,27088,26968,27770,27616,27481,27279,26918,26503,26547,27467,27305,26259,26048,25743)
> par8 = ''
> par7 = '0.95'
> par6 = 'White Noise'
> par5 = '12'
> par4 = '1'
> 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/www/rcomp/tmp/1hlbn1293630948.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/www/rcomp/tmp/2rusq1293630948.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/www/rcomp/tmp/3rusq1293630948.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]  1.000000e+00  3.086088e-01  3.377605e-01  3.084874e-01  4.069799e-01
 [6]  3.094359e-01  2.888688e-01  1.924371e-01  1.496107e-01  1.281480e-01
[11]  5.132717e-02  1.089928e-01 -2.815412e-01 -6.736582e-02 -4.617999e-02
[16] -1.020865e-01 -3.479852e-01 -2.200864e-01 -2.371632e-01 -2.078363e-01
[21] -2.221408e-01 -3.208108e-01 -2.734927e-01 -2.835577e-01 -1.858027e-01
[26] -1.816635e-01 -1.688659e-01 -2.763432e-01 -4.257371e-02 -1.093492e-01
[31] -9.907892e-02 -7.810734e-02 -1.929391e-02  6.866475e-02  1.618608e-02
[36]  4.133190e-02  4.899983e-02  7.962558e-02  8.313753e-03  1.296655e-01
[41]  1.249072e-02  6.791065e-02  6.462014e-02  8.839794e-02  3.060376e-02
[46] -4.461004e-07  4.019870e-02  6.542511e-03 -3.032129e-02
> (mypacf <- c(rpacf$acf))
 [1]  0.308608758  0.268050033  0.177992073  0.270711152  0.103378587
 [6]  0.055813102 -0.065125491 -0.117785788 -0.084534293 -0.138225340
[11]  0.033399994 -0.449385214 -0.044832254  0.102667622  0.001264414
[16] -0.191384000 -0.000452964  0.044902062  0.017912416  0.074134841
[21] -0.106725700 -0.073897823  0.027715138 -0.108470830  0.027090425
[26]  0.126966473 -0.093370904 -0.029158501  0.001280533 -0.003982023
[31]  0.000770278  0.026101892  0.036112576 -0.105983663  0.024477839
[36] -0.016425071 -0.076935614 -0.087581577 -0.109444330 -0.122523432
[41]  0.047732974  0.040234802 -0.040858763  0.016254667  0.009738515
[46] -0.017492431 -0.010614878 -0.079579083
> lengthx <- length(x)
> sqrtn <- sqrt(lengthx)
> 
> #Note: the /var/www/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/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/www/rcomp/tmp/4vcre1293630948.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/www/rcomp/tmp/5gdp21293630948.tab") 
> 
> try(system("convert tmp/1hlbn1293630948.ps tmp/1hlbn1293630948.png",intern=TRUE))
character(0)
> try(system("convert tmp/2rusq1293630948.ps tmp/2rusq1293630948.png",intern=TRUE))
character(0)
> try(system("convert tmp/3rusq1293630948.ps tmp/3rusq1293630948.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  0.890   0.510   1.394