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(0.072,0.073,0.073,0.073,0.074,0.073,0.074,0.074,0.076,0.076,0.077,0.077,0.078,0.078,0.080,0.081,0.081,0.082,0.081,0.081,0.081,0.080,0.082,0.084,0.084,0.085,0.086,0.085,0.083,0.078,0.078,0.080,0.086,0.089,0.089,0.086,0.083,0.083,0.083,0.084,0.085,0.084,0.086,0.085,0.085,0.085,0.085,0.085,0.085,0.085,0.085,0.086,0.086,0.086,0.086,0.084,0.080,0.079,0.080,0.080,0.080,0.080,0.079,0.079,0.079,0.080,0.079,0.075,0.072,0.070,0.069,0.071,0.071,0.072,0.071,0.069,0.068,0.067,0.067,0.069,0.073,0.074,0.073,0.071,0.070,0.071,0.075,0.077,0.078,0.077,0.077,0.078,0.080,0.081,0.081,0.080,0.081,0.082,0.083,0.084,0.085,0.085,0.085,0.085,0.085,0.083,0.082,0.081,0.079,0.076,0.073,0.071,0.070,0.070,0.070,0.070,0.069,0.068,0.067,0.066)
> par8 = ''
> par7 = '0.95'
> par6 = 'White Noise'
> par5 = '12'
> par4 = '0'
> par3 = '0'
> par2 = '1'
> par1 = 'Default'
> #'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/1vbzx1324599761.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/2slgj1324599761.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/372rg1324599761.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]  1.00000000  0.94018847  0.84913369  0.75507152  0.68491231  0.64069437
 [7]  0.59708111  0.53892744  0.45938966  0.36938807  0.28033956  0.20088587
[13]  0.13163168  0.07209646  0.01940496 -0.02669111 -0.06523065 -0.10232856
[19] -0.13186194 -0.15694630 -0.17866687
> (mypacf <- c(rpacf$acf))
 [1]  0.940188466 -0.300060040 -0.006750494  0.167135279  0.091827174
 [6] -0.129688368 -0.122439560 -0.118954625 -0.061016454 -0.069954453
[11] -0.049809457 -0.042667756  0.007956599  0.010859923  0.025641015
[16]  0.030048117 -0.040291594  0.039516788 -0.015075098 -0.039934838
> 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/48e5t1324599761.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/5cvjw1324599761.tab") 
> 
> try(system("convert tmp/1vbzx1324599761.ps tmp/1vbzx1324599761.png",intern=TRUE))
character(0)
> try(system("convert tmp/2slgj1324599761.ps tmp/2slgj1324599761.png",intern=TRUE))
character(0)
> try(system("convert tmp/372rg1324599761.ps tmp/372rg1324599761.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  0.963   0.212   1.174