R version 2.9.0 (2009-04-17)
Copyright (C) 2009 The R Foundation for Statistical Computing
ISBN 3-900051-07-0

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> x <- c(9.4,9.4,9.5,9.5,9.4,9.4,9.3,9.4,9.4,9.2,9.1,9.1,9.1,9.0,9.0,8.9,8.8,8.7,8.5,8.3,8.1,7.9,7.8,7.6,7.4,7.2,7.0,7.0,6.8,6.8,6.7,6.8,6.7,6.7,6.7,6.5,6.3,6.3,6.3,6.5,6.6,6.5,6.3,6.3,6.5,7.0,7.1,7.3,7.3,7.4,7.4,7.3,7.4,7.5,7.7,7.7,7.7,7.7,7.7,7.8,8.0,8.1,8.1,8.2,8.2,8.2,8.1,8.1,8.2,8.3,8.3,8.4,8.5,8.5,8.4,8.0,7.9,8.1,8.5,8.8,8.8,8.6,8.3,8.3,8.3,8.4,8.4,8.5,8.6,8.6,8.6,8.6,8.6,8.5,8.4,8.4,8.4,8.5,8.5,8.6,8.6,8.4,8.2,8.0,8.0,8.0,8.0,7.9,7.9,7.8,7.8,8.0,7.8,7.4,7.2,7.0,7.0,7.2,7.2,7.2,7.0,6.9,6.8,6.8,6.8,6.9,7.2,7.2,7.2,7.1,7.2,7.3,7.5,7.6,7.7,7.7,7.7,7.8,8.0,8.1,8.1,8.0,8.1,8.2,8.3,8.4,8.4,8.4,8.5,8.5,8.6,8.6,8.5,8.5)
> par8 = ''
> par7 = '0.95'
> par6 = 'White Noise'
> par5 = '12'
> par4 = '0'
> par3 = '1'
> 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/www/html/rcomp/tmp/1l6mv1293475844.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/html/rcomp/tmp/2vf3g1293475844.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/html/rcomp/tmp/3vf3g1293475844.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  0.490130280  0.144270628 -0.140976609 -0.087507402
 [6]  0.140668180  0.290404165  0.322271023  0.247384524  0.197665811
[11]  0.101386696  0.090468318  0.061722760  0.008648342  0.047855803
[16]  0.051408902  0.029794216 -0.016568792  0.019492696  0.030596131
[21]  0.045055270 -0.086668476
> (mypacf <- c(rpacf$acf))
 [1]  0.490130280 -0.126297133 -0.212286404  0.128716672  0.235274358
 [6]  0.102043157  0.107077307  0.125035130  0.160575166 -0.002163419
[11]  0.047889032 -0.009971973 -0.125214253 -0.002191662 -0.063928069
[16] -0.144708503 -0.111473919  0.050002534 -0.020354096 -0.025894080
[21] -0.149572451
> lengthx <- length(x)
> sqrtn <- sqrt(lengthx)
> 
> #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/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/html/rcomp/tmp/44jrt1293475844.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/html/rcomp/tmp/5kyis1293475844.tab") 
> 
> try(system("convert tmp/1l6mv1293475844.ps tmp/1l6mv1293475844.png",intern=TRUE))
character(0)
> try(system("convert tmp/2vf3g1293475844.ps tmp/2vf3g1293475844.png",intern=TRUE))
character(0)
> try(system("convert tmp/3vf3g1293475844.ps tmp/3vf3g1293475844.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  0.686   0.461   2.447