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(6.6,6.5,6.3,6.2,6.3,6.5,6.6,6.4,6.2,6.3,6.6,7.1,7.2,7.3,7.3,7.3,7.4,7.3,7.4,7.4,7.6,7.6,7.7,7.7,7.8,7.8,8,8.1,8.1,8.2,8.1,8.1,8.1,8,8.2,8.4,8.4,8.5,8.6,8.5,8.3,7.8,7.8,8,8.6,8.9,8.9,8.6,8.3,8.3,8.3,8.4,8.5,8.4,8.6,8.5,8.5,8.5,8.5,8.5,8.5,8.5,8.5,8.6,8.6,8.6,8.6,8.4,8,7.9,8,8,8,8,7.9,7.9,7.9,8,7.9,7.5,7.2,7,6.9,7.1,7.1,7.2,7.1,6.9,6.8,6.7,6.7,6.9,7.3,7.4,7.3,7.1,7,7.1,7.5,7.7,7.8,7.7,7.7,7.8,8,8.1,8.1,8,8.1,8.2,8.3,8.4,8.5,8.5,8.5,8.5,8.5,8.3,8.2,8.1,7.9,7.6,7.3,7.1,7,7,7,7,6.9,6.8,6.7,6.6)
> 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/1c5ty1324309828.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/2k7yd1324309828.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/3u9wq1324309828.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  0.95183860  0.87516544  0.79322911  0.72871664  0.68328402
 [7]  0.64014099  0.58562924  0.51219605  0.42716375  0.34445703  0.27178703
[13]  0.21366091  0.16245394  0.11702132  0.07289189  0.03010165 -0.01170220
[19] -0.05179966 -0.08600037 -0.11655790 -0.14692104
> (mypacf <- c(rpacf$acf))
 [1]  0.9518386035 -0.3279810485 -0.0097227754  0.1683576816  0.0685615852
 [6] -0.1159477391 -0.1317626668 -0.1373976923 -0.0703356635 -0.0106278054
[11] -0.0287181450  0.0153260243 -0.0305250168  0.0470796245  0.0079877235
[16] -0.0043818147 -0.0410011184 -0.0408747319  0.0005434132 -0.0492843164
[21] -0.0798168470
> 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/451b41324309828.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/5bmgx1324309828.tab") 
> 
> try(system("convert tmp/1c5ty1324309828.ps tmp/1c5ty1324309828.png",intern=TRUE))
character(0)
> try(system("convert tmp/2k7yd1324309828.ps tmp/2k7yd1324309828.png",intern=TRUE))
character(0)
> try(system("convert tmp/3u9wq1324309828.ps tmp/3u9wq1324309828.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  0.953   0.192   1.145