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(252.5,251.1,255.1,258.3,255.3,261.1,253.8,252.9,253.9,255.5,262,262.8,263.3,262.5,269.2,270.8,274.1,273,267.3,267.1,268.2,270.2,271.5,281,280.1,281.5,285.9,289.8,292.9,291.2,291.8,289.8,292.5,290.3,297.5,307.5,304.7,304.6,310.7,310.7,315.7,314.7,312.2,312.8,314.3,319.7,319.9,329.5,326.9,329.7,335.7,337.2,339.7,338.3,339.2,342.5,342.2,338.3,339,345.9)
> par7 = '0.95'
> par6 = 'White Noise'
> par5 = '12'
> par4 = '1'
> par3 = '1'
> par2 = '1'
> par1 = '36'
> #'GNU S' R Code compiled by R2WASP v. 1.0.44 ()
> #Author: Prof. Dr. P. Wessa
> #To cite this work: AUTHOR(S), (YEAR), YOUR SOFTWARE TITLE (vNUMBER) in Free Statistics Software (v$_version), Office for Research Development and Education, URL http://www.wessa.net/rwasp_YOURPAGE.wasp/
> #Source of accompanying publication: Office for Research, Development, and Education
> #Technical description: 
> if (par1 == 'Default') {
+ par1 = 10*log10(length(x))
+ } else {
+ par1 <- as.numeric(par1)
+ }
> par2 <- as.numeric(par2)
> par3 <- as.numeric(par3)
> par4 <- as.numeric(par4)
> par5 <- as.numeric(par5)
> if (par6 == 'White Noise') par6 <- 'white' else par6 <- 'ma'
> par7 <- as.numeric(par7)
> if (par2 == 0) {
+ x <- log(x)
+ } else {
+ x <- (x ^ par2 - 1) / par2
+ }
> if (par3 > 0) x <- diff(x,lag=1,difference=par3)
> if (par4 > 0) x <- diff(x,lag=par5,difference=par4)
> postscript(file="/var/www/html/rcomp/tmp/1i6ax1259342929.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> racf <- acf(x, par1, main='Autocorrelation', xlab='time lag', ylab='ACF', ci.type=par6, ci=par7, sub=paste('(lambda=',par2,', d=',par3,', D=',par4,', CI=', par7, ', CI type=',par6,')',sep=''))
> dev.off()
null device 
          1 
> postscript(file="/var/www/html/rcomp/tmp/2hn581259342929.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> rpacf <- pacf(x,par1,main='Partial Autocorrelation',xlab='lags',ylab='PACF')
> dev.off()
null device 
          1 
> (myacf <- c(racf$acf))
 [1]  1.00000000 -0.43325856  0.15626086 -0.24095441  0.14286628  0.10451492
 [7] -0.19350196  0.24870166 -0.32243638  0.14991085 -0.09472780  0.37723210
[13] -0.37966713  0.07683680 -0.04873065  0.14203780 -0.06815156 -0.06657399
[19]  0.10351250 -0.11544723  0.20936292 -0.07099643  0.15376045 -0.32793073
[25]  0.18859832 -0.01727938  0.02419158 -0.06434999 -0.08972592  0.09121993
[31] -0.09496437  0.12877194 -0.08528652  0.01158200 -0.15947210  0.15329664
[37] -0.06054053
> (mypacf <- c(rpacf$acf))
 [1] -0.433258561 -0.038720454 -0.231062404 -0.059311835  0.196431731
 [6] -0.144359710  0.186178568 -0.144466297 -0.166218850  0.006032312
[11]  0.373564230 -0.253592676 -0.022098394  0.021324123  0.005575766
[16] -0.113549751  0.093009932 -0.103619464  0.142532076  0.171831260
[21]  0.040598660  0.051037825 -0.010081529 -0.099339736  0.038859661
[26] -0.074431708 -0.020546025 -0.039674681 -0.098578794 -0.063028159
[31] -0.019328099 -0.048968299  0.012794497 -0.088221921 -0.077105751
[36] -0.054246193
> 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/3p5mh1259342929.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/4n0td1259342929.tab") 
> 
> system("convert tmp/1i6ax1259342929.ps tmp/1i6ax1259342929.png")
> system("convert tmp/2hn581259342929.ps tmp/2hn581259342929.png")
> 
> 
> proc.time()
   user  system elapsed 
  0.549   0.314   1.158