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(14.9,18.6,19.1,18.8,18.2,18,19,20.7,21.2,20.7,19.6,18.6,18.7,23.8,24.9,24.8,23.8,22.3,21.7,20.7,19.7,18.4,17.4,17,18,23.8,25.5,25.6,23.7,22,21.3,20.7,20.4,20.3,20.4,19.8,19.5,23.1,23.5,23.5,22.9,21.9,21.5,20.5,20.2,19.4,19.2,18.8,18.8,22.6,23.3,23,21.4,19.9,18.8,18.6,18.4,18.6,19.9,19.2,18.4)
> par7 = '0.95'
> par6 = 'MA'
> par5 = '12'
> par4 = '1'
> par3 = '0'
> 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$_version), Office for Research Development and Education, URL http://www.wessa.net/rwasp_YOURPAGE.wasp/
> #Source of accompanying publication: Office for Research, Development, and Education
> #Technical description: 
> if (par1 == 'Default') {
+ par1 = 10*log10(length(x))
+ } else {
+ par1 <- as.numeric(par1)
+ }
> par2 <- as.numeric(par2)
> par3 <- as.numeric(par3)
> par4 <- as.numeric(par4)
> par5 <- as.numeric(par5)
> if (par6 == 'White Noise') par6 <- 'white' else par6 <- 'ma'
> par7 <- as.numeric(par7)
> if (par2 == 0) {
+ x <- log(x)
+ } else {
+ x <- (x ^ par2 - 1) / par2
+ }
> if (par3 > 0) x <- diff(x,lag=1,difference=par3)
> if (par4 > 0) x <- diff(x,lag=par5,difference=par4)
> postscript(file="/var/www/html/rcomp/tmp/13wlq1259231133.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> racf <- acf(x, par1, main='Autocorrelation', xlab='time lag', ylab='ACF', ci.type=par6, ci=par7, sub=paste('(lambda=',par2,', d=',par3,', D=',par4,', CI=', par7, ', CI type=',par6,')',sep=''))
> dev.off()
null device 
          1 
> postscript(file="/var/www/html/rcomp/tmp/24qy81259231133.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> rpacf <- pacf(x,par1,main='Partial Autocorrelation',xlab='lags',ylab='PACF')
> dev.off()
null device 
          1 
> (myacf <- c(racf$acf))
 [1]  1.00000000  0.88744155  0.64729459  0.36443721  0.11326820 -0.05360721
 [7] -0.12095023 -0.12036573 -0.08308283 -0.05966099 -0.06462926 -0.08621409
[13] -0.10420842 -0.08592184 -0.03056112  0.04550768  0.11982298  0.17727121
[19]  0.18441049  0.14808784  0.08992986  0.03327488 -0.01682532 -0.05991149
[25] -0.08713260 -0.09677689 -0.08187208 -0.06216600 -0.04934870 -0.05293921
[31] -0.05469272 -0.04742819 -0.03744990 -0.04145792 -0.05569472 -0.08867735
[37] -0.14136607
> (mypacf <- c(rpacf$acf))
 [1]  0.887441550 -0.660200369 -0.027973503  0.071423471  0.107690708
 [6]  0.046616121 -0.116589427  0.014023305 -0.177744440  0.029280123
[11]  0.059567666  0.030695183  0.160168414 -0.063707095  0.019644192
[16] -0.003693533  0.094227854 -0.144262417  0.042838054  0.068863638
[21] -0.026901005 -0.101396573 -0.098163784  0.125245844 -0.012328416
[26]  0.137224797 -0.172899991 -0.047772003 -0.042825618  0.112476571
[31]  0.065087603 -0.159955161 -0.084775450 -0.100731112 -0.049386259
[36] -0.071556290
> 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/3oxr21259231133.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/4aqk51259231133.tab") 
> system("convert tmp/13wlq1259231133.ps tmp/13wlq1259231133.png")
> system("convert tmp/24qy81259231133.ps tmp/24qy81259231133.png")
> 
> 
> proc.time()
   user  system elapsed 
  0.555   0.306   0.672