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(12.3,14.6,17.7,15.2,22.3,14.8,10,2.9,5.6,16.1,23.7,26.5,20.9,15.9,13,7.8,17.5,24.4,33.7,32.3,33.4,22.2,21.7,12.8,15.2,17.1,17.6,17.5,14.7,12.9,12,11.1,12.3,18.9,24,29.6,30.9,33,34.9,40.1,30.8,31,23.8,30.8,27.6,30.2,22.2,19.9,18.3,15.2,10.1,6.5,1.9,2,4.3,4.8,4.9,2.1,5.5,10.6)
> par7 = '0.95'
> par6 = 'White Noise'
> par5 = '12'
> par4 = '0'
> 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$_version), Office for Research Development and Education, URL http://www.wessa.net/rwasp_YOURPAGE.wasp/
> #Source of accompanying publication: Office for Research, Development, and Education
> #Technical description: 
> if (par1 == 'Default') {
+ par1 = 10*log10(length(x))
+ } else {
+ par1 <- as.numeric(par1)
+ }
> par2 <- as.numeric(par2)
> par3 <- as.numeric(par3)
> par4 <- as.numeric(par4)
> par5 <- as.numeric(par5)
> if (par6 == 'White Noise') par6 <- 'white' else par6 <- 'ma'
> par7 <- as.numeric(par7)
> if (par2 == 0) {
+ x <- log(x)
+ } else {
+ x <- (x ^ par2 - 1) / par2
+ }
> if (par3 > 0) x <- diff(x,lag=1,difference=par3)
> if (par4 > 0) x <- diff(x,lag=par5,difference=par4)
> postscript(file="/var/www/html/rcomp/tmp/1dgiq1259965829.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> racf <- acf(x, par1, main='Autocorrelation', xlab='time lag', ylab='ACF', ci.type=par6, ci=par7, sub=paste('(lambda=',par2,', d=',par3,', D=',par4,', CI=', par7, ', CI type=',par6,')',sep=''))
> dev.off()
null device 
          1 
> postscript(file="/var/www/html/rcomp/tmp/2jdec1259965829.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> rpacf <- pacf(x,par1,main='Partial Autocorrelation',xlab='lags',ylab='PACF')
> dev.off()
null device 
          1 
> (myacf <- c(racf$acf))
 [1]  1.000000000  0.157517546  0.235489943 -0.430112070 -0.183150239
 [6] -0.241301637  0.096671479  0.100941849  0.260680599  0.102120984
[11] -0.034303224 -0.260304011 -0.288794182 -0.260027878 -0.059481894
[16]  0.053581725  0.152998219  0.070545639 -0.008697805  0.007268832
[21] -0.073860129  0.095219201 -0.119684899  0.134391007 -0.041076263
[26]  0.189507659  0.015512548  0.095891798 -0.033503495  0.057254510
[31] -0.088991626 -0.079570252 -0.100942775 -0.026981797  0.044630754
[36]  0.077540079 -0.078169251
> (mypacf <- c(rpacf$acf))
 [1]  0.157517546  0.216038464 -0.530532448 -0.095020296  0.091023175
 [6] -0.014445553  0.002392614  0.151261993  0.050653901 -0.165505889
[11] -0.162933751 -0.099014237 -0.175965133 -0.130552158 -0.065569871
[16] -0.063165360 -0.107903577 -0.075966712  0.201826215 -0.006683374
[21]  0.104361931 -0.145759537  0.049647641 -0.010962867 -0.072760401
[26]  0.018226494 -0.041121257  0.008904069  0.071058949 -0.061375842
[31] -0.111207254  0.074126877  0.009632796 -0.025147269  0.009896939
[36] -0.191602344
> 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/3itea1259965829.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/4n0zz1259965829.tab") 
> 
> system("convert tmp/1dgiq1259965829.ps tmp/1dgiq1259965829.png")
> system("convert tmp/2jdec1259965829.ps tmp/2jdec1259965829.png")
> 
> 
> proc.time()
   user  system elapsed 
  0.551   0.314   0.647