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(12.6,15.7,13.2,20.3,12.8,8,0.9,3.6,14.1,21.7,24.5,18.9,13.9,11,5.8,15.5,22.4,31.7,30.3,31.4,20.2,19.7,10.8,13.2,15.1,15.6,15.5,12.7,10.9,10,9.1,10.3,16.9,22,27.6,28.9,31,32.9,38.1,28.8,29,21.8,28.8,25.6,28.2,20.2,17.9,16.3,13.2,8.1,4.5,-0.1,0,2.3,2.8,2.9,0.1,3.5,8.6,13.8)
> par7 = '0.95'
> par6 = 'MA'
> par5 = '12'
> par4 = '2'
> par3 = '2'
> 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$_version), Office for Research Development and Education, URL http://www.wessa.net/rwasp_YOURPAGE.wasp/
> #Source of accompanying publication: Office for Research, Development, and Education
> #Technical description: 
> if (par1 == 'Default') {
+ par1 = 10*log10(length(x))
+ } else {
+ par1 <- as.numeric(par1)
+ }
> par2 <- as.numeric(par2)
> par3 <- as.numeric(par3)
> par4 <- as.numeric(par4)
> par5 <- as.numeric(par5)
> if (par6 == 'White Noise') par6 <- 'white' else par6 <- 'ma'
> par7 <- as.numeric(par7)
> if (par2 == 0) {
+ x <- log(x)
+ } else {
+ x <- (x ^ par2 - 1) / par2
+ }
> if (par3 > 0) x <- diff(x,lag=1,difference=par3)
> if (par4 > 0) x <- diff(x,lag=par5,difference=par4)
> postscript(file="/var/www/html/rcomp/tmp/1p8ns1261239684.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> racf <- acf(x, par1, main='Autocorrelation', xlab='time lag', ylab='ACF', ci.type=par6, ci=par7, sub=paste('(lambda=',par2,', d=',par3,', D=',par4,', CI=', par7, ', CI type=',par6,')',sep=''))
> dev.off()
null device 
          1 
> postscript(file="/var/www/html/rcomp/tmp/2nm9j1261239684.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> rpacf <- pacf(x,par1,main='Partial Autocorrelation',xlab='lags',ylab='PACF')
> dev.off()
null device 
          1 
> (myacf <- c(racf$acf))
 [1]  1.000000000 -0.421429573  0.423305796 -0.553667803  0.104905486
 [6] -0.254528531  0.216450628 -0.160242149  0.238665953 -0.022316313
[11]  0.092541451 -0.011255919 -0.219296222  0.016428264 -0.121732395
[16]  0.160141262 -0.068939354  0.182732935 -0.182003616  0.266610119
[21] -0.271469282  0.281301396 -0.314365079  0.198648099 -0.204374942
[26]  0.184739128 -0.041332698  0.079588695 -0.070039544 -0.014465278
[31] -0.055333756  0.023805801  0.015924712  0.001002731
> (mypacf <- c(rpacf$acf))
 [1] -0.421429573  0.298764315 -0.404095916 -0.379915309 -0.082064171
 [6] -0.016105168 -0.329888794 -0.091005090  0.275152286 -0.091505605
[11] -0.040299280 -0.137335858 -0.047314579 -0.040005680 -0.090745116
[16] -0.206610999  0.016865197 -0.118986558  0.006775349 -0.057957297
[21]  0.156100809  0.013824353 -0.083868857  0.023988743  0.014362851
[26]  0.163261902 -0.104906734 -0.093046398  0.055805696 -0.064708424
[31] -0.014763247 -0.001598495  0.104546344
> 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/3o6oy1261239684.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/4o94r1261239684.tab") 
> try(system("convert tmp/1p8ns1261239684.ps tmp/1p8ns1261239684.png",intern=TRUE))
character(0)
> try(system("convert tmp/2nm9j1261239684.ps tmp/2nm9j1261239684.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  0.541   0.312   0.668