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(80.2,74.8,77.8,73,72,75.8,72.6,71.9,74.8,72.9,72.9,79.9,74,76,69.6,77.3,75.2,75.8,77.6,76.7,77,77.9,76.7,71.9,73.4,72.5,73.7,69.5,74.7,72.5,72.1,70.7,71.4,69.5,73.5,72.4,74.5,72.2,73,73.3,71.3,73.6,71.3,71.2,81.4,76.1,71.1,75.7,70,68.5,56.7,57.9,58.8,59.3,61.3,62.9,61.4,64.5,63.8,61.6)
> par7 = '0.95'
> par6 = 'MA'
> 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$_version), Office for Research Development and Education, URL http://www.wessa.net/rwasp_YOURPAGE.wasp/
> #Source of accompanying publication: Office for Research, Development, and Education
> #Technical description: 
> if (par1 == 'Default') {
+ par1 = 10*log10(length(x))
+ } else {
+ par1 <- as.numeric(par1)
+ }
> par2 <- as.numeric(par2)
> par3 <- as.numeric(par3)
> par4 <- as.numeric(par4)
> par5 <- as.numeric(par5)
> if (par6 == 'White Noise') par6 <- 'white' else par6 <- 'ma'
> par7 <- as.numeric(par7)
> if (par2 == 0) {
+ x <- log(x)
+ } else {
+ x <- (x ^ par2 - 1) / par2
+ }
> if (par3 > 0) x <- diff(x,lag=1,difference=par3)
> if (par4 > 0) x <- diff(x,lag=par5,difference=par4)
> postscript(file="/var/www/html/rcomp/tmp/1jqhe1261134153.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> racf <- acf(x, par1, main='Autocorrelation', xlab='time lag', ylab='ACF', ci.type=par6, ci=par7, sub=paste('(lambda=',par2,', d=',par3,', D=',par4,', CI=', par7, ', CI type=',par6,')',sep=''))
> dev.off()
null device 
          1 
> postscript(file="/var/www/html/rcomp/tmp/2ai9j1261134153.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> rpacf <- pacf(x,par1,main='Partial Autocorrelation',xlab='lags',ylab='PACF')
> dev.off()
null device 
          1 
> (myacf <- c(racf$acf))
 [1]  1.00000000 -0.40987313  0.10075394  0.02902307 -0.01969983 -0.06261245
 [7] -0.04284665 -0.13458675  0.07192373 -0.06589251  0.10848595  0.08756002
[13] -0.30734687  0.33733842 -0.23070747  0.03274666 -0.04139328  0.04212200
[19] -0.08678716  0.15076918 -0.07652606  0.06153316 -0.18741160  0.23205234
[25] -0.07113728 -0.05212175  0.11884380 -0.01040997 -0.01350919  0.10038166
[31] -0.10779118 -0.03120063 -0.02676951  0.00817589  0.07696721 -0.27708309
[37]  0.28703474
> (mypacf <- c(rpacf$acf))
 [1] -0.409873127 -0.080819370  0.049035510  0.023157068 -0.080182625
 [6] -0.127692697 -0.240945381 -0.083706020 -0.059104883  0.092389522
[11]  0.197691807 -0.320499439  0.019572191 -0.154646673 -0.073846772
[16] -0.046137368  0.046603596 -0.085872673  0.001480579 -0.012228918
[21] -0.090653497 -0.242885972  0.093223523  0.010576854  0.107346839
[26]  0.051829595  0.040948439 -0.097788216  0.087666019 -0.085912848
[31]  0.016110546 -0.069070848  0.062084657  0.049838186 -0.149611262
[36] -0.020811283
> 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/3j71p1261134153.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/439fc1261134153.tab") 
> 
> try(system("convert tmp/1jqhe1261134153.ps tmp/1jqhe1261134153.png",intern=TRUE))
character(0)
> try(system("convert tmp/2ai9j1261134153.ps tmp/2ai9j1261134153.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  0.547   0.313   0.677