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(2.05,2.11,2.09,2.05,2.08,2.06,2.06,2.08,2.07,2.06,2.07,2.06,2.09,2.07,2.09,2.28,2.33,2.35,2.52,2.63,2.58,2.70,2.81,2.97,3.04,3.28,3.33,3.50,3.56,3.57,3.69,3.82,3.79,3.96,4.06,4.05,4.03,3.94,4.02,3.88,4.02,4.03,4.09,3.99,4.01,4.01,4.19,4.30,4.27,3.82,3.15,2.49,1.81,1.26,1.06,0.84,0.78,0.70,0.36,0.35)
> par7 = '0.95'
> par6 = 'White Noise'
> par5 = '12'
> par4 = '2'
> par3 = '1'
> par2 = '1'
> par1 = '60'
> #'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$_version), Office for Research Development and Education, URL http://www.wessa.net/rwasp_YOURPAGE.wasp/
> #Source of accompanying publication: Office for Research, Development, and Education
> #Technical description: 
> if (par1 == 'Default') {
+ par1 = 10*log10(length(x))
+ } else {
+ par1 <- as.numeric(par1)
+ }
> par2 <- as.numeric(par2)
> par3 <- as.numeric(par3)
> par4 <- as.numeric(par4)
> par5 <- as.numeric(par5)
> if (par6 == 'White Noise') par6 <- 'white' else par6 <- 'ma'
> par7 <- as.numeric(par7)
> if (par2 == 0) {
+ x <- log(x)
+ } else {
+ x <- (x ^ par2 - 1) / par2
+ }
> if (par3 > 0) x <- diff(x,lag=1,difference=par3)
> if (par4 > 0) x <- diff(x,lag=par5,difference=par4)
> postscript(file="/var/www/html/rcomp/tmp/1vg5y1259502727.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> racf <- acf(x, par1, main='Autocorrelation', xlab='time lag', ylab='ACF', ci.type=par6, ci=par7, sub=paste('(lambda=',par2,', d=',par3,', D=',par4,', CI=', par7, ', CI type=',par6,')',sep=''))
> dev.off()
null device 
          1 
> postscript(file="/var/www/html/rcomp/tmp/2mqhu1259502727.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> rpacf <- pacf(x,par1,main='Partial Autocorrelation',xlab='lags',ylab='PACF')
> dev.off()
null device 
          1 
> (myacf <- c(racf$acf))
 [1]  1.000000000  0.169639818  0.225706078 -0.174934037 -0.164386192
 [6] -0.278816880  0.053888308  0.042203869  0.152672089 -0.018276061
[11] -0.162917050 -0.161198108 -0.294574636  0.166770230 -0.040274157
[16]  0.301228708  0.115823328  0.069073082 -0.114529047  0.032901906
[21] -0.139271830  0.063123136  0.061500991  0.111572029 -0.047331033
[26] -0.118015332 -0.061020125 -0.176465629 -0.071774055  0.000927386
[31]  0.012209021  0.029001889  0.024483615 -0.091110209 -0.017831103
> (mypacf <- c(rpacf$acf))
 [1]  0.169639818  0.202763470 -0.257551725 -0.162766077 -0.150868162
 [6]  0.184178101  0.074384543 -0.025886245 -0.135134047 -0.230492512
[11]  0.021960621 -0.181498722  0.319995192 -0.176911868  0.096657196
[16]  0.065196524 -0.116017269  0.134336789  0.003976540  0.009889208
[21] -0.092415214  0.064517207  0.097309657 -0.198793884  0.076882500
[26] -0.074786915  0.032754956 -0.153901521 -0.013901700  0.002009162
[31] -0.062050991  0.008655106 -0.123655022  0.036276477
> 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/3m7o41259502727.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/48w2a1259502727.tab") 
> 
> system("convert tmp/1vg5y1259502727.ps tmp/1vg5y1259502727.png")
> system("convert tmp/2mqhu1259502727.ps tmp/2mqhu1259502727.png")
> 
> 
> proc.time()
   user  system elapsed 
  0.586   0.308   0.770