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(13.4,14,14.7,16.1,16.3,16.1,16.5,19,18.7,17.7,17.2,16.6,17.4,15.5,12.4,11.1,11.1,13.7,12.1,11.3,9.9,10.9,13.2,14.2,16.8,17,19.6,18.3,20.6,17.7,19.6,17.4,17.6,19,17.8,17,15.7,16,17.1,17,15.7,15.6,16.1,17.4,16,15,14.3,14.5,14.3,16.2,14.8,16.3,14,15.4,13.4,12.9,14.3,11.9,8.6,5.5,0.8)
> par7 = '0.95'
> par6 = 'MA'
> par5 = '12'
> par4 = '0'
> 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$_version), Office for Research Development and Education, URL http://www.wessa.net/rwasp_YOURPAGE.wasp/
> #Source of accompanying publication: Office for Research, Development, and Education
> #Technical description: 
> if (par1 == 'Default') {
+ par1 = 10*log10(length(x))
+ } else {
+ par1 <- as.numeric(par1)
+ }
> par2 <- as.numeric(par2)
> par3 <- as.numeric(par3)
> par4 <- as.numeric(par4)
> par5 <- as.numeric(par5)
> if (par6 == 'White Noise') par6 <- 'white' else par6 <- 'ma'
> par7 <- as.numeric(par7)
> if (par2 == 0) {
+ x <- log(x)
+ } else {
+ x <- (x ^ par2 - 1) / par2
+ }
> if (par3 > 0) x <- diff(x,lag=1,difference=par3)
> if (par4 > 0) x <- diff(x,lag=par5,difference=par4)
> postscript(file="/var/www/html/rcomp/tmp/1b3zf1259338706.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> racf <- acf(x, par1, main='Autocorrelation', xlab='time lag', ylab='ACF', ci.type=par6, ci=par7, sub=paste('(lambda=',par2,', d=',par3,', D=',par4,', CI=', par7, ', CI type=',par6,')',sep=''))
> dev.off()
null device 
          1 
> postscript(file="/var/www/html/rcomp/tmp/2vxtf1259338706.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> rpacf <- pacf(x,par1,main='Partial Autocorrelation',xlab='lags',ylab='PACF')
> dev.off()
null device 
          1 
> (myacf <- c(racf$acf))
 [1]  1.000000000  0.727216445  0.540442503  0.349503963  0.264315638
 [6]  0.202913956  0.072194482 -0.057352662 -0.114425499 -0.173810532
[11] -0.176707996 -0.201745071 -0.180270568 -0.153872277 -0.127409779
[16] -0.112433714 -0.101011674 -0.088722229 -0.034412615 -0.016235788
[21] -0.020059333 -0.020270899 -0.042047572 -0.023790425 -0.074129395
[26] -0.095630241 -0.126003042 -0.150167181 -0.156570094 -0.168607167
[31] -0.187254259 -0.152260081 -0.175469282 -0.129196444 -0.093220154
[36] -0.009096555  0.050452595
> (mypacf <- c(rpacf$acf))
 [1]  0.727216445  0.024617620 -0.109885507  0.085867642  0.020442520
 [6] -0.200202068 -0.118166891  0.056219801 -0.105094223 -0.007579746
[11] -0.020491934  0.040104623 -0.012930906 -0.018405874 -0.026134509
[16] -0.027946781 -0.025025198  0.059552259 -0.027752067 -0.067343263
[21]  0.027754999 -0.059402749  0.008683222 -0.131600991  0.001295932
[26] -0.047262691 -0.067715873 -0.025672628 -0.023767442 -0.072001789
[31]  0.028100752 -0.112065070  0.025074097  0.029999538  0.072893721
[36] -0.009345570
> 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/3kejs1259338706.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/43vmf1259338706.tab") 
> 
> system("convert tmp/1b3zf1259338706.ps tmp/1b3zf1259338706.png")
> system("convert tmp/2vxtf1259338706.ps tmp/2vxtf1259338706.png")
> 
> 
> proc.time()
   user  system elapsed 
  0.548   0.320   0.660