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(8.00,8.10,7.70,7.50,7.60,7.80,7.80,7.80,7.50,7.50,7.10,7.50,7.50,7.60,7.70,7.70,7.90,8.10,8.20,8.20,8.20,7.90,7.30,6.90,6.60,6.70,6.90,7.00,7.10,7.20,7.10,6.90,7.00,6.80,6.40,6.70,6.60,6.40,6.30,6.20,6.50,6.80,6.80,6.40,6.10,5.80,6.10,7.20,7.30,6.90,6.10,5.80,6.20,7.10,7.70,7.90,7.70,7.40,7.50,8.00)
> 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$_version), Office for Research Development and Education, URL http://www.wessa.net/rwasp_YOURPAGE.wasp/
> #Source of accompanying publication: Office for Research, Development, and Education
> #Technical description: 
> if (par1 == 'Default') {
+ par1 = 10*log10(length(x))
+ } else {
+ par1 <- as.numeric(par1)
+ }
> par2 <- as.numeric(par2)
> par3 <- as.numeric(par3)
> par4 <- as.numeric(par4)
> par5 <- as.numeric(par5)
> if (par6 == 'White Noise') par6 <- 'white' else par6 <- 'ma'
> par7 <- as.numeric(par7)
> if (par2 == 0) {
+ x <- log(x)
+ } else {
+ x <- (x ^ par2 - 1) / par2
+ }
> if (par3 > 0) x <- diff(x,lag=1,difference=par3)
> if (par4 > 0) x <- diff(x,lag=par5,difference=par4)
> postscript(file="/var/www/html/rcomp/tmp/1u1r51260215233.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> racf <- acf(x, par1, main='Autocorrelation', xlab='time lag', ylab='ACF', ci.type=par6, ci=par7, sub=paste('(lambda=',par2,', d=',par3,', D=',par4,', CI=', par7, ', CI type=',par6,')',sep=''))
> dev.off()
null device 
          1 
> postscript(file="/var/www/html/rcomp/tmp/2hsyz1260215233.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> rpacf <- pacf(x,par1,main='Partial Autocorrelation',xlab='lags',ylab='PACF')
> dev.off()
null device 
          1 
> (myacf <- c(racf$acf))
 [1]  1.00000000  0.84655741  0.60618272  0.42591996  0.37288814  0.41120947
 [7]  0.43464158  0.37253909  0.26559264  0.19664634  0.18888294  0.23317954
[13]  0.24916052  0.19276556  0.13943987  0.08280982  0.02075304 -0.03127965
[19] -0.08084385 -0.12777633 -0.16693115 -0.20379381 -0.25571548 -0.29180103
[25] -0.30454709 -0.29787187 -0.24552333 -0.21695836 -0.22908403 -0.26863720
[31] -0.32733085 -0.36917617 -0.37189814 -0.33661342 -0.27670274 -0.20593860
[37] -0.16635038
> (mypacf <- c(rpacf$acf))
 [1]  0.846557414 -0.389907950  0.177897400  0.235678981  0.127207885
 [6] -0.074383498 -0.126860603  0.034678840  0.100139925 -0.011166480
[11]  0.074337308 -0.089590895 -0.080684545  0.186250985 -0.211958048
[16] -0.169018187 -0.002056728 -0.037015216 -0.044585901 -0.114319267
[21] -0.072134230 -0.085526652  0.012426080  0.020348359 -0.077615042
[26]  0.138190161 -0.045447431 -0.031627974 -0.055547983 -0.135875837
[31] -0.006741496 -0.013427328  0.066500589  0.137549075  0.046368831
[36]  0.025275136
> 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/3ihdj1260215233.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/4tka91260215233.tab") 
> system("convert tmp/1u1r51260215233.ps tmp/1u1r51260215233.png")
> system("convert tmp/2hsyz1260215233.ps tmp/2hsyz1260215233.png")
> 
> 
> proc.time()
   user  system elapsed 
  0.527   0.314   0.949