R version 2.15.2 (2012-10-26) -- "Trick or Treat"
Copyright (C) 2012 The R Foundation for Statistical Computing
ISBN 3-900051-07-0
Platform: i686-pc-linux-gnu (32-bit)

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> x <- c(0.51,0.50,0.47,0.47,0.44,0.43,0.45,0.46,0.46,0.45,0.45,0.45,0.44,0.43,0.45,0.45,0.44,0.47,0.46,0.48,0.49,0.52,0.56,0.58,0.58,0.55,0.55,0.53,0.56,0.57,0.61,0.57,0.59,0.53,0.43,0.38,0.40,0.45,0.40,0.37,0.37,0.40,0.41,0.43,0.45,0.44,0.47,0.47,0.52,0.55,0.54,0.54,0.53,0.52,0.50,0.50,0.53,0.54,0.59,0.66,0.67,0.61,0.62,0.65,0.63,0.58,0.60,0.60,0.61,0.61,0.59,0.60)
> par8 = ''
> par7 = '0.95'
> par6 = 'White Noise'
> par5 = '12'
> par4 = '0'
> par3 = '1'
> par2 = '1'
> par1 = '48'
> par8 <- ''
> par7 <- '0.95'
> par6 <- 'White Noise'
> par5 <- '12'
> par4 <- '0'
> par3 <- '1'
> par2 <- '1'
> par1 <- '48'
> #'GNU S' R Code compiled by R2WASP v. 1.2.291 ()
> #Author: root
> #To cite this work: Wessa P., (2012), (Partial) Autocorrelation Function (v1.0.11) in Free Statistics Software (v$_version), Office for Research Development and Education, URL http://www.wessa.net/rwasp_autocorrelation.wasp/
> #Source of accompanying publication: 
> #
> 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 (par8 != '') par8 <- as.numeric(par8)
> ox <- x
> if (par8 == '') {
+ if (par2 == 0) {
+ x <- log(x)
+ } else {
+ x <- (x ^ par2 - 1) / par2
+ }
+ } else {
+ x <- log(x,base=par8)
+ }
> if (par3 > 0) x <- diff(x,lag=1,difference=par3)
> if (par4 > 0) x <- diff(x,lag=par5,difference=par4)
> postscript(file="/var/wessaorg/rcomp/tmp/1xvbo1358241674.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> op <- par(mfrow=c(2,1))
> plot(ox,type='l',main='Original Time Series',xlab='time',ylab='value')
> if (par8=='') {
+ mytitle <- paste('Working Time Series (lambda=',par2,', d=',par3,', D=',par4,')',sep='')
+ mysub <- paste('(lambda=',par2,', d=',par3,', D=',par4,', CI=', par7, ', CI type=',par6,')',sep='')
+ } else {
+ mytitle <- paste('Working Time Series (base=',par8,', d=',par3,', D=',par4,')',sep='')
+ mysub <- paste('(base=',par8,', d=',par3,', D=',par4,', CI=', par7, ', CI type=',par6,')',sep='')
+ }
> plot(x,type='l', main=mytitle,xlab='time',ylab='value')
> par(op)
> dev.off()
null device 
          1 
> postscript(file="/var/wessaorg/rcomp/tmp/2nuax1358241674.ps",horizontal=F,onefile=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=mysub)
> dev.off()
null device 
          1 
> postscript(file="/var/wessaorg/rcomp/tmp/3kxvu1358241674.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> rpacf <- pacf(x,par1,main='Partial Autocorrelation',xlab='lags',ylab='PACF',sub=mysub)
> dev.off()
null device 
          1 
> (myacf <- c(racf$acf))
 [1]  1.000000000  0.230561137 -0.079963289 -0.100061782  0.075113942
 [6] -0.055590469 -0.140073621  0.073148654  0.005792340  0.022915859
[11] -0.099001330  0.016784082 -0.137125192 -0.112463037 -0.064171971
[16] -0.043915206 -0.001702165 -0.158320636 -0.008446457 -0.008261309
[21]  0.010110797 -0.066221206  0.086597753  0.035779320 -0.259243787
[26] -0.167911825  0.095301028  0.164888739 -0.103372212  0.064500459
[31]  0.197671849  0.122164385 -0.006231319 -0.096816055  0.067240183
[36] -0.009727892  0.113195665  0.062989746  0.029675082 -0.010730611
[41] -0.008660804  0.011171913 -0.014556999 -0.020638342 -0.079819949
[46]  0.011512014 -0.039730467 -0.072173476 -0.025979094
> (mypacf <- c(rpacf$acf))
 [1]  0.230561137 -0.140595568 -0.050227491  0.110301687 -0.129329932
 [6] -0.092797322  0.154781359 -0.115747922  0.063644441 -0.086727867
[11]  0.017113927 -0.169098398 -0.029890107 -0.056295999 -0.071147014
[16]  0.001167177 -0.181835991  0.011219823 -0.020321036 -0.072213144
[21] -0.024799201  0.081032460 -0.103916728 -0.297364149 -0.060916348
[26]  0.078763386 -0.067647507 -0.109813467  0.078452961  0.036330631
[31]  0.001985916  0.046466553 -0.154999854  0.053477991 -0.024265719
[36]  0.053781458 -0.006641047 -0.063006192  0.040270115 -0.007233925
[41] -0.045551619  0.046896425 -0.028363010  0.001741469 -0.049791138
[46]  0.019410979 -0.026676022 -0.036711301
> lengthx <- length(x)
> sqrtn <- sqrt(lengthx)
> 
> #Note: the /var/wessaorg/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/wessaorg/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/wessaorg/rcomp/tmp/4br2t1358241674.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/wessaorg/rcomp/tmp/53nzh1358241674.tab") 
> 
> try(system("convert tmp/1xvbo1358241674.ps tmp/1xvbo1358241674.png",intern=TRUE))
character(0)
> try(system("convert tmp/2nuax1358241674.ps tmp/2nuax1358241674.png",intern=TRUE))
character(0)
> try(system("convert tmp/3kxvu1358241674.ps tmp/3kxvu1358241674.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  1.804   0.261   2.056