R version 2.13.0 (2011-04-13)
Copyright (C) 2011 The R Foundation for Statistical Computing
ISBN 3-900051-07-0
Platform: i486-pc-linux-gnu (32-bit)

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> x <- c(34.74,34.89,34.98,34.93,35.01,35.03,35.03,34.98,34.92,35.04,35.21,35.21,35.21,35.26,35.45,35.53,35.53,35.57,35.57,35.57,35.63,35.92,36.05,36.1,36.1,36.02,36.07,36.17,36.52,36.49,36.49,36.48,36.62,36.63,36.7,36.7,36.7,36.69,36.86,36.85,36.83,36.88,36.88,36.92,36.93,37.06,37.1,37.09,37.09,37.15,37.27,37.43,37.42,37.4,37.4,37.39,37.42,37.7,37.85,37.88)
> par8 = ''
> par7 = '0.95'
> par6 = 'White Noise'
> par5 = '12'
> par4 = '0'
> par3 = '0'
> 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/1xxdv1333542739.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/2cytm1333542739.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/3tjsd1333542739.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]  1.00000000  0.94333535  0.88792397  0.83942440  0.79890767  0.75959316
 [7]  0.71779317  0.67134454  0.61776917  0.55912420  0.50821754  0.46452176
[13]  0.41967170  0.37131010  0.32043992  0.27507222  0.23584442  0.19585262
[19]  0.15480756  0.11066410  0.06516095  0.01969570 -0.01768710 -0.04757087
[25] -0.07926582 -0.11357857 -0.15149597 -0.18657702 -0.21955544 -0.23877632
[31] -0.26291402 -0.29009900 -0.32034531 -0.33496029 -0.34621120 -0.35446569
[37] -0.36704050 -0.38320047 -0.40057402 -0.40848002 -0.40743847 -0.40600533
[43] -0.40420441 -0.40321133 -0.40081323 -0.39932610 -0.39165273 -0.37678961
[49] -0.36190482
> (mypacf <- c(rpacf$acf))
 [1]  0.943335352 -0.017777335  0.033554840  0.047363457 -0.006766949
 [6] -0.036530285 -0.060638653 -0.094004986 -0.088528789  0.018529673
[11]  0.019311871 -0.038841125 -0.047154341 -0.044704984  0.015525258
[16]  0.018600594 -0.043266791 -0.044285229 -0.058128142 -0.045120485
[21] -0.045305878  0.016398834  0.017172067 -0.041989593 -0.032066173
[26] -0.058111833 -0.023217207 -0.040192412  0.071420399 -0.083105516
[31] -0.052286056 -0.050096356  0.101385266 -0.014882576 -0.009153846
[36] -0.065730479 -0.055883725 -0.034487544  0.043081548  0.017653621
[41] -0.048411571 -0.005438755  0.006255005  0.012152185 -0.049390652
[46]  0.002640769  0.024634100 -0.002401105
> 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/4tai91333542740.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/5wqpk1333542740.tab") 
> 
> try(system("convert tmp/1xxdv1333542739.ps tmp/1xxdv1333542739.png",intern=TRUE))
character(0)
> try(system("convert tmp/2cytm1333542739.ps tmp/2cytm1333542739.png",intern=TRUE))
character(0)
> try(system("convert tmp/3tjsd1333542739.ps tmp/3tjsd1333542739.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  0.948   0.189   1.147