R version 2.15.3 (2013-03-01) -- "Security Blanket"
Copyright (C) 2013 The R Foundation for Statistical Computing
ISBN 3-900051-07-0
Platform: i686-pc-linux-gnu (32-bit)

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> x <- c(0.67,0.66,0.66,0.67,0.67,0.67,0.67,0.68,0.68,0.67,0.67,0.67,0.67,0.67,0.69,0.69,0.69,0.69,0.69,0.69,0.7,0.69,0.68,0.7,0.7,0.71,0.69,0.7,0.7,0.71,0.71,0.71,0.71,0.7,0.7,0.71,0.71,0.71,0.71,0.7,0.69,0.7,0.7,0.7,0.71,0.7,0.7,0.69,0.7,0.71,0.71,0.71,0.71,0.71,0.71,0.71,0.71,0.69,0.7,0.7,0.7,0.72,0.7,0.69,0.7,0.71,0.72,0.72,0.73,0.72,0.74,0.75)
> 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/1sqvn1369132314.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/20mqi1369132314.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/31yfw1369132314.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 -0.216232466 -0.103477203 -0.085558340 -0.065594487
 [6]  0.097518650  0.099333218  0.121342061 -0.221679772  0.009940522
[11]  0.023769406 -0.044968173  0.136294248 -0.081727584 -0.112121605
[16]  0.010602984 -0.062224574  0.191634984 -0.026386849 -0.117363691
[21]  0.029645151  0.081817593 -0.065652093 -0.005299692  0.105410582
[26] -0.058163398 -0.026185230 -0.044564936 -0.133496789  0.122407759
[31]  0.031430917  0.015096201 -0.077925631 -0.082246032 -0.046177885
[36]  0.010084536  0.155048388 -0.060928454  0.065886114 -0.101777845
[41] -0.140351825  0.224448429 -0.048021256 -0.028057404 -0.062541404
[46]  0.046123880  0.005504911  0.114170195 -0.029209511
> (mypacf <- c(rpacf$acf))
 [1] -0.216232466 -0.157602626 -0.156566191 -0.158076018  0.003934482
 [6]  0.091824303  0.195556242 -0.105431014  0.003326932  0.020578974
[11] -0.079093303  0.054323074 -0.057950926 -0.129976143 -0.017753183
[16] -0.146519099  0.126262615  0.034344178 -0.123074964  0.092624146
[21]  0.145456418 -0.090128799 -0.012926400  0.045659466  0.041095303
[26] -0.008833755 -0.185853709 -0.198650300  0.039997655 -0.075000518
[31]  0.046723808 -0.017156516 -0.099270762 -0.041554773 -0.061823872
[36]  0.064323157  0.017791252  0.034615331  0.034027043 -0.123363264
[41]  0.022778413 -0.109208083 -0.106913602 -0.069125624  0.044866833
[46] -0.023715930  0.143118764 -0.045451676
> 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/4exy81369132314.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/5gd001369132314.tab") 
> 
> try(system("convert tmp/1sqvn1369132314.ps tmp/1sqvn1369132314.png",intern=TRUE))
character(0)
> try(system("convert tmp/20mqi1369132314.ps tmp/20mqi1369132314.png",intern=TRUE))
character(0)
> try(system("convert tmp/31yfw1369132314.ps tmp/31yfw1369132314.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  2.115   0.449   2.553