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(49.98,50.12,50.37,50.39,50.34,50.32,50.32,50.32,50.67,50.86,50.95,51.02,51.02,51.06,50.9,51.23,51.29,51.3,51.3,51.3,51.46,51.47,51.77,51.82,51.82,51.84,51.9,51.94,52.22,52.27,52.27,52.28,52.53,52.73,52.72,52.67,52.67,52.65,52.69,52.73,52.84,52.83,52.83,52.84,52.82,53.09,53.4,53.43,53.43,53.42,53.6,53.69,54.05,54.04,54.04,54.08,54.05,54.39,54.38,54.46,54.46,54.69,54.91,55.52,56.01,56.07,56.07,56.09,56.29,56.45,56.87,56.87)
> par8 = ''
> par7 = '0.95'
> par6 = 'White Noise'
> par5 = '12'
> par4 = '0'
> par3 = '0'
> par2 = '1'
> par1 = '48'
> 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/1pipt1353324873.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/268pk1353324873.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/3wt321353324873.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  0.943474849  0.884697562  0.833582712  0.784585616
 [6]  0.736747442  0.685902540  0.630887042  0.572273531  0.525135968
[11]  0.489521878  0.457647016  0.427997254  0.395592812  0.362013856
[16]  0.324795344  0.296829515  0.267971319  0.237282747  0.203069643
[21]  0.166829695  0.137067875  0.108342934  0.085510017  0.061272346
[26]  0.034261343  0.006174883 -0.016376028 -0.034072313 -0.049192533
[31] -0.064623256 -0.082573802 -0.102737343 -0.119145972 -0.132818904
[36] -0.146447936 -0.162949358 -0.180972679 -0.202502020 -0.224792546
[41] -0.243912614 -0.258226806 -0.274064499 -0.292208357 -0.310494042
[46] -0.325862117 -0.337663505 -0.345523970 -0.353440016
> (mypacf <- c(rpacf$acf))
 [1]  0.943474849 -0.049585541  0.039120045 -0.011527279 -0.013235287
 [6] -0.053391169 -0.065263895 -0.068211393  0.064707575  0.065070113
[11]  0.017556446  0.011977428 -0.037328676 -0.032195433 -0.072280213
[16]  0.041910634 -0.041871261 -0.016952365 -0.043849618 -0.030432112
[21]  0.028714241 -0.026709180  0.021139834 -0.031949500 -0.033531278
[26] -0.040357848  0.017640704 -0.001182799  0.009238497 -0.020908690
[31] -0.021371293 -0.036854748  0.001428174 -0.014985517 -0.027994673
[36] -0.029780692 -0.030815014 -0.044807171 -0.044339328 -0.015436629
[41]  0.007906729 -0.031291959 -0.033874587 -0.029735772 -0.012304885
[46] -0.015815400 -0.006116783 -0.024626620
> 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/4grel1353324873.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/57d1w1353324873.tab") 
> 
> try(system("convert tmp/1pipt1353324873.ps tmp/1pipt1353324873.png",intern=TRUE))
character(0)
> try(system("convert tmp/268pk1353324873.ps tmp/268pk1353324873.png",intern=TRUE))
character(0)
> try(system("convert tmp/3wt321353324873.ps tmp/3wt321353324873.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  2.942   0.482   3.405