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(16.68,16.68,16.69,16.61,16.58,16.6,16.6,16.62,16.62,16.6,16.63,16.66,16.66,16.65,16.5,16.39,16.34,16.35,16.35,16.38,16.36,16.38,16.39,16.41,16.41,16.41,16.45,16.41,16.44,16.47,16.47,16.49,16.54,16.62,16.69,16.72,16.72,16.71,16.89,16.93,16.91,16.93,16.93,16.93,16.95,16.93,16.95,16.95,16.95,16.95,16.92,16.91,16.9,16.96,16.96,16.95,16.92,16.87,16.87,16.88,16.88,16.86,16.88,16.88,16.88,16.88,16.88,16.87,16.92,16.94,17.03,17.02)
> 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/fisher/rcomp/tmp/1yibr1363730657.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/fisher/rcomp/tmp/229ll1363730657.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/fisher/rcomp/tmp/3l23y1363730657.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  0.96691238  0.92073957  0.87875401  0.83668331  0.79810868
 [7]  0.75303527  0.70219184  0.65207468  0.60297929  0.55276697  0.50091930
[13]  0.44537272  0.38709140  0.32976673  0.27389208  0.20817535  0.14038002
[19]  0.07466329  0.01814252 -0.02445660 -0.06442866 -0.10606110 -0.14738300
[25] -0.18031535 -0.20600513 -0.22844928 -0.24752258 -0.27080819 -0.29224308
[31] -0.31089065 -0.32980868 -0.34812566 -0.37100807 -0.38943275 -0.39158169
[37] -0.39200763 -0.39769271 -0.40374842 -0.39990446 -0.38648388 -0.36921914
[43] -0.35243523 -0.34036950 -0.32688381 -0.31089127 -0.29822951 -0.28214682
[49] -0.26774704
> (mypacf <- c(rpacf$acf))
 [1]  0.966912385 -0.217884099  0.083523655 -0.060155785  0.049816342
 [6] -0.159042186 -0.054482856 -0.017295424 -0.019907259 -0.065272556
[11] -0.044426400 -0.078511824 -0.062642939 -0.030169745 -0.029137618
[16] -0.218075686 -0.012299768 -0.054433552  0.103778186  0.086128994
[21] -0.014219790 -0.034378929 -0.024863504  0.093474795 -0.005856626
[26] -0.006898336  0.034976328 -0.106960564  0.016901639 -0.082212592
[31] -0.029598421 -0.080931470 -0.122410265  0.028195106  0.116608439
[36] -0.100604230 -0.086345643  0.024698533  0.171018813  0.018614551
[41]  0.010795298 -0.013789333  0.023998061  0.031330029  0.007371364
[46] -0.123121684  0.042551110 -0.048735931
> lengthx <- length(x)
> sqrtn <- sqrt(lengthx)
> 
> #Note: the /var/fisher/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/fisher/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/fisher/rcomp/tmp/417re1363730657.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/fisher/rcomp/tmp/5q97z1363730657.tab") 
> 
> try(system("convert tmp/1yibr1363730657.ps tmp/1yibr1363730657.png",intern=TRUE))
character(0)
> try(system("convert tmp/229ll1363730657.ps tmp/229ll1363730657.png",intern=TRUE))
character(0)
> try(system("convert tmp/3l23y1363730657.ps tmp/3l23y1363730657.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  1.785   0.285   2.049