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(15.13,15.25,15.33,15.36,15.4,15.4,15.41,15.47,15.54,15.55,15.59,15.65,15.75,15.86,15.89,15.94,15.93,15.95,15.99,15.99,16.06,16.08,16.07,16.11,16.15,16.18,16.3,16.42,16.49,16.5,16.58,16.64,16.66,16.81,16.91,16.92,16.95,17.11,17.16,17.16,17.27,17.34,17.39,17.43,17.45,17.5,17.56,17.65,17.62,17.7,17.72,17.71,17.74,17.75,17.78,17.8,17.86,17.88,17.89,17.94,17.98,18.1,18.14,18.19,18.23,18.24,18.27,18.3,18.34,18.36,18.36,18.4,18.43,18.47,18.56,18.58,18.61,18.61,18.69,18.74,18.75,18.81,18.85,18.88)
> par8 = ''
> par7 = '0.95'
> par6 = 'White Noise'
> par5 = '12'
> par4 = '1'
> par3 = '0'
> par2 = '1'
> par1 = '48'
> par8 <- ''
> par7 <- '0.95'
> par6 <- 'White Noise'
> par5 <- '12'
> par4 <- '1'
> 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/11k2u1363687681.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/2x2tv1363687681.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/3vj2p1363687681.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  0.936302242  0.864098765  0.816050920  0.729264994
 [6]  0.625770191  0.539837557  0.437930352  0.306336417  0.200873264
[11]  0.110347814  0.004690885 -0.075867032 -0.103624554 -0.136778890
[16] -0.184051634 -0.210384737 -0.240372375 -0.252434091 -0.243377688
[21] -0.235167778 -0.233087290 -0.227200984 -0.213589160 -0.206903957
[26] -0.193011668 -0.174501066 -0.154219289 -0.138113882 -0.126720276
[31] -0.126694826 -0.138664753 -0.144202697 -0.148074853 -0.150310116
[36] -0.166560100 -0.189881185 -0.201453363 -0.216785463 -0.228015984
[41] -0.223565996 -0.205912085 -0.192732006 -0.167556551 -0.136581432
[46] -0.111419575 -0.086181227 -0.050659186 -0.012657159
> (mypacf <- c(rpacf$acf))
 [1]  0.936302242 -0.101859223  0.163481916 -0.383304475 -0.085402757
 [6] -0.032444125 -0.163914439 -0.239013975  0.092321843 -0.028271517
[11] -0.022275345  0.111075797  0.317491531 -0.017784220 -0.123213449
[16] -0.208649128 -0.238541900  0.226697641 -0.074666619 -0.030887945
[21]  0.005865001  0.030725152  0.060088929  0.037772350  0.093078810
[26] -0.066876380 -0.039752649 -0.240737769 -0.130832467  0.013364142
[31] -0.080849041 -0.072523825  0.049885112  0.117892233 -0.010144025
[36]  0.011657976  0.119850695 -0.054680321 -0.008074916 -0.079873438
[41]  0.009633528  0.006663277  0.015285091 -0.089842933  0.083396822
[46] -0.066955660 -0.056380463 -0.043908442
> 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/4haol1363687681.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/55bed1363687681.tab") 
> 
> try(system("convert tmp/11k2u1363687681.ps tmp/11k2u1363687681.png",intern=TRUE))
character(0)
> try(system("convert tmp/2x2tv1363687681.ps tmp/2x2tv1363687681.png",intern=TRUE))
character(0)
> try(system("convert tmp/3vj2p1363687681.ps tmp/3vj2p1363687681.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  1.866   0.284   2.125