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(14.544,14.931,14.886,16.005,17.064,15.168,16.050,15.839,15.137,14.954,15.648,15.305,15.579,16.348,15.928,16.171,15.937,15.713,15.594,15.683,16.438,17.032,17.696,17.745,19.394,20.148,20.108,18.584,18.441,18.391,19.178,18.079,18.483,19.644,19.195,19.650,20.830,23.595,22.937,21.814,21.928,21.777,21.383,21.467,22.052,22.680,24.320,24.977,25.204,25.739,26.434,27.525,30.695,32.436,30.160,30.236,31.293,31.077,32.226,33.865,32.810,32.242,32.700,32.819,33.947,34.148,35.261,39.506,41.591,39.148,41.216,40.225)
> 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/fisher/rcomp/tmp/1rvwt1363731436.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/2lj581363731436.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/36jaa1363731436.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  0.018384966 -0.191106409  0.087584873 -0.039910844
 [6] -0.135398378  0.043247566 -0.034203127 -0.018482015  0.080061903
[11] -0.148740037  0.065394566  0.101715611 -0.114268134  0.010853232
[16]  0.306100402  0.086028902 -0.090760561 -0.030439821 -0.079506888
[21]  0.024581105  0.040360454  0.129941389  0.011947472 -0.067101000
[26] -0.161605647  0.011358722  0.069106007 -0.098040778 -0.032552158
[31]  0.106991210  0.109418998 -0.115179400  0.054532723  0.070387750
[36] -0.028653900 -0.142298093  0.001067372 -0.001608978 -0.111204937
[41] -0.033791549 -0.123577289  0.065152527  0.073458308 -0.031911625
[46] -0.049334065  0.098657596 -0.065999484 -0.046561772
> (mypacf <- c(rpacf$acf))
 [1]  0.018384966 -0.191509147  0.098953527 -0.086329743 -0.099134804
 [6]  0.021231199 -0.077386707  0.016492693  0.041652732 -0.169000196
[11]  0.119570979  0.004704733 -0.063246952  0.040625155  0.247001109
[16]  0.139018643 -0.011403909 -0.050932253 -0.047956190  0.070766776
[21]  0.051765936  0.205631417 -0.021283545 -0.061754326 -0.139458293
[26] -0.013703159  0.028370010 -0.062868250 -0.050163889 -0.018583648
[31]  0.030195695 -0.104354657  0.090493819  0.080173955  0.002770030
[36] -0.213213581 -0.130456744 -0.097767798 -0.029760033  0.113210617
[41] -0.143449377 -0.057583987 -0.023305510 -0.019593627 -0.054395336
[46]  0.037091806  0.011678583 -0.030747298
> 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/4mead1363731436.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/5njto1363731436.tab") 
> 
> try(system("convert tmp/1rvwt1363731436.ps tmp/1rvwt1363731436.png",intern=TRUE))
character(0)
> try(system("convert tmp/2lj581363731436.ps tmp/2lj581363731436.png",intern=TRUE))
character(0)
> try(system("convert tmp/36jaa1363731436.ps tmp/36jaa1363731436.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  1.960   0.315   2.255