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(96.24,95.56,95.56,95.56,95.96,95.96,95.96,95.96,95.61,95.30,95.68,97.94,97.32,97.32,97.45,98.08,98.25,98.25,97.95,97.81,97.68,98.03,98.03,98.03,98.11,98.11,98.11,97.95,97.95,97.95,97.95,97.95,97.95,97.89,97.16,97.16,97.16,97.18,97.18,96.47,97.47,97.47,97.47,97.47,96.63,96.78,96.25,96.25,96.28,95.62,95.62,96.85,96.85,96.85,96.85,96.85,96.85,96.85,96.75,97.15,98.28,98.28,98.28,98.51,98.51,98.51,96.03,96.03,96.77,96.92,96.92,96.92)
> 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/1bek31352710955.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/2hi981352710955.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/3d0741352710955.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  0.817480347  0.636957831  0.517161731  0.423585147
 [6]  0.326422920  0.199669111  0.143636569  0.111457397  0.053368238
[11] -0.020428399 -0.091120394 -0.149719387 -0.218369467 -0.277205142
[16] -0.316213325 -0.298166756 -0.259578928 -0.254193339 -0.247832191
[21] -0.243374998 -0.269845744 -0.277231122 -0.315409344 -0.318308753
[26] -0.298476333 -0.282431580 -0.221835810 -0.203353973 -0.152566402
[31] -0.118005309 -0.093702196 -0.064123158 -0.067673799 -0.035610990
[36] -0.004110621  0.047306700  0.077527519  0.095786518  0.127912914
[41]  0.165459497  0.175814919  0.179952655  0.202843126  0.223743525
[46]  0.225574404  0.231350388  0.219955173  0.197511449
> (mypacf <- c(rpacf$acf))
 [1]  0.817480347 -0.094404109  0.074454776 -0.003168566 -0.057305583
 [6] -0.145419232  0.124730861 -0.016080361 -0.085003481 -0.075003682
[11] -0.064617565 -0.090304226 -0.094038728 -0.035156559 -0.050904759
[16]  0.086519240  0.027968209 -0.082597962 -0.020631212 -0.055285815
[21] -0.164887662  0.029413187 -0.153399277 -0.002574204 -0.031948398
[26] -0.044545719  0.063255689 -0.136772848  0.086926016 -0.078138391
[31]  0.016345877 -0.016073089 -0.103143043  0.032275608 -0.034284552
[36]  0.031038812 -0.068663485 -0.007736603 -0.005284165  0.079371765
[41] -0.072726739  0.067316617  0.045636164 -0.030522005  0.016935617
[46]  0.024230479 -0.085518240 -0.016835152
> 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/4t0181352710955.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/5puad1352710955.tab") 
> 
> try(system("convert tmp/1bek31352710955.ps tmp/1bek31352710955.png",intern=TRUE))
character(0)
> try(system("convert tmp/2hi981352710955.ps tmp/2hi981352710955.png",intern=TRUE))
character(0)
> try(system("convert tmp/3d0741352710955.ps tmp/3d0741352710955.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  2.099   0.432   2.522