R version 3.0.2 (2013-09-25) -- "Frisbee Sailing"
Copyright (C) 2013 The R Foundation for Statistical Computing
Platform: i686-pc-linux-gnu (32-bit)

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> x <- c(96.86,96.77,96.5,96.01,96.07,95.93,95.93,95.83,96.24,96.25,96.59,96.62,96.62,96.81,96.71,96.45,96.63,96.56,96.56,96.65,97.04,97.14,97.2,97.26,97.26,97.24,97.35,97.36,97.28,97.31,97.31,97.31,97.23,97.78,97.64,97.68,97.68,97.81,97.75,97.63,97.6,97.65,97.65,97.65,97.86,98.41,98.79,98.75,98.74,98.55,98.65,98.86,98.94,99.05,99.05,99.05,99.17,98.99,98.91,98.89,98.89,98.72,98.89,98.97,99.16,99.54,99.54,99.55,100.01,99.52,99.44,99.39,99.39,99.4,100.43,100.62,101.05,100.95,100.95,100.91,101.13,100.81,100.47,100.56)
> 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/1ghpo1385137247.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/2cxqk1385137247.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/3z67s1385137247.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  0.073380412  0.115018957 -0.054792033 -0.062780190
 [6] -0.328024738  0.001527826 -0.274250548 -0.049098821  0.084281545
[11]  0.080102412  0.039730091  0.248411438  0.013309452 -0.074718810
[16] -0.048894018 -0.141642979 -0.117867332 -0.066932756 -0.058881655
[21]  0.077470059  0.035723940  0.046372887  0.116047815 -0.016035907
[26]  0.038932613 -0.063185207 -0.025063201  0.002853439  0.148862695
[31]  0.004082518 -0.005187013  0.042640209  0.028800902 -0.020958120
[36]  0.070375276 -0.135494943 -0.025711925 -0.020837789 -0.018317567
[41] -0.068438977  0.065454406 -0.031720135  0.020410994 -0.044227585
[46]  0.017866440  0.005334538  0.012283558 -0.037806263
> (mypacf <- c(rpacf$acf))
 [1]  0.073380412  0.110227814 -0.071641940 -0.068266046 -0.312803228
 [6]  0.057106766 -0.242903046 -0.061544421  0.113885154 -0.053285231
[11]  0.019849380  0.112139883 -0.021455728 -0.113597137 -0.048154099
[16] -0.071281615  0.002587766 -0.093321070 -0.033568714  0.105443048
[21] -0.144896904 -0.017296155  0.080864183 -0.148269116  0.093323852
[26] -0.094127722  0.039484255  0.123003410  0.079365120  0.098301640
[31] -0.106097968  0.024791132  0.093445539  0.002441008  0.086581999
[36] -0.083401546  0.022733945  0.009523267 -0.005235001 -0.064777016
[41] -0.010243570 -0.014597742 -0.001736909 -0.040274458 -0.026049920
[46]  0.121742318 -0.088596966  0.002717866
> 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/4e1031385137247.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/52i491385137247.tab") 
> 
> try(system("convert tmp/1ghpo1385137247.ps tmp/1ghpo1385137247.png",intern=TRUE))
character(0)
> try(system("convert tmp/2cxqk1385137247.ps tmp/2cxqk1385137247.png",intern=TRUE))
character(0)
> try(system("convert tmp/3z67s1385137247.ps tmp/3z67s1385137247.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  1.791   0.428   2.201