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(124275,58605,21828,42811,65963,128457,26867,143540,107458,258558,22475,294584,159848,289458,117950,78351,84589,44324,52285,185486,23846,13257,166999,148488,74747,55700,218584,187888,44788,18840,48787,69100,41892,90588,148574,50201,86828,102785,118844,145288,56790,287525,187880,87740,55258,58769,43366,77051,91574,15533,18425,65192,81059,73322,91261,86166,61842,25192,21059,15855,12618,101667,224275,55700,60748,41848,61781,120077,42032,46485,36861,55027,48999,68352,126987,86526,125340,69029,153287,135724,92108,119906,79798,97206)
> 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/1rus91352710439.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/28dmu1352710439.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/3vtjf1352710439.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  0.175832181  0.166739227  0.007081129  0.178536659
 [6] -0.063432235 -0.095865698 -0.042189589 -0.020958222 -0.179475445
[11] -0.073355048  0.021724163 -0.011040657  0.042090987  0.222748353
[16]  0.222926263 -0.061690494 -0.091792765 -0.063072686  0.011523760
[21] -0.029981839 -0.052451067 -0.023115553 -0.046363270 -0.138503855
[26]  0.020243123  0.044517877 -0.017877837  0.170821623  0.089318623
[31]  0.095086863 -0.097770550 -0.019944477 -0.042718449 -0.024799171
[36] -0.024526104 -0.018287098 -0.068160128 -0.108873244 -0.037270919
[41]  0.012876541 -0.050610734 -0.022379103  0.018292356 -0.069156674
[46] -0.087841669 -0.148215019 -0.088353793 -0.014383750
> (mypacf <- c(rpacf$acf))
 [1]  0.175832181  0.140155451 -0.045020662  0.169633520 -0.121242333
 [6] -0.125891867  0.035063409 -0.027896080 -0.163654755  0.027455195
[11]  0.072278838 -0.050987783  0.109176450  0.234188166  0.078150526
[16] -0.201435122 -0.115565015 -0.110369760  0.007357044  0.147943491
[21]  0.002158263 -0.030631425  0.021505541 -0.124650564  0.029160735
[26]  0.075004302 -0.118873345  0.185909145  0.001919553 -0.012050425
[31]  0.018800888 -0.027202158 -0.123838464 -0.053961854  0.077764715
[36] -0.018209581  0.024067502  0.020094887 -0.049163216 -0.051984008
[41] -0.064989573 -0.103946196 -0.046042821 -0.036868287 -0.029500729
[46] -0.019035158 -0.038637255  0.031817390
> 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/4lah01352710439.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/5vc3l1352710439.tab") 
> 
> try(system("convert tmp/1rus91352710439.ps tmp/1rus91352710439.png",intern=TRUE))
character(0)
> try(system("convert tmp/28dmu1352710439.ps tmp/28dmu1352710439.png",intern=TRUE))
character(0)
> try(system("convert tmp/3vtjf1352710439.ps tmp/3vtjf1352710439.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  2.131   0.431   2.542