R version 3.0.1 (2013-05-16) -- "Good Sport"
Copyright (C) 2013 The R Foundation for Statistical Computing
Platform: i686-pc-linux-gnu (32-bit)

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> x <- c(58896,57616,56232,53708,79784,78524,58896,45848,47112,47112,48372,51040,54968,53708,45848,47112,83716,91572,70664,58896,61548,62828,69404,75856,77260,64088,65476,48372,96888,111200,78524,68016,74596,82452,94220,108656,108656,99412,95484,71928,111200,129564,113848,96888,99412,108656,121704,137420,126896,120444,120444,99412,129564,149188,133492,116516,121704,142612,151856,164888,154380,137420,133492,102080,122968,145260,120444,106008,120444,134756,142612,163624,153120,126896,129564,104744,125636,144000,122968,108656,121704,137420,134756,166168,160976,140068,141332,113848,130824,157048,137420,125636,145260,157048,147928,189724,179340,155784,149188,119056,136140,151856,132212,132212,154380,166168,159696,205420,193652,171484,162240,129564,141332,162240,146524,142612,160976,176672,159696,200228)
> 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/fisher/rcomp/tmp/1s4n61377043295.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/2gkvi1377043296.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/3t1gj1377043296.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  0.869396355  0.765539085  0.723450705  0.686949367
 [6]  0.704136048  0.723788230  0.677776982  0.627205691  0.627467162
[11]  0.613786160  0.664012467  0.722977855  0.600400670  0.494967815
[16]  0.447246090  0.409723743  0.423483667  0.448344992  0.407335285
[21]  0.348752014  0.341368378  0.322110179  0.360383910  0.412417101
[26]  0.311733435  0.216806392  0.175290171  0.141318082  0.155547982
[31]  0.182204898  0.146261332  0.088257549  0.080104571  0.064592140
[36]  0.096859375  0.147773907  0.079504568  0.006880313 -0.021283048
[41] -0.041527748 -0.026787153  0.003505836 -0.015819940 -0.069876968
[46] -0.074759591 -0.081933478 -0.051566000 -0.004119870
> (mypacf <- c(rpacf$acf))
 [1]  0.869396355  0.039684876  0.204313070  0.048745264  0.279621020
 [6]  0.120374603 -0.114177661 -0.029160126  0.167294404 -0.022763207
[11]  0.294578494  0.151091497 -0.593768938 -0.118956089 -0.003852161
[16] -0.027314997  0.010667371  0.048608135  0.022845837 -0.089413176
[21]  0.057896780  0.061446528  0.020175641  0.106689132 -0.129249006
[26] -0.076162111 -0.020822664 -0.065233420 -0.012681898 -0.060622844
[31]  0.004668318 -0.024694199  0.005350125  0.062643750 -0.017711042
[36]  0.056508017  0.085165198  0.002619203  0.009277281 -0.006580197
[41] -0.063246881 -0.059173508  0.037452326 -0.074516397 -0.028465120
[46]  0.019111784 -0.011511625 -0.048798233
> 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/4jsw71377043296.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/5idzm1377043296.tab") 
> 
> try(system("convert tmp/1s4n61377043295.ps tmp/1s4n61377043295.png",intern=TRUE))
character(0)
> try(system("convert tmp/2gkvi1377043296.ps tmp/2gkvi1377043296.png",intern=TRUE))
character(0)
> try(system("convert tmp/3t1gj1377043296.ps tmp/3t1gj1377043296.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  1.725   0.368   2.084