R version 3.0.2 (2013-09-25) -- "Frisbee Sailing"
Copyright (C) 2013 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu (64-bit)

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> x <- c(5452304,5431998,5411406,5368792,5790356,5768048,5452304,5242380,5262686,5262686,5285280,5325892,5389098,5389098,5348486,5242380,5790356,5873868,5747742,5452304,5578716,5389098,5474612,5515510,5558124,5452304,5474612,5325892,5790356,5937074,5810948,5578716,5831254,5558124,5810948,5790356,5853562,5621330,5873868,5853562,6232512,6146998,5810948,5641636,5873868,5558124,5790356,5831254,5916768,5727436,5831254,5894460,6126692,5937074,5684536,5411406,5664230,4969250,5305586,5494918,5684536,5411406,5411406,5411406,5558124,5348486,5073354,4843124,5010148,4358068,4757610,4989842,5032456,4800224,4820530,4757610,4969250,4820530,4527380,4315454,4673812,3895606,4400968,4631198,4631198,4358068,4105530,4085224,4315454,4105530,3706274,3431142,3726580,3031886,3663374,3999424,4105530,3873298,3579862,3789786,3873298,3810092,3178318,2885168,3094806,2463318,3115398,3347630,3536962,3221218,2925780,3094806,3178318,3011294,2379806,2104674,2357212,1662518,2420418,2885168)
> 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/wessaorg/rcomp/tmp/1viz81439657281.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/2lces1439657281.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/3qyc31439657281.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 -0.216906446 -0.052827322 -0.144727805  0.067032654
 [6] -0.127179009  0.050569592 -0.084742431  0.084978735 -0.162055038
[11] -0.039800266 -0.178013951  0.824287703 -0.222698508 -0.040342745
[16] -0.126437263  0.071258070 -0.148907792  0.078667375 -0.087465743
[21]  0.093310633 -0.122621987 -0.020635016 -0.146840728  0.675921307
[26] -0.227425146 -0.032956284 -0.105104111  0.066524468 -0.166075093
[31]  0.104620093 -0.071964980  0.086993795 -0.110953120 -0.009771313
[36] -0.106315699  0.538592547 -0.216558025 -0.033416903 -0.080525516
[41]  0.018627649 -0.174392760  0.110791908 -0.049793222  0.094964870
[46] -0.089998172 -0.015308292 -0.057284165  0.413157273
> (mypacf <- c(rpacf$acf))
 [1] -0.216906446 -0.104806718 -0.191112625 -0.021979115 -0.161886526
 [6] -0.047081058 -0.123988802 -0.013632948 -0.190287725 -0.202374259
[11] -0.356777310  0.754905414  0.022631468  0.022005934 -0.014819356
[16]  0.043267296  0.008467711  0.077159848 -0.100726069 -0.019258003
[21]  0.140163318  0.053431381  0.021184632 -0.006015418 -0.016165610
[26]  0.003921620  0.043699725 -0.046821294 -0.046629764  0.025739925
[31]  0.071146511 -0.010282635 -0.060150593 -0.048444187  0.058721880
[36] -0.025591516  0.001550177 -0.081775934  0.006203055 -0.123150358
[41] -0.043859163 -0.129025292 -0.025570888  0.015936061  0.019650740
[46] -0.090472167  0.040273386 -0.056760623
> 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/474321439657281.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/5vva01439657281.tab") 
> 
> try(system("convert tmp/1viz81439657281.ps tmp/1viz81439657281.png",intern=TRUE))
character(0)
> try(system("convert tmp/2lces1439657281.ps tmp/2lces1439657281.png",intern=TRUE))
character(0)
> try(system("convert tmp/3qyc31439657281.ps tmp/3qyc31439657281.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  1.188   0.218   1.414