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(5204472,5185089,5165433,5124756,5527158,5505864,5204472,5004090,5023473,5023473,5045040,5083806,5144139,5144139,5105373,5004090,5527158,5606874,5486481,5204472,5325138,5144139,5225766,5264805,5305482,5204472,5225766,5083806,5527158,5667207,5546814,5325138,5566197,5305482,5546814,5527158,5587491,5365815,5606874,5587491,5949216,5867589,5546814,5385198,5606874,5305482,5527158,5566197,5647824,5467098,5566197,5626530,5848206,5667207,5426148,5165433,5406765,4743375,5064423,5245149,5426148,5165433,5165433,5165433,5305482,5105373,4842747,4622982,4782414,4159974,4541355,4763031,4803708,4582032,4601415,4541355,4743375,4601415,4321590,4119297,4461366,3718533,4200924,4420689,4420689,4159974,3918915,3899532,4119297,3918915,3537807,3275181,3557190,2894073,3496857,3817632,3918915,3697239,3417141,3617523,3697239,3636906,3033849,2754024,2954133,2351349,2973789,3195465,3376191,3074799,2792790,2954133,3033849,2874417,2271633,2009007,2250066,1586949,2310399,2754024)
> par8 = ''
> par7 = '0.95'
> par6 = 'White Noise'
> par5 = '12'
> par4 = '1'
> par3 = '0'
> par2 = '1'
> par1 = '48'
> par8 <- ''
> par7 <- '0.95'
> par6 <- 'White Noise'
> par5 <- '12'
> par4 <- '0'
> par3 <- '0'
> par2 <- '1'
> par1 <- 'Default'
> 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/1gcuq1439735125.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/2zyab1439735125.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/3a53d1439735125.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$acf))
 [1] 1.0000000 0.9479027 0.9052665 0.8557292 0.8262057 0.7856802 0.7579676
 [8] 0.7361888 0.7236538 0.7031823 0.6921023 0.6875711 0.7001329 0.6479600
[15] 0.6088358 0.5635115 0.5363629 0.4979727 0.4738353 0.4526909 0.4400095
> (mypacf <- c(rpacf$acf))
 [1]  0.94790270  0.06648533 -0.08260409  0.16175586 -0.09500606  0.07523346
 [7]  0.10334782  0.04908932 -0.04033834  0.08825935  0.10241210  0.17086284
[13] -0.61756420  0.14011718  0.07910901 -0.10178835  0.06287159  0.03841640
[19] -0.04100481  0.02651036
> 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/4rdgs1439735125.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/5bne31439735125.tab") 
> 
> try(system("convert tmp/1gcuq1439735125.ps tmp/1gcuq1439735125.png",intern=TRUE))
character(0)
> try(system("convert tmp/2zyab1439735125.ps tmp/2zyab1439735125.png",intern=TRUE))
character(0)
> try(system("convert tmp/3a53d1439735125.ps tmp/3a53d1439735125.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  1.162   0.202   1.374