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(564410,658506,574787,611567,565210,638288,524970,505151,605350,517957,510879,622942,459903,486911,545974,481494,492324,609265,573243,524622,540071,564556,465319,458048,492603,606596,776475,749810,832426,895273,643875,348031,301771,411429,350941,425245,447041,449723,514318,445044,532552,469484,442289,532681,524463,590857,487590,612157,598030,577042,755394,697253,476835,510995,527816,482667,531528,628748,472131,445430,551715,561949,769474,583410,480271,576444,550457,534892,541769,741041,482062,586176)
> 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/1zvqh1413379245.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/2kclh1413379245.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/3u3qj1413379245.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  0.529275552  0.240849894  0.104093339 -0.141652345
 [6] -0.264087068 -0.207096463 -0.132331732 -0.164068976 -0.067808456
[11] -0.069421710 -0.057071757  0.005653910 -0.184786154 -0.207284912
[16] -0.116624700 -0.148392636 -0.084803838  0.043164541  0.052318771
[21]  0.064219793  0.222015909  0.242890347  0.110704692  0.178949311
[26]  0.082382657 -0.017199004 -0.020010436 -0.045246617 -0.095013156
[31] -0.169385391 -0.152769430 -0.055627723  0.038170617  0.004276419
[36] -0.052462889  0.022348792 -0.059924910 -0.137507283 -0.002624632
[41]  0.053978489 -0.014198535  0.043571311  0.059456847  0.006004700
[46]  0.029209772  0.029461972 -0.022070759  0.019000487
> (mypacf <- c(rpacf$acf))
 [1]  0.529275552 -0.054569378 -0.002029566 -0.258870768 -0.112602655
 [6]  0.027183008  0.031253071 -0.152225761  0.026367416 -0.128430191
[11]  0.029378561  0.006046621 -0.344303014 -0.041692337  0.019390373
[16] -0.120797797 -0.002190787 -0.073464514 -0.101795710  0.065632159
[21]  0.117731272  0.034309090 -0.154052119  0.119681786  0.004500499
[26]  0.006893284 -0.059272788 -0.017180345 -0.062278412 -0.130672306
[31] -0.004503777  0.140332195 -0.029066591 -0.083959751 -0.051719903
[36]  0.047308951 -0.005967302 -0.093194341  0.049505596  0.038181798
[41] -0.082311332  0.041751395 -0.161481581 -0.081385062  0.073212893
[46] -0.059399703 -0.034098601 -0.026148076
> 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/4ke8o1413379245.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/53km21413379245.tab") 
> 
> try(system("convert tmp/1zvqh1413379245.ps tmp/1zvqh1413379245.png",intern=TRUE))
character(0)
> try(system("convert tmp/2kclh1413379245.ps tmp/2kclh1413379245.png",intern=TRUE))
character(0)
> try(system("convert tmp/3u3qj1413379245.ps tmp/3u3qj1413379245.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  1.212   0.192   1.418