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(560576,548854,531673,525919,511038,498662,555362,564591,541657,527070,509846,514258,516922,507561,492622,490243,469357,477580,528379,533590,517945,506174,501866,516141,528222,532638,536322,536535,523597,536214,586570,596594,580523,564478,557560,575093,580112,574761,563250,551531,537034,544686,600991,604378,586111,563668,548604,551174,555654,547970,540324,530577,520579,518654,572273,581302,563280,547612,538712,540735,561649,558685,545732,536352,527676,530455,581744,598714,583775,571477,563278,564872,577537,572399,565430,560619,551227,553397,610893,621668,613148,598778,590623,595902)
> 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/1k2oa1413622946.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/2yims1413622946.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/38dpd1413622946.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  0.809360730  0.536690919  0.393229558  0.372528557
 [6]  0.430595014  0.450671770  0.361133925  0.222534371  0.144958689
[11]  0.187066221  0.353129133  0.439901681  0.253397364  0.002731192
[16] -0.132601404 -0.149291336 -0.094071676 -0.063716738 -0.118216799
[21] -0.215372637 -0.258310383 -0.187120524 -0.010107853  0.111796001
[26]  0.015900581 -0.143334568 -0.210229005 -0.180795793 -0.099419522
[31] -0.041783942 -0.040048742 -0.080906998 -0.078657211  0.007556319
[36]  0.171626405  0.287062742  0.213481499  0.079808294  0.012315643
[41]  0.011402129  0.053364331  0.081494317  0.067772739  0.017192014
[46] -0.011391586  0.010912635  0.088101400  0.139150586
> (mypacf <- c(rpacf$acf))
 [1]  0.809360730 -0.343177122  0.287661980  0.091055030  0.227217838
 [6] -0.067554351 -0.110734475 -0.064913166  0.062184702  0.154352970
[11]  0.337771017 -0.180061862 -0.548237787 -0.002034053 -0.025855516
[16] -0.047436566 -0.085759693  0.008896872  0.078541381  0.039770968
[21]  0.059930496  0.032547655  0.050531360  0.148739069 -0.060160126
[26]  0.019377313 -0.006259060 -0.011743871 -0.050947025 -0.036336241
[31]  0.117440674 -0.002927845  0.087417143 -0.043996971  0.038475470
[36]  0.020796731 -0.070467222  0.004073194 -0.075339656 -0.062472197
[41]  0.029089318 -0.036446061  0.015078414 -0.024480919 -0.026565814
[46] -0.094889956 -0.087033260  0.034387776
> 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/4wkc31413622946.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/5eacg1413622946.tab") 
> 
> try(system("convert tmp/1k2oa1413622946.ps tmp/1k2oa1413622946.png",intern=TRUE))
character(0)
> try(system("convert tmp/2yims1413622946.ps tmp/2yims1413622946.png",intern=TRUE))
character(0)
> try(system("convert tmp/38dpd1413622946.ps tmp/38dpd1413622946.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  1.165   0.168   1.347