R version 2.12.2 (2011-02-25)
Copyright (C) 2011 The R Foundation for Statistical Computing
ISBN 3-900051-07-0
Platform: x86_64-redhat-linux-gnu (64-bit)

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> x <- c(6827,6178,7084,8162,8462,9644,10466,10748,9963,8194,6848,7027,7269,6775,7819,8371,9069,10248,11030,10882,10333,9109,7685,7602,8350,7829,8829,9948,10638,11253,11424,11391,10665,9396,7775,7933,8186,7444,8484,9948,10252,12282,11637,11577,12417,9637,8094,9280,8334,7899,9994,10078,10801,12950,12222,12246,13281,10366,8730,9614,8639,8772,10894,10455,11179,10588,10794,12770,13812,10857,9290,10925,9491,8919,11607,8852,12537,14759,13667,13731,15110,12185,10645,12161,10840,10436,13589,13402,13103,14933,14147,14057,16234,12389,11595,12772)
> 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. 1.0.44 ()
> #Author: Dr. Ian E. Holliday
> #To cite this work: Ian E. Holliday, 2009, YOUR SOFTWARE TITLE (vNUMBER) in Free Statistics Software (v$_version), Office for Research Development and Education, URL http://www.wessa.net/rwasp_YOURPAGE.wasp/
> #Source of accompanying publication: 
> #Technical description: 
> 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/www/wessaorg/rcomp/tmp/1d7gv1304354879.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/www/wessaorg/rcomp/tmp/24rh11304354879.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/www/wessaorg/rcomp/tmp/38dp31304354879.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]  1.00000000  0.77729806  0.58959885  0.48368540  0.19648338  0.05527735
 [7]  0.07597409  0.02758903  0.15713201  0.39248104  0.45243728  0.55030713
[13]  0.66344333  0.50851353  0.35690907  0.25361076  0.01000118 -0.12688828
[19] -0.11305437 -0.14556863 -0.02986174  0.15608573  0.21463683  0.34481056
[25]  0.43135656  0.31482557  0.20047918  0.10168110 -0.08409769 -0.18074607
[31] -0.18532319 -0.20773225 -0.09475638  0.05989197  0.11182743  0.22822880
[37]  0.30163878  0.20943008  0.11936229  0.01689404 -0.15119632 -0.23241782
[43] -0.24752236 -0.26665210 -0.17860477 -0.06420476 -0.01810400  0.07414454
[49]  0.12959390
> (mypacf <- c(rpacf$acf))
 [1]  0.777298063 -0.036870004  0.093994166 -0.514782708  0.237184850
 [6]  0.190103936  0.077282657  0.358536794  0.241474128 -0.031082274
[11]  0.072792181  0.151819325 -0.240606365 -0.080776453 -0.077958348
[16] -0.084346601 -0.135003632 -0.012282841 -0.001086926  0.083123894
[21] -0.125859981  0.034079935  0.225258515 -0.060269728  0.022131398
[26] -0.093675582  0.106934736  0.002616455 -0.002727180 -0.008114503
[31] -0.036639572  0.009009809 -0.069199462 -0.010062824  0.039038969
[36]  0.009916264 -0.038618869 -0.099222476 -0.030914903  0.031200451
[41] -0.043747345  0.040074429 -0.072679131 -0.048044946 -0.062105684
[46] -0.040531027  0.040186547 -0.036645984
> lengthx <- length(x)
> sqrtn <- sqrt(lengthx)
> 
> #Note: the /var/www/wessaorg/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/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/www/wessaorg/rcomp/tmp/4j7m21304354879.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/www/wessaorg/rcomp/tmp/564de1304354879.tab") 
> 
> try(system("convert tmp/1d7gv1304354879.ps tmp/1d7gv1304354879.png",intern=TRUE))
character(0)
> try(system("convert tmp/24rh11304354879.ps tmp/24rh11304354879.png",intern=TRUE))
character(0)
> try(system("convert tmp/38dp31304354879.ps tmp/38dp31304354879.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  2.140   0.260   2.455