R version 2.12.0 (2010-10-15)
Copyright (C) 2010 The R Foundation for Statistical Computing
ISBN 3-900051-07-0
Platform: i486-pc-linux-gnu (32-bit)

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> x <- c(26281,23899,25727,30733,28599,16723,43738,45272,46532,41032,37967,35366,33892,21560,26588,33527,24859,17952,45504,40129,40357,41913,33730,37842,33025,24050,30429,34507,25189,20253,48527,44446,46380,48950,38883,42928,37107,30186,32602,39892,32194,21629,59968,45694,55756,48554,41052,49822,39191,31994,35735,38930,33658,23849,58972,59249,63955,53785,52760,44795,37348,32370,32717,40974,33591,21124,58608,46865,51378,46235,47206,45382,41227,33795,31295,42625,33625,21538,56421,53152,53536,52408,41454,38271,35306,26414,31917,38030,27534,18387)
> par8 = ''
> par7 = '0.95'
> par6 = 'White Noise'
> par5 = '12'
> par4 = '1'
> par3 = '0'
> par2 = '1'
> par1 = '60'
> #'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/rcomp/tmp/18eon1302549408.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/rcomp/tmp/29wz41302549408.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/rcomp/tmp/3i0ll1302549408.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  0.432376718  0.426249712  0.323403982  0.041942407
 [6]  0.197071190  0.171601899  0.098949229  0.205315674  0.078314617
[11] -0.065681368 -0.004769440 -0.231046853 -0.053917249  0.107284529
[16]  0.125183010  0.225689121  0.122383650  0.115513578  0.094451950
[21] -0.013941586  0.096297994  0.016206611  0.042955718  0.016622522
[26] -0.082656052 -0.127063585 -0.237648899 -0.220262084 -0.151816948
[31] -0.162191124 -0.171439315 -0.095611383 -0.192129501 -0.189887487
[36] -0.143161068 -0.252980014 -0.082685767 -0.133441627 -0.090038113
[41] -0.039981052 -0.106623792 -0.119656782 -0.042682055 -0.055484241
[46] -0.065398729  0.036103200 -0.020721475  0.020161918  0.001153388
[51] -0.068813452 -0.051913467 -0.085208776 -0.094265944 -0.022840763
[56] -0.077323947 -0.078614505 -0.073916740 -0.031616859 -0.057702567
[61] -0.001328131
> (mypacf <- c(rpacf$acf))
 [1]  4.323767e-01  2.943238e-01  8.899423e-02 -2.723131e-01  1.786463e-01
 [6]  1.778782e-01 -5.494028e-02  1.217427e-02 -1.785940e-02 -2.000204e-01
[11] -5.692775e-03 -1.669509e-01  1.607162e-01  2.659293e-01  1.734311e-01
[16] -7.278185e-02 -1.157168e-01  1.556809e-01  3.847832e-02 -2.084581e-01
[21]  5.368968e-02 -1.182368e-01 -2.112322e-02 -1.769446e-01 -5.128154e-03
[26]  6.848371e-02 -1.053940e-01 -1.841909e-02  5.553824e-03 -5.087901e-03
[31] -9.315128e-02 -6.470295e-02  1.502263e-02 -1.622285e-01  1.278340e-02
[36] -1.806003e-01  7.607245e-02  1.631160e-02 -2.834249e-02 -6.835406e-04
[41]  1.392987e-01 -1.098512e-02  5.498988e-02  4.023929e-02  3.686410e-02
[46] -4.347526e-02  5.079576e-02 -2.908242e-02  9.926133e-03 -6.917708e-02
[51] -4.168551e-02 -2.699219e-02 -1.109281e-03  2.779545e-02 -3.234445e-02
[56] -4.666393e-02 -6.113042e-05  4.822064e-02 -1.042436e-02 -6.050661e-02
> lengthx <- length(x)
> sqrtn <- sqrt(lengthx)
> 
> #Note: the /var/www/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/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/rcomp/tmp/4r1x31302549408.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/rcomp/tmp/5ix351302549408.tab") 
> 
> try(system("convert tmp/18eon1302549408.ps tmp/18eon1302549408.png",intern=TRUE))
character(0)
> try(system("convert tmp/29wz41302549408.ps tmp/29wz41302549408.png",intern=TRUE))
character(0)
> try(system("convert tmp/3i0ll1302549408.ps tmp/3i0ll1302549408.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  0.810   0.600   1.419