R version 2.12.1 (2010-12-16)
Copyright (C) 2010 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(5393,5147,4846,3995,4491,4676,5461,4758,5302,5066,3491,4944,5148,5351,5178,4025,4449,4594,4603,4911,5236,4652,3479,4556,4815,4949,4499,3865,3657,4814,4614,4539,4492,4779,3193,3894,4531,4008,3764,3290,3644,3438,3833,3922,3524,3493,2814,3899,3653,3969,3427,3067,3301,3211,3382,3613,3783,3971,2842,4161)
> par8 = ''
> par7 = '0.95'
> par6 = 'White Noise'
> par5 = '12'
> par4 = '0'
> 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/wessaorg/rcomp/tmp/1j9941296668682.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/26shj1296668682.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/3josn1296668682.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  0.575829100  0.409000383  0.368952147  0.435542486
 [6]  0.566396876  0.587842372  0.552110769  0.342738433  0.204658991
[11]  0.200291244  0.342934472  0.527870364  0.292966876  0.109002276
[16]  0.028624977  0.092188184  0.167088302  0.160700201  0.125750165
[21] -0.031128115 -0.156435225 -0.162078329 -0.029699423  0.095615965
[26] -0.113535889 -0.239440035 -0.226499663 -0.213575049 -0.139979376
[31] -0.134475115 -0.140501500 -0.262659079 -0.330706334 -0.307486108
[36] -0.231893016 -0.129545465 -0.279439821 -0.318962485 -0.321584267
[41] -0.285338732 -0.220526861 -0.215158840 -0.172485478 -0.262097254
[46] -0.270441785 -0.243601691 -0.174015369 -0.098262081 -0.153295349
[51] -0.169123806 -0.137720163 -0.146018791 -0.100384165 -0.072238718
[56] -0.032585054 -0.052905280 -0.053072369 -0.055401239 -0.001807263
> (mypacf <- c(rpacf$acf))
 [1]  0.575829100  0.115827073  0.142572870  0.238383828  0.339619727
 [6]  0.238938681  0.201903811 -0.160775683 -0.272578392 -0.294584077
[11] -0.075520696  0.304934090 -0.135609084 -0.141975996 -0.079408324
[16]  0.071026270 -0.000709407 -0.141592367 -0.122559740 -0.020713814
[21]  0.004165155 -0.022527875 -0.004671379  0.097413829 -0.115504997
[26] -0.030073309  0.165833921 -0.034950371 -0.033041105 -0.062160378
[31]  0.020629426 -0.021342950 -0.015348598 -0.061737417 -0.156403850
[36] -0.036625789 -0.034661632  0.116745904 -0.021308243 -0.016352938
[41]  0.060879345  0.083766663  0.080983848 -0.056652814 -0.011840432
[46] -0.040378140 -0.046202784 -0.005551408  0.119291361 -0.007911846
[51]  0.044638672 -0.062258850 -0.007522406 -0.058321549 -0.076827702
[56] -0.002828433  0.013386629 -0.028227018  0.083256500
> 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/412zc1296668682.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/54r1d1296668682.tab") 
> 
> try(system("convert tmp/1j9941296668682.ps tmp/1j9941296668682.png",intern=TRUE))
character(0)
> try(system("convert tmp/26shj1296668682.ps tmp/26shj1296668682.png",intern=TRUE))
character(0)
> try(system("convert tmp/3josn1296668682.ps tmp/3josn1296668682.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  0.990   0.100   1.159