R version 2.12.1 (2010-12-16)
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(19097.1,19304.6,19601.7,16006.9,17681.2,19790.4,17014.2,17424.5,18908.9,15692.1,15160,15794.3,16032.1,16065,16236.8,12521,14762.1,15446.9,13635,14212.6,15021.7,14134.3,13721.4,14384.5,15638.6,19711.6,20359.8,16141.4,20056.9,20605.5,19325.8,20547.7,19211.2,19009.5,18746.8,16471.5,18957.2,20515.2,18374.4,16192.9,18147.5,19301.4,18344.7,17183.6,19630,17167.2,17428.5,16016.5,18466.5,18406.6,18174.1,14851.9,16260.7,18329.6,18003.8,15903.8,19554.2,16554.2,16198.9,16571.8,17535.2,16198.1,17487.5,13768,14915.8,17160.9,15607.4,16181.5,17413.2,15116.3,14544.5,15050.6,15535.4,15919.3,15853.1,12336.4,14355.5,16040.8,13867.7,14656.6)
> par8 = ''
> par7 = '0.95'
> par6 = 'White Noise'
> par5 = '12'
> par4 = '0'
> par3 = '1'
> 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/rcomp/tmp/1p8ge1305827225.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/20yun1305827225.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/3c97s1305827225.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 -0.33243123 -0.32311436  0.23353287  0.04003871 -0.14171923
 [7]  0.24722962 -0.25562509  0.16977529  0.10512647 -0.36238180 -0.11507797
[13]  0.62004743 -0.25595035 -0.19292569  0.05607718  0.05626332 -0.04901567
[19]  0.08378166 -0.16090395  0.18969530  0.01466463 -0.30537872  0.01427391
[25]  0.34716018 -0.06921912 -0.19666711 -0.03839795  0.19123261 -0.06335166
[31] -0.01679461  0.01851059  0.05677758 -0.02332008 -0.08619083 -0.13072855
[37]  0.30119277  0.02679658 -0.29526403  0.06645342  0.17036333 -0.17281734
[43]  0.09284599  0.03271685 -0.06753633  0.04259689 -0.02353233 -0.19226159
[49]  0.31902080
> (mypacf <- c(rpacf$acf))
 [1] -0.33243123 -0.48749861 -0.13022312 -0.07691374 -0.09309775  0.25974675
 [7] -0.15761750  0.28112655  0.13784230 -0.23710404 -0.49320629  0.15693298
[13]  0.15588171  0.14127648 -0.14199718 -0.06354423 -0.07759511 -0.12779518
[19] -0.02858014 -0.03461069  0.04594107 -0.08317519  0.02980944 -0.15954860
[25]  0.11658959 -0.11208552 -0.09692910  0.09767412 -0.01524313  0.10841819
[31]  0.04131071 -0.06471377 -0.20333029  0.07389003 -0.17819269  0.07221745
[37] -0.13275860 -0.02258005  0.12080071 -0.00853373 -0.03838650 -0.07994327
[43]  0.08998817 -0.10667303 -0.02041090 -0.08681530  0.03869515 -0.06602365
> 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/4p7zp1305827225.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/5uwn31305827225.tab") 
> 
> try(system("convert tmp/1p8ge1305827225.ps tmp/1p8ge1305827225.png",intern=TRUE))
character(0)
> try(system("convert tmp/20yun1305827225.ps tmp/20yun1305827225.png",intern=TRUE))
character(0)
> try(system("convert tmp/3c97s1305827225.ps tmp/3c97s1305827225.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  1.272   0.204   1.450