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(1070,1240,1200,1280,1180,1190,1190,1230,1470,1190,1190,1400,1130,1260,1260,1260,1130,1220,1180,1280,1140,1160,1170,1410,1100,1280,1330,1260,1070,1260,1270,1410,1160,1130,1160,1300,1080,1380,1260,1250,990,1180,1240,1500,1650,1110,1080,1270,1050,1490,1280,1230,960,1100,1270,1530,1290,1120,1100,1310,1020,1510,1260,1160,970,1020,1210,1530,1350,1070,1140,1250,930,1510,1230,1180,960,960,1240,1640,1350,1100,1120,1290,890,1560,1250,1170,900,860,1310,1610,1440,1130,1220,1400,930,1490,1250,1160,910,880,1300,1550,1460,1120,1270,1410)
> 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/rcomp/tmp/16s8e1311686441.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/20cgb1311686441.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/3lz6x1311686441.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  0.062148900 -0.236120489 -0.390667310 -0.121131951
 [6]  0.111251110  0.329423736  0.065021979 -0.127949515 -0.372702064
[11] -0.217481949  0.022336479  0.775144472  0.054581479 -0.180284546
[16] -0.318719073 -0.107157723  0.095811165  0.319721611  0.038689365
[21] -0.070020528 -0.307453276 -0.200297818  0.006660550  0.602401291
[26]  0.017478325 -0.132218685 -0.272434938 -0.103461234  0.079672112
[31]  0.231356739  0.024175666 -0.032779423 -0.244397975 -0.165093542
[36]  0.021331603  0.503668223 -0.006037028 -0.091122786 -0.218379008
[41] -0.091765812  0.085685358  0.161650339  0.001147121 -0.019736863
[46] -0.212135088 -0.117589821  0.024723623  0.351438860
> (mypacf <- c(rpacf$acf))
 [1]  0.062148900 -0.240913500 -0.380982981 -0.190904230 -0.098983733
 [6]  0.137840761 -0.011692477 -0.022398097 -0.258256685 -0.299207641
[11] -0.329132661  0.613339056 -0.144511750  0.080625478  0.110176073
[16] -0.011632415 -0.071297552  0.021770110 -0.067966642  0.081536327
[21]  0.041895729 -0.018232363  0.063855886  0.010509560 -0.099310831
[26]  0.022055053 -0.055644010 -0.052940039  0.012143273 -0.209885022
[31]  0.006606281 -0.084289364 -0.101025799 -0.024722454  0.026983217
[36]  0.014621903 -0.012866728 -0.016809875 -0.006396278 -0.025575978
[41] -0.010460537 -0.038088450  0.007445264 -0.041115197 -0.029957030
[46]  0.046715362 -0.049678200 -0.170116325
> 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/48r0x1311686441.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/5sdn41311686441.tab") 
> 
> try(system("convert tmp/16s8e1311686441.ps tmp/16s8e1311686441.png",intern=TRUE))
character(0)
> try(system("convert tmp/20cgb1311686441.ps tmp/20cgb1311686441.png",intern=TRUE))
character(0)
> try(system("convert tmp/3lz6x1311686441.ps tmp/3lz6x1311686441.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  1.430   0.090   1.509