R version 2.13.0 (2011-04-13)
Copyright (C) 2011 The R Foundation for Statistical Computing
ISBN 3-900051-07-0
Platform: i486-pc-linux-gnu (32-bit)

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> x <- c(36.68,36.77,36.78,36.78,37,37.12,37.3,37.34,37.4,37.4,37.34,37.29,37.39,37.42,37.42,43.49,44.3,44.36,44.52,44.66,44.77,44.77,44.82,44.97,45.28,45.5,45.52,45.52,45.17,45.25,45.32,45.41,45.44,45.44,45.46,45.53,45.61,45.8,45.83,45.83,45.96,46.01,46.18,46.32,46.51,46.51,46.56,46.54,46.62,46.76,46.82,46.82,46.7,46.72,46.47,46.74,46.89,46.89,46.96,47.6,47.67,47.58,47.58,47.58,47.57,47.53,47.68,47.56,47.81,47.81,47.81,47.81,48.12,48.13,48.01)
> 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/wessaorg/rcomp/tmp/1821z1323163384.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/wessaorg/rcomp/tmp/25jv71323163384.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/wessaorg/rcomp/tmp/3o0mh1323163384.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]  1.0000000000  0.0947371146 -0.0253908882  0.0014650430 -0.0203788067
 [6] -0.0405054060 -0.0400057797 -0.0178022945 -0.0091321655  0.0426711143
[11]  0.0139867678 -0.0010210095 -0.0470546187 -0.0871927048 -0.0203004543
[16] -0.0069642435 -0.0008652393 -0.0057236794 -0.0131881319 -0.0050013875
[21] -0.0002717374 -0.0021400759  0.0154130669 -0.0124929103 -0.0114054543
[26]  0.0065731206 -0.0014763691  0.0077555871  0.0065937758  0.0109027082
[31] -0.0193454488 -0.0152521156 -0.0209525712 -0.0034662298  0.0051932734
[36] -0.0047421745 -0.0192552159 -0.0374653940 -0.0231040262 -0.0531366565
[41]  0.0258777092  0.0058838059 -0.0188920842  0.0056388570  0.0829691916
[46] -0.0128890134 -0.0361814939 -0.0217324720 -0.0242764030
> (mypacf <- c(rpacf$acf))
 [1]  0.0947371146 -0.0346772415  0.0073134941 -0.0223426701 -0.0364790205
 [6] -0.0342257539 -0.0129927599 -0.0086458917  0.0428398295  0.0026336503
[11] -0.0031227992 -0.0500880381 -0.0797844165 -0.0054720333 -0.0060306106
[16]  0.0006992095 -0.0112357851 -0.0237179139 -0.0121152736 -0.0051604605
[21] -0.0014948934  0.0221299509 -0.0166419248 -0.0119550579 -0.0019218354
[26] -0.0108417250  0.0089204817  0.0045386705  0.0088826781 -0.0252026588
[31] -0.0177457868 -0.0216319864  0.0010111366  0.0060432078 -0.0044088679
[36] -0.0258637979 -0.0414058505 -0.0228968313 -0.0526323727  0.0380889196
[41] -0.0025909836 -0.0228162771 -0.0046885232  0.0710041257 -0.0332126626
[46] -0.0245901006 -0.0191006005 -0.0199710939
> lengthx <- length(x)
> sqrtn <- sqrt(lengthx)
> 
> #Note: the /var/wessaorg/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/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/wessaorg/rcomp/tmp/48bqd1323163384.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/wessaorg/rcomp/tmp/5ncva1323163384.tab") 
> 
> try(system("convert tmp/1821z1323163384.ps tmp/1821z1323163384.png",intern=TRUE))
character(0)
> try(system("convert tmp/25jv71323163384.ps tmp/25jv71323163384.png",intern=TRUE))
character(0)
> try(system("convert tmp/3o0mh1323163384.ps tmp/3o0mh1323163384.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  0.930   0.149   1.086