R version 2.12.2 (2011-02-25)
Copyright (C) 2011 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(106.42,106.22,106.32,105.81,105.92,107.54,107.34,107.24,107.74,105.71,105.41,106.22,106.32,106.12,106.22,105.92,105.71,105.71,105.92,105.71,105.41,104.49,101.35,99.72,99.01,97.89,95.86,94.95,95.35,95.15,95.46,95.56,95.05,94.64,93.63,93.12,93.53,97.18,96.27,95.15,97.08,101.95,103.07,103.68,102.87,102.56,103.38,103.27,102.89,102.69,101.54,102.9,101.53,101.96,101.99,101.11,101.75,101.71,104.11,103.57,103.32,103.64,103.68,103.79,103.01,101.54,101.9,103.68,104.62,104.11,105.04,104.83,105.05,104.68,107.32,109.9,109.77,110.69,110.54,110.89,110.95,109.73,110.85,110.39,110.58,110.4,111.07,110.86,111.38,111.44,110.36,110.06,108.34,107.94,107.39,107.1,107.61,107.74,106.9,106.71,106.6,108.21,110.54,110.91,109.51,110.27,111.39,112.13,111.64)
> 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/wessaorg/rcomp/tmp/1jw5x1301847090.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/29xve1301847090.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/32do31301847090.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  0.96426846  0.91568889  0.87050171  0.82788348  0.77941001
 [7]  0.71703081  0.65612469  0.60221758  0.55529694  0.51051477  0.46549785
[13]  0.42200117  0.37635330  0.33203836  0.29045042  0.26009084  0.22755370
[19]  0.18811964  0.15657207  0.12886558  0.10781229  0.08544611  0.06865979
[25]  0.05745988  0.05040841  0.04602096  0.03313224  0.02006215  0.00367661
[31] -0.01506510 -0.03705029 -0.06155922 -0.08128811 -0.10818916 -0.12956258
[37] -0.14765290 -0.16427403 -0.18396074 -0.20823241 -0.23123063 -0.25634287
[43] -0.27931293 -0.29693560 -0.31658070 -0.33790772 -0.36150456 -0.38441232
[49] -0.40602968
> (mypacf <- c(rpacf$acf))
 [1]  0.964268458 -0.201246750  0.057805924 -0.010651769 -0.116243270
 [6] -0.199546643  0.045549142  0.024792901  0.042831390  0.009018143
[11] -0.002611546 -0.032619525 -0.105701793 -0.022209032 -0.002104745
[16]  0.141899980 -0.103957751 -0.074241849  0.114526390 -0.067130029
[21]  0.017456292 -0.017215192  0.124486876 -0.016929915  0.025689443
[26] -0.006701984 -0.145618542 -0.018351019 -0.098410347 -0.015400845
[31] -0.029410870 -0.002296021  0.029541470 -0.113121043  0.092658692
[36] -0.047381720 -0.010717906 -0.087842571 -0.019893304 -0.058725262
[41] -0.068956903 -0.010823106  0.108348797 -0.064256773 -0.079411037
[46] -0.029203990 -0.085846636 -0.030680851
> 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/4pf991301847090.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/5gxfz1301847090.tab") 
> 
> try(system("convert tmp/1jw5x1301847090.ps tmp/1jw5x1301847090.png",intern=TRUE))
character(0)
> try(system("convert tmp/29xve1301847090.ps tmp/29xve1301847090.png",intern=TRUE))
character(0)
> try(system("convert tmp/32do31301847090.ps tmp/32do31301847090.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  0.920   0.100   1.073