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(105.46,105.1,105.09,105.04,104.87,104.67,104.54,104.9,104.9,104.89,104.8,104.41,104.31,103.88,103.88,103.86,103.89,103.98,103.98,104.29,104.29,104.24,103.98,103.54,103.44,103.32,103.3,103.26,103.14,103.11,102.91,103.23,103.23,103.14,102.91,102.42,102.1,102.07,102.06,101.98,101.83,101.75,101.56,101.66,101.65,101.61,101.52,101.31,101.19,101.11,101.1,101.07,100.98,100.93,100.92,101.02,101.01,100.97,100.89,100.62,100.53,100.48,100.48,100.47,100.52,100.49,100.47,100.44,100.35,100.38,100.33,100.32)
> 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/177mh1321351730.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/2l40m1321351730.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/36h4a1321351730.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  0.959177420  0.920241797  0.879345025  0.838831636
 [6]  0.803240234  0.769556582  0.738549256  0.699996507  0.660668981
[11]  0.620461495  0.578206087  0.539687244  0.496963403  0.461435706
[16]  0.425417611  0.390491698  0.356385438  0.317883989  0.279228000
[21]  0.234505264  0.190676594  0.147058996  0.104812308  0.067864719
[26]  0.029286784 -0.007168532 -0.043311786 -0.078523161 -0.111007353
[31] -0.145626967 -0.175493572 -0.211030032 -0.245406081 -0.278233745
[36] -0.309245023 -0.333970711 -0.352304633 -0.365632998 -0.377068246
[41] -0.386482238 -0.393303169 -0.403048294 -0.407332319 -0.413315980
[46] -0.418029654 -0.422334340 -0.426230060 -0.426462700
> (mypacf <- c(rpacf$acf))
 [1]  9.591774e-01  2.756660e-03 -4.427485e-02 -1.804553e-02  4.039367e-02
 [6]  6.648728e-03  1.250980e-02 -1.122160e-01 -3.454316e-02 -2.734428e-02
[11] -4.613994e-02  1.082316e-02 -8.087774e-02  5.177525e-02 -2.040412e-02
[16] -1.042656e-02 -1.808339e-02 -6.920335e-02 -3.799260e-02 -9.147705e-02
[21] -3.856907e-02 -3.826235e-02 -2.333770e-02  1.132144e-02 -4.203653e-02
[26] -2.293818e-02 -1.014007e-02 -1.640712e-02 -7.524715e-04 -5.497039e-02
[31] -3.038062e-05 -9.933697e-02 -4.515706e-02 -2.714683e-02 -1.705400e-02
[36]  2.201663e-02  6.388842e-02  2.320985e-02  1.628495e-02  1.040449e-02
[41]  1.036835e-02 -4.393221e-02  1.609629e-02 -4.288552e-02 -3.667203e-02
[46] -3.548782e-02 -2.316773e-02  6.849511e-03
> 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/4z2r71321351730.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/5e7ol1321351730.tab") 
> 
> try(system("convert tmp/177mh1321351730.ps tmp/177mh1321351730.png",intern=TRUE))
character(0)
> try(system("convert tmp/2l40m1321351730.ps tmp/2l40m1321351730.png",intern=TRUE))
character(0)
> try(system("convert tmp/36h4a1321351730.ps tmp/36h4a1321351730.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  1.116   0.184   1.285