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)

R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.

R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.

Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.

> x <- c(102.43,102.43,102.43,102.43,104.2,104.2,104.2,104.2,104.2,104.2,104.2,104.2,104.2,104.2,104.2,104.2,108.1,109.2,109.2,109.2,109.2,109.2,109.2,109.2,109.2,109.2,109.2,109.2,112.1,112.1,112.1,112.1,112.1,112.1,112.1,112.1,112.1,112.1,112.1,112.1,114.81,114.81,114.81,114.81,114.81,114.81,114.81,114.81,114.81,114.81,114.81,114.81,115.57,115.57,115.57,115.57,115.57,115.57,115.57,115.57)
> 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/1rnlg1323202329.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/2xnjr1323202330.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/3gznb1323202330.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  0.948461837  0.893400181  0.838338525  0.783276869
 [6]  0.739629565  0.695982260  0.652334955  0.608687650  0.568341368
[11]  0.527995086  0.487648804  0.444682489  0.378610931  0.310940249
[16]  0.243269567  0.175598885  0.133078469  0.097651717  0.062224964
[21]  0.026798212  0.003142212 -0.020513788 -0.044169787 -0.070274163
[26] -0.111085220 -0.151896278 -0.192707335 -0.233518392 -0.255627970
[31] -0.277737548 -0.299847126 -0.321956704 -0.331470274 -0.340983844
[36] -0.350497414 -0.360697613 -0.377271885 -0.393846157 -0.410420429
[41] -0.426994701 -0.426092763 -0.425190825 -0.424288887 -0.418609153
[46] -0.395989960 -0.373370767 -0.350751574 -0.328132380
> (mypacf <- c(rpacf$acf))
 [1]  0.948461837 -0.061538202 -0.027944650 -0.029992738  0.083412585
 [6] -0.033219712 -0.025987153 -0.027565399  0.018319617 -0.029837440
[11] -0.026822630 -0.054716885 -0.253881386 -0.051456937 -0.051486839
[16] -0.059140355  0.164089943  0.024652310 -0.039180725 -0.040750244
[21]  0.123804794 -0.028551970 -0.032472716 -0.049931805 -0.111739161
[26] -0.036293243 -0.042644611 -0.059100808  0.036722350 -0.078420251
[31] -0.046588930 -0.057694452  0.121159587 -0.021335144 -0.033812230
[36] -0.041866249  0.030710450 -0.022746315 -0.038826034 -0.058829270
[41]  0.067136941 -0.054897883 -0.038210277 -0.002096152  0.181244078
[46] -0.038152579 -0.030272605 -0.022826678
> 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/4fck21323202330.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/5jt1l1323202330.tab") 
> 
> try(system("convert tmp/1rnlg1323202329.ps tmp/1rnlg1323202329.png",intern=TRUE))
character(0)
> try(system("convert tmp/2xnjr1323202330.ps tmp/2xnjr1323202330.png",intern=TRUE))
character(0)
> try(system("convert tmp/3gznb1323202330.ps tmp/3gznb1323202330.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  1.244   0.224   1.826