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(17.1,13.4,15.3,14,9.7,13.7,13.7,12.5,9.8,7,-1.9,-2.9,-6.8,-10.4,-17.2,-19.8,-16.8,-23.2,-21.7,-17.6,-13,-12.6,-4,-0.2,3.1,6.5,19.2,26.6,26.6,31.4,31.2,26.4,20.7,20.7,15,13.3,8.7,10.2,4.3,-0.1,-4.6,-3.9,-3.5,-3.4,-2.5,-1.1,0.3,-0.9,3.6,2.7,-0.2,-1,5.8,6.4,9.6,13.2,10.6,10.9,12.9,15.9,12.2,9.1,9,17.4,14.7,17,13.7,9.5,14.8,13.6,12.6,8.9,10.2,12.7,16,10.4,9.9,9.5,8.6,10,3.5,-4.2,-4.4,-1.5,-0.1,0.8,-2.4,-1.2,0.2,-1.9,-1.6,-4.2,-2.2,6.2,5.7,3.1,1.1,-0.9,0.1,-4,-4,-5.3,-8,-6.3,-3.6,-3.5,-5.1,-3.3)
> 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/www/rcomp/tmp/1woq51302622904.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/2cj111302622904.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/3sz6e1302622904.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  0.228316899  0.130998013  0.170077016  0.221880904
 [6]  0.088513700  0.052733223 -0.045962839 -0.178945397 -0.147810602
[11] -0.077887415  0.053428689 -0.576804172 -0.293573576 -0.152666616
[16] -0.073086463 -0.197210344 -0.112029271 -0.174589078  0.024285722
[21]  0.094175194  0.078566193  0.092137680 -0.153628665  0.097094806
[26]  0.113693956  0.116864347 -0.044600111  0.099811749  0.024155116
[31]  0.198538268  0.030083638  0.016572607  0.021136780 -0.094519549
[36]  0.064779013  0.052309262  0.021600007 -0.095632646  0.084496982
[41] -0.039330254  0.068681666 -0.039405979 -0.004073419 -0.064730945
[46] -0.056220049  0.057334355  0.040483480 -0.030899592
> (mypacf <- c(rpacf$acf))
 [1]  0.228316899  0.083206864  0.131369266  0.163067669 -0.009865848
 [6] -0.010986145 -0.118452017 -0.222229233 -0.108917456 -0.006069357
[11]  0.194424589 -0.588482847 -0.041682036 -0.024796393  0.103860684
[16] -0.028658824 -0.034574418 -0.125170325  0.176637130 -0.044845752
[21] -0.060198357 -0.006296630 -0.048488047 -0.293168733 -0.107517018
[26] -0.014705707  0.048175175  0.096874290 -0.043396514 -0.005251515
[31]  0.003459853  0.051186930 -0.007669501 -0.090030209 -0.043177007
[36] -0.076432760  0.003816648 -0.022151794  0.041490015 -0.009002030
[41] -0.006526294  0.119342762 -0.004371879 -0.032528614  0.017181857
[46]  0.037423203  0.033532705 -0.038458580
> 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/46nqq1302622904.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/5t53s1302622904.tab") 
> 
> try(system("convert tmp/1woq51302622904.ps tmp/1woq51302622904.png",intern=TRUE))
character(0)
> try(system("convert tmp/2cj111302622904.ps tmp/2cj111302622904.png",intern=TRUE))
character(0)
> try(system("convert tmp/3sz6e1302622904.ps tmp/3sz6e1302622904.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  1.336   0.228   1.537