R version 2.9.0 (2009-04-17)
Copyright (C) 2009 The R Foundation for Statistical Computing
ISBN 3-900051-07-0

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> x <- c(8.6,8.5,8.3,7.8,7.8,8,8.6,8.9,8.9,8.6,8.3,8.3,8.3,8.4,8.5,8.4,8.6,8.5,8.5,8.4,8.5,8.5,8.5,8.5,8.5,8.5,8.5,8.5,8.6,8.4,8.1,8,8,8,8,7.9,7.8,7.8,7.9,8.1,8,7.6,7.3,7,6.8,7,7.1,7.2,7.1,6.9,6.7,6.7,6.6,6.9,7.3,7.5,7.3,7.1,6.9,7.1)
> par7 = '0.95'
> par6 = 'MA'
> par5 = '12'
> par4 = '0'
> par3 = '0'
> par2 = '1'
> par1 = '36'
> #'GNU S' R Code compiled by R2WASP v. 1.0.44 ()
> #Author: Prof. Dr. P. Wessa
> #To cite this work: AUTHOR(S), (YEAR), YOUR SOFTWARE TITLE (vNUMBER) in Free Statistics Software (v$_version), Office for Research Development and Education, URL http://www.wessa.net/rwasp_YOURPAGE.wasp/
> #Source of accompanying publication: Office for Research, Development, and Education
> #Technical description: 
> if (par1 == 'Default') {
+ par1 = 10*log10(length(x))
+ } else {
+ par1 <- as.numeric(par1)
+ }
> par2 <- as.numeric(par2)
> par3 <- as.numeric(par3)
> par4 <- as.numeric(par4)
> par5 <- as.numeric(par5)
> if (par6 == 'White Noise') par6 <- 'white' else par6 <- 'ma'
> par7 <- as.numeric(par7)
> if (par2 == 0) {
+ x <- log(x)
+ } else {
+ x <- (x ^ par2 - 1) / par2
+ }
> if (par3 > 0) x <- diff(x,lag=1,difference=par3)
> if (par4 > 0) x <- diff(x,lag=par5,difference=par4)
> postscript(file="/var/www/html/rcomp/tmp/1ihpd1259310986.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> racf <- acf(x, par1, main='Autocorrelation', xlab='time lag', ylab='ACF', ci.type=par6, ci=par7, sub=paste('(lambda=',par2,', d=',par3,', D=',par4,', CI=', par7, ', CI type=',par6,')',sep=''))
> dev.off()
null device 
          1 
> postscript(file="/var/www/html/rcomp/tmp/2g99b1259310986.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> rpacf <- pacf(x,par1,main='Partial Autocorrelation',xlab='lags',ylab='PACF')
> dev.off()
null device 
          1 
> (myacf <- c(racf$acf))
 [1]  1.000000000  0.932493641  0.819456550  0.722194506  0.689827066
 [6]  0.704508706  0.721556603  0.693763926  0.623772997  0.533728038
[11]  0.446266243  0.380041607  0.332470964  0.292058249  0.252434287
[16]  0.195852148  0.126866878  0.054568848 -0.002230197 -0.042287973
[21] -0.066393233 -0.098662079 -0.145246781 -0.196623154 -0.237351369
[26] -0.256724114 -0.264995169 -0.281548124 -0.309537988 -0.340623706
[31] -0.355599156 -0.344151401 -0.332250113 -0.338943663 -0.361806637
[36] -0.385852740 -0.391027942
> (mypacf <- c(rpacf$acf))
 [1]  0.932493641 -0.383945468  0.204054318  0.388198374  0.078564549
 [6] -0.050060205 -0.172066574 -0.040454593 -0.112760018 -0.221074636
[11] -0.074417993 -0.067035142 -0.048996358  0.040221386 -0.124425334
[16]  0.012691904  0.004351821  0.052800400 -0.007932465  0.029914115
[21] -0.079582137 -0.042487407  0.028506055  0.002532133  0.021803402
[26] -0.063073820 -0.083720255  0.006779169 -0.017647966  0.064096247
[31]  0.098768812 -0.178023536 -0.064366565  0.002937701 -0.030038420
[36]  0.003565909
> lengthx <- length(x)
> sqrtn <- sqrt(lengthx)
> 
> #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/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/html/rcomp/tmp/3iujk1259310986.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/html/rcomp/tmp/4pica1259310986.tab") 
> 
> system("convert tmp/1ihpd1259310986.ps tmp/1ihpd1259310986.png")
> system("convert tmp/2g99b1259310986.ps tmp/2g99b1259310986.png")
> 
> 
> proc.time()
   user  system elapsed 
  0.551   0.323   0.682