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(108.01,101.21,119.93,94.76,95.26,117.96,115.86,111.44,108.16,108.77,109.45,124.83,115.31,109.49,124.24,92.85,98.42,120.88,111.72,116.1,109.37,111.65,114.29,133.68,114.27,126.49,131,104,108.88,128.48,132.44,128.04,116.35,120.93,118.59,133.1,121.05,127.62,135.44,114.88,114.34,128.85,138.9,129.44,114.96,127.98,127.03,128.75,137.91,128.37,135.9,122.19,113.08,136.2,138,115.24,110.95,99.23,102.39,112.67)
> 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$_version), Office for Research Development and Education, URL http://www.wessa.net/rwasp_YOURPAGE.wasp/
> #Source of accompanying publication: Office for Research, Development, and Education
> #Technical description: 
> if (par1 == 'Default') {
+ par1 = 10*log10(length(x))
+ } else {
+ par1 <- as.numeric(par1)
+ }
> par2 <- as.numeric(par2)
> par3 <- as.numeric(par3)
> par4 <- as.numeric(par4)
> par5 <- as.numeric(par5)
> if (par6 == 'White Noise') par6 <- 'white' else par6 <- 'ma'
> par7 <- as.numeric(par7)
> if (par2 == 0) {
+ x <- log(x)
+ } else {
+ x <- (x ^ par2 - 1) / par2
+ }
> if (par3 > 0) x <- diff(x,lag=1,difference=par3)
> if (par4 > 0) x <- diff(x,lag=par5,difference=par4)
> postscript(file="/var/www/html/rcomp/tmp/1ryri1259260358.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> racf <- acf(x, par1, main='Autocorrelation', xlab='time lag', ylab='ACF', ci.type=par6, ci=par7, sub=paste('(lambda=',par2,', d=',par3,', D=',par4,', CI=', par7, ', CI type=',par6,')',sep=''))
> dev.off()
null device 
          1 
> postscript(file="/var/www/html/rcomp/tmp/2iaxt1259260358.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> rpacf <- pacf(x,par1,main='Partial Autocorrelation',xlab='lags',ylab='PACF')
> dev.off()
null device 
          1 
> (myacf <- c(racf$acf))
 [1]  1.00000000  0.40937679  0.14356444  0.28764526  0.19537395  0.27712626
 [7]  0.33031448  0.21040964  0.12247174  0.07496111 -0.09436366  0.12332042
[13]  0.48528291  0.10879871 -0.08115830  0.02670712  0.02404041  0.05479723
[19]  0.08685144  0.03239133 -0.08709919 -0.12370601 -0.24863984 -0.08172116
[25]  0.13634899 -0.06823141 -0.26784259 -0.20418188 -0.12855999 -0.14643484
[31] -0.11404932 -0.07856024 -0.22477020 -0.23177680 -0.26141405 -0.20606131
[37] -0.01589343
> (mypacf <- c(rpacf$acf))
 [1]  0.409376789 -0.028861852  0.287348151 -0.031820256  0.269888850
 [6]  0.091904318  0.054393009 -0.070284680 -0.065634134 -0.281816956
[11]  0.233538199  0.420260598 -0.238190220 -0.129342341 -0.070924495
[16]  0.136369603 -0.132606650 -0.051716180 -0.036495882 -0.122239172
[21]  0.015756387 -0.060590059  0.031147654 -0.128268180  0.132089565
[26] -0.177783902 -0.004459115 -0.056905376 -0.007780914 -0.096009548
[31]  0.056484619 -0.104375528  0.023883210  0.013265245 -0.105134142
[36]  0.019410401
> 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/3es1d1259260358.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/484151259260358.tab") 
> 
> system("convert tmp/1ryri1259260358.ps tmp/1ryri1259260358.png")
> system("convert tmp/2iaxt1259260358.ps tmp/2iaxt1259260358.png")
> 
> 
> proc.time()
   user  system elapsed 
  0.554   0.330   0.668