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(95.6,74.3,88.5,88,84.3,112.8,105.3,97.2,112.4,123.2,143.7,205.1,102.8,89.4,90.7,101.1,93.6,119.3,106.4,105.2,106.5,117.6,144.2,195.5,109.5,84.9,102.9,93.9,104.6,115.2,104.9,114.9,115.1,126.4,156.7,197.3,116.1,89.1,107.8,100.4,113.6,128.3,113.3,113.7,116.1,133.6,167.7,214.6,120.3,106,103.9,118,116.3,134.8,117.8,123.3,125.2,135.8,158.9,217.9)
> par7 = '0.95'
> par6 = 'MA'
> par5 = '12'
> par4 = '1'
> par3 = '1'
> 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$_version), Office for Research Development and Education, URL http://www.wessa.net/rwasp_YOURPAGE.wasp/
> #Source of accompanying publication: Office for Research, Development, and Education
> #Technical description: 
> if (par1 == 'Default') {
+ par1 = 10*log10(length(x))
+ } else {
+ par1 <- as.numeric(par1)
+ }
> par2 <- as.numeric(par2)
> par3 <- as.numeric(par3)
> par4 <- as.numeric(par4)
> par5 <- as.numeric(par5)
> if (par6 == 'White Noise') par6 <- 'white' else par6 <- 'ma'
> par7 <- as.numeric(par7)
> if (par2 == 0) {
+ x <- log(x)
+ } else {
+ x <- (x ^ par2 - 1) / par2
+ }
> if (par3 > 0) x <- diff(x,lag=1,difference=par3)
> if (par4 > 0) x <- diff(x,lag=par5,difference=par4)
> postscript(file="/var/www/html/rcomp/tmp/1wfda1259357537.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> racf <- acf(x, par1, main='Autocorrelation', xlab='time lag', ylab='ACF', ci.type=par6, ci=par7, sub=paste('(lambda=',par2,', d=',par3,', D=',par4,', CI=', par7, ', CI type=',par6,')',sep=''))
> dev.off()
null device 
          1 
> postscript(file="/var/www/html/rcomp/tmp/2j2371259357537.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> rpacf <- pacf(x,par1,main='Partial Autocorrelation',xlab='lags',ylab='PACF')
> dev.off()
null device 
          1 
> (myacf <- c(racf$acf))
 [1]  1.000000000 -0.719910441  0.454763507 -0.340606833  0.165262588
 [6] -0.106024223  0.080827716 -0.026690373  0.005149037  0.038039069
[11] -0.001579341 -0.035438927 -0.123105714  0.154407392 -0.149431906
[16]  0.225138961 -0.112212432 -0.014425361 -0.001313459  0.027197148
[21] -0.103212325  0.205238315 -0.282144500  0.371852129 -0.362115962
[26]  0.298210309 -0.262186796  0.148285637 -0.082252454  0.063683697
[31] -0.019569964 -0.015365868  0.029191578 -0.043886572  0.055554246
[36] -0.079255109  0.107819273
> (mypacf <- c(rpacf$acf))
 [1] -0.71991044 -0.13183251 -0.13724309 -0.22915179 -0.18394656 -0.09935959
 [7] -0.03768510 -0.05903894  0.03990541  0.15574427  0.06348659 -0.32053999
[13] -0.18195031 -0.16233966 -0.02397449  0.17118017 -0.04828131 -0.11783137
[19]  0.07805937 -0.13832576  0.17112977 -0.11196614  0.06167377 -0.07651452
[25] -0.14204079 -0.02090570  0.05302527 -0.03810662 -0.09940310 -0.12510717
[31] -0.20470856 -0.03994601  0.02305513 -0.03972587  0.01877619 -0.11546363
> 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/3r64o1259357537.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/4yflo1259357537.tab") 
> 
> system("convert tmp/1wfda1259357537.ps tmp/1wfda1259357537.png")
> system("convert tmp/2j2371259357537.ps tmp/2j2371259357537.png")
> 
> 
> proc.time()
   user  system elapsed 
  0.542   0.315   0.644