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(580,575,558,564,581,597,587,536,524,537,536,533,528,516,502,506,518,534,528,478,469,490,493,508,517,514,510,527,542,565,555,499,511,526,532,549,561,557,566,588,620,626,620,573,573,574,580,590,593,597,595,612,628,629,621,569,567,573,584,589,591,595,594,611,613,611,594,543,537,544,555,561,562)
> par7 = '0.95'
> par6 = 'White Noise'
> 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$_version), Office for Research Development and Education, URL http://www.wessa.net/rwasp_YOURPAGE.wasp/
> #Source of accompanying publication: Office for Research, Development, and Education
> #Technical description: 
> if (par1 == 'Default') {
+ par1 = 10*log10(length(x))
+ } else {
+ par1 <- as.numeric(par1)
+ }
> par2 <- as.numeric(par2)
> par3 <- as.numeric(par3)
> par4 <- as.numeric(par4)
> par5 <- as.numeric(par5)
> if (par6 == 'White Noise') par6 <- 'white' else par6 <- 'ma'
> par7 <- as.numeric(par7)
> if (par2 == 0) {
+ x <- log(x)
+ } else {
+ x <- (x ^ par2 - 1) / par2
+ }
> if (par3 > 0) x <- diff(x,lag=1,difference=par3)
> if (par4 > 0) x <- diff(x,lag=par5,difference=par4)
> postscript(file="/var/www/html/rcomp/tmp/1bhjq1273069029.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> racf <- acf(x, par1, main='Autocorrelation', xlab='time lag', ylab='ACF', ci.type=par6, ci=par7, sub=paste('(lambda=',par2,', d=',par3,', D=',par4,', CI=', par7, ', CI type=',par6,')',sep=''))
> dev.off()
null device 
          1 
> postscript(file="/var/www/html/rcomp/tmp/2bhjq1273069029.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> rpacf <- pacf(x,par1,main='Partial Autocorrelation',xlab='lags',ylab='PACF')
> dev.off()
null device 
          1 
> (myacf <- c(racf$acf))
 [1]  1.00000000  0.88971619  0.72125432  0.60801371  0.56437264  0.56527573
 [7]  0.54029465  0.47094635  0.39664693  0.36928140  0.39747274  0.46912263
[13]  0.48445288  0.33477268  0.15378863  0.02864096 -0.02640076 -0.03790699
[19] -0.07032202 -0.13603998 -0.19915550 -0.21463946 -0.18246610 -0.11866126
[25] -0.10481057 -0.21424585 -0.33883491 -0.40800836 -0.41586452 -0.39113774
[31] -0.38605891 -0.40476335 -0.41487713 -0.38544480 -0.31899243 -0.23393558
[37] -0.18693390
> (mypacf <- c(rpacf$acf))
 [1]  0.889716188 -0.337518495  0.270806594  0.117954836  0.134504957
 [6] -0.141155472 -0.039786698  0.025539436  0.149000111  0.106803711
[11]  0.238393484 -0.256791638 -0.662467200  0.145245202 -0.154437317
[16] -0.060683366  0.015081860  0.119897303 -0.029302915 -0.071769810
[21]  0.081028295 -0.034156784 -0.067002423  0.046612031 -0.006047782
[26] -0.039389620  0.030672060 -0.042545316 -0.052255589 -0.003985081
[31]  0.051791270 -0.008041332 -0.043429199  0.083526556 -0.034199195
[36]  0.096915733
> 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/3o9yh1273069029.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/4zif21273069029.tab") 
> 
> try(system("convert tmp/1bhjq1273069029.ps tmp/1bhjq1273069029.png",intern=TRUE))
character(0)
> try(system("convert tmp/2bhjq1273069029.ps tmp/2bhjq1273069029.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  0.527   0.316   1.130