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(3.2,1.9,0,0.6,0.2,0.9,2.4,4.7,9.4,12.5,15.8,18.2,16.8,17.3,19.3,17.9,20.2,18.7,20.1,18.2,18.4,18.2,18.9,19.9,21.3,20,19.5,19.6,20.9,21,19.9,19.6,20.9,21.7,22.9,21.5,21.3,23.5,21.6,24.5,22.2,23.5,20.9,20.7,18.1,17.1,14.8,13.8,15.2,16,17.6,15,15,16.3,19.4,21.3,20.5,21.1,21.6,22.6)
> 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$_version), Office for Research Development and Education, URL http://www.wessa.net/rwasp_YOURPAGE.wasp/
> #Source of accompanying publication: Office for Research, Development, and Education
> #Technical description: 
> if (par1 == 'Default') {
+ par1 = 10*log10(length(x))
+ } else {
+ par1 <- as.numeric(par1)
+ }
> par2 <- as.numeric(par2)
> par3 <- as.numeric(par3)
> par4 <- as.numeric(par4)
> par5 <- as.numeric(par5)
> if (par6 == 'White Noise') par6 <- 'white' else par6 <- 'ma'
> par7 <- as.numeric(par7)
> if (par2 == 0) {
+ x <- log(x)
+ } else {
+ x <- (x ^ par2 - 1) / par2
+ }
> if (par3 > 0) x <- diff(x,lag=1,difference=par3)
> if (par4 > 0) x <- diff(x,lag=par5,difference=par4)
> postscript(file="/var/www/html/rcomp/tmp/1481d1259932027.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> racf <- acf(x, par1, main='Autocorrelation', xlab='time lag', ylab='ACF', ci.type=par6, ci=par7, sub=paste('(lambda=',par2,', d=',par3,', D=',par4,', CI=', par7, ', CI type=',par6,')',sep=''))
> dev.off()
null device 
          1 
> postscript(file="/var/www/html/rcomp/tmp/21njx1259932027.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> rpacf <- pacf(x,par1,main='Partial Autocorrelation',xlab='lags',ylab='PACF')
> dev.off()
null device 
          1 
> (myacf <- c(racf$acf))
 [1]  1.000000000  0.923803781  0.833918666  0.709337603  0.592368183
 [6]  0.461766387  0.330933034  0.215170682  0.119876189  0.057837130
[11]  0.011036806 -0.009456741 -0.015626892 -0.014009908 -0.014523676
[16] -0.005957515 -0.010086813 -0.013193337 -0.024552521 -0.036012099
[21] -0.052587305 -0.070625061 -0.092813560 -0.107403064 -0.120550033
[26] -0.120402313 -0.140407517 -0.164752909 -0.189077897 -0.201144464
[31] -0.213740116 -0.234252503 -0.257509670 -0.269470628 -0.269498661
[36] -0.260864377 -0.248775061
> (mypacf <- c(rpacf$acf))
 [1]  0.923803781 -0.132991443 -0.282200720  0.013898528 -0.133771204
 [6] -0.116714814  0.056051145  0.039349625  0.101229133 -0.008453876
[11]  0.046502632  0.020301319 -0.071399059 -0.071321895  0.062218235
[16] -0.101883996  0.004321450  0.013492569 -0.005745675 -0.021552137
[21] -0.019673287 -0.048023732  0.040614723 -0.044750677  0.066397777
[26] -0.185745842 -0.107898930  0.038039426  0.043983638 -0.066762186
[31] -0.059704494 -0.055997236  0.064256464 -0.014327173  0.010206371
[36] -0.018718092
> 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/34gjl1259932027.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/4twc71259932027.tab") 
> system("convert tmp/1481d1259932027.ps tmp/1481d1259932027.png")
> system("convert tmp/21njx1259932027.ps tmp/21njx1259932027.png")
> 
> 
> proc.time()
   user  system elapsed 
  0.550   0.325   0.698