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(7.55,7.55,7.59,7.59,7.59,7.57,7.57,7.59,7.6,7.64,7.64,7.76,7.76,7.76,7.77,7.83,7.94,7.94,7.94,8.09,8.18,8.26,8.28,8.28,8.28,8.29,8.3,8.3,8.31,8.33,8.33,8.34,8.48,8.59,8.67,8.67,8.67,8.71,8.72,8.72,8.72,8.74,8.74,8.74,8.74,8.79,8.85,8.86,8.87,8.92,8.96,8.97,8.99,8.98,8.98,9.01,9.01,9.03,9.05,9.05)
> par7 = '0.95'
> par6 = 'MA'
> par5 = '12'
> par4 = '0'
> 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$_version), Office for Research Development and Education, URL http://www.wessa.net/rwasp_YOURPAGE.wasp/
> #Source of accompanying publication: Office for Research, Development, and Education
> #Technical description: 
> if (par1 == 'Default') {
+ par1 = 10*log10(length(x))
+ } else {
+ par1 <- as.numeric(par1)
+ }
> par2 <- as.numeric(par2)
> par3 <- as.numeric(par3)
> par4 <- as.numeric(par4)
> par5 <- as.numeric(par5)
> if (par6 == 'White Noise') par6 <- 'white' else par6 <- 'ma'
> par7 <- as.numeric(par7)
> if (par2 == 0) {
+ x <- log(x)
+ } else {
+ x <- (x ^ par2 - 1) / par2
+ }
> if (par3 > 0) x <- diff(x,lag=1,difference=par3)
> if (par4 > 0) x <- diff(x,lag=par5,difference=par4)
> postscript(file="/var/www/html/rcomp/tmp/16qkn1259695623.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> racf <- acf(x, par1, main='Autocorrelation', xlab='time lag', ylab='ACF', ci.type=par6, ci=par7, sub=paste('(lambda=',par2,', d=',par3,', D=',par4,', CI=', par7, ', CI type=',par6,')',sep=''))
> dev.off()
null device 
          1 
> postscript(file="/var/www/html/rcomp/tmp/2ei8z1259695623.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> rpacf <- pacf(x,par1,main='Partial Autocorrelation',xlab='lags',ylab='PACF')
> dev.off()
null device 
          1 
> (myacf <- c(racf$acf))
 [1]  1.000000000  0.282108613 -0.019514273 -0.042867339  0.064319937
 [6]  0.086183047 -0.237504090 -0.252311143 -0.079086498 -0.076510185
[11] -0.153625438 -0.090877428  0.149860716  0.311528821  0.073554305
[16] -0.125263935 -0.012385793  0.179601234  0.101145811 -0.143218792
[21] -0.189723782  0.022132724 -0.007474469 -0.004373741 -0.104602074
[26] -0.018566179  0.032333950 -0.100019620 -0.137065729 -0.038327352
[31]  0.136470536 -0.011168743 -0.088322842 -0.055660680  0.028471785
[36]  0.036583583 -0.005201677
> (mypacf <- c(rpacf$acf))
 [1]  0.2821086134 -0.1076683582 -0.0070297656  0.0853113780  0.0412317127
 [6] -0.2989219923 -0.0955118783  0.0096123622 -0.1279788360 -0.1278618062
[11]  0.0600456596  0.1564678344  0.1719324142 -0.0746031470 -0.1387426494
[16] -0.0164224810  0.0912840278 -0.0009250102 -0.0523914206 -0.0387649419
[21]  0.0808058972 -0.0708518953  0.1222220187 -0.0923254328 -0.0889746917
[26] -0.0944309292 -0.0460924074 -0.0688432961 -0.0134831126  0.0649746513
[31] -0.1205222358  0.0433699510  0.0031286370 -0.1317896937 -0.1079148179
[36]  0.0519561638
> 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/3k3ue1259695623.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/4jyex1259695623.tab") 
> 
> system("convert tmp/16qkn1259695623.ps tmp/16qkn1259695623.png")
> system("convert tmp/2ei8z1259695623.ps tmp/2ei8z1259695623.png")
> 
> 
> proc.time()
   user  system elapsed 
  0.560   0.311   0.664