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(111.5,108.1,124.5,106.3,111.1,121.3,116.5,117.4,123.6,98.4,107.2,118.9,111.9,115.2,124.4,104.6,117,126.2,117.5,122.2,124.1,105.8,107.5,125.6,112.1,120.1,130.6,109.8,122.1,129.5,132.1,133.3,128.4,114.7,114.1,136.9,123.4,134,137,127.8,140.1,140.4,157.8,151.8,141.1,138.8,141.1,139.5,150.7,144.4,146,143.6,143.1,156.4,164.8,145.1,153.4,133.2,131.4,145.9)
> par7 = '0.95'
> par6 = 'White Noise'
> par5 = '12'
> par4 = '1'
> par3 = '1'
> par2 = '0.4'
> 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$_version), Office for Research Development and Education, URL http://www.wessa.net/rwasp_YOURPAGE.wasp/
> #Source of accompanying publication: Office for Research, Development, and Education
> #Technical description: 
> if (par1 == 'Default') {
+ par1 = 10*log10(length(x))
+ } else {
+ par1 <- as.numeric(par1)
+ }
> par2 <- as.numeric(par2)
> par3 <- as.numeric(par3)
> par4 <- as.numeric(par4)
> par5 <- as.numeric(par5)
> if (par6 == 'White Noise') par6 <- 'white' else par6 <- 'ma'
> par7 <- as.numeric(par7)
> if (par2 == 0) {
+ x <- log(x)
+ } else {
+ x <- (x ^ par2 - 1) / par2
+ }
> if (par3 > 0) x <- diff(x,lag=1,difference=par3)
> if (par4 > 0) x <- diff(x,lag=par5,difference=par4)
> postscript(file="/var/www/html/rcomp/tmp/1m6161259782489.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> racf <- acf(x, par1, main='Autocorrelation', xlab='time lag', ylab='ACF', ci.type=par6, ci=par7, sub=paste('(lambda=',par2,', d=',par3,', D=',par4,', CI=', par7, ', CI type=',par6,')',sep=''))
> dev.off()
null device 
          1 
> postscript(file="/var/www/html/rcomp/tmp/28rfh1259782489.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> rpacf <- pacf(x,par1,main='Partial Autocorrelation',xlab='lags',ylab='PACF')
> dev.off()
null device 
          1 
> (myacf <- c(racf$acf))
 [1]  1.000000000 -0.582351120 -0.074622610  0.442496060 -0.373511321
 [6]  0.106678780  0.146024546 -0.247532873  0.174620666 -0.002725889
[11] -0.153652850  0.194727716 -0.102911715 -0.119510832  0.199057245
[16] -0.089502428 -0.054336334  0.069821046 -0.003669911 -0.068572091
[21]  0.080280686 -0.012225355 -0.112390836  0.181497111 -0.128466589
[26]  0.017796205  0.050551087 -0.008456170 -0.101408046  0.098563877
[31]  0.024185611 -0.105398620  0.068232790  0.038663514 -0.110035335
[36]  0.117138939 -0.077738845
> (mypacf <- c(rpacf$acf))
 [1] -0.582351120 -0.626079572  0.018003170  0.013839133  0.082747875
 [6]  0.100319834 -0.031957847 -0.009217874  0.014595899 -0.059885054
[11]  0.020605577  0.008042076 -0.199567667 -0.201764200 -0.033300812
[16]  0.085022531 -0.037143771  0.016980955 -0.065349352 -0.018261700
[21]  0.067833851 -0.098480914  0.019528576 -0.038378639  0.013879935
[26] -0.132498954  0.122219018 -0.077605489 -0.164702656 -0.030213626
[31]  0.069839831  0.003826706  0.075289886 -0.045874949  0.002449572
[36] -0.046289331
> 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/3xwky1259782489.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/41nrj1259782489.tab") 
> system("convert tmp/1m6161259782489.ps tmp/1m6161259782489.png")
> system("convert tmp/28rfh1259782489.ps tmp/28rfh1259782489.png")
> 
> 
> proc.time()
   user  system elapsed 
  0.549   0.323   0.651