R version 2.6.0 (2007-10-03)
Copyright (C) 2007 The R Foundation for Statistical Computing
ISBN 3-900051-07-0

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> x <- c(106.8,114.3,105.7,90.1,91.6,97.7,100.8,104.6,95.9,102.7,104,107.9,113.8,113.8,123.1,125.1,137.6,134,140.3,152.1,150.6,167.3,153.2,142,154.4,158.5,180.9,181.3,172.4,192,199.3,215.4,214.3,201.5,190.5,196,215.7,209.4,214.1,237.8,239,237.8,251.5,248.8,215.4,201.2,203.1,214.2)
> 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$_version), Office for Research Development and Education, URL http://www.wessa.net/rwasp_YOURPAGE.wasp/
> #Source of accompanying publication: Office for Research, Development, and Education
> #Technical description: Write here your technical program description (don't use hard returns!)
> if (par1 == 'Default') {
+ par1 = 10*log10(length(x))
+ } else {
+ par1 <- as.numeric(par1)
+ }
> par2 <- as.numeric(par2)
> par3 <- as.numeric(par3)
> par4 <- as.numeric(par4)
> par5 <- as.numeric(par5)
> if (par2 == 0) {
+ x <- log(x)
+ } else {
+ x <- (x ^ par2 - 1) / par2
+ }
> if (par3 > 0) x <- diff(x,lag=1,difference=par3)
> if (par4 > 0) x <- diff(x,lag=par5,difference=par4)
> postscript(file="/var/www/html/rcomp/tmp/1ts3c1198162352.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> racf <- acf(x,par1,main='Autocorrelation',xlab='lags',ylab='ACF')
> dev.off()
null device 
          1 
> postscript(file="/var/www/html/rcomp/tmp/2p19w1198162352.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> rpacf <- pacf(x,par1,main='Partial Autocorrelation',xlab='lags',ylab='PACF')
> dev.off()
null device 
          1 
> (myacf <- c(racf$acf))
 [1]  1.00000000  0.94889748  0.90003017  0.85698140  0.80022287  0.73277374
 [7]  0.65866276  0.59442910  0.52906818  0.46446913  0.41757978  0.35578420
[13]  0.28257094  0.21362552  0.15028523  0.09142572  0.02424948 -0.03594326
[19] -0.09390708 -0.14187458 -0.17063983 -0.21000972 -0.24637453 -0.28421413
[25] -0.32331489 -0.35002158 -0.38099490 -0.40725537 -0.42457181 -0.44280568
[31] -0.44502530 -0.44288219 -0.43668537 -0.42411213 -0.41382400 -0.40384534
[37] -0.39181466
> (mypacf <- c(rpacf$acf))
 [1]  0.948897477 -0.003777907  0.033169517 -0.158654971 -0.143818022
 [6] -0.132189397  0.056073030 -0.025773649  0.011322158  0.137687694
[11] -0.194360465 -0.190784987 -0.093206511 -0.012766651  0.056493392
[16] -0.034271352  0.004789053 -0.099803389  0.048742238  0.103588125
[21] -0.147957822 -0.012676527 -0.123783643 -0.113418433  0.044755999
[26] -0.008488040  0.028129958  0.079223420 -0.066779810 -0.035716949
[31] -0.016578146  0.007791804  0.051674701 -0.004697261 -0.122743430
[36] -0.031184496
> lengthx <- length(x)
> sqrtn <- sqrt(lengthx)
> 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 1:par1) {
+ 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(mytstat,lengthx),6))
+ a<-table.row.end(a)
+ }
> a<-table.end(a)
> table.save(a,file="/var/www/html/rcomp/tmp/30sme1198162352.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-1,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(mytstat,lengthx),6))
+ a<-table.row.end(a)
+ }
> a<-table.end(a)
> table.save(a,file="/var/www/html/rcomp/tmp/42o7p1198162352.tab") 
> 
> system("convert tmp/1ts3c1198162352.ps tmp/1ts3c1198162352.png")
> system("convert tmp/2p19w1198162352.ps tmp/2p19w1198162352.png")
> 
> 
> proc.time()
   user  system elapsed 
  0.814   0.310   0.930