R version 2.6.1 (2007-11-26)
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 = '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$_version), Office for Research Development and Education, URL http://www.wessa.net/rwasp_YOURPAGE.wasp/
> #Source of accompanying publication: Office for Research, Development, and Education
> #Technical description: Write here your technical program description (don't use hard returns!)
> if (par1 == 'Default') {
+ par1 = 10*log10(length(x))
+ } else {
+ par1 <- as.numeric(par1)
+ }
> par2 <- as.numeric(par2)
> par3 <- as.numeric(par3)
> par4 <- as.numeric(par4)
> par5 <- as.numeric(par5)
> if (par2 == 0) {
+ x <- log(x)
+ } else {
+ x <- (x ^ par2 - 1) / par2
+ }
> if (par3 > 0) x <- diff(x,lag=1,difference=par3)
> if (par4 > 0) x <- diff(x,lag=par5,difference=par4)
> postscript(file="/var/www/html/rcomp/tmp/1dc451198162606.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> racf <- acf(x,par1,main='Autocorrelation',xlab='lags',ylab='ACF')
> dev.off()
null device 
          1 
> postscript(file="/var/www/html/rcomp/tmp/2kldx1198162606.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> rpacf <- pacf(x,par1,main='Partial Autocorrelation',xlab='lags',ylab='PACF')
> dev.off()
null device 
          1 
> (myacf <- c(racf$acf))
 [1]  1.000000000  0.089717384 -0.221101478 -0.054195336 -0.132042246
 [6]  0.102740514 -0.105212922 -0.010519283 -0.151173306 -0.130075798
[11]  0.300217387  0.157170202  0.102294629 -0.104850852 -0.139735313
[16]  0.023666194 -0.073143636  0.021861042 -0.110409212 -0.120962660
[21]  0.088283159  0.080359173  0.068968998 -0.072120202 -0.034741921
[26]  0.005470395 -0.020190248 -0.039287275 -0.097765443 -0.031809898
[31]  0.037647214  0.045386852 -0.021145426 -0.058989082 -0.018279192
[36]  0.012991317 -0.022748857
> (mypacf <- c(rpacf$acf))
 [1]  0.089717384 -0.231010136 -0.009638399 -0.187611954  0.133771572
 [6] -0.234967930  0.107609465 -0.342483931  0.044223746  0.111721414
[11]  0.154478437  0.089910711 -0.058924778 -0.014630978 -0.062471234
[16] -0.029247488 -0.048360543 -0.056544759 -0.051852010  0.026343116
[21] -0.015973278 -0.084081216 -0.077926355 -0.001577121 -0.029155743
[26]  0.029502832 -0.144775003 -0.005924486 -0.068441111  0.064413522
[31] -0.089648541 -0.077195797 -0.088585458 -0.040831157 -0.028437433
[36] -0.147915925
> 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/3gqj21198162606.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/4dckl1198162606.tab") 
> 
> system("convert tmp/1dc451198162606.ps tmp/1dc451198162606.png")
> system("convert tmp/2kldx1198162606.ps tmp/2kldx1198162606.png")
> 
> 
> proc.time()
   user  system elapsed 
  1.473   0.558   1.565