R version 3.0.3 (2014-03-06) -- "Warm Puppy"
Copyright (C) 2014 The R Foundation for Statistical Computing
Platform: i686-pc-linux-gnu (32-bit)

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> x <- c(85,82,92.4,100.3,105.2,104.5,105.1,105,106.5,106,99.4,107.4,89.6,85.3,96.3,107.7,112.7,110.1,110.4,111.6,113.3,109,106.5,113,95.6,93.8,106.4,116.6,119.1,120.9,117.3,117.6,115.3,112.3,107.7,113.4,94.3,97.8,106.6,113,122.4,114.6,115,118.7,110.4,111.6,105.1,107.5,92.9,91,100.2,112.2,116.5,111.2,113.3,112.2,102.2,105.3,96,101.3,86.2,84.4,93.4,104.8,106.2,101.9,105.5,106.4,103.9,108.6,96.4,102.2,90.3,88.5,100.2,111.6,111.5,112.9,110.7,105.5,110.7,108.9,101.3,109.6,94.4,91.4,105.8,112.9,116.1,113.7,112.9,110.7,114.3,109.7,105.7,114)
> par8 = ''
> par7 = '0.95'
> par6 = 'White Noise'
> par5 = '12'
> par4 = '0'
> par3 = '1'
> par2 = '1'
> par1 = '48'
> par8 <- ''
> par7 <- '0.95'
> par6 <- 'White Noise'
> par5 <- '12'
> par4 <- '0'
> par3 <- '1'
> par2 <- '1'
> par1 <- '48'
> #'GNU S' R Code compiled by R2WASP v. 1.2.291 ()
> #Author: root
> #To cite this work: Wessa P., (2012), (Partial) Autocorrelation Function (v1.0.11) in Free Statistics Software (v$_version), Office for Research Development and Education, URL http://www.wessa.net/rwasp_autocorrelation.wasp/
> #Source of accompanying publication: 
> #
> 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 (par8 != '') par8 <- as.numeric(par8)
> ox <- x
> if (par8 == '') {
+ if (par2 == 0) {
+ x <- log(x)
+ } else {
+ x <- (x ^ par2 - 1) / par2
+ }
+ } else {
+ x <- log(x,base=par8)
+ }
> if (par3 > 0) x <- diff(x,lag=1,difference=par3)
> if (par4 > 0) x <- diff(x,lag=par5,difference=par4)
> postscript(file="/var/wessaorg/rcomp/tmp/1p5rz1394716632.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> op <- par(mfrow=c(2,1))
> plot(ox,type='l',main='Original Time Series',xlab='time',ylab='value')
> if (par8=='') {
+ mytitle <- paste('Working Time Series (lambda=',par2,', d=',par3,', D=',par4,')',sep='')
+ mysub <- paste('(lambda=',par2,', d=',par3,', D=',par4,', CI=', par7, ', CI type=',par6,')',sep='')
+ } else {
+ mytitle <- paste('Working Time Series (base=',par8,', d=',par3,', D=',par4,')',sep='')
+ mysub <- paste('(base=',par8,', d=',par3,', D=',par4,', CI=', par7, ', CI type=',par6,')',sep='')
+ }
> plot(x,type='l', main=mytitle,xlab='time',ylab='value')
> par(op)
> dev.off()
null device 
          1 
> postscript(file="/var/wessaorg/rcomp/tmp/2xg5t1394716632.ps",horizontal=F,onefile=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=mysub)
> dev.off()
null device 
          1 
> postscript(file="/var/wessaorg/rcomp/tmp/3pbea1394716632.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> rpacf <- pacf(x,par1,main='Partial Autocorrelation',xlab='lags',ylab='PACF',sub=mysub)
> dev.off()
null device 
          1 
> (myacf <- c(racf$acf))
 [1]  1.000000000 -0.042935452 -0.106272439 -0.095130256 -0.126503280
 [6] -0.011442505 -0.133325211 -0.081262595 -0.043045910 -0.085729550
[11] -0.150423070  0.062912643  0.775123852 -0.054507371 -0.024538331
[16] -0.146845834 -0.102792000  0.024528840 -0.185644163 -0.052154396
[21]  0.003852583 -0.127603225 -0.072574386  0.086632625  0.600166970
[26] -0.018707354 -0.024422901 -0.185769859 -0.047474740  0.053447170
[31] -0.227586928  0.001096472 -0.018666683 -0.144712832 -0.000597449
[36]  0.053591429  0.442127276  0.060849736 -0.080281205 -0.172532134
[41]  0.025139651 -0.037252757 -0.160152137  0.058484680 -0.083120260
[46] -0.075752460  0.028034990 -0.019014289  0.380111128
> (mypacf <- c(rpacf$acf))
 [1] -0.042935452 -0.108315567 -0.106278425 -0.152503013 -0.054795028
 [6] -0.191898550 -0.161089605 -0.160873242 -0.232947293 -0.394304676
[11] -0.303518194  0.681725415  0.039163479  0.085109554 -0.043520439
[16]  0.099944002 -0.011048371 -0.087476514  0.065470028  0.018069132
[21] -0.100641052  0.140395686 -0.006664061  0.028578840  0.006144484
[26] -0.003294180 -0.072024924 -0.007584687  0.144761774 -0.062523413
[31]  0.018235123 -0.005481372 -0.053383952 -0.030973579 -0.054292679
[36] -0.174215347  0.052957194 -0.117129040 -0.006614468  0.005973467
[41] -0.211764438  0.042830139  0.031791965 -0.073903456  0.028928566
[46]  0.018435476 -0.044467211 -0.079631665
> lengthx <- length(x)
> sqrtn <- sqrt(lengthx)
> 
> #Note: the /var/wessaorg/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/wessaorg/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/wessaorg/rcomp/tmp/46f0i1394716632.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/wessaorg/rcomp/tmp/5a72d1394716632.tab") 
> 
> try(system("convert tmp/1p5rz1394716632.ps tmp/1p5rz1394716632.png",intern=TRUE))
character(0)
> try(system("convert tmp/2xg5t1394716632.ps tmp/2xg5t1394716632.png",intern=TRUE))
character(0)
> try(system("convert tmp/3pbea1394716632.ps tmp/3pbea1394716632.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  2.102   0.375   2.481