R version 3.1.0 (2014-04-10) -- "Spring Dance"
Copyright (C) 2014 The R Foundation for Statistical Computing
Platform: i686-pc-linux-gnu (32-bit)

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> x <- c(15579,16348,15928,16171,15937,15713,15594,15683,16438,17032,17696,17745,19394,20148,20108,18584,18441,18391,19178,18079,18483,19644,19195,19650,20830,23595,22937,21814,21928,21777,21383,21467,22052,22680,24320,24977,25204,25739,26434,27525,30695,32436,30160,30236,31293,31077,32226,33865,32810,32242,32700,32819,33947,34148,35261,39506,41591,39148,41216,40225,41126,42362,40740,40256,39804,41002,41702,42254,43605,43271,43221,41373)
> par8 = ''
> par7 = '0.95'
> par6 = 'White Noise'
> par5 = '12'
> par4 = '0'
> par3 = '0'
> par2 = '1'
> par1 = '48'
> par8 <- ''
> par7 <- '0.95'
> par6 <- 'White Noise'
> par5 <- '12'
> par4 <- '0'
> par3 <- '0'
> 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/1sqan1400764431.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/2bt4r1400764431.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/3nz8b1400764431.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]  1.00000000  0.96559908  0.92639989  0.88722716  0.84598228  0.80719190
 [7]  0.76799043  0.72868802  0.69146134  0.65408798  0.61458317  0.57313153
[13]  0.53248087  0.49343397  0.45319998  0.41451270  0.36254751  0.31369116
[19]  0.27428051  0.23881795  0.20187781  0.16579162  0.12973862  0.09158936
[25]  0.05270472  0.01422328 -0.01449096 -0.04292435 -0.07635847 -0.10801413
[31] -0.14071839 -0.18065616 -0.21818952 -0.24763937 -0.27462439 -0.29802392
[37] -0.32023322 -0.34093079 -0.35887235 -0.37188802 -0.37999201 -0.38135818
[43] -0.37846333 -0.38224727 -0.38841508 -0.39359418 -0.40198676 -0.40966946
[49] -0.40884140
> (mypacf <- c(rpacf$acf))
 [1]  0.965599085 -0.088462582 -0.015156740 -0.052043566  0.018517692
 [6] -0.033162597 -0.021115574  0.005860376 -0.026355923 -0.054433218
[11] -0.051268979 -0.008384129 -0.003392735 -0.047700894 -0.003069812
[16] -0.231354053  0.040413451  0.094025222  0.029393325 -0.079925489
[21] -0.018098705 -0.027635300 -0.072699886 -0.040312457 -0.007360036
[26]  0.131294480 -0.069776408 -0.142193401  0.007852406 -0.045806754
[31] -0.111579743 -0.021487468  0.066093786 -0.027844618  0.015367489
[36] -0.034925761 -0.006919483  0.022883178  0.034883859  0.041058505
[41]  0.010983995  0.043916777 -0.082957332 -0.068509633 -0.033992420
[46] -0.023448466 -0.020619592  0.018324817
> 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/4budo1400764431.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/5mbpc1400764431.tab") 
> 
> try(system("convert tmp/1sqan1400764431.ps tmp/1sqan1400764431.png",intern=TRUE))
character(0)
> try(system("convert tmp/2bt4r1400764431.ps tmp/2bt4r1400764431.png",intern=TRUE))
character(0)
> try(system("convert tmp/3nz8b1400764431.ps tmp/3nz8b1400764431.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  1.662   0.279   1.947