R version 2.15.3 (2013-03-01) -- "Security Blanket"
Copyright (C) 2013 The R Foundation for Statistical Computing
ISBN 3-900051-07-0
Platform: i686-pc-linux-gnu (32-bit)

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> x <- c(1.01,1.02,1.04,1.06,1.06,1.06,1.06,1.06,1.02,0.98,0.99,0.99,0.94,0.96,0.98,1.01,1.01,1.02,1.04,1.03,1.05,1.08,1.17,1.11,1.11,1.11,1.2,1.21,1.31,1.37,1.37,1.26,1.23,1.17,1.06,0.95,0.92,0.92,0.9,0.93,0.93,0.97,0.96,0.99,0.98,0.96,1,0.99,1.03,1.02,1.07,1.13,1.15,1.16,1.14,1.15,1.15,1.16,1.17,1.22,1.26,1.29,1.36,1.38,1.37,1.37,1.37,1.36,1.38,1.4,1.44,1.42)
> 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/1hxt21365337020.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/2evzn1365337020.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/33znn1365337020.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  0.933363233  0.837914111  0.730252745  0.621607568
 [6]  0.504992834  0.400848253  0.311583821  0.223856594  0.134812495
[11]  0.054141042 -0.009672391 -0.079660266 -0.145236361 -0.193805840
[16] -0.232979577 -0.265905427 -0.284012617 -0.286501799 -0.284919094
[21] -0.283435453 -0.271560303 -0.245445507 -0.216550076 -0.201798644
[26] -0.184601348 -0.168645771 -0.143034836 -0.114385359 -0.070679807
[31] -0.015081409  0.038783363  0.092765987  0.146661503  0.194823242
[36]  0.230118572  0.258166831  0.276930370  0.272750262  0.247126137
[41]  0.216352375  0.173183611  0.107269331  0.038292595 -0.016198540
[46] -0.056600333 -0.096904770 -0.119932725 -0.144608906
> (mypacf <- c(rpacf$acf))
 [1]  0.933363233 -0.258107739 -0.106258780 -0.041897695 -0.133153194
 [6]  0.050427267  0.017234588 -0.113551840 -0.083490852 -0.012544756
[11]  0.037087368 -0.160667221 -0.022489631  0.048668949 -0.068663369
[16] -0.006534347  0.044199803 -0.010746964 -0.048161008 -0.027026628
[21]  0.043774253  0.035327676 -0.006443770 -0.134271048  0.004049547
[26] -0.020361790  0.113572388  0.011594201  0.065807148  0.081153220
[31] -0.014826894  0.063890667  0.035540002 -0.014718347  0.015190853
[36]  0.010630083 -0.010659164 -0.131108563 -0.069421761  0.024251724
[41] -0.132896880 -0.134959287  0.052812967  0.064118316  0.045444339
[46] -0.036320625  0.119713906 -0.145648304
> 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/4ll9k1365337020.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/58rjc1365337020.tab") 
> 
> try(system("convert tmp/1hxt21365337020.ps tmp/1hxt21365337020.png",intern=TRUE))
character(0)
> try(system("convert tmp/2evzn1365337020.ps tmp/2evzn1365337020.png",intern=TRUE))
character(0)
> try(system("convert tmp/33znn1365337020.ps tmp/33znn1365337020.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  2.031   0.394   2.421