R version 2.15.2 (2012-10-26) -- "Trick or Treat"
Copyright (C) 2012 The R Foundation for Statistical Computing
ISBN 3-900051-07-0
Platform: i686-pc-linux-gnu (32-bit)

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> x <- c(14,14,15,13,8,7,3,3,4,4,0,-4,-14,-18,-8,-1,1,2,0,1,0,-1,-3,-3,-3,-4,-8,-9,-13,-18,-11,-9,-10,-13,-11,-5,-15,-6,-6,-3,-1,-3,-4,-6,0,-4,-2,-2,-6,-7,-6,-6,-3,-2,-5,-11,-11,-11,-10,-14,-8,-9,-5,-1,-2,-5,-4,-6,-2,-2,-2,-2,2,1,-8,-1,1,-1,2,2,1,-1,-2,-2,-1,-8,-4,-6,-3,-3,-7,-9,-11,-13,-11,-9,-17,-22,-25,-20,-24,-24,-22,-19,-18,-17,-11,-11,-12,-10,-15,-15,-15,-13,-8,-13,-9,-7,-4,-4,-2,0,-2,-3,1,-2,-1,1,-3,-4,-9,-9,-7,-14,-12,-16,-20,-12,-12,-10,-10,-13,-16)
> 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/fisher/rcomp/tmp/1rtgj1353490567.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/fisher/rcomp/tmp/2j4f51353490567.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/fisher/rcomp/tmp/3cvy01353490567.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 -0.102967842 -0.039903223  0.006620276 -0.130346168
 [6]  0.034605536 -0.030946758  0.128289329 -0.008125744 -0.088883444
[11] -0.010434807 -0.057644321 -0.057606804  0.027776678 -0.051039576
[16]  0.046178961  0.088695315 -0.071459760 -0.009148422  0.018915809
[21]  0.018021431 -0.082554549 -0.083130530  0.174101986 -0.115392221
[26] -0.010889379  0.081949256 -0.167092983 -0.012236797 -0.035970346
[31]  0.007066317  0.040442343  0.006900610  0.012218859 -0.107919131
[36] -0.012036309  0.024391671  0.022619760  0.163629552 -0.083875061
[41] -0.145684248  0.028524271  0.041297673  0.070643258 -0.015573788
[46]  0.116443227  0.052257710 -0.127133212  0.052270617
> (mypacf <- c(rpacf$acf))
 [1] -0.102967842 -0.051046817 -0.002993852 -0.133750906  0.006544332
 [6] -0.040563769  0.125725671 -0.002599788 -0.074228567 -0.038165920
[11] -0.038669782 -0.081428763 -0.005560441 -0.080050140  0.021692127
[16]  0.098093734 -0.043517707 -0.029060781  0.034287278  0.028269909
[21] -0.098042067 -0.124830049  0.122136456 -0.081506299 -0.029419084
[26]  0.040204801 -0.130929675 -0.045577433 -0.030865544 -0.049388251
[31] -0.009394119  0.018260274 -0.030705450 -0.102348871 -0.031917942
[36] -0.020186043  0.044003550  0.130999069 -0.143111870 -0.152818916
[41]  0.024593440  0.047350806  0.047388274 -0.033014962  0.097588050
[46]  0.074594137 -0.027220249 -0.004589445
> lengthx <- length(x)
> sqrtn <- sqrt(lengthx)
> 
> #Note: the /var/fisher/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/fisher/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/fisher/rcomp/tmp/4lb441353490567.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/fisher/rcomp/tmp/5m05z1353490567.tab") 
> 
> try(system("convert tmp/1rtgj1353490567.ps tmp/1rtgj1353490567.png",intern=TRUE))
character(0)
> try(system("convert tmp/2j4f51353490567.ps tmp/2j4f51353490567.png",intern=TRUE))
character(0)
> try(system("convert tmp/3cvy01353490567.ps tmp/3cvy01353490567.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  1.879   0.482   2.344