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(39.28,39.36,39.55,39.64,39.8,39.79,39.79,39.86,39.91,40,40.01,40.01,40.01,39.96,40,39.76,39.68,39.7,39.7,39.73,39.64,39.56,39.67,39.66,39.66,40.05,39.99,40.06,40.08,40.1,40.1,40.12,40.07,40.24,40.58,40.72,40.72,40.89,40.9,41.04,41.27,41.29,41.29,41.33,41.34,41.37,41.33,41.37,41.37,41.42,41.61,41.58,41.75,41.75,41.75,41.85,41.84,41.97,42.01,42.04,42.04,42.06,41.93,41.93,41.99,42.03,42.03,42.12,42.22,42.21,42.23,42.22)
> 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/11p4r1354448121.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/2z7fk1354448121.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/337k31354448121.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  0.081288241  0.091859631  0.169180246 -0.096851443
 [6]  0.083047800  0.090196096 -0.070156639  0.005047323  0.060252865
[11] -0.065216813 -0.106975498 -0.050252728 -0.153209913 -0.174570562
[16]  0.189646566  0.026204483 -0.046201758 -0.011148333 -0.309955209
[21] -0.127717548 -0.046137278 -0.155251201  0.014427067 -0.093942514
[26]  0.010336883 -0.084377651  0.027127789 -0.097077167 -0.154025692
[31]  0.140280405  0.064424723  0.081945497  0.144649349 -0.034351451
[36] -0.051153830  0.035812487 -0.166660327  0.044075301  0.019478193
[41] -0.027073701  0.028957424 -0.002867922  0.069576047 -0.070374261
[46]  0.021644358  0.041668228  0.049137097  0.090893988
> (mypacf <- c(rpacf$acf))
 [1]  0.081288241  0.085818926  0.157571920 -0.131814876  0.076475867
 [6]  0.073474802 -0.062643552 -0.038281088  0.072373443 -0.043057111
[11] -0.144480829 -0.041008543 -0.084837206 -0.155086027  0.243180692
[16]  0.098717367 -0.078550460 -0.123011209 -0.253391898 -0.101781913
[21] -0.049017895 -0.022740833  0.062956067 -0.138711486  0.051315103
[26] -0.131948904  0.075362918 -0.084429722 -0.089484131  0.084162014
[31] -0.005398738 -0.023904006 -0.025311700  0.050502274 -0.051388784
[36] -0.066396030 -0.183325758 -0.058726485 -0.056090292 -0.047935792
[41] -0.015622626 -0.051718220  0.073319526 -0.025585804 -0.036473703
[46] -0.026340032 -0.016697869 -0.142801788
> 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/4rxdc1354448121.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/56m3o1354448121.tab") 
> 
> try(system("convert tmp/11p4r1354448121.ps tmp/11p4r1354448121.png",intern=TRUE))
character(0)
> try(system("convert tmp/2z7fk1354448121.ps tmp/2z7fk1354448121.png",intern=TRUE))
character(0)
> try(system("convert tmp/337k31354448121.ps tmp/337k31354448121.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  1.912   0.421   2.312