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(2.79,3.08,3.89,3.7,4.61,5.07,5.22,4.93,5.15,4.8,3.89,3.54,3.34,2.8,1.6,1.53,0.69,-0.11,-0.67,-0.2,-0.62,-0.58,-0.31,-0.25,-0.08,0.13,0.94,1.05,1.59,2.03,2.15,2.06,2.56,2.55,2.53,2.6,2.71,2.82,2.93,2.88,2.89,3.27,3.32,3.14,3.04,3.08,3.39,3.23,3.38,3.41,3.14,2.96,2.73,2.21,2.23,2.56,2.39,2.49,2.17,2.16,1.48,1.09,1.25,1.26,1.39,1.69,1.55,1.19,1.08,0.93,0.98,1.01)
> 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/1i56q1395070681.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/2h1i41395070681.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/3neku1395070681.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  0.958591046  0.892346945  0.799829190  0.683152638
 [6]  0.541217494  0.405479110  0.266127924  0.112088906 -0.035453716
[11] -0.169427798 -0.289146550 -0.393652499 -0.453566889 -0.499301399
[16] -0.523784504 -0.532326551 -0.520563526 -0.508781288 -0.486546809
[21] -0.452842806 -0.416465104 -0.375373651 -0.334225990 -0.292349400
[26] -0.255353328 -0.214887757 -0.179566020 -0.145680734 -0.109209999
[31] -0.070979155 -0.034059855  0.004771666  0.048979025  0.088357461
[36]  0.129368653  0.169991735  0.200903856  0.225667773  0.249885281
[41]  0.272279269  0.282528845  0.293776181  0.298526727  0.292710930
[46]  0.272595495  0.253079302  0.220784572  0.183871206
> (mypacf <- c(rpacf$acf))
 [1]  0.958591046 -0.327358820 -0.300844628 -0.255921546 -0.294654432
 [6]  0.204162624 -0.050401515 -0.373298811 -0.026843964  0.008825277
[11]  0.128324004  0.050680156  0.259360560 -0.294562885 -0.052558880
[16] -0.104430737 -0.086416489 -0.056268938 -0.117885235 -0.172085101
[21] -0.050673652  0.128912530 -0.077685147 -0.052189198  0.148092013
[26] -0.097515472 -0.020855284 -0.107574690  0.006579464 -0.101231224
[31]  0.063783025 -0.052092497 -0.010713514  0.019757008  0.003610526
[36]  0.015215404 -0.179644695  0.047096946 -0.001495776  0.102327876
[41] -0.009329368 -0.030334617 -0.055299535 -0.030092671  0.027306570
[46]  0.003603969 -0.120439297  0.005884614
> 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/4ofe71395070681.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/5171g1395070681.tab") 
> 
> try(system("convert tmp/1i56q1395070681.ps tmp/1i56q1395070681.png",intern=TRUE))
character(0)
> try(system("convert tmp/2h1i41395070681.ps tmp/2h1i41395070681.png",intern=TRUE))
character(0)
> try(system("convert tmp/3neku1395070681.ps tmp/3neku1395070681.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  2.932   0.562   3.492