R version 3.0.2 (2013-09-25) -- "Frisbee Sailing"
Copyright (C) 2013 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu (64-bit)

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> x <- c(1.3,1.2,1.1,1.4,1.5,1.4,1.1,1.1,1,1.4,1.3,1.2,1.5,1.6,1.8,1.5,1.3,1.6,1.6,1.8,1.8,1.6,1.8,2,1.3,1.1,1,1.2,1.2,1.3,1.3,1.4,1.1,0.9,1,1.1,1.4,1.5,1.8,1.8,1.8,1.7,1.5,1.1,1.3,1.6,1.9,1.9,2,2.2,2.2,2,2.3,2.6,3.2,3.2,3.1,2.8,2.3,1.9,1.9,2,2,1.8,1.6,1.4,0.2,0.3,0.4,0.7,1,1.1,0.8,0.8,1,1.1,1,0.8,1.6,1.5,1.6,1.6,1.6,1.9,2,1.9,2,2.1,2.3,2.3,2.6,2.6,2.7,2.6,2.6,2.4,2.5,2.5,2.5,2.4,2.1,2.1,2.3,2.3,2.3,2.9,2.8,2.9,3,3,2.9,2.6,2.8,2.9,3.1,2.8,2.4,1.6,1.5,1.7,1.4,1.1,0.8,1.2,0.8,0.9,0.9,1,0.9,1.1,1,0.7)
> par8 = ''
> par7 = '0.95'
> par6 = 'White Noise'
> par5 = '12'
> par4 = '0'
> par3 = '1'
> par2 = '1'
> par1 = 'Default'
> par8 <- ''
> par7 <- '0.95'
> par6 <- 'White Noise'
> par5 <- '12'
> par4 <- '0'
> par3 <- '1'
> par2 <- '1'
> par1 <- 'Default'
> #'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/1cii11425307579.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/2f5gj1425307579.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/3872n1425307579.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]  1.000000e+00  1.280516e-01 -4.758353e-06 -1.182174e-01 -2.295205e-02
 [6] -3.202755e-02  2.150115e-03  7.241248e-02  1.407182e-01  1.482393e-01
[11] -6.932524e-03 -8.384866e-02 -4.445076e-01 -9.648479e-02 -1.034446e-02
[16]  5.146813e-02  8.580163e-02  8.677716e-03  9.022954e-02 -2.901340e-02
[21] -1.493385e-01 -1.241301e-01
> (mypacf <- c(rpacf$acf))
 [1]  0.128051575 -0.016675394 -0.118049486  0.007551382 -0.031132419
 [6] -0.004036866  0.073418787  0.119348126  0.121034818 -0.023980111
[11] -0.054428435 -0.424371517 -0.016636123 -0.015573870 -0.042711949
[16]  0.089967492 -0.045524875  0.124424403  0.040764548 -0.053688326
[21]  0.023045405
> 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/48dy61425307579.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/5ffgp1425307579.tab") 
> 
> try(system("convert tmp/1cii11425307579.ps tmp/1cii11425307579.png",intern=TRUE))
character(0)
> try(system("convert tmp/2f5gj1425307579.ps tmp/2f5gj1425307579.png",intern=TRUE))
character(0)
> try(system("convert tmp/3872n1425307579.ps tmp/3872n1425307579.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  1.202   0.219   1.436