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(1.5,1.439,1.49,1.502,1.531,1.611,1.644,1.559,1.553,1.494,1.298,1.215,1.179,1.267,1.282,1.304,1.32,1.413,1.38,1.426,1.394,1.354,1.415,1.406,1.44,1.449,1.489,1.53,1.548,1.518,1.507,1.499,1.487,1.487,1.491,1.56,1.587,1.584,1.647,1.666,1.699,1.671,1.622,1.669,1.663,1.624,1.621,1.607,1.671,1.699,1.751,1.821,1.77,1.734,1.703,1.752,1.823,1.827,1.773,1.75,1.733,1.765,1.791,1.773,1.712,1.735,1.729,1.769,1.776,1.709,1.678,1.691)
> 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/1t4591413750381.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/2awh01413750381.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/3eotw1413750381.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]  1.00000000  0.95036223  0.87820331  0.80512187  0.73616518  0.68378414
 [7]  0.64403938  0.61662792  0.60531927  0.59412667  0.57766888  0.54877580
[13]  0.49381585  0.43168581  0.36558156  0.30407424  0.25471311  0.21480938
[19]  0.18232251  0.15034315  0.11769713  0.08050919  0.03816452 -0.01173464
[25] -0.06385717 -0.11338397 -0.15369165 -0.18399973 -0.21213069 -0.22670753
[31] -0.23636416 -0.24792132 -0.26451361 -0.28583120 -0.30944059 -0.33534004
[37] -0.36591901 -0.39132233 -0.40951485 -0.42285427 -0.42616428 -0.42019280
[43] -0.40552802 -0.39451651 -0.39173055 -0.38975891 -0.38332350 -0.37287121
[49] -0.35449179
> (mypacf <- c(rpacf$acf))
 [1]  9.503622e-01 -2.580790e-01  4.244146e-03 -3.059092e-03  1.247246e-01
 [6]  3.232345e-02  7.222336e-02  1.200570e-01 -4.763410e-02 -2.679441e-02
[11] -9.786980e-02 -2.142989e-01  4.436746e-03 -7.979102e-02  9.684872e-03
[16] -5.746363e-03 -1.613819e-02 -3.459369e-02 -1.014648e-01 -1.336704e-03
[21] -6.703671e-02 -1.457597e-02 -4.878078e-02 -3.600009e-02 -7.325813e-03
[26]  2.108342e-03  9.829836e-05 -8.411905e-02  1.211680e-01 -1.000659e-02
[31] -2.901405e-02 -3.285658e-02 -1.430715e-02 -5.220257e-04 -6.916098e-02
[36] -7.146682e-02 -3.671936e-03 -2.663328e-02 -2.110797e-02 -1.628148e-02
[41]  6.576902e-02  5.244384e-02 -7.783896e-02 -4.624431e-02  3.599322e-02
[46]  8.655970e-02  1.804884e-02  6.688419e-02
> 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/46xqx1413750381.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/5vhtj1413750381.tab") 
> 
> try(system("convert tmp/1t4591413750381.ps tmp/1t4591413750381.png",intern=TRUE))
character(0)
> try(system("convert tmp/2awh01413750381.ps tmp/2awh01413750381.png",intern=TRUE))
character(0)
> try(system("convert tmp/3eotw1413750381.ps tmp/3eotw1413750381.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  1.188   0.212   1.404