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(15.58,15.66,15.73,15.74,15.77,15.78,15.8,15.81,15.82,15.88,15.85,15.89,15.92,16.02,16.1,16.13,16.21,16.25,16.27,16.21,16.21,16.24,16.32,16.32,16.36,16.48,16.54,16.58,16.56,16.55,16.58,16.53,16.6,16.46,16.48,16.48,16.49,16.54,16.67,16.72,16.79,16.86,16.84,16.86,16.96,17.01,17.02,17.04,17.04,17.39,17.54,17.57,17.58,17.56,17.63,17.67,17.71,17.75,17.82,17.86,17.89,17.96,18,18.08,18,18.02,18.01,18.02,17.95,17.96,18,18.01)
> 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/1hu031353678419.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/2594b1353678419.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/326pm1353678419.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  0.144101248  0.056089920 -0.091274394 -0.011162407
 [6]  0.073786958 -0.097280504 -0.141831531 -0.078802550  0.094931709
[11] -0.022109317  0.117948101  0.166888900  0.075893617  0.028668445
[16] -0.183098209 -0.194537660 -0.138324490 -0.159128886 -0.189651519
[21] -0.112197371 -0.114581687 -0.031224852  0.106185596  0.132803802
[26]  0.074996188 -0.074640064 -0.005529033 -0.038459483 -0.041273185
[31] -0.205394391 -0.013163959 -0.025435004  0.120622935  0.008566039
[36]  0.117930570  0.165447332  0.070283209  0.048913546 -0.110663787
[41]  0.012517163 -0.012129959 -0.068584194 -0.030878068 -0.054932747
[46]  0.057399434 -0.039753993  0.054870126  0.084961460
> (mypacf <- c(rpacf$acf))
 [1]  0.144101248  0.036073830 -0.106613438  0.014869022  0.086827001
 [6] -0.135650398 -0.125394652 -0.008466896  0.111126812 -0.090127571
[11]  0.134527582  0.197046876 -0.023513787 -0.042231764 -0.139802232
[16] -0.173944159 -0.119408256 -0.126742604 -0.128190042 -0.062526211
[21] -0.137307934 -0.104119583  0.029999329  0.085993196 -0.012051156
[26] -0.101333584  0.126637717  0.023018541 -0.058441594 -0.135907366
[31]  0.121208125 -0.083340859  0.017067551 -0.086195341  0.063259632
[36] -0.053346688 -0.138550507 -0.021928135 -0.082667123 -0.041568778
[41] -0.014526860 -0.038976337  0.069382516 -0.076023689 -0.053642834
[46] -0.090991320 -0.036218131  0.021378695
> 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/48qy01353678419.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/5a6o01353678419.tab") 
> 
> try(system("convert tmp/1hu031353678419.ps tmp/1hu031353678419.png",intern=TRUE))
character(0)
> try(system("convert tmp/2594b1353678419.ps tmp/2594b1353678419.png",intern=TRUE))
character(0)
> try(system("convert tmp/326pm1353678419.ps tmp/326pm1353678419.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  1.782   0.459   2.228