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(70.38,70.38,70.29,70.42,70.29,70.59,70.64,70.64,70.68,70.78,70.9,71.04,71.15,71.15,71.15,71.07,71.17,71.24,71.23,71.23,71.23,71.24,71.28,71.52,71.52,71.52,71.6,71.61,71.78,71.66,71.86,71.86,71.82,71.8,72.22,72.51,72.56,72.56,72.78,72.88,73.05,73.02,73.08,73.08,73.24,73.82,74,74.37,74.38,74.38,74.36,74.42,74.59,75.07,75.19,75.19,75.21,75.18,75.86,75.93,76.01,73.23,73.23,73.2,73.24,73.36,73.4,73.49,73.49,73.57,73.82,74.08,74.08)
> 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/12csd1420276433.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/2p58m1420276433.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/3b4ba1420276433.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  0.953455752  0.904475255  0.853985086  0.817011731
 [6]  0.778140237  0.739751864  0.700021847  0.658196276  0.623405598
[11]  0.594353704  0.569629407  0.541368617  0.487740753  0.429711150
[16]  0.375472705  0.326701891  0.286516152  0.246914906  0.203300624
[21]  0.158601536  0.115274970  0.075143432  0.035396431 -0.001582897
[26] -0.042070247 -0.084598875 -0.120345064 -0.149194567 -0.173256270
[31] -0.199530958 -0.225667574 -0.249879161 -0.277754185 -0.303220480
[36] -0.323565790 -0.340252363 -0.358362309 -0.377852235 -0.388599177
[41] -0.394839739 -0.400186171 -0.407277823 -0.415674636 -0.422856538
[46] -0.428823916 -0.424926592 -0.420654412 -0.412485228
> (mypacf <- c(rpacf$acf))
 [1]  0.953455752 -0.050621505 -0.041697521  0.122860875 -0.049958100
 [6] -0.020911553 -0.015000042 -0.054051214  0.057780199  0.037445038
[11]  0.014218155 -0.038260819 -0.294536968 -0.061899416  0.013799900
[16] -0.055714712  0.079685984 -0.016388899 -0.080685889 -0.003827084
[21] -0.075158086 -0.047180646 -0.046667119 -0.004475703  0.030778655
[26] -0.039608872  0.030098471  0.027360590 -0.058799157 -0.052550893
[31]  0.001519590 -0.004536435 -0.070640002 -0.005947713  0.038271266
[36] -0.018413807 -0.039907002 -0.030996823  0.030960896 -0.013527579
[41] -0.037545578 -0.015380540 -0.039765395 -0.014958564  0.018394459
[46]  0.067799769 -0.048018315  0.023067257
> 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/4rne71420276433.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/5mmd81420276433.tab") 
> 
> try(system("convert tmp/12csd1420276433.ps tmp/12csd1420276433.png",intern=TRUE))
character(0)
> try(system("convert tmp/2p58m1420276433.ps tmp/2p58m1420276433.png",intern=TRUE))
character(0)
> try(system("convert tmp/3b4ba1420276433.ps tmp/3b4ba1420276433.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  1.206   0.179   1.392