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(3004,3080,3017,3114,3057,3032,3127,3050,2910,2671,2638,2672,2654,2568,2467,2419,2363,2291,2560,2527,2370,2310,2231,2367,2346,2286,2249,2226,2108,2131,2387,2358,2284,2312,2293,2576,2665,2749,2926,2886,2893,2944,3060,3045,2894,2955,2954,3243,3120,3074,3034,2981,2876,2835,2978,2881,2768,2722,2630,2753,2771,2652,2584,2501,2449,2445,2620,2579,2460,2434,2392,1037,1212,1232,1174,1158,1140,1118,1212,1207,1186,608,627,626,649,619,612,643,623,649,699,693,659,669,668,693)
> 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/1yepj1419845280.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/2xlte1419845280.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/3qlr71419845280.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  0.956912385  0.914225872  0.873660130  0.830057469
 [6]  0.787001382  0.744296220  0.696881790  0.647231777  0.598861188
[11]  0.554697125  0.500102236  0.446215352  0.387593179  0.327992440
[16]  0.270938729  0.227720390  0.186330987  0.146276891  0.099784600
[21]  0.051362995  0.004144687 -0.039853813 -0.078758780 -0.121953645
[26] -0.166428443 -0.180549791 -0.189225625 -0.197138311 -0.199865241
[31] -0.201646121 -0.209761751 -0.218327662 -0.225253150 -0.226017950
[36] -0.219968912 -0.214110069 -0.206957213 -0.205873113 -0.201722186
[41] -0.196100966 -0.188007167 -0.174706099 -0.167592795 -0.161441632
[46] -0.151283072 -0.139092885 -0.124657078 -0.113512073
> (mypacf <- c(rpacf$acf))
 [1]  9.569124e-01 -1.726117e-02  2.880874e-03 -5.747981e-02 -1.700279e-02
 [6] -2.160886e-02 -7.901712e-02 -5.557087e-02 -1.826978e-02  2.255380e-02
[11] -1.516519e-01 -2.862766e-02 -1.028078e-01 -4.426789e-02 -2.242358e-02
[16]  1.223501e-01  1.178433e-04 -3.537234e-03 -1.202827e-01 -7.457302e-02
[21] -2.679059e-02 -2.509697e-02  2.813040e-02 -9.188557e-02 -4.323990e-02
[26]  3.015772e-01  5.488322e-02 -3.643156e-02  2.059699e-02  8.990519e-03
[31] -6.520817e-02 -6.157207e-02 -5.730039e-02  4.982735e-02  9.259197e-02
[36] -9.201214e-02  1.445021e-02 -1.203228e-01 -2.265487e-02 -1.991113e-02
[41]  1.130204e-01  1.120965e-01 -3.587950e-02 -8.819833e-02 -3.216851e-02
[46] -8.552335e-05 -2.250939e-02 -1.457166e-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/49g4b1419845280.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/5m6941419845280.tab") 
> 
> try(system("convert tmp/1yepj1419845280.ps tmp/1yepj1419845280.png",intern=TRUE))
character(0)
> try(system("convert tmp/2xlte1419845280.ps tmp/2xlte1419845280.png",intern=TRUE))
character(0)
> try(system("convert tmp/3qlr71419845280.ps tmp/3qlr71419845280.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  1.389   0.232   1.626