R version 3.3.1 (2016-06-21) -- "Bug in Your Hair"
Copyright (C) 2016 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu (64-bit)

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> x <- c(84543,55735,65814,55382,57422,57729,48213,44789,50998,50328,47719,19946,80608,50747,61687,47539,54412,83362,36911,39254,37597,32557,35537,21500,56125,37432,43347,36870,36247,41293,36190,33381,36609,41861,45926,45079,51469,39013,37036,34865,37505,39379,35653,30515,35984,41068,37851,40333,56004,39797,37960,34357,35069,45299,40475,36277,41910,45234,46425,73241)
> 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. 1.2.327 (Mon, 30 Nov 2015 06:58:35 +0000)
> #Author: root
> #To cite this work: Wessa P., (2015), (Partial) Autocorrelation Function (v1.0.12) 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)
> x <- na.omit(x)
> 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/1gxzo1477059972.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/2e4i81477059972.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/3fhmm1477059972.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  0.20743983  0.31889500  0.19137711  0.16705346  0.21945119
 [7] -0.14006046  0.10503094  0.10325648  0.06782063  0.14428321  0.01132166
[13]  0.41756468  0.02154374  0.09602364  0.01309472  0.00134852  0.09981016
[19] -0.11017356 -0.04849352 -0.05688419 -0.08217969 -0.04252216 -0.09040651
[25]  0.07066923 -0.14756148 -0.13563270 -0.16034407 -0.12706363 -0.10802642
[31] -0.13240524 -0.06339980 -0.05027849 -0.04009671 -0.07357075 -0.06203174
[37] -0.06804806 -0.19783687 -0.20528765 -0.16615995 -0.12391931 -0.10622244
[43] -0.01711524 -0.08158939 -0.04142417  0.01092119 -0.02916759  0.03869128
[49] -0.07295347
> (mypacf <- c(rpacf$acf))
 [1]  0.207439831  0.288268269  0.096298406  0.042264996  0.129083903
 [6] -0.296052480  0.060413862  0.188544424  0.006358197  0.096272219
[11] -0.002501657  0.319423710 -0.177616421 -0.079123882 -0.071371913
[16] -0.035520032  0.024926795  0.082200758 -0.132604187 -0.114351646
[21] -0.042376000 -0.066850193  0.075203319  0.009843398 -0.146407652
[26] -0.175564343 -0.046465244  0.018185837 -0.034481590  0.105614905
[31]  0.094221067 -0.022789323  0.014638683 -0.056101408 -0.088756590
[36] -0.081653655 -0.028015493 -0.054722191  0.073148482  0.002833982
[41] -0.017810467  0.119885856 -0.107270430 -0.117785588  0.061374684
[46]  0.031596997  0.005011695 -0.020236242
> 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/43xpe1477059972.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/5v4i01477059972.tab") 
> 
> try(system("convert tmp/1gxzo1477059972.ps tmp/1gxzo1477059972.png",intern=TRUE))
character(0)
> try(system("convert tmp/2e4i81477059972.ps tmp/2e4i81477059972.png",intern=TRUE))
character(0)
> try(system("convert tmp/3fhmm1477059972.ps tmp/3fhmm1477059972.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  1.182   0.092   1.286