R version 3.3.1 (2016-06-21) -- "Bug in Your Hair"
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Platform: x86_64-pc-linux-gnu (64-bit)

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> x <- c(2421.21,2378.63,2336.00,2250.79,3113.00,3070.38,2421.21,1990.13,2032.71,2032.71,2075.33,2165.17,1904.92,1644.25,1430.79,1430.79,2250.79,2336.00,1686.83,952.46,1340.96,1340.96,1644.25,1819.29,1776.67,1340.96,1559.04,1473.42,2207.79,2032.71,1340.96,824.25,1298.33,1430.79,1559.04,1729.46,1383.54,1084.92,1213.17,1255.75,2378.63,2378.63,1729.46,1644.25,1904.92,1776.67,2122.58,2553.67,2639.29,2032.71,1861.88,1686.83,2856.96,2942.58,2724.50,2942.58,2899.54,2553.67,2942.58,3373.67,3548.71,3027.79,2681.88,2942.58,4065.42,4411.33,4326.13,4496.50,4453.92,4022.83,4757.21,4932.25,5188.29,4411.33,4108.04,4453.92,5278.13,6012.50,5837.46,5837.46,5923.08,5624.00,6401.42,6401.42,6268.96,5534.17,5666.63,5752.25,6315.79,7050.17,6529.21,6789.92,6571.83,6444.00,7439.08,7221.00,6917.71,6486.63,6917.71,7135.79,7396.04,7741.92,7396.04,7609.50,7349.21,7306.63,8386.88,8476.71,8130.83,7524.29,8041.00,8258.67,8519.33,8907.83,8519.33,8822.63,8690.17,8216.04,9211.08,9211.08)
> 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. 1.2.327 (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/1585o1471082458.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/2baee1471082458.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/346xi1471082458.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  0.018817162 -0.301952623 -0.309553033 -0.140991371
 [6]  0.190834813  0.300910041  0.175894029 -0.089058094 -0.332197134
[11] -0.286088182  0.065212377  0.798031953  0.003690066 -0.253092162
[16] -0.244858939 -0.117946955  0.127764365  0.273749706  0.152461780
[21] -0.087045642 -0.325780326 -0.188679089  0.079851908  0.605594256
[26] -0.041288989 -0.189746818 -0.144887361 -0.140570770  0.033676993
[31]  0.280724676  0.155507581 -0.050021505 -0.330089847 -0.180604957
[36]  0.077280132  0.424386839 -0.026096694 -0.115720730 -0.068791991
[41] -0.163472390 -0.056719889  0.274980398  0.183469987 -0.016885356
[46] -0.316521547 -0.159941038  0.038161298  0.317646267
> (mypacf <- c(rpacf$acf))
 [1]  0.018817162 -0.302413789 -0.326419722 -0.304045775 -0.070775258
 [6]  0.095369585  0.211232776  0.185050332 -0.031131839 -0.240332976
[11] -0.235165155  0.676210209 -0.030312746  0.081387166  0.126619901
[16]  0.182844689 -0.102569296  0.015195554 -0.035663302 -0.122820855
[21] -0.095902393  0.175433204 -0.048514450 -0.064559677 -0.054794774
[26]  0.100361272  0.054769329 -0.125404094 -0.166682602  0.074829406
[31]  0.059927924  0.106192716 -0.059266498 -0.134827670 -0.082750890
[36] -0.121370239  0.009596691 -0.133512957 -0.005239048  0.023999121
[41]  0.085497733  0.061593205  0.090511026 -0.034850670 -0.019567357
[46]  0.039176345 -0.023387350 -0.016668018
> 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/4euoh1471082458.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/56jzk1471082459.tab") 
> 
> try(system("convert tmp/1585o1471082458.ps tmp/1585o1471082458.png",intern=TRUE))
character(0)
> try(system("convert tmp/2baee1471082458.ps tmp/2baee1471082458.png",intern=TRUE))
character(0)
> try(system("convert tmp/346xi1471082458.ps tmp/346xi1471082458.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  1.452   0.118   1.601