R version 3.2.2 (2015-08-14) -- "Fire Safety"
Copyright (C) 2015 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu (64-bit)

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> x <- c(1795,1756,2237,1960,1829,2524,2077,2366,2185,2098,1836,1863,2044,2136,2931,3263,3328,3570,2313,1623,1316,1507,1419,1660,1790,1733,2086,1814,2241,1943,1773,2143,2087,1805,1913,2296,2500,2210,2526,2249,2024,2091,2045,1882,1831,1964,1763,1688,2149,1823,2094,2145,1790,1996,2097,1795,1963,2041,1746,2210,2949,3110,3716,3014,1515,1498,1366,1607,1757,1623,1451,1765)
> 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/1ozl71445436691.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/25zvg1445436691.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/3o8yv1445436691.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  0.696290777  0.355094843  0.053639198 -0.248741492
 [6] -0.321049640 -0.284982179 -0.263856919 -0.212601159 -0.078958264
[11] -0.030880055 -0.007697812  0.028082245 -0.088438382 -0.113374258
[16] -0.139869078 -0.189272036 -0.130370299 -0.043647106  0.042021657
[21]  0.094188981  0.176022461  0.189195383  0.184609030  0.193773111
[26]  0.124765417  0.059131931 -0.004334592 -0.083301815 -0.105874109
[31] -0.095193464 -0.059516123 -0.078013028 -0.025474989 -0.001170712
[36] -0.048504928 -0.029939693 -0.064414746 -0.137781179 -0.135992734
[41] -0.158691841 -0.161508334 -0.080389592  0.083995706  0.238862765
[46]  0.401792414  0.415532710  0.256317644  0.119718316
> (mypacf <- c(rpacf$acf))
 [1]  0.696290777 -0.251807555 -0.166913623 -0.296896544  0.137728083
 [6] -0.038232836 -0.160334948 -0.124983408  0.177684825 -0.131076029
[11] -0.091370248 -0.040710399 -0.214594128  0.086817482 -0.219458976
[16] -0.094330539 -0.023368895  0.013455146 -0.034572988 -0.153360348
[21]  0.094895867  0.033958416  0.003989559 -0.041004842  0.053465088
[26] -0.031199883  0.021505153 -0.112454652  0.046073830  0.023657653
[31]  0.015917795 -0.176813341  0.127572016  0.045920775 -0.149643904
[36] -0.013015441 -0.030583717 -0.067152561 -0.049195621 -0.219567532
[41] -0.021362947  0.032305994  0.144940961  0.061736410  0.060081510
[46] -0.040875592 -0.023872313 -0.046702681
> 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/4ihtn1445436691.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/5pn5t1445436691.tab") 
> 
> try(system("convert tmp/1ozl71445436691.ps tmp/1ozl71445436691.png",intern=TRUE))
character(0)
> try(system("convert tmp/25zvg1445436691.ps tmp/25zvg1445436691.png",intern=TRUE))
character(0)
> try(system("convert tmp/3o8yv1445436691.ps tmp/3o8yv1445436691.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  1.199   0.209   1.411