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(13671,15698,18150,16245,18479,18479,18819,18059,17004,16981,16578,21604,13419,14487,17349,15646,17419,17358,18221,19554,14386,16833,18067,19662,12192,15081,13698,18474,13871,15669,17597,15469,15374,16568,11619,16780,8700,8906,9612,10073,10275,9921,13237,9572,10425,11385,9970,15456,7708,8892,11145,11069,9893,10929,12240,10411,9747,9950,10079,14064,8368,9558,10432,10068,9915,9549,10433,10009,10327,9453,9494,13133,7082,7805,9064,8236,10182,16210,7451,8384,7143,8507,9833,17364,6260,7897,8933,6554,8333,7224,9659,9977,9289,9929,10576,15463)
> 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. 1.2.291 ()
> #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/1wzum1432631448.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/2pbrx1432631448.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/38gjd1432631448.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 -0.506300309  0.037726635  0.019276466 -0.033018818
 [6]  0.012119761  0.072191508 -0.089729859  0.060075998  0.015535222
[11] -0.043142451 -0.274037938  0.489246391 -0.257729017  0.070971786
[16] -0.033128151  0.013315918  0.014270584 -0.042750138  0.017898890
[21]  0.022473642  0.004409589 -0.013067494 -0.225618979  0.407988534
[26] -0.227903112  0.049853422 -0.034461244  0.004624694  0.060480176
[31] -0.062877990  0.011787929  0.034261526 -0.007528721 -0.046644767
[36] -0.174160021  0.341339427 -0.182393376  0.033533413 -0.019866553
[41] -0.032805336  0.075643924 -0.034405104 -0.037783561  0.084087392
[46] -0.027037404 -0.003941378 -0.165277594  0.264392642
> (mypacf <- c(rpacf$acf))
 [1] -0.506300309 -0.293969514 -0.154320200 -0.124760935 -0.087499090
 [6]  0.052273065 -0.014074132  0.027911041  0.078238062  0.033286263
[11] -0.440401722  0.139404457  0.086750955  0.079987104  0.003198534
[16]  0.099263203  0.091256008 -0.123721728 -0.002275335 -0.007176412
[21] -0.061693672 -0.057833558 -0.136887567  0.186747395  0.087001279
[26]  0.032900961 -0.007289240 -0.046161146 -0.003371318 -0.050388411
[31]  0.001182187  0.021037754 -0.007389941 -0.057502279 -0.127085792
[36]  0.032853877  0.021917754 -0.051058674  0.001092378 -0.031309671
[41] -0.025824274  0.037007057 -0.036339633  0.010207750 -0.058162140
[46]  0.049171938  0.010260940  0.006323832
> 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/4c1ce1432631448.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/54wfu1432631448.tab") 
> 
> try(system("convert tmp/1wzum1432631448.ps tmp/1wzum1432631448.png",intern=TRUE))
character(0)
> try(system("convert tmp/2pbrx1432631448.ps tmp/2pbrx1432631448.png",intern=TRUE))
character(0)
> try(system("convert tmp/38gjd1432631448.ps tmp/38gjd1432631448.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  1.192   0.219   1.416