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(169701,164182,161914,159612,151001,158114,186530,187069,174330,169362,166827,178037,186412,189226,191563,188906,186005,195309,223532,226899,214126,206903,204442,220376,214320,212588,205816,202196,195722,198563,229139,229527,211868,203555,195770,199834,203089,198480,192684,187827,182414,182510,211524,211451,200140,191568,186424,191987,203583,201920,195978,191395,188222,189422,214419,224325,216222,210506,207221,210027,215191,215177,211701,210176,205491,206996,235980,241292,236675,229127,225436,229570,239973,236168,230703,224790,217811,219576,245472,248511,242084,235572,229827,229697)
> 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/1uc0c1445589331.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/2ewkn1445589331.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/31syi1445589331.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  0.871575640  0.689510083  0.583891577  0.557558870
 [6]  0.563468232  0.538928574  0.472142614  0.362995322  0.274165093
[11]  0.254670682  0.308862862  0.336556423  0.212211952  0.047490088
[16] -0.047093096 -0.070924338 -0.057883382 -0.062673997 -0.085209455
[21] -0.138140658 -0.171230709 -0.145085483 -0.049372211  0.042686502
[26] -0.002888303 -0.096705231 -0.144424720 -0.133686197 -0.091616992
[31] -0.053489489 -0.030746785 -0.040653489 -0.045499015 -0.011194467
[36]  0.073786845  0.154421673  0.137258890  0.074215807  0.037092439
[41]  0.037725692  0.058366329  0.069067949  0.081071834  0.061066749
[46]  0.041339030  0.044913563  0.087124782  0.129025658
> (mypacf <- c(rpacf$acf))
 [1]  0.871575640 -0.291792348  0.281479498  0.131286071  0.101163531
 [6] -0.059303949 -0.045076755 -0.192656826  0.040293382  0.091192894
[11]  0.219778031 -0.124708058 -0.479560788  0.040827329  0.029290705
[16] -0.064984659  0.024629265 -0.031346974  0.139282765  0.005630078
[21]  0.101257753  0.020411896  0.133449189  0.085466612 -0.244567199
[26]  0.029827305 -0.074681637 -0.031487904 -0.026843221  0.049074257
[31]  0.023205888  0.054866034  0.064367646  0.001608426  0.003094071
[36] -0.010747711  0.076136792 -0.011177971 -0.034160269 -0.025754705
[41] -0.042248270 -0.041786256  0.063648032 -0.076991842  0.044358484
[46] -0.031466123  0.016697381 -0.057866510
> 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/4jz591445589331.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/5pafq1445589331.tab") 
> 
> try(system("convert tmp/1uc0c1445589331.ps tmp/1uc0c1445589331.png",intern=TRUE))
character(0)
> try(system("convert tmp/2ewkn1445589331.ps tmp/2ewkn1445589331.png",intern=TRUE))
character(0)
> try(system("convert tmp/31syi1445589331.ps tmp/31syi1445589331.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  1.132   0.172   1.316