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 = '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/1y5ke1445590675.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/2n8el1445590675.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/38spv1445590675.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  0.226364342 -0.395447399 -0.412085996 -0.215441918
 [6]  0.174953248  0.388574443  0.205600121 -0.173560291 -0.372588065
[11] -0.382739926  0.155047062  0.782451412  0.211485257 -0.338384207
[16] -0.373776978 -0.206023135  0.133700526  0.283662782  0.163226740
[21] -0.160994424 -0.317177758 -0.352944874  0.081655974  0.643048398
[26]  0.229179198 -0.258250713 -0.311918550 -0.202843742  0.055780888
[31]  0.271835959  0.161796397 -0.105763234 -0.234676542 -0.292417853
[36]  0.030083143  0.510229267  0.213931634 -0.163946689 -0.227405995
[41] -0.154677657  0.042489930  0.196059714  0.151927621 -0.064876759
[46] -0.162668851 -0.225181138  0.007220706  0.358267419
> (mypacf <- c(rpacf$acf))
 [1]  0.226364342 -0.470813059 -0.235425551 -0.323733894  0.001491118
 [6]  0.089031600  0.102455605 -0.041141925 -0.118956388 -0.397882146
[11]  0.068088555  0.586729761 -0.169808725  0.051619186  0.040792731
[16]  0.021125340 -0.042635840 -0.243888470 -0.088696952 -0.181000075
[21] -0.066960182 -0.188386606 -0.169260766  0.013998114 -0.004716206
[26]  0.026898866  0.054875192 -0.048153617 -0.099066871  0.140330177
[31] -0.144373795  0.002454493 -0.045521407  0.032620074 -0.022835508
[36] -0.129786621 -0.107017961 -0.035663862 -0.054815048  0.020229381
[41] -0.007559791 -0.160717236  0.126039573 -0.071693223  0.048005664
[46] -0.012528452 -0.040007211 -0.048967800
> 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/4txql1445590675.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/5v0tf1445590675.tab") 
> 
> try(system("convert tmp/1y5ke1445590675.ps tmp/1y5ke1445590675.png",intern=TRUE))
character(0)
> try(system("convert tmp/2n8el1445590675.ps tmp/2n8el1445590675.png",intern=TRUE))
character(0)
> try(system("convert tmp/38spv1445590675.ps tmp/38spv1445590675.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  1.105   0.225   1.333