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(82303,79596,74472,73562,66618,69029,89899,93774,90305,83799,80320,82497,84420,84646,84186,83269,77793,81145,101691,107357,104253,95963,91432,94324,93855,92183,87600,83641,78195,79604,100846,105293,102518,93132,87479,85476,85460,82868,79941,76909,72613,72496,93244,99126,96748,89318,84724,83111,87497,86961,82319,79196,76898,77971,97335,106855,105401,99108,93456,92506,94602,93027,89722,87391,83030,83390,104501,110393,111017,103434,97817,96893)
> 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/1nhdp1413467145.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/277cm1413467145.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/3skhr1413467145.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  0.748109182  0.326176412  0.021314388 -0.078048277
 [6] -0.042076291 -0.017250209 -0.057199510 -0.129662286 -0.108924173
[11]  0.086603352  0.395240034  0.575372308  0.365161717  0.002631410
[16] -0.265125992 -0.353907336 -0.322152802 -0.287391271 -0.296213630
[21] -0.329526745 -0.285627870 -0.098911800  0.179508555  0.374326626
[26]  0.257720225  0.001384911 -0.190163330 -0.246979357 -0.207019022
[31] -0.155903606 -0.123528635 -0.118032867 -0.065594900  0.080872626
[36]  0.292173080  0.444520915  0.362584797  0.162828025  0.005511865
[41] -0.057200467 -0.045120463 -0.024211480 -0.010645437 -0.024038840
[46] -0.009997462  0.060194309  0.174157964  0.256144134
> (mypacf <- c(rpacf$acf))
 [1]  0.748109182 -0.530260329  0.140905566  0.051957869  0.007581099
 [6] -0.125603137 -0.045072563 -0.054553418  0.188852725  0.287794041
[11]  0.320918023 -0.042466812 -0.600080727  0.153050489 -0.105215786
[16] -0.149985355 -0.165055656 -0.028502475 -0.019426592 -0.007788729
[21]  0.028447935 -0.014750315 -0.003382609  0.175275826 -0.045300813
[26]  0.075067697  0.014262164 -0.002839108  0.011051758  0.045473307
[31]  0.080067331 -0.056005116  0.023587518 -0.033234201 -0.001688001
[36] -0.030731084  0.060450144 -0.010396886  0.037398984  0.013128041
[41]  0.077099421 -0.040967701  0.028191440 -0.030057267  0.005007986
[46] -0.099960299 -0.027517628 -0.063347949
> 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/4ig321413467145.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/5edmq1413467145.tab") 
> 
> try(system("convert tmp/1nhdp1413467145.ps tmp/1nhdp1413467145.png",intern=TRUE))
character(0)
> try(system("convert tmp/277cm1413467145.ps tmp/277cm1413467145.png",intern=TRUE))
character(0)
> try(system("convert tmp/3skhr1413467145.ps tmp/3skhr1413467145.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  1.238   0.226   1.473