R version 3.3.3 (2017-03-06) -- "Another Canoe"
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Platform: x86_64-pc-linux-gnu (64-bit)

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> x <- c(45570,45118,41921,40167,37315,39206,57075,58664,51705,45527,41057,40867,41484,39738,37254,35177,32846,34079,51287,52800,48443,42223,38796,38952,42343,42023,39340,37149,35431,36537,49626,58677,56009,50069,46470,45603,46729,46989,44666,42920,40125,40941,57748,61246,59809,52682,48394,47436,49750,48172,44960,41831,38672,39704,56207,59254,57374,51309,47083,45092,46353,45348,42867,39980,36790,37504,53331,55997,54764,48590,45565,44959)
> 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. 1.2.327 (Mon, 30 Nov 2015 06:58:35 +0000)
> #Author: root
> #To cite this work: Wessa P., (2015), (Partial) Autocorrelation Function (v1.0.12) 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)
> x <- na.omit(x)
> 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/16lcg1489937312.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/2ybtj1489937312.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/3gb181489937312.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  0.314233558 -0.259870321 -0.454863229 -0.292282379
 [6]  0.045511560  0.272094285  0.067246850 -0.227893716 -0.387187072
[11] -0.239875755  0.249918435  0.789679573  0.298829774 -0.185008433
[16] -0.380505176 -0.257705279  0.027559992  0.220053552  0.070837255
[21] -0.176407605 -0.322925735 -0.216959273  0.174802348  0.615385890
[26]  0.264168378 -0.112282665 -0.294742881 -0.207183515  0.004169781
[31]  0.156486450  0.057486122 -0.124982656 -0.234226246 -0.183478682
[36]  0.136260974  0.473999535  0.182355755 -0.074538582 -0.212526024
[41] -0.161810496 -0.002553284  0.124407446  0.051861717 -0.077383350
[46] -0.158886562 -0.142003584  0.058484617  0.328814823
> (mypacf <- c(rpacf$acf))
 [1]  0.314233558 -0.397903087 -0.284321409 -0.180050716 -0.033673383
 [6]  0.032823622 -0.226436822 -0.254781680 -0.391895484 -0.457729097
[11] -0.247266114  0.471568680 -0.237317394  0.051684240  0.091699779
[16]  0.091536742  0.016932243 -0.012476085  0.068127911  0.008039510
[21]  0.009676706 -0.007780682 -0.066344210 -0.029257616 -0.107683671
[26] -0.023765358 -0.056383817 -0.023715275 -0.078729673 -0.081443193
[31] -0.062471344 -0.049823823  0.011572790 -0.057839594  0.073690125
[36]  0.013349750 -0.111095455  0.031444295 -0.017224696 -0.065272933
[41] -0.052550050  0.012864848 -0.009456302 -0.008104519  0.043037326
[46]  0.058365620 -0.125511335 -0.022886010
> 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/49otf1489937312.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/5njqm1489937312.tab") 
> 
> try(system("convert tmp/16lcg1489937312.ps tmp/16lcg1489937312.png",intern=TRUE))
character(0)
> try(system("convert tmp/2ybtj1489937312.ps tmp/2ybtj1489937312.png",intern=TRUE))
character(0)
> try(system("convert tmp/3gb181489937312.ps tmp/3gb181489937312.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  1.275   0.095   1.389