R version 3.2.5 (2016-04-14) -- "Very, Very Secure Dishes"
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Platform: x86_64-pc-linux-gnu (64-bit)

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> x <- c(74787,49019,56601,47637,49806,50499,42092,39062,44382,43635,41082,17244,70170,43949,52333,41032,47758,76116,30917,32996,31951,26775,30268,18214,47957,31901,35559,30408,30083,35043,30475,28309,31394,36313,40357,38918,44368,33298,29366,28282,30943,32699,29764,25524,29807,35112,32192,36214,47639,33421,28642,26996,27757,36839,33821,30839,35032,38821,40347,68799)
> 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. 1.2.327 (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/17gam1462267617.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/2isa71462267617.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/3ic1x1462267617.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  0.243466247  0.306637953  0.193494336  0.166248428
 [6]  0.222413916 -0.123461891  0.108486354  0.101833160  0.058956798
[11]  0.131468508  0.036499779  0.395119770  0.035831514  0.079394144
[16]  0.013115267  0.006440657  0.110473142 -0.100197280 -0.041738509
[21] -0.055608821 -0.092405808 -0.050046633 -0.076738393  0.052455028
[26] -0.131658754 -0.146078151 -0.155273546 -0.118504567 -0.097354151
[31] -0.107857334 -0.052197660 -0.051751668 -0.051848901 -0.086967964
[36] -0.066003154 -0.105427109 -0.204280399 -0.230842385 -0.174981535
[41] -0.132008130 -0.109785848  0.010883220 -0.070655405 -0.047058526
[46]  0.009759562 -0.032268936  0.047471600 -0.093803801
> (mypacf <- c(rpacf$acf))
 [1]  0.243466247  0.262948634  0.085019485  0.045092208  0.134042057
 [6] -0.285092101  0.086720746  0.156501554 -0.021717601  0.087709314
[11]  0.039316650  0.300425825 -0.178473759 -0.069154925 -0.078902411
[16] -0.024644407  0.053369175  0.054910308 -0.134114914 -0.095545894
[21] -0.055380062 -0.064464800  0.083240597 -0.007402947 -0.130414842
[26] -0.147044267 -0.045682036  0.004505066 -0.037268330  0.123000871
[31]  0.084435701 -0.028184681  0.002974490 -0.084340898 -0.089942834
[36] -0.085899089 -0.029305537 -0.063183566  0.070359497 -0.016458803
[41] -0.010631998  0.150500077 -0.099619161 -0.116195944  0.081446988
[46]  0.022016985 -0.010214214 -0.012129838
> 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/46s9m1462267617.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/5kqgk1462267617.tab") 
> 
> try(system("convert tmp/17gam1462267617.ps tmp/17gam1462267617.png",intern=TRUE))
character(0)
> try(system("convert tmp/2isa71462267617.ps tmp/2isa71462267617.png",intern=TRUE))
character(0)
> try(system("convert tmp/3ic1x1462267617.ps tmp/3ic1x1462267617.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  1.252   0.189   1.439