R version 3.0.1 (2013-05-16) -- "Good Sport"
Copyright (C) 2013 The R Foundation for Statistical Computing
Platform: i686-pc-linux-gnu (32-bit)

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> x <- c(42364,42206,42046,41715,44991,44818,42364,40733,40891,40891,41067,41382,41873,41873,41558,40733,44991,45640,44660,42364,43346,41873,42538,42855,43186,42364,42538,41382,44991,46131,45151,43346,45309,43186,45151,44991,45482,43678,45640,45482,48426,47762,45151,43835,45640,43186,44991,45309,45973,44502,45309,45800,47604,46131,44169,42046,44011,38611,41224,42695,44169,42046,42046,42046,43186,41558,39420,37631,38929,33862,36967,38771,39102,37298,37455,36967,38611,37455,35178,33531,36315,30269,34195,35984,35984,33862,31900,31742,33531,31900,28798,26660,28956,23558,28464,31075,31900,30096,27816,29447,30096,29604,24696,22418,24047,19140,24207,26011,27482,25029,22733,24047,24696,23398,18491,16353,18316,12918,18807,22418)
> 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/13q9j1376761062.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/29j3j1376761062.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/3sr7z1376761062.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]  1.00000000  0.94790080  0.90526717  0.85572873  0.82620676  0.78567936
 [7]  0.75796625  0.73618776  0.72365449  0.70318323  0.69210364  0.68756922
[13]  0.70013273  0.64795753  0.60883550  0.56350873  0.53636124  0.49797067
[19]  0.47383384  0.45268822  0.44000872  0.41829279  0.40339680  0.39332587
[25]  0.39690171  0.34807529  0.31176484  0.26871574  0.24336094  0.20637918
[31]  0.18442204  0.16033880  0.14528141  0.11903191  0.10228281  0.08819116
[37]  0.08556695  0.04215319  0.01252713 -0.02312323 -0.04234859 -0.07005715
[43] -0.08184590 -0.09661957 -0.10510026 -0.12496049 -0.13603358 -0.14763488
[49] -0.15225743
> (mypacf <- c(rpacf$acf))
 [1]  0.947900796  0.066525271 -0.082630179  0.161765700 -0.095017515
 [6]  0.075222792  0.103373912  0.049093709 -0.040345918  0.088257354
[11]  0.102377910  0.170900535 -0.617574728  0.140126346  0.079095254
[16] -0.101804041  0.062935735  0.038390285 -0.041055006  0.026578134
[21] -0.026540960  0.084762761 -0.085810346 -0.059785533 -0.132100452
[26]  0.009547233  0.006423000 -0.014112639 -0.004661319  0.005739745
[31] -0.091599969  0.033570017 -0.043532903  0.058516508 -0.071719305
[36] -0.075159293  0.014577321  0.007270846 -0.021750037  0.017314103
[41]  0.014217777  0.003855367 -0.029022093 -0.021887436  0.016685332
[46] -0.028126739 -0.067391808 -0.046556089
> 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/4d4bt1376761062.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/5pxli1376761062.tab") 
> 
> try(system("convert tmp/13q9j1376761062.ps tmp/13q9j1376761062.png",intern=TRUE))
character(0)
> try(system("convert tmp/29j3j1376761062.ps tmp/29j3j1376761062.png",intern=TRUE))
character(0)
> try(system("convert tmp/3sr7z1376761062.ps tmp/3sr7z1376761062.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  2.217   0.504   2.697