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(1.4718,1.4748,1.5527,1.5751,1.5557,1.5553,1.577,1.4975,1.4369,1.3322,1.2732,1.3449,1.3239,1.2785,1.305,1.319,1.365,1.4016,1.4088,1.4268,1.4562,1.4816,1.4914,1.4614,1.4272,1.3686,1.3569,1.3406,1.2565,1.2209,1.277,1.2894,1.3067,1.3898,1.3661,1.322,1.336,1.3649,1.3999,1.4442,1.4349,1.4388,1.4264,1.4343,1.377,1.3706,1.3556,1.3179,1.2905,1.3224,1.3201,1.3162,1.2789,1.2526,1.2288,1.24,1.2856,1.2974,1.2828,1.3119,1.3288,1.3359,1.2964,1.3026,1.2982,1.3189,1.308,1.331,1.3348,1.3635,1.3493,1.3704,1.361,1.3658,1.3823,1.3812,1.3732,1.3592,1.3539,1.3316,1.2901,1.2673,1.2472,1.2331)
> 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/1zu1v1445715068.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/29y0i1445715068.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/3r7xe1445715068.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  0.886963200  0.724649559  0.547734173  0.352489812
 [6]  0.170747939  0.014927113 -0.136646522 -0.216413367 -0.241931735
[11] -0.224587576 -0.185233301 -0.128695066 -0.045456441  0.059964214
[16]  0.179053243  0.279054759  0.330003000  0.353306626  0.339616452
[21]  0.269174432  0.180834928  0.096732593  0.013000029 -0.040463726
[26] -0.069856545 -0.082729064 -0.080352873 -0.083034694 -0.087664343
[31] -0.072653112 -0.054574275 -0.025034509  0.024431137  0.067965161
[36]  0.102880668  0.113040507  0.114712221  0.100176796  0.063592788
[41]  0.006603329 -0.037715382 -0.079394914 -0.098529125 -0.118384234
[46] -0.127942633 -0.155046262 -0.174015519 -0.179353228
> (mypacf <- c(rpacf$acf))
 [1]  0.886963200 -0.290929399 -0.122672221 -0.193851524 -0.045908753
 [6] -0.043739336 -0.171376088  0.203322670  0.025419483  0.074724300
[11] -0.065660289  0.016594369  0.146124563  0.066440636  0.173952903
[16] -0.026295041 -0.066248272  0.031506187 -0.082667719 -0.125506546
[21]  0.018652360  0.142286782  0.032519951  0.052937591  0.004842083
[26]  0.017312365 -0.049131185 -0.154505244 -0.035799426  0.066212270
[31]  0.004841200  0.041087355  0.083107833 -0.026675371 -0.005841294
[36] -0.109807870  0.070985206 -0.018011291 -0.023767406 -0.099960107
[41]  0.015886522 -0.030662598  0.005439564 -0.055089529  0.055478473
[46] -0.137402554  0.048630840 -0.019568507
> 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/4acly1445715068.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/5tmzh1445715068.tab") 
> 
> try(system("convert tmp/1zu1v1445715068.ps tmp/1zu1v1445715068.png",intern=TRUE))
character(0)
> try(system("convert tmp/29y0i1445715068.ps tmp/29y0i1445715068.png",intern=TRUE))
character(0)
> try(system("convert tmp/3r7xe1445715068.ps tmp/3r7xe1445715068.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  1.189   0.249   1.440