R version 3.2.2 (2015-08-14) -- "Fire Safety"
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Platform: x86_64-pc-linux-gnu (64-bit)

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> x <- c(98.71,100.46,100.46,100.67,100.01,100.01,99.99,99.98,99.87,99.91,96.59,96.99,96.68,96.57,96.55,96.78,95.99,97.54,97.45,97.58,97.66,97.67,97.71,98.52,98.87,97.91,97.92,97.97,97.97,97.97,97.58,97.57,96.7,96.72,96.72,96.74,101.2,100.59,100.58,99.62,99.63,99.17,99.17,98.99,98.92,99.52,99.45,99.04,99.23,98.71,98.73,97.1,100.94,100.93,101.02,101.01,100.86,100.56,100.75,100.15,99.49,99.15,99.15,99.14,98.77,98.8,99.29,98.38,98.31,98.24,96.99,96.81)
> 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. 1.2.291 ()
> #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/101hg1445624877.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/2v9vl1445624877.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/341l51445624877.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 -0.189168817  0.065363906 -0.087121041 -0.039910765
 [6] -0.082475810  0.073681934 -0.083273982 -0.028296402 -0.055143852
[11]  0.054275569 -0.120447417  0.066134946 -0.090375647  0.052673422
[16] -0.218358188  0.335992533  0.008189335 -0.052964935  0.142905095
[21] -0.098215490  0.048149895  0.038798387 -0.019230929 -0.094866881
[26]  0.010261129 -0.209054519 -0.020114889  0.007263763  0.091698957
[31]  0.038387318 -0.026528372 -0.054741091  0.047025258 -0.122875865
[36]  0.224980302 -0.082385052  0.037573842 -0.030441371  0.034983079
[41] -0.047502934  0.097667420 -0.204926515  0.001835444 -0.011282143
[46]  0.021836934 -0.014878114  0.016381597 -0.070134919
> (mypacf <- c(rpacf$acf))
 [1] -0.189168817  0.030676830 -0.071973303 -0.073515337 -0.101364289
 [6]  0.039958152 -0.069810190 -0.083753565 -0.078998857  0.021756323
[11] -0.124242679 -0.019525768 -0.090159329 -0.009517959 -0.248265746
[16]  0.234215992  0.124126722 -0.134413492  0.150121247 -0.043622921
[21]  0.091306561  0.007281599  0.021221664 -0.068917463  0.018182565
[26] -0.293624368 -0.026394751 -0.035985619  0.065631031  0.044080003
[31]  0.012718264 -0.091466344 -0.096388809 -0.040223330  0.066824647
[36]  0.028344843 -0.085708621 -0.063395773 -0.044993685  0.021961095
[41] -0.030797205 -0.063588360  0.010400121  0.001950675 -0.035624024
[46] -0.082122876 -0.044649082 -0.020908845
> 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/44m8x1445624877.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/56q2u1445624877.tab") 
> 
> try(system("convert tmp/101hg1445624877.ps tmp/101hg1445624877.png",intern=TRUE))
character(0)
> try(system("convert tmp/2v9vl1445624877.ps tmp/2v9vl1445624877.png",intern=TRUE))
character(0)
> try(system("convert tmp/341l51445624877.ps tmp/341l51445624877.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  1.219   0.212   1.440