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(87.16,87.16,87.16,87.16,87.16,87.16,87.16,87.16,87.16,89.24,89.24,89.24,89.24,89.24,89.24,89.24,89.24,89.24,89.24,89.24,89.24,91,91,91,91,91,91,91,91,91,91,91,91,92.51,92.51,92.51,92.51,92.51,92.51,92.51,92.51,92.51,92.51,92.51,92.51,96.67,96.67,96.67,96.67,96.67,96.67,96.67,96.67,96.67,96.67,96.67,96.67,96.19,96.19,96.19,96.19,96.19,96.19,96.19,96.19,96.19,96.19,96.19,96.19,99.13,99.13,99.13,99.13,99.13,99.13,99.13,99.13,99.13,99.13,99.13,99.13,99.58,99.58,99.58,99.58,99.58,99.58,99.58,99.58,99.58,99.58,99.58,99.58,101.27,101.27,101.27,101.25,101.25,101.25,101.25,101.25,101.25,101.25,101.25,101.25,102.55,102.55,102.55)
> 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/1qfyi1445540129.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/2tgg41445540129.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/3d19i1445540129.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  0.966282527  0.932565055  0.898847582  0.869203449
 [6]  0.839559315  0.809915182  0.780271048  0.750626915  0.720982781
[11]  0.698409218  0.675835655  0.653262091  0.624921630  0.596581168
[16]  0.568240707  0.545180792  0.522120877  0.499060962  0.476001047
[21]  0.452941132  0.429881217  0.412794777  0.395708337  0.378621898
[26]  0.349973871  0.321325845  0.292677819  0.265459737  0.238241656
[31]  0.211023574  0.183805493  0.156587411  0.129369330  0.107276219
[36]  0.085183107  0.063089996  0.033743710  0.004397423 -0.024948863
[41] -0.045119567 -0.065290270 -0.085460974 -0.105631678 -0.125802382
[46] -0.145973086 -0.152024667 -0.158076248 -0.164127829
> (mypacf <- c(rpacf$acf))
 [1]  0.966282527 -0.017147827 -0.017447005  0.043719753 -0.015985351
 [6] -0.016245033 -0.012790819 -0.016665992 -0.016948455  0.090035126
[11] -0.014148626 -0.014351682 -0.089475218 -0.017172297 -0.017472337
[16]  0.055205102 -0.015644139 -0.015892767  0.001908852 -0.015832209
[21] -0.016086900  0.061552525 -0.014221351 -0.014426516 -0.162979354
[26] -0.020044595 -0.020454599 -0.020965052 -0.021330628 -0.021795541
[31] -0.005182397 -0.022022624 -0.022518542  0.017494112 -0.021744204
[36] -0.022227524 -0.097050041 -0.027005601 -0.027755145  0.093035441
[41] -0.023030299 -0.023573197 -0.003499836 -0.023738781 -0.024316013
[46]  0.162256392 -0.017526756 -0.017839424
> 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/4arho1445540129.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/5bbq61445540129.tab") 
> 
> try(system("convert tmp/1qfyi1445540129.ps tmp/1qfyi1445540129.png",intern=TRUE))
character(0)
> try(system("convert tmp/2tgg41445540129.ps tmp/2tgg41445540129.png",intern=TRUE))
character(0)
> try(system("convert tmp/3d19i1445540129.ps tmp/3d19i1445540129.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  1.299   0.255   1.559