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(79.21,79.08,79.88,80.57,80.9,80.89,80.61,80.98,81.68,83.28,83.94,89.25,95.3,97.68,98.53,98.32,97.02,90.13,88.49,88.07,87.17,86.1,86.59,85.89,85.82,86.68,86.3,86.32,85.61,85.52,85.97,86.6,86.78,84.98,85.21,86.39,88.39,88.83,95.76,100.98,102.56,102.92,104.35,105.07,105.41,105.06,104.33,104.61,104.78,104.38,104.08,103.4,101.72,100.1,100.37,96.27,95.28,95.85,96.76,97,96.71,96.97,96.97,98.01,99.18,99.51,99.16,99.4,97.59,96.71,96.56,96.42)
> 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/1yb3s1445624456.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/2hzbr1445624456.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/3z0kv1445624456.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  0.951425299  0.872866792  0.781183131  0.680402763
 [6]  0.575619232  0.481295385  0.395885039  0.315788477  0.244759369
[11]  0.181826242  0.124048599  0.084741245  0.067162952  0.059838558
[16]  0.062005584  0.070858506  0.078347043  0.072202843  0.066663674
[21]  0.062745586  0.058524616  0.065226263  0.081645346  0.095505712
[26]  0.105521938  0.111317310  0.102625808  0.076745657  0.038593938
[31] -0.005736238 -0.048242486 -0.090927454 -0.134802364 -0.181039191
[36] -0.223848511 -0.268526338 -0.311360877 -0.353184546 -0.379216374
[41] -0.391620337 -0.395292792 -0.391111732 -0.377556915 -0.355135167
[46] -0.325026019 -0.295075844 -0.265804114 -0.233617464
> (mypacf <- c(rpacf$acf))
 [1]  0.951425299 -0.341210483 -0.095665429 -0.104123981 -0.061646417
 [6]  0.080789109 -0.022803963 -0.052950279  0.004729919 -0.028846766
[11] -0.031778266  0.145526119  0.100951184 -0.034703222  0.023598309
[16] -0.021792776 -0.045840222 -0.125195032  0.086813339  0.028095796
[21]  0.011868109  0.130158284  0.025883844 -0.051990455 -0.006984537
[26] -0.036713903 -0.113928844 -0.091662972 -0.116096343 -0.040322147
[31]  0.087067082 -0.067147340 -0.041858847 -0.020850720  0.013967438
[36] -0.123425849 -0.017858317 -0.104158298  0.033944814 -0.011177522
[41] -0.043240090 -0.003021884  0.050502458  0.087966920  0.052922144
[46] -0.053902334 -0.040942899 -0.031359973
> 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/4rwo31445624456.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/55wd41445624456.tab") 
> 
> try(system("convert tmp/1yb3s1445624456.ps tmp/1yb3s1445624456.png",intern=TRUE))
character(0)
> try(system("convert tmp/2hzbr1445624456.ps tmp/2hzbr1445624456.png",intern=TRUE))
character(0)
> try(system("convert tmp/3z0kv1445624456.ps tmp/3z0kv1445624456.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  1.155   0.229   1.390