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(98.41,98.94,99.09,100.45,101.99,102.35,102.69,102.6,102.62,102.73,102.74,103.45,103.9,103.45,103.5,103.33,103.56,103.58,103.86,103.77,103.73,104.21,104.55,104.5,104.66,104.99,104.99,105.62,106.52,106.1,106.73,106.63,106.72,106.5,107.12,106.84,107.25,108.19,108.21,107.98,109.12,109.79,109.69,109.69,109.24,108.55,106.47,107.27,105.95,108.55,110.81,111.54,110.38,106.67,106.45,105.44,105.37,103.72,106.57,108.54,110.36,106.64,103.45,101.36,101.9,100.86,100.37,100.16,99.5,99.52,99.2,99.35,99.37,99.85,99.76,100.07,99.77,99.93,99.16,99.4,99.81,99.67,99.37,99.49,99.28,99.33,99.19,98.11,99.12,99.06,97.41,98.45,100.33,103.18,103.06,103.48,102.8,103.92,103.9,103.96,103.62,103.83,104.09,104.07,103.22,104.01,104.01,104.24)
> 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/13ysl1445720565.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/2chfb1445720565.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/3q3qq1445720565.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  0.94259937  0.86508731  0.78538376  0.74195862  0.70935380
 [7]  0.68807322  0.67425883  0.66192012  0.63294977  0.57216873  0.50004377
[13]  0.43593772  0.39218514  0.34753257  0.30815404  0.26315711  0.22060760
[19]  0.16952118  0.12078410  0.06834058  0.01583070 -0.03441274 -0.08999436
[25] -0.14497386 -0.20404148 -0.25700201 -0.30772757 -0.34447466 -0.37788269
[31] -0.40955257 -0.43179846 -0.43910752 -0.43955432 -0.45410139 -0.47196596
[37] -0.48882648 -0.49418856 -0.49895811 -0.50182860 -0.50604539 -0.48551612
[43] -0.45752401 -0.43132886 -0.41371533 -0.39618514 -0.37724757 -0.37019314
[49] -0.36225495
> (mypacf <- c(rpacf$acf))
 [1]  0.942599370 -0.209909516 -0.031456870  0.297234854 -0.043357242
 [6]  0.051700016  0.140060487 -0.022220948 -0.140682233 -0.219086694
[11] -0.029135204  0.010552446 -0.012071367 -0.149958857  0.024129039
[16] -0.081019513 -0.058282435 -0.029402027  0.059129730 -0.076213094
[21] -0.128887095 -0.011652481 -0.114888983 -0.065679481 -0.087980951
[26] -0.041034513 -0.049108390  0.003710662 -0.032558378 -0.039971330
[31]  0.155202610  0.115917016  0.030559686 -0.114275477  0.060691170
[36]  0.028935723 -0.034939250 -0.027241165 -0.015395669 -0.081129682
[41]  0.123425685  0.033439017  0.008097039  0.070627710  0.001328423
[46] -0.033550606 -0.124838475  0.014921458
> 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/4un131445720565.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/5u5tc1445720565.tab") 
> 
> try(system("convert tmp/13ysl1445720565.ps tmp/13ysl1445720565.png",intern=TRUE))
character(0)
> try(system("convert tmp/2chfb1445720565.ps tmp/2chfb1445720565.png",intern=TRUE))
character(0)
> try(system("convert tmp/3q3qq1445720565.ps tmp/3q3qq1445720565.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  1.162   0.192   1.365