R version 3.2.3 (2015-12-10) -- "Wooden Christmas-Tree"
Copyright (C) 2015 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu (64-bit)

R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.

R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.

Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.

> x <- c(98.72,98.67,98.82,99.39,99.33,99.22,99.05,98.83,98.84,98.89,98.8,99.4,98.89,98.85,98.69,98.48,98.39,98.35,98.26,98.06,98.14,98.17,98.41,98.64,99.25,99.61,100.28,100.31,100.55,100.45,100.78,100.68,101.69,98.09,99.13,99.18,96.22,96.11,96,95.96,97.95,98.43,98.32,97.45,96.42,95.36,95.1,95.54,94.07,93.48,92.86,90.98,91.45,91.16,90.71,90.31,89.78,91.02,90.77,90.69)
> 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. 1.2.327 (Mon, 30 Nov 2015 06:58:35 +0000)
> #Author: root
> #To cite this work: Wessa P., (2015), (Partial) Autocorrelation Function (v1.0.12) 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)
> x <- na.omit(x)
> 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/1k3fi1457966352.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/2avaq1457966352.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/3tvgi1457966352.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  0.928023874  0.862754279  0.796644682  0.696719832
 [6]  0.617392508  0.539346357  0.459425487  0.388504550  0.310326229
[11]  0.255089883  0.204876980  0.165689485  0.133713264  0.097542637
[16]  0.068463163  0.033735857  0.012680999 -0.005452255 -0.033463892
[21] -0.059834616 -0.108625821 -0.154534746 -0.195937188 -0.241351743
[26] -0.247603602 -0.251722262 -0.267451498 -0.243538034 -0.227987539
[31] -0.214798955 -0.203621239 -0.193310707 -0.189974532 -0.174868019
[36] -0.168104013 -0.165556951 -0.163981611 -0.166785002 -0.173674458
[41] -0.182434423 -0.194850313 -0.206919096 -0.216745723 -0.223720506
[46] -0.228611827 -0.226119614 -0.222125254 -0.218215378
> (mypacf <- c(rpacf$acf))
 [1]  0.928023874  0.010996245 -0.039007261 -0.281304262  0.073385094
 [6] -0.025774777 -0.007766442 -0.050214689 -0.096543065  0.117220035
[11] -0.008110302  0.074233703 -0.073912399 -0.046558423 -0.013571309
[16] -0.062864122  0.100152605 -0.052155114 -0.057210207 -0.098354418
[21] -0.173458668  0.016836993 -0.030666852  0.010861077  0.180853093
[26]  0.018501097 -0.111008443  0.160076460 -0.006449577 -0.045175254
[31] -0.193891039  0.007969560 -0.072452986  0.213244170 -0.087168974
[36] -0.052982905 -0.073923768 -0.026246208  0.048016426 -0.079762247
[41]  0.018093548 -0.085101133  0.007528421  0.017827074 -0.064261792
[46]  0.018267719 -0.094725929 -0.050972393
> 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/4c3v51457966352.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/5rzm71457966352.tab") 
> 
> try(system("convert tmp/1k3fi1457966352.ps tmp/1k3fi1457966352.png",intern=TRUE))
character(0)
> try(system("convert tmp/2avaq1457966352.ps tmp/2avaq1457966352.png",intern=TRUE))
character(0)
> try(system("convert tmp/3tvgi1457966352.ps tmp/3tvgi1457966352.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  1.352   0.258   1.617