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(99.2,99.1,99.1,99.1,99.1,99.1,99.9,100,100,101.3,102,102,102.4,103,103,103.6,103.6,103.6,103.6,103.6,103.9,104,104,104,104.9,105.1,105.2,105.5,105.7,105.7,105.7,105.7,105.7,105.8,105.8,105.8,106.6,107,107.2,107.3,107.3,107.3,107.4,107.4,107.4,107.4,107.5,107.5,105,105.2,105.2,105.3,105.3,105.3,105.3,105.3,105.3,105.3,106.1,106.1)
> 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/1jzk81452267681.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/2tdzj1452267681.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/3psf21452267681.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  0.94579178  0.88648380  0.82844178  0.76364176  0.69401095
 [7]  0.62253004  0.55869961  0.49390474  0.42815912  0.37653589  0.33887231
[13]  0.30123614  0.25824326  0.22082121  0.18050926  0.14386665  0.10516839
[19]  0.06495407  0.02128454 -0.02377257 -0.06442543 -0.10438450 -0.14593499
[25] -0.18599170 -0.20681600 -0.22640861 -0.24655454 -0.26567435 -0.28196935
[31] -0.29962621 -0.31990405 -0.34190350 -0.36379845 -0.38026989 -0.39855202
[37] -0.41189885 -0.40878669 -0.40107842 -0.38697362 -0.36323291 -0.33901427
[43] -0.31430740 -0.28352434 -0.25438581 -0.22527297 -0.19487021 -0.16396724
[49] -0.13100347
> (mypacf <- c(rpacf$acf))
 [1]  0.945791778 -0.076208204 -0.017216372 -0.097398520 -0.077361530
 [6] -0.057713384  0.033460154 -0.052049518 -0.045342166  0.084560947
[11]  0.083245662 -0.037978918 -0.091282079 -0.004275177 -0.084387533
[16]  0.019811065 -0.049402130 -0.054040287 -0.074653641 -0.017744255
[21]  0.007305843 -0.044463945 -0.065985913 -0.041060913  0.142759818
[26] -0.034601314 -0.038449205 -0.079429599 -0.028631990 -0.055771026
[31] -0.028175786 -0.084760753 -0.065504224  0.055665570 -0.014189535
[36]  0.009395346  0.082339499  0.010917344  0.014439139  0.081643132
[41] -0.059538362 -0.046209646  0.043487447 -0.020564391  0.006599802
[46]  0.038561849  0.024859249  0.027267432
> 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/4ff6l1452267681.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/5vx3g1452267681.tab") 
> 
> try(system("convert tmp/1jzk81452267681.ps tmp/1jzk81452267681.png",intern=TRUE))
character(0)
> try(system("convert tmp/2tdzj1452267681.ps tmp/2tdzj1452267681.png",intern=TRUE))
character(0)
> try(system("convert tmp/3psf21452267681.ps tmp/3psf21452267681.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  1.369   0.282   1.645