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)

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> x <- c(99.1,98.9,98.8,98.8,99.2,99.6,100.5,100.6,100.7,101,101.3,101.5,102.3,103,102.9,103.5,103.8,103.6,103.4,103.4,103.3,103.2,103.2,103.5,104.5,105.7,106.5,107,106.7,107.1,106.1,106.2,106.5,106.8,107,107.2,107.8,107.9,107.9,108.2,108.9,109.1,109.3,109.8,109.8,109.9,109.9,109.9,108.8,108.5,108.8,108.8,108.8,108.9,108.8,108.4,107.7,107.3,107,107.7)
> par8 = ''
> par7 = '0.95'
> par6 = 'White Noise'
> par5 = '12'
> par4 = '0'
> par3 = '1'
> par2 = '1'
> par1 = '48'
> par8 <- ''
> par7 <- '0.95'
> par6 <- 'White Noise'
> par5 <- '12'
> par4 <- '0'
> par3 <- '1'
> 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/1ztf81452539234.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/2zdqn1452539234.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/3pykw1452539234.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  0.376438488  0.184497713  0.029299894 -0.086897458
 [6] -0.247762411 -0.139796600  0.083224482  0.023823019  0.120501271
[11]  0.100863159  0.028679507 -0.003009049 -0.002936745  0.048887077
[16] -0.095256718  0.040920210 -0.002943342  0.114519589  0.110652924
[21]  0.075399056 -0.017569276 -0.227118644 -0.184215887 -0.218021834
[26] -0.044152239  0.062817153  0.166190095  0.133006911 -0.065254897
[31]  0.003383497 -0.124148122 -0.155494159 -0.114584240  0.075056801
[36]  0.031224387 -0.031057350  0.040321197  0.008975161 -0.035308755
[41] -0.037493964 -0.065243550 -0.173749792 -0.134023121 -0.073169251
[46] -0.074934095  0.009039812  0.052285088 -0.014309275
> (mypacf <- c(rpacf$acf))
 [1]  0.376438488  0.049856780 -0.064774648 -0.101529710 -0.208489661
 [6]  0.041068070  0.217485811 -0.076580053  0.072453721 -0.026901544
[11] -0.051901915  0.081349247  0.012123382  0.069896068 -0.136633490
[16]  0.074052527 -0.020028866  0.167242243  0.061874327 -0.074498069
[21] -0.106146501 -0.234046687  0.003916355  0.016298436  0.105396809
[26]  0.042945145 -0.028394965 -0.085583306 -0.168105863  0.138160747
[31]  0.036229243 -0.111542480 -0.027095552  0.060829657  0.001407941
[36] -0.001523559 -0.053119219  0.023148741 -0.062383844  0.052887828
[41] -0.066337560 -0.096708526  0.009767505 -0.145742377 -0.009903680
[46] -0.038378218  0.038330757 -0.079817568
> 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/4qgzi1452539234.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/5vyp81452539234.tab") 
> 
> try(system("convert tmp/1ztf81452539234.ps tmp/1ztf81452539234.png",intern=TRUE))
character(0)
> try(system("convert tmp/2zdqn1452539234.ps tmp/2zdqn1452539234.png",intern=TRUE))
character(0)
> try(system("convert tmp/3pykw1452539234.ps tmp/3pykw1452539234.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  1.155   0.269   1.420