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(100.71,100.75,100.75,100.70,100.77,100.44,100.17,100.21,100.27,100.29,100.33,100.35,100.94,101.07,101.01,100.86,100.71,99.95,100.02,100.03,100.04,99.73,99.76,99.83,100.08,99.35,99.43,99.53,99.03,99.05,99.07,99.23,99.03,99.06,99.13,99.14,100.91,100.97,100.55,100.68,100.31,100.31,99.28,99.24,99.29,99.27,99.26,99.25,99.57,98.97,99.00,98.88,98.90,98.92,98.80,98.83,98.88,98.88,98.89,98.89,99.05,99.20,99.13,98.92,98.98,98.99,99.08,99.10,99.10,99.06,99.05,99.11,99.75,99.80,99.95,99.69,99.55,99.14,99.05,99.00,99.03,99.16,99.01,99.00,99.90,100.18,100.20,100.13,99.85,99.88,99.88,99.89,99.96,100.05,100.04,100.06,99.72,99.70,99.63,99.73,99.77,99.76,99.61,99.61,99.59,99.42,99.52,99.46)
> 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/1b6yd1445718068.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/2trwm1445718068.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/3rwl11445718068.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  0.876635036  0.749122565  0.624969931  0.506181700
 [6]  0.403177406  0.319669237  0.301987294  0.284826411  0.277958010
[11]  0.270693979  0.258150983  0.255416313  0.195579504  0.149611424
[16]  0.091974280  0.052726071  0.033374284  0.012824150  0.011782670
[21]  0.034226233  0.062848304  0.086574578  0.115879956  0.137737235
[26]  0.107788752  0.070114173  0.024988954 -0.018250997 -0.059401951
[31] -0.097606593 -0.093927029 -0.066994733 -0.035811730 -0.008895707
[36]  0.014547335  0.030545060 -0.034780421 -0.117886411 -0.198513380
[41] -0.270652975 -0.326973723 -0.363657889 -0.348984204 -0.321031994
[46] -0.282311797 -0.251604322 -0.213815052 -0.171972759
> (mypacf <- c(rpacf$acf))
 [1]  0.876635036 -0.083652264 -0.058026133 -0.053449277 -0.010448570
 [6]  0.009041346  0.220115004 -0.032685887  0.028882041 -0.011490419
[11] -0.009171509  0.061890846 -0.199431468  0.040728615 -0.077087713
[16]  0.054832213  0.041332104 -0.024778645 -0.029996247  0.131272054
[21] -0.006069910  0.038335993  0.071870290 -0.043077847 -0.136622519
[26] -0.017202976 -0.018038862 -0.032879313 -0.030817325 -0.053194442
[31]  0.096287542  0.050451244  0.018680620 -0.024200910 -0.008095922
[36]  0.002547362 -0.271927133 -0.094581015 -0.013717501 -0.066023081
[41] -0.037292804  0.034032383  0.017663986 -0.018524772  0.026784920
[46] -0.041950590  0.079923492  0.035909193
> 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/4oo1o1445718068.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/5tc2s1445718068.tab") 
> 
> try(system("convert tmp/1b6yd1445718068.ps tmp/1b6yd1445718068.png",intern=TRUE))
character(0)
> try(system("convert tmp/2trwm1445718068.ps tmp/2trwm1445718068.png",intern=TRUE))
character(0)
> try(system("convert tmp/3rwl11445718068.ps tmp/3rwl11445718068.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  1.188   0.215   1.409