R version 3.2.2 (2015-08-14) -- "Fire Safety"
Copyright (C) 2015 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu (64-bit)

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> x <- c(92.51,92.51,92.51,92.51,92.51,92.51,92.51,92.51,92.51,96.67,96.67,96.67,96.67,96.67,96.67,96.67,96.67,96.67,96.67,96.67,96.67,96.19,96.19,96.19,96.19,96.19,96.19,96.19,96.19,96.19,96.19,96.19,96.19,99.13,99.13,99.13,99.13,99.13,99.13,99.13,99.13,99.13,99.13,99.13,99.13,99.58,99.58,99.58,99.58,99.58,99.58,99.58,99.58,99.58,99.58,99.58,99.58,101.27,101.27,101.27,101.25,101.25,101.25,101.25,101.25,101.25,101.25,101.25,101.25,102.55,102.55,102.55)
> 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. 1.2.291 ()
> #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/1mrrd1445441887.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/2h1sv1445441887.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/3sttk1445441887.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 -0.048789999 -0.049467637 -0.045061007 -0.044593227
 [6] -0.045270866 -0.045948505 -0.046626144 -0.047303783 -0.028927511
[11] -0.028724059 -0.029401698 -0.000607786 -0.030852817 -0.031530456
[16] -0.024414493 -0.024787139 -0.025464778 -0.026142417 -0.026820055
[21] -0.027497694 -0.030475526 -0.031153165 -0.031830803  0.562838193
[26] -0.033186081 -0.033863720 -0.034377550 -0.033062567 -0.033740206
[31] -0.034417845 -0.035095484 -0.035773123 -0.022362083 -0.023039722
[36] -0.023717360  0.141073953 -0.025072638 -0.025750277 -0.012013911
[41] -0.013016876 -0.013694515 -0.014372153 -0.015049792 -0.015727431
[46] -0.014248640 -0.014926278 -0.015603917  0.200819348
> (mypacf <- c(rpacf$acf))
 [1] -0.048789999 -0.051971818 -0.050391415 -0.052581185 -0.056161806
 [6] -0.060191270 -0.064745579 -0.069928715 -0.056326157 -0.059093212
[11] -0.063071968 -0.037183727 -0.067802952 -0.073177471 -0.071512690
[16] -0.076859002 -0.083301252 -0.091340046 -0.101062752 -0.112975400
[21] -0.131637746 -0.152380235 -0.180520074  0.484691807 -0.029503432
[26] -0.028353278 -0.035931067 -0.034146426 -0.033634866 -0.032757360
[31] -0.032014148 -0.031244627 -0.042119809 -0.049035257 -0.051660430
[36]  0.168930337 -0.008228673 -0.005063700  0.003145228 -0.001996127
[41]  0.001470875  0.005501855  0.010229922  0.015260476  0.016482756
[46]  0.015757661  0.020189715 -0.151721212
> 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/4j9fu1445441887.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/50arq1445441887.tab") 
> 
> try(system("convert tmp/1mrrd1445441887.ps tmp/1mrrd1445441887.png",intern=TRUE))
character(0)
> try(system("convert tmp/2h1sv1445441887.ps tmp/2h1sv1445441887.png",intern=TRUE))
character(0)
> try(system("convert tmp/3sttk1445441887.ps tmp/3sttk1445441887.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  1.239   0.202   1.448