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(87.16,87.16,87.16,87.16,87.16,87.16,87.16,87.16,87.16,89.24,89.24,89.24,89.24,89.24,89.24,89.24,89.24,89.24,89.24,89.24,89.24,91,91,91,91,91,91,91,91,91,91,91,91,92.51,92.51,92.51,92.51,92.51,92.51,92.51,92.51,92.51,92.51,92.51,92.51,96.67,96.67,96.67,96.67,96.67,96.67,96.67,96.67,96.67,96.67,96.67,96.67,96.19,96.19,96.19,96.19,96.19,96.19,96.19,96.19,96.19,96.19,96.19,96.19,99.13,99.13,99.13,99.13,99.13,99.13,99.13,99.13,99.13,99.13,99.13,99.13,99.58,99.58,99.58,99.58,99.58,99.58,99.58,99.58,99.58,99.58,99.58,99.58,101.27,101.27,101.27,101.25,101.25,101.25,101.25,101.25,101.25,101.25,101.25,101.25,102.55,102.55,102.55)
> 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/1i8fz1445540347.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/21cmc1445540347.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/37gcw1445540347.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 -0.05815485 -0.05869332 -0.05524468 -0.05490338 -0.05544185
 [7] -0.05598032 -0.05651879 -0.05705726 -0.05048547 -0.05034720 -0.05088567
[13]  0.29917265 -0.05203748 -0.05257595 -0.04702174 -0.04732595 -0.04786442
[19] -0.04840289 -0.04894136 -0.04947983 -0.04342930 -0.04396777 -0.04450624
[25]  0.66568457 -0.04558318 -0.04612165 -0.04650592 -0.04551390 -0.04605238
[31] -0.04659085 -0.04712932 -0.04766779 -0.04255319 -0.04309166 -0.04363013
[37]  0.40170824 -0.04470707 -0.04524554 -0.03452750 -0.03531585 -0.03585432
[43] -0.03639279 -0.03693126 -0.03746973 -0.02243418 -0.02297266 -0.02351113
[49]  0.26908302
> (mypacf <- c(rpacf$acf))
 [1] -5.815485e-02 -6.228596e-02 -6.294909e-02 -6.682491e-02 -7.214380e-02
 [6] -7.830374e-02 -8.551549e-02 -9.407483e-02 -9.698451e-02 -1.071976e-01
[11] -1.205716e-01  2.417393e-01 -6.929608e-02 -7.455842e-02 -7.673265e-02
[16] -8.439238e-02 -9.215418e-02 -1.015698e-01 -1.131602e-01 -1.276940e-01
[21] -1.442718e-01 -1.697158e-01 -2.044317e-01  5.484802e-01 -2.490664e-02
[26] -2.218092e-02 -3.138851e-02 -3.647963e-02 -3.601100e-02 -3.539428e-02
[31] -3.457532e-02 -3.351283e-02 -4.204674e-02 -5.005264e-02 -5.202658e-02
[36]  2.169026e-01 -1.446524e-05  4.574989e-03  1.302870e-02  7.722784e-03
[41]  1.244467e-02  1.762395e-02  2.340559e-02  2.986432e-02  4.484303e-02
[46]  4.689908e-02  5.578837e-02 -3.635341e-01
> 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/40q7l1445540347.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/5dgab1445540347.tab") 
> 
> try(system("convert tmp/1i8fz1445540347.ps tmp/1i8fz1445540347.png",intern=TRUE))
character(0)
> try(system("convert tmp/21cmc1445540347.ps tmp/21cmc1445540347.png",intern=TRUE))
character(0)
> try(system("convert tmp/37gcw1445540347.ps tmp/37gcw1445540347.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  1.236   0.215   1.450