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(104.93,105.68,106.93,107.29,107.25,106.74,106.44,106.6,107.26,107.35,107.22,106.99,106.87,107.68,108.9,109.48,109.57,109.03,109.58,109.76,110.15,110.2,109.86,109.58,109.52,110.35,111.61,112.06,111.9,111.36,112.09,112.24,112.7,113.36,112.9,112.74,112.7,113.66,114.87,114.97,115,114.57,115.54,115.39,115.46,115.13,114.56,114.62,114.37,114.86,115.82,116.35,115.95,115.64,116.58,116.5,116.48,116.34,115.65,115.42)
> 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/1r86b1445589657.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/2e5121445589657.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/3zqf71445589657.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  0.94665434  0.89058624  0.84448369  0.80801033  0.77359833
 [7]  0.72665023  0.67449993  0.61672333  0.56813425  0.53005767  0.49642950
[13]  0.45564892  0.39464877  0.33562120  0.28640915  0.24644595  0.20740678
[19]  0.15436288  0.10538778  0.05352361  0.01096445 -0.02467381 -0.05761645
[25] -0.09505607 -0.14588219 -0.19277153 -0.22758421 -0.25085596 -0.27425193
[31] -0.30727800 -0.33288626 -0.36033576 -0.37988581 -0.38676424 -0.39221036
[37] -0.39951850 -0.41448176 -0.42327497 -0.42111771 -0.41645095 -0.41137493
[43] -0.41234175 -0.40228252 -0.39516552 -0.38299802 -0.36801531 -0.35233651
[49] -0.33378328
> (mypacf <- c(rpacf$acf))
 [1]  9.466543e-01 -5.361993e-02  6.721741e-02  6.302436e-02  3.168142e-03
 [6] -1.270629e-01 -6.129756e-02 -1.004507e-01  3.285106e-02  4.793593e-02
[11]  2.986357e-02 -6.397298e-02 -1.912420e-01 -3.013322e-02  1.427460e-03
[16]  9.304249e-03 -1.342244e-02 -1.138741e-01  3.699375e-02 -8.338211e-02
[21]  6.744709e-04 -1.699645e-02  5.530722e-03 -4.525102e-02 -1.125603e-01
[26] -4.249122e-02  1.520577e-02  2.654498e-02 -1.270490e-02 -5.884844e-02
[31]  4.792103e-02 -7.826756e-02 -1.720244e-02  5.338358e-02  1.499847e-05
[36] -9.293845e-03 -2.922305e-02 -9.831141e-03  1.927682e-02 -5.480735e-02
[41]  1.041896e-02 -2.132123e-02  8.843683e-02 -6.603069e-02 -1.560403e-03
[46] -2.944049e-02  1.271733e-02  1.855559e-02
> 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/4nru31445589657.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/5gyuc1445589657.tab") 
> 
> try(system("convert tmp/1r86b1445589657.ps tmp/1r86b1445589657.png",intern=TRUE))
character(0)
> try(system("convert tmp/2e5121445589657.ps tmp/2e5121445589657.png",intern=TRUE))
character(0)
> try(system("convert tmp/3zqf71445589657.ps tmp/3zqf71445589657.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  1.179   0.246   1.423