R version 3.0.2 (2013-09-25) -- "Frisbee Sailing"
Copyright (C) 2013 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu (64-bit)

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> x <- c(1.8,1.8,1.81,1.81,1.81,1.81,1.81,1.81,1.82,1.82,1.81,1.8,1.8,1.81,1.81,1.81,1.81,1.81,1.81,1.82,1.82,1.82,1.83,1.83,1.83,1.84,1.85,1.86,1.86,1.87,1.87,1.86,1.88,1.89,1.91,1.91,1.91,1.91,1.92,1.93,1.93,1.94,1.94,1.95,1.95,1.96,1.97,1.97,1.97,1.97,1.98,1.98,1.99,1.99,1.99,2,2,2.01,2.01,2.02,2.01,2.01,2.03,2.03,2.04,2.05,2.05,2.06,2.06,2.06,2.04,2.04,2.04,2.03,2.03,2.03,2.03,2.03,2.03,2.03,2.03,2.03,2.02,2.03,2.03,2.02,2.03,2.04,2.05,2.05,2.05,2.05,2.07,2.07,2.08,2.08)
> 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/1b0v41413731802.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/2n72r1413731802.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/3ju3m1413731802.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  0.97440889  0.94801847  0.92368341  0.89832067  0.87504895
 [7]  0.84995027  0.82370972  0.79552802  0.77054352  0.74586233  0.72030333
[13]  0.69074783  0.65947954  0.63060915  0.59926593  0.56803690  0.53589437
[19]  0.50318092  0.47023910  0.43779327  0.40466233  0.37027534  0.33764039
[25]  0.30298935  0.26742482  0.23212791  0.19443668  0.15804073  0.12107386
[31]  0.08684745  0.05079406  0.01420543 -0.01800489 -0.04983340 -0.07503914
[37] -0.10092999 -0.12838019 -0.15529871 -0.18080775 -0.20334796 -0.22657329
[43] -0.24625885 -0.26697209 -0.28639003 -0.30424863 -0.32069774 -0.33417802
[49] -0.34777248
> (mypacf <- c(rpacf$acf))
 [1]  0.974408888 -0.028780582  0.027404946 -0.034332611  0.030459634
 [6] -0.051931970 -0.030934617 -0.057293680  0.051455201 -0.016436946
[11] -0.024605513 -0.099659797 -0.040958473  0.021020554 -0.069577577
[16] -0.022634418 -0.038042812 -0.019126700 -0.030370247 -0.018099370
[21] -0.045857130 -0.035775438  0.009833396 -0.062520675 -0.049657502
[26] -0.024266231 -0.069885395 -0.008478999 -0.047075245  0.023747316
[31] -0.071095666 -0.034726886  0.047283597 -0.023864733  0.103342734
[36] -0.038057773 -0.048098893 -0.011201155  0.003722077  0.013762341
[41] -0.039850034  0.047304048 -0.027418025 -0.008859376 -0.010402170
[46] -0.009504990  0.025648111 -0.003437507
> 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/4ya0e1413731802.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/51dvt1413731802.tab") 
> 
> try(system("convert tmp/1b0v41413731802.ps tmp/1b0v41413731802.png",intern=TRUE))
character(0)
> try(system("convert tmp/2n72r1413731802.ps tmp/2n72r1413731802.png",intern=TRUE))
character(0)
> try(system("convert tmp/3ju3m1413731802.ps tmp/3ju3m1413731802.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  1.179   0.188   1.380