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(4.8,4.81,5.16,5.26,5.29,5.29,5.29,5.3,5.3,5.3,5.3,5.3,5.3,5.3,5.3,5.35,5.44,5.47,5.47,5.48,5.48,5.48,5.48,5.48,5.48,5.48,5.5,5.55,5.57,5.58,5.58,5.58,5.59,5.59,5.59,5.55,5.61,5.61,5.61,5.63,5.69,5.7,5.7,5.7,5.7,5.7,5.7,5.7,5.7,5.7,5.7,5.71,5.74,5.77,5.79,5.79,5.8,5.8,5.8,5.8,5.8,5.81,5.81,5.83,5.94,5.98,5.99,6,6.02,6.02,6.02,6.02,6.02,6.02,6.02,6.04,6.06,6.06,6.07,6.14,6.19,6.2,6.22,6.22)
> 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/1b32k1425297884.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/2idpb1425297884.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/3toac1425297884.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  0.252241017  0.013912011 -0.046265875 -0.030762538
 [6] -0.067048635 -0.092229990 -0.084225371 -0.076401808 -0.059185988
[11] -0.036598853  0.020426557  0.066807409  0.153261890  0.182110530
[16]  0.055394728 -0.014175414 -0.033012281 -0.075099699 -0.091613020
[21] -0.040336123 -0.043157118 -0.055634409 -0.002546957  0.107701242
[26]  0.131540677  0.021647955 -0.004257623 -0.007885824 -0.063122401
[31] -0.054046537 -0.077085402 -0.070876251 -0.117972872  0.065534930
[36] -0.040140707  0.007658414  0.082216036  0.116700030  0.003676555
[41] -0.030550034 -0.058235992 -0.061321026 -0.050185655 -0.066880031
[46] -0.067196424 -0.056506148 -0.037675916  0.028281568
> (mypacf <- c(rpacf$acf))
 [1]  0.252241017 -0.053091494 -0.039164758 -0.008684053 -0.062473872
 [6] -0.066976277 -0.050791884 -0.054899111 -0.041151275 -0.027816503
[11]  0.019860747  0.040791230  0.118561237  0.115707039 -0.020060536
[16] -0.013625073 -0.010866561 -0.054175606 -0.037702714  0.022135923
[21] -0.019388381 -0.028670237  0.027987855  0.099546870  0.062390719
[26] -0.061811783 -0.036146554 -0.031361774 -0.067653731 -0.005785902
[31] -0.039982965 -0.015871594 -0.083313450  0.133533305 -0.098739926
[36]  0.020980302  0.040358626  0.014163344 -0.082016179 -0.008586256
[41] -0.049499128 -0.022569430  0.012086477 -0.025496643 -0.036716083
[46] -0.003876899 -0.025025076 -0.006337935
> 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/4k72z1425297884.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/5rbvx1425297884.tab") 
> 
> try(system("convert tmp/1b32k1425297884.ps tmp/1b32k1425297884.png",intern=TRUE))
character(0)
> try(system("convert tmp/2idpb1425297884.ps tmp/2idpb1425297884.png",intern=TRUE))
character(0)
> try(system("convert tmp/3toac1425297884.ps tmp/3toac1425297884.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  1.316   0.255   1.577