R version 2.15.2 (2012-10-26) -- "Trick or Treat"
Copyright (C) 2012 The R Foundation for Statistical Computing
ISBN 3-900051-07-0
Platform: i686-pc-linux-gnu (32-bit)

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> x <- c(46.56,46.72,47.01,47.26,47.49,47.51,47.52,47.66,47.71,47.87,48,48,48.05,48.25,48.72,48.94,49.16,49.18,49.25,49.34,49.49,49.57,49.63,49.67,49.7,49.8,50.09,50.49,50.73,51.12,51.15,51.41,51.61,52.06,52.17,52.18,52.19,52.74,53.05,53.38,53.78,53.82,53.88,53.96,54.14,54.2,54.35,54.36,54.39,54.77,54.91,55.06,55.38,55.41,55.47,55.58,55.67,55.97,56.03,56.06,56.08,56.43,56.65,56.96,57.37,57.51,57.61,57.7,57.91,58.12,58.18,58.16)
> 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/1fc0g1356537518.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/2191j1356537518.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/3ovgd1356537518.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  0.217586204 -0.001720281 -0.172153277 -0.106222243
 [6] -0.013437656  0.098536535 -0.064457381 -0.238190989 -0.207951539
[11] -0.139030170  0.215586024  0.396846038  0.174234616 -0.142778847
[16] -0.088768071 -0.262583843  0.003419625 -0.010745128 -0.044662740
[21] -0.140000058 -0.293912697 -0.185466149  0.181152466  0.374437605
[26]  0.140001063  0.018641560 -0.174128135 -0.099959086 -0.034180488
[31]  0.116965361 -0.022949137 -0.133147317 -0.141864384 -0.063243347
[36]  0.257760229  0.225041562  0.124718190 -0.023328376 -0.094833828
[41] -0.097339950 -0.030467275  0.001626270 -0.017643457 -0.141280847
[46] -0.075681712 -0.053733252  0.094854704  0.138998239
> (mypacf <- c(rpacf$acf))
 [1]  0.217586204 -0.051502352 -0.168980667 -0.034222513  0.015412250
 [6]  0.074970603 -0.135401502 -0.224237278 -0.098583783 -0.104624296
[11]  0.211492169  0.290857435  0.018009809 -0.180581472  0.028014212
[16] -0.299378039 -0.038308098 -0.109816203  0.000140902  0.088215721
[21] -0.228306854 -0.138849180  0.084397017  0.070171845 -0.024440584
[26]  0.006946085 -0.120139082  0.026082704 -0.137912108 -0.034954156
[31]  0.022114113 -0.134601864  0.232150177  0.015751568  0.028067539
[36] -0.068024023 -0.166852074 -0.012809275 -0.037455614 -0.008754876
[41] -0.003379745 -0.028658725 -0.104550103 -0.020031548  0.031769134
[46] -0.045410974 -0.067816499 -0.140231695
> 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/4yn121356537518.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/5i6by1356537518.tab") 
> 
> try(system("convert tmp/1fc0g1356537518.ps tmp/1fc0g1356537518.png",intern=TRUE))
character(0)
> try(system("convert tmp/2191j1356537518.ps tmp/2191j1356537518.png",intern=TRUE))
character(0)
> try(system("convert tmp/3ovgd1356537518.ps tmp/3ovgd1356537518.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  1.731   0.270   2.028