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(0.75,0.75,0.77,0.78,0.79,1.01,1.16,1.14,1.12,1.1,1.1,1.1,1.1,1.09,1.09,1.1,1.1,1.17,1.15,1.04,0.94,0.88,0.85,0.85,0.85,0.84,0.83,0.8,0.78,1.02,1.19,1.1,0.96,0.87,0.83,0.82,0.81,0.78,0.79,0.8,0.79,0.97,1.01,0.92,0.87,0.84,0.81,0.81,0.83,0.83,0.85,0.88,0.89,1.21,1.32,1.33,1.23,1.16,1.12,1.06,1.08,1.09,1.03,1.04,1.05,1.19,1.14,1.05,0.95,0.87,0.86,0.85)
> 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/175xv1352716421.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/2wg0o1352716421.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/3fe4p1352716421.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  0.843155214  0.580994629  0.347246712  0.177340248
 [6]  0.060858492 -0.005428783 -0.039324875 -0.072687535 -0.070391739
[11] -0.022124467  0.055822375  0.075676977 -0.056985553 -0.212192999
[16] -0.316576218 -0.356651232 -0.337974625 -0.283454343 -0.225770513
[21] -0.194187813 -0.140401000 -0.043117244  0.086609557  0.148827561
[26]  0.051060382 -0.102902389 -0.224903686 -0.296228931 -0.324323949
[31] -0.291244675 -0.230330617 -0.187456936 -0.132173551 -0.052248565
[36]  0.040145397  0.090294499  0.057524542  0.009329505 -0.013164475
[41] -0.003341360  0.032834784  0.106017781  0.171577144  0.203819226
[46]  0.237105946  0.276141878  0.312436562  0.307782923
> (mypacf <- c(rpacf$acf))
 [1]  0.843155214 -0.449397791  0.069977865 -0.026823337 -0.037568718
 [6]  0.026176103 -0.029710470 -0.085502152  0.143817937  0.058844152
[11]  0.072035640 -0.215667442 -0.460695405  0.213808223 -0.055426455
[16] -0.029727785  0.062649126 -0.137598285  0.036865711 -0.002679197
[21]  0.011502389  0.131120375  0.041248064 -0.170019639 -0.276530763
[26] -0.082601737  0.018958852 -0.115128974 -0.159973444  0.076318724
[31] -0.010706717 -0.020680534 -0.049141631 -0.140021333 -0.002888505
[36]  0.118456254  0.038569441  0.026548435 -0.069508856 -0.023191836
[41] -0.008704316 -0.036301251  0.009270712  0.090026861 -0.011181362
[46] -0.060097880 -0.042159871  0.004177893
> 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/4c4jn1352716421.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/5zdqq1352716421.tab") 
> 
> try(system("convert tmp/175xv1352716421.ps tmp/175xv1352716421.png",intern=TRUE))
character(0)
> try(system("convert tmp/2wg0o1352716421.ps tmp/2wg0o1352716421.png",intern=TRUE))
character(0)
> try(system("convert tmp/3fe4p1352716421.ps tmp/3fe4p1352716421.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  2.040   0.325   2.345