R version 2.15.3 (2013-03-01) -- "Security Blanket"
Copyright (C) 2013 The R Foundation for Statistical Computing
ISBN 3-900051-07-0
Platform: i686-pc-linux-gnu (32-bit)

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> x <- c(0.67,0.66,0.66,0.67,0.67,0.67,0.67,0.68,0.68,0.67,0.67,0.67,0.67,0.67,0.69,0.69,0.69,0.69,0.69,0.69,0.7,0.69,0.68,0.7,0.7,0.71,0.69,0.7,0.7,0.71,0.71,0.71,0.71,0.7,0.7,0.71,0.71,0.71,0.71,0.7,0.69,0.7,0.7,0.7,0.71,0.7,0.7,0.69,0.7,0.71,0.71,0.71,0.71,0.71,0.71,0.71,0.71,0.69,0.7,0.7,0.7,0.72,0.7,0.69,0.7,0.71,0.72,0.72,0.73,0.72,0.74,0.75)
> 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/1g4x01369132091.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/2jn8f1369132091.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/3w0kk1369132091.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  0.799423980  0.658200589  0.585140937  0.518811996
 [6]  0.488767702  0.432290073  0.372447089  0.317009661  0.337506884
[11]  0.318354103  0.244254251  0.225101471  0.170704243  0.133929239
[16]  0.171008485  0.157546214  0.157300611  0.108593893  0.064292732
[21]  0.046424905  0.031922434 -0.016784284 -0.064450801 -0.064696404
[26] -0.068307362 -0.069593166 -0.090826348 -0.114139931 -0.083546642
[31] -0.071615778 -0.068496026 -0.046713850 -0.030377430 -0.031663233
[36] -0.024137925 -0.008841706 -0.033195490 -0.021264626 -0.026955985
[41] -0.045864012 -0.046109615 -0.091450978 -0.127981229 -0.137037944
[46] -0.120701524 -0.106690258 -0.143220509 -0.199698138
> (mypacf <- c(rpacf$acf))
 [1]  0.799423980  0.052980770  0.123595394  0.021336814  0.101997786
 [6] -0.047299347 -0.015987624 -0.033957203  0.186446458 -0.058890684
[11] -0.117337542  0.069535383 -0.094507278 -0.015730483  0.162273334
[16] -0.048996694  0.079396242 -0.163967673 -0.048487002  0.030746391
[21] -0.024864141 -0.141108764  0.060237725 -0.004176093 -0.010149129
[26] -0.003423569 -0.088069356  0.064822087  0.120838996 -0.093559449
[31]  0.077231891  0.040212718 -0.011757599 -0.029165488  0.024278772
[36]  0.002290768 -0.024521800  0.007297673 -0.031059084  0.022558796
[41] -0.092494225 -0.147870492  0.040521075 -0.009889159  0.030398199
[46]  0.017551715 -0.147791724 -0.139487983
> 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/41srm1369132092.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/5dw7t1369132092.tab") 
> 
> try(system("convert tmp/1g4x01369132091.ps tmp/1g4x01369132091.png",intern=TRUE))
character(0)
> try(system("convert tmp/2jn8f1369132091.ps tmp/2jn8f1369132091.png",intern=TRUE))
character(0)
> try(system("convert tmp/3w0kk1369132091.ps tmp/3w0kk1369132091.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  2.646   0.518   3.450