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(163.93,164.28,164.58,165.97,166.3,166.27,166.27,166.44,166.26,166.64,166.07,166.19,166.19,166.19,166.35,166.52,167.17,167.16,167.16,167.16,167.39,168.46,168.55,168.58,168.58,169.21,169.29,169.24,169.53,169.57,169.57,169.67,170.04,170.39,170.57,170.48,170.48,170.48,170.49,170.72,171.11,171.07,171.07,171.07,171.05,172.28,172.74,172.86,172.86,173.24,173.2,173.38,172.89,172.98,172.98,172.69,172.77,172.65,172.3,172.17,172.17,173.07,173.27,173.05,173.41,173.37,173.37,173.08,173.97,175.23,174.9,174.83)
> par8 = ''
> par7 = '0.95'
> par6 = 'White Noise'
> par5 = '12'
> par4 = '1'
> par3 = '1'
> par2 = '1'
> par1 = '48'
> par8 <- ''
> par7 <- '0.95'
> par6 <- 'White Noise'
> par5 <- '12'
> par4 <- '1'
> 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/fisher/rcomp/tmp/1oock1358192294.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/fisher/rcomp/tmp/2zl6i1358192294.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/fisher/rcomp/tmp/39a4g1358192294.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]  1.000000e+00  1.641595e-01  6.851145e-02 -1.916000e-02  6.268200e-02
 [6]  1.084604e-01 -8.799058e-02 -1.286851e-01 -7.920209e-03 -6.781766e-02
[11] -1.836269e-01 -1.721554e-01 -4.495265e-01 -3.184039e-02  1.202160e-02
[16]  9.185161e-02 -6.693327e-02 -1.361377e-01  1.427940e-02  8.037669e-02
[21]  1.197139e-01  2.388739e-02  1.364998e-01  1.044704e-01  2.005745e-01
[26]  4.698995e-02 -1.413764e-03 -7.256079e-02 -2.836712e-05  1.172191e-01
[31] -3.293431e-02 -1.244823e-01 -1.719955e-01 -5.522893e-02 -8.557474e-02
[36] -9.759736e-02 -1.932212e-01  1.213271e-02 -4.145879e-02  8.904196e-02
[41]  4.670856e-02 -9.056606e-02  1.082453e-01  1.334619e-01  1.604552e-01
[46]  1.603919e-02 -2.581952e-03  7.491309e-02  1.401006e-01
> (mypacf <- c(rpacf$acf))
 [1]  0.164159505  0.042714185 -0.038030728  0.070763303  0.094263054
 [6] -0.134051016 -0.107583165  0.051921020 -0.084808306 -0.189621814
[11] -0.074270870 -0.427640711  0.055130047  0.076355470  0.089776537
[16] -0.096966270 -0.116659000 -0.079902682 -0.034150411  0.145165147
[21] -0.054358611 -0.001686791 -0.045926461 -0.004262017  0.107614867
[26]  0.044003635 -0.069283383 -0.144350942  0.066577854 -0.022984441
[31] -0.026020527 -0.003297438 -0.111801450 -0.071306565 -0.026177040
[36] -0.057855337  0.057346081 -0.125490155  0.046165286  0.010243333
[41] -0.050506334  0.074130178  0.030811831 -0.040922146 -0.121904980
[46] -0.001405877  0.013936538  0.010907445
> lengthx <- length(x)
> sqrtn <- sqrt(lengthx)
> 
> #Note: the /var/fisher/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/fisher/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/fisher/rcomp/tmp/4qj661358192294.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/fisher/rcomp/tmp/57gn01358192294.tab") 
> 
> try(system("convert tmp/1oock1358192294.ps tmp/1oock1358192294.png",intern=TRUE))
character(0)
> try(system("convert tmp/2zl6i1358192294.ps tmp/2zl6i1358192294.png",intern=TRUE))
character(0)
> try(system("convert tmp/39a4g1358192294.ps tmp/39a4g1358192294.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  1.673   0.534   2.190