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 = '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/fisher/rcomp/tmp/15bd91353097407.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/25b891353097407.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/3ozn21353097407.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]  1.00000000  0.94239867  0.88385596  0.82527537  0.78929484  0.76079943
 [7]  0.72686614  0.69256264  0.65781962  0.62099744  0.58690102  0.54956982
[13]  0.51989246  0.48726366  0.45148930  0.41392309  0.37534565  0.34152538
[19]  0.30338623  0.26196694  0.21850052  0.17118597  0.13453630  0.09640845
[25]  0.05816828  0.01455635 -0.02333197 -0.05714037 -0.08169898 -0.10568776
[31] -0.13308548 -0.16248651 -0.19193156 -0.21494184 -0.23322779 -0.24920110
[37] -0.26617532 -0.28574615 -0.30693080 -0.32659199 -0.34125486 -0.35153428
[43] -0.36258127 -0.37622008 -0.39210201 -0.40846706 -0.41428228 -0.41567085
[49] -0.41310000
> (mypacf <- c(rpacf$acf))
 [1]  0.942398673 -0.038068612 -0.031350471  0.170396767  0.043608699
 [6] -0.070776581  0.014872788  0.002358066 -0.056291883  0.002797651
[11] -0.042749037  0.035791897 -0.042961721 -0.057975694 -0.020868138
[16] -0.032511789 -0.004949206 -0.070329844 -0.059426801 -0.042509390
[21] -0.078466699  0.038589354 -0.048470932 -0.056307653 -0.063983029
[26]  0.025277092 -0.017840641  0.042332749 -0.011616498 -0.052516309
[31] -0.016778360 -0.029057935  0.029113010  0.002604425 -0.007692077
[36] -0.025885167 -0.026682984 -0.029662297 -0.019964773  0.005549804
[41] -0.007939809 -0.037066734 -0.038190610 -0.033723735 -0.049126984
[46]  0.037364791  0.008072894 -0.006969795
> 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/40hrz1353097407.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/534zq1353097407.tab") 
> 
> try(system("convert tmp/15bd91353097407.ps tmp/15bd91353097407.png",intern=TRUE))
character(0)
> try(system("convert tmp/25b891353097407.ps tmp/25b891353097407.png",intern=TRUE))
character(0)
> try(system("convert tmp/3ozn21353097407.ps tmp/3ozn21353097407.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  1.796   0.438   2.227