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(65,65.3,62.9,63.5,62.1,59.3,61.6,61.5,60.1,59.5,62.7,65.5,63.8,63.8,62.7,62.3,62.4,64.8,66.4,65.1,67.4,68.8,68.6,71.5,75,84.3,84,79.1,78.8,82.7,85.3,84.5,80.8,70.1,68.2,68.1,72.3,73.1,71.5,74.1,80.3,80.6,81.4,87.4,89.3,93.2,92.8,96.8,100.3,95.6,89,87.4,86.7,92.8,98.6,100.8,105.5,107.8,113.7,120.3,126.5,134.8,134.5,133.1,128.8,127.1,129.1,128.4,126.5,117.1,114.2,109.1)
> 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/1qgz31363625320.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/2mu5o1363625320.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/3kwsa1363625320.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  0.442701848  0.117461035 -0.044028447  0.003036451
 [6]  0.142336540  0.044031524 -0.036314577 -0.221532016 -0.341133259
[11] -0.366844119 -0.160015849 -0.110342915 -0.023397577  0.090537266
[16]  0.010453687 -0.016294229  0.096548275  0.221978663  0.243572332
[21]  0.014786684 -0.125530028 -0.027992146 -0.028728177 -0.111315526
[26] -0.131444104 -0.236486471 -0.213522617 -0.132897716 -0.004027473
[31]  0.098640976  0.099895415  0.021075466  0.005439266  0.015943705
[36]  0.071585327  0.270302053  0.200869738  0.081582004 -0.107398538
[41] -0.105520377 -0.014914337  0.026925470  0.008655886 -0.070142724
[46] -0.065736588 -0.109838459 -0.025677744 -0.002572532
> (mypacf <- c(rpacf$acf))
 [1]  0.442701848 -0.097664700 -0.072670551  0.080306842  0.147187064
 [6] -0.121929267 -0.028746165 -0.200024349 -0.217746306 -0.212202446
[11]  0.084241890 -0.139691879  0.100017170  0.218326986 -0.047140348
[16] -0.078250592  0.194683596 -0.008440940 -0.090741884 -0.216375316
[21] -0.107285472  0.029717717 -0.040289319 -0.149682498  0.041007831
[26] -0.097117020  0.009847879  0.010132127  0.103893977  0.019456933
[31]  0.084376829 -0.155251408 -0.141061249 -0.094337006 -0.017778369
[36]  0.025026637  0.015812245  0.130154125  0.017771849  0.092502723
[41] -0.001307489 -0.020927623 -0.039444455 -0.120271148 -0.020129822
[46] -0.033953645 -0.038179341 -0.033730929
> 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/49kxj1363625320.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/522aq1363625320.tab") 
> 
> try(system("convert tmp/1qgz31363625320.ps tmp/1qgz31363625320.png",intern=TRUE))
character(0)
> try(system("convert tmp/2mu5o1363625320.ps tmp/2mu5o1363625320.png",intern=TRUE))
character(0)
> try(system("convert tmp/3kwsa1363625320.ps tmp/3kwsa1363625320.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  1.840   0.301   2.121