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(4.00,4.00,4.00,4.00,4.00,4.00,4.00,4.00,4.06,4.07,4.07,4.07,4.07,4.07,4.30,4.44,4.52,4.52,4.52,4.53,4.53,4.53,4.53,4.53,4.53,4.53,4.53,4.61,4.63,4.63,4.63,4.63,4.63,4.63,4.63,4.63,4.63,4.63,4.66,4.70,4.72,4.73,4.73,4.74,4.74,4.74,4.76,4.88,4.88,4.88,4.88,4.89,4.97,4.97,4.97,4.97,4.97,4.97,4.97,4.97,4.97,4.97,4.97,4.98,5.00,5.03,5.04,5.04,5.05,5.05,5.05,5.06)
> 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/1s4741368888885.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/289aa1368888885.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/3a22o1368888885.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  0.362828155  0.039871442 -0.143771324 -0.120454744
 [6] -0.015447030  0.019896653 -0.038986090 -0.043281030 -0.108671396
[11] -0.148991180 -0.038972173  0.039976817  0.127946135 -0.042328477
[16] -0.109808058 -0.075014912 -0.078251127 -0.055428619  0.010985080
[21]  0.017714986 -0.083248503 -0.070448581 -0.022569607  0.083440366
[26]  0.123216572 -0.009325121 -0.032662974 -0.046938151 -0.049680295
[31] -0.039887149  0.069623671  0.150563062  0.215452199 -0.074952283
[36] -0.062152361  0.009780819  0.076702706  0.154127134  0.003530670
[41] -0.073886799 -0.068610875 -0.077860642 -0.063564390 -0.021713085
[46] -0.067100627 -0.065339666 -0.043604115 -0.024790641
> (mypacf <- c(rpacf$acf))
 [1]  0.362828155 -0.105685751 -0.141408024 -0.013865095  0.040601512
 [6] -0.014643366 -0.076908589 -0.001252236 -0.096706753 -0.110119061
[11]  0.046818625  0.020280283  0.070169933 -0.162916741 -0.036276512
[16]  0.015696074 -0.105403869 -0.060994342  0.026325725 -0.010435140
[21] -0.161274243  0.008580794  0.039328926  0.006555816  0.012154931
[26] -0.112173358  0.041776557 -0.050085735 -0.074681026 -0.022936301
[31]  0.090159061  0.071092334  0.116261316 -0.186723202  0.071747276
[36]  0.050337723  0.012116245  0.093477799 -0.069347167 -0.011193015
[41]  0.019471173 -0.004799580 -0.032909629 -0.080696902 -0.056697103
[46] -0.027560168  0.078503993 -0.059779823
> 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/4vog41368888885.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/50jrs1368888885.tab") 
> 
> try(system("convert tmp/1s4741368888885.ps tmp/1s4741368888885.png",intern=TRUE))
character(0)
> try(system("convert tmp/289aa1368888885.ps tmp/289aa1368888885.png",intern=TRUE))
character(0)
> try(system("convert tmp/3a22o1368888885.ps tmp/3a22o1368888885.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  2.106   0.493   2.571