R version 3.0.2 (2013-09-25) -- "Frisbee Sailing"
Copyright (C) 2013 The R Foundation for Statistical Computing
Platform: i686-pc-linux-gnu (32-bit)

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> x <- c(500,500.01,500.02,500.03,500.04,500.05,500.06,500.07,500.08,500.09,500.10,500.11,500.12,500.13,500.14,500.15,500.16,500.17,500.18,500.19,500.20,500.21,500.22,500.23,500.24,500.25,500.26,500.27,500.28,500.29,500.30,500.31,500.32,500.33,500.34,500.35,500.36,500.37,500.38,500.39,500.40,500.41,500.42,500.43,500.44,500.45,500.46,500.47,500.48,500.49,500.50,500.51,500.52,500.53,500.54,500.55,500.56,500.57,500.58,500.59,500.60,500.61,500.62,500.63,500.64,500.65,500.66,500.67,500.68,500.69,500.70,500.71)
> 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/1frij1387650188.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/2dyv81387650188.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/37f4z1387650188.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  0.95833333  0.91669882  0.87512863  0.83365490  0.79230979
 [7]  0.75112547  0.71013409  0.66936781  0.62885877  0.58863914  0.54874108
[13]  0.50919673  0.47003827  0.43129783  0.39300759  0.35519969  0.31790630
[19]  0.28115956  0.24499164  0.20943469  0.17452087  0.14028233  0.10675124
[25]  0.07395974  0.04194000  0.01072416 -0.01965560 -0.04916715 -0.07777831
[31] -0.10545694 -0.13217088 -0.15788797 -0.18257605 -0.20620297 -0.22873657
[37] -0.25014470 -0.27039520 -0.28945591 -0.30729468 -0.32387935 -0.33917776
[43] -0.35315776 -0.36578719 -0.37703389 -0.38686571 -0.39525050 -0.40215609
[49] -0.40755032
> (mypacf <- c(rpacf$acf))
 [1]  0.95833333 -0.02088251 -0.02093333 -0.02098540 -0.02103833 -0.02109171
 [7] -0.02114507 -0.02119796 -0.02124988 -0.02130030 -0.02134866 -0.02139436
[13] -0.02143678 -0.02147522 -0.02150896 -0.02153723 -0.02155918 -0.02157394
[19] -0.02158054 -0.02157796 -0.02156510 -0.02154078 -0.02150374 -0.02145262
[25] -0.02138597 -0.02130224 -0.02119977 -0.02107678 -0.02093136 -0.02076150
[31] -0.02056503 -0.02033967 -0.02008296 -0.01979233 -0.01946504 -0.01909820
[37] -0.01868877 -0.01823356 -0.01772923 -0.01717229 -0.01655911 -0.01588594
[43] -0.01514891 -0.01434405 -0.01346730 -0.01251453 -0.01148158 -0.01036424
> 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/4gmx31387650188.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/5ywp41387650188.tab") 
> 
> try(system("convert tmp/1frij1387650188.ps tmp/1frij1387650188.png",intern=TRUE))
character(0)
> try(system("convert tmp/2dyv81387650188.ps tmp/2dyv81387650188.png",intern=TRUE))
character(0)
> try(system("convert tmp/37f4z1387650188.ps tmp/37f4z1387650188.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  2.569   0.541   3.085