R version 3.0.2 (2013-09-25) -- "Frisbee Sailing"
Copyright (C) 2013 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu (64-bit)

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> x <- c(2240,2240,2380,2380,2380,2380,2140,2400,2180,2260,2280,2480,2360,2160,2380,2280,2320,2400,1960,2520,2200,2420,2300,2280,2220,2240,2200,2340,2240,2500,1820,2520,2180,2480,2260,2400,2240,2240,2240,2140,2200,2460,1860,2480,1960,2540,2280,2320,2320,2440,2320,2180,2120,2460,2140,2480,2100,2700,2200,2260,2340,2720,2300,2360,2020,2380,2000,2540,1980,2940,2260,2300,2300,2820,2380,2360,1980,2340,2160,2700,1920,2980,2240,2180,2440,2740,2360,2380,2000,2500,2180,2740,1960,3060,2300,2240,2580,2740,2260,2400,1820,2440,2080,2680,1900,3000,2240,2300)
> 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/12egl1409417655.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/2iuqd1409417655.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/3r2pe1409417655.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 -0.48586785  0.36915732 -0.34715096  0.32973693 -0.27895616
 [7]  0.22803224 -0.28285057  0.34352128 -0.27913050  0.30379338 -0.43184561
[13]  0.79924255 -0.43294521  0.32268127 -0.30760038  0.27306210 -0.20808661
[19]  0.18144146 -0.27923402  0.29423741 -0.23919080  0.26601166 -0.35656089
[25]  0.61928832 -0.37953527  0.29423255 -0.29607366  0.21524830 -0.16836690
[31]  0.11803093 -0.26285569  0.23778612 -0.20856637  0.23834118 -0.29464824
[37]  0.43554458 -0.32791246  0.27102218 -0.27195784  0.15459829 -0.11489428
[43]  0.07045493 -0.19570822  0.15695146 -0.16872010  0.18613357 -0.23344286
[49]  0.25158441
> (mypacf <- c(rpacf$acf))
 [1] -0.485867850  0.174216650 -0.154426502  0.115229949 -0.041831653
 [6]  0.005836621 -0.125226445  0.160910871 -0.012299756  0.094654580
[11] -0.242377078  0.707798165  0.178619217 -0.184464208  0.126786911
[16] -0.011430991  0.060699596 -0.018909185 -0.104703923 -0.090964652
[21] -0.078056277  0.055708233  0.075384392 -0.088479802 -0.062607529
[26]  0.079683207 -0.032334025 -0.066166228 -0.025705072 -0.138912520
[31] -0.077621074 -0.026442609 -0.027527440 -0.007626684 -0.023697748
[36] -0.131147825 -0.045153544  0.082801317  0.024189790 -0.099558979
[41]  0.026141304  0.047515107  0.097882578 -0.018081062 -0.008751162
[46] -0.052870440 -0.056919673 -0.098224950
> 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/4k6do1409417655.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/5fvf51409417655.tab") 
> 
> try(system("convert tmp/12egl1409417655.ps tmp/12egl1409417655.png",intern=TRUE))
character(0)
> try(system("convert tmp/2iuqd1409417655.ps tmp/2iuqd1409417655.png",intern=TRUE))
character(0)
> try(system("convert tmp/3r2pe1409417655.ps tmp/3r2pe1409417655.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  1.249   0.185   1.439