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(679,687,638,628,604,713,712,693,697,555,486,470,465,426,384,379,381,380,351,346,339,336,333,324,324,321,304,343,407,389,361,353,361,387,692,704,742,721,843,847,945,946,946,945,1082,1075,820,832,851,1090,1203,1239,1535,1527,1480,1452,1383,1381,1429,1376,1602,1597,2003,1958,1997,1986,2129,2115,2297,2250,2309,2648,2627,2711,2732,2825,2932,2910,2969,2999,2965,2846,2847,2751)
> 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/1xke11384522697.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/22kjl1384522697.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/3o0yb1384522697.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  0.972745492  0.942704929  0.908907029  0.871735002
 [6]  0.832060243  0.792859418  0.754425274  0.715491779  0.676853106
[11]  0.636746761  0.593931756  0.550002487  0.506299209  0.467910000
[16]  0.429654609  0.389925521  0.353306541  0.315978320  0.279600929
[21]  0.242131118  0.206180413  0.169278685  0.140251399  0.110984617
[26]  0.084940166  0.059893912  0.033517478  0.006472876 -0.023996600
[31] -0.054755900 -0.086859471 -0.118509376 -0.143272733 -0.167674913
[36] -0.187487404 -0.202336850 -0.216681392 -0.233160128 -0.254664384
[41] -0.276351867 -0.293563664 -0.310245865 -0.326789068 -0.342692632
[46] -0.356015291 -0.369214887 -0.381489267 -0.393850216
> (mypacf <- c(rpacf$acf))
 [1]  9.727455e-01 -6.563346e-02 -8.306699e-02 -7.468515e-02 -5.768436e-02
 [6] -1.979707e-03 -6.627737e-06 -2.982174e-02 -1.867442e-02 -5.361608e-02
[11] -7.512163e-02 -4.094783e-02 -1.443183e-02  8.197085e-02 -2.598089e-02
[16] -7.043575e-02  1.816301e-02 -5.002267e-02 -7.664174e-03 -4.470633e-02
[21] -2.079827e-03 -4.468314e-02  1.158545e-01 -5.510228e-02  1.831890e-02
[26] -2.383558e-02 -6.109948e-02 -4.317428e-02 -9.868811e-02 -1.819718e-02
[31] -4.672811e-02 -2.390831e-02  9.304852e-02 -4.197198e-02  3.904015e-02
[36]  7.096124e-02 -4.312277e-02 -8.437743e-02 -1.152402e-01 -5.438438e-02
[41]  9.340900e-02 -3.573819e-02 -3.572390e-02 -4.995324e-02  1.134293e-02
[46] -1.667980e-02 -1.432257e-02 -2.743243e-02
> 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/41k791384522697.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/5vv8s1384522697.tab") 
> 
> try(system("convert tmp/1xke11384522697.ps tmp/1xke11384522697.png",intern=TRUE))
character(0)
> try(system("convert tmp/22kjl1384522697.ps tmp/22kjl1384522697.png",intern=TRUE))
character(0)
> try(system("convert tmp/3o0yb1384522697.ps tmp/3o0yb1384522697.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  1.835   0.385   2.197