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 = '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/fisher/rcomp/tmp/1y3sf1384523152.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/fisher/rcomp/tmp/2brr31384523152.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/fisher/rcomp/tmp/35kds1384523152.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 -0.021077289  0.194031211 -0.036426857  0.041028563
 [6]  0.018212240 -0.022153966 -0.086986298  0.107075556  0.120413999
[11]  0.129708206  0.158011941 -0.134478089  0.120291547  0.004197229
[16] -0.044490455  0.031027100 -0.036833776  0.108196482 -0.002650659
[21] -0.114648305 -0.077107540  0.080255217 -0.052332115  0.116763992
[26] -0.229718149  0.128956366  0.022203032  0.128499242 -0.095662492
[31] -0.058261835 -0.114281115 -0.034652149  0.005980056  0.013896600
[36]  0.032183905 -0.009096396  0.143632737 -0.035362828 -0.032478017
[41] -0.061166174 -0.073256722 -0.042423757 -0.080943453  0.043914899
[46] -0.033651840 -0.045572353 -0.056826861 -0.074913129
> (mypacf <- c(rpacf$acf))
 [1] -0.021077289  0.193672999 -0.030192568  0.002608305  0.032867812
 [6] -0.032400683 -0.099929599  0.123205414  0.164922457  0.089912577
[11]  0.133893794 -0.177241557  0.045838952  0.068059692 -0.079659889
[16]  0.057775395  0.003303342  0.059707661 -0.081751108 -0.177274150
[21] -0.090423857  0.133755310  0.015172402  0.049647454 -0.196592370
[26]  0.070767612  0.040368828  0.133405944 -0.066382512 -0.039005500
[31] -0.078455085 -0.149668259  0.088953632  0.168096618  0.046750824
[36] -0.049939191 -0.024498673 -0.032707991 -0.038939612  0.002348295
[41] -0.011653937 -0.006098913 -0.037956603 -0.035234841 -0.099775945
[46] -0.137338242  0.054022078 -0.025493774
> lengthx <- length(x)
> sqrtn <- sqrt(lengthx)
> 
> #Note: the /var/fisher/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/fisher/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/fisher/rcomp/tmp/4yodo1384523152.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/fisher/rcomp/tmp/59jyh1384523152.tab") 
> 
> try(system("convert tmp/1y3sf1384523152.ps tmp/1y3sf1384523152.png",intern=TRUE))
character(0)
> try(system("convert tmp/2brr31384523152.ps tmp/2brr31384523152.png",intern=TRUE))
character(0)
> try(system("convert tmp/35kds1384523152.ps tmp/35kds1384523152.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  1.735   0.370   2.092