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(790,766,1040,2596,949,758,1023,2730,921,775,907,2603,835,871,836,2542,10471,789,811,996,2596,778,603,990,2371,735,800,706,2241,766,870,647,2283,9491,726,784,884,2394,696,893,674,2263,703,799,793,2295,799,1022,758,2579,9531,1021,944,915,2880,864,1022,891,2777,1087,822,890,2799,1092,967,833,2892,11348,1104,1063,1103,3270,1039,1185,1047,3271,1155,878,879,2912,1133,920,943,2996,12449)
> 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/1xcev1413752522.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/22nqr1413752522.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/31wrn1413752522.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  0.036914070 -0.160143700 -0.142853529  0.109044581
 [6]  0.052942118 -0.158935519 -0.160772354  0.066384274  0.096279080
[11] -0.154026401 -0.160281819  0.017484990  0.127486153 -0.137882871
[16] -0.161706324 -0.007920261  0.760618067  0.032816952 -0.120009427
[21] -0.108499020  0.076004839  0.041599085 -0.114152811 -0.125148588
[26]  0.041725172  0.067979767 -0.120285475 -0.125712643  0.004743833
[31]  0.090897925 -0.107353946 -0.127139617 -0.014546770  0.559573506
[36]  0.024902759 -0.089753672 -0.084684397  0.050332473  0.027675816
[41] -0.087996757 -0.095702695  0.024606145  0.049180405 -0.094134904
[46] -0.104822958 -0.002396113  0.063540087 -0.084485227
> (mypacf <- c(rpacf$acf))
 [1]  0.036914070 -0.161726725 -0.133690068  0.096358784  0.004002159
 [6] -0.157948881 -0.123239059  0.032973032  0.008171876 -0.175585286
[11] -0.111012330 -0.028239703 -0.003934462 -0.200801598 -0.129713574
[16] -0.072677819  0.709984202 -0.098804952  0.077234669  0.047189627
[21] -0.061029564 -0.080362077  0.093582753  0.025692738 -0.028375235
[26] -0.089823039  0.072495572  0.001157910 -0.003420390 -0.082797506
[31]  0.084246497 -0.009734317  0.019643800 -0.030025758  0.040305719
[36] -0.062174370 -0.019359774 -0.001238431  0.022275515 -0.070015521
[41]  0.005842880 -0.016987339  0.019542918 -0.047413581 -0.002921257
[46] -0.016251223 -0.003012230 -0.040412894
> 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/4f6zr1413752522.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/5qf0d1413752522.tab") 
> 
> try(system("convert tmp/1xcev1413752522.ps tmp/1xcev1413752522.png",intern=TRUE))
character(0)
> try(system("convert tmp/22nqr1413752522.ps tmp/22nqr1413752522.png",intern=TRUE))
character(0)
> try(system("convert tmp/31wrn1413752522.ps tmp/31wrn1413752522.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  1.179   0.182   1.367