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(11236,10954,9580,10337,8961,10372,12782,15119,19940,13957,10849,9429,11816,11329,11334,9898,8961,10783,13149,16244,20067,13601,10573,8623,10962,11911,11677,9679,9116,11394,13240,18983,21545,14360,11839,9726,12347,12624,11918,10028,10228,11026,13878,22165,23533,13445,12164,9606,12177,13142,11210,9485,10082,10680,13579,21709,22205,14687,11222,8196,12794,12627,11080,10425,10865,10771,14771,20993,23882,14825,11648,10091)
> 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/1byeo1415864478.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/2y5ew1415864478.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/3q2sf1415864478.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  0.595551087  0.014371999 -0.354448544 -0.353018319
 [6] -0.176521069 -0.078848172 -0.155813013 -0.298288371 -0.295932414
[11]  0.012514201  0.515995378  0.814449059  0.472376853 -0.005831684
[16] -0.325980387 -0.324068498 -0.157300716 -0.080414195 -0.135012343
[21] -0.240203610 -0.235089036  0.019186158  0.422516757  0.633974410
[26]  0.353930635 -0.010242281 -0.267980110 -0.254269497 -0.135699191
[31] -0.083909222 -0.115054402 -0.185637234 -0.183012231  0.020820519
[36]  0.316713664  0.435086365  0.226494840 -0.024886734 -0.205726657
[41] -0.193009960 -0.116669061 -0.082668569 -0.089182673 -0.129270091
[46] -0.118581081  0.013718756  0.195955610  0.265426269
> (mypacf <- c(rpacf$acf))
 [1]  0.595551087 -0.527350271 -0.114750935  0.048645305 -0.096282867
 [6] -0.193880357 -0.248451632 -0.262691682 -0.154204241  0.178404911
[11]  0.442934836  0.421988354 -0.387225656  0.291650927  0.022813198
[16] -0.059113885  0.061767127 -0.064093989  0.064446892  0.015245402
[21] -0.028671660 -0.008642956 -0.093875814  0.015282282 -0.052767982
[26]  0.078853361 -0.010328553  0.018361014 -0.074483463  0.070308306
[31]  0.006640311 -0.020317022 -0.021455488  0.002090582 -0.109648078
[36] -0.129755105  0.064787423 -0.067578911 -0.066817364 -0.055174996
[41]  0.009864663 -0.024828207 -0.033487310  0.037405644 -0.013573559
[46] -0.143184575 -0.012818801  0.048228648
> 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/4qt8s1415864478.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/5yv5q1415864478.tab") 
> 
> try(system("convert tmp/1byeo1415864478.ps tmp/1byeo1415864478.png",intern=TRUE))
character(0)
> try(system("convert tmp/2y5ew1415864478.ps tmp/2y5ew1415864478.png",intern=TRUE))
character(0)
> try(system("convert tmp/3q2sf1415864478.ps tmp/3q2sf1415864478.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  1.142   0.215   1.366