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(18293.9,18613.4,18728.5,20091.8,18947.2,20124.9,19819.2,15908.6,19927.4,19551.9,15588.6,14206.2,13566.7,13941.5,14964.1,14086,13505.1,15300.4,14725.2,12484.9,16082.6,15915.8,15916.1,15713,14746,15253.2,18384.3,16848.5,16485.5,19257.1,17093.4,15700.1,19124.3,18640.8,18439.2,17106.3,18347.7,19372.7,22263.8,19422.9,21268.6,20310,19256,17535.9,19857.4,19628.4,19727.5,18112.2,19080.2,20684.6,22537.7,19954.6,20230.2,20445.5,19615.3,18071.6,19287.2,21031.4,19860.9,17671.3,19359.2,19287,21498,20859.7,20833.1,20318.8,21375.9,17403.4,21050.1,22010.2,20372.1,19028.4)
> 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/1ugvm1413376716.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/2pka41413376716.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/3jn7f1413376716.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  0.720717646  0.610073370  0.632205616  0.603716629
 [6]  0.519001827  0.510993534  0.388170780  0.399842324  0.310960842
[11]  0.188469051  0.250793412  0.361655575  0.165700944  0.082354741
[16]  0.061179696  0.066211314  0.030188217  0.020309461 -0.048993699
[21] -0.008230875 -0.097707527 -0.172529218 -0.111123830 -0.029342936
[26] -0.160869780 -0.212448668 -0.215728711 -0.142864005 -0.165523577
[31] -0.155731209 -0.164295222 -0.144045277 -0.206656181 -0.235480926
[36] -0.206260891 -0.153332659 -0.213401802 -0.295790466 -0.260754852
[41] -0.204633720 -0.217831444 -0.201517250 -0.202251274 -0.195355856
[46] -0.210589202 -0.221746657 -0.206262265 -0.147136227
> (mypacf <- c(rpacf$acf))
 [1]  0.720717646  0.188609744  0.301012716  0.107443107 -0.033141143
 [6]  0.081386815 -0.241309595  0.151101017 -0.226710244 -0.148389926
[11]  0.266805256  0.269441049 -0.288632042 -0.177172136 -0.135277990
[16]  0.091611087 -0.018914226  0.076872118 -0.005341988 -0.006023931
[21] -0.082559718 -0.043861547 -0.008150474  0.009268770 -0.099541480
[26] -0.026849344  0.043793437  0.184249610 -0.083324914  0.028688700
[31] -0.028911020 -0.182417410 -0.010648540 -0.040698787 -0.033820566
[36] -0.088409197  0.100999530 -0.064832328  0.116907178 -0.081584078
[41]  0.037176843 -0.067821147 -0.059517734 -0.012978620  0.021998437
[46]  0.018203564 -0.049081547 -0.074275615
> 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/4337o1413376716.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/517d81413376716.tab") 
> 
> try(system("convert tmp/1ugvm1413376716.ps tmp/1ugvm1413376716.png",intern=TRUE))
character(0)
> try(system("convert tmp/2pka41413376716.ps tmp/2pka41413376716.png",intern=TRUE))
character(0)
> try(system("convert tmp/3jn7f1413376716.ps tmp/3jn7f1413376716.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  1.142   0.218   1.377