R version 2.12.0 (2010-10-15)
Copyright (C) 2010 The R Foundation for Statistical Computing
ISBN 3-900051-07-0
Platform: i486-pc-linux-gnu (32-bit)

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> x <- c(1200,1400,1210,1260,1320,1320,1310,1260,1340,1180,1330,1390,1130,1340,1140,1290,1260,1280,1330,1270,1300,1150,1410,1250,1030,1320,1160,1300,1190,1310,1290,1320,1300,1230,1330,1220,1010,1290,1170,1240,1260,1260,1310,1360,1250,1170,1360,1140,1030,1260,1210,1190,1230,1350,1300,1340,1270,1220,1400,1120,1000,1260,1260,1150,1240,1360,1350,1280,1320,1210,1370,1060,1040,1260,1210,1200,1200,1290,1400,1280,1280,1220,1350,1000,980,1240,1190,1200,1150,1270,1410,1420,1260,1300,1410,1000,950,1280,1330,1190,1170,1270,1340,1470,1270,1280,1430,980)
> 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/www/rcomp/tmp/1487v1344873778.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/www/rcomp/tmp/2rb4p1344873778.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/www/rcomp/tmp/3h63n1344873778.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  0.051926941 -0.087052281  0.126941217 -0.049180509
 [6] -0.182339051 -0.399601216 -0.178582686 -0.077054565  0.106832271
[11] -0.110436380  0.121356460  0.770000296  0.032403594 -0.041925442
[16]  0.091813175 -0.037635009 -0.191176739 -0.339206987 -0.190920997
[21] -0.096071955  0.127792048 -0.126115312  0.112233360  0.583724874
[26]  0.008341760 -0.004839875  0.062903658 -0.024322981 -0.159410218
[31] -0.270185525 -0.175812169 -0.061109682  0.116439706 -0.141043955
[36]  0.138806244  0.468973316 -0.042096917  0.012067915  0.075452425
[41] -0.039844071 -0.130746473 -0.211246466 -0.134912458 -0.065400234
[46]  0.093852502 -0.117846286  0.135726531  0.356710466
> (mypacf <- c(rpacf$acf))
 [1]  0.051926941 -0.089991341  0.138028325 -0.075870843 -0.154085597
 [6] -0.429979688 -0.215058702 -0.176553351  0.197628686 -0.197498772
[11]  0.041646718  0.659758347  0.036889077  0.007522364 -0.097104510
[16] -0.052398161 -0.028617801  0.082963736 -0.034963612 -0.044103304
[21]  0.079069482 -0.032776979 -0.119032713 -0.086227256 -0.102802942
[26]  0.005721121  0.016357206  0.027680722  0.038403853  0.018868512
[31]  0.015722167  0.044876410 -0.042464547 -0.042722563  0.083463553
[36]  0.117709289 -0.075145106 -0.022264118  0.023965813 -0.061692024
[41]  0.016049636 -0.027839443  0.020207310 -0.084314451  0.009249743
[46]  0.009624915 -0.043290517 -0.034034525
> lengthx <- length(x)
> sqrtn <- sqrt(lengthx)
> 
> #Note: the /var/www/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/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/www/rcomp/tmp/4xoh81344873778.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/www/rcomp/tmp/5aq4y1344873778.tab") 
> 
> try(system("convert tmp/1487v1344873778.ps tmp/1487v1344873778.png",intern=TRUE))
character(0)
> try(system("convert tmp/2rb4p1344873778.ps tmp/2rb4p1344873778.png",intern=TRUE))
character(0)
> try(system("convert tmp/3h63n1344873778.ps tmp/3h63n1344873778.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  0.910   0.320   1.207