Nothing
"FitARMA" <-
function(z,order=c(0,0,0),demean=TRUE,MeanMLEQ=FALSE,pApprox=30,MaxLag=30){
p<-order[1]
d<-order[2]
q<-order[3]
Z<-z
if (d > 0) Z<-diff(z, differences=d)
if (demean)
mz<-mean(Z)
else
mz<-0
y<-Z-mz
pApp<-pApprox
if (q == 0) pApp<-p
ans<-GetFitARMA(y,p,q,pApp)
LL<-ans$loglikelihood
mu<-iter<-0
if (MeanMLEQ && (p>0||q>0)) {
etol <- MaxIter <- 10
while(etol> 1e-06 && iter<MaxIter){
LLPrev<-LL
iter<-iter+1
g<-TacvfARMA(ans$phi,ans$theta,pApp)
coefAR<-PacfDL(g, LinearPredictor=TRUE)$ARCoefficients
mu<-GetARMeanMLE(y, coefAR)
ans<-GetFitARMA(y-mu,p,q,pApp)
LL<-ans$loglikelihood
etol<-abs(LL-LLPrev)/LLPrev
if (ans$convergence != 0)
stop("GetARFit returned convergence = ",ans$convergence)
}
}
muHat<-mu+mz
phiHat<-ans$phiHat
thetaHat<-ans$thetaHat
if (p>0 || q>0) {
g<-TacvfARMA(phiHat,thetaHat,pApp)
coefAR<-PacfDL(g, LinearPredictor=TRUE)$ARCoefficients
res<-BackcastResidualsAR(y, coefAR, Q=100, demean=FALSE)
}
else
res<-Z-muHat
fits<-Z-res
n<-length(res)
sigsq<-sum(res^2)/n
if (p>0 || q>0)
covHat<-solve(InformationMatrixARMA(phiHat,thetaHat))/n
else
covHat<-numeric(0)
racf<-(acf(res, plot=FALSE, lag.max=MaxLag)$acf)[-1]
LBQ<-LjungBoxTest(res, lag.max=MaxLag, k=order[1]+order[3])
if (d == 0)
if (q == 0) ModelTitle<-paste("AR(",p,")",sep="")
if (q > 1) ModelTitle<-paste("ARMA(",p,",",q,")",sep="")
else
ModelTitle<-paste("ARIMA(",p,",",d,",",q,")",sep="")
out<-list(loglikelihood=ans$loglikelihood,phiHat=phiHat,thetaHat=thetaHat,sigsqHat=sigsq,muHat=muHat,covHat=covHat,
racf=racf, LjungBoxQ=LBQ,res=res,fits=fits, demean=demean,
iterationCount=iter,convergence=ans$convergence, MeanMLE=MeanMLEQ, tsp=tsp(z),order=order,call=match.call(),
DataTitle=attr(z,"title"),ModelTitle=ModelTitle)
class(out)<-"FitARMA"
out
}
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