Asymptotic properties of the maximum likelihood estimator in autoregressive models with Markov regime
2004 (English)In: Annals of Statistics, ISSN 0090-5364, Vol. 32, no 5, 2254-2304 p.Article in journal (Refereed) Published
An autoregressive process with Markov regime is an autoregressive process for which the regression function at each time point is given by a nonobservable Markov chain. In this paper we consider the asymptotic properties of the maximum likelihood estimator in a possibly nonstationary process of this kind for which the hidden state space is compact but not necessarily finite. Consistency and asymptotic normality are shown to follow from uniform exponential forgetting of the initial distribution for the hidden Markov chain conditional on the observations.
Place, publisher, year, edition, pages
2004. Vol. 32, no 5, 2254-2304 p.
Probability Theory and Statistics
IdentifiersURN: urn:nbn:se:kth:diva-61546DOI: 10.1214/009053604000000021ISI: 000225071400018OAI: oai:DiVA.org:kth-61546DiVA: diva2:479345
QC 201201252012-01-172012-01-172012-01-25Bibliographically approved