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Asymptotic properties of the maximum likelihood estimator in autoregressive models with Markov regime

  • Lund University

Résultats de recherche: Contribution à un journalArticleRevue par des pairs

144 Citations (Scopus)

Résumé

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.

langue originaleAnglais
Pages (de - à)2254-2304
Nombre de pages51
journalAnnals of Statistics
Volume32
Numéro de publication5
Les DOIs
étatPublié - 1 oct. 2004

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