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Asymptotic properties of the maximum likelihood estimator in autoregressive models with Markov regime
Lund University.
2004 (English)In: Annals of Statistics, ISSN 0090-5364, E-ISSN 2168-8966, Vol. 32, no 5, 2254-2304 p.Article in journal (Refereed) Published
Abstract [en]

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.
National Category
Probability Theory and Statistics
Identifiers
URN: urn:nbn:se:kth:diva-61546DOI: 10.1214/009053604000000021ISI: 000225071400018OAI: oai:DiVA.org:kth-61546DiVA: diva2:479345
Note
QC 20120125Available from: 2012-01-17 Created: 2012-01-17 Last updated: 2017-12-08Bibliographically approved

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CiteExportLink to record
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