Consistency and identifiability of autoregressive models with Markov regime

TitleConsistency and identifiability of autoregressive models with Markov regime
Publication TypeConference Paper
Year of Publication1999
AuthorsKrishnamurthy, V., and T. Ryden
Conference NameInformation, Decision and Control, 1999. IDC 99. Proceedings. 1999
Pagination251 -256
Keywordsautoregressive model consistency, autoregressive model identifiability, autoregressive processes, conditional maximum likelihood estimation, identification, Markov processes, Markov regime, maximum likelihood estimation, nonobservable Markov chain, regression function
Abstract

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. We show consistency of a conditional maximum likelihood estimation and discuss identifiability of such models

URLhttp://dx.doi.org/10.1109/IDC.1999.754164
DOI10.1109/IDC.1999.754164

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