Maximum likelihood estimation of time-series with Markov regime

TitleMaximum likelihood estimation of time-series with Markov regime
Publication TypeConference Paper
Year of Publication1994
AuthorsDey, S., and V. Krishnamurthy
Conference NameDecision and Control, 1994., Proceedings of the 33rd IEEE Conference on
Pagination2856 -2857 vol.3
Date Publisheddec.
Keywordsestimation theory, expectation maximization, Markov chain, Markov processes, Markov regime, maximum likelihood estimation, optimisation, parameter estimation, probability, time series, time-series, transition probability
Abstract

In this paper, we consider the estimation of various Markov-modulated time-series. We obtain maximum likelihood estimates of the time-series parameters including the Markov chain transition probabilities and the time-series coefficients using the expectation maximization (EM) algorithm. Also the recursive EM algorithm is used to obtain online parameter estimates. Simulation studies show that both algorithms yield satisfactory results

URLhttp://dx.doi.org/10.1109/CDC.1994.411365
DOI10.1109/CDC.1994.411365

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