Dey, Subhrakanti and Krishnamurthy, Vikram (1994) Maximum likelihood estimation of time-series with Markov regime. In: Proceedings of 1994 33rd IEEE Conference on Decision and Control. IEEE, pp. 2867-2857. ISBN 0780319680

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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.

Item Type:	Book Section
Additional Information:	Cite as: S. Dey and V. Krishnamurthy, "Maximum likelihood estimation of time-series with Markov regime," Proceedings of 1994 33rd IEEE Conference on Decision and Control, 1994, pp. 2856-2857 vol.3, doi: 10.1109/CDC.1994.411365.
Keywords:	Maximum; likelihood; estimation; time-series; Markov; regime;
Academic Unit:	Faculty of Science and Engineering > Electronic Engineering Faculty of Science and Engineering > Research Institutes > Hamilton Institute
Item ID:	14426
Identification Number:	https://doi.org/10.1109/CDC.1994.411365
Depositing User:	Subhrakanti Dey
Date Deposited:	12 May 2021 14:25
Publisher:	IEEE
Refereed:	Yes
URI:	Publisher
Use Licence:	This item is available under a Creative Commons Attribution Non Commercial Share Alike Licence (CC BY-NC-SA). Details of this licence are available here

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