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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: | 10.1109/CDC.1994.411365 |
| Depositing User: | Subhrakanti Dey |
| Date Deposited: | 12 May 2021 14:25 |
| Publisher: | IEEE |
| Refereed: | Yes |
| Related URLs: | |
| URI: | https://mu.eprints-hosting.org/id/eprint/14426 |
| 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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