On Use of the Em Algorithm for Penalized Likelihood Estimation

1990415 citationsJournal Article

Authors

Abstract

SUMMARY The EM algorithm is a popular approach to maximum likelihood estimation but has not been much used for penalized likelihood or maximum a posteriori estimation. This paper discusses properties of the EM algorithm in such contexts, concentrating on rates of convergence, and presents an alternative that is usually more practical and converges at least as quickly.

Topics & Keywords

Direction-of-Arrival Estimation Techniques Survey Sampling and Estimation Techniques Control Systems and Identification

UN Sustainable Development Goals

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Publication Details

Published in: Journal of the Royal Statistical Society Series B (Statistical Methodology)

Volume 52, Issue 3, pp. 443-452

DOI: 10.1111/j.2517-6161.1990.tb01798.x

Field-Weighted Citation Impact: 10.21