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A note on NPML estimation for exponential family regression models with unspecified dispersion parameter

Einbeck, Jochen; Hinde, John

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Authors

John Hinde



Abstract

Nonparametric maximum likelihood (NPML) estimation for exponential families with unspecified dispersion parameter \phi suffers from computational instability, which can lead to highly fluctuating EM trajectories and suboptimal solutions, in particular when \phi is allowed to vary over mixture components. In this paper, a damped version of the EM algorithm is proposed to cope with these problems.

Citation

Einbeck, J., & Hinde, J. (2006). A note on NPML estimation for exponential family regression models with unspecified dispersion parameter. Austrian Journal of Statistics, 35(2&3), 233-243

Journal Article Type Article
Publication Date Jun 1, 2006
Deposit Date Sep 29, 2008
Publicly Available Date Mar 29, 2024
Journal Austrian Journal of Statistics
Print ISSN 1026-597X
Publisher Austrian Society for Statistics
Peer Reviewed Peer Reviewed
Volume 35
Issue 2&3
Pages 233-243
Keywords EM algorithm, Random effect models, Nonparametric maximum likelihood, Overdispersion, Gamma distribution, Generalized linear model.
Publisher URL http://www.stat.tugraz.at/AJS/ausg062+3/Welcome.html

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