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Local mixture models of exponential families

Anaya-Izquierdo, Karim and Marriott, Paul (2007). Local mixture models of exponential families. Bernoulli, 13(3) pp. 623–640.

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DOI (Digital Object Identifier) Link: http://doi.org/10.3150/07-BEJ6170
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Abstract

Exponential families are the workhorses of parametric modelling theory. One reason for their popularity is their associated inference theory, which is very clean, both from a theoretical and a computational point of view. One way in which this set of tools can be enriched in a natural and interpretable way is through mixing. This paper develops and applies the idea of local mixture modelling to exponential families. It shows that the highly interpretable and flexible models which result have enough structure to retain the attractive inferential properties of exponential families. In particular, results on identification, parameter orthogonality and log-concavity of the likelihood are proved.

Item Type: Journal Article
Copyright Holders: 2007 ISI/BS
ISSN: 1350-7265
Keywords: affine geometry; convex geometry; differential geometry; dispersion model; exponential families; mixture model; statistical manifold
Academic Unit/Department: Mathematics, Computing and Technology > Mathematics and Statistics
Mathematics, Computing and Technology
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Item ID: 10290
Depositing User: Karim Anaya Izquierdo
Date Deposited: 18 Jan 2008
Last Modified: 24 Feb 2016 14:32
URI: http://oro.open.ac.uk/id/eprint/10290
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