Local mixture models of exponential families

Karim Anaya-Izquierdo, Paul Marriott

Research output: Contribution to journalArticle

9 Citations (Scopus)
130 Downloads (Pure)

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.
Original languageEnglish
Pages (from-to)623-640
Number of pages18
JournalBernoulli
Volume13
Issue number3
DOIs
Publication statusPublished - 2007

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