Bernoulli

  • Bernoulli
  • Volume 13, Number 3 (2007), 623-640.

Local mixture models of exponential families

Karim Anaya-Izquierdo and Paul Marriott

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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.

Article information

Source
Bernoulli, Volume 13, Number 3 (2007), 623-640.

Dates
First available in Project Euclid: 7 August 2007

Permanent link to this document
https://projecteuclid.org/euclid.bj/1186503479

Digital Object Identifier
doi:10.3150/07-BEJ6170

Mathematical Reviews number (MathSciNet)
MR2348743

Zentralblatt MATH identifier
1129.62005

Keywords
affine geometry convex geometry differential geometry dispersion model exponential families mixture model statistical manifold

Citation

Anaya-Izquierdo, Karim; Marriott, Paul. Local mixture models of exponential families. Bernoulli 13 (2007), no. 3, 623--640. doi:10.3150/07-BEJ6170. https://projecteuclid.org/euclid.bj/1186503479


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