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Default Bayesian model determination for generalised liner mixed models

Overstall, Anthony Marshall (2010) Default Bayesian model determination for generalised liner mixed models University of Southampton, School of Mathematics, Doctoral Thesis , 145pp.

Record type: Thesis (Doctoral)


In this thesis, an automatic, default, fully Bayesian model determination strategy for GLMMs is considered. This strategy must address the two key issues of default prior specification and computation.

Default prior distributions for the model parameters, that are based on a unit information concept, are proposed.

A two-phase computational strategy, that uses a reversible jump algorithm and implementation of bridge sampling, is also proposed.

This strategy is applied to four examples throughout this thesis.

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Published date: 9 March 2010
Organisations: University of Southampton, Faculty of Social, Human and Mathematical Sciences


Local EPrints ID: 170229
PURE UUID: 491892fd-acae-4b79-b3ee-5bdc838de7aa

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Date deposited: 18 Jan 2011 14:54
Last modified: 18 Jul 2017 12:17

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Author: Anthony Marshall Overstall
Thesis advisor: Jonathan Forster

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