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.


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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.

Item Type: Thesis (Doctoral)
Subjects: Q Science > QA Mathematics
Divisions : University Structure - Pre August 2011 > School of Mathematics
Faculty of Social and Human Sciences
ePrint ID: 170229
Accepted Date and Publication Date:
9 March 2010Made publicly available
Date Deposited: 18 Jan 2011 14:54
Last Modified: 31 Mar 2016 13:31

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