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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Description/Abstract

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
Date Deposited: 18 Jan 2011 14:54
Last Modified: 27 Mar 2014 19:20
URI: http://eprints.soton.ac.uk/id/eprint/170229

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