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:
Organisations: University of Southampton, Faculty of Social, Human and Mathematical Sciences
ePrint ID: 170229
Date :
Date Event
9 March 2010Published
Date Deposited: 18 Jan 2011 14:54
Last Modified: 18 Apr 2017 03:29
Further Information:Google Scholar
URI: http://eprints.soton.ac.uk/id/eprint/170229

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