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.
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
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
|Date Deposited:||18 Jan 2011 14:54|
|Last Modified:||27 Mar 2014 19:20|
|RDF:||RDF+N-Triples, RDF+N3, RDF+XML, Browse.|
Actions (login required)