A default prior distribution for contingency tables with dependent factor levels
A default prior distribution for contingency tables with dependent factor levels
A default prior distribution is proposed for the Bayesian analysis of contingency tables. The prior is specified to allow for dependence between levels of the factors. Different dependence structures are considered, including conditional autoregressive and distance correlation structures. To demonstrate the prior distribution, a dataset is considered which involves estimating the number of injecting drug users in the eleven National Health Service board regions of Scotland using an incomplete contingency table where the dependence structure relates to geographical regions.
90-99
Overstall, Antony
c1d6c8bd-1c5f-49ee-a845-ec9ec7b20910
King, Ruth
64ab7d0e-2ce7-4c68-96c3-e25d876542be
January 2014
Overstall, Antony
c1d6c8bd-1c5f-49ee-a845-ec9ec7b20910
King, Ruth
64ab7d0e-2ce7-4c68-96c3-e25d876542be
Overstall, Antony and King, Ruth
(2014)
A default prior distribution for contingency tables with dependent factor levels.
Statistical Methodology, 16 (1), .
(doi:10.1016/j.stamet.2013.08.007).
Abstract
A default prior distribution is proposed for the Bayesian analysis of contingency tables. The prior is specified to allow for dependence between levels of the factors. Different dependence structures are considered, including conditional autoregressive and distance correlation structures. To demonstrate the prior distribution, a dataset is considered which involves estimating the number of injecting drug users in the eleven National Health Service board regions of Scotland using an incomplete contingency table where the dependence structure relates to geographical regions.
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Accepted/In Press date: 14 August 2013
e-pub ahead of print date: 23 August 2013
Published date: January 2014
Organisations:
Statistics
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Local EPrints ID: 401171
URI: http://eprints.soton.ac.uk/id/eprint/401171
ISSN: 1572-3127
PURE UUID: d20118a7-5e14-49b4-9aba-b744351168a8
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Date deposited: 05 Oct 2016 14:07
Last modified: 15 Mar 2024 03:27
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Author:
Ruth King
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