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Stochastic search variable selection for log-linear models

Record type: Article

We develop a Markov chain Monte Carlo algorithm, based on 'stochastic search variable selection' (George and McCuUoch, 1993), for identifying promising log-linear models. The method may be used in the analysis of multi-way contingency tables where the set of plausible models is very large.

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Citation

Ntzoufras, Ioannis, Forster, Jonathan J. and Dellaportas, Petros (2000) Stochastic search variable selection for log-linear models Journal of Statistical Computation and Simulation, 68, (1), pp. 23-37. (doi:10.1080/00949650008812054).

More information

Published date: 2000
Keywords: bayesian analysis, contingency table, gibbs sampling, markov chain monte carlo
Organisations: Statistics

Identifiers

Local EPrints ID: 29961
URI: http://eprints.soton.ac.uk/id/eprint/29961
ISSN: 0094-9655
PURE UUID: ad91a24d-7346-49f3-a930-8605f27652c4

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Date deposited: 12 Mar 2007
Last modified: 17 Jul 2017 15:56

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Contributors

Author: Ioannis Ntzoufras
Author: Petros Dellaportas

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