Stochastic search variable selection for log-linear models


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), 23-37. (doi:10.1080/00949650008812054).

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Description/Abstract

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.

Item Type: Article
ISSNs: 0094-9655 (print)
Related URLs:
Keywords: bayesian analysis, contingency table, gibbs sampling, markov chain monte carlo
Subjects: Q Science > QA Mathematics
H Social Sciences > HA Statistics
Divisions: University Structure - Pre August 2011 > School of Mathematics > Statistics
ePrint ID: 29961
Date Deposited: 12 Mar 2007
Last Modified: 27 Mar 2014 18:18
URI: http://eprints.soton.ac.uk/id/eprint/29961

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