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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Original Publication URL: http://dx.doi.org/10.1080/00949650008812054
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 |
| Item ID: | 29961 |
| Date Deposited: | 12 Mar 2007 |
| Last Modified: | 01 Jun 2011 02:09 |
| Contributors: | Ntzoufras, Ioannis (Author) Forster, Jonathan J. (Author) Dellaportas, Petros (Author) |
| Date: | 2000 |
| Status: | Published |
| URI: | http://eprints.soton.ac.uk/id/eprint/29961 |
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