A Comparison of Marginal Likelihood Computation Methods
AbstractIn a Bayesian analysis, different models can be compared on the basis of theexpected or marginal likelihood they attain. Many methods have been devised to compute themarginal likelihood, but simplicity is not the strongest point of most methods. At the sametime, the precision of methods is often questionable.In this paper several methods are presented in a common framework. The explanation of thedifferences is followed by an application, in which the precision of the methods is testedon a simple regression model where a comparison with analytical results is possible.
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Date of creation: 17 Sep 2002
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Marginal likelihood; Bayesian analysis.;
Find related papers by JEL classification:
- C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
- C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
- C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
This paper has been announced in the following NEP Reports:
- NEP-ALL-2002-12-02 (All new papers)
- NEP-CMP-2002-12-02 (Computational Economics)
- NEP-ECM-2002-12-10 (Econometrics)
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