Computing Bayes Factors Using Thermodynamic Integration
Université de Montpellier · Centre National de la Recherche Scientifique · +3 more institutions
Abstract
In the Bayesian paradigm, a common method for comparing two models is to compute the Bayes factor, defined as the ratio of their respective marginal likelihoods. In recent phylogenetic works, the numerical evaluation of marginal likelihoods has often been performed using the harmonic mean estimation procedure. In the present article, we propose to employ another method, based on an analogy with statistical physics, called thermodynamic integration. We describe the method, propose an implementation, and show on two analytical examples that this numerical method yields reliable estimates. In contrast, the harmonic mean estimator leads to a strong overestimation of the marginal likelihood, which is all the more…
Citation impact
- FWCI
- 7.91
- Percentile
- 100%
- References
- 63
Authors
2Topics & keywords
- Bayes factor
- Estimator
- Bayes' theorem
- Marginal likelihood
- Harmonic mean
- Mathematics
- Bayesian probability
- Applied mathematics