A comparative study of Monte Carlo methods for efficient evaluation of marginal likelihoods
David Ardia, Nalan Basturk, Lennart Hoogerheide & Herman Van Dijk
| Résumé |
Strategic choices for efficient and accurate evaluation of marginal
likelihoods by means of Monte Carlo simulation methods are studied
for the case of highly non-elliptical posterior distributions. A
comparative analysis is presented of possible advantages and
limitations of different simulation techniques; of possible choices
of candidate distributions and choices of target or warped target
distributions; and finally of numerical standard errors. The
importance of a robust and flexible estimation strategy is
demonstrated where the complete posterior distribution is explored.
Given an appropriately yet quickly tuned adaptive candidate,
straightforward importance sampling provides a computationally
efficient estimator of the marginal likelihood (and a reliable and
easily computed corresponding numerical standard error) in the
cases investigated, which include a non-linear regression model and
a mixture GARCH model. Warping the posterior density can lead to a
further gain in efficiency, but it is more important that the
posterior kernel be appropriately wrapped by the candidate
distribution than that it is warped. |
| Mots-clés |
Marginal likelihood; Bayes factor; Importance sampling; Bridge sampling; Adaptive mixture of Student-tt distributions |
| Citation | Ardia, D., Basturk, N., Hoogerheide, L., & Van Dijk , H. (2012). A comparative study of Monte Carlo methods for efficient evaluation of marginal likelihoods. Computational Statistics & Data Analysis, 56(11), 3398-3414. |
| Type | Article de périodique (Anglais) |
| Date de publication | 2012 |
| Nom du périodique | Computational Statistics & Data Analysis |
| Volume | 56 |
| Numéro | 11 |
| Pages | 3398-3414 |
| URL | http://www.sciencedirect.com/science/article/pii/S0167947... |
| Liée au projet | Bayesian estimation of regime-switching GARCH models |