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Chapitre D'ouvrage Année : 2016

Approximate Bayesian Computation: A Survey on Recent Results

Résumé

Approximate Bayesian Computation (ABC) methods have become a “mainstream” statistical technique in the past decade, following the realisation by statisticians that they are a special type of non-parametric inference. In this survey of ABC methods, we focus on the recent literature, building on the previous survey of Marin et al. Stat Comput 21(2):279–291, 2011, [39]. Given the importance of model choice in the applications of ABC, and the associated difficulties in its implementation, we also give emphasis to this aspect of ABC techniques.

Dates et versions

hal-01409281 , version 1 (05-12-2016)

Identifiants

Citer

Christian Robert. Approximate Bayesian Computation: A Survey on Recent Results. Ronald Cools; Dirk Nuyens. Monte Carlo and Quasi-Monte Carlo Methods, Springer International Publishing, pp.185-205, 2016, 978-3-319-33505-6. ⟨10.1007/978-3-319-33507-0_7⟩. ⟨hal-01409281⟩
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