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Chapitre D'ouvrage Année : 2020

Markov Chain Monte Carlo Algorithms for Bayesian Computation, a Survey and Some Generalisation

Résumé

This chapter briefly recalls the major simulation based methods for conducting Bayesian computation, before focusing on partly deterministic Markov processes and a novel modification of the bouncy particle sampler that offers an interesting alternative when dealing with large datasets.
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Dates et versions

hal-03912194 , version 1 (23-12-2022)

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Wu Changye, Christian Robert. Markov Chain Monte Carlo Algorithms for Bayesian Computation, a Survey and Some Generalisation. Case Studies in Applied Bayesian Data Science, 2259, Springer International Publishing, pp.89-119, 2020, Lecture Notes in Mathematics, ⟨10.1007/978-3-030-42553-1_4⟩. ⟨hal-03912194⟩
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