688 citations · 1.8k across the 36 of their papers we have counts for
38 papers
Computational Solutions for Bayesian Inference in Mixture Models
Gilles Celeux, Kaniav Kamary, Gertraud Malsiner-Walli +2
This chapter surveys the most standard Monte Carlo methods available for simulating from a posterior distribution associated with a mixture and conducts some experiments about the…
Some discussions on the Read Paper "Beyond subjective and objective in statistics" by A. Gelman and C. Hennig
Gilles Celeux, Jack Jewson, Julie Josse +2
This note is a collection of several discussions of the paper "Beyond subjective and objective in statistics", read by A. Gelman and C. Hennig to the Royal Statistical Society on A…
A fully objective Bayesian approach for the Behrens-Fisher problem using historical studies
Antoine Barbieri, Jean-Michel Marin, Karine Florin
For in vivo research experiments with small sample sizes and available historical data, we propose a sequential Bayesian method for the Behrens-Fisher problem. We consider it as a…
ABC random forests for Bayesian parameter inference
Louis Raynal, Jean-Michel Marin, Pierre Pudlo +3
This preprint has been reviewed and recommended by Peer Community In Evolutionary Biology (http://dx.doi.org/10.24072/pci.evolbiol.100036). Approximate Bayesian computation (ABC) h…
Hidden Gibbs random fields model selection using Block Likelihood Information Criterion
Julien Stoehr, Jean-Michel Marin, Pierre Pudlo
Performing model selection between Gibbs random fields is a very challenging task. Indeed, due to the Markovian dependence structure, the normalizing constant of the fields cannot…
Bayesian Essentials with R: The Complete Solution Manual
Christian P. Robert, Jean-Michel Marin
This is the collection of solutions for all the exercises proposed in Bayesian Essentials with R (2014).