834 citations · 3.9k across the 95 of their papers we have counts for
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Model Selection for Mixture Models - Perspectives and Strategies
Gilles Celeux, Sylvia Fruewirth-Schnatter, Christian P. Robert
Determining the number G of components in a finite mixture distribution is an important and difficult inference issue. This is a most important question, because statistical infere…
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…
Rethinking the Effective Sample Size
Víctor Elvira, Luca Martino, Christian P. Robert
The effective sample size (ESS) is widely used in sample-based simulation methods for assessing the quality of a Monte Carlo approximation of a given distribution and of related in…
Accelerating MCMC Algorithms
Christian P. Robert, Victor Elvira, Nick Tawn +1
Markov chain Monte Carlo algorithms are used to simulate from complex statistical distributions by way of a local exploration of these distributions. This local feature avoids heav…
Approximating the Likelihood in Approximate Bayesian Computation
Christopher C Drovandi, Clara Grazian, Kerrie Mengersen +1
This chapter will appear in the forthcoming Handbook of Approximate Bayesian Computation (2018). The conceptual and methodological framework that underpins approximate Bayesian com…