Computational solutions for Bayesian inference in mixture models

Gilles Celeux, Kaniav Kamary, Gertraud Malsiner-Walli, Jean-Michel Marin, Christian P. Robert

Publication: Chapter in book/Conference proceedingChapter in edited volume

Abstract

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 robustness of the Gibbs sampler in high dimensional Gaussian settings.
Original languageEnglish
Title of host publicationHandbook of Mixture Analysis
Editors Sylvia Frühwirth-Schnatter, Gilles Celeux, Christian P. Robert
Place of PublicationBoca Raton, Florida
PublisherChapman & Hall
Pages73 - 96
ISBN (Print)978-1498763813
Publication statusPublished - 2019

Austrian Classification of Fields of Science and Technology (ÖFOS)

  • 101018 Statistics

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