On Choosing Mixture Components via Non-Local Priors

DOI10.1111/rssb.12333zbMath1429.62243arXiv1604.00314OpenAlexW2966460335MaRDI QIDQ5213449

Jairo A. Fúquene, Mark F. J. Steel, David Rossell

Publication date: 3 February 2020

Published in: Journal of the Royal Statistical Society Series B: Statistical Methodology (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1604.00314

zbMATH Keywords

model selectionBayes factorAkaike information criterionmixture modelsnon-local priors

Mathematics Subject Classification ID

Classification and discrimination; cluster analysis (statistical aspects) (62H30) Statistical aspects of information-theoretic topics (62B10)

Related Items (7)

MCMC Computations for Bayesian Mixture Models Using Repulsive Point Processes ⋮ On a class of repulsive mixture models ⋮ Heterogeneous large datasets integration using Bayesian factor regression ⋮ On posterior contraction of parameters and interpretability in Bayesian mixture modeling ⋮ Density regression using repulsive distributions ⋮ Determinantal point process mixtures via spectral density approach ⋮ An explanatory rationale for priors sharpened into Occam's razors

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