Marginal Likelihood Computation for Model Selection and Hypothesis Testing: An Extensive Review

DOI10.1137/20M1310849OpenAlexW3000534101WikidataQ122235370 ScholiaQ122235370MaRDI QIDQ5883296

David Delgado, Luca Martino, Unnamed Author, Fernando Rodriguez Llorente

Publication date: 30 March 2023

Published in: SIAM Review (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/2005.08334

zbMATH Keywords

numerical integrationmodel selectionhypothesis testingpartition functionsmarginal likelihoodquadrature rulesBayesian evidencedoubly intractable posteriors

Mathematics Subject Classification ID

Related Items (4)

Priors in Bayesian Deep Learning: A Review ⋮ Target-aware Bayesian inference via generalized thermodynamic integration ⋮ Generalized integral transform and Hamiltonian Monte Carlo for Bayesian structural damage identification ⋮ MCMC-driven importance samplers

Uses Software

• BayesDA
• tsbridge

Cites Work

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