Accelerating Bayesian Structure Learning in Sparse Gaussian Graphical Models

DOI10.1080/01621459.2021.1996377arXiv1706.04416OpenAlexW3185747415MaRDI QIDQ6110023

Reza Mohammadi, Gérard Letac, Hélène Massam

Publication date: 4 July 2023

Published in: Journal of the American Statistical Association (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1706.04416

zbMATH Keywords

model selectionBayes factors\(G\)-Wishartnormalizing constants

Mathematics Subject Classification ID

Statistics (62-XX)

Related Items (2)

Guest editors' introduction to the special issue ``Network psychometrics in action: methodological innovations inspired by empirical problems ⋮ The G-Wishart Weighted Proposal Algorithm: Efficient Posterior Computation for Gaussian Graphical Models

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