Bayesian Inference for Gaussian Graphical Models Beyond Decomposable Graphs

DOI10.1111/rssb.12276zbMath1398.62063arXiv1505.00703OpenAlexW2963145051MaRDI QIDQ4962087

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Publication date: 30 October 2018

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/1505.00703

zbMATH Keywords

Gibbs samplerGaussian graphical modelsgeneralized \(G\)-Wishart distributiongeneralized Bartlett graphscalable Bayesian inference

Mathematics Subject Classification ID

Bayesian inference (62F15) Exact distribution theory in statistics (62E15) Graphical methods in statistics (62A09)

Related Items (4)

The G-Wishart Weighted Proposal Algorithm: Efficient Posterior Computation for Gaussian Graphical Models ⋮ A Bayesian Subset Specific Approach to Joint Selection of Multiple Graphical Models ⋮ Bayesian graph selection consistency under model misspecification ⋮ Bayesian method for causal inference in spatially-correlated multivariate time series

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