Exact formulas for the normalizing constants of Wishart distributions for graphical models

DOI10.1214/17-AOS1543zbMath1392.62146arXiv1406.4901OpenAlexW2963026254MaRDI QIDQ1747734

Caroline Uhler, Alex Lenkoski, Donald St. P. Richards

Publication date: 27 April 2018

Published in: The Annals of Statistics (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1406.4901

zbMATH Keywords

generalized hypergeometric function of matrix argumentbipartite graphdirected acyclic graphWishart distributionchordal graphCholesky decompositionGaussian graphical modelnormalizing constant\(G\)-Wishart distributionBartlett decompositionmoral graph

Mathematics Subject Classification ID

Characterization and structure theory for multivariate probability distributions; copulas (62H05) Exact distribution theory in statistics (62E15) Probability distributions: general theory (60E05)

Related Items (14)

Unbiased approximation of posteriors via coupled particle Markov chain Monte Carlo ⋮ The G-Wishart Weighted Proposal Algorithm: Efficient Posterior Computation for Gaussian Graphical Models ⋮ Gaussian graphical modeling for spectrometric data analysis ⋮ Bayesian analysis of nonparanormal graphical models using rank-likelihood ⋮ The Inverse G‐Wishart distribution and variational message passing ⋮ Rejoinder: ``Robust Bayesian graphical modeling using Dirichlet \(t\)-distributions ⋮ On a wider class of prior distributions for graphical models ⋮ Accelerating Bayesian Structure Learning in Sparse Gaussian Graphical Models ⋮ Bayesian graph selection consistency under model misspecification ⋮ Bayesian inference in nonparanormal graphical models ⋮ Exact formulas for the normalizing constants of Wishart distributions for graphical models ⋮ Bayesian method for causal inference in spatially-correlated multivariate time series ⋮ A review of Gaussian Markov models for conditional independence ⋮ Simultaneous Variable and Covariance Selection With the Multivariate Spike-and-Slab LASSO

Uses Software

• HdBCS

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