Scaling It Up: Stochastic Search Structure Learning in Graphical Models
[摘要] Gaussian concentration graph models and covariance graph models are two classes of graphical models that are useful for uncovering latent dependence structures among multivariate variables. In the Bayesian literature, graphs are often determined through t
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[效力级别] [学科分类] 统计和概率
[关键词] Bayesian inference;Bi-directed graph;Block Gibbs;Concentration graph models;Covariance graph models;Credit default swap;Undirected graph;Structural learning [时效性]
