Learning Block Structured Graphs in Gaussian Graphical Models
Learning Block Structured Graphs in Gaussian Graphical Models
Within the framework of Gaussian graphical models, a prior distribution for the underlying graph is introduced to induce a block structure in the adjacency matrix of the graph and learning relationships between fixed groups of variables. A novel sampling strategy named Double Reversible Jumps Markov chain Monte Carlo is developed …