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Sponsored by the Center for Science and Technology Development of the Ministry of Education
Supervised by Ministry of Education of the People's Republic of China
Directed acyclic graphs (DAGs) and completed partial directed acyclic graphs (CPDAG) are widely used to represent causal systems or uncertain probability systems. Some studies about small graphs with dozens of nodes have shown that given the number of nodes, p, in average, each CPDAG encode about 3.7 DAGs. In this paper, we analyze the properties of CPDAGs with large dimensions and sparsity settings via MCMC approach.
Keywords:Mathematical statistics; Graphical model; causal network; space of graphs; sparse graph