Size of Interventional Markov Equivalence Classes in Random DAG Models

Directed acyclic graph (DAG) models are popular for capturing causal relationships. From observational and interventional data, a DAG model can only be determined up to its interventional Markov equivalence class (I-MEC). We investigate the size of MECs for random DAG models generated by uniformly sampling and ordering an Erdős-Rényi graph. For constant density, we show that the expected.

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The International Conference on Artificial Intelligence and Statistics