# Size of Interventional Markov Equivalence Classes in Random DAG Models

@article{Katz2019SizeOI, title={Size of Interventional Markov Equivalence Classes in Random DAG Models}, author={Dmitriy Katz and Karthikeyan Shanmugam and Chandler Squires and Caroline Uhler}, journal={ArXiv}, year={2019}, volume={abs/1903.02054} }

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 \emph{interventional Markov equivalence class} (I-MEC). We investigate the size of MECs for random DAG models generated by uniformly sampling and ordering an Erdős-Renyi graph. For constant density, we show that the expected $\log$ observational MEC size asymptotically (in the number of vertices) approaches a constant. We… CONTINUE READING

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