Corpus ID: 70350062

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}
}
  • Dmitriy Katz, Karthikeyan Shanmugam, +1 author Caroline Uhler
  • Published in AISTATS 2019
  • Computer Science, Mathematics
  • 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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