Ordinal causal discovery based on Markov blankets

Yu Du (), Yi Sun () and Luyao Tan ()
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Yu Du: Xinjiang University
Yi Sun: Xinjiang University
Luyao Tan: Xinjiang University

Computational Statistics, 2025, vol. 40, issue 3, No 7, 1335 pages

Abstract: Abstract This work focuses on learning causal network structures from ordinal categorical data. By combining constraint-based with score-and-search methodologies in structural learning, we propose a hybrid method called Markov Blanket Based Ordinal Causal Discovery (MBOCD) algorithm, which can capture the ordinal relationship of values in ordinal categorical variables. Theoretically, it is proved that for ordinal causal networks, two adjacent DAGs belonging to the same Markov equivalence class are identifiable, which results in the generation of a causal graph. Simulation experiments demonstrate that the proposed algorithm outperforms existing methods in terms of computational efficiency and accuracy. The code of this work is open at: https://github.com/leoydu/MBOCDcode.git .

Keywords: Bayesian network; Causal discovery; Ordinal regression; Markov blanket; V-structure (search for similar items in EconPapers)
Date: 2025
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DOI: 10.1007/s00180-024-01513-1

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