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Tropical combinatorics of max-linear Bayesian networks

Journal of symbolic computation (JSC), 2024
15 November 2024
Carlos Améndola
Kamillo Ferry
    TPM
ArXiv (abs)PDFHTML
Main:25 Pages
9 Figures
Bibliography:2 Pages
1 Tables
Abstract

A polytrope is a tropical polyhedron that is also classically convex. We study the tropical combinatorial types of polytropes associated to weighted directed acyclic graphs (DAGs). This family of polytropes arises in algebraic statistics when describing the model class of max-linear Bayesian networks. We show how the edge weights of a network directly relate to the facet structure of the corresponding polytrope. We also give a classification of polytropes from weighted DAGs at different levels of equivalence. These results give insight on the statistical problem of identifiability for a max-linear Bayesian network.

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