Tropical combinatorics of max-linear Bayesian networks
File(s)
Published version
Author(s)
Améndola, Carlos
Ferry, Kamillo
Type
Journal Article
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.
Date Issued
2026-05-01
Date Acceptance
2025-10-03
Citation
Journal of Symbolic Computation, 2026, 134
ISSN
0747-7171
Publisher
Elsevier BV
Journal / Book Title
Journal of Symbolic Computation
Volume
134
Copyright Statement
© 2025 The Author(s). Published by Elsevier Ltd. This is an open access article under the CC BY license (http:// creativecommons.org/licenses/by/4.0/).
License URL
Publication Status
Published
Article Number
102518
Date Publish Online
2025-10-08