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Matroid Stratification of ML Degrees of Independence Models

Authors :
Clarke, Oliver
Hoşten, Serkan
Kushnerchuk, Nataliia
Oldekop, Janike
Publication Year :
2023

Abstract

We study the maximum likelihood (ML) degree of discrete exponential independence models and models defined by the second hypersimplex. For models with two independent variables, we show that the ML degree is an invariant of a matroid associated to the model. We use this description to explore ML degrees via hyperplane arrangements. For independence models with more variables, we investigate the connection between the vanishing of factors of its principal $A$-determinant and its ML degree. Similarly, for models defined by the second hypersimplex, we determine its principal $A$-determinant and give computational evidence towards a conjectured lower bound of its ML degree.<br />Comment: 24 pages, 3 figures, 6 tables

Details

Database :
arXiv
Publication Type :
Report
Accession number :
edsarx.2312.10010
Document Type :
Working Paper