Discrete Statistical Models with Rational Maximum Likelihood Estimator

  • Eliana Duarte (Max Planck Institute for Mathematics in the Sciences)
E1 05 (Leibniz-Saal)


A discrete statistical model is a subset of a probability simplex. Its maximum likelihood estimator (MLE) is a retraction from that simplex onto the model. We characterize all models for which this retraction is a rational function. This is a contribution via real algebraic geometry which rests on results due to Huh and Kapranov on Horn uniformization. We present an algorithm for constructing models with rational MLE, and we demonstrate it on a range of instances. Our focus lies on models like Bayesian networks, decomposable graphical models, and staged trees.


Valeria Hünniger

Max-Planck-Institut für Mathematik in den Naturwissenschaften Contact via Mail

Guido Montúfar

Max Planck Institute for Mathematics in the Sciences