Toric invariant theory for maximum likelihood estimation in log-linear models

12/14/2020

∙

by   Carlos Améndola, et al.

∙

0

∙

share

We establish connections between invariant theory and maximum likelihood estimation for discrete statistical models. We show that norm minimization over a torus orbit is equivalent to maximum likelihood estimation in log-linear models. We use notions of stability under a torus action to characterize the existence of the maximum likelihood estimate, and discuss connections to scaling algorithms.