The Geometry of Mixture Likelihoods, Part II: The Exponential Family

Abstract

Geometric analysis of the mixture likelihood set of univariate exponential family densities yields results which tie the number and location of support points for the nonparametric maximum likelihood estimator of the mixing distribution to sign changes in certain integrated polynomials. One corollary is a very general uniqueness theorem for the estimator.