Tudor Manole

Refined Convergence Rates for Maximum Likelihood Estimation under Finite Mixture Models

We revisit the classical problem of deriving convergence rates for the maximum likelihood estimator (MLE) in finite mixture models. The Wasserstein distance has become a standard loss function for the analysis of parameter estimation in these models, due in part to its ability to circumvent label sw…