Efron’s elegant approach to $g$-modeling for empirical Bayes problems is contrasted with an implementation of the Kiefer–Wolfowitz nonparametric maximum likelihood estimator for mixture models for several examples. The latter approach has the advantage that it is free of tuning parameters and consequently provides a relatively simple complementary method.
"Comment: Minimalist $g$-Modeling." Statist. Sci. 34 (2) 209 - 213, May 2019. https://doi.org/10.1214/19-STS706