There is an innate human tendency, one might call it the “league table mentality,” to
construct rankings. Schools, hospitals, sports teams, movies, and myriad other objects are …

Abstract Models of unobserved heterogeneity, or frailty as it is commonly known in survival
analysis, can often be formulated as semiparametric mixture models and estimated by …

This article concerns the Bayes and frequentist aspects of empirical Bayes inference. Some
of the ideas explored go back to Robbins in the 1950s, while others are current. Several …

Empirical Bayes methods for Gaussian compound decision problems involving longitudinal
data are considered. The new convex optimization formulation of the nonparametric (Kiefer …

Multivariate, heteroscedastic errors complicate statistical inference in many large-scale
denoizing problems. Empirical Bayes is attractive in such settings, but standard parametric …

Labor economists increasingly work in empirical contexts with large numbers of unitspecific
parameters. These settings include a growing number of value-added studies measuring …

We study empirical Bayes estimation in high-dimensional linear regression. To facilitate
computationally efficient estimation of the underlying prior, we adopt a variational empirical …

Nonparametric maximum likelihood (NPML) for mixture models is a technique for estimating
mixing distributions that has a long and rich history in statistics going back to the 1950s, and …

The two key issues of modern Bayesian statistics are:(i) establishing principled approach for
distilling statistical prior that is consistent with the given data from an initial believable …

The venerable method of maximum likelihood has found numerous recent applications in
nonparametric estimation of regression and shape constrained densities. For mixture …