Empirical Bayes estimation via data fission

Abstract

We demonstrate how data fission, a method for creating synthetic replicates from single observations, can be applied to empirical Bayes estimation. This extends recent work on empirical Bayes with multiple replicates to the classical single-replicate setting. The key insight is that after data fission, empirical Bayes estimation can be cast as a general regression problem.

This note was prepared as a comment on "Data Fission: Splitting a Single Data Point," by James Leiner, Boyan Duan, Larry Wasserman, and Aaditya Ramdas, a discussion paper in the Journal of the American Statistical Association