Winter 2024 STAT 41551-1

Course: STAT 41551

Title: Empirical Bayes

Instructor(s): Nikos Ignatiadis

Class Schedule: MW 1:30 PM-2:50 PM in Jones 226

Description: In an empirical Bayes analysis, we imitate inferences made by an oracle Bayesian with extensive knowledge of the data-generating distribution. Empirical Bayes provides a principled approach for “learning from the experience of others” and is widely used in application domains such as genomics, small-area estimation, economics, and large-scale experimentation. In this graduate topics course, we provide an overview of empirical Bayes. We revisit the original papers that introduced the core ideas and explain how empirical Bayes is applied in practice. We also develop mathematical techniques to study empirical Bayes procedures from a theoretical perspective.