Empirical Bayes and Its Applications: Shrinkage, Hypothesis Testing, and More

Explore the principles and applications of Empirical Bayes in this comprehensive lecture by Matthew Stephens at the Computational Genomics Summer Institute (CGSI) 2024. Delve into key concepts such as shrinkage and hypothesis testing, and discover how these statistical methods are revolutionizing genomic studies. Learn about the historical context of Empirical Bayes, including Efron and Morris's seminal work on Stein's estimation rule. Gain insights into practical applications through examples like baseball statistics analysis. Examine the impact of Empirical Bayes on false discovery rates and its role in developing flexible statistical methods for estimating and testing effects in genomic studies with multiple conditions. This 46-minute talk provides a thorough overview of Empirical Bayes, its theoretical foundations, and its growing importance in computational genomics and beyond.