Our upcoming event for the Statistics Colloquium Series is scheduled for Monday, October 5th from 12:00 – 1:00pm (ET) and will be an in-person presentation at Maxwell-Dworkin, Room 119. Lunch will be provided to guests following the talk. This week's speaker will be Zhimei Ren of Assistant professor in the Department of Statistics and Data Science at the Wharton School, University of Pennsylvania.
Adaptive experimental design for multiple testing
Abstract: I will talk about adaptive experimental design for multiple testing, where an experimenter sequentially chooses which hypothesis to sample. We propose the e-value-based posterior sampling (e-PS) procedure, which uses the empirical average of log e-value increments to guide randomized sampling and applies e-BH to construct rejection sets. Under conditionally valid e-value increments, the procedure controls the false discovery rate at arbitrary stopping times and produces nested rejection sets. We establish high-probability bounds on the number of samples needed to discover all nonnull hypotheses in terms of the growth and concentration of the underlying e-processes. We specialize these bounds to simple-versus-simple, composite-versus-simple, and simple-versus-composite testing. Simulations and experiments illustrate the procedure’s power under limited sampling budgets.
Speakers Bio: Zhimei Ren is an assistant professor in the Department of Statistics and Data Science at the Wharton School, University of Pennsylvania. From 2021-2023, she was a postdoctoral researcher in the Statistics Department at the University of Chicago. She obtained her Ph.D. in Statistics from Stanford University in 2021. Her research interests include selective inference, distribution-free inference, and data-driven decision making.