Date/Time
Date(s) - 09/10/2025
3:30 pm - 4:30 pm

Britton Lectures

Dr. Giles Hooker
Professor, Department of Statistics & Data Science
University of Pennsylvania
Research Area: statistical methods using dynamical systems models, functional data analysis, and statistical aspects of fair and interpretable machine learning

Location: BSB-B135

Title: V-Statistics and Variance Estimation: Inference for Ensemble Methods

Abstract: This talk discusses uncertainty quantification and inference using ensemble methods. Recent theoretical developments inspired by random forests have cast bagging-type methods as U-statistics when bootstrap samples are replaced by subsamples, resulting in a central limit theorem and hence the potential for inference. However, to carry this out requires estimating a variance for which all proposed estimators exhibit substantial upward bias. In this talk, we convert subsamples without replacement to subsamples with replacement resulting in V-statistics for which we prove a novel central limit theorem. We also show that in this context, the asymptotic variance can be expressed as the variance of a conditional expectation which is approximated by sampling from the empirical distribution and allows for valid bias corrections. We finish by illustrating the use of these tools in combining or comparing statistical models.