统计与数据科学系系列学术报告之四百二十四期

时    间：2024年4月18日（周四）16:00-17:00

地    点：李达三楼104室

主持人：复旦大学 管理学院 统计与数据科学系 刚博文 博士

报告人：Dr. Brad Rava  The University of Sydney

题   目：Irrational Exuberance: Correcting Bias in Probability Estimates

摘   要：We consider the common setting where one observes probability estimates for a large number of events, such as default risks for numerous bonds. Unfortunately, even with unbiased estimates, selecting events corresponding to the most extreme probabilities can result in systematically underestimating the true level of uncertainty. We develop an empirical Bayes approach “Excess Certainty Adjusted Probabilities” (ECAP), using a variant of Tweedie’s formula, which updates probability estimates to correct for selection bias. ECAP is a flexible non-parametric method, which directly estimates the score function associated with the probability estimates, so it does not need to make any restrictive assumptions about the prior on the true probabilities. ECAP also works well in settings where the probability estimates are biased. We demonstrate through theoretical results, simulations, and an analysis of two real world data sets, that ECAP can provide significant improvements over the original probability estimates.

Link: https://www.tandfonline.com/doi/full/10.1080/01621459.2020.1787175

个人简介：Brad Rava is a Lecturer in the discipline of Business Analytics at the University of Sydney's Business School. His research focuses on Empirical Bayes techniques, Fairness in Machine Learning, Statistical Machine Learning, and High Dimensional Statistics. Brad Rava’s research interests focus modern statistical methods for addressing pressing societal problems that arise from combining automated decision making with high-risk scenarios.

统计与数据科学系

2024-4-7