Game-theoretic Statistical Inference: Optional Sampling, Universal Inference, and Multiple Testing Based on E-values

This half-size MFO workshop brings together researchers in mathematical statistics, probability theory, machine learning, medical sciences, and economics to discuss recent developments in sequential inference. New sequential inference methods that build on nonnegative martingale techniques allow us to elegantly solve prominent shortcomings of traditional statistical hypothesis tests. Instead of p-values, they are based on e-values which have the added benefit that their meaning is much easier to communicate to applied researchers, due to their intuitive interpretation in terms of the wealth of a gambler playing a hypothetically fair game. Significant new contributions to this fast growing research area will be presented in order to stimulate collaborations, discuss and unify notation and concepts in the fields, and tackle a variety of open problems and address current major challenges.

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Publication Details

Journal
Oberwolfach Reports
Published
2024-11-25
DOI
https://doi.org/10.4171/owr/2024/24
Primary Topic
Statistical Methods in Clinical Trials
Type
article
Field-Weighted Citation Impact
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article

Game-theoretic Statistical Inference: Optional Sampling, Universal Inference, and Multiple Testing Based on E-values

Aaditya Ramdas, Ruodu Wang, Peter Grünwald, Johanna F. Ziegel
Oberwolfach Reports
Statistical Methods in Clinical Trials
article

Game-theoretic Statistical Inference: Optional Sampling, Universal Inference, and Multiple Testing Based on E-values

Aaditya Ramdas, Ruodu Wang, Peter Grünwald, Johanna F. Ziegel
article en

Abstract

This half-size MFO workshop brings together researchers in mathematical statistics, probability theory, machine learning, medical sciences, and economics to discuss recent developments in sequential inference. New sequential inference methods that build on nonnegative martingale techniques allow us to elegantly solve prominent shortcomings of traditional statistical hypothesis tests. Instead of p-values, they are based on e-values which have the added benefit that their meaning is much easier to communicate to applied researchers, due to their intuitive interpretation in terms of the wealth of a gambler playing a hypothetically fair game. Significant new contributions to this fast growing research area will be presented in order to stimulate collaborations, discuss and unify notation and concepts in the fields, and tackle a variety of open problems and address current major challenges.

Oberwolfach ReportsVol. 21(2)
Centrum Wiskunde & Informatica (NL), University of Waterloo (CA), ETH Zurich (CH), Carnegie Mellon University (US)
Openalex Percentile: Top 78%
Statistical Methods in Clinical Trials
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