E-values : Calibration, combination, and applications. / Vovk, Vladimir; Wang, Ruodu.

In: The Annals of Statistics, 17.09.2020.

Research output: Contribution to journalArticle

Forthcoming

Documents

  • Accepted Manuscript

    Accepted author manuscript, 582 KB, PDF document

Abstract

Multiple testing of a single hypothesis and testing multiple hypotheses are usually done in terms of p-values. In this paper we replace p-values with their natural competitor, e-values, which are closely related to betting, Bayes factors, and likelihood ratios. We demonstrate that e-values are often mathematically more tractable; in particular, in multiple testing of a single hypothesis, e-values can be merged simply by averaging them. This allows us to develop efficient procedures using e-values for testing multiple hypotheses.
Original languageEnglish
JournalThe Annals of Statistics
Publication statusAccepted/In press - 17 Sep 2020

ID: 39085461