##Statistics Seminar##\\ Department of Mathematics and Statistics
^ **DATE:**|Thursday, October 12, 2023 |
^ **TIME:**|1:15pm -- 2:15pm |
^ **LOCATION:**|WH 100E |
^ **SPEAKER:**|Baozhen Wang, Binghamton University |
^ **TITLE:**|E-values: Calibration, combination and applications |
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**Abstract**
Multiple testing of a single hypothesis and testing multiple
hypotheses are usually done in terms of p-values. In this paper, the
authors replace p-values with their natural competitor, e-values, which
are closely related to betting, Bayes factors and likelihood ratios. They
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.