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E-VALUES
by
Vovk, Vladimir
, Wang, Ruodu
in
Bayesian analysis
/ Calibration
/ Hypotheses
/ Hypothesis testing
/ Likelihood ratio
/ Statistical inference
/ Testing
2021
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E-VALUES
by
Vovk, Vladimir
, Wang, Ruodu
in
Bayesian analysis
/ Calibration
/ Hypotheses
/ Hypothesis testing
/ Likelihood ratio
/ Statistical inference
/ Testing
2021
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Journal Article
E-VALUES
2021
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Overview
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.
Publisher
Institute of Mathematical Statistics
Subject
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