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Paper detail

Optimal e-values for testing the mean of a bounded random variable against a composite alternative

We derive the unique e-values with optimal (relative) growth rate in the worst case for testing the mean of a bounded random variable, hereby contributing with the first application beyond the assumption of mutually absolutely continuous hypotheses of the (RE)GROW quality criteria for e-values originally proposed by Grünwald et al. (2024). For both criteria, we characterise explicitly the alternatives for which it is most difficult to test against, which also admit a meaningful interpretation. We give two important examples of interest where REGROW provides a powerful quality criterion to choose optimal e-variables whereas GROW leads to trivial solutions.

preprint2026arXivOpen access
Sebastian ArnoldEugenio Clerico
math.STStatistics Theory
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Sebastian ArnoldEugenio Clerico

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