Constrained log-optimal e-variables are obtained by post-processing the unconstrained optimal e-variable via an appropriate transformation.
arXiv preprint arXiv:2409.05654 , year=
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E-measures generalize E-values to intersection-closed hypothesis classes, yielding uniform evidence bounds, automatic familywise evidence control without multiplicity correction, and a frequentist E-prior to E-posterior update.
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Optimal e-variables under constraints
Constrained log-optimal e-variables are obtained by post-processing the unconstrained optimal e-variable via an appropriate transformation.
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The E-measure
E-measures generalize E-values to intersection-closed hypothesis classes, yielding uniform evidence bounds, automatic familywise evidence control without multiplicity correction, and a frequentist E-prior to E-posterior update.