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=
3 Pith papers cite this work. Polarity classification is still indexing.
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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.
Demonstrates formal equivalence between adaptive design tools and e-value sequential tests while noting differences in emphasis on flexibility aspects.
citing papers explorer
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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.
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Anytime-valid testing with e-values and confirmatory adaptive designs
Demonstrates formal equivalence between adaptive design tools and e-value sequential tests while noting differences in emphasis on flexibility aspects.