A framework for optimal posterior e-values with non-convex composite hypotheses, demonstrated via statistical tests for multiple voting systems including the first treatment of Schulze.
Hypothesis testing with e-values.Foundations and Trends® in Statistics2025;1(1-2):1–390
8 Pith papers cite this work. Polarity classification is still indexing.
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Introduces a set-preserving P2E calibrator for conformal prediction that improves efficiency and supports exact 1-alpha coverage in cross-conformal prediction and conformal aggregation.
Characterizes the optimal e-power for ε-DP e-value hypothesis testing between P^n and Q^n, supplies a matching algorithm, and gives matching bounds on stopping times for private e-processes.
Finite-horizon optimal e-value designs for adaptive single-arm binary trials are constructed via dynamic programming and shown to have competitive operating characteristics with automatic futility indication.
The authors create e-processes for monotonicity and unimodality testing that achieve power one and consistent mode estimation under i.i.d. sampling.
PFWCP achieves personalized asymptotic marginal and calibration-conditional coverage in federated conformal prediction via density ratio weighting and quantile aggregation under one-shot communication.
The paper argues that statistical inference requires nuanced scientific context and that universal significance thresholds should be abandoned.
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Optimal Posterior E-values with Non-Convex Parameter Sets with Applications to Voting Systems
A framework for optimal posterior e-values with non-convex composite hypotheses, demonstrated via statistical tests for multiple voting systems including the first treatment of Schulze.
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E-values and sequential power-one tests for monotonicity and unimodality
The authors create e-processes for monotonicity and unimodality testing that achieve power one and consistent mode estimation under i.i.d. sampling.