Admissibility and Complete Classes for False Discovery Rate Control with E-values
arXiv:2607.14380
The paper analyzes the admissibility of e‑value based procedures for controlling the false discovery rate, showing that weighted‑mean e‑Benjamini‑Hochberg methods form a complete class of optimal procedures.
Abstract
The false discovery rate (FDR) is the most widely used error metric in modern multiple testing. We provide the first comprehensive analysis of the admissibility of e-value-based procedures with FDR control. We consider both simultaneous and point procedures and introduce strong and weak notions of dominance. We show that every simultaneous procedure is strongly, and hence weakly, dominated by an admissible weighted-mean closed e-Benjamini-Hochberg () procedure, so weighted-mean procedures form a complete class. Moreover, every constant-free weighted-mean procedure is admissible at every level. Within the symmetric class, the usual mean procedure is the largest element if and only if the FDR level is small enough; otherwise this class has no largest element. We also obtain results on the admissibility of symmetric procedures with non-zero constant terms, and give guidance on the choice of the constant terms. Point e-testing procedures have a parallel theory for admissibility, where point weighted-mean procedures form a complete class. These results highlight the central role of weighted-mean procedures in multiple testing.
46 pages, 2 figures; includes supplementary material