English

The FDR-Linking Theorem

Statistics Theory 2018-12-24 v1 Statistics Theory

Abstract

This paper introduces the \texttt{FDR-linking} theorem, a novel technique for understanding \textit{non-asymptotic} FDR control of the Benjamini--Hochberg (BH) procedure under arbitrary dependence of the pp-values. This theorem offers a principled and flexible approach to linking all pp-values and the null pp-values from the FDR control perspective, suggesting a profound implication that, to a large extent, the FDR of the BH procedure relies mostly on the null pp-values. To illustrate the use of this theorem, we propose a new type of dependence only concerning the null pp-values, which, while strictly \textit{relaxing} the state-of-the-art PRDS dependence (Benjamini and Yekutieli, 2001), ensures the FDR of the BH procedure below a level that is independent of the number of hypotheses. This level is, furthermore, shown to be optimal under this new dependence structure. Next, we present a concept referred to as \textit{FDR consistency} that is weaker but more amenable than FDR control, and the \texttt{FDR-linking} theorem shows that FDR consistency is completely determined by the joint distribution of the null pp-values, thereby reducing the analysis of this new concept to the global null case. Finally, this theorem is used to obtain a sharp FDR bound under arbitrary dependence, which improves the log\log-correction FDR bound (Benjamini and Yekutieli, 2001) in certain regimes.

Keywords

Cite

@article{arxiv.1812.08965,
  title  = {The FDR-Linking Theorem},
  author = {Weijie J. Su},
  journal= {arXiv preprint arXiv:1812.08965},
  year   = {2018}
}
R2 v1 2026-06-23T06:52:14.632Z