E-values have gained attention as potential alternatives to p-values as measures of
uncertainty, significance and evidence. In brief, e-values are realized by random variables …

The classic frequentist theory of hypothesis testing developed by Neyman, Pearson and
Fisher has a claim to being the twentieth century's most influential piece of applied …

There are various multiple comparison procedures used in confirmatory clinical studies and
exploratory research for multiplicity adjustment. Among them are the Hochberg and …

In the context of large-scale multiple hypothesis testing, the hypotheses often possess
certain group structures based on additional information such as Gene Ontology in gene …

In the context of multiple hypothesis testing, the proportion π0 of true null hypotheses in the
pool of hypotheses to test often plays a crucial role, although it is generally unknown a priori …

We study how to combine p-values and e-values, and design multiple testing procedures
where both p-values and e-values are available for every hypothesis. Our results provide a …

We show that the control of the false discovery rate (FDR) for a multiple testing procedure is
implied by two coupled simple sufficient conditions. The first one, which we call “self …

Within a Bayesian decision theoretic framework we investigate some asymptotic optimality
properties of a large class of multiple testing rules. A parametric setup is considered, in …

In this work we study an adaptive step-down procedure for testing m hypotheses. It stems
from the repeated use of the false discovery rate controlling the linear step-up procedure …

For the problem of multiple testing, the Benjamini-Hochberg (BH) procedure has become a
very popular method in applications. We show how the BH procedure can be interpreted as …