False Discovery Rate Control under Archimedean Copula
Abstract
We are considered with the false discovery rate (FDR) of the linear step-up test LSU considered by Benjamini and Hochberg (1995). It is well known that LSU controls the FDR at level m0 q / m if the joint distribution of p-values is multivariate totally positive of order 2. In this, m denotes the total number of hypotheses, m0 the number of true null hypotheses, and q the nominal FDR level. Under the assumption of an Archimedean p-value copula with completely monotone generator, we derive a sharper upper bound for the FDR of LSU as well as a non-trivial lower bound. Application of the sharper upper bound to parametric subclasses of Archimedean p-value copulae allows us to increase the power of LSU by pre-estimating the copula parameter and adjusting q. Based on the lower bound, a sufficient condition is obtained under which the FDR of LSU is exactly equal to m0 q / m, as in the case of stochastically independent p-values. Finally, we deal with high-dimensional multiple test problems with exchangeable test statistics by drawing a connection between infinite sequences of exchangeable p-values and Archimedean copulae with completely monotone generators. Our theoretical results are applied to important copula families, including Clayton copulae and Gumbel copulae.
Turn this paper into a lesson
ArcXiv compiles a structured reading guide from this paper's metadata: plain-English importance, contributions, prerequisite concepts, which sections to read first, flashcards, and a quiz. Grounded in the abstract, never invented.