Optimal weighting for false discovery rate control
arXiv:0807.4081 · doi:10.1214/09-EJS430
Abstract
How to weigh the Benjamini-Hochberg procedure? In the context of multiple hypothesis testing, we propose a new step-wise procedure that controls the false discovery rate (FDR) and we prove it to be more powerful than any weighted Benjamini-Hochberg procedure. Both finite-sample and asymptotic results are presented. Moreover, we illustrate good performance of our procedure in simulations and a genomics application. This work is particularly useful in the case of heterogeneous -value distributions.
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- Heterocedasticity-Adjusted Ranking and Thresholding for Large-Scale Multiple Testing
- Using prior information to boost power in correlation structure support recovery