7 papers
Estimating the local false discovery rate under an unknown symmetric null
Daniel Xiang, William Fithian, Nikolaos Ignatiadis +2
This paper is concerned with estimating the local false discovery rate (lfdr) in a two-groups model where the only assumption regarding the null distribution is symmetry about zero…
Estimating the False Discovery Rate of Variable Selection
Yixiang Luo, William Fithian, Lihua Lei
We introduce a generic estimator for the false discovery rate of any model selection procedure, in common statistical modeling settings including the Gaussian linear model, Gaussia…
A frequentist local false discovery rate
Daniel Xiang, Jake A. Soloff, William Fithian
The local false discovery rate (lfdr) of Efron et al. (2001) enjoys major conceptual and decision-theoretic advantages over the false discovery rate (FDR) as an error criterion in…
A Flexible Defense Against the Winner's Curse
Tijana Zrnic, William Fithian
Across science and policy, decision-makers often need to draw conclusions about the best candidate among competing alternatives. For instance, researchers may seek to infer the eff…
Improving knockoffs with conditional calibration
Yixiang Luo, William Fithian, Lihua Lei
The knockoff filter of Barber and Candes (arXiv:1404.5609) is a flexible framework for multiple testing in supervised learning models, based on introducing synthetic predictor vari…
Asymptotically Optimal Knockoff Statistics via the Masked Likelihood Ratio
Asher Spector, William Fithian
In feature selection problems, knockoffs are synthetic controls for the original features. Employing knockoffs allows analysts to use nearly any variable importance measure or "fea…