4 citations · 13 across the 10 of their papers we have counts for
11 papers · 1 filter
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…
Locally Simultaneous Inference
Tijana Zrnic, William Fithian
Selective inference is the problem of giving valid answers to statistical questions chosen in a data-driven manner. A standard solution to selective inference is simultaneous infer…
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…
BONuS: Multiple multivariate testing with a data-adaptivetest statistic
Chiao-Yu Yang, Lihua Lei, Nhat Ho +1
We propose a new adaptive empirical Bayes framework, the Bag-Of-Null-Statistics (BONuS) procedure, for multiple testing where each hypothesis testing problem is itself multivariate…
AdaPT-GMM: Powerful and robust covariate-assisted multiple testing
Patrick Chao, William Fithian
We propose a new empirical Bayes method for covariate-assisted multiple testing with false discovery rate (FDR) control, where we model the local false discovery rate for each hypo…