285 citations · 784 across the 27 of their papers we have counts for
Showing 2021Show all
3 papers · 1 filter
stat.ME2021★ 4 cited
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…
math.ST2021★ 3 cited
Whiteout: when do fixed-X knockoffs fail?
Xiao Li, William Fithian
A core strength of knockoff methods is their virtually limitless customizability, allowing an analyst to exploit machine learning algorithms and domain knowledge without threatenin…
stat.ME2021★ 3 cited
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…