2 citations · 2 across the 21 of their papers we have counts for
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Empirical Bayes prepivoting under group invariance: false discovery rate control and moderated t-tests
Nikolaos Ignatiadis, Etienne Roquain
We consider simultaneously testing hypotheses about thousands of units, e.g., genes or proteins, where each unit yields a handful of replicate measurements and we test whether its…
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…
How does limma-trend work? An empirical partially Bayes perspective
Sagnik Nandy, Wanyi Ling, Nikolaos Ignatiadis
In high-throughput biology, it is common to fit thousands of linear regressions -- one per gene, protein, or other unit -- with very few samples per unit. Limma-trend, one of the m…
Empirical Bayes Rebiasing
Wanyi Ling, Sida Li, Junming Guan +1
We study methods for simultaneous analysis of many noisy and biased estimates, each paired with an even noisier estimate of its own bias. The analyst's goal is to construct short c…
Tiny but uniform improvements of adaptive BH procedures via compound e-values
Nikolaos Ignatiadis, Ruodu Wang, Aaditya Ramdas
After the seminal Benjamini-Hochberg (BH) procedure for controlling the false discovery rate (FDR) was proposed, dozens of papers have attempted to improve its power by adapting to…
Partially Bayes p-values for large scale inference
Nikolaos Ignatiadis, Li Ma
We seek to conduct statistical inference for a large collection of primary parameters, each with its own nuisance parameters. Our approach is partially Bayesian, in that we treat t…