Aggregation of Multiple Knockoffs

Tuan-Binh Nguyen, Jérôme-Alexis Chevalier, Bertrand Thirion, Sylvain Arlot
2/21/2020
math.STstat.APstat.ME

Official code: ja-che/hidimstat (23 stars, BSD-2-Clause, last commit 2024-10-16).

Abstract

We develop an extension of the Knockoff Inference procedure, introduced by Barber and Candes (2015). This new method, called Aggregation of Multiple Knockoffs (AKO), addresses the instability inherent to the random nature of Knockoff-based inference. Specifically, AKO improves both the stability and power compared with the original Knockoff algorithm while still maintaining guarantees for False Discovery Rate control. We provide a new inference procedure, prove its core properties, and demonstrate its benefits in a set of experiments on synthetic and real datasets.

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ja-che/hidimstatOfficial100%
BSD-2-Clause

HiDimStat: High-dimensional statistical inference tool for Python

238Shell, PythonApr 29, 20202 years agoBSD-2-Clause

Cite this paper

@article{nguyen2020aggregation,
  title  = {Aggregation of Multiple Knockoffs},
  author = {Tuan-Binh Nguyen and Jérôme-Alexis Chevalier and Bertrand Thirion and Sylvain Arlot},
  year   = {2020},
  eprint = {2002.09269},
  archivePrefix = {arXiv},
  url    = {https://arxiv.org/abs/2002.09269}
}

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