Aggregation of Multiple Knockoffs
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Publication:6335295
arXiv2002.09269MaRDI QIDQ6335295
Author name not available (Why is that?)
Publication date: 21 February 2020
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.
Has companion code repository: https://github.com/ja-che/hidimstat
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