In statistics, the knockoff filter, or simply knockoffs, is a framework for variable selection. It was originally introduced for linear regression by Rina Barber and Emmanuel Candès, and later generalized to other regression models in the random design setting. Knockoffs has found application in many practical areas, notably in genome-wide association studies.
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