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- W2991402341 abstract "Barber and Candes recently introduced a feature selection method called knockoff+ that controls the false discovery rate (FDR) among the selected features in the classical linear regression problem. Knockoff+ uses the competition between the original features and artificially created knockoff features to control the FDR [1]. We generalize Barber and Candes' knockoff construction to generate multiple knockoffs and use those in conjunction with a recently developed general framework for multiple competition-based FDR control [9]. We prove that using our initial multiple-knockoff construction the combined procedure rigorously controls the FDR in the finite sample setting. Because this construction has a somewhat limited utility we introduce a heuristic we call batching which significantly improves the power of our multiple-knockoff procedures. Finally, we combine the batched knockoffs with a new context-dependent resampling scheme that replaces the generic resampling scheme used in the general multiple-competition setup. We show using simulations that the resulting multi-knockoff-select procedure empirically controls the FDR in the finite setting of the variable selection problem while often delivering substantially more power than knockoff+." @default.
- W2991402341 created "2019-12-05" @default.
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- W2991402341 date "2019-11-21" @default.
- W2991402341 modified "2023-09-27" @default.
- W2991402341 title "Controlling the FDR in variable selection via multiple knockoffs" @default.
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