RANK: Large-Scale Inference With Graphical Nonlinear Knockoffs
نویسندگان
چکیده
منابع مشابه
Robust inference with knockoffs
We consider the variable selection problem, which seeks to identify important variables influencing a response Y out of many candidate features X1, . . . , Xp. We wish to do so while offering finite-sample guarantees about the fraction of false positives—selected variables Xj that in fact have no effect on Y after the other features are known. When the number of features p is large (perhaps eve...
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We consider the variable selection problem, which seeks to identify important variables influencing a response Y out of many candidate features X1, . . . , Xp. We wish to do so while offering finite-sample guarantees about the fraction of false positives—selected variables Xj that in fact have no effect on Y after the other features are known. When the number of features p is large (perhaps eve...
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Power and reproducibility are key to enabling refined scientific discoveries in contemporary big data applications with general high-dimensional nonlinear models. In this paper, we provide theoretical foundations on the power and robustness for the modelfree knockoffs procedure introduced recently in Candès, Fan, Janson and Lv (2016) in high-dimensional setting when the covariate distribution i...
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ژورنال
عنوان ژورنال: Journal of the American Statistical Association
سال: 2019
ISSN: 0162-1459,1537-274X
DOI: 10.1080/01621459.2018.1546589