Unverified50% confidenceFactExact time
Model-X knockoffs was proposed by Barber and Candès in 2015 and is a variable selection framework that achieves exact FDR control under the condition that the covariate distribution is known.
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10/16/2026
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UnverifiedThe knockoff method constructs a counterfeit variable for each original variable and requires the two to satisfy exchange symmetry in the joint distribution, thereby using the difference in statistics between original variables and knockoffs to control the FDR; column-permutation equivariance is a key prerequisite for constructing valid knockoff statistics.65% similarUnverifiedA new study proposes a complementary method called MAS (Model-Agnostic Selection with agent-X importance) for achieving FDR-controlled variable selection without assumptions on the covariate distribution.65% similarUnverifiedModel-X knockoffs does not depend on the model form of the outcome variable Y, and only requires that the distribution of the covariates X is known.64% similarUnverifiedMAS and Model-X knockoffs are complementary: when the covariate distribution is known or can be estimated accurately, knockoffs may be the more efficient choice; when the distribution is unknown or difficult to model, MAS exhibits a model-agnostic advantage.60% similarUnverified卡尔曼滤波是线性高斯假设下的贝叶斯最优估计器，其预测-更新两步迭代对应先验与后验概率的递推计算60% similar
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