A conditional adaptive perturbation approach enables valid in-sample inference for machine learning-identified subgroups with nonregular boundaries via triple robustness.
Journal of the Royal Statistical Society Series B: Statistical Methodology , volume=
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PRADAS derives a Bayes-optimal mirror statistic for any splitting scheme, establishes asymptotic FDR control under weak dependence, and optimizes the split ratio as a stopping time to improve power over standard equal-split methods.
The weighted Holm procedure (WHP) based on ordered weighted p-values is uniformly more powerful than the weighted alternative Holm procedure (WAP) based on ordered raw p-values, with stronger optimality properties under FWER control.
citing papers explorer
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In-Sample Evaluation of Subgroups Identified by Generic Machine Learning
A conditional adaptive perturbation approach enables valid in-sample inference for machine learning-identified subgroups with nonregular boundaries via triple robustness.
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PRADAS: PRior-Assisted DAta Splitting for False Discovery Rate Control
PRADAS derives a Bayes-optimal mirror statistic for any splitting scheme, establishes asymptotic FDR control under weak dependence, and optimizes the split ratio as a stopping time to improve power over standard equal-split methods.
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Weighted Holm Procedures: Theory, Properties, and Recommendations
The weighted Holm procedure (WHP) based on ordered weighted p-values is uniformly more powerful than the weighted alternative Holm procedure (WAP) based on ordered raw p-values, with stronger optimality properties under FWER control.