# Efficient Multiple Testing Adjustment for Hierarchical Inference

@inproceedings{Renaux2021EfficientMT, title={Efficient Multiple Testing Adjustment for Hierarchical Inference}, author={Claude Renaux and Peter Buhlmann}, year={2021} }

Hierarchical inference in (generalized) regression problems is powerful for finding significant groups or even single covariates, especially in high-dimensional settings where identifiability of the entire regression parameter vector may be ill-posed. The general method proceeds in a fully data-driven and adaptive way from large to small groups or singletons of covariates, depending on the signal strength and the correlation structure of the design matrix. We propose a novel hierarchical…

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