A Scalable Hierarchical Lasso for Gene–Environment Interactions

DOI10.1080/10618600.2022.2039161OpenAlexW3136099372MaRDI QIDQ5057242

W. James Gauderman, Juan Pablo Lewinger, Natalia Zemlianskaia

Publication date: 16 December 2022

Published in: Journal of Computational and Graphical Statistics (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/2103.13510

zbMATH Keywords

hierarchical variable selectionjoint analysisscreening rules

Mathematics Subject Classification ID

Statistics (62-XX)

Related Items (1)

gesso

Uses Software

• R
• glmnet
• hierNet

Cites Work

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• A lasso for hierarchical interactions
• The composite absolute penalties family for grouped and hierarchical variable selection
• Pathwise coordinate optimization
• Interaction
• Dynamic Screening: Accelerating First-Order Algorithms for the Lasso and Group-Lasso
• Bayesian variable selection with related predictors
• Safe Feature Elimination in Sparse Supervised Learning
• Structured gene‐environment interaction analysis
• Identification of biomarker‐by‐treatment interactions in randomized clinical trials with survival outcomes and high‐dimensional spaces
• Regularization and Variable Selection Via the Elastic Net
• Convergence of a block coordinate descent method for nondifferentiable minimization

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