On the distribution, model selection properties and uniqueness of the Lasso estimator in low and high dimensions

DOI10.1214/20-EJS1687zbMath1440.62060arXiv1708.09608MaRDI QIDQ2180053

Ulrike Schneider, Karl Ewald

Publication date: 13 May 2020

Published in: Electronic Journal of Statistics (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1708.09608

zbMATH Keywords

uniquenessmodel selectionleast-squares estimatorlinear regressionshrinkageLasso estimator

Mathematics Subject Classification ID

Ridge regression; shrinkage estimators (Lasso) (62J07) Linear regression; mixed models (62J05) Exact distribution theory in statistics (62E15)

Related Items (5)

Sparse Bayesian inference with regularized Gaussian distributions ^* ⋮ The Geometry of Sparse Analysis Regularization ⋮ The generalized Lasso problem and uniqueness ⋮ Simple expressions of the LASSO and SLOPE estimators in low-dimension ⋮ Visualization and assessment of model selection uncertainty

Cites Work

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• The LASSO estimator: Distributional properties
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• Gap Safe screening rules for sparsity enforcing penalties
• Safe Feature Elimination in Sparse Supervised Learning
• Monte Carlo Simulation for Lasso-Type Problems by Estimator Augmentation
• Strong Rules for Discarding Predictors in Lasso-Type Problems

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