Strong consistency of Lasso estimators

DOI10.1007/S13171-011-0006-0zbMath1395.62208OpenAlexW1986756847MaRDI QIDQ354203

Arindam Chatterjee, Soumendra Nath Lahiri

Publication date: 18 July 2013

Published in: Sankhyā. Series A (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s13171-011-0006-0

zbMATH Keywords

convergence ratesstrong lawpenalized regression

Mathematics Subject Classification ID

Ridge regression; shrinkage estimators (Lasso) (62J07) Asymptotic distribution theory in statistics (62E20) Strong limit theorems (60F15)

Related Items (5)

Random weighting in LASSO regression ⋮ Rates of convergence of the adaptive LASSO estimators to the oracle distribution and higher order refinements by the bootstrap ⋮ On the residual empirical process based on the ALASSO in high dimensions and its functional oracle property ⋮ Leave-one-out cross-validation is risk consistent for Lasso ⋮ Simulation-based Value-at-Risk for nonlinear portfolios

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• Weak and strong consistency of the least squares estimators in regression models
• Strong consistency of least squares estimates in multiple regression
• Measure Theory and Probability Theory
• Linear Statistical Inference and its Applications

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