Duality in robust linear regression using Huber's \(M\)-estimator

DOI10.1016/S0893-9659(97)00061-XzbMath0884.62073OpenAlexW2043202332MaRDI QIDQ1372307

J. Ning

Publication date: 12 November 1997

Published in: Applied Mathematics Letters (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/s0893-9659(97)00061-x

zbMATH Keywords

robust regressionLagrangean dualityHuber's M-estimator

Mathematics Subject Classification ID

Linear regression; mixed models (62J05) Robustness and adaptive procedures (parametric inference) (62F35) Quadratic programming (90C20)

Related Items (1)

Necessary and Sufficient Conditions for Noiseless Sparse Recovery via Convex Quadratic Splines

Uses Software

• Octave
• LSSOL

Cites Work

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• A new algorithm for the Huber estimator in linear models
• An extension of Karmarkar's projective algorithm for convex quadratic programming
• New characterizations of \(\ell_ 1\) solutions to overdetermined systems of linear equations
• Symmetric indefinite systems for interior point methods
• Robust regression: Asymptotics, conjectures and Monte Carlo
• Finite algorithms for robust linear regression
• The Mathematical Structure of Huber’s M-Estimator
• Inertia-Controlling Methods for General Quadratic Programming
• Finite Algorithms for Huber’sM-Estimator
• Robust regression using iteratively reweighted least-squares
• Numerical Methods for Robust Regression: Linear Models
• The Fitting of Power Series, Meaning Polynomials, Illustrated on Band-Spectroscopic Data
• Robust Statistics

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