Finite algorithms for robust linear regression

DOI10.1007/BF01933216zbMath0717.65118MaRDI QIDQ2638753

Kaj Madsen, Hans Bruun Nielsen

Publication date: 1990

Published in: BIT (Search for Journal in Brave)

zbMATH Keywords

algorithmsNewton's methodtest problemsrobust regressionsimulation experimentsHuber estimatorcomputing timenumber of iterationslinear estimation problemrank deficient problems

Mathematics Subject Classification ID

Numerical smoothing, curve fitting (65D10) Linear regression; mixed models (62J05) Numerical solutions to overdetermined systems, pseudoinverses (65F20) Probabilistic methods, stochastic differential equations (65C99)

Related Items (12)

New characterizations of \(\ell_ 1\) solutions to overdetermined systems of linear equations ⋮ Piecewise-linear pathways to the optimal solution set in linear programming ⋮ Duality in robust linear regression using Huber's \(M\)-estimator ⋮ A penalty continuation method for the \(\ell_\infty\) solution of overdetermined linear systems ⋮ A global piecewise smooth Newton method for fast large-scale model predictive control ⋮ Linear M-estimation with bounded variables ⋮ Iteratively reweighted least squares: A comparison of several single step algorithms for linear models ⋮ Computation of Huber's \(M\)-estimates for a block-angular regression problem ⋮ On the characterization of quadratic splines ⋮ On Newton's method for Huber's robust M-estimation problems in linear regression ⋮ Newton's method for linear inequality systems ⋮ Recursive Finite Newton Algorithm for Support Vector Regression in the Primal

Cites Work

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• A new algorithm for the Huber estimator in linear models
• The Mathematical Structure of Huber’s M-Estimator
• Finite Algorithms for Huber’sM-Estimator
• An extended set of FORTRAN basic linear algebra subprograms
• Numerical solution of robust regression problems: computational aspects, a comparison
• Numerical Methods for Robust Regression: Linear Models
• Robust Estimation of a Location Parameter
• Robust Statistics

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