Robust Regression Computation Using Iteratively Reweighted Least Squares

DOI10.1137/0611032zbMath0704.65027OpenAlexW1993803475MaRDI QIDQ3484265

Dianne P. O'Leary

Publication date: 1990

Published in: SIAM Journal on Matrix Analysis and Applications (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1137/0611032

zbMATH Keywords

linear systemNewton's methodestimateslinear modelsparse matricesill-posed problemrobust regressionperformancesresidual vectorsiteratively reweighted least squares criterionsolution vectors

Mathematics Subject Classification ID

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

Related Items (7)

Nonlinear Complex-Valued Extensions of Hebbian Learning: An Essay ⋮ Robust regression for mixed Poisson-Gaussian model ⋮ 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 ⋮ Weiszfeld's method: old and new results ⋮ Fast robust regression algorithms for problems with Toeplitz structure ⋮ Symbiosis between linear algebra and optimization

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