Functional stability of one-step GM-estimators in approximately linear regression

DOI10.1214/aos/1024691092zbMath0930.62030OpenAlexW1970069248MaRDI QIDQ1807106

Douglas G. Simpson, Víctor J. Yohai

Publication date: 9 November 1999

Published in: The Annals of Statistics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1214/aos/1024691092

zbMATH Keywords

robust statisticsweighted least squaresmaximum bias functionbreak-down pointsNewton-Raphson estimators

Mathematics Subject Classification ID

Linear regression; mixed models (62J05) Point estimation (62F10) Robustness and adaptive procedures (parametric inference) (62F35) General nonlinear regression (62J02)

Related Items

Combining locally and globally robust estimates for regression, Robust mixture regression using the \(t\)-distribution, Local and global robustness of regression estimators, Reweighting approximate GM estimators: Asymptotics and residual-based graphics, High-breakdown robust multivariate methods, Uniform asymptotics for S- and MM-regression estimators, Longitudinal data analysis using \(t\)-type regression., Improving bias-robustness of regression estimates through projections, A review of robust regression and diagnostic procedures in linear regression, Functional stability of one-step GM-estimators in approximately linear regression, Asymptotic behavior for S-estimators in random design linear model with long-range-dependent errors, Robust regression with both continuous and categorical predictors, Maximum bias curves for robust regression with non-elliptical regressors, A class of robust and fully efficient regression estimators

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