Reweighted LS estimators converge at the same rate as the initial estimator
From MaRDI portal
Publication:1208670
DOI10.1214/aos/1176348910zbMath0764.62043OpenAlexW2079692321WikidataQ30052982 ScholiaQ30052982MaRDI QIDQ1208670
Publication date: 16 May 1993
Published in: The Annals of Statistics (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1214/aos/1176348910
asymptotic equivalencehigh efficiencyregression estimatorsleast median of squares estimatorhigh breakdown propertiesreweighted least squares estimator
Density estimation (62G07) Asymptotic properties of nonparametric inference (62G20) Nonparametric robustness (62G35) Linear regression; mixed models (62J05)
Related Items
An entropy-like estimator for robust parameter identification, Reweighting approximate GM estimators: Asymptotics and residual-based graphics, Reweighted least trimmed squares: an alternative to one-step estimators, Efficient Robust Regression via Two-Stage Generalized Empirical Likelihood, A one-step robust estimator for regression based on the weighted likelihood reweighting scheme, A comparative study of some robust methods for coefficient-estimation in linear regression, Implicitly weighted methods in robust image analysis, Semiparametrically weighted robust estimation of regression models, Robust regression with high coverage., High breakdown estimation for multiple populations with applications to discriminant analysis, Using Wald-type estimator to combat outliers and Berkson-type uncertainties with mixture distributions in linear regression models, Trimming and likelihood: Robust location and dispersion estimation in the elliptical model, Two simple resistant regression estimators, A procedure for robust fitting in nonlinear regression, Asymptotic Theory of Outlier Detection Algorithms for Linear Time Series Regression Models, Outlier detection and robust estimation in linear regression models with fixed group effects, Asymptotics of reweighted estimators of multivariate location and scatter, Some results for robust GM-based estimators in heteroscedastic regression models, A class of robust and fully efficient regression estimators, A journey in single steps: robust one-step \(M\)-estimation in linear regression, On the asymptotic behavior of one-step estimates in heteroscedastic regression models.
