Optimum robust estimation of linear aspects in conditionally contaminated linear models

DOI10.1214/aos/1176348525zbMath0792.62024OpenAlexW1971988372MaRDI QIDQ1192974

Viktor Kurotschka, Christine H. Müller

Publication date: 27 September 1992

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

Full work available at URL: https://doi.org/10.1214/aos/1176348525

zbMATH Keywords

parametrizationcharacterizationsrobust estimationasymptotic covariance matrixasymptotically linear estimatorsquadratic regressionminimum tracebias boundconditionally contaminated general linear modelsHampel-Krasker estimatorslinear aspectsminimum asymptotic bias

Mathematics Subject Classification ID

Density estimation (62G07) Nonparametric robustness (62G35) Linear regression; mixed models (62J05) Design of statistical experiments (62K99) Point estimation (62F10) Robustness and adaptive procedures (parametric inference) (62F35)

Related Items (6)

Optimal designs for robust estimation in conditionally contaminated linear models ⋮ Optimal bounded influence regression and scale m-estimators in the context of experimental desing ⋮ A generalized class of shrinkage estimators in linear regression when disturbances are not normal ⋮ Robust Linear Calibration ⋮ Optimum robust testing in linear models ⋮ Bounded influence estimation for regression and scale

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