A smoothing principle for the Huber and other location \(M\)-estimators

DOI10.1016/j.csda.2010.05.001zbMath1247.62058OpenAlexW2064301386WikidataQ60471573 ScholiaQ60471573MaRDI QIDQ452579

Frank Hampel, Elvezio Ronchetti, Christian Hennig

Publication date: 15 September 2012

Published in: Computational Statistics and Data Analysis (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.csda.2010.05.001

zbMATH Keywords

medianMADbreakdown pointrobust estimationCauchy distributiondouble exponential distributionHuber's least favourable distributionML-estimatorPitman estimatorsmall sample asymptotics

Mathematics Subject Classification ID

Point estimation (62F10) Exact distribution theory in statistics (62E15) Robustness and adaptive procedures (parametric inference) (62F35)

Related Items

Robust estimation for survival partially linear single-index models, \(M\)-type penalized splines with auxiliary scale estimation, M-estimator based unit root tests in the ESTAR framework, Unnamed Item, Renewable Huber estimation method for streaming datasets, Higher-Order Infinitesimal Robustness, Consistency of the elastic net under a finite second moment assumption on the noise, Empirical likelihood-based inference for the difference of two location parameters using smoothed M-estimators, Unnamed Item, Penalized unimodal spline density estimation with application to \(M\)-estimation, The Extent of Gross Errors Eliminated by Robust Multiple Linear Regressions

Uses Software

• robustbase

Cites Work

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