Two simple resistant regression estimators

DOI10.1016/j.csda.2004.06.005zbMath1429.62108OpenAlexW2124493177MaRDI QIDQ957245

David J. Olive

Publication date: 26 November 2008

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

Full work available at URL: https://opensiuc.lib.siu.edu/cgi/viewcontent.cgi?article=1011&context=math_articles

zbMATH Keywords

outliersrobust regressiondiagnostics

Mathematics Subject Classification ID

Linear regression; mixed models (62J05) Robustness and adaptive procedures (parametric inference) (62F35) Diagnostics, and linear inference and regression (62J20)

Related Items (3)

Robust Regression Using Data Partitioning and M-Estimation ⋮ Cluster-based multivariate outlier identification and re-weighted regression in linear models ⋮ Nonparametric and robust methods. (Editorial)

Cites Work

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• A local breakdown property of robust tests in linear regression
• Reweighted LS estimators converge at the same rate as the initial estimator
• Aspects of robust linear regression
• A comparison of some quick algorithms for robust regression
• On a General Concept of "In Probability"
• Least Median of Squares Regression
• Inconsistency of Resampling Algorithms for High-Breakdown Regression Estimators and a New Algorithm
• Some quantitative relationships between two types of finite sample breakdown point

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