A Re-Weighted Least Squares Method for Robust Regression Estimation

DOI10.1080/01966324.2006.10737673zbMath1244.62024OpenAlexW1966498198WikidataQ58117250 ScholiaQ58117250MaRDI QIDQ2903217

Nedret Billor, Ali S. Hadi, Samprit Chatterjee

Publication date: 7 August 2012

Published in: American Journal of Mathematical and Management Sciences (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/01966324.2006.10737673

Mathematics Subject Classification ID

Point estimation (62F10) Linear inference, regression (62J99) Robustness and adaptive procedures (parametric inference) (62F35)

Related Items (7)

Robust regression analysis: a useful two stage procedure ⋮ Robust cluster-based multivariate outlier diagnostics and parameter estimation in regression analysis ⋮ Cluster-based multivariate outlier identification and re-weighted regression in linear models ⋮ A fast algorithm for robust regression with penalised trimmed squares ⋮ Cluster-based \(L2\) re-weighted regression ⋮ A Genetic Algorithm Based Modification on the LTS Algorithm for Large Data Sets ⋮ A performance counterexample of Billor–Chatterjee–Hadi procedure and an improvement proposal for robust regression

Uses Software

• Stata

Cites Work

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• A new measure of overall potential influence in linear regression
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• Robust regression:a weighted least squares approach
• Inconsistency of Resampling Algorithms for High-Breakdown Regression Estimators and a New Algorithm
• Applied regression analysis bibliography update 1992–93
• Robust Statistics

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