Robust Estimation of Multivariate Linear Model Based on Depth Weighted Mean and Scatter

DOI10.1080/03610910902903117zbMath1167.62054OpenAlexW2040726081MaRDI QIDQ3391872

Weihua Zhou

Publication date: 13 August 2009

Published in: Communications in Statistics - Simulation and Computation (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/03610910902903117

zbMATH Keywords

influence functiondepthbreakdown pointrobust estimationmultivariate regressionscatter estimator

Mathematics Subject Classification ID

Estimation in multivariate analysis (62H12) Asymptotic distribution theory in statistics (62E20) Linear regression; mixed models (62J05) Robustness and adaptive procedures (parametric inference) (62F35)

Cites Work

• On a notion of data depth based on random simplices
• Finite sample breakdown points of projection based multivariate location and scatter statistics
• Projection-based depth functions and associated medians
• Depth weighted scatter estimators
• Robustness properties of \(S\)-estimators of multivariate location and shape in high dimension
• General notions of statistical depth function.
• On the Stahel-Donoho estimator and depth-weighted means of multivariate data.
• Influence function and maximum bias of projection depth based estimators.
• The multivariate least-trimmed squares estimator
• Robust estimation for the multivariate linear model based on a \(\tau\)-scale
• Robust regression through robust covariances
• Estimates of Regression Coefficients Based on Lift Rank Covariance Matrix
• Estimates of Regression Coefficients Based on the Sign Covariance Matrix

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