Outlier detection by means of robust regression estimators for use in engineering science

DOI10.1631/jzus.A0820140zbMath1178.62015OpenAlexW2066564327MaRDI QIDQ1048353

R. Cuneyt Erenoglu, Serif Hekimoglu, Jan Kalina

Publication date: 11 January 2010

Published in: Journal of Zhejiang University. Science A (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1631/jzus.a0820140

zbMATH Keywords

least trimmed squares (LTS)leverage pointleast median of squares (LMS)mean success rate (MSR)

Mathematics Subject Classification ID

Linear regression; mixed models (62J05) Point estimation (62F10) Robustness and adaptive procedures (parametric inference) (62F35) Monte Carlo methods (65C05) Diagnostics, and linear inference and regression (62J20)

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Cites Work

• Breakdown points of affine equivariant estimators of multivariate location and covariance matrices
• Aspects of robust linear regression
• A note on Tyler's modification of the MAD for the Stahel-Donoho estimator
• Effect of heteroscedasticity and heterogeneousness on outlier detection for geodetic networks
• Breakdown and groups. (With discussions and rejoinder)
• Least Median of Squares Regression
• Robust regression using repeated medians
• Computing the Exact Least Median of Squares Estimate and Stability Diagnostics in Multiple Linear Regression
• Estimates of the Regression Coefficient Based on Kendall's Tau
• A General Qualitative Definition of Robustness
• Robust Statistics
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