LAD regression for detecting outliers in response and explanatory variables

DOI10.1006/jmva.1997.1666zbMath0877.62067OpenAlexW2067482206MaRDI QIDQ1364673

Yadolah Dodge

Publication date: 14 December 1997

Published in: Journal of Multivariate Analysis (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1006/jmva.1997.1666

zbMATH Keywords

outliersrobust regressionleverage pointsinverse least absolute deviations regressionleast absolute deviations regression

Mathematics Subject Classification ID

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

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Cites Work

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• A bootstrap approach to hypothesis testing in least absolute value regression
• A note on hypothesis testing in LAV multiple regression: A small sample comparison
• Data. A collection of problems from many fields for the student and research worker
• The Gaussian hare and the Laplacian tortoise: computability of squared-error versus absolute-error estimators. With comments by Ronald A. Thisted and M. R. Osborne and a rejoinder by the authors
• Linear Curve Fitting Using Least Deviations
• Tests of linear hypotheses based on regression rank scores
• Tests of Linear Hypotheses and l"1 Estimation
• Leverage and Breakdown in L 1 Regression
• Two Robust Alternatives to Least-Squares Regression
• An Improved Algorithm for Discrete $l_1 $ Linear Approximation

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