A modified ridge m-estimator for linear regression model with multicollinearity and outliers

DOI10.1080/03610918.2017.1310231OpenAlexW2599878605MaRDI QIDQ5084787

Hasan Ertaş

Publication date: 28 June 2022

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

Full work available at URL: https://doi.org/10.1080/03610918.2017.1310231

zbMATH Keywords

outliersmulticollinearityrobust estimatorbiased estimator

Mathematics Subject Classification ID

Ridge regression; shrinkage estimators (Lasso) (62J07) Linear regression; mixed models (62J05)

Related Items (4)

Quantile-based robust ridge m-estimator for linear regression model in presence of multicollinearity and outliers ⋮ Modified robust ridge M-estimators for linear regression models: an application to tobacco data ⋮ New robust ridge estimators for the linear regression model with outliers ⋮ New quantile based ridge M-estimator for linear regression models with multicollinearity and outliers

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• Mean Square Error Comparisons of the Alternative Estimators For The Distributed Lag Models
• A Simulation Study of Some Ridge Estimators
• ROBUST RIDGE REGRESSION BASED ON AN M-ESTIMATOR
• A Monte Carlo Evaluation of Some Ridge-Type Estimators
• Good ridge estimators based on prior information
• Performance of Some New Ridge Regression Estimators
• Ridge Regression: Biased Estimation for Nonorthogonal Problems
• Robust Statistics

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