Quantile based estimation of biasing parameters in ridge regression model

DOI10.1080/03610918.2018.1530782zbMath1489.62217OpenAlexW2911659915WikidataQ128476455 ScholiaQ128476455MaRDI QIDQ5083892

Muhammad Suhail, B. M. Golam Kibria, Sohail Chand

Publication date: 21 June 2022

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

Full work available at URL: https://doi.org/10.1080/03610918.2018.1530782

zbMATH Keywords

ridge regressionsimulation studyMSEmulticollinearity

Mathematics Subject Classification ID

Ridge regression; shrinkage estimators (Lasso) (62J07)

Related Items

Quantile-based robust ridge m-estimator for linear regression model in presence of multicollinearity and outliers, New robust ridge estimators for the linear regression model with outliers, Robust correlation scaled principal component regression, New quantile based ridge M-estimator for linear regression models with multicollinearity and outliers

Cites Work

• A Simulation Study of Some Ridge Estimators
• Ridge regression:some simulations
• A Monte Carlo Evaluation of Some Ridge-Type Estimators
• A simulation study of ridge and other regression estimators
• A Class of Biased Estimators in Linear Regression
• A Simulation Study of Alternatives to Ordinary Least Squares
• Choosing Ridge Parameter for Regression Problems
• Performance of Some New Ridge Regression Estimators
• Modified Ridge Regression Estimators
• Ridge Regression: Biased Estimation for Nonorthogonal Problems