Average ordinary least squares<scp>‐centered</scp> penalized regression: A more efficient way to address multicollinearity than ridge regression

DOI10.1111/stan.12263zbMath1527.62054OpenAlexW4207004168MaRDI QIDQ6089391

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Publication date: 14 December 2023

Published in: Statistica Neerlandica (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1111/stan.12263

zbMATH Keywords

ridge regressionmulticollinearityaverage OLS-centered penalized regressionshrinkage center

Mathematics Subject Classification ID

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

Cites Work

• The Adaptive Lasso and Its Oracle Properties
• Asymptotic optimality of \(C_ L\) and generalized cross-validation in ridge regression with application to spline smoothing
• A Simulation Study of Some Ridge Regression Estimators under Different Distributional Assumptions
• Sparsity and Smoothness Via the Fused Lasso
• A Simulation Study of Some Biasing Parameters for the Ridge Type Estimation of Poisson Regression
• Regularization and Variable Selection Via the Elastic Net
• Ridge Regression: Biased Estimation for Nonorthogonal Problems
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