Enhancing accuracy in modelling highly multicollinear data using alternative shrinkage parameters for ridge regression methods

Abstract In this study, we introduce three new shrinkage parameters for ridge regression, which dynamically adjust the ridge penalty based on the properties of the data, particularly the multicollinearity structure. Using these new parameters, we develop three ridge condition-adjusted estimators (CA...

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Auteurs principaux:	Nadeem Akhtar, Muteb Faraj Alharthi
Format:	Artigo
Langue:	Inglês
Publié:	Nature Portfolio 2025-03-01
Collection:	Scientific Reports
Sujets:	Regression analysis Multicollinearity Shrinkage ridge estimators Mean squared error (MSE) Monte-Carlo simulations
Accès en ligne:	https://doi.org/10.1038/s41598-025-94857-7
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