Adaptive Penalized Regression for High-Efficiency Estimation in Correlated Predictor Settings: A Data-Driven Shrinkage Approach

Penalized regression estimators have become widely adopted alternatives to ordinary least squares while analyzing collinear data, despite introducing some bias. However, existing penalized methods lack universal superiority across diverse data conditions. To address this limitation, we propose a nov...

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Autors principals:	Muhammad Shakir Khan, Amirah Saeed Alharthi
Format:	Artigo
Idioma:	Inglês
Publicat:	MDPI AG 2025-09-01
Col·lecció:	Mathematics
Matèries:	mean squared error Monte Carlo simulation multicollinearity ordinary least squared ridge regression
Accés en línia:	https://www.mdpi.com/2227-7390/13/17/2884
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