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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Principais autores:	Muhammad Shakir Khan, Amirah Saeed Alharthi
Format:	Artigo
Jezik:	Inglês
Izdano:	MDPI AG 2025-09-01
Serija:	Mathematics
Teme:	mean squared error Monte Carlo simulation multicollinearity ordinary least squared ridge regression
Online dostop:	https://www.mdpi.com/2227-7390/13/17/2884
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