New robust ridge-type estimators for beta regression under multicollinearity and outliers with application to breast cancer data

The beta regression model (BRM) is a widely applied modeling approach for data bounded within the open interval (0, 1), and it is extensively used in fields such as chemistry, environmental science, medicine, and biology. Parameter estimation in these models is conventionally performed using the max...

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Autors principals:	Ali T. Hammad, I. Elbatal, Ohud A. Alqasem, Ehab M. Almetwally, Amin M. A. Haleeb, Abdirashid M. Yousuf, M. M. Abd El-Raouf, Ahmed M. Gemeay
Format:	Artigo
Idioma:	Inglês
Publicat:	Taylor & Francis Group 2025-12-01
Col·lecció:	Applied Mathematics in Science and Engineering
Matèries:	Beta regression model biased estimator outliers multicollinearity robust estimator SMLE
Accés en línia:	https://www.tandfonline.com/doi/10.1080/27690911.2025.2590432
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