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SEMMS with Random Effects: A Mixed-Model Extension for Variable Selection in Clustered and Longitudinal Data

Fuente: arXiv

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Détails bibliographiques
Auteurs principaux:	Bar, Haim, Wells, Martin T.
Format:	Preprint
Publié:	2026
Sujets:	Computation Methodology
Accès en ligne:	Acceder al recurso
Tags:	Ajouter un tag Pas de tags, Soyez le premier à ajouter un tag!

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