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What is Variable Selection in Functional Regression about?

This paper reviews methodological advances in variable selection for functional regression models, highlighting the intersection of Functional Data Analysis (FDA) and High-Dimensional Data Analysis (HDS). It discusses the challenges of infinite-dimensional functional objects and the need for effective variable selection techniques, focusing on both finite-dimensional regression methods and their adaptations for functional settings. The review aims to foster collaboration between FDA and HDS, presenting vari

Author

Manuel Castro

Language

EN