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Variable selection in functional regression models: A review
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NSTL
Elsevier
Despite of various similar features, Functional Data Analysis and High-Dimensional Data Analysis are two major fields in Statistics that grew up recently almost independently one from each other. The aim of this paper is to propose a survey on methodological advances for variable selection in functional regression, which is typically a question for which both functional and multivariate ideas are crossing. More than a simple survey, this paper aims to promote even more new links between both areas. (C) 2021 Elsevier Inc. All rights reserved.
Functional Data AnalysisRegressionVariable selectionNONCONCAVE PENALIZED LIKELIHOODSHRINKAGE ESTIMATIONDIMENSION REDUCTIONLINEAR-MODELLASSO
NSTL
Elsevier
