A method for variable selection in a multivariate functional linear regression model

2023/11/01 by Alban Mina Mbina, Mbina, Alban Mina, Guy Martial Nkiet +1
Chemistry · Decision Sciences · #Analytical Chemistry and Chromatography #FOS: Mathematics #Optimal Experimental Design Methods #Spectroscopy and Chemometric Analyses #Statistics Theory (math.ST)

paper · pdf · doi:10.48550/arxiv.2311.00803

openalex publication_date 2023/11/01 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28

Abstract

We propose a new variable selection procedure for a functional linear model with multiple scalar responses and multiple functional predictors. This method is based on basis expansions of the involved functional predictors and coefficients that lead to a multivariate linear regression model. Then a criterion by means of which the variable selection problem reduces to that of estimating a suitable set is introduced. Estimation of this set is achieved by using appropriate penalizations of estimates of this criterion, so leading to our proposal. A simulation study that permits to investigate the effectiveness of the proposed approach and to compare it with existing methods is given.

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