Multivariate functional group sparse regression: functional predictor selection
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Publication:6372032
arXiv2107.02146MaRDI QIDQ6372032
Author name not available (Why is that?)
Publication date: 5 July 2021
Abstract: In this paper, we propose methods for functional predictor selection and the estimation of smooth functional coefficients simultaneously in a scalar-on-function regression problem under high-dimensional multivariate functional data setting. In particular, we develop two methods for functional group-sparse regression under a generic Hilbert space of infinite dimension. We show the convergence of algorithms and the consistency of the estimation and the selection (oracle property) under infinite-dimensional Hilbert spaces. Simulation studies show the effectiveness of the methods in both the selection and the estimation of functional coefficients. The applications to the functional magnetic resonance imaging (fMRI) reveal the regions of the human brain related to ADHD and IQ.
Has companion code repository: https://github.com/Ali-Mahzarnia/222
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