Functional variable selection via Gram–Schmidt orthogonalization for multiple functional linear regression

DOI10.1080/00949655.2018.1530776OpenAlexW2897615392WikidataQ129160982 ScholiaQ129160982MaRDI QIDQ4960785

Shan-shan Wang, Ruiping Liu, Hui-Wen Wang

Publication date: 23 April 2020

Published in: Journal of Statistical Computation and Simulation (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/00949655.2018.1530776

zbMATH Keywords

Gram-Schmidt orthogonalizationhigh dimensionalityvariable selectionfunctional data

Mathematics Subject Classification ID

Nonparametric estimation (62G05) Linear inference, regression (62J99)

Related Items (1)

Functional classwise principal component analysis: a classification framework for functional data analysis

Uses Software

• fda (R)
• grpreg

Cites Work

• Unnamed Item
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• 10.1162/153244303322753733
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• NONPARAMETRIC REGRESSION ON FUNCTIONAL DATA: INFERENCE AND PRACTICAL ASPECTS

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