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Lookup NU author(s): Dr Jian Shi
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© 2021 Institute of Statistical Science. All rights reserved.For functional regression models with functional responses, we propose a nonparametric random-effects model using Gaussian process priors. The proposed model captures the heterogeneity nonlinearly and the covariance structure nonparametrically, enabling longitudinal studies of functional data. The model also has a flexible form of mean structure. We develop a procedure to estimate the unknown parameters and calculate the random effects nonparametrically. The procedure uses a penalized least squares regression and a maximum a posterior estimate, yielding a more accurate prediction. The statistical theory is discussed, including information consistency. Simulation studies and two real-data examples show that the proposed method performs well.
Author(s): Wang Z, Ding H, Chen Z, Shi JQ
Publication type: Article
Publication status: Published
Journal: Statistica Sinica
Online publication date: 01/01/2021
Acceptance date: 02/04/2018
ISSN (electronic): 1017-0405
Publisher: Institute of Statistical Science
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