Estimation and Hypothesis Test for Mean Curve with Functional Data by Reproducing Kernel Hilbert Space Methods, with Applications in Biostatistics

Autor:	Ming Xiong, Ao Yuan, Hong-Bin Fang, Colin O. Wu, Ming T. Tan
Jazyk:	angličtina
Rok vydání:	2022
Předmět:	functional data hypothesis testing kernel function mean curve estimation reproducing kernel Hilbert space Mathematics QA1-939
Zdroj:	Mathematics, Vol 10, Iss 23, p 4549 (2022)
Druh dokumentu:	article
ISSN:	2227-7390
DOI:	10.3390/math10234549
Popis:	Functional data analysis has important applications in biomedical, health studies and other areas. In this paper, we develop a general framework for a mean curve estimation for functional data using a reproducing kernel Hilbert space (RKHS) and derive its asymptotic distribution theory. We also propose two statistics for testing the equality of mean curves from two populations and a mean curve belonging to some subspace, respectively. Simulation studies are conducted to evaluate the performance of the proposed method and are compared with the major existing methods, which shows that the proposed method has a better performance than the existing ones. The method is then illustrated with an analysis of the growth data from the National Growth and Health Study (NGHS) project sponsored by the NIH.
Databáze:	Directory of Open Access Journals
Externí odkaz:	https://doaj.org/article/5c3c36dd30634a6b9935cd5d3936b8a1 Zobrazit plný text záznamu View record in DOAJ Plný text ve formátu PDF Plný text ve formátu HTML
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