A faster U-statistic for testing independence in the functional linear models

Zhao, Fanrong; Lin, Nan; Hu, Wenjuan; Zhang, Baoxue

doi:10.1016/j.jspi.2021.08.002

Journal of Statistical Planning and Inference

2022

DOI: 10.1016/j.jspi.2021.08.002

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A faster U-statistic for testing independence in the functional linear models

Fanrong Zhao

Nan Lin

Wenjuan Hu

et al.

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2024

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A U-Statistic for Testing the Lack of Dependence in Functional Partially Linear Regression Model

Zhao,

Zhang

2024

Mathematics

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The functional partially linear regression model comprises a functional linear part and a non-parametric part. Testing the linear relationship between the response and the functional predictor is of fundamental importance. In cases where functional data cannot be approximated with a few principal components, we develop a second-order U-statistic using a pseudo-estimate for the unknown non-parametric component. Under some regularity conditions, the asymptotic normality of the proposed test statistic is established using the martingale central limit theorem. The proposed test is evaluated for finite sample properties through simulation studies and its application to real data.

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A U-Statistic for Testing the Lack of Dependence in Functional Partially Linear Regression Model

Zhao,

Zhang

2024

Mathematics

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A faster U-statistic for testing independence in the functional linear models

Cited by 1 publication

References 17 publications

A U-Statistic for Testing the Lack of Dependence in Functional Partially Linear Regression Model

A U-Statistic for Testing the Lack of Dependence in Functional Partially Linear Regression Model

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