Rank-Based Test for Partial Functional Linear Regression Models

XIE Tianfa · CAO Ruiyuan · YU Ping

系统科学与复杂性(英文) ›› 2020, Vol. 33 ›› Issue (5) : 1571-1584.

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PDF(217 KB)
系统科学与复杂性(英文) ›› 2020, Vol. 33 ›› Issue (5) : 1571-1584. DOI: 10.1007/s11424-020-8362-2

Rank-Based Test for Partial Functional Linear Regression Models

    XIE Tianfa · CAO Ruiyuan · YU Ping
作者信息 +

Rank-Based Test for Partial Functional Linear Regression Models

    XIE Tianfa · CAO Ruiyuan · YU Ping
Author information +
文章历史 +

Abstract

This paper investigates the hypothesis test of the parametric component in partial functional linear regression models. Based on a rank score function, the authors develop a rank test using functional principal component analysis, and establish the asymptotic properties of the resulting test under null and local alternative hypotheses. A simulation study shows that the proposed test procedure has good size and power with finite sample sizes. The authors also present an illustration through fitting the Berkeley Growth Data and testing the effect of gender on the height of kids.

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XIE Tianfa · CAO Ruiyuan · YU Ping. Rank-Based Test for Partial Functional Linear Regression Models. 系统科学与复杂性(英文), 2020, 33(5): 1571-1584 https://doi.org/10.1007/s11424-020-8362-2
XIE Tianfa · CAO Ruiyuan · YU Ping. Rank-Based Test for Partial Functional Linear Regression Models. Journal of Systems Science and Complexity, 2020, 33(5): 1571-1584 https://doi.org/10.1007/s11424-020-8362-2
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