Function-on-function quadratic regression models

Yifan Sun and Qihua Wang

Computational Statistics & Data Analysis, 2020, vol. 142, issue C

Abstract: A quadratic regression model where the covariate and the response are both functional is considered, which is a reasonable extension of common function-on-function linear regression models. Methods to estimate the coefficient functions, predict unknown response and test significance of the quadratic term are developed in functional principal component regression paradigm. Asymptotic theories for these approaches are also established. A simulation study is presented to demonstrate the finite sample performances of the proposed methods and an application to real data is used to illustrate the improvement that can be gained by comparing to the function-on-function linear models.

Keywords: Functional data analysis; Quadratic regression; Functional principal component analysis; Test of significance; Asymptotics (search for similar items in EconPapers)
Date: 2020
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Citations: View citations in EconPapers (2)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:csdana:v:142:y:2020:i:c:s0167947319301616

DOI: 10.1016/j.csda.2019.106814

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