Semi-functional partial linear regression with measurement error: an approach based on kNN estimation

Silvia Novo (), Germán Aneiros and Philippe Vieu
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Silvia Novo: Universidad Carlos III de Madrid
Germán Aneiros: Universidade da Coruña
Philippe Vieu: Université Paul Sabatier

TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, 2025, vol. 34, issue 1, No 9, 235-261

Abstract: Abstract This paper focuses on a semi-parametric regression model in which the response variable is explained by the sum of two components. One of them is parametric (linear), the corresponding explanatory variable is measured with additive error and its dimension is finite (p). The other component models, in a nonparametric way, the effect of a functional variable (infinite dimension) on the response. kNN-based estimators are proposed for each component, and some asymptotic results are obtained. A simulation study illustrates the behaviour of such estimators for finite sample sizes, while an application to real data shows the usefulness of our proposal.

Keywords: Errors-in-variables; Functional data; Semi-functional regression; Partially linear models; kNN estimation (search for similar items in EconPapers)
Date: 2025
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DOI: 10.1007/s11749-024-00957-3

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