Semi-functional partial linear regression with measurement error: An approach based on kNN estimation. Articles uri icon

published in

publication date

  • March 2025

start page

  • 235

end page

  • 261

volume

  • 34

International Standard Serial Number (ISSN)

  • 1133-0686

Electronic International Standard Serial Number (EISSN)

  • 1863-8260

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.

subjects

  • Statistics

keywords

  • errors-in-variables; functional data; semi-functional regression; partially linear models; knn estimation