S. Novo Díaz, G. Aneiros, P. Vieu
This work explores a semiparametric regression model where the response variable is expressed as the sum of two components. The first is a parametric (linear) term associated with a finite-dimensional (p) explanatory variable, which is subject to additive measurement error. The second component captures the effect of a functional (infinite-dimensional) variable on the response in a nonparametric manner. To estimate each component, we propose k-NN-based estimators and derive some asymptotic properties. A simulation study evaluates their performance in finite sample settings, while an application to real data demonstrates the practical relevance of our approach.
Palabras clave: errors-in-variables, functional data, semi-functional regression, partially linear models
Programado
Estimación no paramétrica
12 de junio de 2025 19:00
Sala de prensa (MR 13)