Bolancé Losilla, CatalinaDai, Lei2024-09-132024-09-132024https://hdl.handle.net/2445/215131Treballs Finals del Màster de Ciències Actuarials i Financeres, Facultat d'Economia i Empresa, Universitat de Barcelona, Curs: 2023-2024, Tutoria: Catalina Bolancé LosillaThis work explores the utilization of double cross-validation methods for determining the optimal bandwidth in kernel regression using single index-models. Kernel regression is a non-parametric technique widely employed in various fields, particularly in smoothing noisy data. The bandwidth parameter plays a crucial role in kernel regression, controlling the smoothness of the estimated function. Selecting an appropriate bandwidth is essential for achieving accurate and robust model performance. Traditional approaches to band- width selection often rely on heuristic methods or fixed rules, which may not be optimal for all datasets (...)38 p.application/pdfengcc-by-nc-nd (c) Dai, 2024http://creativecommons.org/licenses/by-nc-nd/3.0/es/Funcions de KernelAnàlisi de regressióTreballs de fi de màsterKernel functionsRegression analysisMaster's thesisinfo:eu-repo/semantics/masterThesisinfo:eu-repo/semantics/openAccess