Regression Methods: Spline Smoothing

This lecture covers regression methods focusing on spline smoothing, discussing the balance between fidelity to the data and smoothness. It explains the penalised sum of squares, natural cubic splines, roughness penalties, and the choice of smoothing parameters. The lecture also delves into penalised fitting, mixed models, and equivalent degrees of freedom in spline estimation.