Nonparametric regression

Regression methods that do not assume a predetermined functional form for the relationship between the response and predictors. Examples include kernel regression, local polynomial (LOESS) smoothing, and spline methods. Nonparametric regression is flexible and data-driven but typically requires larger samples than parametric alternatives.