Regression spline

A regression spline fits a regression function in a finite-dimensional spline approximation space with selected knots. Evaluating its basis at predictor values gives a design matrix, reducing fitting to regression on basis coefficients.

A penalized regression spline estimates basis coefficients by minimizing a residual or likelihood criterion plus a curvature penalty. Basis size limits the available complexity; the penalty controls how much of that complexity is used.