Projection Pursuit Regression: Some Mathematics

Résumé du livre

We present some mathematical analysis for a class of curve fitting algorithms labeled 'projection pursuit' algorithms. These algorithms approximate a general function of p variables by a sum of non-linear functions of linear combinations. The approximation is computationally feasible and performs well in examples of nonparametric regression with noisy data, high dimensional density estimation, and multidimensional spline approximation. This note treats the algorithms from the point of view of approximation theory. It is easy to show that approximation is always possible.