
Accession Number : ADA134544
Title : Projection Pursuit Regression: Some Mathematics.
Descriptive Note : Technical rept.,
Corporate Author : STANFORD UNIV CA DEPT OF STATISTICS
Personal Author(s) : Diaconis,Persi ; Shahshahani,Mehrdad
PDF Url : ADA134544
Report Date : 07 Apr 1983
Pagination or Media Count : 34
Abstract : 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 nonlinear 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.
Descriptors : *Algorithms, *Approximation(Mathematics), Linear regression analysis, Problem solving, Curve fitting, Nonparametric statistics, Theorems
Subject Categories : Statistics and Probability
Distribution Statement : APPROVED FOR PUBLIC RELEASE