A new approach to linear regression with multivariate splines

De Visser, C.C.; Chu, Q.P.; Mulder, J.A.

doi:doi:10.1016/j.automatica.2009.09.017

A new approach to linear regression with multivariate splines

Title

A new approach to linear regression with multivariate splines

Author

De Visser, C.C.
Chu, Q.P.
Mulder, J.A.

Faculty

Aerospace Engineering

Department

Control & Operations

Date

2009-10-07

Abstract

A new methodology for creating highly accurate, static nonlinear maps from scattered, multivariate data is presented. This new methodology uses the B-form polynomials of multivariate simplex splines in a new linear regression scheme. This allows the use of standard parameter estimation techniques for estimating the B-coefficients of the multivariate simplex splines. We present a generalized least squares estimator for the B-coefficients, and show how the estimated B-coefficient variances lead to a new model quality assessment measure in the form of the B-coefficient variance surface. The new modeling methodology is demonstrated on a nonlinear scattered bivariate dataset.

Subject

splines
parameter estimation
scattered data
multivariate splines

To reference this document use:

http://resolver.tudelft.nl/uuid:f2b6bdbd-5d11-4ec5-ac7e-d2c2ce21144c

Publisher

Elsevier

Embargo date

2014-05-01

ISSN

0005-1098

Source

https://doi.org/10.1016/j.automatica.2009.09.017