A new approach to linear regression with multivariate splines

作者：de Visser C C^*; Chu Q P; Mulder J A

来源：Automatica, 2009, 45(12): 2903-2909.

DOI：10.1016/j.automatica.2009.09.017

• Splines
• Parameter estimation
• Scattered data
• Function approximation
• Estimators

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.

• 出版日期2009-12