Bivariate Splines for Data Fitting

Ming-Jun Lai
Department of Mathematics
University of Georgia

Abstract: Given a set of scattered data, we would like to find a smooth function to fit the given data. There are several methods available for data fitting such as minimal energy interpolation, discrete least squares method, penalized least squares method. We discuss bivariate splines for data fitting using these methods. Mainly, we discuss the existence, uniqueness, polynomial reproduction, and convergence of these methods. Numerical examples will be included.