Shepard’s and Hardy’s Multiquadric (and Reciprocal Multiquadric) Methods for the Trivariate Case

Lecture 8: In this lecture, professor Hamann covers gradient estimation based on local least squares approximation as well as efficiency via localization and spatial data structures (k-nearest-neighbors method and octress). He also goes into a detailed discussion of Project 2 - Scattered Data Interpolation Based on Shepard’s and Hardy’s Methods.