Robust Kernel Smoothing of 3D Point Spatial Data

This contains classical and robust versions of kernel regression and local linear regression with optimal and heuristic bandwidth design.

This archive contains classical and robust versions of both kernel regression and local linear regression with optimal and heuristic bandwidth selection. Robust nonparametric smoothers have been proved effective to preserve edges in image denoising. As an extension, they are capable to estimate multivariate surfaces containing discontinuities on the basis of a random spatial sampling. A crucial problem is the design of their coefficients, in particular those of the kernels which concern robustness and allow jump preserving.