  In this paper we propose an enhanced version of the residual sub-sampling
method (RSM) in [9] for adaptive interpolation by radial basis functions
(RBFs). More precisely, we introduce in the context of sub-sampling methods a
maximum profile likelihood estimation (MPLE) criterion for the optimal
selection of the RBF shape parameter. This choice is completely automatic,
provides highly reliable and accurate results for any RBFs, and, unlike the
original RSM, guarantees that the RBF interpolant exists uniquely. The efficacy
of this new method, called MPLE-RSM, is tested by numerical experiments on some
1D and 2D benchmark target functions.

Numerical Analysis;Numerical Analysis