Kriging Riemannian Data via Random Domain Decompositions
Kriging Riemannian Data via Random Domain Decompositions
Data taking value on a Riemannian manifold and observed over a complex spatial domain are becoming more frequent in applications, for example, in environmental sciences and in geoscience. The analysis of these data needs to rely on local models to account for the nonstationarity of the generating random process, the …