Kriging Riemannian Data via Random Domain Decompositions
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DOI: 10.1080/10618600.2020.1853548
Abstract: Abstract 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… read more here.
Keywords: kriging riemannian; riemannian data; local models; random domain ... See more keywords