Kriging-based interpolatory subdivision schemes
Résumé
This paper is devoted to the definition, analysis and implementation of a new type of subdivision schemes adapted to data (through a stochastic approach) and to a partition of their support. Its construction combines position-dependent multiscale approximation ([7]) and the Kriging method ([12]). After a full convergence analysis that requires to extend classical results to this new framework, it is applied to data prediction for uni and bi-variate problems and compared to the Lagrange interpolatory subdivision.
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