A data-driven stochastic model for water wave kinematics is built by combining functional PCA feature reduction with vine copulas for the bulk distribution and Heffernan-Tawn conditional modeling for the tails, enabling synthetic trajectory generation under a breaking constraint.
Akima, A new method of interpolation and smooth curve fitting based on local procedures, Journal of the ACM (JACM) 17 (4) (1970) 589–602
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Data-driven modeling of multivariate stochastic trajectories -- Application to water waves
A data-driven stochastic model for water wave kinematics is built by combining functional PCA feature reduction with vine copulas for the bulk distribution and Heffernan-Tawn conditional modeling for the tails, enabling synthetic trajectory generation under a breaking constraint.