|Author(s)||Monbet Valérie1, 2, Ailliot P1, Prevosto Marc2|
|Affiliation(s)||1 : Univ S Brittany, Dept Appl Stat, F-56017 Vannes, France.
2 : IFREMER, Ctr Brest, ERT HO, Hydrodynam & Metocean, F-29280 Plouzane, France.
|Source||Probabilistic Engineering Mechanics (0266-8920) (Elsevier), 2007-04 , Vol. 22 , N. 2 , P. 113-126|
|WOS© Times Cited||59|
|Keyword(s)||Model validation, Simulation, Nonlinear time series, Wind, Sea state|
|Abstract||The knowledge of sea state and wind conditions is of central importance for many offshore and nearshore operations. In this paper, we make a complete survey of stochastic models for sea state and wind time series. We begin with methods based on Gaussian processes, then non-parametric resampling methods for time series are introduced followed by various parametric models. We also propose an original statistical method, based on Monte Carlo goodness-of-fit tests, for model validation and comparison and this method is illustrated on an example of multivariate sea state time series. (C) 2006 Elsevier Ltd. All rights reserved.|
Monbet Valérie, Ailliot P, Prevosto Marc (2007). Survey of stochastic models for wind and sea state time series. Probabilistic Engineering Mechanics, 22(2), 113-126. Publisher's official version : https://doi.org/10.1016/j.probengmech.2006.08.003 , Open Access version : https://archimer.ifremer.fr/doc/00000/2679/