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
%0 Journal Article
%1 Monbet.Ailliot.ea2007
%A Monbet, J.
%A Ailliot, P.
%A Prevosto, M.
%D 2007
%J Probabilistic Engineering Mechanics
%K Model, Non Prediction, Reconstruction, Sea Simulation, Wind linear series, state, time
%N 2
%T Survey of Stochastic Models for Wind and Sea State Time Series
%V 22
%X 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
@article{Monbet.Ailliot.ea2007,
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},
added-at = {2011-09-01T13:26:03.000+0200},
author = {Monbet, J. and Ailliot, P. and Prevosto, M.},
biburl = {https://www.bibsonomy.org/bibtex/2a44c3fdc641056b9f1918323b1cbfef3/procomun},
file = {Monbet.Ailliot.ea2007.pdf:Monbet.Ailliot.ea2007.pdf:PDF},
interhash = {6288cd0f437318c5f202b4d6cf9588de},
intrahash = {a44c3fdc641056b9f1918323b1cbfef3},
journal = {Probabilistic Engineering Mechanics},
keywords = {Model, Non Prediction, Reconstruction, Sea Simulation, Wind linear series, state, time},
number = 2,
owner = {oscar},
refid = {Monbet.Ailliot.ea2007},
timestamp = {2011-09-02T08:25:25.000+0200},
title = {Survey of Stochastic Models for Wind and Sea State Time Series},
volume = 22,
year = 2007
}