1 citations · 2 across the 7 of their papers we have counts for
9 papers
EM algorithm for generalized Ridge regression with spatial covariates
Said Obakrim, Pierre Ailliot, Valérie Monbet +1
The generalized Ridge penalty is a powerful tool for dealing with overfitting and for high-dimensional regressions. The generalized Ridge regression can be derived as the mean of a…
Learning the spatio-temporal relationship between wind and significant wave height using deep learning
Said Obakrim, Valérie Monbet, Nicolas Raillard +1
Ocean wave climate has a significant impact on near-shore and off-shore human activities, and its characterisation can help in the design of ocean structures such as wave energy co…
An algorithm for non-parametric estimation in state-space models
Thi Tuyet Trang Chau, Pierre Ailliot, Valérie Monbet
State-space models are ubiquitous in the statistical literature since they provide a flexible and interpretable framework for analyzing many time series. In most practical applicat…
An efficient particle-based method for maximum likelihood estimation in nonlinear state-space models
Thi Tuyet Trang Chau, Pierre Ailliot, Valérie Monbet +1
Data assimilation methods aim at estimating the state of a system by combining observations with a physical model. When sequential data assimilation is considered, the joint distri…
Dependent time changed processes with applications to nonlinear ocean waves
Pierre Ailliot, Bernard Delyon, Valérie Monbet +1
Many records in environmental sciences exhibit asymmetric trajectories and there is a need for simple and tractable models which can reproduce such features. In this paper we explo…
Gaussian linear state-space model for wind fields in the North-East Atlantic
Julie Bessac, Pierre Ailliot, Valerie Monbet
A space-time model for wind fields is proposed. It aims at simulating realistic wind conditions with a focus on reproducing the space-time motions of the meteorological systems. A…