Research interests

Hidden Markov Models

• Non-homogeneous hidden Markov chain
• Non-parametric filtering (ex: talk)
• Non-linear state-space models(ex: talk)
• Parameter estimation
• Multivariate Markov-switching Autoregressive model (ex: talk)

applied to environmental statistics

• Space-time stochastic generators for weather variables (wind, temperature, sea state, etc)
• Correction of meteorological forecast with stochastic models
• Metocean, stochastic wind-wave models
• Data assimilation (Actimar, Previmer)

Machine learning and biostatistics

Decision trees with multivariate splits
Methods for functionnal data

applied to medical statistics

Spectrometry data (NIR)
NASH, arthritis, etc
Cancer

Some research projects

SEACS (projet inter labex): Stochastic modEl-dAta-Coupled representationS for the analysis, simulation and reconstruction of upper ocean dynamics
This project aims at exploring novel statistical and stochastic methods to address the emulation, reconstruction and forecast of fine-scale upper ocean dynamics.
PhD student: Thi Tuyet Trang Chau

DESIRES (ERANET MED) : This project aims to develop an Internet-based, multi-parametric electronic platform for optimum design of desalination plants, supplied by Renewable Energy Sources (RES). The platform will rely upon 1) a solar, wind and wave energy potential database, 2) existing statistical algorithms for processing energy-related data, 3) information regarding the inter-annual water needs, 3) a database with the technical characteristics of desalination plant units and the RES components, and 4) existing algorithms for cost effective design, optimal sizing and location selection of desalination plants.

PREDICTIVE (projet inter labex) : The general objective of the study is to generate new tools allowing for the exploitation of the big available amount of heterogeneous data to better adapt radiotherapy for individuals suffering from prostate cancer.
PhD student: Audrey Poterie

Workshops

• Workshop "Fonctional Data Analysis 2018", Rennes, Oct.  24-26, 2018
• Workshop "Data Science & environment", Brest, July 04-07, 2017
• "Workshop on Stochastic Weather Generators" , Vannes, May 17-20, 2016
• "Workshop on Stochastic Weather Generators" , Avignon, September 17-19, 2014
• Colloque "Analyse de données spatio-temporelles en océano-météo", 28-29 novembre 2013, Landéda
• Colloque "Analyse de données spatio-temporelles en océano-météo", 03-05 juillet 2013, Ile de Berder.
• "Workshop on Stochastic Weather Generators" May 29th-June 1st, 2012, Roscoff, Britanny
• Journées "Méthodes statistiques spatio-temporelles en environnement"
• "Spatio-temporal Stochastic Models with Environmental and Marine Applications"
• Meteobs-bzh (with P. Ailliot, M. Dragone, A. Cuzol)
• Data Assimilation project , Pôle Math-stic (with N. Courty, A. Cuzol, P. Allain)

Software development

NHMSAR, a R package including

estimation of non homogeneous Markov switching models

simulation

validation by parametric bootstrap

Lasso and Scad penalty for the autoregressive and precision matrices

available on CRAN

Metocean Time Series, a Matlab® toolbox (with M. Prevosto, P. Ailliot, P.F. Marteau) including:

• estimation of parametrical and non parametrical models for multivariate sea state processes (Hs, Tp, Wind speed, Wind directions)
• parametrical and non parametrical simulation for multivariate sea state processes
• estimation of persistence statistics such as duration of storms
• non parametric filtering
• a bootstrap validation method for complex models

download METIS toolbox
download documentation (pdf)

To get the toolbox for public research and non commercial use,  just send me an email : I'll send it to you!

Some talks

Space-time models for moving fields - Application to significant wave height,  download pdf

Publications

Link

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