Mathieu RIBATET – Associate professor in Statistics

Mathieu RIBATET
H +33(0)6 17 93 16 12
B [email protected]
Í www.math.univ-montp2.fr/ ribatet
Date of birth 07/01/1980
Associate professor in Statistics
Research interests
EXTREMES max-stable process, Pareto process, spatio–temporal extremes
INFERENCE composite likelihood, Monte–Carlo techniques, computational statistics
APPLICATION environmental extremes
Appointments
2013
2010
2007
2010
Associate project scientist, Institute of Financial and Actuarial Sciences, University of Lyon, France.
Associate professor, Department of Mathematics, University of Montpellier, France.
Post-doc, Department of Mathematics, EPFL, Lausanne, Switzerland.
2004
2007
PhD student, PhD thesis jointly hosted by INPG and INRS, France/Canada.
Scientific activities
2010
ANR Mc Sim project, Multisupport conditional simulation of max-stable processes.
http://web.math.univ-montp2.fr/McSim
2010
GICC MIRACCLE project, Risk measures and indices for climate change.
2010
Associate editor, Journal of Statistical Theory and Practice.
www.tandfonline.com/loi/UJSP20
2007
2011
CCES EXTREMES project, Spatial extremes and environmental sustainability : Statistical methods
and applications in geophysics and the environment.
www.cces.ethz.ch/projects/hazri/EXTREMES
Software : R packages
2008
SpatialExtremes, Statistical modelling of spatial extremes using max-stable processes or Bayesian
hierarchical models.
http://spatialextremes.r-forge.r-project.org
2006
2005
JointModeling, Joint modeling of the mean and dispersion using generalized linear/additive models.
POT, Statistical modelling of peaks over threshold using the generalized Pareto distribution.
http://pot.r-forge.r-project.org
Publications
Submitted papers or work in progress
[1] E. Gilleland, and M. Ribatet. Reinsurance and extremal events. Chapitre de contribution à Computational
Actuarial Science. Editor : Arthur Charpentier. Chapman, 2013.
[2] C. Dombry, and M. Ribatet. Functional regular variations, Pareto processes and peaks over threshold.
Soumis à Extremes, 2012
Published papers
[3] M. Ribatet. Spatial extremes : Max-stable processes at work. To appear in Journal de la Société Française
de Statistique, 2013.
[4] M. Ribatet, and M. A. Sedki. Extreme value copulas and max-stable processes. Journal de la Société
Française de Statistique, 154(1) :138–150, 2013.
[5] A.C. Davison, S.A. Padoan, and M. Ribatet. Statistical modelling of spatial extremes. Statistical Science,
7(2) :161–186, 2012.
1/4
[6] C. Dombry, F. Éyi-Minko, and M. Ribatet. Conditional simulation of max-stable processes. Biometrika,
100(1) :111–124, 2013.
[7] L. Frossard, H. Rieder, M. Ribatet, J. Staehelin, J. Maeder, S. Di Rocco, A. C. Davison, and T. Peter.
On the relationship between total ozone and atmospheric dynamics and chemistry at mid-latitudes —
part 1 : Statistical models and spatial fingerprints of atmospheric dynamics and chemistry. Atmos. Chem.
Phys., 13 :147–164, 2013.
[8] E. Gilleland, M. Ribatet, and A. G. Stephenson. A comparative software review for extreme value analysis.
To appear in Extremes, 2012.
[9] B. Iooss and M. Ribatet. Global sensitivity analysis of stochastic computer models with functional inputs.
Reliability Engineering and System Safety, 94(7) :1194–1204, 2009.
[10] A. Marrel, B. Iooss, S. da Veiga, and M. Ribatet. Global sensitivity analysis of stochastic momputer
models with joint metamodels. Statistics and Computing, 22(3) :833–847, 2012.
[11] S.A. Padoan, M. Ribatet, and S. Sisson. Likelihood-based inference for max-stable processes. Journal of
the American Statistical Association (Theory & Methods), 105(489) :263–277, 2010.
[12] M. Ribatet. POT : Modelling Peaks Over a Threshold. R News, 7(1) :34–36, April 2007.
[13] M. Ribatet, D. Cooley, and A.C. Davison. Bayesian inference from composite likelihoods, with an
application to spatial extremes. Statistica Sinica, 22 :813–845, 2012.
[14] M. Ribatet, T.B.M.J. Ouarda, E. Sauquet, and J.-M. Grésillon. Modeling All Exceedances Above a
Threshold Using an Extremal Dependence Structure : Inferences on Several Flood Characteristics. Water
Resources Research, 45 :W03407, 2009.
[15] M. Ribatet, E. Sauquet, J.-M. Grésillon, and T.B.M.J. Ouarda. A regional Bayesian POT model for flood
frequency analysis. Stochastic Environmental Research and Risk Assessment (SERRA), 21(4) :327–339,
2007.
[16] M. Ribatet, E. Sauquet, J.-M. Grésillon, and T.B.M.J. Ouarda. Usefulness of the Reversible Jump
Markov Chain Monte Carlo Model in Regional Flood Frequency Analysis. Water Resources Research,
43(8) :W08403, 2007.
[17] H. Rieder, L. Frossard, M. Ribatet, J. Staehelin, J. Maeder, S. Di Rocco, A. C. Davison, T. Peter,
P. Weihs, and F. Holawe. On the relationship between total ozone and atmospheric dynamics and
chemistry at mid-latitudes — part 2 : The effects of the el nino/southern oscillation, volcanic eruptions
and contributions of atmospheric dynamics and chemistry to long-term total ozone changes. Atmos.
Chem. Phys., 13 :165–179, 2013.
[18] H. Rieder, J. Staehelin, J. Maeder, T. Peter, M. Ribatet, A. C. Davison, , R. Stubi, P. Weihs, and
F. Holawe. Extreme events in total ozone over arosa—part 1 : Application of extreme value theory.
Atmos. Chem. Phys., 10 :10021–10031, 2010.
[19] H. Rieder, J. Staehelin, J. Maeder, T. Peter, M. Ribatet, A. C. Davison, , R. Stubi, P. Weihs, and
F. Holawe. Extreme events in total ozone over arosa—part 2 : Fingerprints of atmospheric dynamics and
chemistry and effects on mean values and long-term changes. Atmos. Chem. Phys., 10 :10033–10045,
2010.
[20] L. M. Rieder, H. Jancso, S. Di Rocco, J. Maeder, J. Staehelin, T. Peter, M. Ribatet, and A. C. Davison.
Extreme events in total ozone over the northern mid-latitude : An analysis based on long-term data sets
from five european ground-based stations. Tellus B, 63(5) :860–874, 2011.
References
1. Prof. Anthony DAVISON
École Polytechnique Fédérale de Lausanne
Institut de Mathématiques, Chaire de Statistique
STAT-IMA-FSB-EPFL, Station 8
CH-1015 Lausanne, Switzerland
T : +41 (0)21 693 5502
B : [email protected]
Í : http://people.epfl.ch/Anthony.Davison
2/4
2. Prof. Anne-Laure FOUGÈRES
Université Lyon 1
Institut Camille Jordan
21 avenue Claude Bernard
69622 Villeurbanne Cedex, France
T : +33 (0)4 72 44 62 71
B : [email protected]
Í : http://math.univ-lyon1.fr/~fougeres
3. Prof. Jean-Michel MARIN
Université Montpellier 2
Département de Mathématiques
4 place Eugène Bataillon
34095 Montpellier Cedex 5, France
T : +33 (0)4 67 14 39 55
B : [email protected]
Í : http://www.math.univ-montp2.fr/~marin
Teachings
2012–2013 : University of Montpellier
BSc Biology
BSc Biology
BSc Maths
MSc Biostatistics
MSc Biostatistics
MSc Biostatistics
Mathematics and Statistics
Statistics 3
Survey analysis
Applied statistics
Spatial statistics
Extreme value theory
2011–2012 : University of Montpellier
BSc Biology
BSc Maths
BSc Maths
MSc Biostatistics
MSc Biostatistics
MSc Biostatistics
Statistics 3
Data mining
Survey analysis
Data mining
Spatial statistics
Extreme value theory
2010–2011 : University of Montpellier
BSc Physics
BSc Biology
BSc Maths
MSc Biostatistics
Analysis 1
Biostatistics 1
Inferential statistics
Extreme value theory
2009–2010 : Federal Institute of Technology of Lausanne (EPFL)
MSc Finance Times series
BSc Scientific Probability and statistics
Police
2008–2009 : Federal Institute of Technology of Lausanne (EPFL)
MSc Maths Monte–Carlo inference
MSc Finance Times series
BSc Civil Probability and statistics
Engineering
2007–2008 : Federal Institute of Technology of Lausanne (EPFL), University of Lyon
MSc Mechanics Probability and statistics
3/4
BSc Probability and statistics
Environmental
engineering
Student supervising
2012–2013 Detecting anomalies in medical imaging using Gibbs random fields, Audrey Winter and Alexis
Arnaud.
MSc Maths, Montpellier
Monte–Carlo methods in Finance, Mehdi Kahoul and Hugo Girma.
MSc Maths, Montpellier
Financial time series, Camille Marguerit and Aliénor Marie.
MSc Maths, Montpellier
2011–2012 Modeling hospital loss of appeal using MCMC methods, Mathilde Saccareau and Fanny Bonnafous.
MSc Maths, Montpellier
The maximum spacing estimator, Maximilien Dossa.
MSc Maths, Montpellier
2010–2011 An introduction to the extreme value theory, Antoine Barbieri and Marc Crivello.
MSc Maths, Montpellier
An introduction to MCMC techniques, Marc Bourotte.
MSc Maths, Montpellier
2009–2010 Bayesian trend estimation and change point detection in statistics of extremes, Sven Conter.
MSc Maths, EPFL
Assessment of dependence and uncertainty in the extremes of gridded ozone data in the
southern hemisphere, Linda Frossard.
MSc Maths, EPFL
2008–2009 Composite Marginal Likelihood, Corina Grünenfelder.
MSc Maths, EPFL
Bayesian inference and statistics of extremes, Irene Vicari.
MSc Maths, EPFL
Simulation by circular embedding method of max-stable random fields, Nathalie Pellet.
MSc Maths, EPFL
2007–2008 GARCH Model Selection, Mathieu Cambou.
MSc Maths, EPFL
Statistical approaches for the modelling of financial products, Franck Tiambo.
MSc Maths, EPFL
Bayesian Spatial Modeling of Extreme Precipitation Return Levels, Raphael Huser.
MSc Maths, EPFL
Semi-parametric Estimation of Portfolio Tail Probabilities, Pirmin Maier.
MSc Maths, EPFL
4/4