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Mathieu Ribatet
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Chair of Statistics
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Research Assistant
birth date: 07.01.1980
nationality: French
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office(s):
MAA1364
phone(s): [+41 21 69] 37907
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Professional responsabilities
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Associate editor for Journal of Statistical Theory and Practice 2010-present
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MAIN PUBLICATIONS
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Bayesian Inference from Composite Likelihoods, with an Application to Spatial Extremes, M. Ribatet, D. Cooley and A.C.D. Davison, Submitted to Statistica Sinica
Likelihood-based inference for max-stable processes, S. A. Padoan, M. Ribatet and S. A. Sisson, To appear in the Journal of the American Statistical Association (Theory and Methods)
Global Sensitivity Analysis of Computer Models with Functional Inputs (2009), B. Iooss and M. Ribatet, Reliability Engineering and System Safety 94(7):1194-1204
Modelling All Exceedances Abobe a Threshold Using an Extremal Dependence Structure: Inferences on Several Flood Characteristics, M. Ribatet, T.B.J.M. Ouarda, E. Sauquet and J.M. Grésillon, In press. Water Resour. Res.
Global Sensitivity Analysis of Stochastic Computer Models with Generalized Additive Models, B. Iooss and M. Ribatet, Submitted to Technometrics
Usefulness of the Reversible Jump Markov Chain Monte Carlo Model in Regional Flood Frequency Analysis (2007), M. Ribatet, E. Sauquet, J.M. Grésillon and T.B.J.M. Ouarda, Water Resour. Res., 43, W08403
A Regional Bayesian POT Model for Flood Frequency Analysis (2007), M. Ribatet, E. Sauquet, J.M. Grésillon and T.B.J.M. Ouarda, Stochastic Environmental Research and Risk Assessment 21(4):327:339
POT: Modelling Peaks Over a Threshold (2007), M. Ribatet, R News, 7, 34-36
Bayesian priors based on regional information: Application to regional flood frequency analysis (2006), M. Ribatet, E. Sauquet, J.-M. Grésillon and T.B.M.J. Ouarda, IAHS-AISH Publ., 226-231
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Softwares
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Developer and maintainer of several R packages:
- SpatialExtremes: Modeling of Spatial Extremes
- POT: Modeling (multivariate) peaks over threshold
- evdbayes: Bayesian analysis with extreme value distributions
- RFA: Regional frequency analysis
- JointModeling: Joint modeling of mean and dispersion using interlinked GLMs/GAMS
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