Homepage Thomas Opitz
Homepage of Thomas Opitz
I am a research associate ("chargé de recherche") at the Biostatistics and Spatial processes lab of INRAE in Avignon.
Mail: thomas POINT opitz AT inrae POINT fr
Telephone: 04 32 72 21 86
Address: INRAEBioSP – Domaine St. Paul – 228, route de l'Aérodrome – 84914 Avignon – France
My general research interests
 My research concerns spatiotemporal modeling and prediction of environmental, climatological, ecological and epidemiological risks.
 I develop and implement theoretical and statistical tools at the inferface of ExtremeValue Theory, which provides a framework for predicting probabilities of events with very extreme magnitudes, and stochastic geometry, useful for studying geometric patterns in occurrence locations/times and in agricultural landscapes.
 For inference in stochastic models, a blend of frequentist and Bayesian inference techniques is used, with a particular focus on the integrated nested Laplace approximation (INLA).
 Statistical models are constructed to combine data available at multiple spatial and temporal scales (e.g., raster, lattice, irregularly spaced locations) and from multiple sources (validated data with strict observation / transformation protocol, citizen science programs, etc.), often large georeferenced datasets.
Current research
 Bayesian modeling of wildfire activity and landslides using marked logGaussian Cox processes.

Spacetime modeling of extremes in climate and weather data:
 New theory and inference tools for models with flexible joint tail decay rates, often based on scale or location mixture representation.
 Modeling temporal trends and dependence in spatially resolved observations.
 Semiparametric resampling techniques for spatial and spatiotemporal extremes.
 Applications to meteorological and climatic processes (precipitation, wind speed, temperature, air pollution), with a view towards climate change.
 Stochastic simulation and statistical inference for agricultural landscapes using stochastic geometry tools.
 (Latent) Lévy convolutions: novel spatialtemporal models for non Gaussian data (extremes, count data) based on kernelsmoothed infinitely divisible distributions, with a focus on gamma processes.
 Spatial and spatiotemporal modeling of ecological processes (Asian hornet invasion and efficiency of capturing them ; wolf attacks on sheep herds).
 Spacetime mapping of soil variables with focus on temporal trends in soil properties.
Projects with funding

CoInvestigator of a KAUST Competitive Research Grant (20182021) coordinated by Raphael Huser, with partners at KAUST and Lancaster University:
"Statistical Estimation and Detection of Extreme Hot Spots, with Environmental and Ecological Applications". 
PhD project of Patrizia Zamberletti (20182021), cosupervised with Julien Papaix and Edith Gabriel at BioSP. Funding: INRAE divisions MIA (25%) and SPE (25%), and ProvenceAlpes Côtes d’Azur region (50%).
"Simulation and inference of agricultural landscapes using stochastic geometry; agroecological analysis of numerical simulations of spatially explicit population dynamics model (sensitivity analysis, statistical learning)". 
Postdoc project (20172019) of Fátima PalacíosRodriguez, with funding from MUSE, Labex Numev and Inria:
"Semiparametric resampling of extreme events over space and time, with an application to precipitation data, and with a view towards extreme risk measures". 
LEFECERISE, LEFEFRAISE projects (20162021) funded by INSU:
"Simulation de scénarii intégrant des champs extrêmes spatiotemporelle avec éventuelle indépendance asymptotique pour des études d'impact en science de l'environnement". 
Pari scientifique EA, coordinated by Hocine Bourennane and Nicolas Saby (20182020):
"Innovative approaches for spacetime prediction and mapping of soil properties using INLA" ("Approches innovantes de prévisions géodatées des propriétés des sols").
Responsibilities and research networks
 Steering committee member of RESSTE ("RESeau Statistique pour données SpatioTEmporelles"), one of INRAE's current research networks.
 Elected member and webmaster of the "Groupe Environnement et Statistique" of the French Statistical Society.
 Coorganizer of BioSP's seminar.
Teaching
 2020/2021: Course "Introduction to extremevalue analysis" at École Centrale Marseille, Master Climaths
 since 2018: Course "Statistique spatiale et écologie", M2 Data Science, Marseille
 21/03/2019: Oneday master course on Multivariate Extremes, ATHENS network, MinesParisTech
 2016/2017: Statistique Descriptive 2, L1 STID, IUT Avignon
Preprints
 CastroCamilo, D., Mhalla, L. and Opitz, T. ‘Bayesian spacetime gap filling for inference on hot spots: an application to Red Sea surface temperatures’.
 Lombardo, L. et al. ‘SpaceTime Landslide Predictive Modelling’, In revision for Earth Science Reviews. Available at: http://arxiv.org/abs/1912.01233.
 Opitz, T. et al. ‘Highresolution Bayesian mapping of landslide hazard with unobserved trigger event’.
 Opitz, T. ‘Spatial random field models based on Lévy indicator convolutions’, arXiv preprint arXiv:1710.06826.
 PalaciosRodriguez, F. et al. ‘Semiparametric generalized Pareto processes for simulating spacetime extreme events’.
 Pimont, F. et al. ‘Prediction of regional wildfire activity with a probabilistic Bayesian framework’.
 Yadav, R., Opitz, T. and Huser, R. ‘Spatial hierarchical modeling of threshold exceedances using rate mixtures’.
 Zamberletti, P. et al. ‘Landscape allocation: stochastic generators and statistical inference’.
 Zhong, P., Huser, R. and Opitz, T. ‘Assessing NonStationary Heatwave Hazard with MagnitudeDependent Spatial Extremal Dependence’. arXiv preprint arXiv:2006.01569.
Publications
 Opitz, T., Allard, D. and Mariethoz, G. (2020) ‘Semiparametric resampling with extremes’, Spatial Statistics. doi: 10.1016/j.spasta.2020.100445.
 Opitz, T., Bonneu, F. and Gabriel, E. (2020) ‘Pointprocess based modeling of spacetime structures of forest fire occurrences in Mediterranean France’, Spatial Statistics, In press. doi: 10.1016/j.spasta.2020.100429.
 Bacro, J.N. et al. (2019) ‘Hierarchical SpaceTime Modeling of Asymptotically Independent Exceedances With an Application to Precipitation Data’, Journal of the American Statistical Association. Taylor & Francis, 0(0), pp. 1–26. doi: 10.1080/01621459.2019.1617152.
 Engelke, S., Opitz, T. and Wadsworth, J. L. (2019) ‘Extremal dependence of random scale constructions’, Extremes.
 Lombardo, L., Opitz, T. and Huser, R. (2019) ‘Numerical Recipes for Landslide Spatial Prediction Using RINLA: A StepbyStep Tutorial’, in Spatial Modeling in GIS and R for Earth and Environmental Sciences. Elsevier, pp. 55–83.
 Mhalla, L., Opitz, T. and ChavezDemoulin, V. (2019) ‘Exceedancebased nonlinear regression of tail dependence’, Extremes. Springer, pp. 1–30.
 Bakka, H. et al. (2018) ‘Discussion of ``Using Stacking to Average Bayesian Predictive Distributions" by Yao et. al’, Bayesian Analysis.
 Fargeon, H. et al. (2018) ‘Assessing the increase in wildfire occurrence with climate change and the uncertainties associated with this projection’, in 8th International conference on forest fire research.
 Huser, R., Opitz, T. and Thibaud, E. (2018) ‘Maxinfinitely divisible models and inference for spatial extremes’, arXiv:1801.02946v2.
 Lombardo, L., Opitz, T. and Huser, R. (2018) ‘Point processbased modeling of multiple debris flow landslides using INLA: an application to the 2009 Messina disaster’, Stochastic environmental research and risk assessment. Springer, 32(7), pp. 2179–2198.
 Opitz, T. et al. (2018) ‘INLA goes extreme: Bayesian tail regression for the estimation of high spatiotemporal quantiles’, Extremes. Springer, 21(3), pp. 441–462.
 Tapi Nzali, M. D. et al. (2018) ‘Reconciliation of patient/doctor vocabulary in a structured resource’, Health Informatics journal. SAGE Publications Sage UK: London, England.
 Gabriel, E., Opitz, T. and Bonneu, F. (2017) ‘Detecting and modeling multiscale spacetime structures: the case of wildfire occurrences’, Journal of the French Statistical Society (Special Issue on SpaceTime Statistics).
 Huser, R., Opitz, T. and Thibaud, E. (2017) ‘Bridging asymptotic independence and dependence in spatial extremes using Gaussian scale mixtures’, Spatial Statistics. Elsevier, 21, pp. 166–186.
 Mornet, A. et al. (2017) ‘Wind storm risk management: sensitivity of return period calculations and spread on the territory’, Stochastic Environmental Research and Risk Assessment. Springer, 31(8), pp. 1977–1995.
 Nzali, M. D. T. et al. (2017) ‘What patients can tell us: topic analysis for social media on breast cancer’, JMIR Medical Informatics. JMIR Publications Inc., 5(3).
 Opitz, T. (2017) ‘Latent Gaussian modeling and INLA: A review with focus on spacetime applications’, Journal of the French Statistical Society (Special Issue on SpaceTime Statistics), 158(3).
 Opitz, T. (2016) ‘Modeling asymptotically independent spatial extremes based on Laplace random fields’, Spatial Statistics, 16, pp. 1–18.
 Mornet, A. et al. (2015) ‘Index for Predicting Insurance Claims from Wind Storms with an Application in France’, Risk Analysis. Wiley Online Library, 35(11), pp. 2029–2056.
 Opitz, T., Bacro, J.N. and Ribereau, P. (2015) ‘The spectrogram: A thresholdbased inferential tool for extremes of stochastic processes’, Electronic Journal of Statistics. Institute of Mathematical Statistics, 9(1), pp. 842–868.
 Tapi Nzali, M. D. et al. (2015) ‘Construction d’un vocabulaire patient/médecin dédié au cancer du sein à partir des médias sociaux’, 26. Journées Francophones d’Ingénierie des Connaissances (IC), Rennes.
 Thibaud, E. and Opitz, T. (2015) ‘Efficient inference and simulation for elliptical Pareto processes’, Biometrika, 102(4), pp. 855–870.
 Opitz, T. et al. (2014) ‘Breast cancer and quality of life: medical information extraction from health forums’, in Medical Informatics Europe Conference 2014, pp. 1070–1074.
 Opitz, T. (2013) ‘Extremal t processes: Elliptical domain of attraction and a spectral representation’, J. Multivar. Anal., 122, pp. 409–413.
Current responsibilities
 Coorganizer of the weekly seminar of BioSP
 Elected member of the French Statistical Society's "Environment and Statistics" group
Past responsibilities and activities
 Organizing committee and webmaster of the GdR GeoSto Meeting 2019 in Avignon
 Program Committee of Spatial Statistics 2019, Sitges, Spain
 Member of the organizing team and Webmaster of the GdR GeoSto meeting in June 2019 (Avignon)
 Vicepresident of organizing committee and webmaster (web site and registration, submission, review systems) of the METMA IX conference on Spacetime modeling and statistics, 1315 June 2018, Montpellier
 Webmaster (web site and registration, submission, review systems) of the Journées de Statistique 2017, Avignon
 Organization and Program Committee of AG MIA 2017 / Journées MathsInfos / Journées INRAInria
 Program Committee of Spatial Statistics 2015, Avignon