Spatial extremes

Statistics of Extremes

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B9 L2 H1 R2322

Extreme environmental events such as droughts, floods and heat-waves take place in space and time, and it is necessary to take this into account when evaluating their risks and estimating their probabilities. During this seminar, I will review some classical and more recent work on this topic, focusing on the modeling of univariate and spatial extremes. The ideas will be illustrated by applications to peak river flow data from the UK, and heavy rainfall close to Jeddah.

Dr. Sebastian Engelke (EPFL) visits extSTAT

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Sebastian is an Ambizione fellow at EPF Lausanne with Anthony Davison. Sebastian did his studies in Mathematics at University of Göttingen and UC Berkeley, and he finished his PhD as a Deutsche Telekom Foundation fellow in 2013 at the University of Göttingen with Martin Schlather. His research interests are in extreme value theory, spatial statistics, graphical models and data science.

Prof. Benjamin Shaby (Penn State University, USA) visits extSTAT

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Prof. Ben Shaby is an Assistant Professor in the Statistics Department and the Institute for CyberScience at Penn State, where he started in 2013. Before that, he was a postdoc with Cari Kaufman at UC Berkeley. Previous stop was in Durham at the Statistics and Applied Mathematical Institute (SAMSI) and Duke University. He did his Ph.D. work in Statistics at Cornell University with David Ruppert and Marty Wells. Before starting at Cornell, he spent his undergrad years at Stanford (go Cardinal!). He then spent two great years working for Chris Field at the Carnegie Institution's Department of

PhD student Sabrina Vettori selected for an ENVR Student Paper Award. Congrats!

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PhD student Sabrina Vettori has been selected to receive a Best Student Paper Award from the Section on Statistics and the Environment (ENVR) of the American Statistical Association (ASA) for her manuscript entitled "Bayesian clustering and dimension reduction in air pollutant multivariate extremes".

Best 2016 Paper in the Journal of Agricultural, Biological and Environmental Statistics

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Professor Huser will present the work in a special invited session (JABES showcase) at the International Biometric Conference taking place in Barcelona, Spain, in July 2018.

Prof. Raphaël Huser now serving as AE of Econometrics and Statistics

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Prof. Raphaël Huser has been appointed to serve as an Associate Editor for the Econometrics and Statistics ( EcoSta) part B (Statistics) starting from May 2019.

Local likelihood estimation of complex tail dependence structures, applied to U.S. precipitation extremes

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New accepted paper: Castro Camilo, D., and Huser, R. (2019+), Local likelihood estimation of complex tail dependence structures, applied to U.S. precipitation extremes, Journal of the American Statistical Association, to appear.

Prof. Raphaël Huser now serving as AE for the journal Environmetrics

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Prof. Raphaël Huser has been appointed to serve as an Associate Editor for Environmetrics, the Journal of The International Environmetrics Society ( TIES​), starting on March 16, 2020.

A hierarchical max-infinitely divisible spatial model for extreme precipitation

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New paper accepted: Bopp, G., Shaby, B., and Huser, R. (2020+), A hierarchical max-infinitely divisible spatial model for extreme precipitation, Journal of the American Statistical Association .

Estimating high-resolution Red Sea surface temperature hotspots, using a low-rank semiparametric spatial model

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New paper accepted: Hazra, A., and Huser, R. (2020+), Estimating high-resolution Red Sea surface temperature hotspots, using a low-rank semiparametric spatial model, Annals of Applied Statistics [ PDF preprint].

Modeling non-stationary temperature maxima based on extremal dependence changing with event magnitude

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New paper accepted: Zhong, P., Huser, R., and Opitz, T. (2021+), Modeling non-stationary temperature maxima based on extremal dependence changing with event magnitude, Annals of Applied Statistics [ arXiv][ PDF preprint].

Approximate Bayesian inference for analysis of spatio-temporal flood frequency data

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New paper accepted : Jóhannesson, Á. V., Siegert, S., Huser, R. , Bakka, H., and Hrafnkelsson, B. (2021+), Approximate Bayesian inference for analysis of spatio-temporal flood frequency data , Annals of Applied Statistics, to appear [ arXiv][ PDF preprint ]

New book chapter accepted

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New book chapter accepted: Hazra, A., Huser, R. , and Jóhannesson, Á. V. (2021+), Bayesian l atent Gaussian models for high-dimensional spatial extremes , In Statistical Modeling Using Bayesian Latent Gaussian Models – With Applications in Geophysics and Environmental Sciences, editor B. Hrafnkelsson, Springer, to appear [ arXiv ][ PDF preprint ].

New paper accepted

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New paper accepted: Zhong, P., Huser, R., and Opitz, T. (2022+), Exact simulation of max-infinitely divisible processes, Econometrics and Statistics [ arXiv][ PDF preprint ].

Congratulations to Peng for successfully defending his PhD thesis

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Title page of PhD defense slides Group picture with Peng (center), Prof. Raphael Huser (3rd from right), after Peng's defense