Bayesian Extreme Value Theory

Nicolas Bousquet ()
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Nicolas Bousquet: EDF R & D

Chapter Chapter 11 in Extreme Value Theory with Applications to Natural Hazards, 2021, pp 271-325 from Springer

Abstract: Abstract This chapter provides an introduction to Bayesian statistical theory and a broad review of its application to extreme values. The Bayesian methodology differs greatly from the traditional approaches considered in the other chapters. Indeed, it requires the construction of so-called prior measures for the parameters of extreme value models and defines estimation through the minimization of a cost function adapted to the event. While Bayesian calculations (as those based on Monte Carlo Markov Chains) remain superficially discussed, this chapter focuses on modeling features, which allow expert opinion and historical knowledge to be integrated into the estimation of quantities of interest. In this respect, the Bayesian approach constitutes a methodology of increasing use, allowing the mixed treatment of aleatoric and epidemic uncertainties and adapted to the specific needs of engineers.

Date: 2021
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Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-030-74942-2_11

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DOI: 10.1007/978-3-030-74942-2_11

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