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渐近独立阈值超越的层次时空建模及降水应用AI 解读

The statistical modeling of space-time extremes in environmental applications is key to understanding complex dependence structures in original event data and to generating realistic scenarios for impact models. In this context of high-dimensional data, we propose a novel hierarchical model for high threshold exceedances defined over continuous space and time by embedding a space-time Gamma process convolution for the rate of an exponential variable, leading to asymptotic…

椭圆型 ℓ-Pareto 过程的高效推断与模拟AI 解读

Recent advances in extreme value theory have established |$\ell $|-Pareto processes as the natural limits for extreme events defined in terms of exceedances of a risk functional. In this paper we provide methods for the practical modelling of data based on a tractable yet flexible dependence model. We introduce the class of elliptical |$\ell $|-Pareto processes, which arise as the limits of threshold exceedances of certain elliptical processes characterized by a correlation…