Extreme Value Theory: Theory, Methodology and Applications

Dear Colleagues,

Extreme Values arising out of univariate, bivariate, and multivariate random variables, as well as through stochastic processes, have soared to prominence over recent decades, being notably spurred on by a climate emergency, among other elements. Regular Variation theory not only lies at the centre of classical Extreme Value theory, but it also continues to steadily underpin significant advances in statistical inference for tail-related data and connected empirical processes.

This Special Issue aims to celebrate, explore and disseminate the latest research taking place within the realms of Extreme Values, examining new advancements in terms of theory, methodology, Regular Variation and Empirical Processes, including research developed at the interface of Extremes (broadly understood) with applied sciences at large. High-quality research contributions describing original, innovative, empirical, or scoping out-type unpublished work in the above-named areas, also mirrored in the following keywords, are cordially invited for publication:

spatial and/or temporal processes; methodological statistics; nonparametric statistic machine learning; causal inference; regression models; applied probability; graphical models; optimization; data science; applied statistical modelling and simulation.

Dr. Indranil Ghosh
Guest Editor

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