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A utopic adventure in the modelling of conditional univariate and multivariate extremes

  • Léo R. Belzile,
  • Arnab Hazra,
  • Rishikesh Yadav

摘要

This paper presents the contribution of Team Yahabe to the EVA (2023) Conference Data Challenge. We tackle the four problems posed by the organizers by revisiting the current and existing literature on conditional univariate and multivariate extremes. We highlight overarching themes linking the four tasks, ranging from model validation at extremely high quantile levels to building customized estimation strategies that leverage model assumptions.