From environmental sciences to finance, there is a growing demand for methods that can assess the risks of extreme events beyond those observed in available data. Extrapolating extreme events beyond the range of the data is not obvious. Risk assessments are often further complicated by the need to account for multiple variables simultaneously. Extreme value theory provides important tools for the analysis of multivariate or spatial extreme events, but these are not easily accessible to professionals without appropriate expertise. This article provides a minimal background on multivariate and spatial extremes and gives simple yet thorough instructions on how to analyse them using the R package ExtremalDep. After briefly introducing the statistical methodologies, we focus on road testing the package's toolbox through several real-world applications.

翻译：从环境科学到金融领域，对于评估超越现有观测数据范围的极端事件风险的方法需求日益增长。将极端事件外推至数据范围之外并非易事。风险评估往往因需同时考虑多个变量而进一步复杂化。极值理论为分析多元或空间极端事件提供了重要工具，但缺乏专业知识的从业者难以直接运用这些工具。本文提供关于多元与空间极值的基础知识，并给出使用R语言ExtremalDep包进行此类分析的操作指南。在简要介绍统计方法之后，我们通过多个实际应用案例重点测试该工具包的功能。