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，对能够评估超出可用数据观测范围的极端事件风险的方法需求日益增长。在数据范围之外推断极端事件并非易事。由于需要同时考虑多个变量，风险评估往往变得更加复杂。极值理论为多元或空间极端事件的分析提供了重要工具，但这些工具对于缺乏相应专业知识的从业者而言并不容易掌握。本文提供了多元与空间极值理论的基础背景，并通过R软件包ExtremalDep给出了分析这些问题的简明而完整的操作指南。在简要介绍统计方法后，我们将重点通过多个实际应用案例对该软件包的工具箱进行实践检验。