Multivariate Dependence Modeling with Copulas

使用 Copula 进行多元依赖建模

• 批准号: RGPIN-2015-06801
• 负责人: Neslehova, Johanna
• 金额: $ 2.26万
• 依托单位: McGill University
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2017
• 资助国家: 加拿大
• 起止时间: 2017-01-01 至 2018-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=636016
• 关键词: Multivariate; Dependence; Modeling; Copulas

The proposed research focuses on new statistical methodology for copula-based dependence models, which are now widely used in many fields, including environmental and health sciences, finance, insurance, and risk management. Dependence in multivariate data is a complex phenomenon and copula-based models are far more capable of accounting for it than traditional multivariate distributions. My research program is a continuation of my previous NSERC Discovery Grant, with a new focus on complex data structures and recent challenges in applications, such as high-dimensional data, discontinuous variables, or low-probability, high-impact events.

拟议的研究重点是基于Copula的依赖模型的新统计方法，这些模型现在广泛应用于许多领域，包括环境和健康科学，金融，保险和风险管理。多元数据的相关性是一个复杂的现象，基于Copula的模型比传统的多元分布更能解释它。我的研究计划是我以前的NSERC发现补助金的延续，新的重点是复杂的数据结构和应用程序中的最新挑战，如高维数据，不连续变量，或低概率，高影响事件。