EMPIRICAL LIKELIHOOD BASED TESTING FOR MULTIVARIATE REGULAR VARIATION

• 成果类型: Article
• 署名作者: Einmahl, John h. j.; Krajina, Andrea; Cai, Juan juan
• 署名单位: Tilburg University; University of Gottingen; Vrije Universiteit Amsterdam
• 刊物名称: ANNALS OF STATISTICS
• ISSN/ISSBN: 0090-5364
• DOI: 10.1214/24-AOS2472
• 发表日期: 2025
• 页码: 352-373
• 关键词: risk; diversification; Respect

摘要

Multivariate regular variation is a common assumption in the statistics literature and needs to be verified in real-data applications. We develop a novel hypothesis test for multivariate regular variation, employing localized empirical likelihood. We establish the weak convergence of the test statistic to a nonstandard, distribution-free limit and hence can provide universal critical values for the test. We show the very good finite-sample behavior of the procedure through simulations and apply the test to several real-data examples.