Trends in Extreme Value Indices

• 成果类型: Article
• 署名作者: de Haan, Laurens; Zhou, Chen
• 署名单位: Erasmus University Rotterdam; Erasmus University Rotterdam - Excl Erasmus MC; European Central Bank; De Nederlandsche Bank NV; Tinbergen Institute
• 刊物名称: JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION
• ISSN/ISSBN: 0162-1459
• DOI: 10.1080/01621459.2019.1705307
• 发表日期: 2021
• 页码: 1265-1279
• 关键词: models

摘要

We consider extreme value analysis for independent but nonidentically distributed observations. In particular, the observations do not share the same extreme value index. Assuming continuously changing extreme value indices, we provide a nonparametric estimate for the functional extreme value index. Besides estimating the extreme value index locally, we also provide a global estimator for the trend and its joint asymptotic theory. The asymptotic theory for the global estimator can be used for testing a prespecified parametric trend in the extreme value indices. In particular, it can be applied to test whether the extreme value index remains at a constant level across all observations.