Diagnostics for dependence within time series extremes

• 成果类型: Article
• 署名作者: Ledford, AW; Tawn, JA
• 署名单位: Lancaster University
• 刊物名称: JOURNAL OF THE ROYAL STATISTICAL SOCIETY SERIES B-STATISTICAL METHODOLOGY
• ISSN/ISSBN: 1369-7412
• DOI: 10.1111/1467-9868.00400
• 发表日期: 2003
• 页码: 521-543
• 关键词: tail index estimation; stationary; models; CONVERGENCE; estimator; bootstrap; threshold; inference; BEHAVIOR

摘要

The analysis of extreme values within a stationary time series entails various assumptions concerning its long- and short-range dependence. We present a range of new diagnostic tools for assessing whether these assumptions are appropriate and for identifying structure within extreme events. These tools are based on tail characteristics of joint survivor functions but can be implemented by using existing estimation methods for extremes of univariate independent and identically distributed variables. Our diagnostic aids are illustrated through theoretical examples, simulation studies and by application to rainfall and exchange rate data. On the basis of these diagnostics we can explain characteristics that are found in the observed extreme events of these series and also gain insight into the properties of events that are more extreme than those observed.