Improving estimation for asymptotically independent bivariate extremes via global estimators for the angular dependence function

Research output: Contribution to journalResearch articleContributedpeer-review

Contributors

Abstract

Modelling the extremal dependence of bivariate variables is important in a wide variety of practical applications, including environmental planning, catastrophe modelling and hydrology. The majority of these approaches are based on the framework of bivariate regular variation, and a wide range of literature is available for estimating the dependence structure in this setting. However, such procedures are only applicable to variables exhibiting asymptotic dependence, even though asymptotic independence is often observed in practice. In this paper, we consider the so-called ‘angular dependence function’; this quantity summarises the extremal dependence structure for asymptotically independent variables. Until recently, only pointwise estimators of the angular dependence function have been available. We introduce a range of global estimators and compare them to another recently introduced technique for global estimation through a systematic simulation study, and a case study on river flow data from the north of England, UK.

Details

Original languageEnglish
Number of pages29
JournalExtremes : statistical theory and applications in science, engineering and economics
Volume27
Issue number4
Publication statusPublished - 13 Aug 2024
Peer-reviewedYes

External IDs

unpaywall 10.1007/s10687-024-00490-4
Scopus 85201321035

Keywords