Detecting breaks in the dependence of multivariate extreme-value distributions

TL;DR

This paper introduces a statistical test to detect changes in the dependence structure of multivariate extreme values over time, accounting for known marginal distribution breaks, with validation through simulations and hydrological data analysis.

Contribution

It proposes a novel test for dependence change detection in multivariate extremes, including adjustments for known marginal distribution breaks.

Findings

Test effectively detects dependence changes in simulations.

Method performs well with real hydrological data.

Adjustments improve detection accuracy when marginal breaks are known.

Abstract

In environmental sciences, it is often of interest to assess whether the dependence between extreme measurements has changed during the observation period. The aim of this work is to propose a statistical test that is particularly sensitive to such changes. The resulting procedure is also extended to allow the detection of changes in the extreme-value dependence under the presence of known breaks in the marginal distributions. Simulations are carried out to study the finite-sample behavior of both versions of the proposed test. Illustrations on hydrological data sets conclude the work.