Advances and Applications in Statistics

The Advances and Applications in Statistics is an internationally recognized journal indexed in the Emerging Sources Citation Index (ESCI). It provides a platform for original research papers and survey articles in all areas of statistics, both computational and experimental in nature.

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ASSESSMENT AND APPLICATION OF THIRD AND FOURTH ORDER GAUGE FUNCTIONS IN EXTREME VALUE ANALYSIS TOWARD ENHANCED GEOMETRIC MODELING

Authors

  • Remi Guillaume Bagré
  • Souleymane Ouédraogo
  • Frédéric Béré

Keywords:

vine density, copulas, multivariate extremes, gauge function, geometric construction

DOI:

https://doi.org/10.17654/0972361725038

Abstract

The gauge function is the basis for modeling the dependence of multivariate extremes using the so-called geometric approach developed in [1] and [12], and many others in recent literature. The work of Wadsworth and Campbell [12] as well as Nolde and Zhang [9] establishes a relationship between the domain G described by a function known as the gauge function and the dependence of the extreme values found there. In this paper, we propose two new candidates of gauge functions for modeling by the geometric approach of multivariate extremes. These functions are constructed through the decompositions of densities D-vine of orders 3 and 4 in connection with the form proposed in [12]. These theoretical constructions are followed by practical simulations, including probability estimation in extreme regions, as well as an application to real-world data.

Received: November 28, 2024
Accepted: March 6, 2025

References

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Janet E. Heffernan and Jonathan A. Tawn, A conditional approach for multivariate extreme values (with discussion), Journal of the Royal Statistical Society Series B: Statistical Methodology 66(3) (2004), 497-546.

Harry Joe, Families of m-variate distributions with given margins and m (m-1)/2 bivariate dependence parameters, Lecture Notes-Monograph Series, 1996, 120-141.

Natalia Nolde, The analysis of extremes in multivariate models: a geometric approach, Ph.D. Thesis, 2010.

Natalia Nolde, Geometric interpretation of the residual dependence coefficient, Journal of Multivariate Analysis 123 (2014), 85-95.

Natalia Nolde and Jennifer L. Wadsworth, Linking representations for multivariate extremes via a limit set, Advances in Applied Probability 54(3) (2022), 688-717.

Natalia Nolde and Jinyuan Zhang, Conditional extremes in asymmetric financial markets, Journal of Business and Economic Statistics 38(1) (2020), 201-213.

Ralph dos Santos Silva and Hedibert Freitas Lopes, Copula, marginal distributions and model selection: a Bayesian note, Statistics and Computing 18 (2008), 313-320.

Emma Siobhan Simpson, Classifying and Exploiting Structure in Multivariate Extremes, Lancaster University (United Kingdom), 2019.

Jennifer Wadsworth and Ryan Campbell, Statistical inference for multivariate extremes via a geometric approach, Journal of the Royal Statistical Society Series B: Statistical Methodology 86(5) (2024), 1243-1265.

Published

14-05-2025

Issue

Section

Articles

How to Cite

ASSESSMENT AND APPLICATION OF THIRD AND FOURTH ORDER GAUGE FUNCTIONS IN EXTREME VALUE ANALYSIS TOWARD ENHANCED GEOMETRIC MODELING. (2025). Advances and Applications in Statistics , 92(6), 911-928. https://doi.org/10.17654/0972361725038

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