Far East Journal of Theoretical Statistics

The Far East Journal of Theoretical Statistics publishes original research papers and survey articles in the field of theoretical statistics, covering topics such as Bayesian analysis, multivariate analysis, and stochastic processes.

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FUZZY VINE COPULA CONSTRUCTION: AN APPROACH TO MODELING DEPENDENCE UNDER UNCERTAINTY

Authors

  • Sayouba Traoré
  • Remi Guillaume Bagré
  • Abdoulaye Compaoré

Keywords:

copulas, vine copulas, fuzzy copulas, fuzzy sets

DOI:

https://doi.org/10.17654/0972086325014

Abstract

This paper introduces a systematic methodology for constructing vine copulas from fuzzy data, providing a novel framework for modeling complex dependence under uncertainty. Our approach first builds bivariate fuzzy copulas, including those from the Archimedean family, which serve as foundational building blocks. We then assemble these into a complete fuzzy vine structure. The methodology leverages the -cut decomposition of fuzzy numbers, transforming fuzzy parameters and data into intervals. This allows us to apply and extend standard copula techniques to interval-valued data, a key aspect of our contribution. The resulting framework addresses both parametric and structural uncertainties, opening new avenues for robust modeling in risk analysis, finance, engineering and other domains where uncertainty and dependence coexist.

Received: July 10, 2025
Revised: August 5, 2025
Accepted: August 19, 2025

References

[1] Abdoulaye Compaoré, Kounhinir Somé and Blaise Somé, New approach to the resolution of triangular fuzzy linear programs: MOMA-plus method, International Journal of Applied Mathematical Research 6(4) (2017), 115-120.

[2] T. Bedford and R. M. Cooke, Probability density decomposition for conditionally dependent random variables modeled by vines, Annals of Mathematics and Artificial Intelligence 32(1-4) (2001), 245-268.

[3] T. Bedford and R. M. Cooke, Vines - a new graphical model for dependent random variables, Ann. Statist. 30(4) (2002), 1031-1068.

[4] Farid Aiche, Thèse de Doctorat, comparaison d’ intervalles flous pour la programmation multi-objectifs dans l’incertain, Université de Toulouse, 2013.

[5] Ju Wu, Lianming Mou, Fang Liu, Haobin Liu and Yi Liu, Archimedean copula-based hesitant fuzzy information, aggregation operators for multiple attribute decision making, Math. Probl. Eng. 2020, Article ID 6284245, 21 pages.

[6] R. B. Nelsen, An Introduction to Copulas, Springer Science & Business Media, 2006.

[7] S. Giakoumakis and B. Papadopoulos, Novel Construction of Copulas based on Transformation for Fuzzy Random Variables, Hindawi, 2021.

[8] A. Sklar, Fonctions de répartition à n dimensions et leurs marges, Publications de l’Institut de Statistique de l’Université de Paris 8 (1959), 229-231.

[9] L. A. Zadeh, Fuzzy sets, Information and Control 8(3) (1965), 338-353.

Published

2025-09-09

Issue

Section

Articles

How to Cite

FUZZY VINE COPULA CONSTRUCTION: AN APPROACH TO MODELING DEPENDENCE UNDER UNCERTAINTY. (2025). Far East Journal of Theoretical Statistics , 69(3), 281-293. https://doi.org/10.17654/0972086325014