Author(s)

Zhuhao Zhang ¹, Xuanyi Zhang ¹, Yangang Zhao ¹

Affiliation(s)

¹ Key Laboratory of Urban Security and Disaster Engineering of Ministry of Education, Beijing University of Technology, No.100 Pingleyuan, Beijing, 100124, China

Corresponding Author

Xuanyi Zhang

ABSTRACT

Two-dimensional joint distribution functions are extensively employed across multiple disciplines, serving as a critical tool to describe and quantify the intricate relationships between two random variables. Copula theory is widely used in the calculation of joint distribution function due to its flexibility in selection of marginal distributions and the dependency structure However, existing methods of constructing joint distributions based on Copula theory often face issues regarding the selection of an appropriate Copula function, which may be inefficient and inflexible. To address these issues, this paper proposes a method based on copula entropy. By using the maximum entropy copula entropy theory as the creteria, a two-dimensional joint probability density function is proposed. Case studies demonstrate that the copula entropy method is not limited to existing copula types and exhibits superior computational efficiency and greater flexibility compared to conventional copula methods when handling mixed distributions and multimodal distributions.

KEYWORDS

Two-Dimensional Joint PDF; Copula Theory; Copula Entropy

CITE THIS PAPER

Zhuhao Zhang, Xuanyi Zhang, Yangang Zhao, Application of Copula Entropy in Constructing Two-Dimensional Joint PDF. Journal of Civil Engineering and Urban Planning (2025) Vol. 7: 136-147. DOI: http://dx.doi.org/10.23977/jceup.2025.070116.

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