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Fitting Copulas with Maximal Entropy

. 2025 Jan 18 ; 27 (1) : . [epub] 20250118

Status PubMed-not-MEDLINE Language English Country Switzerland Media electronic

Document type Journal Article

Grant support
13000 Czech Technical University in Prague

We deal with two-dimensional copulas from the perspective of their differential entropy. We formulate a problem of finding a copula with maximum differential entropy when some copula values are given. As expected, the solution is a copula with a piecewise constant density (a checkerboard copula). This allows us to simplify the optimization of the continuous objective function, the differential entropy, to an optimization of finitely many density values. We present several ideas to simplify this problem. It has a feasible numerical solution. We also present several instances that admit closed-form solutions.

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Nelsen R.B. An Introduction to Copulas. 2nd ed. Volume 139 Springer; New York, NY, USA: 2006. Lecture Notes in Statistics.

Sklar A. Fonctions de Répartition à n Dimensions et Leurs Marges. Publ. Inst. Statist. Univ. Paris. 1959;8:229–231.

Shannon C.E. A Mathematical Theory of Communication. Bell Syst. Tech. J. 1948;27:379–423. doi: 10.1002/j.1538-7305.1948.tb01338.x. DOI

Jaynes E.T. Information theory and statistical mechanics. Phys. Rev. 1957;106:620–628. doi: 10.1103/PhysRev.106.620. DOI

Pougaza D.B., Mohammad-Djafari A. Maximum Entropies Copulas; Proceedings of the 30th International Workshop on Bayesian Inference and Maximum Entropy Methods in Science and Engineering; Chamonix, France. 4–9 July 2010; [(accessed on 7 October 2024)]. pp. 329–336. Available online: https://pubs.aip.org/aip/acp/article-pdf/1305/1/329/11567694/329_1_online.pdf.

Pougaza D.B., Mohammad-Djafari A., Bercher J.F. Link between copula and tomography. Pattern Recognit. Lett. 2010;31:2258–2264. doi: 10.1016/j.patrec.2010.05.001. DOI

Ma J., Sun Z. Mutual information is copula entropy. Tsinghua Sci. Technol. 2011;16:51–54. doi: 10.1016/S1007-0214(11)70008-6. DOI

Singh V.P., Zhang L. Copula–entropy theory for multivariate stochastic modeling in water engineering. Geosci. Lett. 2018;5:6. doi: 10.1186/s40562-018-0105-z. DOI

Piantadosi J., Howlett P., Boland J.W. Matching the grade correlation coefficient using a copula with maximum disorder. J. Ind. Manag. Optim. 2007;3:305–312. doi: 10.3934/jimo.2007.3.305. DOI

Piantadosi J., Howlett P., Borwein J. Copulas with Maximum Entropy. Optim. Lett. 2012;6:99–125. doi: 10.1007/s11590-010-0254-2. DOI

Lin L., Wang R., Zhang R., Zhao C. The checkerboard copula and dependence concepts. [(accessed on 7 October 2024)];arXiv. 2024 Available online: http://arxiv.org/abs/arXiv:2404.15023.2404.15023

Genest C., Nešlehová J.G., Rémillard B. Asymptotic behavior of the empirical multilinear copula process under broad conditions. J. Multivar. Anal. 2017;159:82–110. doi: 10.1016/j.jmva.2017.04.002. DOI

Dibala M., Navara M. Discrete Copulas and Maximal Entropy Principle; Proceedings of the Copulas and Their Applications; Almeria, Spain. 3–5 July 2017; p. 24.

Bubák M. Bachelor’s Thesis. Czech Technical University in Prague; Prague, Czech Republic: 2024. [(accessed on 7 October 2024)]. Copulas with Maximal Entropy (in Czech) Available online: http://hdl.handle.net/10467/115430.

Bertsekas D.P., Nedić A., Ozdaglar A.E. Convex Analysis and Optimization. Athena Scientific; Nashua, NH, USA: 2003.

Boyd S., Vandenberghe L. Convex Optimization. Cambridge University Press; Cambridge, UK: 2004.

Hiriart-Urruty J., Lemaréchal C. Fundamentals of Convex Analysis. Springer; Berlin/Heidelberg, Germany: 2004. Grundlehren Text Editions.

Rockafellar R.T. Convex Analysis. Princeton University Press; Princeton, NJ, USA: 1970. (Princeton Mathematical Series).

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