Nonparametric Universal Copula Modeling
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Abstract (arXiv)
To handle the ubiquitous problem of "dependence learning," copulas are quickly becoming a pervasive tool across a wide range of data-driven disciplines encompassing neuroscience, finance, econometrics, genomics, social science, machine learning, healthcare and many more. Copula (or connection) functions were invented in 1959 by Abe Sklar in response to a query of Maurice Frechet. After 60 years, where do we stand now? This article provides a history of the key developments and offers a unified perspective.
Key facts. Cited by 2 papers in the map (data through 14 Oct 2026). First posted on arXiv 11 Dec 2019.
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Citing papers per year: 2021: 1; 2022: 0; 2023: 1.
2 papers.
- 2021Abductive Inference and C. S. Peirce: 150 Years Latercited by 0
- 20232-Cats: 2D Copula Approximating Transformscited by 0
- 20232-Cats: 2D Copula Approximating Transforms28 Sep 2023
- 2021Abductive Inference and C. S. Peirce: 150 Years Later15 Nov 2021