Nonparametric Universal Copula Modeling
Methodology
2019-12-12 v1 Applications
Computation
Abstract
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.
Cite
@article{arxiv.1912.05503,
title = {Nonparametric Universal Copula Modeling},
author = {Subhadeep Mukhopadhyay and Emanuel Parzen},
journal= {arXiv preprint arXiv:1912.05503},
year = {2019}
}
Comments
A perspective on "60 years of Copula"