eFCM-package: eFCM: Exponential Factor Copula Model

In eFCM: Exponential Factor Copula Model

eFCM: Exponential Factor Copula Model

Description

Implements the exponential Factor Copula Model (eFCM) of Castro-Camilo and Huser (2020) for spatial extremes, with tools for dependence estimation, tail inference,and visualization. The package supports likelihood-based inference, Gaussian process modeling via Matérn covariance functions, and bootstrap uncertainty quantification.

References

Castro-Camilo, D. & Huser, R. (2020). Local likelihood estimation of complex tail dependence structures, with application to U.S. precipitation extremes. Journal of the American Statistical Association, 115(531), 1037–1054. \Sexpr[results=rd]{tools:::Rd_expr_doi("10.1080/01621459.2019.1611584")}

Li, M. & Castro-Camilo, D. (2025). On the importance of tail assumptions in climate extreme event attribution. arXiv. \Sexpr[results=rd]{tools:::Rd_expr_doi("10.48550/arXiv.2507.14019")}

eFCM documentation built on Sept. 9, 2025, 5:52 p.m.