eFCM: Exponential Factor Copula Model
Implements the exponential Factor Copula Model (eFCM) of Castro-Camilo, D. and Huser, R. (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. See Castro-Camilo and Huser (2020) <doi:10.1080/01621459.2019.1647842>.
| Version: | 1.0 |
| Depends: | R (≥ 3.5.0) |
| Imports: | Rcpp,nsRFA,ismev,fields,mnormt,numDeriv,pbmcapply,boot,progress |
| LinkingTo: | Rcpp,RcppArmadillo |
| Suggests: | knitr,rmarkdown,testthat (≥ 3.0.0) |
| Published: | 2025-09-09 |
| DOI: | 10.32614/CRAN.package.eFCM |
| Author: | Mengran Li [aut, cre], Daniela Castro-Camilo [aut] |
| Maintainer: | Mengran Li <m.li.3 at research.gla.ac.uk> |
| License: | GPL (≥ 3) |
| NeedsCompilation: | yes |
| CRAN checks: | eFCM results |
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