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 |
Documentation:
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