R/eFCM-package.R

In eFCM: Exponential Factor Copula Model

#' eFCM: Exponential Factor Copula Model
#'
#' 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.
#'
#' @docType package
#' @name eFCM-package
#'
#' @references
#' Castro-Camilo, D. & Huser, R. (2020).
#' Local likelihood estimation of complex tail dependence structures, with application
#' to U.S. precipitation extremes. \emph{Journal of the American Statistical Association},
#' \strong{115}(531), 1037–1054. \doi{10.1080/01621459.2019.1611584}
#'
#' Li, M. & Castro-Camilo, D. (2025).
#' On the importance of tail assumptions in climate extreme event attribution.
#' \emph{arXiv}. \doi{10.48550/arXiv.2507.14019}
#'
#' @useDynLib eFCM, .registration = TRUE
#' @importFrom Rcpp sourceCpp
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