Exponential Factor Copula Model
Akaike Information Criterion (AIC) for fcm objects
Corrected Akaike Information Criterion (AICc) for fcm objects
Bayesian Information Criterion (BIC) for fcm objects
Tail Dependence Coefficient (Chi Statistic)
Chi Plot for Fitted eFCM Model
Extract Model Coefficients
eFCM: Exponential Factor Copula Model
Fit the exponential Factor Copula Model (eFCM)
Transform datasets for factor copula modeling
Log-likelihood of a fitted factor copula model
Homogeneous neighborhood selection
The Distribution of Univariate Factor Copula Model
CDF of the exponential Factor Copula Model (vector input)
Q–Q Plot for Fitted Factor Copula Model
Random generation from the exponential Factor Copula Model (eFCM)
Summarizing Factor Copula Model Fits
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>.