loglik_HR: Compute Huesler-Reiss log-likelihood, AIC, and BIC

In sebastian-engelke/graphicalExtremes: Statistical Methodology for Graphical Extreme Value Models

Compute Huesler-Reiss log-likelihood, AIC, and BIC

Description

Computes (censored) Huesler-Reiss log-likelihood, AIC, and BIC values.

Usage

loglik_HR(data, p = NULL, graph = NULL, Gamma, cens = FALSE)

Arguments

data	Numeric \nxd matrix. It contains observations following a multivariate HR Pareto distribution.
p	Numeric between 0 and 1 or NULL. If NULL (default), it is assumed that the data are already on multivariate Pareto scale. Else, p is used as the probability in the function data2mpareto() to standardize the data.
graph	An [igraph::graph] object or NULL. The graph must be undirected and connected. If no graph is specified, the complete graph is used.
Gamma	Numeric \nxd matrix. It represents a variogram matrix \eGamma.
cens	Boolean. If true, then censored log-likelihood is computed. By default, cens = FALSE.

Value

Numeric vector c("loglik"=..., "aic"=..., "bic"=...) with the evaluated log-likelihood, AIC, and BIC values.

See Also

Other parameter estimation methods: data2mpareto(), emp_chi(), emp_chi_multdim(), emp_vario(), emtp2(), fmpareto_HR_MLE(), fmpareto_graph_HR()

sebastian-engelke/graphicalExtremes documentation built on Jan. 10, 2025, 10:02 a.m.