242 citations · 778 across the 62 of their papers we have counts for
6 papers · 2 filters
Tails of correlation mixtures of elliptical copulas
Hans Manner, Johan Segers
Correlation mixtures of elliptical copulas arise when the correlation parameter is driven itself by a latent random process. For such copulas, both penultimate and asymptotic tail…
Extreme-Value Copulas
Gordon Gudendorf, Johan Segers
Being the limits of copulas of componentwise maxima in independent random samples, extreme-value copulas can be considered to provide appropriate models for the dependence structur…
Nonparametric Bayesian Inference on Bivariate Extremes
Simon Guillotte, Francois Perron, Johan Segers
The tail of a bivariate distribution function in the domain of attraction of a bivariate extreme-value distribution may be approximated by the one of its extreme-value attractor. T…
Nonparametric estimation of an extreme-value copula in arbitrary dimensions
Gordon Gudendorf, Johan Segers
Inference on an extreme-value copula usually proceeds via its Pickands dependence function, which is a convex function on the unit simplex satisfying certain inequality constraints…
On the covariance of the asymptotic empirical copula process
Christian Genest, Johan Segers
Conditions are given under which the empirical copula process associated with a random sample from a bivariate continuous distribution has a smaller asymptotic covariance function…
Second-order refined peaks-over-threshold modelling for heavy-tailed distributions
Jan Beirlant, Elisabeth Joossens, Johan Segers
Modelling excesses over a high threshold using the Pareto or generalized Pareto distribution (PD/GPD) is the most popular approach in extreme value statistics. This method typicall…