6 citations · 6 across the 5 of their papers we have counts for
6 papers
A Tractable Family of Smooth Copulas with Rotational Dependence: Properties, Inference, and Application
Michaël Lalancette, Robert Zimmerman
We introduce a new family of copula densities constructed from univariate distributions on . Although our construction is structurally simple, the resulting family is versat…
Graphical models for multivariate extremes
Sebastian Engelke, Manuel Hentschel, Michaël Lalancette +1
Graphical models in extremes have emerged as a diverse and quickly expanding research area in extremal dependence modeling. They allow for parsimonious statistical methodology and…
On pairwise interaction multivariate Pareto models
Michaël Lalancette
The rich class of multivariate Pareto distributions forms the basis of recently introduced extremal graphical models. However, most existing literature on the topic is focused on t…
A new family of smooth copulas with arbitrarily irregular densities
Michaël Lalancette, Robert Zimmerman
Copulas are known to satisfy a number of regularity properties, and one might therefore believe that their densities, when they exist, admit a certain degree of regularity themselv…
Learning extremal graphical structures in high dimensions
Sebastian Engelke, Michaël Lalancette, Stanislav Volgushev
Extremal graphical models encode the conditional independence structure of multivariate extremes. Key statistics for learning extremal graphical structures are empirical extremal v…
Rank-based Estimation under Asymptotic Dependence and Independence, with Applications to Spatial Extremes
Michaël Lalancette, Sebastian Engelke, Stanislav Volgushev
Multivariate extreme value theory is concerned with modeling the joint tail behavior of several random variables. Existing work mostly focuses on asymptotic dependence, where the p…