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Identifiability and Estimation of Meta-elliptical Copula Generators by Derumigny, Alexis; Fermanian, Jean-David is a scholarly article available to read on EtoBox.

What is Identifiability and Estimation of Meta-elliptical Copula Generators about?

Meta-elliptical copulas are often proposed to model dependence between the components of a random vector. They are specified by a correlation matrix and a map $g$, called density generator. While the latter correlation matrix can easily be estimated from pseudo-samples of observations, the density generator is harder to estimate, especially when it does not belong to a parametric family. We give sufficient conditions to non-parametrically identify this generator. Several nonparametric estimators of $g$ are then proposed, by M-estimation, simulation-based inference, or by an iterative procedure available in the R package ElliptCopulas. Some simulations illustrate the relevance of the latter method.

Author

Derumigny, Alexis; Fermanian, Jean-David

Published

2021

Language

EN