Identifiability and estimation of meta-elliptical copula generators

Journal Article (2022)
Author(s)

Alexis Derumigny (TU Delft - Statistics)

Jean David Fermanian (CREST-ENSAE)

Research Group
Statistics
Copyright
© 2022 Alexis Derumigny, J. D. Fermanian
DOI related publication
https://doi.org/10.1016/j.jmva.2022.104962
More Info
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Publication Year
2022
Language
English
Copyright
© 2022 Alexis Derumigny, J. D. Fermanian
Research Group
Statistics
Volume number
190
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Abstract

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.

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