Discussion: Statistical models and methods for dependence in insurance data

DOI10.1016/j.jkss.2011.03.004zbMath1296.62203OpenAlexW2035640238MaRDI QIDQ458106

Martin Ruppert, Christian Genest, Johanna G. Nešlehová

Publication date: 30 September 2014

Published in: Journal of the Korean Statistical Society (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.jkss.2011.03.004

Mathematics Subject Classification ID

Related Items (8)

Some copula inference procedures adapted to the presence of ties ⋮ On the empirical multilinear copula process for count data ⋮ Testing Asymmetry in Dependence with Copula-Coskewness ⋮ Using B-splines for nonparametric inference on bivariate extreme-value copulas ⋮ Rejoinder on: Inference in multivariate Archimedean copula models ⋮ Asymptotic behavior of the empirical multilinear copula process under broad conditions ⋮ Bivariate integer-autoregressive process with an application to mutual fund flows ⋮ Nonparametric maximum likelihood estimation for dependent truncation data based on copulas

Cites Work

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• Validity of the parametric bootstrap for goodness-of-fit testing in semiparametric models
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• On rank correlation measures for non-continuous random variables
• Construction of asymmetric multivariate copulas
• Nonparametric rank-based tests of bivariate extreme-value dependence
• Estimating copula densities through wavelets
• Revisiting the Edge, Ten Years On
• On the Ghoudi, Khoudraji, and Rivest test for extreme-value dependence
• Propriétés statistiques des copules de valeurs extrêmes bidimensionnelles
• Non-Parametric Bayesian Inference on Bivariate Extremes
• On the properties of some nonparametric concordance measures in the discrete case
• A bayesian estimator for the dependence function of a bivariate extreme‐value distribution
• A Primer on Copulas for Count Data

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