Nonparametric estimation of multivariate extreme-value copulas

DOI10.1016/j.jspi.2012.05.007zbMath1349.62207arXiv1107.2410OpenAlexW2002666430MaRDI QIDQ451184

Gordon Gudendorf, Johan Segers

Publication date: 21 September 2012

Published in: Journal of Statistical Planning and Inference (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1107.2410

zbMATH Keywords

weak convergencespectral measuresimplexPickands dependence functionempirical copulashape constraintsextreme-value copula

Mathematics Subject Classification ID

Estimation in multivariate analysis (62H12) Asymptotic properties of nonparametric inference (62G20) Nonparametric estimation (62G05) Characterization and structure theory for multivariate probability distributions; copulas (62H05) Statistics of extreme values; tail inference (62G32)

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Uses Software

• quadprog
• evd

Cites Work

• Unnamed Item
• Asymptotics of empirical copula processes under non-restrictive smoothness assumptions
• Nonparametric estimation of multivariate extreme-value copulas
• Nonparametric estimation of an extreme-value copula in arbitrary dimensions
• A goodness-of-fit test for bivariate extreme-value copulas
• New estimators of the Pickands dependence function and a test for extreme-value dependence
• The oscillation behavior of empirical processes: The multivariate case
• Rank-based inference for bivariate extreme-value copulas
• Nonparametric rank-based tests of bivariate extreme-value dependence
• On the limiting behavior of the Pickands estimator for bivariate extreme- value distributions
• Distribution and dependence-function estimation for bivariate extreme-value distributions.
• Simulating multivariate extreme value distributions of logistic type
• Weak convergence and empirical processes. With applications to statistics
• Nonparametric estimation of the dependence function for a multivariate extreme value distribution
• Modelling multivariate extreme value distributions
• A nonparametric estimation procedure for bivariate extreme value copulas
• Statistics of Extremes
• Projection estimators of Pickands dependence functions
• Semiparametric estimation in copula models
• Nonparametric estimation of the dependence function in bivariate extreme value distributions

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