Large-sample tests of extreme-value dependence for multivariate copulas

DOI10.1002/cjs.10110zbMath1284.62333arXiv1105.2220OpenAlexW1995524554MaRDI QIDQ3108012

Jun Yan, Ivan Kojadinovic, Johan Segers

Publication date: 28 December 2011

Published in: Canadian Journal of Statistics (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1105.2220

zbMATH Keywords

rankspseudo-observationsmultiplier central limit theoremmax-stability

Mathematics Subject Classification ID

Applications of statistics to actuarial sciences and financial mathematics (62P05) Hypothesis testing in multivariate analysis (62H15) Order statistics; empirical distribution functions (62G30) Statistics of extreme values; tail inference (62G32) Nonparametric statistical resampling methods (62G09) Applications of statistics to physics (62P35)

Related Items (20)

A dependent multiplier bootstrap for the sequential empirical copula process under strong mixing ⋮ A flexible and tractable class of one-factor copulas ⋮ Some copula inference procedures adapted to the presence of ties ⋮ A moment-based test for extreme-value dependence ⋮ A Test for Truncation Invariant Dependence ⋮ A modeler's guide to extreme value software ⋮ Inference for Archimax copulas ⋮ Modeling Influenza-Like Illness Activity in the United States ⋮ Joint and conditional dependence modelling of peak district heating demand and outdoor temperature: a copula-based approach ⋮ GOODNESS-OF-FIT TESTS FOR MULTIVARIATE COPULA-BASED TIME SERIES MODELS ⋮ Using B-splines for nonparametric inference on bivariate extreme-value copulas ⋮ Extreme value copula estimation based on block maxima of a multivariate stationary time series ⋮ A class of multivariate copulas based on products of bivariate copulas ⋮ Testing for a \(\delta \)-neighborhood of a generalized Pareto copula ⋮ Nonparametric rank-based tests of bivariate extreme-value dependence ⋮ Detecting changes in cross-sectional dependence in multivariate time series ⋮ Nonparametric inference for max-stable dependence ⋮ Nonparametric sequential change-point detection for multivariate time series based on empirical distribution functions ⋮ Some results on change-point detection in cross-sectional dependence of multivariate data with changes in marginal distributions ⋮ Conditional empirical copula processes and generalized measures of association

Uses Software

• R
• copula

Cites Work

• Unnamed Item
• A goodness-of-fit test for bivariate extreme-value copulas
• The oscillation behavior of empirical processes: The multivariate case
• An introduction to copulas.
• Construction of asymmetric multivariate copulas
• Testing for equality between two copulas
• Weak convergence of empirical copula processes
• Modelling multivariate extreme value distributions
• On the Ghoudi, Khoudraji, and Rivest test for extreme-value dependence
• Bivariate extreme value theory: Models and estimation
• Propriétés statistiques des copules de valeurs extrêmes bidimensionnelles
• Empirical processes indexed by estimated functions
• Understanding Relationships Using Copulas
• Semiparametric estimation in copula models
• A kolmogorov-smirnov type test for positive quadrant dependence

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