Weak convergence of the empirical copula process with respect to weighted metrics

DOI10.3150/15-BEJ751zbMath1367.60026arXiv1411.5888OpenAlexW2963009380MaRDI QIDQ502904

Betina Berghaus, Axel Bücher, Stanislav Volgushev

Publication date: 11 January 2017

Published in: Bernoulli (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1411.5888

zbMATH Keywords

weak convergencePickands dependence functionempirical copula processweighted metricsbivariate rank statistics

Mathematics Subject Classification ID

Multivariate distribution of statistics (62H10) Asymptotic properties of nonparametric inference (62G20) Central limit and other weak theorems (60F05) Functional limit theorems; invariance principles (60F17)

Related Items (16)

Quantile spectral processes: asymptotic analysis and inference ⋮ An estimator of the stable tail dependence function based on the empirical beta copula ⋮ Nonparametric inference for sensitivity of Haezendonck–Goovaerts risk measure ⋮ Efficient estimation of multivariate semi-nonparametric GARCH filtered copula models ⋮ A copula approach for dependence modeling in multivariate nonparametric time series ⋮ Estimation and inference in factor copula models with exogenous covariates ⋮ Inference for Archimax copulas ⋮ Inference for semiparametric Gaussian copula model adjusted for linear regression using residual ranks ⋮ Estimation of Copulas via Maximum Mean Discrepancy ⋮ A STATISTICAL METHODOLOGY FOR ASSESSING THE MAXIMAL STRENGTH OF TAIL DEPENDENCE ⋮ Weak convergence of the weighted empirical beta copula process ⋮ Subsampling (weighted smooth) empirical copula processes ⋮ Identifiability and estimation of meta-elliptical copula generators ⋮ Validation of association ⋮ Donsker results for the empirical process indexed by functions of locally bounded variation and applications to the smoothed empirical process ⋮ Testing exchangeability of copulas in arbitrary dimension

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