Almost sure convergence of the stable tail empirical dependence function in multivariate extreme statistics

DOI10.1007/BF02015138zbMath0904.62061OpenAlexW1993927541MaRDI QIDQ1367249

Yongcheng Qi

Publication date: 21 September 1997

Published in: Acta Mathematicae Applicatae Sinica. English Series (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/bf02015138

zbMATH Keywords

multivariate extremesalmost sure convergencestrong consistencystable tail empirical dependence function

Mathematics Subject Classification ID

Asymptotic properties of nonparametric inference (62G20) Order statistics; empirical distribution functions (62G30) Strong limit theorems (60F15)

Related Items

Choice of smoothing parameter in multivariate copula-based tail coefficients ⋮ \(k\)-means clustering of extremes ⋮ Smoothed jackknife empirical likelihood method for tail copulas ⋮ Bias-corrected and robust estimation of the bivariate stable tail dependence function ⋮ Multiplier bootstrap of tail copulas with applications ⋮ Statistical models and methods for dependence in insurance data ⋮ Parametric tail copula estimation and model testing ⋮ Bootstrap approximation of tail dependence function ⋮ Dependence estimation and visualization in multivariate extremes with applications to financial data ⋮ Identifying groups of variables with the potential of being large simultaneously ⋮ Non-parametric Estimation of Tail Dependence ⋮ Nonparametric estimation of the spectral measure of an extreme value distribution.

Cites Work

• Unnamed Item
• A moment estimator for the index of an extreme-value distribution
• Statistical inference using extreme order statistics
• A simple general approach to inference about the tail of a distribution
• Limit theorems for the ratio of the empirical distribution function to the true distribution function