Estimation of the multivariate conditional tail expectation for extreme risk levels: illustration on environmental data sets
From MaRDI portal
Publication:6626007
DOI10.1002/ENV.2510zbMATH Open1545.62751MaRDI QIDQ6626007
Elena Di Bernardino, Clémentine Prieur
Publication date: 28 October 2024
Published in: Environmetrics (Search for Journal in Brave)
central limit theoremmultivariate risk measuresmultivariate extreme value theoryhydrological applications
Cites Work
- Title not available (Why is that?)
- Title not available (Why is that?)
- Title not available (Why is that?)
- Title not available (Why is that?)
- Weighted approximations of tail copula processes with application to testing the bivariate extreme value condition
- Second order regular variation and conditional tail expectation of multiple risks
- TVaR-based capital allocation with copulas
- On multivariate extensions of conditional-tail-expectation
- Quantile curves and dependence structure for bivariate distributions
- A simple general approach to inference about the tail of a distribution
- An introduction to copulas. Properties and applications
- Best attainable rates of convergence for estimators of the stable tail dependence function
- Kendall distribution functions.
- Bivariate tail estimation: dependence in asymptotic independence
- On Kendall's process
- Large quantile estimation in a multivariate setting
- Second-order properties of the Haezendonck-Goovaerts risk measure for extreme risks
- Conditional tail expectations for multivariate phase-type distributions
- Goodness-of-fit Procedures for Copula Models Based on the Probability Integral Transformation
- Estimation of Parameters and Larger Quantiles Based on the k Largest Observations
- Statistics of Extremes
- Empirical processes indexed by estimated functions
- Estimation of the Marginal Expected Shortfall: the Mean When a Related Variable is Extreme
- Plug-in estimation of level sets in a non-compact setting with applications in multivariate risk theory
- Estimation of multivariate conditional-tail-expectation using Kendall's process
- Tail Conditional Expectations for Elliptical Distributions
- On the multivariate probability integral transformation
- Estimation of extreme quantiles conditioning on multivariate critical layers
- A semi-parametric stochastic generator for bivariate extreme events
- Directional multivariate extremes in environmental phenomena
Related Items (4)
Monge-Kantorovich superquantiles and expected shortfalls with applications to multivariate risk measurements ⋮ Reduced-bias estimation of the extreme conditional tail expectation for Box-Cox transforms of heavy-tailed distributions ⋮ Estimation of marginal excess moments for Weibull-type distributions ⋮ Multivariate modeling of precipitation-induced home insurance risks using data depth
This page was built for publication: Estimation of the multivariate conditional tail expectation for extreme risk levels: illustration on environmental data sets
Report a bug (only for logged in users!)Click here to report a bug for this page (MaRDI item Q6626007)
