Multivariate Tail Estimation: Conditioning on an extreme event
Methodology
2015-02-26 v1
Abstract
We consider regularly varying random vectors. Our goal is to estimate in a non-parametric way some characteristics related to conditioning on an extreme event, like the tail dependence coefficient. We introduce a quasi-spectral decomposition that allow to improve efficiency of estimators. Asymptotic normality of estimators is based on weak convergence of tail empirical processes. Theoretical results are supported by simulation studies.
Cite
@article{arxiv.1502.07189,
title = {Multivariate Tail Estimation: Conditioning on an extreme event},
author = {Rafał Kulik and Zhigang Tong},
journal= {arXiv preprint arXiv:1502.07189},
year = {2015}
}
Comments
8 figures