Robust nonparametric estimation of the conditional tail dependence coefficient

Yuri Goegebeur, Armelle Guillou*, Nguyen Khanh Le Ho, Jing Qin

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Abstrakt

We consider robust and nonparametric estimation of the coefficient of tail dependence in presence of random covariates. The estimator is obtained by fitting the extended Pareto distribution locally to properly transformed bivariate observations using the minimum density power divergence criterion. We establish convergence in probability and asymptotic normality of the proposed estimator under some regularity conditions. The finite sample performance is evaluated with a small simulation experiment, and the practical applicability of the method is illustrated on a real dataset of air pollution measurements.

OriginalsprogEngelsk
Artikelnummer104607
TidsskriftJournal of Multivariate Analysis
Vol/bind178
Antal sider20
ISSN0047-259X
DOI
StatusUdgivet - jul. 2020

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