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Local Estimation of the Conditional Stable Tail Dependence Function
Author(s) -
EscobarBach Mikael,
Goegebeur Yuri,
Guillou Armelle
Publication year - 2018
Publication title -
scandinavian journal of statistics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.359
H-Index - 65
eISSN - 1467-9469
pISSN - 0303-6898
DOI - 10.1111/sjos.12315
Subject(s) - estimator , covariate , mathematics , statistics , econometrics , consistent estimator , sample (material) , minimum variance unbiased estimator , physics , thermodynamics
We consider the local estimation of the stable tail dependence function when a random covariate is observed together with the variables of main interest. Our estimator is a weighted version of the empirical estimator adapted to the covariate framework. We provide the main asymptotic properties of our estimator, when properly normalized, in particular the convergence of the empirical process towards a tight centred Gaussian process. The finite sample performance of our estimator is illustrated on a small simulation study and on a dataset of air pollution measurements.