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.
Escobar-Bach, M., Goegebeur, Y., & Guillou, A. (2018). Local estimation of the conditional stable tail dependence function. Scandinavian Journal of Statistics, 45(3), 590-617. https://doi.org/10.1111/sjos.12315