Asymptotic confidence bands for copulas based on the local linear kernel estimator
Methodology
2015-10-02 v1
Abstract
In this paper we establish asymptotic simultaneous confidence bands for copulas based on the local linear kernel estimator proposed by Chen and Huang [1]. For this, we prove under smoothness conditions on the copula function, a uniform in bandwidth law of the iterated logarithm for the maximal deviation of this estimator from its expectation. We also show that the bias term converges uniformly to zero with a precise rate. The performance of these bands is illustrated in a simulation study. An application based on pseudo-panel data is also provided for modeling dependence.
Cite
@article{arxiv.1510.00071,
title = {Asymptotic confidence bands for copulas based on the local linear kernel estimator},
author = {Diam Ba and Cheikh Tidiane Seck and Gane Samb Lo},
journal= {arXiv preprint arXiv:1510.00071},
year = {2015}
}