Thresholding methods to estimate the copula density
Statistics Theory
2011-11-04 v1 Statistics Theory
Abstract
This paper deals with the problem of the multivariate copula density estimation. Using wavelet methods we provide two shrinkage procedures based on thresholding rules for which the knowledge of the regularity of the copula density to be estimated is not necessary. These methods, said to be adaptive, are proved to perform very well when adopting the minimax and the maxiset approaches. Moreover we show that these procedures can be discriminated in the maxiset sense. We produce an estimation algorithm whose qualities are evaluated thanks some simulation. Last, we propose a real life application for financial data.
Cite
@article{arxiv.0802.2424,
title = {Thresholding methods to estimate the copula density},
author = {Florent Autin and Erwan Le Pennec and Karine Tribouley},
journal= {arXiv preprint arXiv:0802.2424},
year = {2011}
}