Superefficient estimation of the marginals by exploiting knowledge on the copula
We consider the problem of estimating the marginals in the case where there is knowledge on the copula. If the copula is smooth, it is known that it is possible to improve on the empirical distribution functions: optimal estimators still have a rate of convergence n-1/2, but a smaller asymptotic variance. In this paper we show that for non-smooth copulas it is sometimes possible to construct superefficient estimators of the marginals: we construct both a copula and, exploiting the information our copula provides, estimators of the marginals with the rate of convergence logn/n.
Year of publication: |
2011
|
---|---|
Authors: | Einmahl, John H.J. ; van den Akker, Ramon |
Published in: |
Journal of Multivariate Analysis. - Elsevier, ISSN 0047-259X. - Vol. 102.2011, 9, p. 1315-1319
|
Publisher: |
Elsevier |
Keywords: | Copula Estimation of marginals Superefficient estimation |
Saved in:
Online Resource
Saved in favorites
Similar items by person
-
Estimating the spectral measure of an extreme value distribution
Einmahl, John H.J., (1997)
-
VaR stress tests for highly non-linear portfolios
Einmahl, John H.J., (2005)
-
Specification tests in nonparametric regression
Einmahl, John H.J., (2008)
- More ...