Extending the scope of empirical likelihood

Thumbnail Image

Date

Authors

Journal Title

Journal ISSN

Volume Title

Publisher

Abstract

Description

This article extends the scope of empirical likelihood methodology in three directions: to allow for plug-in estimates of nuisance parameters in estimating equations, slower than $\sqrt{n}$-rates of convergence, and settings in which there are a relatively large number of estimating equations compared to the sample size. Calibrating empirical likelihood confidence regions with plug-in is sometimes intractable due to the complexity of the asymptotics, so we introduce a bootstrap approximation that can be used in such situations. We provide a range of examples from survival analysis and nonparametric statistics to illustrate the main results.
Published in at http://dx.doi.org/10.1214/07-AOS555 the Annals of Statistics (http://www.imstat.org/aos/) by the Institute of Mathematical Statistics (http://www.imstat.org)

Keywords

Statistics Theory, 62G20, 62F40 (Primary)

Citation

URI

http://salesiana.dossiersoluciones.com/handle/123456789/227640

Consulte el texto completo en el siguiente enlace:

https://arxiv.org/abs/0904.2949
 http://arxiv.org/abs/0904.2949
 Annals of Statistics 2009, Vol. 37, No. 3, 1079-1111
 doi:10.1214/07-AOS555

Collections

arXiv