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.
Publié le : 2009-06-15
Classification:
Bootstrap calibration,
current status data,
empirical processes,
estimating equations,
growing number of parameters,
nonparametric regression,
nuisance parameters,
orthogonal series,
plug-in,
62G20,
62F40
@article{1239369016,
author = {Hjort, Nils Lid and McKeague, Ian W. and Van Keilegom, Ingrid},
title = {Extending the scope of empirical likelihood},
journal = {Ann. Statist.},
volume = {37},
number = {1},
year = {2009},
pages = { 1079-1111},
language = {en},
url = {http://dml.mathdoc.fr/item/1239369016}
}
Hjort, Nils Lid; McKeague, Ian W.; Van Keilegom, Ingrid. Extending the scope of empirical likelihood. Ann. Statist., Tome 37 (2009) no. 1, pp. 1079-1111. http://gdmltest.u-ga.fr/item/1239369016/