Extending the scope of empirical likelihood

dc.creatorHjort, Nils Lid
dc.creatorMcKeague, Ian W.
dc.creatorVan Keilegom, Ingrid
dc.date2009-04-20
dc.date.accessioned2026-07-07T13:05:54Z
dc.date.available2026-07-07T13:05:54Z
dc.descriptionThis 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.
dc.descriptionPublished 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)
dc.identifierhttps://arxiv.org/abs/0904.2949
dc.identifierhttp://arxiv.org/abs/0904.2949
dc.identifierAnnals of Statistics 2009, Vol. 37, No. 3, 1079-1111
dc.identifierdoi:10.1214/07-AOS555
dc.identifier.urihttp://salesiana.dossiersoluciones.com/handle/123456789/227640
dc.subjectStatistics Theory
dc.subject62G20, 62F40 (Primary)
dc.titleExtending the scope of empirical likelihood
dc.typetext

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