Extending the scope of empirical likelihood

This paper extends the scope of empirical likelihood methodology in three directions: to allow for plug-in estimates of nuisance parameters in estimating equations, slower than √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

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Document type	Document de travail (Working Paper)
Access type	Accès libre
Publication date	2004
Language	Anglais
Number of pages	33 pages
Collection	STAT Discussion Papers - 0414
Affiliation	UCL - EUEN/STAT - Institut de statistique
Keywords	bootstrap calibration ; current status data ; empirical processes ; estimating equations ; growing number of parameters ; nonparametric regression ; nuisance parameters ; orthogonal series ; plug-in
Links	http://sites.uclouvain.be/IAP-Stat-Phase-V-VI/ISBApub/ISBAdp.html#2004 http://hdl.handle.net/2078.1/115244[Handle]

See also
	[boreal:35625]	Extending the Scope of Empirical Likelihood