Logo
Munich Personal RePEc Archive

Reduce computation in profile empirical likelihood method

Li, Minqiang and Peng, Liang and Qi, Yongcheng (2011): Reduce computation in profile empirical likelihood method.

[thumbnail of MPRA_paper_33744.pdf]
Preview
PDF
MPRA_paper_33744.pdf

Download (408kB) | Preview

Abstract

Since its introduction by Owen in [29, 30], the empirical likelihood method has been extensively investigated and widely used to construct confidence regions and to test hypotheses in the literature. For a large class of statistics that can be obtained via solving estimating equations, the empirical likelihood function can be formulated from these estimating equations as proposed by [35]. If only a small part of parameters is of interest, a profile empirical likelihood method has to be employed to construct confidence regions, which could be computationally costly. In this paper we propose a jackknife empirical likelihood method to overcome this computational burden. This proposed method is easy to implement and works well in practice.

Atom RSS 1.0 RSS 2.0

Contact us: mpra@ub.uni-muenchen.de

This repository has been built using EPrints software.

MPRA is a RePEc service hosted by Logo of the University Library LMU Munich.