Reduce Computation in Profile Empirical Likelihood Method
38 Pages Posted: 27 Apr 2013
Date Written: April 25, 2013
Since its introduction by Owen, 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 Qin, J. and Lawless, J.F. (1994). 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.
Keywords: profile empirical likelihood, estimating equation, Jackknife
JEL Classification: C10, C13
Suggested Citation: Suggested Citation