Adjusted Jackknife Empirical Likelihood
Methodology
2016-03-15 v1
Abstract
Jackknife empirical likelihood (JEL) is an effective modified version of empirical likelihood method (EL). Through the construction of the jackknife pseudo-values, JEL overcomes the computational difficulty of EL method when its constraints are nonlinear while maintaining the same asymptotic results for one sample and two-sample U statistics. In this paper, we propose an adjusted version of JEL to guarantee that the adjusted jackknife empirical likelihood (AJEL) statistic is well-defined for all the values of the parameter, instead of restricting on the convex hull of the estimation equation. The properties of JEL have been preserved for AJEL.
Cite
@article{arxiv.1603.04093,
title = {Adjusted Jackknife Empirical Likelihood},
author = {Ying-Ju Chen and Wei Ning},
journal= {arXiv preprint arXiv:1603.04093},
year = {2016}
}