Bootstrapping Regression Models via Empirical Likelihood Resampling

In this paper an empirical likelihood resampling is proposed for bootstrapping studentizedleast square estimation in linear regression models. It is proved that our method captures ageneral s-2 term Edgeworth expansion and achieves a second order accuracy, furthermore, ithas smaller loss than the classical one in most cases.