Comparing Empirical Likelihood and Bootstrap Hypothesis Tests

The Bootstrap and Empirical Likelihood

We point out connections between the bootstrap and empirical likelihood and indicate how the other pre sentations in the session The Bootstrap and Empir ical Likelihood at the Joint Statistical Meet ings t into this framework Empirical Likelihood for a mean The goal of this article is to point out connections be tween the bootstrap and empirical likelihood EL We consider only univariate statist...

Bootstrap and empirical likelihood methods in extremes

One of the major interests in extreme-value statistics is to infer the tail properties of the distribution functions in the domain of attraction of an extreme-value distribution and to predict rare events. In recent years, much effort in developing new methodologies has been made by many researchers in this area so as to diminish the impact of the bias in the estimation and achieve some asympto...

The Bootstrap and Hypothesis Tests in Econometrics

Bootstrap Tilting Conndence Intervals and Hypothesis Tests

Bootstrap tilting conndence intervals could be the method of choice in many applications for reasons of both speed and accuracy. With the right implementation , tilting intervals are 37 times as fast as bootstrap BC-a limits, in terms of the number of bootstrap samples needed for comparable simulation accuracy. Thus 100 bootstrap samples might suuce instead of 3700. Tilting limits have other de...

Nonparametric Bootstrap for Quasi-Likelihood Ratio Tests∗

We introduce a nonparametric bootstrap approach for Quasi-Likelihood Ratio type tests of nonlinear restrictions. Our method applies to extremum estimators, such as quasimaximum likelihood and generalized method of moments estimators. Unlike existing parametric bootstrap procedures for Quasi-Likelihood Ratio type tests, our procedure constructs bootstrap samples in a fully nonparametric way. We ...