Research Repository

Mean Empirical Likelihood

Liang, Wei and Dai, Hongsheng and He, Shuyuan (2019) 'Mean Empirical Likelihood.' Computational Statistics and Data Analysis, 138. 155 - 169. ISSN 0167-9473

[img]
Preview
Text
MEL_CSDA_r1.pdf - Accepted Version
Available under License Creative Commons Attribution Non-commercial No Derivatives.

Download (365kB) | Preview

Abstract

Empirical likelihood methods are widely used in different settings to construct the confidence regions for parameters which satisfy the moment constraints. However, the empirical likelihood ratio confidence regions may have poor accuracy, especially for small sample sizes and multi-dimensional situations. A novel Mean Empirical Likelihood (MEL) method is proposed. A new pseudo dataset using the means of observation values is constructed to define the empirical likelihood ratio and it is proved that this MEL ratio satisfies Wilks’ theorem. Simulations with different examples are given to assess its finite sample performance, which shows that the confidence regions constructed by Mean Empirical Likelihood are much more accurate than that of the other Empirical Likelihood methods.

Item Type: Article
Uncontrolled Keywords: Confidence interval, Empirical likelihood, Exponentially tilted likelihood, Two sample comparison
Subjects: Q Science > QA Mathematics
Divisions: Faculty of Science and Health > Mathematical Sciences, Department of
Depositing User: Elements
Date Deposited: 16 May 2019 11:11
Last Modified: 17 Apr 2020 01:00
URI: http://repository.essex.ac.uk/id/eprint/24427

Actions (login required)

View Item View Item