Robust empirical likelihood for linear models under median constraints

In this paper, we consider the application of the empirical likelihood for linear models under median constraints in view of robustness. For two simple median constraints, it is shown that conditions to ensure the consistency of the empirical likelihood confidence regions can be surprisingly relaxed...

Full description

Saved in:
Bibliographic Details
Published inCommunications in statistics. Theory and methods Vol. 28; no. 10; pp. 2456 - 2476
Main Authors Shi, Jian, Lau, Tai-Shing
Format Journal Article
LanguageEnglish
Published Marcel Dekker, Inc 01.01.1999
Subjects
empirical likelihood
linear model
median constraint
robustness
smoothing
Online AccessGet full text

Cover

More Information
Summary:In this paper, we consider the application of the empirical likelihood for linear models under median constraints in view of robustness. For two simple median constraints, it is shown that conditions to ensure the consistency of the empirical likelihood confidence regions can be surprisingly relaxed compared with the normal approach under L norm. However, the coverage accuracy of the empirical likelihood confidence regions based on simple median constrains cannot be improved because of the discontinuity of the constraints. Therefore, a smoothed version of median constraint is proposed and a general theory is established to ensure its validity.
ISSN:0361-0926
1532-415X
DOI:10.1080/03610929908832430