Spatial median depth-based robust adjusted empirical likelihood

Lei Wang, Wendong Li, Guanfu Liu and Xiaolong Pu

Journal of Nonparametric Statistics, 2015, vol. 27, issue 4, 485-502

Abstract: Empirical likelihood (EL) based inference for parameters defined by general estimating equations of Qin and Lawless [(1994), 'Empirical Likelihood and General Estimating Equations', The Annals of Statistics , 22, 300-325] remains an active research topic. However, the performance of the EL method can be hindered by non-robustness and empty set problems. In this paper, we propose a robust adjusted empirical likelihood (RAEL) to address these two problems simultaneously. The resulting RAEL ratio statistic is shown to have inherited the asymptotic properties of both the robust empirical likelihood and the adjusted empirical likelihood. The finite-sample performance of the proposed method is illustrated by simulation and two real-data examples are also presented.

Date: 2015
References: Add references at CitEc
Citations:

Downloads: (external link)
http://hdl.handle.net/10.1080/10485252.2015.1072179 (text/html)
Access to full text is restricted to subscribers.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:taf:gnstxx:v:27:y:2015:i:4:p:485-502

Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/GNST20

DOI: 10.1080/10485252.2015.1072179

Access Statistics for this article

Journal of Nonparametric Statistics is currently edited by Jun Shao

More articles in Journal of Nonparametric Statistics from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().