Empirical likelihood confidence intervals for M-functionals in the presence of auxiliary information

Biao Zhang

Statistics & Probability Letters, 1997, vol. 32, issue 1, 87-97

Abstract: In this paper, we employ the method of empirical likelihood to construct confidence intervals for M-functionals in the presence of auxiliary information under a nonparametric setting. The modified empirical likelihood confidence intervals which make use of the knowledge of auxiliary information are asymptotically at least as narrow as the standard ones which do not utilize auxiliary information. For testing a hypothesis about a M-functional, the power of a test statistic based on the modified empirical likelihood ratio is larger than the one based on the standard empirical likelihood ratio. A simulation study is presented to demonstrate the performance of the modified empirical likelihood confidence intervals for small samples.

Keywords: Coverage; probability; Empirical; likelihood; ratio; Hypothesis; Power (search for similar items in EconPapers)
Date: 1997
References: View complete reference list from CitEc
Citations: View citations in EconPapers (3)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0167-7152(96)00060-0
Full text for ScienceDirect subscribers only

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:eee:stapro:v:32:y:1997:i:1:p:87-97

Ordering information: This journal article can be ordered from
http://www.elsevier.com/wps/find/supportfaq.cws_home/regional
https://shop.elsevie ... _01_ooc_1&version=01

Access Statistics for this article

Statistics & Probability Letters is currently edited by Somnath Datta and Hira L. Koul

More articles in Statistics & Probability Letters from Elsevier
Bibliographic data for series maintained by Catherine Liu ().