Large deviations for L-statistics

Boistard Hélène

Statistics & Risk Modeling, 2007, vol. 25, issue 2, 89-125

Abstract: The purpose of this paper is to establish a functional large deviations principle (LDP) for L-statistics under some new tail conditions. The method is based on Sanov's theorem and on basic tools of large deviations theory. Our study includes a full treatment of the case of the uniform law and an example in which the rate function can be calculated very precisely. We extend our result by an LDP for normalized L-statistics. The case of the exponential distribution, which is not in the scope of the previous conditions, is completely treated with another method. We provide a functional LDP obtained via Gärtner–Ellis theorem.

Keywords: large deviations; L-statistics (search for similar items in EconPapers)
Date: 2007
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://doi.org/10.1524/stnd.2007.25.2.89 (text/html)
For access to full text, subscription to the journal or payment for the individual article is required.

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:bpj:strimo:v:25:y:2007:i:2/2007:p:37:n:3

Ordering information: This journal article can be ordered from
https://www.degruyter.com/journal/key/strm/html

DOI: 10.1524/stnd.2007.25.2.89

Access Statistics for this article

Statistics & Risk Modeling is currently edited by Robert Stelzer

More articles in Statistics & Risk Modeling from De Gruyter
Bibliographic data for series maintained by Peter Golla ().