Limit properties for multivariate extreme values in sequences of independent, non-identically distributed random vectors

J. Hüsler

Stochastic Processes and their Applications, 1989, vol. 31, issue 1, 105-116

Abstract: Any multivariate distribution can occur as the limit of extreme values in a sequence of independent, non-identically distributed random vectors. Under a reasonable uniform negligibility condition the class of such limit distribution can be totally characterized, which extends the known univariate results. In addition, some results on the dependence structure of a possible limit law are given, as for instance the independence, the positive lower orthant dependence or the association.

Keywords: multivariate; extremes; non; i.i.d.; random; vectors; u.a.n.; condition; limit; laws; dependence; structure (search for similar items in EconPapers)
Date: 1989
References: Add references at CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/0304-4149(89)90105-1
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:spapps:v:31:y:1989:i:1:p:105-116

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

Access Statistics for this article

Stochastic Processes and their Applications is currently edited by T. Mikosch

More articles in Stochastic Processes and their Applications from Elsevier
Bibliographic data for series maintained by Catherine Liu ().