Get 20M+ Full-Text Papers For Less Than $1.50/day. Start a 14-Day Trial for You or Your Team.

Learn More →

Extreme value distributions for dependent jointly ln,p-symmetrically distributed random variables

Extreme value distributions for dependent jointly ln,p-symmetrically distributed random variables AbstractA measure-of-cone representation of skewed continuous ln,p-symmetric distributions, n ∈ N, p > 0,is proved following the geometric approach known for elliptically contoured distributions. On this basis, distributionsof extreme values of n dependent random variables are derived if the latter follow a joint continuousln,p-symmetric distribution. Light, heavy, and extremely far tails as well as tail indices are discussed,and new parameters of multivariate tail behavior are introduced. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Dependence Modeling de Gruyter

Extreme value distributions for dependent jointly ln,p-symmetrically distributed random variables

Müller, K.; Richter, W.-D.
Dependence Modeling , Volume 4 (1): 1 – Feb 22, 2016
Download PDF
33 pages

Loading next page...
 
/lp/de-gruyter/extreme-value-distributions-for-dependent-jointly-ln-p-symmetrically-0JL3mD9bUL
Publisher
de Gruyter
Copyright
© 2016 K. Müller and W.-D. Richter
ISSN
2300-2298
eISSN
2300-2298
DOI
10.1515/demo-2016-0002
Publisher site
See Article on Publisher Site

Abstract

AbstractA measure-of-cone representation of skewed continuous ln,p-symmetric distributions, n ∈ N, p > 0,is proved following the geometric approach known for elliptically contoured distributions. On this basis, distributionsof extreme values of n dependent random variables are derived if the latter follow a joint continuousln,p-symmetric distribution. Light, heavy, and extremely far tails as well as tail indices are discussed,and new parameters of multivariate tail behavior are introduced.

Journal

Dependence Modeling – de Gruyter

Published: Feb 22, 2016

There are no references for this article.