The Annals of Applied Probability

Limit laws for random vectors with an extreme component

Janet E. Heffernan and Sidney I. Resnick

Full-text: Open access

Abstract

Models based on assumptions of multivariate regular variation and hidden regular variation provide ways to describe a broad range of extremal dependence structures when marginal distributions are heavy tailed. Multivariate regular variation provides a rich description of extremal dependence in the case of asymptotic dependence, but fails to distinguish between exact independence and asymptotic independence. Hidden regular variation addresses this problem by requiring components of the random vector to be simultaneously large but on a smaller scale than the scale for the marginal distributions. In doing so, hidden regular variation typically restricts attention to that part of the probability space where all variables are simultaneously large. However, since under asymptotic independence the largest values do not occur in the same observation, the region where variables are simultaneously large may not be of primary interest. A different philosophy was offered in the paper of Heffernan and Tawn [J. R. Stat. Soc. Ser. B Stat. Methodol. 66 (2004) 497–546] which allows examination of distributional tails other than the joint tail. This approach used an asymptotic argument which conditions on one component of the random vector and finds the limiting conditional distribution of the remaining components as the conditioning variable becomes large. In this paper, we provide a thorough mathematical examination of the limiting arguments building on the orientation of Heffernan and Tawn [J. R. Stat. Soc. Ser. B Stat. Methodol. 66 (2004) 497–546]. We examine the conditions required for the assumptions made by the conditioning approach to hold, and highlight simililarities and differences between the new and established methods.

Article information

Source
Ann. Appl. Probab., Volume 17, Number 2 (2007), 537-571.

Dates
First available in Project Euclid: 19 March 2007

Permanent link to this document
https://projecteuclid.org/euclid.aoap/1174323256

Digital Object Identifier
doi:10.1214/105051606000000835

Mathematical Reviews number (MathSciNet)
MR2308335

Zentralblatt MATH identifier
1125.60049

Subjects
Primary: 60G70: Extreme value theory; extremal processes
Secondary: 62G32: Statistics of extreme values; tail inference

Keywords
Conditional models heavy tails regular variation coefficient of tail dependence hidden regular variation asymptotic independence

Citation

Heffernan, Janet E.; Resnick, Sidney I. Limit laws for random vectors with an extreme component. Ann. Appl. Probab. 17 (2007), no. 2, 537--571. doi:10.1214/105051606000000835. https://projecteuclid.org/euclid.aoap/1174323256


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