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Concomitant tail behaviour for extremes

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Concomitant tail behaviour for extremes. / Ledford, Anthony W.; Tawn, Jonathan A.
In: Advances in Applied Probability, Vol. 30, No. 1, 31.03.1998, p. 197-215.

Research output: Contribution to Journal/Magazine › Journal article › peer-review

Harvard

Ledford, AW & Tawn, JA 1998, 'Concomitant tail behaviour for extremes', Advances in Applied Probability, vol. 30, no. 1, pp. 197-215. https://doi.org/10.1017/S0001867800008168

APA

Ledford, A. W., & Tawn, J. A. (1998). Concomitant tail behaviour for extremes. Advances in Applied Probability, 30(1), 197-215. https://doi.org/10.1017/S0001867800008168

Vancouver

Ledford AW, Tawn JA. Concomitant tail behaviour for extremes. Advances in Applied Probability. 1998 Mar 31;30(1):197-215. doi: 10.1017/S0001867800008168

Author

Ledford, Anthony W. ; Tawn, Jonathan A. / Concomitant tail behaviour for extremes. In: Advances in Applied Probability. 1998 ; Vol. 30, No. 1. pp. 197-215.

Bibtex

@article{36b5247a6b264e96932f99f9cd18e274,
title = "Concomitant tail behaviour for extremes",
abstract = "The influence of bivariate extremal dependence on the limiting behaviour of the concomitant of the largest order statistic is examined. Our approach is to fix the marginal distributions and derive a general tail characterisation of the joint survivor function. From this, we identify the normalisation required to obtain the limiting distribution of the concomitant of the largest order statistic, obtain its tail form, and investigate the limiting probability that the vector of componentwise maxima occurs as an observation of the bivariate process. The results are illustrated for a range of extremal dependence forms.",
keywords = "Asymptotic independence, Bivariate extreme value distribution, Coefficient of tail dependence, Concomitants, Extreme value theory, Induced order statistics, Order statistics, Slowly varying functions",
author = "Ledford, {Anthony W.} and Tawn, {Jonathan A.}",
year = "1998",
month = mar,
day = "31",
doi = "10.1017/S0001867800008168",
language = "English",
volume = "30",
pages = "197--215",
journal = "Advances in Applied Probability",
issn = "0001-8678",
publisher = "University of Sheffield",
number = "1",

}

RIS

TY - JOUR

T1 - Concomitant tail behaviour for extremes

AU - Ledford, Anthony W.

AU - Tawn, Jonathan A.

PY - 1998/3/31

Y1 - 1998/3/31

N2 - The influence of bivariate extremal dependence on the limiting behaviour of the concomitant of the largest order statistic is examined. Our approach is to fix the marginal distributions and derive a general tail characterisation of the joint survivor function. From this, we identify the normalisation required to obtain the limiting distribution of the concomitant of the largest order statistic, obtain its tail form, and investigate the limiting probability that the vector of componentwise maxima occurs as an observation of the bivariate process. The results are illustrated for a range of extremal dependence forms.

AB - The influence of bivariate extremal dependence on the limiting behaviour of the concomitant of the largest order statistic is examined. Our approach is to fix the marginal distributions and derive a general tail characterisation of the joint survivor function. From this, we identify the normalisation required to obtain the limiting distribution of the concomitant of the largest order statistic, obtain its tail form, and investigate the limiting probability that the vector of componentwise maxima occurs as an observation of the bivariate process. The results are illustrated for a range of extremal dependence forms.

KW - Asymptotic independence

KW - Bivariate extreme value distribution

KW - Coefficient of tail dependence

KW - Concomitants

KW - Extreme value theory

KW - Induced order statistics

KW - Order statistics

KW - Slowly varying functions

U2 - 10.1017/S0001867800008168

DO - 10.1017/S0001867800008168

M3 - Journal article

AN - SCOPUS:0032023309

VL - 30

SP - 197

EP - 215

JO - Advances in Applied Probability

JF - Advances in Applied Probability

SN - 0001-8678

IS - 1

ER -