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Exploiting occurrence times in likelihood inference for componentwise maxima.

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

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Exploiting occurrence times in likelihood inference for componentwise maxima. / Tawn, Jonathan A.; Stephenson, Alec.
In: Biometrika, Vol. 92, No. 1, 01.03.2005, p. 213-227.

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

Harvard

Tawn, JA & Stephenson, A 2005, 'Exploiting occurrence times in likelihood inference for componentwise maxima.', Biometrika, vol. 92, no. 1, pp. 213-227. https://doi.org/10.1093/biomet/92.1.213

APA

Tawn, J. A., & Stephenson, A. (2005). Exploiting occurrence times in likelihood inference for componentwise maxima. Biometrika, 92(1), 213-227. https://doi.org/10.1093/biomet/92.1.213

Vancouver

Tawn JA, Stephenson A. Exploiting occurrence times in likelihood inference for componentwise maxima. Biometrika. 2005 Mar 1;92(1):213-227. doi: 10.1093/biomet/92.1.213

Author

Tawn, Jonathan A. ; Stephenson, Alec. / Exploiting occurrence times in likelihood inference for componentwise maxima. In: Biometrika. 2005 ; Vol. 92, No. 1. pp. 213-227.

Bibtex

@article{75dea3c0f9e54a148c0470a9aa62293e,
title = "Exploiting occurrence times in likelihood inference for componentwise maxima.",
abstract = "Multivariate extreme value distributions arise as the limiting distributions of normalised componentwise maxima. They are often used to model multivariate data that can be regarded as the componentwise maxima of some unobserved underlying multivariate process. In many applications we have extra information. We often know the locations of the maxima within the underlying process. If the process is temporal this knowledge is frequently available through the dates on which the maxima are recorded. We show how to incorporate this extra information into maximum likelihood procedures. Asymptotic and small-sample efficiency results are presented for the dependence parameter in the logistic parametric sub-class of bivariate extreme value distributions. We conclude with an application to sea levels.",
keywords = "Asymptotic efficiency, Maximum likelihood, Multivariate extreme value distribution, Sea level",
author = "Tawn, {Jonathan A.} and Alec Stephenson",
note = "RAE_import_type : Journal article RAE_uoa_type : Statistics and Operational Research",
year = "2005",
month = mar,
day = "1",
doi = "10.1093/biomet/92.1.213",
language = "English",
volume = "92",
pages = "213--227",
journal = "Biometrika",
issn = "1464-3510",
publisher = "Oxford University Press",
number = "1",

}

RIS

TY - JOUR

T1 - Exploiting occurrence times in likelihood inference for componentwise maxima.

AU - Tawn, Jonathan A.

AU - Stephenson, Alec

N1 - RAE_import_type : Journal article RAE_uoa_type : Statistics and Operational Research

PY - 2005/3/1

Y1 - 2005/3/1

N2 - Multivariate extreme value distributions arise as the limiting distributions of normalised componentwise maxima. They are often used to model multivariate data that can be regarded as the componentwise maxima of some unobserved underlying multivariate process. In many applications we have extra information. We often know the locations of the maxima within the underlying process. If the process is temporal this knowledge is frequently available through the dates on which the maxima are recorded. We show how to incorporate this extra information into maximum likelihood procedures. Asymptotic and small-sample efficiency results are presented for the dependence parameter in the logistic parametric sub-class of bivariate extreme value distributions. We conclude with an application to sea levels.

AB - Multivariate extreme value distributions arise as the limiting distributions of normalised componentwise maxima. They are often used to model multivariate data that can be regarded as the componentwise maxima of some unobserved underlying multivariate process. In many applications we have extra information. We often know the locations of the maxima within the underlying process. If the process is temporal this knowledge is frequently available through the dates on which the maxima are recorded. We show how to incorporate this extra information into maximum likelihood procedures. Asymptotic and small-sample efficiency results are presented for the dependence parameter in the logistic parametric sub-class of bivariate extreme value distributions. We conclude with an application to sea levels.

KW - Asymptotic efficiency

KW - Maximum likelihood

KW - Multivariate extreme value distribution

KW - Sea level

U2 - 10.1093/biomet/92.1.213

DO - 10.1093/biomet/92.1.213

M3 - Journal article

VL - 92

SP - 213

EP - 227

JO - Biometrika

JF - Biometrika

SN - 1464-3510

IS - 1

ER -