Multivariate extreme value analysis and its relevance in a metallographical application

DOI10.1080/02664763.2013.845872OpenAlexW2040005715MaRDI QIDQ5128606

Udo Kamps, Wolfgang Bleck, H. H. Dickert, Anja Bettina Schmiedt

Publication date: 28 October 2020

Published in: Journal of Applied Statistics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/02664763.2013.845872

zbMATH Keywords

Weibullextreme value indexsteelsFréchetGumbelinclusion size distribution

Mathematics Subject Classification ID

Point estimation (62F10) Applications of statistics in engineering and industry; control charts (62P30) Extreme value theory; extremal stochastic processes (60G70)

Uses Software

• AS 215
• ismev

Cites Work

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• Statistics of extremes for IID data and breakthroughs in the estimation of the extreme value index: Laurens de Haan leading contributions
• Extremal processes. II
• Random features of the fatigue limit
• Maximum likelihood estimation in a class of nonregular cases
• Multivariate extremal processes generated by independent non-identically distributed random variables
• Metal fatigue, Wicksell transform and extreme values
• An introduction to statistical modeling of extreme values

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