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Electronic Journal of Probability
Article . 2026 . Peer-reviewed
Data sources: Crossref
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https://dx.doi.org/10.48550/ar...
Article . 2025
License: arXiv Non-Exclusive Distribution
Data sources: Datacite
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Multiple extremal integrals

Authors: Bai, Shuyang; Chen, Jiemiao;

Multiple extremal integrals

Abstract

We introduce the notion of multiple extremal integrals as an extension of single extremal integrals, which have played important roles in extreme value theory. The multiple extremal integrals are formulated in terms of a product-form random sup measure derived from the $α$-Fréchet random sup measure. We establish a LePage-type representation similar to that used for multiple sum-stable integrals, which have been extensively studied in the literature. This approach allows us to investigate the integrability, tail behavior, and independence properties of multiple extremal integrals. Additionally, we discuss an extension of a recently proposed stationary model that exhibits an unusual extremal clustering phenomenon, now constructed using multiple extremal integrals.

Accepted at Electronic Journal of Probability

Related Organizations
Keywords

60G70 (Primary), 60F05 (Secondary), Probability (math.PR), FOS: Mathematics, Probability

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
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