Which distributions in the max-domain of attraction satisfy von Mises representation or variation representation for a given auxiliary function?

Abstract In this paper we characterize the family of distributions F which are in the max-domain of attraction (MDA) of Gumbel, Fréchet, or Weibull extreme value distributions. The extreme value behavior of MDA distribution F can be analyzed in terms of two convenient representations: the von Mises representation ( $$\textsf {vMR}$$ ) and the variation representation ( $$\textsf {VR}$$ ), where the latter covers both regular and gamma variation. Each of these representations is determined by an appropriate auxiliary function, the choice of which is in focus of our analysis. In particular, our main result provides the necessary and sufficient conditions that an MDA distribution F allows $$\textsf {vMR}$$ or $$\textsf {VR}$$ for a given auxiliary function. Moreover, we identify the exact classes of MDA distributions F allowing $$\textsf {vMR}$$ (or $$\textsf {VR}$$ ) with the same auxiliary function $$\psi _{{\textsf {vMR}}}$$ (or $$\psi _{{\textsf {VR}}}$$ ). Hence, our findings complete the characterization of the relation between MDA distributions F and the corresponding $$\textsf {vMR}$$ or $$\textsf {VR}$$ auxiliary functions.

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Publication Details

Journal
Extremes
Published
2025-08-05
DOI
https://doi.org/10.1007/s10687-025-00516-5
Primary Topic
Bayesian Methods and Mixture Models
Type
article
Field-Weighted Citation Impact
0.00

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article

Which distributions in the max-domain of attraction satisfy von Mises representation or variation representation for a given auxiliary function?

Miriam Isabel Seifert
Extremes
Bayesian Methods and Mixture Models
article

Which distributions in the max-domain of attraction satisfy von Mises representation or variation representation for a given auxiliary function?

Miriam Isabel Seifert
article en

Abstract

Abstract In this paper we characterize the family of distributions F which are in the max-domain of attraction (MDA) of Gumbel, Fréchet, or Weibull extreme value distributions. The extreme value behavior of MDA distribution F can be analyzed in terms of two convenient representations: the von Mises representation ( $$\textsf {vMR}$$ ) and the variation representation ( $$\textsf {VR}$$ ), where the latter covers both regular and gamma variation. Each of these representations is determined by an appropriate auxiliary function, the choice of which is in focus of our analysis. In particular, our main result provides the necessary and sufficient conditions that an MDA distribution F allows $$\textsf {vMR}$$ or $$\textsf {VR}$$ for a given auxiliary function. Moreover, we identify the exact classes of MDA distributions F allowing $$\textsf {vMR}$$ (or $$\textsf {VR}$$ ) with the same auxiliary function $$\psi _{{\textsf {vMR}}}$$ (or $$\psi _{{\textsf {VR}}}$$ ). Hence, our findings complete the characterization of the relation between MDA distributions F and the corresponding $$\textsf {vMR}$$ or $$\textsf {VR}$$ auxiliary functions.

ExtremesVol. 28(4)
Ruhr University Bochum (DE)
Ruhr-Universität Bochum
Openalex Percentile: Top 90%
Bayesian Methods and Mixture Models
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Which distributions in the max-domain of attraction satisfy von Mises representation or variation representation for a given auxiliary function? — Miriam Isabel Seifert · Extremes (2025) | TGRS Research Map | TGRS