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Hauptverfasser: Jiu, Lin, Peng, Linyu
Format: Preprint
Veröffentlicht: 2023
Schlagworte:
Online-Zugang:https://arxiv.org/abs/2312.10710
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author Jiu, Lin
Peng, Linyu
author_facet Jiu, Lin
Peng, Linyu
contents The hyperbolic secant distribution has several generalizations with applications in finance. In this study, we explore the dual geometric structure of one such generalization, namely the beta-logistic distribution. Recent findings also interpret Bernoulli and Euler polynomials as moments of specific random variables, treating them as special cases within the framework of the beta-logistic distribution. The current study also uncovers that the beta-logistic distribution admits an $α$-parallel prior for any real number $α$, that has the potential for application in geometric statistical inference.
format Preprint
id arxiv_https___arxiv_org_abs_2312_10710
institution arXiv
publishDate 2023
record_format arxiv
spellingShingle Information geometry and $α$-parallel prior of the beta-logistic distribution
Jiu, Lin
Peng, Linyu
Statistics Theory
Differential Geometry
Number Theory
53B12, 11B68
The hyperbolic secant distribution has several generalizations with applications in finance. In this study, we explore the dual geometric structure of one such generalization, namely the beta-logistic distribution. Recent findings also interpret Bernoulli and Euler polynomials as moments of specific random variables, treating them as special cases within the framework of the beta-logistic distribution. The current study also uncovers that the beta-logistic distribution admits an $α$-parallel prior for any real number $α$, that has the potential for application in geometric statistical inference.
title Information geometry and $α$-parallel prior of the beta-logistic distribution
topic Statistics Theory
Differential Geometry
Number Theory
53B12, 11B68
url https://arxiv.org/abs/2312.10710