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| Hauptverfasser: | , |
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| Format: | Preprint |
| Veröffentlicht: |
2023
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| Schlagworte: | |
| Online-Zugang: | https://arxiv.org/abs/2312.10710 |
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| _version_ | 1866916926199955456 |
|---|---|
| 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 |