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Auteurs principaux: Caro-Lopera, Francisco J., Díaz-García, José A.
Format: Preprint
Publié: 2024
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Accès en ligne:https://arxiv.org/abs/2410.04023
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author Caro-Lopera, Francisco J.
Díaz-García, José A.
author_facet Caro-Lopera, Francisco J.
Díaz-García, José A.
contents In this paper we provide a matrix extension of the scalar binomial series under elliptical contoured models and real normed division algebras. The classical hypergeometric series ${}_{1}F_{0}^β(a;\mathbf{Z})={}_{1}^{k}P_{0}^{β,1}(1:a;\mathbf{Z})=|\mathbf{I}-\mathbf{Z}|^{-a}$ of Jack polynomials are now seen as an invariant generalized determinant with a series representation indexed by any elliptical generator function. In particular, a corollary emerges for a simple derivation of the central matrix variate beta type II distribution under elliptically contoured models in the unified real, complex, quaternions and octonions.
format Preprint
id arxiv_https___arxiv_org_abs_2410_04023
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Matrix generalized elliptical binomial series under real normed division algebras and the central matrix variate beta distribution
Caro-Lopera, Francisco J.
Díaz-García, José A.
Statistics Theory
In this paper we provide a matrix extension of the scalar binomial series under elliptical contoured models and real normed division algebras. The classical hypergeometric series ${}_{1}F_{0}^β(a;\mathbf{Z})={}_{1}^{k}P_{0}^{β,1}(1:a;\mathbf{Z})=|\mathbf{I}-\mathbf{Z}|^{-a}$ of Jack polynomials are now seen as an invariant generalized determinant with a series representation indexed by any elliptical generator function. In particular, a corollary emerges for a simple derivation of the central matrix variate beta type II distribution under elliptically contoured models in the unified real, complex, quaternions and octonions.
title Matrix generalized elliptical binomial series under real normed division algebras and the central matrix variate beta distribution
topic Statistics Theory
url https://arxiv.org/abs/2410.04023