Elliptical Wishart Distribution: Maximum Likelihood Estimator from Information Geometry - Archive ouverte HAL
Communication Dans Un Congrès Année : 2023

Elliptical Wishart Distribution: Maximum Likelihood Estimator from Information Geometry

Imen Ayadi

Résumé

This work deals with elliptical Wishart distributions on the set of symmetric positive definite matrices. It contains two major contributions. First, the information geometry associated with elliptical Wishart distributions is derived. Second, this geometry is leveraged to propose Riemannian-optimization-based maximum likelihood estimators of any elliptical Wishart distribution. Particular attention is given to two specific distributions: the t- and Kotz Wishart ones. The performance of the proposed methods is assessed through numerical experiments on simulated data.
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Dates et versions

hal-04213775 , version 1 (21-09-2023)

Identifiants

Citer

Imen Ayadi, Florent Bouchard, Frédéric Pascal. Elliptical Wishart Distribution: Maximum Likelihood Estimator from Information Geometry. ICASSP 2023 - 2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Jun 2023, Rhodes Island, Greece. pp.1-5, ⟨10.1109/ICASSP49357.2023.10096222⟩. ⟨hal-04213775⟩
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