Titlebook: Elliptically Symmetric Distributions in Signal Processing and Machine Learning; Jean-Pierre Delmas,Mohammed Nabil El Korso,Frédéri Book 20

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Produktentwicklung und Konstruktionstechnikome practical uses of these geometric tools in the framework of elliptical distributions. This second part of the exposition is divided into three main axes: Riemannian optimization for covariance matrix estimation, Intrinsic Cramér–Rao bounds, and classification using Riemannian distances.

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The Fisher–Rao Geometry of CES Distributionsome practical uses of these geometric tools in the framework of elliptical distributions. This second part of the exposition is divided into three main axes: Riemannian optimization for covariance matrix estimation, Intrinsic Cramér–Rao bounds, and classification using Riemannian distances.

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Linear Shrinkage of Sample Covariance Matrix or Matrices Under Elliptical Distributions: A Reviewelliptical sampling are shown to be functions of few key parameters only, such as elliptical kurtosis?and sphericity parameter. Similar results and estimators are derived for multiple population settings and applications of the studied shrinkage estimators are illustrated in portfolio optimization.

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