Nonparametric Information Geometry: From Divergence Function to Referential-Representational Biduality on Statistical Manifolds

Nonparametric Information Geometry: From Divergence Function to Referential-Representational Biduality on Statistical Manifolds

Divergence functions are the non-symmetric “distance” on the manifold, Μθ, of parametric probability density functions over a measure space, (Χ,μ). Classical information geometry prescribes, on Μθ: (i) a Riemannian metric given by the Fisher information; (ii) a pair of dual connections (giving rise...

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Bibliographic Details
Main Author: Jun Zhang
Format: Article
Language:English
Published: MDPI AG 2013-12-01
Series:Entropy
Subjects:
Fisher information
alpha-connection
infinite-dimensional manifold
convex function
Online Access:http://www.mdpi.com/1099-4300/15/12/5384

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http://www.mdpi.com/1099-4300/15/12/5384

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