Abstract
Divergence functions play a relevant role in Information Geometry as they allow for the introduction of a Riemannian metric and a dual connection structure on a finite dimensional manifold of probability distributions. They also allow to define, in a canonical way, a symplectic structure on the square of the above manifold of probability distributions, a property that has received less attention in the literature until recent contributions. In this paper, we hint at a possible application: we study Lagrangian submanifolds of this symplectic structure and show that they are useful for describing the manifold of solutions of the Maximum Entropy principle.
Subject
General Physics and Astronomy
Reference21 articles.
1. Information Geometry and Its Applications;Amari,2016
2. Methods of Information Geometry;Amari,2007
3. Differential Geometry and Statistics;Murray,1993
4. Information geometry of divergence functions
5. A differential geometric approach to statistical inference on the basis of contrast functionals
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