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Foundations of Structural Statistics: Statistical Manifolds (2002.07424v2)

Published 18 Feb 2020 in math.ST, cs.IT, math.IT, and stat.TH

Abstract: Upon a consistent topological statistical theory the application of structural statistics requires a quantification of the proximity structure of model spaces. An important tool to study these structures are Pseudo-Riemannian metrices, which in the category of statistical models are induced by statistical divergences. The present article extends the notation of topological statistical models by a differential structure to statistical manifolds and introduces the differential geometric foundations to study distribution families by their differential-, Riemannian- and symplectic geometry.

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