pith. sign in

arxiv: 2204.00917 · v2 · pith:H365VRV3new · submitted 2022-04-02 · 🧮 math.ST · stat.TH

Dually affine Information Geometry modeled on a Banach space

classification 🧮 math.ST stat.TH
keywords affinebanachchartsgeometryinformationmappingsparticularprobabilities
0
0 comments X
read the original abstract

In this chapter, we study Information Geometry from a particular non-parametric or functional point of view. The basic model is a probabilities subset usually specified by regularity conditions. For example, probability measures mutually absolutely continuous or probability densities with a given degree of smoothness. We construct a manifold structure by giving an atlas of charts as mappings from probabilities to a Banach space. The charts we use are quite peculiar in that we consider only instances where the transition mappings are affine. We chose a particular expression of the tangent and cotangent bundles in this affine setting.

This paper has not been read by Pith yet.

discussion (0)

Sign in with ORCID, Apple, or X to comment. Anyone can read and Pith papers without signing in.