Applications of Structural Statistics: Geometric Inference in Exponential Families
Abstract
Exponential families comprise a broad class of statistical models and parametric families like normal distributions, binomial distributions, gamma distributions or exponential distributions. Thereby the formal representation of its probability distributions induces a confined intrinsic structure, which appears to be that of a dually flat statistical manifold. Conversely it can be shown, that any dually flat statistical manifold, which is given by a regular Bregman divergence uniquely induced a regular exponential family, such that exponential families may - with some restrictions - be regarded as a universal representation of dually flat statistical manifolds. This article reviews the pioneering work of Shun'ichi Amari about the intrinsic structure of exponential families in terms of structural stratistics.
Keywords
Cite
@article{arxiv.2004.08909,
title = {Applications of Structural Statistics: Geometric Inference in Exponential Families},
author = {Patrick Michl},
journal= {arXiv preprint arXiv:2004.08909},
year = {2020}
}