The Basics of Information Geometry

被引：15

作者：

Caticha, Ariel ^{[1
]}

机构：

[1] SUNY Albany, Dept Phys, Albany, NY 12222 USA

来源：

BAYESIAN INFERENCE AND MAXIMUM ENTROPY METHODS IN SCIENCE AND ENGINEERING (MAXENT 2014) | 2015年 / 1641卷

关键词：

Entropic dynamics; Quantum Theory; Maximum Entropy;

D O I：

10.1063/1.4905960

中图分类号：

O59 [应用物理学];

学科分类号：

摘要：

To what extent can we distinguish one probability distribution from another? Are there quantitative measures of distinguishability? The goal of this tutorial is to approach such questions by introducing the notion of the "distance" between two probability distributions and exploring some basic ideas of such an "information geometry".

引用

页码：15 / 26

页数：12

共 20 条

[1]

Amari S.-I., 2000, Translations of mathematical monographs

[2]

Amari S.-I, 1985, Differential-geometrical methods in statistics

[3]

[Anonymous], 1981, TRANSL MATH MONOGRAP

[4]

[Anonymous], 1997, Geometric Foundations of Asymptotic Inference