A distance between elliptical distributions based in an embedding into the Siegel group

作者:

Highlights:

摘要

This paper describes two different embeddings of the manifolds corresponding to many elliptical probability distributions with the informative geometry into the manifold of positive-definite matrices with the Siegel metric, generalizing a result published previously elsewhere. These new general embeddings are applicable to a wide class of elliptical probability distributions, in which the normal, t-Student and Cauchy are specific examples. A lower bound for the Rao distance is obtained, which is itself a distance, and, through these embeddings, a number of statistical tests of hypothesis are derived.

论文关键词:Information metric,Rao distance,Siegel geometry,Elliptical distributions

论文评审过程:Received 2 September 2000, Revised 20 August 2001, Available online 28 November 2001.

论文官网地址:https://doi.org/10.1016/S0377-0427(01)00584-2