多元和矩阵变量分布的库尔贝克-莱布勒散度的精确表达式。
Exact Expressions for Kullback-Leibler Divergence for Multivariate and Matrix-Variate Distributions.
作者信息
Nawa Victor, Nadarajah Saralees
机构信息
Department of Mathematics and Statistics, University of Zambia, Lusaka 10101, Zambia.
Department of Mathematics, University of Manchester, Manchester M13 9PL, UK.
出版信息
Entropy (Basel). 2024 Aug 4;26(8):663. doi: 10.3390/e26080663.
The Kullback-Leibler divergence is a measure of the divergence between two probability distributions, often used in statistics and information theory. However, exact expressions for it are not known for multivariate or matrix-variate distributions apart from a few cases. In this paper, exact expressions for the Kullback-Leibler divergence are derived for over twenty multivariate and matrix-variate distributions. The expressions involve various special functions.
库尔贝克-莱布勒散度是衡量两个概率分布之间差异的一种度量，常用于统计学和信息论。然而，除了少数情况外，多元或矩阵变量分布的精确表达式尚不清楚。在本文中，推导出了二十多种多元和矩阵变量分布的库尔贝克-莱布勒散度的精确表达式。这些表达式涉及各种特殊函数。
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