On mutual information estimation for mixed-pair random variables

被引：6

作者：

Beknazaryan, Aleksandr ^{[1
]}

Dang, Xin ^{[1
]}

Sang, Hailin ^{[1
]}

机构：

[1] Univ Mississippi, Dept Math, University, MS 38677 USA

来源：

STATISTICS & PROBABILITY LETTERS | 2019年 / 148卷

关键词：

Central limit theorem; Entropy; Kernel estimation; Mixed-pair; Mutual information; INTEGRAL FUNCTIONALS; ENTROPY; DENSITY;

D O I：

10.1016/j.spl.2018.12.011

中图分类号：

O21 [概率论与数理统计]; C8 [统计学];

学科分类号：

020208 ; 070103 ; 0714 ;

摘要：

We study the mutual information estimation for mixed-pair random variables. One random variable is discrete and the other one is continuous. We develop a kernel method to estimate the mutual information between the two random variables. The estimates enjoy a central limit theorem under some regular conditions on the distributions. The theoretical results are demonstrated by simulation study. (C) 2018 Elsevier B.V. All rights reserved.

引用

页码：9 / 16

页数：8

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