Entropy and Thinning of Discrete Random Variables

被引：0
作者：
Johnson, Oliver [1 ]
机构：
[1] Univ Bristol, Sch Math, Univ Walk, Bristol BS8 1TW, Avon, England
来源：
CONVEXITY AND CONCENTRATION | 2017年 / 161卷
关键词：
METRIC-MEASURE-SPACES; FISHER INFORMATION; MONOTONICITY PROPERTIES; BINARY SEQUENCES; POWER INEQUALITY; STAM INEQUALITY; LOG-CONCAVITY; POISSON; CONVERGENCE; BOUNDS;
D O I：
10.1007/978-1-4939-7005-6_2
中图分类号：
O1 [数学];
学科分类号：
0701 ; 070101 ;
摘要：
We describe five types of results concerning information and concentration of discrete random variables, and relationships between them, motivated by their counterparts in the continuous case. The results we consider are information theoretic approaches to Poisson approximation, the maximum entropy property of the Poisson distribution, discrete concentration (Poincare and logarithmic Sobolev) inequalities, monotonicity of entropy and concavity of entropy in the Shepp-Olkin regime.
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收藏
页码：33 / 53
页数：21
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