Concentration functions and entropy bounds for discrete log-concave distributions

Sergey G. Bobkov; Arnaud Marsiglietti; James C Melbourne

doi:10.1017/S096354832100016X

Concentration functions and entropy bounds for discrete log-concave distributions

Sergey G. Bobkov, Arnaud Marsiglietti, James C Melbourne

Research output: Contribution to journal › Article › peer-review

1 Scopus citations

Abstract

Two-sided bounds are explored for concentration functions and Rényi entropies in the class of discrete log-concave probability distributions. They are used to derive certain variants of the entropy power inequalities.

Original language	English (US)
Pages (from-to)	1-19
Number of pages	19
Journal	Combinatorics Probability and Computing
DOIs	https://doi.org/10.1017/S096354832100016X
State	Accepted/In press - 2021

Bibliographical note

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© The Author(s), 2021. Published by Cambridge University Press.

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10.1017/S096354832100016X

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abstract = "Two-sided bounds are explored for concentration functions and R{\'e}nyi entropies in the class of discrete log-concave probability distributions. They are used to derive certain variants of the entropy power inequalities.",

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JO - Combinatorics Probability and Computing

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Concentration functions and entropy bounds for discrete log-concave distributions

Abstract

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