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

Mathematics

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

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

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

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title = "Concentration functions and entropy bounds for discrete log-concave distributions",

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.",

author = "Bobkov, {Sergey G.} and Arnaud Marsiglietti and Melbourne, {James C}",

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language = "English (US)",

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AU - Bobkov, Sergey G.

AU - Marsiglietti, Arnaud

AU - Melbourne, James C

N1 - Publisher Copyright: © The Author(s), 2021. Published by Cambridge University Press.

PY - 2021

Y1 - 2021

N2 - 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.

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JO - Combinatorics Probability and Computing

JF - Combinatorics Probability and Computing

SN - 0963-5483

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Concentration functions and entropy bounds for discrete log-concave distributions

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