Relative entropy bounds for sampling with and without replacement
Probability
2026-01-14 v1 Information Theory
math.IT
Abstract
Sharp, nonasymptotic bounds are obtained for the relative entropy between the distributions of sampling with and without replacement from an urn with balls of colors. Our bounds are asymptotically tight in certain regimes and, unlike previous results, they depend on the number of balls of each colour in the urn. The connection of these results with finite de Finetti-style theorems is explored, and it is observed that a sampling bound due to Stam (1978) combined with the convexity of relative entropy yield a new finite de Finetti bound in relative entropy, which achieves the optimal asymptotic convergence rate.
Cite
@article{arxiv.2404.06632,
title = {Relative entropy bounds for sampling with and without replacement},
author = {Oliver Johnson and Lampros Gavalakis and Ioannis Kontoyiannis},
journal= {arXiv preprint arXiv:2404.06632},
year = {2026}
}
Comments
17 pages, 1 figure