Bounding Means of Discrete Distributions
Statistics Theory
2021-11-16 v2 Information Theory
math.IT
Probability
Statistics Theory
Abstract
We introduce methods to bound the mean of a discrete distribution (or finite population) based on sample data, for random variables with a known set of possible values. In particular, the methods can be applied to categorical data with known category-based values. For small sample sizes, we show how to leverage the knowledge of the set of possible values to compute bounds that are stronger than for general random variables such as standard concentration inequalities.
Cite
@article{arxiv.2109.02538,
title = {Bounding Means of Discrete Distributions},
author = {Eric Bax and Frédéric Ouimet},
journal= {arXiv preprint arXiv:2109.02538},
year = {2021}
}
Comments
9 pages, 8 figures