Lower bounds on binomial and Poisson tails: an approach via tail conditional expectations
Probability
2017-12-07 v2
Abstract
We derive upper bounds on the tail conditional expectation of binomial and Poisson random variables. Those upper bounds are subsequently employed to the problem of obtaining non-asymptotic lower bounds on the probability that the aforementioned random variables are significantly larger than their expectation.
Keywords
Cite
@article{arxiv.1609.06651,
title = {Lower bounds on binomial and Poisson tails: an approach via tail conditional expectations},
author = {Christos Pelekis},
journal= {arXiv preprint arXiv:1609.06651},
year = {2017}
}
Comments
13 pages, 6 figures. Some typos are corrected and the results are extended to the Poisson case