English

Optimal tail comparison under convex majorization

Probability 2022-07-06 v1

Abstract

Following results of Kemperman and Pinelis, we show that if XX and YY are real valued random variables such that EY<\mathbb{E}\left\vert Y\right\vert<\infty and for all non-decreasing convex φ:R[0,)\varphi:\mathbb{R}\rightarrow [0,\infty), Eφ(X)Eφ(Y)\mathbb{E}\varphi(X)\leq\mathbb{E}\varphi(Y), then for all sRs\in\mathbb{R} with P{Y>s}0\mathbb{P}\left\{Y>s\right\}\neq 0, P{XE(Y:Y>s)}P{Y>s}\mathbb{P}\left\{X\geq\mathbb{E}\left(Y:Y>s\right)\right\}\leq\mathbb{P}\left\{Y>s\right\}. This bound is sharp in essentially the strictest possible sense: for any such YY and ss there exists such an XX with P{XE(Y:Y>s)}=P{Y>s}\mathbb{P}\left\{X\geq \mathbb{E}\left(Y:Y>s\right)\right\}=\mathbb{P}\left\{Y>s\right\}.

Keywords

Cite

@article{arxiv.2207.01872,
  title  = {Optimal tail comparison under convex majorization},
  author = {Daniel J. Fresen},
  journal= {arXiv preprint arXiv:2207.01872},
  year   = {2022}
}

Comments

9 pages. Most of the material here was originally part of arXiv:2203.12523 and/or arXiv:1812.10938 and now stands as a paper on its own

R2 v1 2026-06-24T12:14:09.533Z