English

Comparing moments of real log-concave random variables

Probability 2022-11-11 v1

Abstract

We show that for every mean zero log-concave real random variable XX one has XppqXq\|X\|_p \leq \frac{p}{q} \|X\|_q for pq1p \geq q \geq 1, going beyond the well-known case of symmetric random variables. We also prove that in the class of arbitrary log-concave real random variables for p>q>0p>q > 0 the quantity Xp/Xq\|X\|_p / \|X\|_q is maximized for some shifted exponential distribution. Building upon this we derive the bound XpC0pqXq\|X\|_p \leq C_0 \frac{p}{q} \|X\|_q for arbitrary log-concave XX, with best possible absolute constant C0=eW(1/e)1.3211C_0=e^{W(1/e)} \approx 1.3211 in front of pq\frac{p}{q}, where WW stands for the Lambert function.

Keywords

Cite

@article{arxiv.2211.05210,
  title  = {Comparing moments of real log-concave random variables},
  author = {Daniel Murawski},
  journal= {arXiv preprint arXiv:2211.05210},
  year   = {2022}
}

Comments

30 pages

R2 v1 2026-06-28T05:33:17.134Z