Comparing moments of real log-concave random variables

Abstract

We show that for every mean zero log-concave real random variable X one has \|X\|p ≤ pq \|X\|q for p ≥ q ≥ 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 > 0 the quantity \|X\|p / \|X\|q is maximized for some shifted exponential distribution. Building upon this we derive the bound \|X\|p ≤ C0 pq \|X\|q for arbitrary log-concave X, with best possible absolute constant C0=eW(1/e) ≈ 1.3211 in front of pq, where W stands for the Lambert function.

0

Turn this paper into a full lesson

ArcXiv compiles a staged curriculum from this paper: 8-12 lessons across beginner → advanced, synthesised section guides, visuals, flashcards, a quiz, exercises, and on-demand deep dives per section. Grounded in the abstract, never invented.

Discussion (0)

Sign in to join the discussion.

Loading comments…