Comparing moments of real log-concave random variables
Abstract
We show that for every mean zero log-concave real random variable $X$ one has $\|X\|_p \leq \frac{p}{q} \|X\|_q$ for $p \geq q \geq 1$, 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 $p>q > 0$ the quantity $\|X\|_p / \|X\|_q$ is maximized for some shifted exponential distribution. Building upon this we derive the bound $\|X\|_p \leq C_0 \frac{p}{q} \|X\|_q$ for arbitrary log-concave $X$, with best possible absolute constant $C_0=e^{W(1/e)} \approx 1.3211$ in front of $\frac{p}{q}$, where $W$ stands for the Lambert function.
Fields of Study & Subjects
Probability and Statistical Research
Point processes and geometric inequalities
Advanced Statistical Methods and Models
Publication details
- Journal / source
- Bernoulli
- Volume
- 32
- Issue
- 3
- Publication date
- 29 April 2026
- Language
- EN