Log-convexity and log-concavity of noncentral gamma sums and differences
Probability
2026-07-10 v1 Classical Analysis and ODEs
Statistics Theory
Abstract
We study log-convexity and log-concavity of densities obtained from sums and differences of two independent noncentral gamma random variables. We give a complete classification of one-sided log-convexity for noncentral gamma differences, a complete log-convexity classification for sums of two independent central gamma random variables, and sharp log-concavity criteria for central differences and for common-scale sums. As special cases, we deduce a log-convexity classification for the density of the product of two correlated normal random variables with arbitrary means and variances, and log-convexity and log-concavity classifications for the densities of the variance-gamma and McKay Type I distributions.
Keywords
Cite
@article{arxiv.2607.09499,
title = {Log-convexity and log-concavity of noncentral gamma sums and differences},
author = {Robert E. Gaunt and Frédéric Ouimet},
journal= {arXiv preprint arXiv:2607.09499},
year = {2026}
}
Comments
12 pages, 0 figures