Concentration of the information in data with log-concave distributions

Abstract

A concentration property of the functional −log f(X) is demonstrated, when a random vector X has a log-concave density f on ℝⁿ. This concentration property implies in particular an extension of the Shannon–McMillan–Breiman strong ergodic theorem to the class of discrete-time stochastic processes with log-concave marginals.