Measure concentration through non-Lipschitz observables and functional inequalities
Probability
2012-02-13 v1
Abstract
Non-Gaussian concentration estimates are obtained for invariant probability measures of reversible Markov processes. We show that the functional inequalities approach combined with a suitable Lyapunov condition allows us to circumvent the classical Lipschitz assumption of the observables. Our method is general and covers diffusions as well as pure-jump Markov processes on unbounded spaces.
Cite
@article{arxiv.1202.2341,
title = {Measure concentration through non-Lipschitz observables and functional inequalities},
author = {Arnaud Guillin and Aldéric Joulin},
journal= {arXiv preprint arXiv:1202.2341},
year = {2012}
}