Measure concentration through non-Lipschitz observables and functional inequalities

Details Measure concentration through non-Lipschitz observables and functional inequalities Measure concentration through non-Lipschitz observables and functional inequalities

2012-02-10

arxiv.org/abs/1202.2341v1

Mathematics

Probability

Scientific paper

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.

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