2012/02/10 by Arnaud Guillin, Guillin, Arnaud, Aldéric Joulin +1
Biochemistry, Genetics and Molecular Biology · Mathematics · #FOS: Mathematics #Gene Regulatory Network Analysis #Markov Chains and Monte Carlo Methods #Mathematical Biology Tumor Growth #Probability (math.PR) #math.PR
paper · pdf · doi:10.48550/arxiv.1202.2341
arxiv created 2012/02/10 · openalex publication_date 2012/02/10 · arxiv updated 2012/02/13 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
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.