English

Deviation bounds for additive functionals of Markov process

Probability 2007-05-23 v1

Abstract

In this paper we derive non asymptotic deviation bounds for ν(1t0tV(Xs)dsVdμR)\P_\nu (|\frac 1t \int_0^t V(X_s) ds - \int V d\mu | \geq R) where XX is a μ\mu stationary and ergodic Markov process and VV is some μ\mu integrable function. These bounds are obtained under various moments assumptions for VV, and various regularity assumptions for μ\mu. Regularity means here that μ\mu may satisfy various functional inequalities (F-Sobolev, generalized Poincar\'e etc...).

Keywords

Cite

@article{arxiv.math/0603021,
  title  = {Deviation bounds for additive functionals of Markov process},
  author = {Patrick Cattiaux and Arnaud Guillin},
  journal= {arXiv preprint arXiv:math/0603021},
  year   = {2007}
}