中文

Deviation bounds for additive functionals of Markov process

概率论 2007-05-23 v1

摘要

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...).

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引用

@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}
}