English

Moderate deviation principle for ergodic Markov chain. Lipschitz summands

Probability 2016-09-07 v1

Abstract

For 1/2<α<1{1/2}<\alpha<1, we propose the MDP analysis for family Snα=1nαi=1nH(Xi1),n1, S^\alpha_n=\frac{1}{n^\alpha}\sum_{i=1}^nH(X_{i-1}), n\ge 1, where (Xn)n0(X_n)_{n\ge 0} be a homogeneous ergodic Markov chain, XnRdX_n\in \mathbb{R}^d, when the spectrum of operator PxP_x is continuous. The vector-valued function HH is not assumed to be bounded but the Lipschitz continuity of HH is required. The main helpful tools in our approach are Poisson's equation and Stochastic Exponential; the first enables to replace the original family by 1nαMn\frac{1}{n^\alpha}M_n with a martingale MnM_n while the second to avoid the direct Laplace transform analysis.

Keywords

Cite

@article{arxiv.math/0503071,
  title  = {Moderate deviation principle for ergodic Markov chain. Lipschitz summands},
  author = {B. Delyon and A. Juditsky and R. Liptser},
  journal= {arXiv preprint arXiv:math/0503071},
  year   = {2016}
}