English

Self-normalized Cram\'er type moderate deviations for stationary sequences and applications

Probability 2020-05-11 v1

Abstract

Let (Xi)i1(X _i)_{i\geq1} be a stationary sequence. Denote m=nα,0<α<1,m=\lfloor n^\alpha \rfloor, 0< \alpha < 1, and k=n/m, k=\lfloor n/m \rfloor, where a\lfloor a \rfloor stands for the integer part of a.a. Set Sj=i=1mXm(j1)+i,1jk,S_{j}^\circ = \sum_{i=1}^m X_{m(j-1)+i}, 1\leq j \leq k, and (Vk)2=j=1k(Sj)2. (V_k^\circ)^2 = \sum_{j=1}^k (S_{j}^\circ)^2. We prove a Cram\'er type moderate deviation expansion for P(j=1kSj/Vkx)\mathbb{P}( \sum_{j=1}^k S_{j}^\circ /V_k^\circ \geq x) as n.n\to \infty. Applications to mixing type sequences, contracting Markov chains, expanding maps and confidence intervals are discussed.

Cite

@article{arxiv.2003.12939,
  title  = {Self-normalized Cram\'er type moderate deviations for stationary sequences and applications},
  author = {Xiequan Fan and Ion Grama and Quansheng Liu and Qi-Man Shao},
  journal= {arXiv preprint arXiv:2003.12939},
  year   = {2020}
}

Comments

30 pages

R2 v1 2026-06-23T14:30:37.962Z