Self-normalized Cramér type moderate deviations for stationary sequences and applications

preprint2020arXivOpen access

Abstract

Let (Xi)i≥1(X _i)_{i\geq1} be a stationary sequence. Denote m=⌊nα⌋,0<α<1,m=\lfloor n^α\rfloor, 0< α< 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(j−1)+i,1≤j≤k,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 Cramér type moderate deviation expansion for P(∑j=1kSj∘/Vk∘≥x)\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.

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