Moderate deviations for nonhomogeneous Markov chains

Mingzhou Xu, Kun Cheng and Yunzheng Ding

Statistics & Probability Letters, 2020, vol. 157, issue C

Abstract: In this work, we establish moderate deviation principles for bounded functionals and empirical measures for nonhomogeneous Markov chains with finite state space under the condition of convergence of transition probability matrices for nonhomogeneous Markov chains in Cesàro sense.

Keywords: Nonhomogeneous Markov chains; Moderate deviations; Empirical measures; Martingale (search for similar items in EconPapers)
Date: 2020
References: Add references at CitEc
Citations:

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0167715219302780
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:stapro:v:157:y:2020:i:c:s0167715219302780

Ordering information: This journal article can be ordered from
http://www.elsevier.com/wps/find/supportfaq.cws_home/regional
https://shop.elsevie ... _01_ooc_1&version=01

DOI: 10.1016/j.spl.2019.108632

Access Statistics for this article

Statistics & Probability Letters is currently edited by Somnath Datta and Hira L. Koul

More articles in Statistics & Probability Letters from Elsevier
Bibliographic data for series maintained by Catherine Liu ().