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Title: Sample-Path Large Deviations for Unbounded Additive Functionals of the Reflected Random Walk
We prove a sample-path large deviation principle (LDP) with sublinear speed for unbounded functionals of certain Markov chains induced by the Lindley recursion. The LDP holds in the Skorokhod space [Formula: see text] equipped with the [Formula: see text] topology. Our technique hinges on a suitable decomposition of the Markov chain in terms of regeneration cycles. Each regeneration cycle denotes the area accumulated during the busy period of the reflected random walk. We prove a large deviation principle for the area under the busy period of the Markov random walk, and we show that it exhibits a heavy-tailed behavior. Funding: The research of B. Zwart and M. Bazhba is supported by the Nederlandse Organisatie voor Wetenschappelijk Onderzoek [Grant 639.033.413]. The research of J. Blanchet is supported by the National Science Foundation (NSF) [Grants 1915967, 1820942, and 1838576] as well as the Defense Advanced Research Projects Agency [Grant N660011824028]. The research of C.-H. Rhee is supported by the NSF [Grant CMMI-2146530].  more » « less
Award ID(s):
2146530
PAR ID:
10500346
Author(s) / Creator(s):
; ; ;
Publisher / Repository:
INFORMS
Date Published:
Journal Name:
Mathematics of Operations Research
ISSN:
0364-765X
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
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