Self-Switching Markov Chains: Emerging dominance phenomena

S. Gallo, G. Iacobelli, G. Ost and D.Y. Takahashi

Stochastic Processes and their Applications, 2022, vol. 143, issue C, 254-284

Abstract: The law of many dynamical systems changes with the evolution of the system. These changes are often associated with the occurrence of certain events whose time of occurrence depends on the trajectory of the system itself. Dynamics that take longer to change will be observed more frequently and may dominate in the long run (the only ones observed). This article proposes a Markov chain model, called Self-Switching Markov Chain, in which the emergence of dominant dynamics can be rigorously addressed. We present conditions and scaling under which we observe with probability one only the subset of dominant dynamics.

Keywords: Markov chains; Scaling limits; Animal behavior; Evolution; Metastability (search for similar items in EconPapers)
Date: 2022
References: View complete reference list from CitEc
Citations:

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0304414921001642
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:spapps:v:143:y:2022:i:c:p:254-284

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

DOI: 10.1016/j.spa.2021.10.001

Access Statistics for this article

Stochastic Processes and their Applications is currently edited by T. Mikosch

More articles in Stochastic Processes and their Applications from Elsevier
Bibliographic data for series maintained by Catherine Liu ().