Comparison Theory for Markov Chains on Different State Spaces and Application to Random Walk on Derangements
Aaron Smith ()
Additional contact information
Aaron Smith: University of Ottawa
Journal of Theoretical Probability, 2015, vol. 28, issue 4, 1406-1430
Abstract:
Abstract We consider two Markov chains on state spaces $$\Omega \subset \widehat{\Omega }$$ Ω ⊂ Ω ^ . In this paper, we prove bounds on the eigenvalues of the chain on the smaller state space based on the eigenvalues of the chain on the larger state space. This generalizes work of Diaconis, Saloff-Coste, and others on comparison of chains in the case $$\Omega = \widehat{\Omega }$$ Ω = Ω ^ . The main tool is the extension of functions from the smaller space to the larger, which allows comparison of the entire spectrum of the two chains. The theory is used to give quick analyses of several chains without symmetry. We apply this theory to analyze the mixing properties of a ‘random transposition’ walk on derangements.
Keywords: Markov chain; Mixing time; Comparison; 60J05; 60J10 (search for similar items in EconPapers)
Date: 2015
References: View references in EconPapers View complete reference list from CitEc
Citations:
Downloads: (external link)
http://link.springer.com/10.1007/s10959-014-0559-7 Abstract (text/html)
Access to the full text of the articles in this series is restricted.
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:spr:jotpro:v:28:y:2015:i:4:d:10.1007_s10959-014-0559-7
Ordering information: This journal article can be ordered from
https://www.springer.com/journal/10959
DOI: 10.1007/s10959-014-0559-7
Access Statistics for this article
Journal of Theoretical Probability is currently edited by Andrea Monica
More articles in Journal of Theoretical Probability from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().