Hostname: page-component-586b7cd67f-2plfb Total loading time: 0 Render date: 2024-11-22T05:24:24.686Z Has data issue: false hasContentIssue false

Mixing and average mixing times for general Markov processes

Published online by Cambridge University Press:  14 August 2020

Robert M. Anderson
Affiliation:
Department of Economics, University of California, Berkeley, CA e-mail: [email protected]@uottawa.ca
Haosui Duanmu*
Affiliation:
Department of Mathematics and Statistics, University of Ottawa, Ottawa, ON, Canada
Aaron Smith
Affiliation:
Department of Economics, University of California, Berkeley, CA e-mail: [email protected]@uottawa.ca
Rights & Permissions [Opens in a new window]

Abstract

Core share and HTML view are not available for this content. However, as you have access to this content, a full PDF is available via the ‘Save PDF’ action button.

Yuval Peres and Perla Sousi showed that the mixing times and average mixing times of reversible Markov chains on finite state spaces are equal up to some universal multiplicative constant. We use tools from nonstandard analysis to extend this result to reversible Markov chains on compact state spaces that satisfy the strong Feller property.

Type
Article
Creative Commons
Creative Common License - CCCreative Common License - BY
This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted re-use, distribution, and reproduction in any medium, provided the original work is properly cited.
Copyright
© Canadian Mathematical Society 2020

References

Arkeryd, L. O., Cutland, N. J., and Henson, C. W. (eds.), Nonstandard analysis . In: Theory and applications, NATO Advanced Science Institutes Series C: Mathematical and Physical Sciences, 493, Kluwer Academic Publishers Group, Dordrecht, 1997. http://dx.doi.org/10.1007/978-94-011-5544-1 Google Scholar
Anderson, R. M., Duanmu, H., and Smith, A., Mixing times and hitting times for general Markov processes. Preprint, 2019. arXiv:1810.06087 CrossRefGoogle Scholar
Cutland, N. J., Neves, V., Oliveira, F., and Sousa-Pinto, J. (eds.), Developments in nonstandard mathematics . Papers from the International Colloquium (CIMNS94) held in memory of Abraham Robinson at the University of Aveiro, Aveiro, July 18–22, 1994. Pitman Research Notes in Mathematics Series, 336, Longman, Harlow, 1995.Google Scholar
Duanmu, H. and Roy, D. M., On extended admissible procedures and their nonstandard Bayes risk. Preprint, 2016. arXiv:1612.09305 Google Scholar
Duanmu, H., Rosenthal, J. S., and Weiss, W., Ergodicity of markov processes via non-standard analysis. Mem. Amer. Math. Soc., to appear, 2018.Google Scholar
Hermon, J. and Peres, Y., The power of averaging at two consecutive time steps: Proof of a mixing conjecture by Aldous and Fill. Ann. Inst. Henri Poincaré, Probab. Stat. 53(2017), 20302042. http://dx.doi.org/10.1214/16-AIHP782 CrossRefGoogle Scholar
Keisler, H. J., An infinitesimal approach to stochastic analysis. Mem. Amer. Math. Soc. 48(1984), no. 297. http://dx.doi.org/10.1090/memo/0297 Google Scholar
Levin, D. A., Peres, Y., and Wilmer, E. L., Markov chains and mixing times. With a chapter by Propp, James G. and Wilson, David B.. American Mathematical Society, Providence, RI, 2009.Google Scholar
Peres, Y. and Sousi, P.. Mixing times are hitting times of large sets. J. Theoret. Probab. 28(2015), 488519. http://dx.doi.org/10.1007/s10959-013-0497-9 CrossRefGoogle Scholar
Wolff, M. and Loeb, P. A. (eds.), Nonstandard analysis for the working mathematician . Mathematics and its Applications, 510, Kluwer Academic Publishers, Dordrecht, 2000. http://dx.doi.org/10.1007/978-94-4168-0 Google Scholar