Quick Search:

uzh logo
Browse by:

Zurich Open Repository and Archive

Maintenance: Tuesday, July the 26th 2016, 07:00-10:00

ZORA's new graphical user interface will be relaunched (For further infos watch out slideshow ZORA: Neues Look & Feel). There will be short interrupts on ZORA Service between 07:00am and 10:00 am. Please be patient.

Bolthausen, E; Schmock, U (1989). On the maximum entropy principle for uniformly ergodic Markov chains. Stochastic Processes and their Applications, 33(1):1-27.

Full text not available from this repository.

View at publisher


For strongly ergodic discrete time Markov chains we discuss the possible limits as n→∞ of probability measures on the path space of the form exp(nH(Ln)) dP/Zn· Ln is the empirical measure (or sojourn measure) of the process, H is a real-valued function (possibly attaining −∞) on the space of probability measures on the state space of the chain, and Zn is the appropriate norming constant. The class of these transformations also includes conditional laws given Ln belongs to some set. The possible limit laws are mixtures of Markov chains minimizing a certain free energy. The method of proof strongly relies on large deviation techniques.


15 citations in Web of Science®
11 citations in Scopus®
Google Scholar™


Additional indexing

Item Type:Journal Article, refereed, original work
Communities & Collections:07 Faculty of Science > Institute of Mathematics
Dewey Decimal Classification:510 Mathematics
Uncontrolled Keywords:maximum entropy; large deviations; Markov chains; variational problem; weak convergence
Deposited On:04 Nov 2009 14:31
Last Modified:05 Apr 2016 13:29
Publisher DOI:10.1016/0304-4149(89)90063-X
Related URLs:http://www.ams.org/mathscinet-getitem?mr=1027105

Users (please log in): suggest update or correction for this item

Repository Staff Only: item control page