Electronic Journal of Probability

Fluctuations of the empirical measure of freezing Markov chains

Florian Bouguet and Bertrand Cloez

Full-text: Open access

Abstract

In this work, we consider a finite-state inhomogeneous-time Markov chain whose probabilities of transition from one state to another tend to decrease over time. This can be seen as a cooling of the dynamics of an underlying Markov chain. We are interested in the long time behavior of the empirical measure of this freezing Markov chain. Some recent papers provide almost sure convergence and convergence in distribution in the case of the freezing speed $n^{-\theta }$, with different limits depending on $\theta <1,\theta =1$ or $\theta >1$. Using stochastic approximation techniques, we generalize these results for any freezing speed, and we obtain a better characterization of the limit distribution as well as rates of convergence and functional convergence.

Article information

Source
Electron. J. Probab., Volume 23 (2018), paper no. 2, 31 pp.

Dates
Received: 11 May 2017
Accepted: 15 December 2017
First available in Project Euclid: 16 January 2018

Permanent link to this document
https://projecteuclid.org/euclid.ejp/1516093310

Digital Object Identifier
doi:10.1214/17-EJP130

Mathematical Reviews number (MathSciNet)
MR3751077

Zentralblatt MATH identifier
1390.60264

Subjects
Primary: 60J10: Markov chains (discrete-time Markov processes on discrete state spaces) 60J25: Continuous-time Markov processes on general state spaces 60F05: Central limit and other weak theorems

Keywords
Markov chain long-time behavior piecewise-deterministic Markov process Ornstein-Uhlenbeck process asymptotic pseudotrajectory

Rights
Creative Commons Attribution 4.0 International License.

Citation

Bouguet, Florian; Cloez, Bertrand. Fluctuations of the empirical measure of freezing Markov chains. Electron. J. Probab. 23 (2018), paper no. 2, 31 pp. doi:10.1214/17-EJP130. https://projecteuclid.org/euclid.ejp/1516093310


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