Bernoulli

  • Bernoulli
  • Volume 13, Number 3 (2007), 831-848.

Computable convergence rates for sub-geometric ergodic Markov chains

Randal Douc, Eric Moulines, and Philippe Soulier

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Abstract

In this paper, we give quantitative bounds on the f-total variation distance from convergence of a Harris recurrent Markov chain on a given state space under drift and minorization conditions implying ergodicity at a subgeometric rate. These bounds are then specialized to the stochastically monotone case, covering the case where there is no minimal reachable element. The results are illustrated with two examples, from queueing theory and Markov Chain Monte Carlo theory.

Article information

Source
Bernoulli, Volume 13, Number 3 (2007), 831-848.

Dates
First available in Project Euclid: 7 August 2007

Permanent link to this document
https://projecteuclid.org/euclid.bj/1186503489

Digital Object Identifier
doi:10.3150/07-BEJ5162

Mathematical Reviews number (MathSciNet)
MR2348753

Zentralblatt MATH identifier
1131.60065

Keywords
Markov chains rates of convergence stochastic monotonicity

Citation

Douc, Randal; Moulines, Eric; Soulier, Philippe. Computable convergence rates for sub-geometric ergodic Markov chains. Bernoulli 13 (2007), no. 3, 831--848. doi:10.3150/07-BEJ5162. https://projecteuclid.org/euclid.bj/1186503489


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