Quantitative bounds on convergence of time-inhomogeneous Markov chains

Research output: Contribution to journalArticlepeer-review

Abstract

Convergence rates of Markov chains have been widely studied in recent years. In particular, quantitative bounds on convergence rates have been studied in various forms by Meyn and Tweedie [Ann. Appl. Probab. 4 (1994) 981-1101], Rosenthal [J. Amer. Statist. Assoc. 90 (1995) 558-566], Roberts and Tweedie [Stochastic Process. Appl. 80 (1999) 211-229], Jones and Hobert [Statist. Sci. 16 (2001) 312-334] and Fort [Ph.D. thesis (2001) Univ. Paris VI]. In this paper, we extend a result of Rosenthal [J. Amer. Statist. Assoc. 90 (1995) 558-566] that concerns quantitative convergence rates for time-homogeneous Markov chains. Our extension allows us to consider f-total variation distance (instead of total variation) and time-inhomogeneous Markov chains. We apply our results to simulated annealing.

Original languageEnglish
Pages (from-to)1643-1665
Number of pages23
JournalAnnals of Applied Probability
Volume14
Issue number4
DOIs
Publication statusPublished - 1 Nov 2004

Keywords

  • Convergence rate
  • Coupling
  • Markov chain Monte Carlo
  • Simulated annealing
  • f-total variation

Fingerprint

Dive into the research topics of 'Quantitative bounds on convergence of time-inhomogeneous Markov chains'. Together they form a unique fingerprint.

Cite this