ODE methods for Markov chain stability with applications to MCMC

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Abstract

Fluid limit techniques have become a central tool to analyze queueing networks over the last decade, with applications to performance analysis, simulation, and optimization.In this paper some of these techniques are extended to a general class of skip-free Markov chains. As in the case of queueing models, a fluid approximation is obtained by scaling time, space, and the initial condition by a large constant. The resulting fluid limit is the solution of an ODE in "most" of the state space. Stability and finer ergodic properties for the stochastic model then follow from stability of the set of fluid limits. Moreover, similar to the queueing context where fluid models are routinely used to design control policies, the structure of the limiting ODE in this general setting provides an understanding of the dynamics of the Markov chain. These results are illustrated through application to Markov Chain Monte Carlo.

Original languageEnglish
Title of host publicationProceedings of VALUETOOLS
Subtitle of host publication1st International Conference on Performance Evaluation Methodologies and Tools
DOIs
Publication statusPublished - 1 Dec 2006
Externally publishedYes
EventVALUETOOLS: 1st International Conference on Performance Evaluation Methodologies and Tools - Pisa, Italy
Duration: 11 Oct 200613 Oct 2006

Publication series

NameACM International Conference Proceeding Series
Volume180

Conference

ConferenceVALUETOOLS: 1st International Conference on Performance Evaluation Methodologies and Tools
Country/TerritoryItaly
CityPisa
Period11/10/0613/10/06

Keywords

  • Fluid limit stability
  • Fluid limits for general state-space Markov chains
  • Markov Chain Monte-Carlo
  • Metropolis-hastings algorithm

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