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Efficient stochastic simulation of metastable Markov chains

Author(s):

A. Milias, J. Lygeros
Conference/Journal:

IEEE Conference on Decision and Control
Abstract:

We address the problem of metastable Markov chain simulation, a class of systems characterized by the existence of two or more “pseudo-equilibrium” states and very slow convergence towards global equilibrium. For such systems, approximation of the stationary distribution by direct application of the Stochastic Simulation Algorithm (SSA) would be very inefficient. In this paper we propose a new method for steady-state simulation of metastable chains that is centered around the concept of stochastic complementation. The use of this mathematical device along with SSA results in an algorithm with much better convergence properties, that facilitates the analysis of rarely switching stochastic biochemical systems.

Year:

2011
Type of Publication:

(01)Article
Supervisor:

J. Lygeros

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% Autogenerated BibTeX entry
@InProceedings { MilLyg:2011:IFA_3857,
    author={A. Milias and J. Lygeros},
    title={{Efficient stochastic simulation of metastable Markov chains}},
    booktitle={IEEE Conference on Decision and Control},
    pages={},
    year={2011},
    address={},
    month=dec,
    url={http://control.ee.ethz.ch/index.cgi?page=publications;action=details;id=3857}
}
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