Bounding the equilibrium distribution of Markov population models
作者： Tuǧrul Dayar , Holger Hermanns , David Spieler , Verena Wolf
DOI: 10.1002/NLA.795
关键词: Mathematical optimization 、 Mathematics 、 Applied mathematics 、 Markov kernel 、 Markov property 、 Markov chain Monte Carlo 、 Balance equation 、 Probability mass function 、 Probability distribution 、 Continuous-time Markov chain 、 Markov chain
摘要: SUMMARY We propose a bounding technique for the equilibrium probability distribution of continuous-time Markov chains with population structure and infinite state space. We use Lyapunov functions to determine finite set states that contains most mass. Then we apply refinement scheme based on stochastic complementation derive lower upper bounds each within set. To show usefulness our approach, present experimental results several examples from biology. Copyright © 2011 John Wiley & Sons, Ltd.
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