Differential equation approximations for Markov chains

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We formulate some simple conditions under which a Markov chain may be approximated by the solution to a differential equation, with quantifiable error probabilities. The role of a choice of coordinate functions for the Markov chain is emphasised. The general theory is illustrated in three examples: the classical stochastic epidemic, a population process model with fast and slow variables, and core-finding algorithms for large random hypergraphs.
Published in at http://dx.doi.org/10.1214/07-PS121 the Probability Surveys (http://www.i-journals.org/ps/) by the Institute of Mathematical Statistics (http://www.imstat.org)

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Probability, 05C65 (Primary) 60J75, 05C80 (Secondary)

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http://salesiana.dossiersoluciones.com/handle/123456789/159297

Consulte el texto completo en el siguiente enlace:

https://arxiv.org/abs/0710.3269
 http://arxiv.org/abs/0710.3269
 Probability Surveys 2008, Vol. 5, 37-79
 doi:10.1214/07-PS121

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arXiv