Asymptotic expansion and central limit theorem for multiscale piecewise-deterministic Markov processes
Abstract
We consider a general class of piecewise-deterministic Markov processes with multiple time-scales. In line with recent results on the stochastic averaging principle for these processes, we obtain a description of their law through an asymptotic expansion. We further study the fluctuations around the averaged system in the form of a central limit theorem, and derive consequences on the law of the first passage-time. We apply the mathematical results to the Morris–Lecar model with stochastic ion channels.Download Info
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Bibliographic Info
Article provided by Elsevier in its journal Stochastic Processes and their Applications.
Volume (Year): 122 (2012)
Issue (Month): 6 ()
Pages: 2292-2318
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Related research
Keywords: Piecewise-deterministic Markov process; Averaging; Homogenization; Central limit theorem; Multiscale; Slow-fast; Neuron models with stochastic ion channels;References
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