Quasi-stationary distributions for randomly perturbed dynamical systems

Mathieu Faure () and Sebastian Schreiber

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Abstract: We analyze quasi-stationary distributions \μ ε \ ε\textgreater0 of a family of Markov chains \X ε \ ε\textgreater0 that are random perturbations of a bounded, continuous map F:M→M , where M is a closed subset of R k . Consistent with many models in biology, these Markov chains have a closed absorbing set M 0 ⊂M such that F(M 0 )=M 0 and F(M∖M 0 )=M∖M 0 . Under some large deviations assumptions on the random perturbations, we show that, if there exists a positive attractor for F (i.e., an attractor for F in M∖M 0 ), then the weak* limit points of μ ε are supported by the positive attractors of F . To illustrate the broad applicability of these results, we apply them to nonlinear branching process models of metapopulations, competing species, host-parasitoid interactions and evolutionary games.

Keywords: Economie; quantitative (search for similar items in EconPapers)
Date: 2014
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Citations: View citations in EconPapers (2)

Published in The Annals of Applied Probability, 2014, 24 (2), pp.553--598. ⟨10.1214/13-AAP923⟩

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Persistent link: https://EconPapers.repec.org/RePEc:hal:journl:hal-01474257

DOI: 10.1214/13-AAP923

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