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A stochastic approximation approach to quasi-stationary distributions on finite spaces

Michel Benaïm, +1 more
- 01 Jan 2015 - 
- Vol. 20, Iss: 37, pp 1-13
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TLDR
In this article, a stochastic approximation algorithm for the simulation of quasi-stationary distributions on finite state spaces has been proposed, which is a generalization of a method introduced by Aldous, Flannery and Palacios.
Abstract
This work is concerned with the analysis of a stochastic approximation algorithm for the simulation of quasi-stationary distributions on finite state spaces. This is a generalization of a method introduced by Aldous, Flannery and Palacios. It is shown that the asymptotic behavior of the empirical occupation measure of this process is precisely related to the asymptotic behavior of some deterministic dynamical system induced by a vector field on the unit simplex. This approach provides new proof of convergence as well as precise asymptotic rates for this type of algorithm. In the last part, our convergence results are compared with those of a particle system algorithm (a discrete-time version of the Fleming-Viot algorithm).

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Quasistationary distributions for one-dimensional diffusions with singular boundary points

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Does deterministic coexistence theory matter in a finite world? Insights from serpentine annual plants

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References
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Book

The Theory of Matrices

TL;DR: In this article, the Routh-Hurwitz problem of singular pencils of matrices has been studied in the context of systems of linear differential equations with variable coefficients, and its applications to the analysis of complex matrices have been discussed.
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TL;DR: The juxtaposition of these two expressions in the title reflects the ambition of the authors to produce a reference work, both for engineers who use adaptive algorithms and for probabilists or statisticians who would like to study stochastic approximations in terms of problems arising from real applications.
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A survey of random processes with reinforcement

TL;DR: The models surveyed in this paper include generalized Polya urns, reinforced random walks, interacting urn models, and continuous reinforced processes, with a focus on methods and results, with sketches provided of some proofs.
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Dynamics of stochastic approximation algorithms

TL;DR: These notes were written for a D.E.A. course given at Ecole Normale Superieure de Cachan and University Toulouse III to introduce the reader to the dynamical system aspects of the theory of stochastic approximations.
Journal ArticleDOI

On Quasi-Stationary distributions in absorbing discrete-time finite Markov chains

TL;DR: In this article, the authors show that the time to absorption from the set T of transient states of a Markov chain may be sufficiently long for the probability distribution over T to settle down in some sense to a quasi-stationary distribution.
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