Electronic Communications in Probability

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

Michel Benaïm and Bertrand Cloez

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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 methodintroduced 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 somedeterministic 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. Inthe last part, our convergence results are compared with those of a particle system algorithm (adiscrete-time version of the Fleming-Viot algorithm).

Article information

Electron. Commun. Probab., Volume 20 (2015), paper no. 37, 13 pp.

Accepted: 12 May 2015
First available in Project Euclid: 7 June 2016

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Zentralblatt MATH identifier

Primary: 65C20: Models, numerical methods [See also 68U20] 60B12: Limit theorems for vector-valued random variables (infinite- dimensional case) 60J10: Markov chains (discrete-time Markov processes on discrete state spaces)
Secondary: 34F05: Equations and systems with randomness [See also 34K50, 60H10, 93E03] 60J20: Applications of Markov chains and discrete-time Markov processes on general state spaces (social mobility, learning theory, industrial processes, etc.) [See also 90B30, 91D10, 91D35, 91E40]

Quasi-stationary distributions approximation method reinforced random walks random perturbations of dynamical

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Benaïm, Michel; Cloez, Bertrand. A stochastic approximation approach to quasi-stationary distributions on finite spaces. Electron. Commun. Probab. 20 (2015), paper no. 37, 13 pp. doi:10.1214/ECP.v20-3956. https://projecteuclid.org/euclid.ecp/1465320964

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