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Stochastic approximation of quasi-stationary distributions on compact spaces and applications

Abstract : In the continuity of a recent paper ([6]), dealing with finite Markov chains, this paper proposes and analyzes a recursive algorithm for the approximation of the quasi-stationary distribution of a general Markov chain living on a compact metric space killed in finite time. The idea is to run the process until extinction and then to bring it back to life at a position randomly chosen according to the (possibly weighted) empirical occupation measure of its past positions. General conditions are given ensuring the convergence of this measure to the quasi-stationary distribution of the chain. We then apply this method to the numerical approximation of the quasi-stationary distribution of a diffusion process killed on the boundary of a compact set and to the estimation of the spectral gap of irreducible Markov processes. Finally, the sharpness of the assumptions is illustrated through the study of the algorithm in a non-irreducible setting.
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https://hal.archives-ouvertes.fr/hal-01334603
Déposant : Fabien Panloup <>
Soumis le : lundi 6 novembre 2017 - 22:14:20
Dernière modification le : lundi 23 novembre 2020 - 10:07:12

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Michel Benaim, Bertrand Cloez, Fabien Panloup. Stochastic approximation of quasi-stationary distributions on compact spaces and applications. Annals of Applied Probability, Institute of Mathematical Statistics (IMS), 2018, 28 (4), pp.2370-2416. ⟨10.1214/17-AAP1360⟩. ⟨hal-01334603v3⟩

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