Quasi-limiting estimates for periodic absorbed Markov chains - Inria - Institut national de recherche en sciences et technologies du numérique
Pré-Publication, Document De Travail Année : 2022

Quasi-limiting estimates for periodic absorbed Markov chains

Résumé

We consider periodic Markov chains with absorption. Applying to iterates of this periodic Markov chain criteria for the exponential convergence of conditional distributions of aperiodic absorbed Markov chains, we obtain exponential estimates for the periodic asymptotic behavior of the semigroup of the Markov chain. This implies in particular the exponential convergence in total variation of the conditional distribution of the Markov chain given non-absorption to a periodic sequence of limit measures and we characterize the cases where this sequence is constant, which corresponds to the cases where the conditional distributions converge to a quasi-stationary distribution. We also characterize the first two eignevalues of the semigroup and give a bound for the spectral gap between these eigenvalues and the next ones. Finally, we give ergodicity estimates in total variation for the Markov chain conditioned to never be absorbed, often called Q-process, and quasi-ergodicity estimates for the original Markov chain.
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hal-03823655 , version 1 (21-10-2022)

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Nicolas Champagnat, Denis Villemonais. Quasi-limiting estimates for periodic absorbed Markov chains. 2022. ⟨hal-03823655⟩
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