2020
DOI: 10.30757/alea.v17-35
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Analytic-geometric methods for finite Markov chains with applications to quasi-stationarity

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Cited by 7 publications
(10 citation statements)
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“…It is well-known that the Doob-transform technique is a useful tool to study problems involving Markov processes with killing. We follow closely the notation used in our previous article [6] which will be used extensively in what follows.…”
Section: General Results Based On the Doob Transformmentioning
confidence: 99%
See 1 more Smart Citation
“…It is well-known that the Doob-transform technique is a useful tool to study problems involving Markov processes with killing. We follow closely the notation used in our previous article [6] which will be used extensively in what follows.…”
Section: General Results Based On the Doob Transformmentioning
confidence: 99%
“…We introduce the notions of Harnack Markov chains and graphs, which allows us to treat the three-dimensional gambler's ruin starting "in the middle" in Example 5.14. Section 6 specializes to nice domains (inner-uniform domains) where the results of the authors' previous paper [6], Analytic-geometric methods for finite Markov chains with applications to quasi-stationarity, can be harnessed. This allows uniform estimates for all starting states, in particular for the three-player gambler's ruin problem.…”
Section: Introductionmentioning
confidence: 99%
“…In particular, it is well-known that the asymptotic behavior of this Doob transform is very linked to the one of the conditional probability measure P µ [X t ∈ •|τ 0 > t], for some µ ∈ M 1 ((0, +∞)), as it was shown for example in [5,4,10] in the context of absorbed Markov processes, or in [6] for exploding Feynman-Kac semi-groups.…”
Section: Asymptotic Behavior For the Bessel-3 Processmentioning
confidence: 92%
“…One of the main goals of this project is to understand the long-time asymptotic and ergodic properties of such Feynman-Kac semigroups and the corresponding processes evolving in the presence of the killing Schrödinger potentials. In this context, we want to mention here a recent work by Diaconis, Houston-Edwards and Saloff-Coste [18] which gave us some new insight and motivation. The two aforementioned motivations are strongly connected to each other -this is manifested via the probabilistic background lying behind the analytic approach which we undertake in this article.…”
Section: Introductionmentioning
confidence: 98%