Computable Convergence Rates for Subgeometrically Ergodic Markov Chains

Details Computable Convergence Rates for Subgeometrically Ergodic Markov Chains Computable Convergence Rates for Subgeometrically Ergodic Markov Chains

2005-11-10

arxiv.org/abs/math/0511273v1

Mathematics

Probability

Scientific paper

In this paper, we give quantitative bounds on the $f$-total variation distance from convergence of an Harris recurrent Markov chain on an arbitrary under drift and minorisation conditions implying ergodicity at a sub-geometric rate. These bounds are then specialized to the stochastically monotone case, covering the case where there is no minimal reachable element. The results are illustrated on two examples from queueing theory and Markov Chain Monte Carlo.

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