Perturbation theory for Markov chains

09.12.2019, 11:15 Uhr  –  Campus Golm, Haus 9, Raum 2.22
Öffentlicher Vortrag

Prof. Dr. D. Rudolf

Abstract:
Perturbation theory for Markov chains addresses the question of how small differences in the transition probabilities of Markov chains are reflected in differences  between  their distributions.  Under  a  convergence  condition  we present an estimate of the Wasserstein distance of thenth step distributions
between  an  ideal,  unperturbed  and  an  approximating, perturbed  Markov chain. We illustrate the result with an example of an autoregressive process as well
as an application to the Monte Carlo within Metropolis algorithm