Approximate regenerative-block bootstrap for Markov chains: some simulation studies

In [7], a novel methodology for bootstrapping general Harris Markov chains has been developed, the (approximate) regenerative block-bootstrap. It is built on the renewal properties of the chain (or of a Nummelin extension of the latter) and has theoretical properties that surpass other existing methods within the Marko-vian framework. This paper is devoted to discuss practical issues related to the implementation of this specific resampling method and to present various simula-tion studies for investigating its performance and comparing it to other bootstrap resampling schemes, standing as natural candidates in the Markov setting