@inbook{b8b6e78be35144d0a317fac685ddb800,
title = "Convergence in the Wasserstein Distance",
abstract = "In the previous chapters, we obtained rates of convergence in the total variation distance of the iterates (Formula Presented) of an irreducible positive Markov kernel P to its unique invariant measure (Formula Presented) for (Formula Presented) -almost every (Formula Presented) if the kernel P is irreducible and positive Harris recurrent. Conversely, convergence in the total variation distance for all (Formula Presented) entails irreducibility and that (Formula Presented) be a maximal irreducibility measure.",
author = "Randal Douc and Eric Moulines and Pierre Priouret and Philippe Soulier",
note = "Publisher Copyright: {\textcopyright} 2018, Springer Nature Switzerland AG.",
year = "2018",
month = jan,
day = "1",
doi = "10.1007/978-3-319-97704-1\_20",
language = "English",
series = "Springer Series in Operations Research and Financial Engineering",
publisher = "Springer Nature",
pages = "455--488",
booktitle = "Springer Series in Operations Research and Financial Engineering",
}