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Subgeometric rates of convergence in Wasserstein distance for Markov chains

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اقرأ أكثر حفظ في قائمتي
  • معلومة اضافية
    • Contributors:
      CB - Centre Borelli - UMR 9010 (CB); Service de Santé des Armées-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Ecole Normale Supérieure Paris-Saclay (ENS Paris Saclay)-Université Paris Cité (UPCité); Laboratoire Traitement et Communication de l'Information (LTCI); Télécom ParisTech-Institut Mines-Télécom Paris (IMT)-Centre National de la Recherche Scientifique (CNRS); Institut de Mathématiques de Toulouse UMR5219 (IMT); Université Toulouse Capitole (UT Capitole); Université de Toulouse (UT)-Université de Toulouse (UT)-Institut National des Sciences Appliquées - Toulouse (INSA Toulouse); Institut National des Sciences Appliquées (INSA)-Université de Toulouse (UT)-Institut National des Sciences Appliquées (INSA)-Université Toulouse - Jean Jaurès (UT2J); Université de Toulouse (UT)-Université Toulouse III - Paul Sabatier (UT3); Université de Toulouse (UT)-Centre National de la Recherche Scientifique (CNRS)
    • بيانات النشر:
      HAL CCSD
    • الموضوع:
      2015
    • Collection:
      Université Toulouse 2 - Jean Jaurès: HAL
    • نبذة مختصرة :
      In this paper, we provide sufficient conditions for the existence of the invariant distribution and for subgeometric rates of convergence in Wasserstein distance for general state-space Markov chains which are (possibly) not irreducible. Compared to previous work, our approach is based on a purely probabilistic coupling construction which allows to retrieve rates of convergence matching those previously reported for convergence in total variation. Our results are applied to establish the subgeometric ergodicity in Wasserstein distance of non-linear autoregressive models and of the pre-conditioned Crank-Nicolson Markov chain Monte Carlo algorithm in Hilbert space.
    • Relation:
      hal-00948661; https://hal.science/hal-00948661; https://hal.science/hal-00948661v3/document; https://hal.science/hal-00948661v3/file/main.pdf
    • الرقم المعرف:
      10.1214/15-AIHP699
    • Rights:
      info:eu-repo/semantics/OpenAccess
    • الرقم المعرف:
      edsbas.84A081F