Polynomial convergence rates for Markov kernels under nested modulated drift conditions - Institut de Recherche Mathématiques de Rennes
Pré-Publication, Document De Travail Année : 2023

Polynomial convergence rates for Markov kernels under nested modulated drift conditions

Résumé

When a Markov kernel $P$ satisfies a minorization condition and nested modulated drift conditions, Jarner and Roberts provided in [JR02, Th. 3.2] an asymptotic polynomial convergence rate in weighted total variation norm of $P^n(x,\cdot)$ to the $P$-invariant probability measure $\pi$. In connection with this polynomial asymptotics, we propose explicit and simple estimates on series of such weighted total variation norms, from which an estimate for the total variation norm of $P^n(x, \cdot)-\pi$ is deduced. The proofs are selfcontained and based on the residual kernel and the Nummelin-type representation of π. No coupling technique is used.
Fichier principal
Vignette du fichier
Vitesse-poly-HAL.pdf (408.48 Ko) Télécharger le fichier
Origine Fichiers produits par l'(les) auteur(s)

Dates et versions

hal-04351652 , version 1 (18-12-2023)

Identifiants

  • HAL Id : hal-04351652 , version 1

Citer

Loïc Hervé, James Ledoux. Polynomial convergence rates for Markov kernels under nested modulated drift conditions. 2023. ⟨hal-04351652⟩
83 Consultations
26 Téléchargements

Partager

More