Approximation of the invariant distribution for a class of ergodic jump diffusions

Autor: Igor Honoré, Dasha Loukianova, Arnaud Gloter
Přispěvatelé: Laboratoire de Mathématiques et Modélisation d'Evry (LaMME), Université d'Évry-Val-d'Essonne (UEVE)-ENSIIE-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)
Rok vydání: 2020
Předmět:
Zdroj: ESAIM: Probability and Statistics
ESAIM: Probability and Statistics, EDP Sciences, 2020, 24, pp.883-913. ⟨10.1051/ps/2020023⟩
ESAIM: Probability and Statistics, 2020, 24, pp.883-913. ⟨10.1051/ps/2020023⟩
ISSN: 1262-3318
1292-8100
DOI: 10.1051/ps/2020023
Popis: In this article, we approximate the invariant distributionνof an ergodic Jump Diffusion driven by the sum of a Brownian motion and a Compound Poisson process with sub-Gaussian jumps. We first construct an Euler discretization scheme with decreasing time steps. This scheme is similar to those introduced in Lamberton and PagèsBernoulli8(2002) 367-405. for a Brownian diffusion and extended in F. Panloup,Ann. Appl. Probab.18(2008) 379-426. to a diffusion with Lévy jumps. We obtain a non-asymptoticquasiGaussian (asymptotically Gaussian) concentration bound for the difference between the invariant distribution and the empirical distribution computed with the scheme of decreasing time step along appropriate test functionsfsuch thatf−ν(f) is a coboundary of the infinitesimal generator.
Databáze: OpenAIRE