NON-ASYMPTOTIC CONCENTRATION INEQUALITY FOR AN APPROXIMATION OF THE INVARIANT DISTRIBUTION OF A DIFFUSION DRIVEN BY COMPOUND POISSON PROCESS
Résumé
In this article we approximate the invariant distribution ν of 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, particularly suitable in cases where the driving Lévy process is a Compound Poisson. This scheme is similar to those introduced by Lamberton and Pagès in [LP02] for a Brownian diffusion and extended by Panloup in [Pan08b] to the Jump Diffusion with Lévy jumps. We obtain a non-asymptotic Gaussian concentration bound for the difference between the invariant distribution and the empirical distribution computed with the scheme of decreasing time step along a appropriate test functions f such that f − ν(f) is is a coboundary of the infinitesimal generator.
Domaines
Probabilités [math.PR]
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GHL_01_10_18_Version_HAL.pdf (438.34 Ko)
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empirical_density_k0.pdf (8.56 Ko)
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Origine | Fichiers produits par l'(les) auteur(s) |
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