Non-asymptotic Gaussian estimates for the recursive approximation of the invariant distribution of a diffusion

DOI10.1214/19-AIHP985zbMath1472.60112arXiv1605.08525OpenAlexW3038039500MaRDI QIDQ2227460

Yanyan Li

Publication date: 15 February 2021

Published in: Annales de l'Institut Henri Poincaré. Probabilités et Statistiques (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1605.08525

zbMATH Keywords

diffusion processesalmost sure central limit theoreminhomogeneous Markov chainsinvariant distributionnon-asymptotic Gaussian concentration

Mathematics Subject Classification ID

Inequalities; stochastic orderings (60E15) Second-order elliptic equations (35J15) Computational methods for stochastic equations (aspects of stochastic analysis) (60H35)

Related Items (7)

Invariant density estimation for a reflected diffusion using an Euler scheme ⋮ Unadjusted Langevin algorithm with multiplicative noise: total variation and Wasserstein bounds ⋮ Poisson Equation on Wasserstein Space and Diffusion Approximations for Multiscale McKean–Vlasov Equation ⋮ Approximation of the invariant distribution for a class of ergodic jump diffusions ⋮ Sharp non-asymptotic concentration inequalities for the approximation of the invariant distribution of a diffusion ⋮ Diffusion approximation for fully coupled stochastic differential equations ⋮ Rate of estimation for the stationary distribution of jump-processes over anisotropic Hölder classes

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