Fisher information bounds and applications to SDEs with small noise
Probability
2024-08-20 v1
Abstract
In this paper, we first establish general bounds on the Fisher information distance to the class of normal distributions of Malliavin differentiable random variables. We then study the rate of Fisher information convergence in the central limit theorem for the solution of small noise stochastic differential equations and its additive functionals. We also show that the convergence rate is of optimal order.
Keywords
Cite
@article{arxiv.2408.09797,
title = {Fisher information bounds and applications to SDEs with small noise},
author = {Nguyen Tien Dung and Nguyen Thu Hang},
journal= {arXiv preprint arXiv:2408.09797},
year = {2024}
}
Comments
To appear in Stochastic Processes and their Applications