Posterior contraction rate for non-parametric Bayesian estimation of the dispersion coefficient of a stochastic differential equation

TL;DR

This paper establishes the rate at which Bayesian methods estimate the dispersion coefficient in a stochastic differential equation, providing theoretical guarantees for non-parametric Bayesian inference.

Contribution

It derives the posterior contraction rate for non-parametric Bayesian estimation of the dispersion coefficient in a linear SDE, a novel theoretical result.

Findings

Established the posterior contraction rate for the dispersion coefficient

Provided theoretical guarantees for Bayesian estimation in SDEs

Enhanced understanding of non-parametric Bayesian methods

Abstract

We derive the posteror contraction rate for non-parametric Bayesian estimation of a deterministic dispersion coefficient of a linear stochastic differential equation.