Nonparametric Bayesian methods for one-dimensional diffusion models

TL;DR

This paper reviews recent nonparametric Bayesian techniques for inferring one-dimensional diffusion models, focusing on prior choices, computational challenges, and asymptotic properties.

Contribution

It provides a comprehensive overview of new nonparametric Bayesian methods tailored for one-dimensional diffusion processes, highlighting their theoretical and computational aspects.

Findings

Comparison of different prior distributions

Discussion of computational algorithms

Asymptotic consistency results

Abstract

In this paper we review recently developed methods for nonparametric Bayesian inference for one-dimensional diffusion models. We discuss different possible prior distributions, computational issues, and asymptotic results.