Expectation-Maximization algorithm to estimate the forcing parameter of a nonlinear McKean-Vlasov diffusion
Statistics Theory
2026-07-07 v1
Abstract
In this article, we address the problem of estimating a forcing parameter in a stochastic differential equation inspired by a model that describes instantaneous turbulent kinetic energy. The stochastic differential equation we analyze is of the nonlinear McKean-Vlasov type, where the drift term depends on a power of the expected value of the solution, which also introduces nonlinearity in an algebraic sense. We propose an estimation algorithm based on the Expectation-Maximization framework and show the consistency of our method. We illustrate our findings through numerical experiments.
Cite
@article{arxiv.2607.06714,
title = {Expectation-Maximization algorithm to estimate the forcing parameter of a nonlinear McKean-Vlasov diffusion},
author = {Eduardo Gutierrez-Turner and Kerlyns Martinez and Hector Olivero},
journal= {arXiv preprint arXiv:2607.06714},
year = {2026}
}
Comments
24 pages, 3 figures