Document detail
ID
oai:arXiv.org:2403.13489
Topic
Mathematics - Numerical Analysis Statistics - Computation Statistics - MethodologyAuthor
Iguchi, Yuga Jasra, Ajay Maama, Mohamed Beskos, AlexandrosCategory
Computer Science
Year
2024
listing date
3/27/2024
Abstract
In this paper, we present a new antithetic multilevel Monte Carlo (MLMC) method for the estimation of expectations with respect to laws of diffusion processes that can be elliptic or hypo-elliptic.
In particular, we consider the case where one has to resort to time discretization of the diffusion and numerical simulation of such schemes.
Motivated by recent developments, we introduce a new MLMC estimator of expectations, which does not require simulation of intractable L\'evy areas but has a weak error of order 2 and achieves the optimal computational complexity.
We then show how this approach can be used in the context of the filtering problem associated to partially observed diffusions with discrete time observations.
We illustrate with numerical simulations that our new approaches provide efficiency gains for several problems relative to some existing methods.
Iguchi, Yuga,Jasra, Ajay,Maama, Mohamed,Beskos, Alexandros, 2024, Antithetic Multilevel Methods for Elliptic and Hypo-Elliptic Diffusions with Applications
A Novel MR Imaging Sequence of 3D-ZOOMit Real Inversion-Recovery Imaging Improves Endolymphatic Hydrops Detection in Patients with Ménière Disease
ménière disease p < detection imaging sequences 3d-zoomit 3d endolymphatic real tse reconstruction ir inversion-recovery hydrops ratio
