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We consider the problem of Bayesian estimation of static parameters associated to a partially and discretely observed diffusion process. We assume that the exact transition dynamics of the diffusion process are unavailable, even up-to an…

Computation · Statistics 2023-09-26 Pierre Del Moral , Shulan Hu , Ajay Jasra , Hamza Ruzayqat , Xinyu Wang

The problem of deriving a gradient flow structure for the porous medium equation which is {\em thermodynamic}, in that it arises from the large deviations of some microscopic particle system, is studied. To this end, a rescaled zero-range…

Probability · Mathematics 2025-03-25 Benjamin Gess , Daniel Heydecker

This paper presents a tractable sufficient condition for the consistency of maximum likelihood estimators (MLEs) in partially observed diffusion models, stated in terms of stationary distribution of the associated fully observed diffusion,…

Statistics Theory · Mathematics 2024-12-10 Sergey Nadtochiy , Yuan Yin

We develop a mesoscopic modeling framework for diffusion in a crowded environment, particularly targeting applications in the modeling of living cells. Through homogenization techniques we effectively coarse-grain a detailed microscopic…

Subcellular Processes · Quantitative Biology 2018-09-19 Stefan Engblom , Per Lötstedt , Lina Meinecke

In this paper, we study the diffusive limit of solutions to the generalized Langevin equation (GLE) in a periodic potential. Under the assumption of quasi-Markovianity, we obtain sharp longtime equilibration estimates for the GLE using…

Mathematical Physics · Physics 2021-02-03 G. A. Pavliotis , G. Stoltz , U. Vaes

This paper reviews standard oversampling strategies as performed in the Multiscale Finite Element Method (MsFEM). Common to those approaches is that the oversampling is performed in the full space restricted to a patch but including coarse…

Numerical Analysis · Mathematics 2014-04-16 Patrick Henning , Daniel Peterseim

This paper introduces a Monte Carlo method for maximum likelihood inference in the context of discretely observed diffusion processes. The method gives unbiased and a.s.\@ continuous estimators of the likelihood function for a family of…

Statistics Theory · Mathematics 2009-03-03 Alexandros Beskos , Omiros Papaspiliopoulos , Gareth Roberts

Diffusion of particles through an heterogenous obstacle line is modeled as a two-dimensional diffusion problem with a one--directional nonlinear convective drift and is examined using two-scale asymptotic analysis. At the scale where the…

Analysis of PDEs · Mathematics 2018-04-24 Emilio N. M. Cirillo , Ida de Bonis , Adrian Muntean , Omar Richardson

We study the weak error associated with the Euler scheme of non degenerate diffusion processes with non smooth bounded coefficients. Namely, we consider the cases of H{\"o}lder continuous coefficients as well as piecewise smooth drifts with…

Probability · Mathematics 2016-12-28 V Konakov , S Menozzi

We study nonparametric estimation of the diffusion coefficient from discrete data, when the observations are blurred by additional noise. Such issues have been developed over the last 10 years in several application fields and in particular…

Statistics Theory · Mathematics 2011-12-30 Marc Hoffmann , Axel Munk , Johannes Schmidt-Hieber

General elliptic equations with spatially discontinuous diffusion coefficients may be used as a simplified model for subsurface flow in heterogeneous or fractured porous media. In such a model, data sparsity and measurement errors are often…

Numerical Analysis · Mathematics 2022-08-29 Andrea Barth , Robin Merkle

Principal stratification is a widely used framework for addressing post-randomization complications. After using principal stratification to define causal effects of interest, researchers are increasingly turning to finite mixture models to…

Methodology · Statistics 2019-08-20 Avi Feller , Evan Greif , Nhat Ho , Luke Miratrix , Natesh Pillai

The Langevin equation is a common tool to model diffusion at a single-particle level. In non-homogeneous environments, such as aqueous two-phase systems or biological condensates with different diffusion coefficients in different phases,…

In this paper we study model reduction of linear and bilinear quadratic stochastic control problems with parameter uncertainties. Specifically, we consider slow-fast systems with unknown diffusion coefficient and study the convergence of…

Optimization and Control · Mathematics 2021-02-10 Hafida Bouanani , Carsten Hartmann , Omar Kebiri

In this article, we consider elliptic diffusion problems on random domains with non-smooth diffusion coefficients. We start by illustrating the problems that arise from a non-smooth diffusion coefficient by recapitulating the corresponding…

Numerical Analysis · Mathematics 2019-05-15 M. D. Multerer

We propose an update estimation method for a diffusion parameter from high-frequency dependent data under a nuisance drift element. We ensure the asymptotic equivalence of the estimator to the corresponding quasi-MLE, which has the…

Statistics Theory · Mathematics 2015-06-30 Yusuke Shimizu

We import the algebro-geometric notion of a complete collineation into the study of maximum likelihood estimation in directed Gaussian graphical models. A complete collineation produces a perturbation of sample data, which we call a…

Statistics Theory · Mathematics 2023-11-07 Gergely Bérczi , Eloise Hamilton , Philipp Reichenbach , Anna Seigal

We prove regularity and stochastic homogenization results for certain degenerate elliptic equations in nondivergence form. The equation is required to be strictly elliptic, but the ellipticity may oscillate on the microscopic scale and is…

Analysis of PDEs · Mathematics 2014-10-29 Scott N. Armstrong , Charles K. Smart

This paper deals with the problem of inference associated with linear fractional diffusion process with random effects in the drift. In particular we are concerned with the maximum likelihood estimators (MLE) of the random effect…

Statistics Theory · Mathematics 2019-12-04 El Omari Mohamed , Hamid El Maroufy , Christiane Fuchs

In this paper, we propose two new algorithms for maximum-likelihood estimation (MLE) of high dimensional sparse covariance matrices. Unlike most of the state of-the-art methods, which either use regularization techniques or penalize the…

Methodology · Statistics 2023-05-12 Ghania Fatima , Prabhu Babu , Petre Stoica