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Related papers: Invariant measures for stochastic functional diffe…

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We consider nonparametric invariant density and drift estimation for a class of multidimensional degenerate resp. hypoelliptic diffusion processes, so-called stochastic damping Hamiltonian systems or kinetic diffusions, under anisotropic…

Statistics Theory · Mathematics 2022-05-24 Niklas Dexheimer , Claudia Strauch

This paper studies explicit numerical approximations of the invariant probability measures (IPMs) for stochastic functional differential equations (SFDEs) with infinite delay under one-sided Lipschitz condition on the drift coefficient. To…

Numerical Analysis · Mathematics 2026-03-06 Guozhen Li , Shan Huang , Xiaoyue Li , Xuerong Mao

Given the importance of continuous-time stochastic volatility models to describe the dynamics of interest rates, we propose a goodness-of-fit test for the parametric form of the drift and diffusion functions, based on a marked empirical…

We consider the problem of the Bayesian inference of drift and diffusion coefficient functions in a stochastic differential equation given discrete observations of a realisation of its solution. We give conditions for the well-posedness and…

Statistics Theory · Mathematics 2020-04-10 Jean-Charles Croix , Masoumeh Dashti , Istvàn Zoltàn Kiss

Wave propagation problems have many applications in physics and engineering, and the stochastic effects are important in accurately modeling them due to the uncertainty of the media. This paper considers and analyzes a fully discrete finite…

Numerical Analysis · Mathematics 2021-06-30 Yukun Li , Shuonan Wu , Yulong Xing

In this paper we investigate the long-time behavior of stochastic reaction-diffusion equations of the type $du = (Au + f(u))dt + \sigma(u) dW(t)$, where $A$ is an elliptic operator, $f$ and $\sigma$ are nonlinear maps and $W$ is an infinite…

Analysis of PDEs · Mathematics 2014-11-04 Oleksandr Misiats , Oleksandr Stanzhytsyi , Nung Kwan Yip

An explicit first-order drift-randomized Milstein scheme for a regime switching stochastic differential equation is proposed and its bi-stability and rate of strong convergence are investigated for a non-differentiable drift coefficient.…

Probability · Mathematics 2025-03-11 Divyanshu Vashistha , Chaman Kumar

In this paper, we prove the existence of martingale solutions of a class of stochastic equations with pseudo-monotone drift of polynomial growth of arbitrary order and a continuous diffusion term with superlinear growth. Both the nonlinear…

Probability · Mathematics 2025-05-28 Bixiang Wang

In this work we study certain invariant measures that can be associated to the time averaged observation of a broad class of dissipative semigroups via the notion of a generalized Banach limit. Consider an arbitrary complete separable…

Dynamical Systems · Mathematics 2015-05-30 Micka ël D. Chekroun , Nathan E. Glatt-Holtz

We establish in this paper the existence of weak solutions of infinite-dimensional shift invariant stochastic differential equations driven by a Brownian term. The drift function is very general, in the sense that it is supposed to be…

Probability · Mathematics 2015-09-01 David Dereudre , Sylvie Roelly

We consider It\^o SDE $\d X_t=\sum_{j=1}^m A_j(X_t) \d w_t^j + A_0(X_t) \d t$ on $\R^d$. The diffusion coefficients $A_1,..., A_m$ are supposed to be in the Sobolev space $W_\text{loc}^{1,p} (\R^d)$ with $p>d$, and to have linear growth;…

Probability · Mathematics 2010-01-19 Shizan Fang , Dejun Luo , Anto Thalmaier

In this paper, we study the weak differentiability of global strong solution of stochastic differential equations, the strong Feller property of the associated diffusion semigroups and the global stochastic flow property in which the…

Probability · Mathematics 2022-11-17 Wenjie Ye

We consider the solution to a stochastic differential equation with a drift function which depends smoothly on some real parameter $\lambda$, and admitting a unique invariant measure for any value of $\lambda$ around $\lambda$ = 0. Our aim…

Probability · Mathematics 2015-09-07 Roland Assaraf , Benjamin Jourdain , Tony Lelièvre , Raphaël Roux

A non-parametric diffusion model with an additive fractional Brownian motion noise is considered in this work. The drift is a non-parametric function that will be estimated by two methods. On one hand, we propose a locally linear estimator…

Probability · Mathematics 2014-03-13 Bruno Saussereau

In this paper, we investigate the uniform large deviation principle of the fractional stochastic reaction-diffusion equation on the entire space R^n as the noise intensity approaches zero. The nonlinear drift term is dissipative and has a…

Probability · Mathematics 2024-06-14 Bixiang Wang

The paper concerns the investigation of nonconvex and nondifferentiable integral functionals on general Banach spaces, which may not be reflexive and/or separable. Considering two major subdifferentials of variational analysis, we derive…

Optimization and Control · Mathematics 2016-03-28 Boris S. Mordukhovich , Nobusumi Sagara

In this paper, the Milstein method is used to approximate invariant measures of stochastic differential equations with commutative noise. The decay rate of the transition probability kernel generated by the Milstein method to the unique…

Numerical Analysis · Mathematics 2019-01-28 Lihui Weng , Wei Liu

We study the numerical approximation of the invariant measure of a viscous scalar conservation law, one-dimensional and periodic in the space variable, and stochastically forced with a white-in-time but spatially correlated noise. The flux…

Analysis of PDEs · Mathematics 2021-05-27 Sébastien Boyaval , Sofiane Martel , Julien Reygner

In the present paper, a systematic study is made of quantitative semicontinuity (a.k.a. Lipschitzian) properties of certain multifunctions, which are defined as a solution map associated to a family of parameterized ``split" feasibility…

Optimization and Control · Mathematics 2026-04-01 Amos Uderzo

Stochastic differential equations of Langevin-diffusion form have received significant attention, thanks to their foundational role in both Bayesian sampling algorithms and optimization in machine learning. In the latter, they serve as a…

Optimization and Control · Mathematics 2024-05-14 Fabio V. Difonzo , Vyacheslav Kungurtsev , Jakub Marecek