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Related papers: Intervention in Ornstein-Uhlenbeck SDEs

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We consider a mixed stochastic differential equation driven by possibly dependent fractional Brownian motion and Brownian motion. Under mild regularity assumptions on the coefficients, it is proved that the equation has a unique solution.

Probability · Mathematics 2011-11-09 Yuliya Mishura , Georgiy Shevchenko

We derive bridges from general multidimensional linear non time-homogeneous processes using only the transition densities of the original process giving their integral representations (in terms of a standard Wiener process) and so-called…

Probability · Mathematics 2014-03-25 Matyas Barczy , Peter Kern

We consider the inverse problem of determining initial data in general Ornstein-Uhlenbeck equations on the Euclidean space from partial measurement localized on the so-called thick sets. Using the logarithmic convexity technique and recent…

Analysis of PDEs · Mathematics 2023-06-13 S. E. Chorfi , L. Maniar

We identify effective stochastic differential equations (SDE) for coarse observables of fine-grained particle- or agent-based simulations; these SDE then provide useful coarse surrogate models of the fine scale dynamics. We approximate the…

We introduce a stochastic partial differential equation (SPDE) with elliptic operator in divergence form, with measurable and bounded coefficients and driven by space-time white noise. Such SPDEs could be used in mathematical modelling of…

Probability · Mathematics 2020-01-09 Mounir Zili , Eya Zougar

~It is considered a transmittion process of a useful signal in Ornstein-Uhlenbeck model in $\mathbb{C}[-l,l[$ defined by the stochastic differential equation $$ d\Psi(t,x,\omega)=\sum_{n=0}^{2m} A_n\frac{\partial^{n}}{\partial…

Statistics Theory · Mathematics 2016-12-20 Levan Labadze , Zurab Kvatadze , Gogi Pantsulaia

In this paper, we prove a sufficient and necessary condition for the transition probability distribution of a general, time-inhomogeneous linear SDE to possess a density function and study the differentiability of the density function and…

Probability · Mathematics 2020-07-09 Xue Dong He , Zhaoli Jiang

A method for analyzing non-asymptotic guarantees of numerical discretizations of ergodic SDEs in Wasserstein-2 distance is presented by Sanz-Serna and Zygalakis in ``Wasserstein distance estimates for the distributions of numerical…

Machine Learning · Statistics 2024-12-03 Daniel Paulin , Peter A. Whalley

In this work, we introduce and study nonlinear Schr\"odinger equations (NLS) with anisotropic dispersion, where the standard Laplacian acts on the Euclidean variable \(x \in \mathbb{R}^d\), and an Ornstein-Uhlenbeck ($\mathcal{OU}$)…

Analysis of PDEs · Mathematics 2025-10-21 Xueying Yu , Haitian Yue , Zehua Zhao

Stochastic differential equations provide a powerful tool for modelling dynamic phenomena affected by random noise. In case of repeated observations of time series for several experimental units, it is often the case that some of the…

Methodology · Statistics 2024-09-06 Fernando Baltazar-Larios , Mogens Bladt , Michael Sørensen

Retarded stochastic differential equations (SDEs) constitute a large collection of systems arising in various real-life applications. Most of the existing results make crucial use of dissipative conditions. Dealing with "pure delay" systems…

Probability · Mathematics 2013-08-12 Jianhai Bao , George Yin , Chenggui Yuan

We propose an explicit drift-randomised Milstein scheme for both McKean--Vlasov stochastic differential equations and associated high-dimensional interacting particle systems with common noise. By using a drift-randomisation step in space…

Probability · Mathematics 2023-06-19 Sani Biswas , Chaman Kumar , Neelima , Gonçalo dos Reis , Christoph Reisinger

Unique existence of analytically strong solutions to stochastic partial differential equations (SPDE) with drift given by the subdifferential of a quasi-convex function and with general multiplicative noise is proven. The proof applies a…

Probability · Mathematics 2011-04-22 Benjamin Gess

We analyze the concepts of analytically weak solutions of stochastic differential equations (SDEs) in Hilbert spaces with time-dependent unbounded operators and give conditions for existence and uniqueness of such solutions. Our studies are…

Functional Analysis · Mathematics 2013-01-31 Benedict Baur , Martin Grothaus , Tan Thanh Mai

This paper deals with the realisation of affine constraints on nonreversible stochastic differential equations (SDE) by strong confining forces. We prove that the confined dynamics converges pathwise and on bounded time intervals to the…

Probability · Mathematics 2025-05-02 Carsten Hartmann , Lara Neureither , Upanshu Sharma

We consider an infinite system of coupled stochastic differential equations (SDE) describing dynamics of the following infinite particle system. Each partricle is characterised by its position $x\in \mathbb{R}^{d}$ and internal parameter…

Functional Analysis · Mathematics 2025-02-21 Georgy Chargaziya , Alexei Daletskii

We prove uniqueness in law for possibly degenerate SDEs having a linear part in the drift term. Diffusion coefficients corresponding to non-degenerate directions of the noise are assumed to be continuous. When the diffusion part is constant…

Probability · Mathematics 2014-09-03 Enrico Priola

This paper continues the study of [11, 13] for stationary solutions of stochastic linear retarded functional differential equations with the emphasis on delays which appear in those terms including spatial partial derivatives. As a…

Probability · Mathematics 2014-02-11 Kai Liu

The use of an Ornstein-Uhlenbeck (OU) process is ubiquitous in business, economics and finance to capture various price processes and evolution of economic indicators exhibiting mean-reverting properties. When structural changes happen,…

Methodology · Statistics 2017-05-30 Fuqi Chen , Rogemar Mamon , Matt Davison

We investigate the joint distribution and the multivariate survival functions for the maxima of an Ornstein-Uhlenbeck (OU) process in consecutive time-intervals. A PDE method, alongside an eigenfunction expansion, is adopted with which we…

Probability · Mathematics 2020-10-19 Yupeng Jiang , Andrea Macrina , Gareth W. Peters