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Via a Bismut-Elworthy-Li formula from [KPP23], we derive uniform gradient estimates for transition semigroups associated with stochastic differential equations driven by a large class of cylindrical L\'{e}vy processes which includes the…

Probability · Mathematics 2025-09-09 Thanh Dang , Lingjiong Zhu

We consider the Ornstein-Uhlenbeck process with a broad initial probability distribution (Levy distribution), which exhibits so-called non-spectral modes. The relaxation of such modes differs from those determined from the parameters of the…

Data Analysis, Statistics and Probability · Physics 2016-09-14 F. Thiel , I. M. Sokolov , E. B. Postnikov

We prove a generalisation of Fernique's theorem which applies to a class of (measurable) functionals on abstract Wiener spaces by using the isoperimetric inequality. Our motivation comes from rough path theory where one deals with iterated…

Probability · Mathematics 2010-04-14 Peter Friz , Harald Oberhauser

This paper is devoted to a construction of the stochastic It\^o integral with respect to infinite dimensional cylindrical Wiener process. The construction given is an alternative one to that introduced by DaPrato and Zabczyk [3]. The…

Probability · Mathematics 2007-05-23 Anna Karczewska

We use asymptotic methods from the theory of differential equations to obtain an analytical expression for the survival probability of an Ornstein-Uhlenbeck process with a potential defined over a broad domain. We form a uniformly…

Statistical Mechanics · Physics 2020-11-26 L. T. Giorgini , W. Moon , J. S. Wettlaufer

We consider the problem of efficient estimation of the drift parameter of an Ornstein-Uhlenbeck type process driven by a L\'{e}vy process when high-frequency observations are given. The estimator is constructed from the time-continuous…

Statistics Theory · Mathematics 2014-03-13 Hilmar Mai

In this paper an analytic operator-valued generalized Feynman integral was studied on a very general Wiener space $C_{a,b}[0,T]$. The general Wiener space $C_{a,b}[0,T]$ is a function space which is induced by the generalized Brownian…

Probability · Mathematics 2021-12-30 Jae Gil Choi

We obtain strong consistency and asymptotic normality of a least squares estimator of the drift coefficient for complex-valued Ornstein-Uhlenbeck processes disturbed by fractional noise, extending the result of Y. Hu and D. Nualart,…

Probability · Mathematics 2017-01-27 Yong Chen , Yaozhong Hu , Zhi Wang

Here we review and extend central limit theorems for highly chaotic but deterministic semi-dynamical discrete time systems. We then apply these results show how Brownian motion-like results are recovered, and how an Ornstein-Uhlenbeck…

Statistical Mechanics · Physics 2008-04-15 Michael C. Mackey , Marta Tyran-Kaminska

We consider a fractional Ornstein-Uhlenbeck process involving a stochastic forcing term in the drift, as a solution of a linear stochastic differential equation driven by a fractional Brownian motion. For such process we specify mean and…

Probability · Mathematics 2020-09-25 Giacomo Ascione , Yuliya Mishura , Enrica Pirozzi

An $N$-particle system with stochastic interactions is considered. Interactions are driven by a Brownian noise term and total energy conservation is imposed. The evolution of the system, in velocity space, is a diffusion on a…

Mathematical Physics · Physics 2013-08-16 Bruno Vieira Ribeiro , Yves Elskens

By using absolutely continuous lower bounds of the L\'evy measure, explicit gradient estimates are derived for the semigroup of the corresponding L\'evy process with a linear drift. A derivative formula is presented for the conditional…

Probability · Mathematics 2011-03-16 Feng-Yu Wang

The Ornstein-Uhlenbeck (OU) process describes the dynamics of Brownian particles in a confining harmonic potential, thereby constituting the paradigmatic model of overdamped, mean-reverting Langevin dynamics. Despite its widespread…

Statistical Mechanics · Physics 2024-05-16 Luca Cocconi , Henry Alston , Jacopo Romano , Thibault Bertrand

In this paper, we consider an inference problem for an Ornstein-Uhlenbeck process driven by a general one-dimensional centered Gaussian process $(G_t)_{t\ge 0}$. The second order mixed partial derivative of the covariance function $ R(t,\,…

Probability · Mathematics 2020-02-25 Yong Chen , Hongjuan Zhou

We consider the problem of modelling restricted interactions between continuously-observed time series as given by a known static graph (or network) structure. For this purpose, we define a parametric multivariate Graph Ornstein-Uhlenbeck…

Statistics Theory · Mathematics 2021-07-08 Valentin Courgeau , Almut E. D. Veraart

In this work we investigate the long time behavior of the Ornstein-Uhlenbeck process driven by Levy noise with regime-switching. We provide explicit criteria on the transience and recurrence of this process. Contrasted with the…

Probability · Mathematics 2019-06-21 Zhong-Wei Liao , Jinghai Shao

In this paper, we establish the existence of transition density for geometric $\alpha$-stable processes by using the property of self-decomposability--a fundamental concept in the theory of L\'evy processes. In contrast to traditional and…

Probability · Mathematics 2026-03-13 Kaneharu Tsuchida

In this paper, we study an approximation scheme for L\'evy processes with drift in terms of a representation that is akin to the celebrated Mehler formula for L\'evy-Ornstein-Uhlenbeck processes. The approximation scheme is based on a…

Probability · Mathematics 2025-11-25 Max Nendel

We characterise the nonequilibrium stationary state of a generic multivariate Ornstein-Uhlenbeck process involving $N$ degrees of freedom. The irreversibility of the process is encoded in the antisymmetric part of the Onsager matrix. The…

Statistical Mechanics · Physics 2018-12-19 Claude Godrèche , Jean-Marc Luck

Dilative stability generalizes the property of selfsimilarity for infinitely divisible stochastic processes by introducing an additional scaling in the convolution exponent. Inspired by results of Igl\'oi, we will show how dilatively stable…

Probability · Mathematics 2018-06-15 Thorsten Bhatti , Peter Kern