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We investigate the stochastic processes obtained as the fractional Riemann-Liouville integral of order $\alpha \in (0,1)$ of Gauss-Markov processes. The general expressions of the mean, variance and covariance functions are given. Due to…

Probability · Mathematics 2019-05-21 Mario Abundo , Enrica Pirozzi

We investigate the dynamics of an inertial active Ornstein-Uhlenbeck particle suspended in a non-Markovian environment. The particle is additionally subjected to external forces, such as harmonic confinement and a magnetic field. Motivated…

Soft Condensed Matter · Physics 2025-10-15 Sanju S Pillai , M Muhsin , M Sahoo

While short-range dependence is widely assumed in the literature for its simplicity, long-range dependence is a feature that has been observed in data from finance, hydrology, geophysics and economics. In this paper, we extend a…

Methodology · Statistics 2019-05-20 Michele Nguyen , Almut E. D. Veraart

The Fokker-Planck equation has been very useful for studying dynamic behavior of stochastic differential equations driven by Gaussian noises. However, there are both theoretical and empirical reasons to consider similar equations driven by…

chao-dyn · Physics 2007-05-23 D. Schertzer , M. Larchevêque , J. Duan , V. V. Yanovsky , S. Lovejoy

The purpose of this article is to derive the crossover from the Ornstein-Uhlenbeck process to energy solutions of the stochastic Burgers equation with characteristic operators given in terms of fractional operators, such as the regional…

Probability · Mathematics 2024-12-16 Pedro Cardoso , Patrícia Gonçalves

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

The steady state of the Fokker-Planck equation corresponding to a density dependent one-step process is approximated by a suitable normal distribution. Starting from the master equations of the process, written in terms of the time…

Dynamical Systems · Mathematics 2016-09-16 Peter L. Simon , Eszter Sikolya

We are interested in the law of the first passage time of an Ornstein-Uhlenbeck process to time-varying thresholds. We show that this problem is connected to the laws of the first passage time of the process to members of a two-parameter…

Probability · Mathematics 2024-03-26 Aria Ahari , Larbi Alili , Massimiliano Tamborrino

In this paper, we study the Ornstein-Uhlenbeck bridge process (i.e. the Ornstein-Uhlenbeck process conditioned to start and end at fixed points) constraints to have a fixed area under its path. We present both anticipative (in this case, we…

Statistical Mechanics · Physics 2017-10-11 Alain Mazzolo

We prove the transfer principle for fractional Ornstein-Uhlenbeck processes, i.e., we construct a Brownian motion that has the same filtration as the fractional Ornstein-Uhlenbeck process and then represent the fractional Ornstein-Uhlenbeck…

Probability · Mathematics 2023-11-03 Tommi Sottinen , Lauri Viitasaari

The Fokker-Planck equation is a partial differential equation that describes the evolution of a probability distribution over time. It is used to model a wide range of physical and biological phenomena, such as diffusion, chemical…

Computational Physics · Physics 2023-11-29 Wisit Mangthas , Waipot Ngamsaad

We propose a new approach to describe the effective microscopic dynamics of (power-law) nonlinear Fokker-Planck equations. Our formalism is based on a nonextensive generalization of the Wiener process. This allow us to obtain, in addition…

Statistical Mechanics · Physics 2021-03-17 Leonardo Santos

A generalized Langevin equation is suggested to describe a system with memory($u(t,t') = \frac{1}{\Gamma (\nu )}(t - t')^\nu $) as well as with positive and negative damping. The equation can be transformed into the Fokker-Planck equation…

Physics and Society · Physics 2019-09-11 Peng Wang , Feng-Chun Pan , Jie Huo , Xu-Ming Wang

Field equations with time and coordinates derivatives of noninteger order are derived from stationary action principle for the cases of power-law memory function and long-range interaction in systems. The method is applied to obtain a…

Mathematical Physics · Physics 2015-03-11 Vasily E. Tarasov , George M. Zaslavsky

In Chen and Zhou 2021, they 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…

Statistics Theory · Mathematics 2021-12-30 Yong Chen , Xiangmeng Gu , Ying Li

The Ornstein-Uhlenbeck process may be used to generate a noise signal with a finite correlation time. If a one-dimensional stochastic process is driven by such a noise source, it may be analysed by solving a Fokker-Planck equation in two…

Data Analysis, Statistics and Probability · Physics 2015-05-14 Michael Wilkinson

This paper is devoted to the fractional generalization of the Fokker-Planck equation associated with a stochastic differential equation in a bounded domain. The driving process of the stochastic differential equation is a L\'evy process…

Mathematical Physics · Physics 2016-10-27 Sabir Umarov

The fractional Ornstein-Uhleneck (fOU) process is described by the overdamped Langevin equation $\dot{x}(t)+\gamma x=\sqrt{2 D}\xi(t)$, where $\xi(t)$ is the fractional Gaussian noise with the Hurst exponent $0<H<1$. For $H\neq 1/2$ the fOU…

Statistical Mechanics · Physics 2025-03-03 Alexander Valov , Baruch Meerson

This paper investigates the transient probabilistic responses of nonlinear single-degree-of-freedom oscillators subjected to external fractional Gaussian noise (FGN) excitation. Owing to the inherent long-range correlations and memory…

Probability · Mathematics 2026-05-28 Lifang Feng , Bin Pei , Yong Xu

Gaussian Process state-space models capture complex temporal dependencies in a principled manner by placing a Gaussian Process prior on the transition function. These models have a natural interpretation as discretized stochastic…

Machine Learning · Computer Science 2022-02-24 Krista Longi , Jakob Lindinger , Olaf Duennbier , Melih Kandemir , Arto Klami , Barbara Rakitsch