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We define various higher-order Markov properties for stochastic processes $(X(t))_{t\in \mathbb{T}}$, indexed by an interval $\mathbb{T} \subseteq \mathbb{R}$ and taking values in a real and separable Hilbert space $U$. We furthermore…

Probability · Mathematics 2026-01-06 Kristin Kirchner , Joshua Willems

We investigate the problem of estimating the drift parameter of a high-dimensional L\'evy-driven Ornstein--Uhlenbeck process under sparsity constraints. It is shown that both Lasso and Slope estimators achieve the minimax optimal rate of…

Statistics Theory · Mathematics 2022-05-17 Niklas Dexheimer , Claudia Strauch

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

We consider a positive stationary generalized Ornstein--Uhlenbeck process \[V_t=\mathrm{e}^{-\xi_t}\biggl(\int_0^t\mathrm{e}^{\xi_{s-}}\ ,\mathrm{d}\eta_s+V_0\biggr)\qquadfor t\geq0,\] and the increments of the integrated generalized…

Statistics Theory · Mathematics 2010-02-24 Vicky Fasen

Even in a simple stochastic process, the study of the full distribution of time integrated observables can be a difficult task. This is the case of a much-studied process such as the Ornstein-Uhlenbeck process where, recently, anomalous…

Statistical Mechanics · Physics 2025-04-09 Alberto Bassanoni , Alessandro Vezzani , Eli Barkai , Raffaella Burioni

We investigate properties of Markov quasi-diffusion processes corresponding to elliptic operators $L=a^{ij}D_{ij}+b^{i}D_{i}$, acting on functions on $\mathbb{R}^{d}$, with measurable coefficients, bounded and uniformly elliptic $a$ and…

Probability · Mathematics 2020-04-01 N. V. Krylov

This paper is devoted to the study of a stochastic process obtained by random switching between a finite collection of vector fields. Such processes have recently been the focus of much attention in the case where the switching times are…

Probability · Mathematics 2025-10-01 Tobias Hurth , Edouard Strickler

Univariate superpositions of Ornstein--Uhlenbeck-type processes (OU), called supOU processes, provide a class of continuous time processes capable of exhibiting long memory behavior. This paper introduces multivariate supOU processes and…

Probability · Mathematics 2011-01-04 Ole Eiler Barndorff-Nielsen , Robert Stelzer

Our first result concerns a characterisation by means of a functional equation of Poisson point processes conditioned by the value of their first moment. It leads to a generalised version of Mecke's formula. En passant, it also allows to…

Probability · Mathematics 2018-09-25 Giovanni Conforti , Tetiana Kosenkova , Sylvie Roelly

We study SDE $$ d X_t = b(X_t) \, dt + A(X_{t-}) \, d Z_t, \quad X_{0} = x \in \mathbb{R}^d, \quad t \geq 0 $$ where $Z=(Z^1, \dots, Z^d)^T$, with $Z^i, i=1,\dots, d$ being independent one-dimensional symmetric jump L\'evy processes, not…

Probability · Mathematics 2022-08-16 Tadeusz Kulczycki , Oleksii Kulyk , Michał Ryznar

In this paper, we derive closed-form expressions for significant statistical properties of the link signal-to-noise ratio (SNR) and the separation distance in mobile ad hoc networks subject to Ornstein-Uhlenbeck (OU) mobility and Rayleigh…

Dynamical Systems · Mathematics 2019-12-23 Arta Cika , Mihai-Alin Badiu , Justin P. Coon

We consider the problem of estimation of the drift parameter of an ergodic Ornstein--Uhlenbeck type process driven by a L\'evy process with heavy tails. The process is observed continuously on a long time interval $[0,T]$, $T\to\infty$. We…

Statistics Theory · Mathematics 2019-11-27 Alexander Gushchin , Ilya Pavlyukevich , Marian Ritsch

In this paper, we study the cut-off phenomenon under the total variation distance of $d$-dimensional Ornstein-Uhlenbeck processes which are driven by L\'evy processes. That is to say, under the total variation distance, there is an abrupt…

Probability · Mathematics 2023-05-05 Gerardo Barrera , Juan Carlos Pardo

Dunkl processes are multidimensional Markov processes defined through the use of Dunkl operators. These processes have discontinuities, and they can be separated into their continuous (radial) part, and their discontinuous (jump) part.…

Mathematical Physics · Physics 2021-05-20 Sergio Andraus

A linear Boltzmann equation is interpreted as the forward equation for the probability density of a Markov process (K(t), Y(t)), where K(t) is a autonomous reversible jump process, with waiting times between two jumps with finite…

Probability · Mathematics 2015-12-04 Giada Basile , Anton Bovier

Under full H\"ormander's conditions, we prove the strong Feller property of the semigroup determined by an SDE driven by additive subordinate Brownian motion, where the drift is allowed to be arbitrarily growth. For this, we extend a…

Probability · Mathematics 2014-02-18 Zhao Dong , Xuhui Peng , Yulin Song , Xicheng Zhang

This paper deals with control of partially observable discrete-time stochastic systems. It introduces and studies Markov Decision Processes with Incomplete Information and with semi-uniform Feller transition probabilities. The important…

Optimization and Control · Mathematics 2022-08-30 Eugene A. Feinberg , Pavlo O. Kasyanov , Michael Z. Zgurovsky

The small noise cut-off phenomenon in continuous time and space has been studied in the recent literature for the linear and non-linear stable Langevin dynamics with additive L\'evy drivers - understood as abrupt thermalization of the…

Probability · Mathematics 2025-02-13 Gerardo Barrera , Michael A. Högele , Pauliina Ilmonen , Lauri Viitasaari

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

We consider a bivariate process $X_t=(X^1_t,X^2_t)$, which is observed on a finite time interval $[0,T]$ at discrete times $0,\Delta_n,2\Delta_n,....$ Assuming that its two components $X^1$ and $X^2$ have jumps on $[0,T]$, we derive tests…

Statistics Theory · Mathematics 2009-08-14 Jean Jacod , Viktor Todorov