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For the Ornstein-Uhlenbeck process, the asymptotic behavior of the maximum likelihood estimator of the drift parameter is totally different in the stable, unstable, and explosive cases. Notwithstanding of this trichotomy, we investigate…

Probability · Mathematics 2011-11-28 Bernard Bercu , Laure Coutin , Nicolas Savy

We show that alpha stable L\'evy motions can be simulated by any ergodic and aperiodic probability preserving transformation. Namely we show: - for $0<\alpha<1$ and every $\alpha$ stable L\'evy motion $\mathbb{W}$, there exists a function f…

Dynamical Systems · Mathematics 2023-09-13 Zemer Kosloff , Dalibor Volný

We consider a one-dimensional stationary time series of fixed duration $T$. We investigate the time $t_{\rm m}$ at which the process reaches the global maximum within the time interval $[0,T]$. By using a path-decomposition technique, we…

Statistical Mechanics · Physics 2022-11-23 Francesco Mori , Satya N. Majumdar , Gregory Schehr

We consider the steady-state behavior of pairs of active particles having different persistence times and diffusivities. To this purpose we employ the active Ornstein-Uhlenbeck model, where the particles are driven by colored noises with…

Soft Condensed Matter · Physics 2018-01-17 René Wittmann , Joseph M. Brader , Abhinav Sharma , Umberto Marini Bettolo Marconi

We consider a stationary queueing process $Q_X$ fed by a centered Gaussian process $X$ with stationary increments and variance function satisfying classical regularity conditions. A criterion when, for a given function $f$, $\mathbb P…

Probability · Mathematics 2018-05-22 Kamil Marcin Kosiński , Peng Liu

A version of the saddle point method is developed, which allows one to describe exactly the asymptotic behavior of distribution densities of Levy driven stochastic integrals with deterministic kernels. Exact asymptotic behavior is…

Probability · Mathematics 2011-02-08 Victoria P. Knopova , Alexey M. Kulik

In stochastic population dynamics, stochastic wandering can produce transition to an absorbing state. In particular, under Allee effects, low densities amplify the possibility of population collapse. We investigate this in an…

Populations and Evolution · Quantitative Biology 2026-01-13 Luis F. Gordillo , Priscilla E. Greenwood

We study the problem of estimating a sequence of evolving probability distributions from historical data, where the underlying distribution changes over time in a nonstationary and nonparametric manner. To capture gradual changes, we…

Optimization and Control · Mathematics 2025-12-16 Edward J. Anderson , Dominic S. T. Keehan

Diesel engine particulate matter (PM) is one of the most challenging emission constituents to predict. As engines become cleaner and emissions levels drop, manufacturers need reliable methods to quantify the PM generated by production…

Applications · Statistics 2026-03-16 Maxwell Bolt , Alex Alberts , Akash S. Desai , Peter Meckl , Ilias Bilionis

We give new and explicitly computable examples of Gibbs-non-Gibbs transitions of mean-field type, using the large deviation approach introduced in [4]. These examples include Brownian motion with small variance and related diffusion…

Probability · Mathematics 2012-12-05 Frank Redig , Feijia Wang

We consider a process $Z$ on the real line composed from a L\'evy process and its exponentially tilted version killed with arbitrary rates and give an expression for the joint law of $Z$ seen from its supremum, the supremum $\overline Z$…

Probability · Mathematics 2014-05-15 Sebastian Engelke , Jevgenijs Ivanovs

Asymptotic behavior of a class of nonlinear Schr\"odinger equations are studied. Particular cases of 1D weakly focusing and Bose-Einstein condensates are considered. A statistical approach is presented to describe the stationary probability…

Condensed Matter · Physics 2009-11-10 Christophe Josserand

Conditions are given, sufficient for the distribution of an Ornstein-Uhlenbeck process with L\'evy noise to be absolutely continuous or to possess a smooth density. For the processes with non-degenerate drift coefficient, these conditions…

Probability · Mathematics 2008-06-04 Semen V. Bodnarchuk , Alexey M. Kulik

In this paper, we consider the composition of two independent processes : one process corresponds to position and the other one to time. Such processes will be called iterated processes. We first propose an algorithm based on the Euler…

Probability · Mathematics 2017-05-03 Michèle Thieullen , Alexis Vigot

We consider the problem of simulating diffusion bridges, which are diffusion processes that are conditioned to initialize and terminate at two given states. The simulation of diffusion bridges has applications in diverse scientific fields…

Computation · Statistics 2025-06-19 Jeremy Heng , Valentin De Bortoli , Arnaud Doucet , James Thornton

Denoising diffusion probabilistic models (DDPMs) represent a recent advance in generative modelling that has delivered state-of-the-art results across many domains of applications. Despite their success, a rigorous theoretical understanding…

Statistics Theory · Mathematics 2025-08-21 Miha Brešar , Aleksandar Mijatović

In this paper we consider a branching particle system consisting of particles moving according to the Ornstein-Uhlenbeck process in $\Rd$ and undergoing a binary, supercritical branching with a constant rate $\lambda>0$. This system is…

Probability · Mathematics 2011-11-23 Radosław Adamczak , Piotr Miłoś

Confined active particles constitute simple, yet realistic, examples of systems that converge into a non-equilibrium steady state. We investigate a run-and-tumble particle in one spatial dimension, trapped by an external potential, with a…

Statistical Mechanics · Physics 2024-04-09 Oded Farago , Naftali R. Smith

The purpose of this article is a set-indexed extension of the well-known Ornstein-Uhlenbeck process. The first part is devoted to a stationary definition of the random field and ends up with the proof of a complete characterization by its…

Probability · Mathematics 2013-08-29 Paul Balança , Erick Herbin

Given the observation of a high-dimensional Ornstein-Uhlenbeck (OU) process in continuous time, we proceed to the inference of the drift parameter under a row-sparsity assumption. Towards that aim, we consider the negative log-likelihood of…

Machine Learning · Statistics 2017-07-12 Stéphane Gaïffas , Gustaw Matulewicz