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Related papers: High-frequency Estimation of the L\'evy-driven Gra…

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A stochastic process is at thermodynamic equilibrium if it obeys time-reversal symmetry; forward and reverse time are statistically indistinguishable at steady state. Non-equilibrium processes break time-reversal symmetry by maintaining…

Mathematical Physics · Physics 2024-11-13 Alexander Strang

The Ornstein-Uhlenbeck process is interpreted as Brownian motion in a harmonic potential. This Gaussian Markov process has a bounded variance and admits a stationary probability distribution, in contrast to the standard Brownian motion. It…

Statistical Mechanics · Physics 2023-06-07 Pece Trajanovski , Petar Jolakoski , Kiril Zelenkovski , Alexander Iomin , Ljupco Kocarev , Trifce Sandev

We consider the fractional Ornstein-Uhlenbeck process with an unknown drift parameter and known Hurst parameter $H$. We propose a new method to test the hypothesis of the sign of the parameter and prove the consistency of the test. Contrary…

Probability · Mathematics 2016-04-12 Alexander Kukush , Yuliya Mishura , Kostiantyn Ralchenko

Measurement on sets with a specific geometric shape can be of interest for many important applications (e.g. measurement along the isotherms in structural engineering). In the present paper the properties of optimal designs for estimating…

Methodology · Statistics 2015-07-21 Sándor Baran , Milan Stehlík

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

In the present paper we study the asymptotic behavior of the auto-covariance function for Ornstein-Uhlenbeck (OU) processes driven by Gaussian noises with stationary and non-stationary increments and for Hermite OU processes. Our results…

Probability · Mathematics 2022-01-19 Khalifa Es-Sebaiy

Stochastic gradient descent is a classic algorithm that has gained great popularity especially in the last decades as the most common approach for training models in machine learning. While the algorithm has been well-studied when…

Machine Learning · Statistics 2025-09-09 Jose Blanchet , Aleksandar Mijatović , Wenhao Yang

We consider high frequency samples from ergodic L\'evy driven stochastic differential equation (SDE) with drift coefficient $a(x,\alpha)$ and scale coefficient $c(x,\gamma)$ involving unknown parameters $\alpha$ and $\gamma$. We suppose…

Statistics Theory · Mathematics 2016-01-12 Hiroki Masuda , Yuma Uehara

In this article we study the asymptotic behaviour of the realized quadratic variation of a process $\int_{0}^{t}u_{s}dY_{s}^{(1)}$% , where $u$ is a $\beta$-H\"older continuous process with $\beta > 1-H$ and…

Probability · Mathematics 2018-02-28 Salwa Bajja , Khalifa Es-Sebaiy , Lauri Viitasaari

Modern methods of generative modelling and unpaired data translation based on Schr\"odinger bridges and stochastic optimal control theory aim to transform an initial density to a target one in an optimal way. In the present paper, we assume…

Machine Learning · Computer Science 2026-03-24 Nikita Puchkin , Denis Suchkov , Alexey Naumov , Denis Belomestny

We obtain Fisher-Hartwig asymptotics with root and jump type singularities in space-time under the law of the stationary Hermitian Ornstein-Uhlenbeck process, which serve as a dynamical generalization of earlier static results obtained by…

Probability · Mathematics 2025-08-18 Ahmet Keles

We study fundamental graph parameters such as the Diameter and Radius in directed graphs, when distances are measured using a somewhat unorthodox but natural measure: the distance between $u$ and $v$ is the minimum of the shortest path…

Data Structures and Algorithms · Computer Science 2019-06-18 Mina Dalirrooyfard , Virginia Vassilevska Williams , Nikhil Vyas , Nicole Wein , Yinzhan Xu , Yuancheng Yu

Assuming that a L\'evy-Driven Ornstein-Uhlenbeck (or CAR(1)) processes is observed at discrete times $0$, $h$, $2h$,$\cdots$ $[T/h]h$. We introduce a step-by-step methodological approach on how a person would verify the model assumptions.…

Applications · Statistics 2025-01-14 Ibrahim Abdelrazeq , Hardy Smith , Dinmukhammed Zhanbyrshy

We study a class of graphs that represent local independence structures in stochastic processes allowing for correlated error processes. Several graphs may encode the same local independencies and we characterize such equivalence classes of…

Statistics Theory · Mathematics 2022-09-01 Søren Wengel Mogensen , Niels Richard Hansen

Efficient estimation of a non-Gaussian stable Levy process with drift and symmetric jumps observed at high frequency is considered. For this statistical experiment, the local asymptotic normality of the likelihood is proved with a…

Statistics Theory · Mathematics 2025-08-19 Alexandre Brouste , Hiroki Masuda

This paper considers the effect of least squares procedures for nearly unstable linear time series with strongly dependent innovations. Under a general framework and appropriate scaling, it is shown that ordinary least squares procedures…

Statistics Theory · Mathematics 2009-09-29 Boris Buchmann , Ngai Hang Chan

We consider equations of nonlinear transport on the circle with regular self interactions appearing in aggregation models and deterministic mean field dynamics. We introduce a random perturbation of such systems through a stochastic…

Probability · Mathematics 2026-01-07 Max-K. von Renesse , Feng-Yu Wang , Alexander Weiß

We consider a simple mean reverting diffusion process, with piecewise constant drift and diffusion coefficients, discontinuous at a fixed threshold. We discuss estimation of drift and diffusion parameters from discrete observations of the…

Statistics Theory · Mathematics 2024-03-12 Sara Mazzonetto , Paolo Pigato

This article establishes the cutoff phenomenon in the Wasserstein distance for systems of nonlinear ordinary differential equations with a unique coercive stable fixed point subject to general additive Markovian noise in the limit of small…

Probability · Mathematics 2023-05-05 Gerardo Barrera , Michael A. Högele , Juan Carlos Pardo

We prove a metric space scaling limit for a critical random graph with independent and identically distributed degrees having power-law tail behaviour with exponent $\alpha+1$, where $\alpha \in (1,2)$. The limiting components are…

Probability · Mathematics 2021-08-02 Guillaume Conchon--Kerjan , Christina Goldschmidt