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In this note, we establish that the stationary distribution of a possibly non-equilibrium Langevin diffusion converges, as the damping parameter goes to infinity (or equivalently in the Smoluchowski-Kramers vanishing mass limit), toward a…

Probability · Mathematics 2022-01-12 Pierre Monmarché , Mouad Ramil

This work focuses on drift-diffusion equations with fractional dissipation $(-\Delta)^{\alpha}$ in the regime $\alpha \in (1/2,1)$. Our main result is an a priori H\"older estimate on smooth solutions to the Cauchy problem, starting from…

Analysis of PDEs · Mathematics 2016-09-12 Matias G. Delgadino , Scott Smith

We obtain a non-linear generalization of the relativistic diffusion of particles with spin. We discuss diffusion equations whose non-linearity is a consequence of quantum statistics. We show that the assumptions of the relativistic…

High Energy Physics - Theory · Physics 2011-06-20 Z. Haba

The paper develops new methods of non-parametric estimation a compound Poisson distribution. Such a problem arise, in particular, in the inference of a Levy process recorded at equidistant time intervals. Our key estimator is based on…

Statistics Theory · Mathematics 2015-10-19 Alexey Lindo , Sergei Zuyev , Serik Sagitov

The paper presents new simple sharp bounds for transition density functions for time-homogeneous diffusions processes. The bounds are obtained under mild conditions on the drift and diffusion coefficients, extending and substantially…

Probability · Mathematics 2008-12-08 Andrew N. Downes

The purpose of this article is to develop a general parametric estimation theory that allows the derivation of the limit distribution of estimators in non-regular models where the true parameter value may lie on the boundary of the…

Statistics Theory · Mathematics 2022-11-28 Junichiro Yoshida , Nakahiro Yoshida

This work extends the applications of Anderson-type Hamiltonians to include transport characterized by anomalous diffusion. Herein, we investigate the transport properties of a one-dimensional disordered system that employs the discrete…

Mathematical Physics · Physics 2020-03-06 J. L. Padgett , E. G. Kostadinova , C. D. Liaw , K. Busse , L. S. Matthews , T. W. Hyde

We assume that we observe $N$ independent copies of a diffusion process on a time-interval $[0,2T]$. For a given time $t$, we estimate the transition density $p_t(x,y)$, namely the conditional density of $X_{t + s}$ given $X_s = x$, under…

Statistics Theory · Mathematics 2025-05-01 Fabienne Comte , Nicolas Marie

We study the quantitative homogenization of linear second order elliptic equations in non-divergence form with highly oscillating periodic diffusion coefficients and with large drifts, in the so-called ``centered'' setting where…

Analysis of PDEs · Mathematics 2023-07-10 Wenjia Jing , Yiping Zhang

We consider the problem of Arnold's diffusion for nearly integrable isochronous Hamiltonian systems. We prove a shadowing theorem which improves the known estimates for the diffusion time. We also develop a new method for measuring the…

Dynamical Systems · Mathematics 2007-05-23 Massimiliano Berti , Philippe Bolle

We study fluctuations of the empirical processes of a non-equilibrium interacting particle system consisting of two species over a domain that is recently introduced in [8] and establish its functional central limit theorem. This…

Probability · Mathematics 2021-01-12 Zhen-Qing Chen , Wai-Tong Louis Fan

A Hamiltonian reduction approach is defined, studied, and finally used to derive asymptotic models of internal wave propagation in density stratified fluids in two-dimensional domains. Beginning with the general Hamiltonian formalism of…

Fluid Dynamics · Physics 2023-07-26 R. Camassa , G. Falqui , G. Ortenzi , M. Pedroni , T. T. Vu Ho

In this paper, we investigate the asymptotic error distributions of symplectic methods for stochastic Hamiltonian systems and further provide Hamiltonian-specific analysis that clarifies the superiority of symplectic methods. Our…

Numerical Analysis · Mathematics 2025-12-04 Chuchu Chen , Xinyu Chen , Jialin Hong , Yuqian Miao

This paper obtains asymptotic results for parametric inference using prediction-based estimating functions when the data are high frequency observations of a diffusion process with an infinite time horizon. Specifically, the data are…

Statistics Theory · Mathematics 2020-07-27 Emil S. Jørgensen , Michael Sørensen

In this paper, we focus on non-asymptotic bounds related to the Euler scheme of an ergodic diffusion with a possibly multiplicative diffusion term (non-constant diffusion coefficient). More precisely, the objective of this paper is to…

Probability · Mathematics 2022-09-23 Gilles Pages , Fabien Panloup

We propose an update estimation method for a diffusion parameter from high-frequency dependent data under a nuisance drift element. We ensure the asymptotic equivalence of the estimator to the corresponding quasi-MLE, which has the…

Statistics Theory · Mathematics 2015-06-30 Yusuke Shimizu

Penalized estimation methods for diffusion processes and dependent data have recently gained significant attention due to their effectiveness in handling high-dimensional stochastic systems. In this work, we introduce an adaptive…

Statistics Theory · Mathematics 2024-12-24 Alessandro De Gregorio , Dario Frisardi , Francesco Iafrate , Stefano Iacus

As a starting point we prove a functional central limit theorem for estimators of the invariant measure of a geometrically ergodic Harris-recurrent Markov chain in a multi-scale space. This allows to construct confidence bands for the…

Statistics Theory · Mathematics 2020-06-12 Jakob Söhl , Mathias Trabs

Asymptotic theory for approximate martingale estimating functions is generalised to diffusions with finite-activity jumps, when the sampling frequency and terminal sampling time go to infinity. Rate optimality and efficiency are of…

Methodology · Statistics 2018-09-05 Nina Munkholt Jakobsen , Michael Sørensen

The problem of determining a periodic Lipschitz vector field $b=(b_1, \dots, b_d)$ from an observed trajectory of the solution $(X_t: 0 \le t \le T)$ of the multi-dimensional stochastic differential equation \begin{equation*} dX_t =…

Statistics Theory · Mathematics 2020-07-21 Richard Nickl , Kolyan Ray