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Parametric estimation for diffusion processes is considered for high frequency observations over a fixed time interval. The processes solve stochastic differential equations with an unknown parameter in the diffusion coefficient. We find…

Methodology · Statistics 2017-04-03 Nina Munkholt Jakobsen , Michael Sørensen

The nonparametric volatility estimation problem of a scalar diffusion process observed at equidistant time points is addressed. Using the spectral representation of the volatility in terms of the invariant density and an eigenpair of the…

Applications · Statistics 2016-04-01 Jakub Chorowski

We consider the asymptotic behaviour of the solution of one dimensional stochastic differential equations and Langevin equations in periodic backgrounds with zero average. We prove that in several such models, there is generically a non…

Probability · Mathematics 2007-05-23 P. Collet S. Martinez

This work investigates the long-time asymptotic behavior of a diffusing passive scalar advected by fluid flow in a straight channel with a periodically varying cross-section. The goal is to derive an asymptotic expansion for the scalar…

Fluid Dynamics · Physics 2026-04-09 Lingyun Ding

We study approximation of non-autonomous linear differential equations with variable delay over infinite intervals. We use piecewise constant argument to obtain a corresponding discrete difference equation. The study of numerical…

Classical Analysis and ODEs · Mathematics 2016-07-26 Daniel Sepúlveda

We present a graphical approach to deriving inequality constraints for directed acyclic graph (DAG) models, where some variables are unobserved. In particular we show that the observed distribution of a discrete model is always restricted…

Statistics Theory · Mathematics 2012-09-14 Robin J. Evans

We study the problem of training neural stochastic differential equations, or diffusion models, to sample from a Boltzmann distribution without access to target samples. Existing methods for training such models enforce time-reversal of the…

Machine Learning · Computer Science 2026-02-05 Julius Berner , Lorenz Richter , Marcin Sendera , Jarrid Rector-Brooks , Nikolay Malkin

The article is devoted to the nonparametric estimation of the quadratic covariation of non-synchronously observed It\^o processes in an additive microstructure noise model. In a high-frequency setting, we aim at establishing an asymptotic…

Statistics Theory · Mathematics 2011-06-22 Markus Bibinger

A truncated sequential procedure is constructed for estimating the drift coefficient at a given state point based on discrete data of ergodic diffusion process. A nonasymptotic upper bound is obtained for a pointwise absolute error risk.…

Statistics Theory · Mathematics 2015-09-21 L. I. Galtchouk , S. M. Pergamenshchikov

In recent years, discrete fractional epidemic models with reaction-diffusion have become increasingly popular in the literature, not only for its necessity of numerical simulation, but also for its defined physical processes. In this paper,…

Numerical Analysis · Mathematics 2022-08-16 Lu Zhenzhen , Yu Yongguang , Xu Weiyi , Ren Guojian , Meng Xiangyun

This paper addresses the nonparametric estimation of the drift function over a compact domain for a time-homogeneous diffusion process, based on high-frequency discrete observations from $N$ independent trajectories. We propose a neural…

Machine Learning · Statistics 2026-04-01 Yuzhen Zhao , Yating Liu , Marc Hoffmann

Consider a Gaussian nonparametric regression problem having both an unknown mean function and unknown variance function. This article presents a class of difference-based kernel estimators for the variance function. Optimal convergence…

Statistics Theory · Mathematics 2009-09-29 Lawrence D. Brown , M. Levine

Let $x$ denote a diffusion process defined on a closed compact manifold. In an earlier article, the author introduced a new approach to constructing admissible vector fields on the associated space of paths, under the assumption of…

Probability · Mathematics 2007-05-23 Denis Bell

A finite dimensional abstract approximation and convergence theory is developed for estimation of the distribution of random parameters in infinite dimensional discrete time linear systems with dynamics described by regularly dissipative…

Optimization and Control · Mathematics 2019-03-15 Melike Sirlanci , Susan E. Luczak , I. Gary Rosen

A delayed term in a differential equation reflects the fact that information takes significant time to travel from one place to another within a process being studied. Despite de apparent similarity with ordinary differential equations,…

Dynamical Systems · Mathematics 2023-08-24 Gregory Kozyreff

The paper contains some musings about the abstractions introduced by Lucien Le Cam into the asymptotic theory of statistical inference and decision theory. A short, self-contained proof of a key result (existence of randomizations via…

Statistics Theory · Mathematics 2011-07-20 David Pollard

We establish asymptotic properties of $M$-estimators, defined in terms of a contrast function and observations from a continuous-time locally stationary process. Using the stationary approximation of the sequence, $\theta$-weak dependence,…

Statistics Theory · Mathematics 2021-05-11 Bennet Ströh

Anomalous dynamics in which local perturbations spread faster than diffusion are ubiquitously observed in the long-time behavior of a wide variety of systems. Here, the manner by which such systems evolve towards their asymptotic…

Statistical Mechanics · Physics 2020-04-09 Asaf Miron

Diffuse domain methods (DDMs) have garnered significant attention for approximating solutions to partial differential equations on complex geometries. These methods implicitly represent the geometry by replacing the sharp boundary interface…

Analysis of PDEs · Mathematics 2025-04-25 Toai Luong , Tadele Mengesha , Steven M. Wise , Ming Hei Wong

We study a nonlinear semigroup associated to a nonexpansive mapping on a Hadamard space and establish its weak convergence to a fixed point. A discrete-time counterpart of such a semigroup, the proximal point algorithm, turns out to have…

Functional Analysis · Mathematics 2014-07-25 Miroslav Bacak , Simeon Reich