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This paper discusses the non-parametric estimation of a non-linear reaction term in a semi-linear parabolic stochastic partial differential equation (SPDE). The estimator's consistency is due to the spatial ergodicity of the SPDE while the…

Probability · Mathematics 2025-01-09 Sascha Gaudlitz

Nonparametric estimation for semilinear SPDEs, namely stochastic reaction-diffusion equations in one space dimension, is studied. We consider observations of the solution field on a discrete grid in time and space with infill asymptotics in…

Statistics Theory · Mathematics 2023-02-03 Florian Hildebrandt , Mathias Trabs

We consider parameter estimation of the reaction term for a second order linear parabolic stochastic partial differential equation in two space dimensions driven by a $Q$-Wiener process under small diffusivity. We first construct an…

Statistics Theory · Mathematics 2024-04-04 Yozo Tonaki , Yusuke Kaino , Masayuki Uchida

Parameter estimation for a parabolic linear stochastic partial differential equation in one space dimension is studied observing the solution field on a discrete grid in a fixed bounded domain. Considering an infill asymptotic regime in…

Statistics Theory · Mathematics 2019-11-26 Florian Hildebrandt , Mathias Trabs

This paper investigates the well-posedness and small-noise asymptotics of a class of stochastic partial differential equations defined on a bounded domain of $\mathbb{R}^d$, where the diffusion coefficient depends nonlinearly and…

Probability · Mathematics 2025-06-23 Sandra Cerrai , Giuseppina Guatteri , Gianmario Tessitore

We consider parametric estimation for a second order linear parabolic stochastic partial differential equation (SPDE) in two space dimensions driven by a $Q$-Wiener process with a small noise based on high frequency spatio-temporal data. We…

Statistics Theory · Mathematics 2024-08-06 Yozo Tonaki , Yusuke Kaino , Masayuki Uchida

The coefficient function of the leading differential operator is estimated from observations of a linear stochastic partial differential equation (SPDE). The estimation is based on continuous time observations which are localised in space.…

Statistics Theory · Mathematics 2021-03-30 Randolf Altmeyer , Markus Reiß

A framework to establish response theory for a class of nonlinear stochastic partial differential equations (SPDEs) is provided. More specifically, it is shown that for a certain class of observables, the averages of those observables…

Mathematical Physics · Physics 2022-10-24 Giulia Carigi , Tobias Kuna , Jochen Bröcker

We study the numerical approximation of the stochastic heat equation with a distributional reaction term. Under a condition on the Besov regularity of the reaction term, it was proven recently that a strong solution exists and is unique in…

Probability · Mathematics 2024-07-12 Ludovic Goudenège , El Mehdi Haress , Alexandre Richard

We consider the Bayesian nonparametric estimation of a nonlinear reaction function in a reaction-diffusion stochastic partial differential equation (SPDE). The likelihood is well-defined and tractable by the infinite-dimensional Girsanov…

Statistics Theory · Mathematics 2025-07-10 Randolf Altmeyer , Sascha Gaudlitz

Recently, we proposed a method to estimate parameters of stochastic dynamics based on the linear response statistics. The method rests upon a nonlinear least-squares problem that takes into account the response properties that stem from the…

Numerical Analysis · Mathematics 2020-11-24 He Zhang , John Harlim , Xiantao Li

We study a change point model based on a stochastic partial differential equation (SPDE) corresponding to the heat equation governed by the weighted Laplacian $\Delta_\vartheta = \nabla\vartheta\nabla$, where $\vartheta=\vartheta(x)$ is a…

Statistics Theory · Mathematics 2026-03-06 Markus Reiß , Claudia Strauch , Lukas Trottner

We consider the numerical approximation of general semilinear parabolic stochastic partial differential equations (SPDEs) driven by additive space-time noise. In contrast to the standard time stepping methods which uses basic increments of…

Numerical Analysis · Mathematics 2010-05-31 Gabriel J. Lord , Antoine Tambue

A parameter estimation problem for a class of semilinear stochastic evolution equations is considered. Conditions for consistency and asymptotic normality are given in terms of growth and continuity properties of the nonlinear part.…

Statistics Theory · Mathematics 2020-02-26 Gregor Pasemann , Wilhelm Stannat

We develop a statistical toolbox for a quantitative model evaluation of stochastic reaction-diffusion systems modeling space-time evolution of biophysical quantities on the intracellular level. Starting from space-time data $X_N(t,x)$, as,…

Methodology · Statistics 2023-07-14 Gregor Pasemann , Carsten Beta , Wilhelm Stannat

We study the parameter estimation for parabolic, linear, second-order, stochastic partial differential equations (SPDEs) observing a mild solution on a discrete grid in time and space. A high-frequency regime is considered where the mesh of…

Statistics Theory · Mathematics 2019-09-11 Markus Bibinger , Mathias Trabs

We construct estimators for the parameters of a parabolic SPDE with one spatial dimension based on discrete observations of a solution in time and space on a bounded domain. We establish central limit theorems for a high-frequency…

Statistics Theory · Mathematics 2025-04-23 Markus Bibinger , Patrick Bossert

A fully discrete finite difference scheme for stochastic reaction-diffusion equations driven by a $1+1$-dimensional white noise is studied. The optimal strong rate of convergence is proved without posing any regularity assumption on the…

Probability · Mathematics 2024-09-25 Oleg Butkovsky , Konstantinos Dareiotis , Máté Gerencsér

We consider statistics for stochastic evolution equations in Hilbert space with emphasis on stochastic partial differential equations (SPDEs). We observe a solution process under additional measurement errors and want to estimate a real or…

Statistics Theory · Mathematics 2025-05-21 Gregor Pasemann , Markus Reiß

The application of Stochastic Differential Equations (SDEs) to the analysis of temporal data has attracted increasing attention, due to their ability to describe complex dynamics with physically interpretable equations. In this paper, we…

Machine Learning · Statistics 2017-08-09 Constantino A. García , Abraham Otero , Paulo Félix , Jesús Presedo , David G. Márquez
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