Non-parametric estimation of the reaction term in semi-linear SPDEs with spatial ergodicity

TL;DR

This paper introduces a non-parametric estimator for the reaction term in semi-linear SPDEs, leveraging spatial ergodicity and advanced calculus techniques to achieve consistency and analyze estimation errors in various asymptotic regimes.

Contribution

It develops a novel estimation method combining Malliavin calculus and ergodic properties for semi-linear SPDEs, with proven consistency and error bounds.

Findings

Estimator is consistent under spatial ergodicity.

Effective in regimes with decreasing diffusivity and noise.

Concentration of occupation time around the occupation measure proved.

Abstract

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 time horizon remains fixed. The analysis of the estimation error requires the concentration of spatial averages of non-linear transformations of the SPDE. The method developed in this paper combines the Clark-Ocone formula from Malliavin calculus with the Markovianity of the SPDE and density estimates. The resulting variance bound utilises the averaging effect of the conditional expectation in the Clark-Ocone formula. The method is applied to two realistic asymptotic regimes. The focus is on a coupling between the diffusivity and the noise level, where both tend to zero. Secondly, the observation of a fixed SPDE on a growing spatial observation window is considered. Furthermore, the concentration of the occupation time around the occupation measure is proved.