Backend
A functional central limit theorem for particle systems under polynomial growth conditions, with applications to statistics
arXiv stat.TH0 views
arXiv:2610.34347v1 Announce Type: cross Abstract: We establish a functional central limit theorem (CLT) for fluctuations of time-integrated functionals of empirical measures arising from interacting McKean--Vlasov particle systems. Our framework allows for coefficients with unbounded spatial growth and dependence on arbitrarily high-order moments of the measure variable, extending the scope of the existing fluctuation theory. The proof uses a novel approach combining linear functional differentiation with new well-posedness results and estimates for perturbed backward parabolic equations in polynomially weighted Schauder spaces, yielding a martingale-type representation of the fluctuations with an asymptotically negligible remainder. The limiting process is shown to be centred Gaussian with an explicit covariance structure. As a statistical application, we derive the asymptotic theory underlying hypothesis tests for both the temporal constancy of population characteristics and parametric restrictions on the drift coefficient.
Source:https://arxiv.org/abs/2610.34347PreviousNonlinear Reduced-Bias Extreme Value Index Estimators: A Comparative StudyNextThe German Tank Problem & Navigating by Scent
Related posts
FiveM Script Database Migrations: What to Check Before You Install
0dev.to
The insurance edge case that breaks event-driven policy pipelines
0dev.to
The fix for an empty state isn't filling it
0dev.to UX
Five Things That Make Dependabot Painful for Terraform
0dev.to GitHub
Tracking Roblox player counts: what the public data actually gives you
0dev.to Data
Telegram gold signals this week: results to Oct 30
0dev.to Data