Maximum likelihood estimation of potential energy in interacting particle systems from single-trajectory data

DOI10.1214/21-ECP416zbMath1479.60125arXiv2007.11048OpenAlexW3180501569MaRDI QIDQ2064853

Xiaohui Chen

Publication date: 6 January 2022

Published in: Electronic Communications in Probability (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/2007.11048

zbMATH Keywords

symmetrymaximum likelihood estimationinteracting particle systemsstochastic Vlasov equationmean-field regime

Mathematics Subject Classification ID

Markov processes: estimation; hidden Markov models (62M05) Stochastic partial differential equations (aspects of stochastic analysis) (60H15)

Related Items (9)

Eigenfunction Martingale Estimators for Interacting Particle Systems and Their Mean Field Limit ⋮ Learning mean-field equations from particle data using WSINDy ⋮ Learning theory for inferring interaction kernels in second-order interacting agent systems ⋮ Online parameter estimation for the McKean-Vlasov stochastic differential equation ⋮ Parameter estimation of discretely observed interacting particle systems ⋮ Nonparametric adaptive estimation for interacting particle systems ⋮ On the coercivity condition in the learning of interacting particle systems ⋮ Identifiability of interaction kernels in mean-field equations of interacting particles ⋮ The LAN property for McKean-Vlasov models in a mean-field regime

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