Recursive MLE algorithms for interacting particle systems employ virtual and tangent virtual particles to optimize the mean-field stationary log-likelihood from single-particle observations, with proven convergence to stationary points in the t to infinity then N,M to infinity limit.
arXiv:2602.20875 , year=
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Proves uniform-in-time QCLT for fluctuations in nonlinear slow-fast stochastic systems with weaker sufficient conditions using second-order Poincaré inequality from Malliavin calculus.
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Recursive Maximum Likelihood Estimation for Interacting Particle Systems using Virtual Particles
Recursive MLE algorithms for interacting particle systems employ virtual and tangent virtual particles to optimize the mean-field stationary log-likelihood from single-particle observations, with proven convergence to stationary points in the t to infinity then N,M to infinity limit.
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Uniform-in-time Gaussian fluctuations for multiscale nonlinear stochastic systems via Malliavin Calculus
Proves uniform-in-time QCLT for fluctuations in nonlinear slow-fast stochastic systems with weaker sufficient conditions using second-order Poincaré inequality from Malliavin calculus.