Researchers introduced a method for online parameter estimation in stochastic interacting particle systems using continuous observation of a subset of particles. The method updates parameters recursively based on observed data and converges to stationary points of the asymptotic log-likelihood under certain conditions, offering practical applications in systemic risk models, neuron interactions, and flocking behaviors.
Read the full article at arXiv stat.ML
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Ali NematiWritten by Ali
