A cSMC-based framework estimates splitting-scheme pseudolikelihoods under several observation regimes, using diffusion bridges to reduce time-discretization bias.
A splitting method for SDE s with locally L ipschitz drift: Illustration on the F itzhugh-- N agumo model
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Inference for Diffusion Processes via Controlled Sequential Monte Carlo and Splitting Schemes
A cSMC-based framework estimates splitting-scheme pseudolikelihoods under several observation regimes, using diffusion bridges to reduce time-discretization bias.