A nested EnKF replaces the particle filter in SMC² to enable static parameter inference in nonlinear state-space models without requiring linear-Gaussian assumptions on the joint state-parameter process.
Marginal filtering means and 95% credible intervals for logβ 1,t and logβ 2,t (top panel), and removal prevalencesR 1,t andR 2,t (bottom panel) using the output of NEnKF
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Nested ensemble Kalman filter for static parameter inference in nonlinear state-space models
A nested EnKF replaces the particle filter in SMC² to enable static parameter inference in nonlinear state-space models without requiring linear-Gaussian assumptions on the joint state-parameter process.