When a model is linear, one can use Kalman filter to get likelihood function and use ML techniques. While nonlinear Kalman filter exists, it is suboptimal. What is the standard way to get likelihood function and apply maximum likelihood(ML) methods when a model is non-linear and not linearized?
closed as too broad by jmbejara Jun 11 '15 at 18:12
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