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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?

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closed as too broad by jmbejara Jun 11 '15 at 18:12

Please edit the question to limit it to a specific problem with enough detail to identify an adequate answer. Avoid asking multiple distinct questions at once. See the How to Ask page for help clarifying this question. If this question can be reworded to fit the rules in the help center, please edit the question.

  • $\begingroup$ It would be useful if you include in your question the specific non-linear model that you are dealing with. In the non-linear world, in many cases there do not exist answers of full general applicability. $\endgroup$ – Alecos Papadopoulos Jun 10 '15 at 14:09