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= Nonlinear Estimation interface =

This page describes the algorithms available to estimate nonlinear models using particle filters. Currently only the estimation based on the solution of the second order approximation of the model is implemented (third order approxiamtion should be implemented in the coming year).

== New options of the estimation command ==

Currently there is no interface (the user has to manipulate the global structure options_), the following options (discussed with Frédéric) needs to be implemented:

 * '''number_of_particles''' = [5000], any integer
 * '''resampling''' = ['''systematic'''], other possible values are '''none''' and '''generic'''
 * '''resampling_method''' = ['''kitagawa'''], other possible value is '''stratified'''
 * '''filter_algorithm''' = ['''sis'''], other possible values are '''apf''', '''gf''', '''gmf''' and '''cpf'''
 * '''proposal_approximation''' = ['''cubature'''], other possible value are '''unscented''' and '''montecarlo''' 
 * '''distribution_approximation''' = ['''cubature'''], other possible values are '''unscented''' and '''montecarlo'''
 * '''online_particle_filter''', this keyword triggers the estimation of the posterior mode using the online particle filter approach.