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.