Fixed headers.
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function [LIK,lik] = auxiliary_particle_filter(ReducedForm,Y,start,DynareOptions)
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% Evaluates the likelihood of a nonlinear model with a particle filter allowing eventually resampling.
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%
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% INPUTS
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% ReducedForm [structure] Matlab's structure describing the reduced form model.
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% ReducedForm.measurement.H [double] (pp x pp) variance matrix of measurement errors.
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% ReducedForm.state.Q [double] (qq x qq) variance matrix of state errors.
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% ReducedForm.state.dr [structure] output of resol.m.
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% Y [double] pp*smpl matrix of (detrended) data, where pp is the maximum number of observed variables.
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% start [integer] scalar, likelihood evaluation starts at 'start'.
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% mf [integer] pp*1 vector of indices.
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% number_of_particles [integer] scalar.
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%
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% OUTPUTS
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% LIK [double] scalar, likelihood
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% lik [double] vector, density of observations in each period.
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%
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% REFERENCES
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%
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% NOTES
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% The vector "lik" is used to evaluate the jacobian of the likelihood.
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% Copyright (C) 2011-2013 Dynare Team
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% Evaluates the likelihood of a nonlinear model with a particle filter allowing eventually resampling.
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% Copyright (C) 2011-2014 Dynare Team
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%
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% This file is part of Dynare.
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% This file is part of Dynare (particles module).
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%
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% Dynare is free software: you can redistribute it and/or modify
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% it under the terms of the GNU General Public License as published by
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% the Free Software Foundation, either version 3 of the License, or
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% (at your option) any later version.
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%
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% Dynare is distributed in the hope that it will be useful,
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% Dynare particles module is distributed in the hope that it will be useful,
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% but WITHOUT ANY WARRANTY; without even the implied warranty of
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% MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
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% GNU General Public License for more details.
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%
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% You should have received a copy of the GNU General Public License
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% along with Dynare. If not, see <http://www.gnu.org/licenses/>.
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persistent init_flag mf0 mf1 number_of_particles
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persistent sample_size number_of_state_variables number_of_observed_variables number_of_structural_innovations
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@ -2,7 +2,7 @@ function [LIK,lik] = sequential_importance_particle_filter(ReducedForm,Y,start,P
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% Evaluates the likelihood of a nonlinear model with a particle filter (optionally with resampling).
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% Copyright (C) 2011-2013 Dynare Team
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% Copyright (C) 2011-2014 Dynare Team
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%
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% This file is part of Dynare (particles module).
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%
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