Merge branch 'pf_options' into 'master'
Particle filter: enable passing of option values and prepare for other samplers Closes preprocessor#59 See merge request Dynare/dynare!1884trust-region-mex
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function [particle_options] = check_particle_filter_options(particle_options)
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% function [particle_filter_options, options_] = check_particle_filter_options(particle_filter_options_string, options_)
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% initialization of particle filter options
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%
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% INPUTS
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% particle_filter_options: structure storing the options
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% OUTPUTS
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% particle_filter_options: checked particle filter options
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%
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% SPECIAL REQUIREMENTS
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% none
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% Copyright (C) 2021 Dynare Team
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%
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% This file is part of Dynare.
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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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% 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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if strcmpi(particle_options.filter_algorithm, 'sis')
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particle_options.algorithm = 'sequential_importance_particle_filter';
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elseif strcmpi(particle_options.filter_algorithm, 'apf')
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particle_options.algorithm = 'auxiliary_particle_filter';
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elseif strcmpi(particle_options.filter_algorithm, 'gf')
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particle_options.algorithm = 'gaussian_filter';
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elseif strcmpi(particle_options.filter_algorithm, 'gmf')
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particle_options.algorithm = 'gaussian_mixture_filter';
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elseif strcmpi(particle_options.filter_algorithm, 'cpf')
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particle_options.algorithm = 'conditional_particle_filter';
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elseif strcmpi(particle_options.filter_algorithm, 'nlkf')
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particle_options.algorithm = 'nonlinear_kalman_filter';
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else
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error(['Estimation: Unknown filter ' particle_options.filter_algorithm])
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end
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if ~isempty(particle_options.particle_filter_options)
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% set default options and user defined options
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options_list = read_key_value_string(particle_options.particle_filter_options);
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for i=1:rows(options_list)
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switch options_list{i,1}
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case 'posterior_sampler'
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if ~(strcmpi(options_list{i,2}, 'Herbst_Schorfheide') || ...
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strcmpi(options_list{i,2}, 'DSMH'))
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error(['check_particle_filter_options:: the proposal_distribution option to estimation takes either ' ...
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'Herbst_Schorfheide or Herbst_Schorfheide as options']);
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else
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particle_options.posterior_sampler=options_list{i,2};
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end
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case 'initial_state_prior_std'
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if options_list{i,2} <= 0
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error('check_particle_filter_options:: the initial_state_prior_std option takes a positive argument');
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else
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particle_options.initial_state_prior_std=options_list{i,2};
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end
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case 'pruning'
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if ~islogical(options_list{i,2})
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error('check_particle_filter_options:: the pruning options takes only true or false');
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else
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particle_options.pruning=options_list{i,2};
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end
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case 'unscented_alpha'
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if options_list{i,2} <= 0
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error('check_particle_filter_options:: the unscented_alpha option takes a positive argument');
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else
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particle_options.unscented.alpha=options_list{i,2};
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end
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case 'unscented_beta'
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if options_list{i,2} <= 0
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error('check_particle_filter_options:: the unscented_beta option takes a positive argument');
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else
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particle_options.unscented.beta=options_list{i,2};
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end
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case 'unscented_kappa'
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if options_list{i,2} <= 0
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error('check_particle_filter_options:: the unscented_kappa option takes a positive argument');
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else
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particle_options.unscented.kappa=options_list{i,2};
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end
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case 'mixture_state_variables'
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if options_list{i,2} <= 0
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error('check_particle_filter_options:: the mixture_state_variables option takes a positive integer');
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else
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particle_options.mixture_state_variables=options_list{i,2};
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end
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case 'mixture_structural_shocks'
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if options_list{i,2} <= 0
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error('check_particle_filter_options:: the mixture_structural_shocks option takes a positive integer');
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else
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particle_options.mixture_structural_shocks=options_list{i,2};
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end
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case 'mixture_measurement_shocks'
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if options_list{i,2} <= 0
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error('check_particle_filter_options:: the mixture_measurement_shocks option takes a positive integer');
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else
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particle_options.mixture_measurement_shocks=options_list{i,2};
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end
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case 'liu_west_delta'
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if options_list{i,2} <= 0
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error('check_particle_filter_options:: the liu_west_delta option takes a positive argument');
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else
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particle_options.liu_west_delta=options_list{i,2};
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end
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case 'liu_west_chol_sigma_bar'
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if options_list{i,2} <= 0
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error('check_particle_filter_options:: the liu_west_chol_sigma_bar option takes a positive argument');
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else
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particle_options.liu_west_chol_sigma_bar=options_list{i,2};
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end
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otherwise
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warning(['check_particle_filter_options: Unknown option (' options_list{i,1} ')!'])
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end
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end
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end
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@ -246,8 +246,6 @@ particle.status = false;
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% How do we initialize the states?
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% How do we initialize the states?
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particle.initialization = 1;
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particle.initialization = 1;
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particle.initial_state_prior_std = .1;
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particle.initial_state_prior_std = .1;
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% Set the default order of approximation of the model (perturbation).
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particle.perturbation = 2;
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% Set the default number of particles.
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% Set the default number of particles.
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particle.number_of_particles = 5000;
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particle.number_of_particles = 5000;
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% Set the default approximation order (Smolyak)
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% Set the default approximation order (Smolyak)
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@ -292,7 +290,8 @@ particle.liu_west_chol_sigma_bar = .01 ;
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% Options for setting the weights in conditional particle filters.
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% Options for setting the weights in conditional particle filters.
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particle.cpf_weights_method.amisanotristani = true;
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particle.cpf_weights_method.amisanotristani = true;
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particle.cpf_weights_method.murrayjonesparslow = false;
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particle.cpf_weights_method.murrayjonesparslow = false;
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% Copy ep structure in options_ global structure
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particle.particle_filter_options ='';
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% Copy particle structure in options_ global structure
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options_.particle = particle;
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options_.particle = particle;
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options_.rwgmh.init_scale = 1e-4 ;
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options_.rwgmh.init_scale = 1e-4 ;
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options_.rwgmh.scale_chain = 1 ;
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options_.rwgmh.scale_chain = 1 ;
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@ -85,21 +85,7 @@ end
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if ~options_.dsge_var
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if ~options_.dsge_var
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if options_.particle.status
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if options_.particle.status
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objective_function = str2func('non_linear_dsge_likelihood');
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objective_function = str2func('non_linear_dsge_likelihood');
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if strcmpi(options_.particle.filter_algorithm, 'sis')
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[options_.particle] = check_particle_filter_options(options_.particle);
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options_.particle.algorithm = 'sequential_importance_particle_filter';
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elseif strcmpi(options_.particle.filter_algorithm, 'apf')
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options_.particle.algorithm = 'auxiliary_particle_filter';
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elseif strcmpi(options_.particle.filter_algorithm, 'gf')
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options_.particle.algorithm = 'gaussian_filter';
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elseif strcmpi(options_.particle.filter_algorithm, 'gmf')
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options_.particle.algorithm = 'gaussian_mixture_filter';
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elseif strcmpi(options_.particle.filter_algorithm, 'cpf')
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options_.particle.algorithm = 'conditional_particle_filter';
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elseif strcmpi(options_.particle.filter_algorithm, 'nlkf')
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options_.particle.algorithm = 'nonlinear_kalman_filter';
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else
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error(['Estimation: Unknown filter ' options_.particle.filter_algorithm])
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end
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else
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else
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if options_.occbin.likelihood.status && options_.occbin.likelihood.inversion_filter
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if options_.occbin.likelihood.status && options_.occbin.likelihood.inversion_filter
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objective_function = str2func('occbin.IVF_posterior');
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objective_function = str2func('occbin.IVF_posterior');
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@ -353,6 +339,14 @@ if ~options_.cova_compute
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stdh = NaN(length(xparam1),1);
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stdh = NaN(length(xparam1),1);
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end
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end
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if options_.particle.status && isfield(options_.particle,'posterior_sampler')
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if strcmpi(options_.particle.posterior_sampler,'Herbst_Schorfheide')
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Herbst_Schorfheide_sampler(objective_function,xparam1,bounds,dataset_,dataset_info,options_,M_,estim_params_,bayestopt_,oo_)
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elseif strcmpi(options_.particle.posterior_sampler,'DSMH')
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DSMH_sampler(objective_function,xparam1,bounds,dataset_,dataset_info,options_,M_,estim_params_,bayestopt_,oo_)
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end
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end
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if any(bayestopt_.pshape > 0) && ~options_.mh_posterior_mode_estimation
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if any(bayestopt_.pshape > 0) && ~options_.mh_posterior_mode_estimation
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% display results table and store parameter estimates and standard errors in results
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% display results table and store parameter estimates and standard errors in results
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oo_ = display_estimation_results_table(xparam1, stdh, M_, options_, estim_params_, bayestopt_, oo_, prior_dist_names, 'Posterior', 'posterior');
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oo_ = display_estimation_results_table(xparam1, stdh, M_, options_, estim_params_, bayestopt_, oo_, prior_dist_names, 'Posterior', 'posterior');
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@ -84,8 +84,6 @@ steady_state_model;
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end;
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end;
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shocks;
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shocks;
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var e_a; stderr 0.035;
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var e_a; stderr 0.035;
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end;
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end;
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@ -207,13 +205,11 @@ options_.threads.local_state_space_iteration_2 = 4;
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@#endif
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@#endif
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@#if ALGO_ONLINE_2
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@#if ALGO_ONLINE_2
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options_.particle.liu_west_delta = 0.9 ;
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estimation(order=2,number_of_particles=1000,mode_compute=11,mh_replic=0,particle_filter_options=('liu_west_delta',0.9));
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estimation(order=2,number_of_particles=1000,mode_compute=11,mh_replic=0);
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@#endif
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@#endif
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@#if ALGO_ONLINE_1
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@#if ALGO_ONLINE_1
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options_.particle.liu_west_delta = 0.9 ;
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estimation(order=1,number_of_particles=1000,mode_compute=11,mh_replic=0,particle_filter_options=('liu_west_delta',0.9));
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estimation(order=1,number_of_particles=1000,mode_compute=11,mh_replic=0);
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@#endif
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@#endif
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@#if MCMC
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@#if MCMC
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