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Commit 80cad320 authored by Johannes Pfeifer's avatar Johannes Pfeifer
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Particle filter: enable passing of option values and prepare for other samplers

parent c4e1d1e8
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matlab/check_particle_filter_options.m 0 → 100644
View file @ 80cad320
function [particle_options] = check_particle_filter_options(particle_options)
% function [particle_filter_options, options_] = check_particle_filter_options(particle_filter_options_string, options_)
% initialization of particle filter options
%
% INPUTS
% particle_filter_options: structure storing the options
% OUTPUTS
% particle_filter_options: checked particle filter options
%
% SPECIAL REQUIREMENTS
% none
% Copyright (C) 2021 Dynare Team
%
% This file is part of Dynare.
%
% Dynare is free software: you can redistribute it and/or modify
% it under the terms of the GNU General Public License as published by
% the Free Software Foundation, either version 3 of the License, or
% (at your option) any later version.
%
% Dynare is distributed in the hope that it will be useful,
% but WITHOUT ANY WARRANTY; without even the implied warranty of
% MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
% GNU General Public License for more details.
%
% You should have received a copy of the GNU General Public License
% along with Dynare. If not, see <http://www.gnu.org/licenses/>.
if strcmpi(particle_options.filter_algorithm, 'sis')
particle_options.algorithm = 'sequential_importance_particle_filter';
elseif strcmpi(particle_options.filter_algorithm, 'apf')
particle_options.algorithm = 'auxiliary_particle_filter';
elseif strcmpi(particle_options.filter_algorithm, 'gf')
particle_options.algorithm = 'gaussian_filter';
elseif strcmpi(particle_options.filter_algorithm, 'gmf')
particle_options.algorithm = 'gaussian_mixture_filter';
elseif strcmpi(particle_options.filter_algorithm, 'cpf')
particle_options.algorithm = 'conditional_particle_filter';
elseif strcmpi(particle_options.filter_algorithm, 'nlkf')
particle_options.algorithm = 'nonlinear_kalman_filter';
else
error(['Estimation: Unknown filter ' particle_options.filter_algorithm])
end
if ~isempty(particle_options.particle_filter_options)
% set default options and user defined options
options_list = read_key_value_string(particle_options.particle_filter_options);
for i=1:rows(options_list)
switch options_list{i,1}
case 'posterior_sampler'
if ~(strcmpi(options_list{i,2}, 'Herbst_Schorfheide') || ...
strcmpi(options_list{i,2}, 'DSMH'))
error(['check_particle_filter_options:: the proposal_distribution option to estimation takes either ' ...
'Herbst_Schorfheide or Herbst_Schorfheide as options']);
else
particle_options.posterior_sampler=options_list{i,2};
end
case 'initial_state_prior_std'
if options_list{i,2} <= 0
error('check_particle_filter_options:: the initial_state_prior_std option takes a positive argument');
else
particle_options.initial_state_prior_std=options_list{i,2};
end
case 'pruning'
if ~islogical(options_list{i,2})
error('check_particle_filter_options:: the pruning options takes only true or false');
else
particle_options.pruning=options_list{i,2};
end
case 'unscented_alpha'
if options_list{i,2} <= 0
error('check_particle_filter_options:: the unscented_alpha option takes a positive argument');
else
particle_options.unscented.alpha=options_list{i,2};
end
case 'unscented_beta'
if options_list{i,2} <= 0
error('check_particle_filter_options:: the unscented_beta option takes a positive argument');
else
particle_options.unscented.beta=options_list{i,2};
end
case 'unscented_kappa'
if options_list{i,2} <= 0
error('check_particle_filter_options:: the unscented_kappa option takes a positive argument');
else
particle_options.unscented.kappa=options_list{i,2};
end
case 'mixture_state_variables'
if options_list{i,2} <= 0
error('check_particle_filter_options:: the mixture_state_variables option takes a positive integer');
else
particle_options.mixture_state_variables=options_list{i,2};
end
case 'mixture_structural_shocks'
if options_list{i,2} <= 0
error('check_particle_filter_options:: the mixture_structural_shocks option takes a positive integer');
else
particle_options.mixture_structural_shocks=options_list{i,2};
end
case 'mixture_measurement_shocks'
if options_list{i,2} <= 0
error('check_particle_filter_options:: the mixture_measurement_shocks option takes a positive integer');
else
particle_options.mixture_measurement_shocks=options_list{i,2};
end
case 'liu_west_delta'
if options_list{i,2} <= 0
error('check_particle_filter_options:: the liu_west_delta option takes a positive argument');
else
particle_options.liu_west_delta=options_list{i,2};
end
case 'liu_west_chol_sigma_bar'
if options_list{i,2} <= 0
error('check_particle_filter_options:: the liu_west_chol_sigma_bar option takes a positive argument');
else
particle_options.liu_west_chol_sigma_bar=options_list{i,2};
end
otherwise
warning(['check_particle_filter_options: Unknown option (' options_list{i,1} ')!'])
end
end
end
matlab/default_option_values.m
View file @ 80cad320
......@@ -246,8 +246,6 @@ particle.status = false;
% How do we initialize the states?
particle.initialization = 1;
particle.initial_state_prior_std = .1;
% Set the default order of approximation of the model (perturbation).
particle.perturbation = 2;
% Set the default number of particles.
particle.number_of_particles = 5000;
% Set the default approximation order (Smolyak)
......@@ -292,7 +290,8 @@ particle.liu_west_chol_sigma_bar = .01 ;
% Options for setting the weights in conditional particle filters.
particle.cpf_weights_method.amisanotristani = true;
particle.cpf_weights_method.murrayjonesparslow = false;
% Copy ep structure in options_ global structure
particle.particle_filter_options ='';
% Copy particle structure in options_ global structure
options_.particle = particle;
options_.rwgmh.init_scale = 1e-4 ;
options_.rwgmh.scale_chain = 1 ;
......
matlab/dynare_estimation_1.m
View file @ 80cad320
......@@ -85,21 +85,7 @@ end
if ~options_.dsge_var
if options_.particle.status
objective_function = str2func('non_linear_dsge_likelihood');
if strcmpi(options_.particle.filter_algorithm, 'sis')
options_.particle.algorithm = 'sequential_importance_particle_filter';
elseif strcmpi(options_.particle.filter_algorithm, 'apf')
options_.particle.algorithm = 'auxiliary_particle_filter';
elseif strcmpi(options_.particle.filter_algorithm, 'gf')
options_.particle.algorithm = 'gaussian_filter';
elseif strcmpi(options_.particle.filter_algorithm, 'gmf')
options_.particle.algorithm = 'gaussian_mixture_filter';
elseif strcmpi(options_.particle.filter_algorithm, 'cpf')
options_.particle.algorithm = 'conditional_particle_filter';
elseif strcmpi(options_.particle.filter_algorithm, 'nlkf')
options_.particle.algorithm = 'nonlinear_kalman_filter';
else
error(['Estimation: Unknown filter ' options_.particle.filter_algorithm])
end
[options_.particle] = check_particle_filter_options(options_.particle);
else
if options_.occbin.likelihood.status && options_.occbin.likelihood.inversion_filter
objective_function = str2func('occbin.IVF_posterior');
......@@ -353,6 +339,14 @@ if ~options_.cova_compute
stdh = NaN(length(xparam1),1);
end
if options_.particle.status && isfield(options_.particle,'posterior_sampler')
if strcmpi(options_.particle.posterior_sampler,'Herbst_Schorfheide')
Herbst_Schorfheide_sampler(objective_function,xparam1,bounds,dataset_,dataset_info,options_,M_,estim_params_,bayestopt_,oo_)
elseif strcmpi(options_.particle.posterior_sampler,'DSMH')
DSMH_sampler(objective_function,xparam1,bounds,dataset_,dataset_info,options_,M_,estim_params_,bayestopt_,oo_)
end
end
if any(bayestopt_.pshape > 0) && ~options_.mh_posterior_mode_estimation
% display results table and store parameter estimates and standard errors in results
oo_ = display_estimation_results_table(xparam1, stdh, M_, options_, estim_params_, bayestopt_, oo_, prior_dist_names, 'Posterior', 'posterior');
......
tests/particle/dsge_base2.mod
View file @ 80cad320
// DGP
@#ifndef RISKY_CALIBRATION
@#define RISKY_CALIBRATION = 1
@#define RISKY_CALIBRATION = 1
@#endif
@#ifndef EXTREME_CALIBRATION
@#define EXTREME_CALIBRATION = 0
@#define EXTREME_CALIBRATION = 0
@#endif
@#ifndef BENCHMARK_CALIBRATION
@#define BENCHMARK_CALIBRATION = 0
@#define BENCHMARK_CALIBRATION = 0
@#endif
// ALGORITHM
@#ifndef LINEAR_KALMAN
@#define LINEAR_KALMAN = 0
@#define LINEAR_KALMAN = 0
@#endif
@#ifndef NON_LINEAR_KALMAN
@#define NON_LINEAR_KALMAN = 1
@#define NON_LINEAR_KALMAN = 1
@#endif
@#ifndef ALGO_SIR
@#define ALGO_SIR = 0
@#define ALGO_SIR = 0
@#endif
@#ifndef ALGO_SISmoothR
@#define ALGO_SISmoothR = 0
@#define ALGO_SISmoothR = 0
@#endif
@#ifndef ALGO_APF
@#define ALGO_APF = 0
@#define ALGO_APF = 0
@#endif
@#ifndef ALGO_CPF
@#define ALGO_CPF = 0
@#define ALGO_CPF = 0
@#endif
@#ifndef ALGO_GPF
@#define ALGO_GPF = 0
@#define ALGO_GPF = 0
@#endif
@#ifndef ALGO_GCF
@#define ALGO_GCF = 0
@#define ALGO_GCF = 0
@#endif
@#ifndef ALGO_GUF
@#define ALGO_GUF = 0
@#define ALGO_GUF = 0
@#endif
@#ifndef ALGO_GMPF
@#define ALGO_GMPF = 0
@#define ALGO_GMPF = 0
@#endif
@#ifndef ALGO_GMCF
@#define ALGO_GMCF = 0
@#define ALGO_GMCF = 0
@#endif
@#ifndef ALGO_ONLINE_1
@#define ALGO_ONLINE_1 = 0
@#define ALGO_ONLINE_1 = 0
@#endif
@#ifndef ALGO_ONLINE_2
@#define ALGO_ONLINE_2 = 0
@#define ALGO_ONLINE_2 = 0
@#endif
@#ifndef MCMC
@#define MCMC = 0
@#define MCMC = 0
@#endif
var k A c l i y;
......@@ -84,8 +84,6 @@ steady_state_model;
end;
shocks;
var e_a; stderr 0.035;
end;
......@@ -207,13 +205,11 @@ options_.threads.local_state_space_iteration_2 = 4;
@#endif
@#if ALGO_ONLINE_2
options_.particle.liu_west_delta = 0.9 ;
estimation(order=2,number_of_particles=1000,mode_compute=11,mh_replic=0);
estimation(order=2,number_of_particles=1000,mode_compute=11,mh_replic=0,particle_filter_options=('liu_west_delta',0.9));
@#endif
@#if ALGO_ONLINE_1
options_.particle.liu_west_delta = 0.9 ;
estimation(order=1,number_of_particles=1000,mode_compute=11,mh_replic=0);
estimation(order=1,number_of_particles=1000,mode_compute=11,mh_replic=0,particle_filter_options=('liu_west_delta',0.9));
@#endif
@#if MCMC
......
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