Factorize estimation: wrapper for tune_mh_jscale
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c356db4531
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6941bd5516
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@ -385,19 +385,10 @@ if (any(bayestopt_.pshape >0 ) && options_.mh_replic) || ...
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% Tunes the jumping distribution's scale parameter
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% Tunes the jumping distribution's scale parameter
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if options_.mh_tune_jscale.status
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if options_.mh_tune_jscale.status
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if strcmp(options_.posterior_sampler_options.posterior_sampling_method, 'random_walk_metropolis_hastings')
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if strcmp(options_.posterior_sampler_options.posterior_sampling_method, 'random_walk_metropolis_hastings')
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%get invhess in case of use_mh_covariance_matrix
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options_.mh_jscale = tune_mcmc_mh_jscale_wrapper(invhess, options_, M_, objective_function, xparam1, bounds,...
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posterior_sampler_options_temp = options_.posterior_sampler_options.current_options;
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dataset_, dataset_info, options_, M_, estim_params_, bayestopt_, bounds, oo_);
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posterior_sampler_options_temp.invhess = invhess;
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posterior_sampler_options_temp = check_posterior_sampler_options(posterior_sampler_options_temp, M_.fname, M_.dname, options_);
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options = options_.mh_tune_jscale;
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options.rwmh = options_.posterior_sampler_options.rwmh;
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options_.mh_jscale = calibrate_mh_scale_parameter(objective_function, ...
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posterior_sampler_options_temp.invhess, xparam1, [bounds.lb,bounds.ub], ...
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options, dataset_, dataset_info, options_, M_, estim_params_, bayestopt_, bounds, oo_);
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clear('posterior_sampler_options_temp','options')
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bayestopt_.jscale(:) = options_.mh_jscale;
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bayestopt_.jscale(:) = options_.mh_jscale;
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fprintf('mh_jscale has been set equal to %s\n', num2str(options_.mh_jscale))
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fprintf('mh_jscale has been set equal to %s\n', num2str(options_.mh_jscale));
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else
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else
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warning('mh_tune_jscale is only available with Random Walk Metropolis Hastings!')
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warning('mh_tune_jscale is only available with Random Walk Metropolis Hastings!')
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end
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end
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@ -0,0 +1,48 @@
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function mh_jscale = tune_mcmc_mh_jscale_wrapper(invhess, options_, M_, objective_function, xparam1, bounds, varargin)
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% function mh_jscale = tune_mcmc_mh_jscale_wrapper(invhess, options_, M_, objective_function, xparam1, bounds, varargin)
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% -------------------------------------------------------------------------
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% Wrapper to call the algorithm to tune the jumping scale parameter for the
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% Metropolis-Hastings algorithm; currently only support RW-MH algorithm.
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% =========================================================================
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% INPUTS
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% o invhess: [matrix] jumping covariance matrix
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% o options_: [struct] Dynare options
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% o M_: [struct] Dynare model structure
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% o objective_function: [function handle] objective function
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% o xparam1: [vector] vector of estimated parameters at the mode
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% o bounds: [struct] structure containing information on bounds
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% o varargin: [cell] additional arguments to be passed to the objective function
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% -------------------------------------------------------------------------
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% OUTPUTS
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% o mh_jscale: [double] tuned jumping scale parameter
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% -------------------------------------------------------------------------
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% This function is called by
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% o dynare_estimation_1.m
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% -------------------------------------------------------------------------
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% Copyright © 2023 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 <https://www.gnu.org/licenses/>.
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% =========================================================================
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% get invhess in case of use_mh_covariance_matrix
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posterior_sampler_options_temp = options_.posterior_sampler_options.current_options;
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posterior_sampler_options_temp.invhess = invhess;
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posterior_sampler_options_temp = check_posterior_sampler_options(posterior_sampler_options_temp, M_.fname, M_.dname, options_);
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opt = options_.mh_tune_jscale;
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opt.rwmh = options_.posterior_sampler_options.rwmh;
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mh_jscale = calibrate_mh_scale_parameter(objective_function, ...
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posterior_sampler_options_temp.invhess, xparam1, [bounds.lb,bounds.ub], ...
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opt, varargin{:});
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