adding new function to initialize parameters from mode file
git-svn-id: https://www.dynare.org/svn/dynare/trunk@2407 ac1d8469-bf42-47a9-8791-bf33cf982152time-shift
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function estim_params_ = initialize_from_mode(fname,M_,estim_params_)
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% function estim_params_ = initialize_from_mode(fname,M_,estim_params_)
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% initialize parameters and initial value of estimated parameters
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% from a *_mode.mat file
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%
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% INPUTS
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% fname: mode file name (*.mat file)
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% M_: sructure of model characteristics
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% estim_params_: structure of estimated parameters
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%
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% OUTPUTS
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% estim_params: modified structure of estimated parameters
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%
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% SPECIAL REQUIREMENTS
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% none
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% Copyright (C) 2003-2009 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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load(fname);
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endo_names = M_.endo_names;
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exo_names = M_.exo_names;
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param_names = M_.param_names;
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param_vals = estim_params_.param_vals;
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var_exo = estim_params_.var_exo;
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var_endo = estim_params_.var_endo;
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corrx = estim_params_.corrx;
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corrn = estim_params_.corrn;
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names = bayestopt_.name;
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for i=1:length(names)
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name = names{i};
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k1 = strmatch(name,param_names,'exact');
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if ~isempty(k1)
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k2 = find(param_vals(:,1) == k1);
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if ~isempty(k2)
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estim_params_.param_vals(k2,2) = xparam1(i);
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end
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M_.params(i) = xparam1(i);
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continue
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end
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k3 = strfind(name,',');
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if isempty(k3)
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k1 = strmatch(name,exo_names,'exact');
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if ~isempty(k1)
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k2 = find(var_exo(:,1) == k1);
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if ~isempty(k2)
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estim_params_.var_exo(k2,2) = xparam1(i);
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end
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M_.Sigma_e(k1,k1) = xparam1(i)^2;
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continue
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end
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k1 = strmatch(name,endo_names,'exact');
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if ~isempty(k1)
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k2 = find(var_endo(:,1) == k1);
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if ~isempty(k2)
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estim_params_.var_endo(k2,2) = xparam1(i);
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end
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M_.H(k1,k1) = xparam1(i)^2;
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continue
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end
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else
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k1 = strmatch(name(1:k3-1),exo_names,'exact');
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k1a = strmatch(name(k3+1:end),exo_names,'exact');
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if ~isempty(k1) & ~isempty(k1a)
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k2 = find(corrx(:,1) == k1 & corrx(:,2) == k1a);
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if ~isempty(k2)
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estim_params_.corrx(k2,3) = xparam1(i);
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end
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M_.Sigma_e(k1,k1a) = xparam1(i)*sqrt(M_.Sigma_e(k1,k1)+M_.Sigma_e(k1a,k1a));
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M_.Sigma_e(k1a,k1) = M_.Sigma_e(k1,k1a);
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continue
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end
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k1 = strmatch(name(1:k3-1),endo_names,'exact');
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k1a = strmatch(name(k3+1:end),endo_names,'exact');
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if ~isempty(k1) & ~isempty(k1a)
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k2 = find(corrn(:,1) == k1 & corrn(:,2) == k1a);
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if ~isempty(k2)
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estim_params_.corrn(k2,3) = xparam1(i);
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end
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M_.H(k1,k1a) = xparam1(i)*sqrt(M_.H(k1,k1)+M_.H(k1a,k1a));
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M_.H(k1a,k1) = M_.H(k1,k1a);
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continue
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end
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end
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error([name 'doesn''t exist in this model'])
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end
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