85 lines
2.5 KiB
Matlab
85 lines
2.5 KiB
Matlab
function M_=set_parameters_locally(M_,xparam1)
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% function M_=set_parameters_locally(M_,xparam1)
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% Sets parameters value (except measurement errors)
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% This is called for computations such as IRF and forecast
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% when measurement errors aren't taken into account; in contrast to
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% set_parameters.m, the global M_-structure is not altered
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%
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% INPUTS
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% xparam1: vector of parameters to be estimated (initial values)
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% M_: Dynare model-structure
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%
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% OUTPUTS
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% M_: Dynare model-structure
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%
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% SPECIAL REQUIREMENTS
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% none
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% Copyright © 2017 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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global estim_params_
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nvx = estim_params_.nvx;
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ncx = estim_params_.ncx;
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nvn = estim_params_.nvn;
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ncn = estim_params_.ncn;
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np = estim_params_.np;
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Sigma_e = M_.Sigma_e;
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Correlation_matrix = M_.Correlation_matrix;
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offset = 0;
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% setting shocks variance on the diagonal of Covariance matrix; used later
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% for updating covariances
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if nvx
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var_exo = estim_params_.var_exo;
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for i=1:nvx
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k = var_exo(i,1);
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Sigma_e(k,k) = xparam1(i)^2;
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end
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end
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% and update offset
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offset = offset + nvx + nvn;
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% correlations among shocks (ncx)
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if ncx
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corrx = estim_params_.corrx;
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for i=1:ncx
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k1 = corrx(i,1);
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k2 = corrx(i,2);
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Correlation_matrix(k1,k2) = xparam1(i+offset);
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Correlation_matrix(k2,k1) = Correlation_matrix(k1,k2);
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end
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end
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%build covariance matrix from correlation matrix and variances already on
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%diagonal
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Sigma_e = diag(sqrt(diag(Sigma_e)))*Correlation_matrix*diag(sqrt(diag(Sigma_e)));
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if isfield(estim_params_,'calibrated_covariances')
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Sigma_e(estim_params_.calibrated_covariances.position)=estim_params_.calibrated_covariances.cov_value;
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end
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% and update offset
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offset = offset + ncx + ncn;
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% structural parameters
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if np
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M_.params(estim_params_.param_vals(:,1)) = xparam1(offset+1:end);
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end
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M_.Sigma_e = Sigma_e;
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M_.Correlation_matrix=Correlation_matrix; |