function M = set_all_parameters(xparam1,estim_params,M) %@info: %! @deftypefn {Function File} {@var{M} =} dseries (@var{xparams1},@var{estim_params},@var{M}) %! @anchor{set_all_parameters} %! @sp 1 %! Update parameter values (deep parameters and covariance matrices). %! @sp 2 %! @strong{Inputs} %! @sp 1 %! @table @ @var %! @item xparam1 %! N*1 vector of doubles, the values of the N estimated parameters. %! @item estim_params %! Dynare structure describing the estimated parameters. %! @item M %! Dynare structure describing the model. %! @end table %! @sp 1 %! @strong{Outputs} %! @sp 1 %! @table @ @var %! @item M %! Dynare structure describing the model, with updated parameters and covariances matrices. %! @end table %! @sp 2 %! @strong{This function is called by:} %! @sp 1 %! @ref{DsgeSmoother}, @ref{dynare_estimation_1}, @ref{@@gsa/filt_mc_}, @ref{identification_analysis}, @ref{PosteriorFilterSmootherAndForecast}, @ref{prior_posterior_statistics_core}, @ref{prior_sampler} %! @sp 2 %! @strong{This function calls:} %! @sp 2 %! @end deftypefn %@eod: % Copyright © 2003-2017 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 . nvx = estim_params.nvx; ncx = estim_params.ncx; nvn = estim_params.nvn; ncn = estim_params.ncn; np = estim_params.np; Sigma_e = M.Sigma_e; Correlation_matrix = M.Correlation_matrix; H = M.H; Correlation_matrix_ME = M.Correlation_matrix_ME; % setting shocks variance on the diagonal of Covariance matrix; used later % for updating covariances if nvx var_exo = estim_params.var_exo; for i=1:nvx k =var_exo(i,1); Sigma_e(k,k) = xparam1(i)^2; end end % update offset offset = nvx; % setting measument error variance; on the diagonal of Covariance matrix; used later % for updating covariances if nvn for i=1:nvn k = estim_params.nvn_observable_correspondence(i,1); H(k,k) = xparam1(i+offset)^2; end end % update offset offset = nvx+nvn; % setting shocks covariances if ncx corrx = estim_params.corrx; for i=1:ncx k1 = corrx(i,1); k2 = corrx(i,2); Correlation_matrix(k1,k2) = xparam1(i+offset); Correlation_matrix(k2,k1) = Correlation_matrix(k1,k2); end end %build covariance matrix from correlation matrix and variances already on %diagonal Sigma_e = diag(sqrt(diag(Sigma_e)))*Correlation_matrix*diag(sqrt(diag(Sigma_e))); %if calibrated covariances, set them now to their stored value if isfield(estim_params,'calibrated_covariances') Sigma_e(estim_params.calibrated_covariances.position)=estim_params.calibrated_covariances.cov_value; end % update offset offset = nvx+nvn+ncx; % setting measurement error covariances if ncn corrn_observable_correspondence = estim_params.corrn_observable_correspondence; for i=1:ncn k1 = corrn_observable_correspondence(i,1); k2 = corrn_observable_correspondence(i,2); Correlation_matrix_ME(k1,k2) = xparam1(i+offset); Correlation_matrix_ME(k2,k1) = Correlation_matrix_ME(k1,k2); end end %build covariance matrix from correlation matrix and variances already on %diagonal H = diag(sqrt(diag(H)))*Correlation_matrix_ME*diag(sqrt(diag(H))); %if calibrated covariances, set them now to their stored value if isfield(estim_params,'calibrated_covariances_ME') H(estim_params.calibrated_covariances_ME.position)=estim_params.calibrated_covariances_ME.cov_value; end % update offset offset = nvx+ncx+nvn+ncn; % setting structural parameters % if np M.params(estim_params.param_vals(:,1)) = xparam1(offset+1:end); end % updating matrices in M if nvx || ncx M.Sigma_e = Sigma_e; M.Correlation_matrix=Correlation_matrix; end if nvn || ncn M.H = H; M.Correlation_matrix_ME=Correlation_matrix_ME; end