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Verified Commit af337d8d authored by Sébastien Villemot's avatar Sébastien Villemot
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Merge branch 'cosmetics' of git.dynare.org:JohannesPfeifer/dynare

Ref. !2353
parents 23d49470 98332833
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......@@ -7,7 +7,9 @@ function xparam = get_posterior_parameters(type,M_,estim_params_,oo_,options_,fi
% o type [char] = 'mode' or 'mean'.
% o M_: [structure] Dynare structure describing the model.
% o estim_params_: [structure] Dynare structure describing the estimated parameters.
% o field_1 [char] optional field like 'mle_'.
% o oo_: [structure] Dynare results structure
% o options_: [structure] Dynare options structure
% o field_1 [char] optional field like 'mle_'.
%
% OUTPUTS
% o xparam vector of estimated parameters
......@@ -15,7 +17,7 @@ function xparam = get_posterior_parameters(type,M_,estim_params_,oo_,options_,fi
% SPECIAL REQUIREMENTS
% None.
% Copyright © 2006-2018 Dynare Team
% Copyright © 2006-2025 Dynare Team
%
% This file is part of Dynare.
%
......@@ -76,8 +78,6 @@ for i=1:ncn
m = m+1;
end
FirstDeep = m;
for i=1:np
name1 = M_.param_names{estim_params_.param_vals(i,1)};
xparam(m) = oo_.([field1 type]).parameters.(name1);
......
......@@ -3,10 +3,11 @@ function [marginal,oo_] = marginal_density(M_, options_, estim_params_, oo_, bay
% Computes the marginal density
%
% INPUTS
% M_ [structure] Dynare model structure
% options_ [structure] Dynare options structure
% estim_params_ [structure] Dynare estimation parameter structure
% M_ [structure] Dynare model structure
% oo_ [structure] Dynare results structure
% bayestopt_ [structure] describing the priors
% outputFolderName [string] name of folder with results
%
% OUTPUTS
......@@ -16,7 +17,7 @@ function [marginal,oo_] = marginal_density(M_, options_, estim_params_, oo_, bay
% SPECIAL REQUIREMENTS
% none
% Copyright © 2005-2023 Dynare Team
% Copyright © 2005-2025 Dynare Team
%
% This file is part of Dynare.
%
......@@ -64,7 +65,7 @@ if ~isfield(oo_,'posterior_mode') || (options_.mh_replic && isequal(options_.pos
end
% save the posterior mean and the inverse of the covariance matrix
% (usefull if the user wants to perform some computations using
% (useful if the user wants to perform some computations using
% the posterior mean instead of the posterior mode ==> ).
parameter_names = bayestopt_.name;
save([M_.dname filesep outputFolderName filesep M_.fname '_mean.mat'],'xparam1','hh','parameter_names','SIGMA');
......
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