Fixed behaviour of write_latex_prior_table command
parent
b70fe62503
commit
64d01a806e
|
@ -10069,11 +10069,15 @@ following @LaTeX{} packages: @code{longtable, booktabs}
|
|||
|
||||
@deffn {MATLAB/Octave command} write_latex_prior_table ;
|
||||
|
||||
Writes descriptive statistics about the prior distribution to
|
||||
a @LaTeX{} table in a file named @code{<<M_.fname>>_latex_priors_table.tex}. The command writes the prior
|
||||
definitions currently stored. Thus, the command must be invoked after the @code{estimated_params} block. The command
|
||||
returns an error if no prior densities are defined (ML estimation). Requires the following @LaTeX{}
|
||||
packages: @code{longtable, booktabs}
|
||||
Writes descriptive statistics about the prior distribution to a @LaTeX{} table
|
||||
in a file named @code{<<M_.fname>>_latex_priors_table.tex}. The command writes
|
||||
the prior definitions currently stored. Thus, this command must be invoked
|
||||
after the @code{estimated_params} block. If priors are defined over the
|
||||
measurement errors, the command must also be preceeded by the declaration of
|
||||
the observed variables (with @code{varobs}). The command displays a warning if
|
||||
no prior densities are defined (ML estimation) or if the declaration of the
|
||||
observed variables is missing. Requires the following @LaTeX{} packages:
|
||||
@code{longtable, booktabs}
|
||||
@end deffn
|
||||
|
||||
@deffn {MATLAB/Octave command} collect_LaTeX_Files (@code{M_}) ;
|
||||
|
|
|
@ -0,0 +1,44 @@
|
|||
function l = isbayes(estim_params_)
|
||||
|
||||
% Returns true iff bayesian priors over parameters are defined.
|
||||
|
||||
% Copyright (C) 2016 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 <http://www.gnu.org/licenses/>.
|
||||
|
||||
l = false;
|
||||
|
||||
if ~isstruct(estim_params_)
|
||||
return
|
||||
end
|
||||
|
||||
if isempty(estim_params_)
|
||||
return
|
||||
end
|
||||
|
||||
ptypes = {'param_vals', 5; 'var_exo', 5 ; 'var_endo', 5; 'corrx', 6; 'corrn', 6};
|
||||
|
||||
for i=1:size(ptypes, 1)
|
||||
if isfield(estim_params_, ptypes{i, 1})
|
||||
tmp = estim_params_.(ptypes{i, 1});
|
||||
if ~isempty(tmp)
|
||||
if any(tmp(:,ptypes{i, 2})>0)
|
||||
l = true;
|
||||
return
|
||||
end
|
||||
end
|
||||
end
|
||||
end
|
|
@ -30,12 +30,24 @@ function write_latex_prior_table
|
|||
|
||||
global M_ options_ bayestopt_ estim_params_
|
||||
|
||||
if ~any(bayestopt_.pshape > 0)
|
||||
if ~isbayes(estim_params_)
|
||||
fprintf('\nwrite_latex_prior_table:: No prior distributions detected. Skipping table creation.\n')
|
||||
return
|
||||
end
|
||||
|
||||
% get untruncated bounds
|
||||
if (size(estim_params_.var_endo,1) || size(estim_params_.corrn,1))
|
||||
% Prior over measurement errors are defined...
|
||||
if ((isfield(options_,'varobs') && isempty(options_.varobs)) || ~isfield(options_,'varobs'))
|
||||
% ... But the list of observed variabled is not yet defined.
|
||||
fprintf(['\nwrite_latex_prior_table:: varobs should be declared before. Skipping table creation.\n'])
|
||||
return
|
||||
end
|
||||
end
|
||||
|
||||
% Fill or update bayestopt_ structure
|
||||
[xparam1, estim_params_, bayestopt_, lb, ub, M_] = set_prior(estim_params_, M_, options_);
|
||||
|
||||
% Get untruncated bounds
|
||||
bounds = prior_bounds(bayestopt_, options_.prior_trunc);
|
||||
lb=bounds.lb;
|
||||
ub=bounds.ub;
|
||||
|
|
Loading…
Reference in New Issue