diff --git a/matlab/optimization/analytic_gradient_wrapper.m b/matlab/optimization/analytic_gradient_wrapper.m
new file mode 100644
index 0000000000000000000000000000000000000000..8ef31deaff85f1815695bab04a9f6396d969a7a8
--- /dev/null
+++ b/matlab/optimization/analytic_gradient_wrapper.m
@@ -0,0 +1,37 @@
+function [fval, grad, hess, exit_flag]=analytic_gradient_wrapper(x, fcn, varargin)
+%function [fval, grad, hess, exitflag]=analytic_gradient_wrapper(x, fcn, varargin)
+% Encapsulates an objective function to be minimized for use with Matlab
+% optimizers
+%
+% INPUTS
+% - x [double] n*1 vector of instrument values.
+% - fcn [fhandle] objective function.
+% - varagin [cell] additional parameters for fcn.
+%
+% OUTPUTS
+% - fval [double] scalar, value of the objective function at x.
+% - grad gradient of the objective function
+% - hess Hessian of the objective function
+% - exit_flag [integer] scalar, flag returned by
+
+% Copyright (C) 2021 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/>.
+
+[fval, info, exit_flag, grad, hess] = fcn(x, varargin{:});
+if size(grad,2)==1
+ grad=grad'; %should be row vector for Matlab; exception lsqnonlin where Jacobian is required
+end
\ No newline at end of file
diff --git a/matlab/optimization/dynare_minimize_objective.m b/matlab/optimization/dynare_minimize_objective.m
index 6e1a773d39c8d0a4572c5f054cc15a481b31abb1..1e6100512e0848c71c3270efba6795ae022a91da 100644
--- a/matlab/optimization/dynare_minimize_objective.m
+++ b/matlab/optimization/dynare_minimize_objective.m
@@ -77,24 +77,37 @@ switch minimizer_algorithm
% is not able to even move away from the initial point.
optim_options = optimoptions(optim_options, 'Algorithm','active-set');
end
+ if options_.analytic_derivation || (isfield(options_,'mom') && options_.mom.analytic_jacobian==1)
+ optim_options = optimoptions(optim_options,'GradObj','on','TolX',1e-7); %alter default TolX
+ end
if ~isempty(options_.optim_opt)
eval(['optim_options = optimoptions(optim_options,' options_.optim_opt ');']);
end
if options_.silent_optimizer
optim_options = optimoptions(optim_options,'display','off');
end
- if options_.analytic_derivation
- optim_options = optimoptions(optim_options,'GradObj','on','TolX',1e-7); %alter default TolX
- end
- if ~isoctave
- [opt_par_values,fval,exitflag,output,lamdba,grad,hessian_mat] = ...
- fmincon(objective_function,start_par_value,[],[],[],[],bounds(:,1),bounds(:,2),[],optim_options,varargin{:});
+ if options_.analytic_derivation || (isfield(options_,'mom') && options_.mom.analytic_jacobian==1) %use wrapper
+ func = @(x) analytic_gradient_wrapper(x,objective_function,varargin{:});
+ if ~isoctave
+ [opt_par_values,fval,exitflag,output,lamdba,grad,hessian_mat] = ...
+ fmincon(func,start_par_value,[],[],[],[],bounds(:,1),bounds(:,2),[],optim_options);
+ else
+ % Under Octave, use a wrapper, since fmincon() does not have an 11th
+ % arg. Also, only the first 4 output arguments are available.
+ [opt_par_values,fval,exitflag,output] = ...
+ fmincon(func,start_par_value,[],[],[],[],bounds(:,1),bounds(:,2),[],optim_options);
+ end
else
- % Under Octave, use a wrapper, since fmincon() does not have an 11th
- % arg. Also, only the first 4 output arguments are available.
- func = @(x) objective_function(x,varargin{:});
- [opt_par_values,fval,exitflag,output] = ...
- fmincon(func,start_par_value,[],[],[],[],bounds(:,1),bounds(:,2),[],optim_options);
+ if ~isoctave
+ [opt_par_values,fval,exitflag,output,lamdba,grad,hessian_mat] = ...
+ fmincon(objective_function,start_par_value,[],[],[],[],bounds(:,1),bounds(:,2),[],optim_options,varargin{:});
+ else
+ % Under Octave, use a wrapper, since fmincon() does not have an 11th
+ % arg. Also, only the first 4 output arguments are available.
+ func = @(x) objective_function(x,varargin{:});
+ [opt_par_values,fval,exitflag,output] = ...
+ fmincon(func,start_par_value,[],[],[],[],bounds(:,1),bounds(:,2),[],optim_options);
+ end
end
case 2
@@ -159,20 +172,28 @@ switch minimizer_algorithm
if ~isempty(options_.optim_opt)
eval(['optim_options = optimoptions(optim_options,' options_.optim_opt ');']);
end
- if options_.analytic_derivation
- optim_options = optimoptions(optim_options,'GradObj','on');
- end
if options_.silent_optimizer
optim_options = optimoptions(optim_options,'display','off');
end
- if ~isoctave
- [opt_par_values,fval,exitflag] = fminunc(objective_function,start_par_value,optim_options,varargin{:});
+ if options_.analytic_derivation || (isfield(options_,'mom') && options_.mom.analytic_jacobian==1)
+ optim_options = optimoptions(optim_options,'GradObj','on');
+ if ~isoctave
+ func = @(x) analytic_gradient_wrapper(x,objective_function,varargin{:});
+ [opt_par_values,fval,exitflag] = fminunc(func,start_par_value,optim_options);
+ else
+ % Under Octave, use a wrapper, since fminunc() does not have a 4th arg
+ func = @(x) analytic_gradient_wrapper(x,objective_function,varargin{:});
+ [opt_par_values,fval,exitflag] = fminunc(func,start_par_value,optim_options);
+ end
else
- % Under Octave, use a wrapper, since fminunc() does not have a 4th arg
- func = @(x) objective_function(x,varargin{:});
- [opt_par_values,fval,exitflag] = fminunc(func,start_par_value,optim_options);
+ if ~isoctave
+ [opt_par_values,fval,exitflag] = fminunc(objective_function,start_par_value,optim_options,varargin{:});
+ else
+ % Under Octave, use a wrapper, since fminunc() does not have a 4th arg
+ func = @(x) objective_function(x,varargin{:});
+ [opt_par_values,fval,exitflag] = fminunc(func,start_par_value,optim_options);
+ end
end
-
case 4
% Set default options.
H0 = 1e-4*eye(n_params);
@@ -500,7 +521,12 @@ switch minimizer_algorithm
if options_.silent_optimizer
solveoptoptions.verbosity = 0;
end
- [opt_par_values,fval]=solvopt(start_par_value,objective_function,[],[],[],solveoptoptions,varargin{:});
+ if options_.analytic_derivation || (isfield(options_,'mom') && options_.mom.analytic_jacobian==1)
+ func = @(x) analytic_gradient_wrapper(x,objective_function,varargin{:});
+ [opt_par_values,fval]=solvopt(start_par_value,func,1,[],[],solveoptoptions);
+ else
+ [opt_par_values,fval]=solvopt(start_par_value,objective_function,[],[],[],solveoptoptions,varargin{:});
+ end
case 102
if isoctave
error('Optimization algorithm 2 is not available under Octave')