172 lines
6.6 KiB
Matlab
172 lines
6.6 KiB
Matlab
function [info, oo_, options_, M_] = run(M_, options_, oo_, var_list, params, i_var,W)
|
|
% [info, oo_, options_, M_] = osr(M_, options_, oo_, var_list, params, i_var,W)
|
|
% Function computing the solution to the optimal simple rule-problem
|
|
%
|
|
% INPUTS
|
|
% M_ [structure] Dynare's model structure
|
|
% oo_ [structure] Dynare's results structure
|
|
% options_ [structure] Dynare's options structure
|
|
% var_list [character array] list of endogenous variables specified
|
|
% params [character array] list of parameter to be chosen in
|
|
% optimal simple rule
|
|
% i_var [n_osr_vars by 1 double] indices of osr-variable in
|
|
% specified in optim_weights in declaration order
|
|
% W [M_.endo_nbr by M_.endo_nbr sparse matrix] Weighting matrix for variance of endogenous variables
|
|
%
|
|
% OUTPUTS
|
|
% info [integer] scalar or vector, error code.
|
|
% oo_ [structure] Dynare's results structure, containing subfield
|
|
% osr_res: results structure containing:
|
|
% - objective_function [scalar double] value of the objective
|
|
% function at the optimum
|
|
% - optim_params [structure] parameter values at the optimum
|
|
% options_ [structure] Dynare's options structure
|
|
% M_ [structure] Dynare's model structure
|
|
%
|
|
% SPECIAL REQUIREMENTS
|
|
% none.
|
|
|
|
% Copyright © 2001-2023 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 <https://www.gnu.org/licenses/>.
|
|
|
|
options_.order = 1;
|
|
|
|
if isempty(options_.qz_criterium)
|
|
options_.qz_criterium = 1+1e-6;
|
|
end
|
|
|
|
oo_=make_ex_(M_,options_,oo_);
|
|
|
|
np = size(params,1);
|
|
i_params = zeros(np,1);
|
|
for i=1:np
|
|
str = deblank(params(i,:));
|
|
i_params(i) = strmatch(str{:}, M_.param_names, 'exact');
|
|
end
|
|
|
|
if ~options_.noprint
|
|
fprintf('\nOPTIMAL SIMPLE RULE\n')
|
|
end
|
|
|
|
osr_res.error_indicator = 1; %initialize indicator
|
|
|
|
if M_.exo_nbr == 0
|
|
oo_.exo_steady_state = [] ;
|
|
end
|
|
|
|
if ~M_.lead_lag_incidence(M_.maximum_lag+1,:) > 0
|
|
error ('OSR: Error in model specification: some variables don''t appear as current') ;
|
|
end
|
|
|
|
if M_.maximum_lead == 0
|
|
error ('OSR: Backward or static model: no point in using OSR') ;
|
|
end
|
|
|
|
if any(any(isinf(W)))
|
|
error ('OSR: At least one of the optim_weights is infinite.') ;
|
|
end
|
|
|
|
if any(isnan(M_.params(i_params)))
|
|
error ('OSR: At least one of the initial parameter values for osr_params is NaN') ;
|
|
end
|
|
|
|
%restore backward compatibility with maxit and tolf
|
|
if isfield(options_.osr,'maxit') || isfield(options_.osr,'tolf')
|
|
warning('OSR: The use of maxit and tolf is now deprecated. Please use the optim-option instead.')
|
|
if options_.osr.opt_algo~=4
|
|
error ('OSR: The maxit and tolf options are not supported when not using the default opt_algo=4. Use the optim-option instead.') ;
|
|
else
|
|
if isfield(options_.osr,'maxit')
|
|
if ~isempty(options_.optim_opt)
|
|
options_.optim_opt=[options_.optim_opt,','];
|
|
end
|
|
options_.optim_opt=[options_.optim_opt,'''MaxIter'',',num2str(options_.osr.maxit),''];
|
|
end
|
|
if isfield(options_.osr,'tolf')
|
|
if ~isempty(options_.optim_opt)
|
|
options_.optim_opt=[options_.optim_opt,','];
|
|
end
|
|
options_.optim_opt=[options_.optim_opt,'''TolFun'',',num2str(options_.osr.tolf),''];
|
|
end
|
|
end
|
|
end
|
|
|
|
oo_.dr = set_state_space(oo_.dr,M_);
|
|
par_0 = M_.params(i_params);
|
|
inv_order_var = oo_.dr.inv_order_var;
|
|
|
|
%extract unique entries of covariance
|
|
i_var=unique(i_var);
|
|
%% do initial checks
|
|
[loss,info]=osr.objective(par_0,M_,oo_,options_,i_params,inv_order_var(i_var),W(i_var,i_var));
|
|
if info~=0
|
|
print_info(info, options_.noprint, options_);
|
|
else
|
|
if ~options_.noprint
|
|
fprintf('\nOSR: Initial value of the objective function: %g \n\n',loss);
|
|
end
|
|
end
|
|
if ~options_.noprint && isinf(loss)
|
|
fprintf('\nOSR: The initial value of the objective function is infinite.\n');
|
|
fprintf('\nOSR: Check whether the unconditional variance of a target variable is infinite\n');
|
|
fprintf('\nOSR: due to the presence of a unit root.\n');
|
|
error('OSR: Initial likelihood is infinite')
|
|
end
|
|
|
|
if isequal(options_.osr.opt_algo,5)
|
|
error('OSR: OSR does not support opt_algo=5.')
|
|
elseif isequal(options_.osr.opt_algo,6)
|
|
error('OSR: OSR does not support opt_algo=6.')
|
|
elseif isequal(options_.osr.opt_algo,10)
|
|
error('OSR: OSR does not support opt_algo=10.')
|
|
elseif isequal(options_.osr.opt_algo,11)
|
|
error('OSR: OSR does not support opt_algo=11.')
|
|
else
|
|
if ~isempty(M_.osr.param_bounds) && ~(ismember(options_.osr.opt_algo,[1,2,5,9]) || ischar(options_.osr.opt_algo))
|
|
error('OSR: OSR with bounds on parameters requires a constrained optimizer, i.e. opt_algo= 1,2 or 9.')
|
|
end
|
|
%%do actual optimization
|
|
[p, f] = dynare_minimize_objective(str2func('osr.objective'),par_0,options_.osr.opt_algo,options_,M_.osr.param_bounds,M_.param_names(i_params),[],[], M_,oo_,options_,i_params,...
|
|
inv_order_var(i_var),W(i_var,i_var));
|
|
end
|
|
|
|
osr_res.objective_function = f;
|
|
M_.params(i_params)=p; %make sure optimal parameters are set (and not the last draw used in csminwel)
|
|
for i=1:length(i_params)
|
|
osr_res.optim_params.(M_.param_names{i_params(i)}) = p(i);
|
|
end
|
|
|
|
if ~options_.noprint
|
|
my_title='OPTIMAL VALUE OF THE PARAMETERS';
|
|
labels = M_.param_names(i_params);
|
|
headers = {'Variables'; 'Value'};
|
|
lh = cellofchararraymaxlength(labels)+2;
|
|
dyntable(options_, my_title, headers, labels, p, lh, 10, 6);
|
|
if options_.TeX
|
|
labels = M_.param_names_tex(i_params);
|
|
lh = cellofchararraymaxlength(labels)+2;
|
|
dyn_latex_table(M_, options_, my_title, 'osr', headers, labels, p, lh, 10, 6);
|
|
end
|
|
fprintf('\nObjective function : %16.6g\n\n',f);
|
|
end
|
|
|
|
[info, oo_, options_, M_] = stoch_simul(M_, options_, oo_, var_list);
|
|
|
|
if ~info(1)
|
|
osr_res.error_indicator=0;
|
|
end
|
|
oo_.osr = osr_res; |