diff --git a/matlab/method_of_moments/method_of_moments.m b/matlab/method_of_moments/method_of_moments.m
index 5d86fb93dfdd2d63b2f87b31bdeb15e1c0bd0ce8..9a4f57fb11cae60b8c400aa96020ddc450db3fbe 100644
--- a/matlab/method_of_moments/method_of_moments.m
+++ b/matlab/method_of_moments/method_of_moments.m
@@ -738,11 +738,6 @@ catch last_error% if check fails, provide info on using calibration if present
rethrow(last_error);
end
-if options_mom_.mode_compute == 0 %We only report value of moments distance at initial value of the parameters
- fprintf('No minimization of moments distance due to ''mode_compute=0''\n')
- return
-end
-
% -------------------------------------------------------------------------
% Step 7a: Method of moments estimation: print some info
% -------------------------------------------------------------------------
@@ -760,27 +755,36 @@ end
if options_mom_.mom.penalized_estimator
fprintf('\n - penalized estimation using deviation from prior mean and weighted with prior precision');
end
-if options_mom_.mode_compute == 1; fprintf('\n - optimizer (mode_compute=1): fmincon');
-elseif options_mom_.mode_compute == 2; fprintf('\n - optimizer (mode_compute=2): continuous simulated annealing');
-elseif options_mom_.mode_compute == 3; fprintf('\n - optimizer (mode_compute=3): fminunc');
-elseif options_mom_.mode_compute == 4; fprintf('\n - optimizer (mode_compute=4): csminwel');
-elseif options_mom_.mode_compute == 5; fprintf('\n - optimizer (mode_compute=5): newrat');
-elseif options_mom_.mode_compute == 6; fprintf('\n - optimizer (mode_compute=6): gmhmaxlik');
-elseif options_mom_.mode_compute == 7; fprintf('\n - optimizer (mode_compute=7): fminsearch');
-elseif options_mom_.mode_compute == 8; fprintf('\n - optimizer (mode_compute=8): Dynare Nelder-Mead simplex');
-elseif options_mom_.mode_compute == 9; fprintf('\n - optimizer (mode_compute=9): CMA-ES');
-elseif options_mom_.mode_compute == 10; fprintf('\n - optimizer (mode_compute=10): simpsa');
-elseif options_mom_.mode_compute == 11; fprintf('\n - optimizer (mode_compute=11): online_auxiliary_filter');
-elseif options_mom_.mode_compute == 12; fprintf('\n - optimizer (mode_compute=12): particleswarm');
-elseif options_mom_.mode_compute == 101; fprintf('\n - optimizer (mode_compute=101): SolveOpt');
-elseif options_mom_.mode_compute == 102; fprintf('\n - optimizer (mode_compute=102): simulannealbnd');
-elseif options_mom_.mode_compute == 13; fprintf('\n - optimizer (mode_compute=13): lsqnonlin');
-elseif ischar(minimizer_algorithm); fprintf(['\n - user-defined optimizer: ' minimizer_algorithm]);
-else
- error('method_of_moments: Unknown optimizer, please contact the developers ')
-end
-if options_mom_.silent_optimizer
- fprintf(' (silent)');
+optimizer_vec=[options_mom_.mode_compute;num2cell(options_mom_.additional_optimizer_steps)]; % at each stage one can possibly use different optimizers sequentially
+for i = 1:length(optimizer_vec)
+ if i == 1
+ str = '- optimizer (mode_compute';
+ else
+ str = ' (additional_optimizer_steps';
+ end
+ if optimizer_vec{i} == 0; fprintf('\n %s=0): no minimization',str);
+ elseif optimizer_vec{i} == 1; fprintf('\n %s=1): fmincon',str);
+ elseif optimizer_vec{i} == 2; fprintf('\n %s=2): continuous simulated annealing',str);
+ elseif optimizer_vec{i} == 3; fprintf('\n %s=3): fminunc',str);
+ elseif optimizer_vec{i} == 4; fprintf('\n %s=4): csminwel',str);
+ elseif optimizer_vec{i} == 5; fprintf('\n %s=5): newrat',str);
+ elseif optimizer_vec{i} == 6; fprintf('\n %s=6): gmhmaxlik',str);
+ elseif optimizer_vec{i} == 7; fprintf('\n %s=7): fminsearch',str);
+ elseif optimizer_vec{i} == 8; fprintf('\n %s=8): Dynare Nelder-Mead simplex',str);
+ elseif optimizer_vec{i} == 9; fprintf('\n %s=9): CMA-ES',str);
+ elseif optimizer_vec{i} == 10; fprintf('\n %s=10): simpsa',str);
+ elseif optimizer_vec{i} == 11; fprintf('\n %s=11): online_auxiliary_filter',str);
+ elseif optimizer_vec{i} == 12; fprintf('\n %s=12): particleswarm',str);
+ elseif optimizer_vec{i} == 101; fprintf('\n %s=101): SolveOpt',str);
+ elseif optimizer_vec{i} == 102; fprintf('\n %s=102): simulannealbnd',str);
+ elseif optimizer_vec{i} == 13; fprintf('\n %s=13): lsqnonlin',str);
+ elseif ischar(optimizer_vec{i});fprintf('\n %s=%s): user-defined',str,optimizer_vec{i});
+ else
+ error('method_of_moments: Unknown optimizer, please contact the developers ')
+ end
+ if options_mom_.silent_optimizer
+ fprintf(' (silent)');
+ end
end
fprintf('\n - perturbation order: %d', options_mom_.order)
if options_mom_.order > 1 && options_mom_.pruning
@@ -802,8 +806,6 @@ if size(options_mom_.mom.weighting_matrix,1)>1 && ~(any(strcmpi('diagonal',optio
fprintf('\nYou did not specify the use of an optimal or diagonal weighting matrix. There is no point in running an iterated method of moments.\n')
end
-optimizer_vec=[options_mom_.mode_compute,options_mom_.additional_optimizer_steps]; % at each stage one can possibly use different optimizers sequentially
-
for stage_iter=1:size(options_mom_.mom.weighting_matrix,1)
fprintf('Estimation stage %u\n',stage_iter);
Woptflag = false;
@@ -849,15 +851,20 @@ for stage_iter=1:size(options_mom_.mom.weighting_matrix,1)
end
for optim_iter= 1:length(optimizer_vec)
- if optimizer_vec(optim_iter)==13
- options_mom_.vector_output = true;
+ if optimizer_vec{optim_iter}==0
+ xparam1=xparam0; %no minimization, evaluate objective at current values
+ fval = feval(objective_function, xparam1, Bounds, oo_, estim_params_, M_, options_mom_);
else
- options_mom_.vector_output = false;
- end
- [xparam1, fval, exitflag] = dynare_minimize_objective(objective_function, xparam0, optimizer_vec(optim_iter), options_mom_, [Bounds.lb Bounds.ub], bayestopt_laplace.name, bayestopt_laplace, [],...
- Bounds, oo_, estim_params_, M_, options_mom_);
- if options_mom_.vector_output
- fval = fval'*fval;
+ if optimizer_vec{optim_iter}==13
+ options_mom_.vector_output = true;
+ else
+ options_mom_.vector_output = false;
+ end
+ [xparam1, fval, exitflag] = dynare_minimize_objective(objective_function, xparam0, optimizer_vec{optim_iter}, options_mom_, [Bounds.lb Bounds.ub], bayestopt_laplace.name, bayestopt_laplace, [],...
+ Bounds, oo_, estim_params_, M_, options_mom_);
+ if options_mom_.vector_output
+ fval = fval'*fval;
+ end
end
fprintf('\nStage %d Iteration %d: value of minimized moment distance objective function: %12.10f.\n',stage_iter,optim_iter,fval)
if options_mom_.mom.verbose