diff --git a/tests/TeX/fs2000_corr_ME.mod b/tests/TeX/fs2000_corr_ME.mod
index b4a17fc7c..b0ebe70fd 100644
--- a/tests/TeX/fs2000_corr_ME.mod
+++ b/tests/TeX/fs2000_corr_ME.mod
@@ -154,7 +154,7 @@ stderr gy_obs, 1;
 corr gp_obs, gy_obs,0;
 end;
 
-estimation(order=1,mode_compute=4,datafile='../fs2000/fsdat_simul',brooks_gelman_plotrows=4, mode_check,smoother,filter_covariance,filter_decomposition,forecast = 8,filtered_vars,filter_step_ahead=[1,3],irf=20,contemporaneous_correlation) m P c e W R k d y gy_obs;
+estimation(order=1,mode_compute=4,silent_optimizer,datafile='../fs2000/fsdat_simul',brooks_gelman_plotrows=4, mode_check,smoother,filter_covariance,filter_decomposition,forecast = 8,filtered_vars,filter_step_ahead=[1,3],irf=20,contemporaneous_correlation) m P c e W R k d y gy_obs;
 
 
 
@@ -172,7 +172,7 @@ end;
 
 write_latex_prior_table;
 
-estimation(mode_compute=8,order=1,datafile='../fs2000/fsdat_simul',mode_check,smoother,filter_decomposition,mh_replic=4000, mh_nblocks=1, mh_jscale=0.8,forecast = 8,bayesian_irf,filtered_vars,filter_step_ahead=[1,3],irf=20,
+estimation(mode_compute=8,silent_optimizer,order=1,datafile='../fs2000/fsdat_simul',mode_check,smoother,filter_decomposition,mh_replic=4000, mh_nblocks=1, mh_jscale=0.8,forecast = 8,bayesian_irf,filtered_vars,filter_step_ahead=[1,3],irf=20,
         moments_varendo,contemporaneous_correlation,conditional_variance_decomposition=[1 2 4],smoothed_state_uncertainty,raftery_lewis_diagnostics) m P c e W R k d y gy_obs;
 
 trace_plot(options_,M_,estim_params_,'PosteriorDensity',1);
diff --git a/tests/analytic_derivatives/fs2000_analytic_derivation.mod b/tests/analytic_derivatives/fs2000_analytic_derivation.mod
index a5e6eeec1..02ce40955 100644
--- a/tests/analytic_derivatives/fs2000_analytic_derivation.mod
+++ b/tests/analytic_derivatives/fs2000_analytic_derivation.mod
@@ -76,7 +76,7 @@ varobs gp_obs gy_obs;
 
 options_.solve_tolf = 1e-12;
 
-estimation(order=1,mode_compute=9,analytic_derivation,kalman_algo=1,datafile=my_data,nobs=192,mh_replic=0,mh_nblocks=2,mh_jscale=0.8,plot_priors=0,prior_trunc=0);
+estimation(order=1,mode_compute=9,silent_optimizer,analytic_derivation,kalman_algo=1,datafile=my_data,nobs=192,mh_replic=0,mh_nblocks=2,mh_jscale=0.8,plot_priors=0,prior_trunc=0);
 if (isoctave && user_has_octave_forge_package('optim', '1.6')) || (~isoctave && user_has_matlab_license('optimization_toolbox'))
     estimation(order=1,mode_compute=1,mode_file='fs2000_analytic_derivation/Output/fs2000_analytic_derivation_mode',analytic_derivation,kalman_algo=1,datafile=my_data,nobs=192,mh_replic=0,mh_nblocks=2,mh_jscale=0.8,plot_priors=0
     %,optim = ('DerivativeCheck', 'on','FiniteDifferenceType','central')
@@ -85,10 +85,10 @@ if (isoctave && user_has_octave_forge_package('optim', '1.6')) || (~isoctave &&
     estimation(order=1,mode_compute=101,mode_file='fs2000_analytic_derivation/Output/fs2000_analytic_derivation_mode',analytic_derivation,kalman_algo=1,datafile=my_data,nobs=192,mh_replic=0,mh_nblocks=2,mh_jscale=0.8,plot_priors=0);    
 end
 if ~isoctave % This estimation randomly fails on Octave
-estimation(order=1,mode_compute=5,mode_file='fs2000_analytic_derivation/Output/fs2000_analytic_derivation_mode',analytic_derivation,kalman_algo=2,datafile=my_data,nobs=192,mh_replic=0,mh_nblocks=2,mh_jscale=0.8,plot_priors=0);
+estimation(order=1,mode_compute=5,silent_optimizer,mode_file='fs2000_analytic_derivation/Output/fs2000_analytic_derivation_mode',analytic_derivation,kalman_algo=2,datafile=my_data,nobs=192,mh_replic=0,mh_nblocks=2,mh_jscale=0.8,plot_priors=0);
 end
-estimation(order=1,mode_compute=4,mode_file='fs2000_analytic_derivation/Output/fs2000_analytic_derivation_mode',analytic_derivation,kalman_algo=1,datafile=my_data,nobs=192,mh_replic=0,mh_nblocks=2,mh_jscale=0.8,plot_priors=0);
-estimation(order=1,mode_compute=4,mode_file='fs2000_analytic_derivation/Output/fs2000_analytic_derivation_mode',analytic_derivation,kalman_algo=2,datafile=my_data,nobs=192,mh_replic=0,mh_nblocks=2,mh_jscale=0.8,plot_priors=0);
+estimation(order=1,mode_compute=4,silent_optimizer,mode_file='fs2000_analytic_derivation/Output/fs2000_analytic_derivation_mode',analytic_derivation,kalman_algo=1,datafile=my_data,nobs=192,mh_replic=0,mh_nblocks=2,mh_jscale=0.8,plot_priors=0);
+estimation(order=1,mode_compute=4,silent_optimizer,mode_file='fs2000_analytic_derivation/Output/fs2000_analytic_derivation_mode',analytic_derivation,kalman_algo=2,datafile=my_data,nobs=192,mh_replic=0,mh_nblocks=2,mh_jscale=0.8,plot_priors=0);
 options_.debug=1;
 estimation(order=1,mode_compute=0,mode_file='fs2000_analytic_derivation/Output/fs2000_analytic_derivation_mode',analytic_derivation,kalman_algo=1,datafile=my_data,nobs=192,mh_replic=0,plot_priors=0);
 fval_ML_1=oo_.likelihood_at_initial_parameters;
@@ -111,19 +111,19 @@ stderr e_a, inv_gamma_pdf, 0.035449, inf;
 stderr e_m, inv_gamma_pdf, 0.008862, inf;
 end;
 
-estimation(order=1,mode_compute=9,analytic_derivation,kalman_algo=1,datafile=my_data,nobs=192,mh_replic=0,mh_nblocks=2,mh_jscale=0.8,plot_priors=0,prior_trunc=0);
+estimation(order=1,mode_compute=9,silent_optimizer,analytic_derivation,kalman_algo=1,datafile=my_data,nobs=192,mh_replic=0,mh_nblocks=2,mh_jscale=0.8,plot_priors=0,prior_trunc=0);
 if (isoctave && user_has_octave_forge_package('optim', '1.6')) || (~isoctave && user_has_matlab_license('optimization_toolbox'))
     estimation(order=1,mode_compute=1,mode_file='fs2000_analytic_derivation/Output/fs2000_analytic_derivation_mode',analytic_derivation,kalman_algo=1,datafile=my_data,nobs=192,mh_replic=0,mh_nblocks=2,mh_jscale=0.8,plot_priors=0
     %,optim = ('DerivativeCheck', 'on','FiniteDifferenceType','central')
     );
-    estimation(order=1,mode_compute=3,mode_file='fs2000_analytic_derivation/Output/fs2000_analytic_derivation_mode',analytic_derivation,kalman_algo=1,datafile=my_data,nobs=192,mh_replic=0,mh_nblocks=2,mh_jscale=0.8,plot_priors=0);
-    estimation(order=1,mode_compute=101,mode_file='fs2000_analytic_derivation/Output/fs2000_analytic_derivation_mode',analytic_derivation,kalman_algo=1,datafile=my_data,nobs=192,mh_replic=0,mh_nblocks=2,mh_jscale=0.8,plot_priors=0);    
+    estimation(order=1,mode_compute=3,silent_optimizer,mode_file='fs2000_analytic_derivation/Output/fs2000_analytic_derivation_mode',analytic_derivation,kalman_algo=1,datafile=my_data,nobs=192,mh_replic=0,mh_nblocks=2,mh_jscale=0.8,plot_priors=0);
+    estimation(order=1,mode_compute=101,silent_optimizer,mode_file='fs2000_analytic_derivation/Output/fs2000_analytic_derivation_mode',analytic_derivation,kalman_algo=1,datafile=my_data,nobs=192,mh_replic=0,mh_nblocks=2,mh_jscale=0.8,plot_priors=0);    
 end
 if ~isoctave % This estimation randomly fails on Octave
-estimation(order=1,mode_compute=5,mode_file='fs2000_analytic_derivation/Output/fs2000_analytic_derivation_mode',analytic_derivation,kalman_algo=2,datafile=my_data,nobs=192,mh_replic=0,mh_nblocks=2,mh_jscale=0.8,plot_priors=0);
+estimation(order=1,mode_compute=5,silent_optimizer,mode_file='fs2000_analytic_derivation/Output/fs2000_analytic_derivation_mode',analytic_derivation,kalman_algo=2,datafile=my_data,nobs=192,mh_replic=0,mh_nblocks=2,mh_jscale=0.8,plot_priors=0);
 end
-estimation(order=1,mode_compute=4,mode_file='fs2000_analytic_derivation/Output/fs2000_analytic_derivation_mode',analytic_derivation,kalman_algo=1,datafile=my_data,nobs=192,mh_replic=0,mh_nblocks=2,mh_jscale=0.8,plot_priors=0);
-estimation(order=1,mode_compute=4,mode_file='fs2000_analytic_derivation/Output/fs2000_analytic_derivation_mode',analytic_derivation,kalman_algo=2,datafile=my_data,nobs=192,mh_replic=0,mh_nblocks=2,mh_jscale=0.8,plot_priors=0);
+estimation(order=1,mode_compute=4,silent_optimizer,mode_file='fs2000_analytic_derivation/Output/fs2000_analytic_derivation_mode',analytic_derivation,kalman_algo=1,datafile=my_data,nobs=192,mh_replic=0,mh_nblocks=2,mh_jscale=0.8,plot_priors=0);
+estimation(order=1,mode_compute=4,silent_optimizer,mode_file='fs2000_analytic_derivation/Output/fs2000_analytic_derivation_mode',analytic_derivation,kalman_algo=2,datafile=my_data,nobs=192,mh_replic=0,mh_nblocks=2,mh_jscale=0.8,plot_priors=0);
 options_.debug=1;
 estimation(order=1,mode_compute=0,mode_file='fs2000_analytic_derivation/Output/fs2000_analytic_derivation_mode',analytic_derivation,kalman_algo=1,datafile=my_data,nobs=192,mh_replic=0,plot_priors=0);
 fval_Bayes_1=oo_.likelihood_at_initial_parameters;
diff --git a/tests/arima/mod1a.mod b/tests/arima/mod1a.mod
index 9020522de..44462f15a 100644
--- a/tests/arima/mod1a.mod
+++ b/tests/arima/mod1a.mod
@@ -25,4 +25,4 @@ end;
 
 varobs dx dy;
 check;
-estimation(datafile=data1,nobs=1000,mh_replic=2000,mh_jscale=1.2);
\ No newline at end of file
+estimation(datafile=data1,silent_optimizer,nobs=1000,mh_replic=2000,mh_jscale=1.2);
\ No newline at end of file
diff --git a/tests/arima/mod1b.mod b/tests/arima/mod1b.mod
index ba439aa0b..23ec97eec 100644
--- a/tests/arima/mod1b.mod
+++ b/tests/arima/mod1b.mod
@@ -28,4 +28,4 @@ stderr e_y,INV_GAMMA_PDF,0.01,inf;
 end;
 
 varobs x y;
-estimation(datafile=data1,nobs=1000,mh_replic=0,mh_jscale=0.8,diffuse_filter);
\ No newline at end of file
+estimation(datafile=data1,silent_optimizer,nobs=1000,mh_replic=0,mh_jscale=0.8,diffuse_filter);
\ No newline at end of file
diff --git a/tests/arima/mod1c.mod b/tests/arima/mod1c.mod
index 527015edd..3cc3a6d19 100644
--- a/tests/arima/mod1c.mod
+++ b/tests/arima/mod1c.mod
@@ -30,4 +30,4 @@ stderr y,INV_GAMMA_PDF,0.01,inf;
 end;
 
 varobs x y;
-estimation(datafile=data1,nobs=1000,mh_replic=2000,lik_init=2,mh_jscale=1.2);
\ No newline at end of file
+estimation(datafile=data1,silent_optimizer,nobs=1000,mh_replic=2000,lik_init=2,mh_jscale=1.2);
\ No newline at end of file
diff --git a/tests/arima/mod2a.mod b/tests/arima/mod2a.mod
index 18eaa2b52..cae45f667 100644
--- a/tests/arima/mod2a.mod
+++ b/tests/arima/mod2a.mod
@@ -36,4 +36,4 @@ end;
 
 varobs dx dy;
 
-estimation(datafile=data2,nobs=100,mh_replic=0,diffuse_filter);
+estimation(datafile=data2,silent_optimizer,nobs=100,mh_replic=0,diffuse_filter);
diff --git a/tests/arima/mod2b.mod b/tests/arima/mod2b.mod
index 432e851d1..049d436f9 100644
--- a/tests/arima/mod2b.mod
+++ b/tests/arima/mod2b.mod
@@ -36,4 +36,4 @@ end;
 
 varobs x y;
 
-estimation(datafile=data2,nobs=100,mh_replic=0,diffuse_filter);
+estimation(datafile=data2,silent_optimizer,nobs=100,mh_replic=0,diffuse_filter);
diff --git a/tests/arima/mod2c.mod b/tests/arima/mod2c.mod
index 132a3887b..d5bf89b4f 100644
--- a/tests/arima/mod2c.mod
+++ b/tests/arima/mod2c.mod
@@ -34,4 +34,4 @@ end;
 
 varobs dx dy;
 
-estimation(datafile=data2,nobs=100,mh_replic=0);
+estimation(datafile=data2,silent_optimizer,nobs=100,mh_replic=0);
diff --git a/tests/bgp/solow-1/solow.mod b/tests/bgp/solow-1/solow.mod
index c5e26af32..930c6d0d7 100644
--- a/tests/bgp/solow-1/solow.mod
+++ b/tests/bgp/solow-1/solow.mod
@@ -66,11 +66,13 @@ verbatim;
             GK(i) = y(12);
             EG(i) = y(2);
         end        
-        % Display the progress
-        percentDone = 100 * i / MC;
-        msg = sprintf('Percent done: %3.1f', percentDone);
-        fprintf([reverseStr, msg]);
-        reverseStr = repmat(sprintf('\b'), 1, length(msg));
+        if mod(i,100)==0
+            % Display the progress
+            percentDone = 100 * i / MC;
+            msg = sprintf('Percent done: %3.1f', percentDone);
+            fprintf([reverseStr, msg]);
+            reverseStr = repmat(sprintf('\b'), 1, length(msg));
+        end
     end
     fprintf('\n');
     % Compute the physical capital stock over output ratio along the BGP as
diff --git a/tests/conditional_forecasts/2/fs2000_est.mod b/tests/conditional_forecasts/2/fs2000_est.mod
index ce069da7b..e2d79f4d7 100644
--- a/tests/conditional_forecasts/2/fs2000_est.mod
+++ b/tests/conditional_forecasts/2/fs2000_est.mod
@@ -107,7 +107,7 @@ varobs gp_obs gy_obs;
 options_.solve_tolf = 1e-12;
 
 // Metropolis replications are too few, this is only for testing purpose
-estimation(order=1,datafile=fsdat_simul,nobs=192,loglinear,mh_replic=2000,mh_nblocks=1,mh_jscale=0.8);
+estimation(order=1,datafile=fsdat_simul,silent_optimizer,nobs=192,loglinear,mh_replic=2000,mh_nblocks=1,mh_jscale=0.8);
 
 conditional_forecast_paths;
 var gy_obs;
diff --git a/tests/data/mod1a.mod b/tests/data/mod1a.mod
index a2f0ff951..b738f20ea 100644
--- a/tests/data/mod1a.mod
+++ b/tests/data/mod1a.mod
@@ -20,4 +20,4 @@ end;
 
 varobs dx dy;
 check;
-estimation(datafile='test.xlsx',nobs=1000,mh_replic=2000,mh_jscale=1.3);
+estimation(datafile='test.xlsx',nobs=1000,mh_replic=2000,mh_jscale=1.3,silent_optimizer);
diff --git a/tests/dates/dseries_interact.mod b/tests/dates/dseries_interact.mod
index 929b1b489..5cc64115e 100644
--- a/tests/dates/dseries_interact.mod
+++ b/tests/dates/dseries_interact.mod
@@ -41,9 +41,9 @@ varobs log_nn;
 
 %reading Excel sheet from column A on creates quarterly dseries starting in
 %1950
-estimation(first_obs=2,datafile='data_uav.xlsx', xls_sheet=Tabelle1, xls_range=a1:b54, mh_replic=2, mh_nblocks=1, mh_jscale=1.1, mh_drop=0.8, plot_priors=0, smoother) log_nn nn hh ;
+estimation(first_obs=2,datafile='data_uav.xlsx', xls_sheet=Tabelle1, xls_range=a1:b54, silent_optimizer,mh_replic=2, mh_nblocks=1, mh_jscale=1.1, mh_drop=0.8, plot_priors=0, smoother) log_nn nn hh ;
 shock_decomposition( parameter_set=posterior_median ) nn hh;
 
 %reading Excel sheet from column B on creates annual dseries starting with 1
-estimation(first_obs=2,datafile='data_uav.xlsx', xls_sheet=Tabelle1, xls_range=b1:b54, mh_replic=2, mh_nblocks=1, mh_jscale=1.1, mh_drop=0.8, plot_priors=0, smoother) log_nn nn hh ;
+estimation(first_obs=2,datafile='data_uav.xlsx', xls_sheet=Tabelle1, xls_range=b1:b54, silent_optimizer, mh_replic=2, mh_nblocks=1, mh_jscale=1.1, mh_drop=0.8, plot_priors=0, smoother) log_nn nn hh ;
 shock_decomposition( parameter_set=posterior_median ) nn hh;
diff --git a/tests/dates/fs2000.mod b/tests/dates/fs2000.mod
index e65a2d926..3bea2a0e0 100644
--- a/tests/dates/fs2000.mod
+++ b/tests/dates/fs2000.mod
@@ -88,5 +88,5 @@ data(series=ts, first_obs=1950Q3, last_obs=2000Q3);
 disp('First date is $1950Q3')  // disp('First date is 1950Q3'), without the $ symbol,  would trigger an error because of the substitution of 1950Q3 by dates('1950Q3')
 
 // Run the estimation. Note that we do not have a datafile option, because of the data command used above.
-estimation(order=1, loglinear, mh_replic=0);
+estimation(order=1, loglinear, mh_replic=0, silent_optimizer);
 
diff --git a/tests/discretionary_policy/dennis_1_estim.mod b/tests/discretionary_policy/dennis_1_estim.mod
index ea05d899e..6f7264e07 100644
--- a/tests/discretionary_policy/dennis_1_estim.mod
+++ b/tests/discretionary_policy/dennis_1_estim.mod
@@ -36,7 +36,7 @@ estimated_params;
 end;
 
 options_.plot_priors=0;
-estimation(order = 1, datafile = dennis_simul, mh_replic = 2000, mh_nblocks=1,smoother,bayesian_irf,moments_varendo, conditional_variance_decomposition=[1,2]) y i pi pi_c q;
+estimation(order = 1, datafile = dennis_simul, mh_replic = 2000, silent_optimizer,mh_nblocks=1,smoother,bayesian_irf,moments_varendo, conditional_variance_decomposition=[1,2]) y i pi pi_c q;
 
 if max(abs(oo_.posterior.optimization.mode - [1; 0.3433])) > 0.025
   error('Posterior mode too far from true parameter values');
diff --git a/tests/dsge-var/dsgevar_forward_calibrated_lambda.mod b/tests/dsge-var/dsgevar_forward_calibrated_lambda.mod
index abebf5d6f..7e04cec2d 100644
--- a/tests/dsge-var/dsgevar_forward_calibrated_lambda.mod
+++ b/tests/dsge-var/dsgevar_forward_calibrated_lambda.mod
@@ -80,4 +80,4 @@ varobs pie r rw y;
 ** The Dashed lines are the first, fifth (ie the median) and ninth posterior deciles of the DSGE-VAR's IRFs, the bold dark curve is the
 ** posterior median of the DSGE's IRfs and the shaded surface covers the space between the first and ninth posterior deciles of the DSGE's IRFs.
 */
-estimation(datafile=datarabanal_hybrid,first_obs=50,mh_nblocks = 1,nobs=90,dsge_var=.8,optim=('NumgradAlgorithm',3),mode_compute=4,mh_replic=2000,bayesian_irf);
+estimation(datafile=datarabanal_hybrid,silent_optimizer,first_obs=50,mh_nblocks = 1,nobs=90,dsge_var=.8,optim=('NumgradAlgorithm',3),mode_compute=4,mh_replic=2000,bayesian_irf);
diff --git a/tests/dsge-var/dsgevar_forward_estimated_lambda.mod b/tests/dsge-var/dsgevar_forward_estimated_lambda.mod
index 9fd000d43..ac901a06f 100644
--- a/tests/dsge-var/dsgevar_forward_estimated_lambda.mod
+++ b/tests/dsge-var/dsgevar_forward_estimated_lambda.mod
@@ -85,4 +85,4 @@ varobs pie r rw y;
 ** posterior median of the DSGE's IRfs and the shaded surface covers the space between the first and ninth posterior deciles of the DSGE's IRFs.
 */
 
-estimation(datafile=datarabanal_hybrid,first_obs=50,mh_nblocks = 1,nobs=90,dsge_var,mode_compute=4,optim=('NumgradAlgorithm',3),mh_replic=2000,bayesian_irf);
+estimation(datafile=datarabanal_hybrid,silent_optimizer,first_obs=50,mh_nblocks = 1,nobs=90,dsge_var,mode_compute=4,optim=('NumgradAlgorithm',3),mh_replic=2000,bayesian_irf);
diff --git a/tests/estimation/MH_recover/fs2000_recover.mod b/tests/estimation/MH_recover/fs2000_recover.mod
index 5b551e8d2..36c1251a0 100644
--- a/tests/estimation/MH_recover/fs2000_recover.mod
+++ b/tests/estimation/MH_recover/fs2000_recover.mod
@@ -3,7 +3,7 @@
 @#include "fs2000.common.inc"
 
 options_.MaxNumberOfBytes=1000*11*8/2;
-estimation(order=1, datafile='../fsdat_simul',nobs=192, loglinear, mh_replic=1000, mh_nblocks=2, mh_jscale=0.8);
+estimation(order=1, datafile='../fsdat_simul',nobs=192, silent_optimizer,loglinear, mh_replic=1000, mh_nblocks=2, mh_jscale=0.8);
 copyfile([M_.dname filesep 'metropolis' filesep M_.dname '_mh1_blck1.mat'],[M_.dname '_mh1_blck1.mat'])
 copyfile([M_.dname filesep 'metropolis' filesep M_.dname '_mh2_blck2.mat'],[M_.dname '_mh2_blck2.mat'])
 delete([M_.dname filesep 'metropolis' filesep M_.dname '_mh2_blck2.mat'])
diff --git a/tests/estimation/MH_recover/fs2000_recover_2.mod b/tests/estimation/MH_recover/fs2000_recover_2.mod
index cb70cd1c9..7c6575cab 100644
--- a/tests/estimation/MH_recover/fs2000_recover_2.mod
+++ b/tests/estimation/MH_recover/fs2000_recover_2.mod
@@ -4,7 +4,7 @@
 @#include "fs2000.common.inc"
 
 options_.MaxNumberOfBytes=2000*11*8/4;
-estimation(order=1, datafile='../fsdat_simul',nobs=192, loglinear, mh_replic=999, mh_nblocks=2, mh_jscale=0.8);
+estimation(order=1, datafile='../fsdat_simul',nobs=192, silent_optimizer,loglinear, mh_replic=999, mh_nblocks=2, mh_jscale=0.8);
 estimation(order=1,mode_compute=0,mode_file='fs2000_recover_2/Output/fs2000_recover_2_mode', datafile='../fsdat_simul',nobs=192, loglinear, load_mh_file,mh_replic=1002, mh_nblocks=2, mh_jscale=0.8);
 copyfile([M_.dname filesep 'metropolis' filesep M_.dname '_mh1_blck1.mat'],[M_.dname '_mh1_blck1.mat'])
 copyfile([M_.dname filesep 'metropolis' filesep M_.dname '_mh3_blck2.mat'],[M_.dname '_mh3_blck2.mat'])
diff --git a/tests/estimation/MH_recover/fs2000_recover_3.mod b/tests/estimation/MH_recover/fs2000_recover_3.mod
index ecf0592d4..58eae4f1b 100644
--- a/tests/estimation/MH_recover/fs2000_recover_3.mod
+++ b/tests/estimation/MH_recover/fs2000_recover_3.mod
@@ -4,7 +4,7 @@
 @#include "fs2000.common.inc"
 
 options_.MaxNumberOfBytes=2000*11*8/4;
-estimation(order=1, datafile='../fsdat_simul',nobs=192, loglinear, mh_replic=1000, mh_nblocks=2, mh_jscale=0.8);
+estimation(order=1, datafile='../fsdat_simul',nobs=192, silent_optimizer,loglinear, mh_replic=1000, mh_nblocks=2, mh_jscale=0.8);
 estimation(order=1,mode_compute=0,mode_file='fs2000_recover_3/Output/fs2000_recover_3_mode', datafile='../fsdat_simul',nobs=192, loglinear, load_mh_file,mh_replic=1000, mh_nblocks=2, mh_jscale=0.8);
 copyfile([M_.dname filesep 'metropolis' filesep M_.dname '_mh1_blck1.mat'],[M_.dname '_mh1_blck1.mat'])
 copyfile([M_.dname filesep 'metropolis' filesep M_.dname '_mh3_blck2.mat'],[M_.dname '_mh3_blck2.mat'])
diff --git a/tests/estimation/MH_recover/fs2000_recover_tarb.mod b/tests/estimation/MH_recover/fs2000_recover_tarb.mod
index ea4cb4520..5acc4254a 100644
--- a/tests/estimation/MH_recover/fs2000_recover_tarb.mod
+++ b/tests/estimation/MH_recover/fs2000_recover_tarb.mod
@@ -3,7 +3,7 @@
 @#include "fs2000.common.inc"
 
 options_.MaxNumberOfBytes=10*11*8/2;
-estimation(posterior_sampling_method='tailored_random_block_metropolis_hastings',order=1, datafile='../fsdat_simul',nobs=192, loglinear, mh_replic=10, mh_nblocks=2, mh_jscale=0.8);
+estimation(posterior_sampling_method='tailored_random_block_metropolis_hastings',silent_optimizer,order=1, datafile='../fsdat_simul',nobs=192, loglinear, mh_replic=10, mh_nblocks=2, mh_jscale=0.8);
 copyfile([M_.dname filesep 'metropolis' filesep M_.dname '_mh1_blck1.mat'],[M_.dname '_mh1_blck1.mat'])
 copyfile([M_.dname filesep 'metropolis' filesep M_.dname '_mh2_blck2.mat'],[M_.dname '_mh2_blck2.mat'])
 delete([M_.dname filesep 'metropolis' filesep M_.dname '_mh2_blck2.mat'])
diff --git a/tests/estimation/conditional-likelihood/1/fs2000_estimation_conditional.mod b/tests/estimation/conditional-likelihood/1/fs2000_estimation_conditional.mod
index 5118a37e0..6ed7ce991 100644
--- a/tests/estimation/conditional-likelihood/1/fs2000_estimation_conditional.mod
+++ b/tests/estimation/conditional-likelihood/1/fs2000_estimation_conditional.mod
@@ -81,7 +81,7 @@ varobs gp_obs gy_obs;
 options_.solve_tolf = 1e-12;
 
 tic
-estimation(conditional_likelihood,order=1,datafile='../../fsdat_simul',nobs=192,mode_compute=4,loglinear,mh_replic=5000,mh_nblocks=2,mh_jscale=0.8);
+estimation(conditional_likelihood,silent_optimizer,order=1,datafile='../../fsdat_simul',nobs=192,mode_compute=4,loglinear,mh_replic=5000,mh_nblocks=2,mh_jscale=0.8);
 toc
 
 exact_likelihood = load('fs2000_estimation_exact/Output/fs2000_estimation_exact_results.mat');
diff --git a/tests/estimation/conditional-likelihood/1/fs2000_estimation_exact.mod b/tests/estimation/conditional-likelihood/1/fs2000_estimation_exact.mod
index 38c641100..2e11b00c6 100644
--- a/tests/estimation/conditional-likelihood/1/fs2000_estimation_exact.mod
+++ b/tests/estimation/conditional-likelihood/1/fs2000_estimation_exact.mod
@@ -81,5 +81,5 @@ varobs gp_obs gy_obs;
 options_.solve_tolf = 1e-12;
 
 tic
-estimation(order=1,datafile='../../fsdat_simul',nobs=192,mode_compute=4,loglinear,mh_replic=5000,mh_nblocks=2,mh_jscale=0.8);
+estimation(order=1,datafile='../../fsdat_simul',nobs=192,silent_optimizer,mode_compute=4,loglinear,mh_replic=5000,mh_nblocks=2,mh_jscale=0.8);
 toc
diff --git a/tests/estimation/fs2000.mod b/tests/estimation/fs2000.mod
index 13f686415..071d047b6 100644
--- a/tests/estimation/fs2000.mod
+++ b/tests/estimation/fs2000.mod
@@ -82,7 +82,7 @@ varobs gp_obs gy_obs;
 
 options_.solve_tolf = 1e-12;
 
-estimation(order=1,datafile=fsdat_simul,nobs=192,loglinear,mh_replic=3000,mh_nblocks=1,mh_jscale=0.8,moments_varendo,selected_variables_only,contemporaneous_correlation,smoother,forecast=8,
+estimation(order=1,silent_optimizer,datafile=fsdat_simul,nobs=192,loglinear,mh_replic=3000,mh_nblocks=1,mh_jscale=0.8,moments_varendo,selected_variables_only,contemporaneous_correlation,smoother,forecast=8,
         geweke_interval = [0.19 0.49],
         taper_steps = [4 7 15],
         raftery_lewis_diagnostics,
diff --git a/tests/estimation/fs2000_MCMC_jumping_covariance.mod b/tests/estimation/fs2000_MCMC_jumping_covariance.mod
index f8f8ac0a1..774411c9d 100644
--- a/tests/estimation/fs2000_MCMC_jumping_covariance.mod
+++ b/tests/estimation/fs2000_MCMC_jumping_covariance.mod
@@ -82,13 +82,13 @@ varobs gp_obs gy_obs;
 options_.solve_tolf = 1e-12;
 options_.mode_compute=4;
 options_.plot_priors=0;
-estimation(order=1,datafile=fsdat_simul,nobs=192,loglinear,mh_replic=1000,mh_nblocks=1,mh_jscale=0.8,mcmc_jumping_covariance=hessian);
+estimation(order=1,silent_optimizer,datafile=fsdat_simul,nobs=192,loglinear,mh_replic=1000,mh_nblocks=1,mh_jscale=0.8,mcmc_jumping_covariance=hessian);
 
 load('fs2000_MCMC_jumping_covariance/Output/fs2000_MCMC_jumping_covariance_mode','hh');
 jumping_covariance=diag(diag(hh));
 save('test_matrix.mat','jumping_covariance');
 
-estimation(order=1,datafile=fsdat_simul,nobs=192,loglinear,mh_replic=1000,mh_nblocks=1,mh_jscale=0.01,mcmc_jumping_covariance=prior_variance);
-estimation(order=1,datafile=fsdat_simul,nobs=192,loglinear,mh_replic=1000,mh_nblocks=1,mh_jscale=0.0001,mcmc_jumping_covariance=identity_matrix);
+estimation(order=1,silent_optimizer,datafile=fsdat_simul,nobs=192,loglinear,mh_replic=1000,mh_nblocks=1,mh_jscale=0.01,mcmc_jumping_covariance=prior_variance);
+estimation(order=1,silent_optimizer,datafile=fsdat_simul,nobs=192,loglinear,mh_replic=1000,mh_nblocks=1,mh_jscale=0.0001,mcmc_jumping_covariance=identity_matrix);
 
-estimation(order=1,datafile=fsdat_simul,nobs=192,loglinear,mh_replic=1000,mh_nblocks=1,mh_jscale=0.8,mcmc_jumping_covariance='test_matrix');
+estimation(order=1,silent_optimizer,datafile=fsdat_simul,nobs=192,loglinear,mh_replic=1000,mh_nblocks=1,mh_jscale=0.8,mcmc_jumping_covariance='test_matrix');
diff --git a/tests/estimation/fs2000_calibrated_covariance.mod b/tests/estimation/fs2000_calibrated_covariance.mod
index a2acc3387..f8cf47edb 100644
--- a/tests/estimation/fs2000_calibrated_covariance.mod
+++ b/tests/estimation/fs2000_calibrated_covariance.mod
@@ -80,7 +80,7 @@ corr e_a, e_m, 0.5;
 stderr gp_obs, 0.5;
 end;
 
-estimation(order=1,datafile=fsdat_simul,nobs=192, loglinear, mh_replic=0, mh_nblocks=1, mh_jscale=0.8,moments_varendo,consider_all_endogenous);
+estimation(order=1,datafile=fsdat_simul,nobs=192,silent_optimizer, loglinear, mh_replic=0, mh_nblocks=1, mh_jscale=0.8,moments_varendo,consider_all_endogenous);
 
 if isequal(M_.Sigma_e(2,1),5e-5) || isequal(M_.Sigma_e(1,2),5e-5)
     error('Problem in overriding calibrated covariance of structural shocks by estimated correlation')
diff --git a/tests/estimation/fs2000_estimated_params_remove.mod b/tests/estimation/fs2000_estimated_params_remove.mod
index a65ddccc9..4d9cb18a7 100644
--- a/tests/estimation/fs2000_estimated_params_remove.mod
+++ b/tests/estimation/fs2000_estimated_params_remove.mod
@@ -94,7 +94,7 @@ varobs gp_obs gy_obs;
 
 options_.solve_tolf = 1e-12;
 
-estimation(order=1,datafile=fsdat_simul,nobs=192,loglinear,mh_replic=0) y m;
+estimation(order=1,datafile=fsdat_simul,nobs=192,silent_optimizer,loglinear,mh_replic=0) y m;
 
 if size(estim_params_.var_exo, 1) ~= 2 || size(estim_params_.param_vals, 1) ~= 7 ...
    || size(estim_params_.var_endo, 1) ~= 0 || size(estim_params_.corrn, 1) ~= 0 ...
diff --git a/tests/estimation/fs2000_fast.mod b/tests/estimation/fs2000_fast.mod
index 37c7f4dde..fededc5b4 100644
--- a/tests/estimation/fs2000_fast.mod
+++ b/tests/estimation/fs2000_fast.mod
@@ -85,4 +85,4 @@ options_.solve_tolf = 1e-12;
 estimation(order=1,datafile=fsdat_simul,nobs=192,loglinear,mh_replic=3000,
            fast_kalman_filter,mh_nblocks=2,mh_jscale=0.8,moments_varendo,
            selected_variables_only,contemporaneous_correlation,
-           smoother,forecast=8) y m;
+           smoother,forecast=8,silent_optimizer) y m;
diff --git a/tests/estimation/fs2000_initialize_from_calib.mod b/tests/estimation/fs2000_initialize_from_calib.mod
index 643c4866d..c9cc45371 100644
--- a/tests/estimation/fs2000_initialize_from_calib.mod
+++ b/tests/estimation/fs2000_initialize_from_calib.mod
@@ -100,4 +100,4 @@ del, 0.020000;
 end;
 
 options_.plot_priors=0;
-estimation(order=1, datafile=fsdat_simul, nobs=192, loglinear, mh_replic=2000, mh_nblocks=1, mh_jscale=0.8,prior_trunc=0);
+estimation(order=1, datafile=fsdat_simul, silent_optimizer, nobs=192, loglinear, mh_replic=2000, mh_nblocks=1, mh_jscale=0.8,prior_trunc=0);
diff --git a/tests/estimation/fs2000_model_comparison.mod b/tests/estimation/fs2000_model_comparison.mod
index 372604a1f..26de29704 100644
--- a/tests/estimation/fs2000_model_comparison.mod
+++ b/tests/estimation/fs2000_model_comparison.mod
@@ -81,7 +81,7 @@ end;
 varobs gp_obs gy_obs;
 
 options_.solve_tolf = 1e-12;
-estimation(order=1,datafile=fsdat_simul,nobs=192,loglinear,mh_replic=2000,mh_nblocks=1,mh_jscale=0.8,tex);
+estimation(order=1,datafile=fsdat_simul,silent_optimizer,nobs=192,loglinear,mh_replic=2000,mh_nblocks=1,mh_jscale=0.8,tex);
 
 
 model_comparison fs2000(0.5) fs2000_calibrated_covariance(0.5);
diff --git a/tests/estimation/fs2000_with_weibull_prior.mod b/tests/estimation/fs2000_with_weibull_prior.mod
index 4ccce1212..e8a8ed132 100644
--- a/tests/estimation/fs2000_with_weibull_prior.mod
+++ b/tests/estimation/fs2000_with_weibull_prior.mod
@@ -81,4 +81,4 @@ varobs gp_obs gy_obs;
 
 options_.solve_tolf = 1e-12;
 
-estimation(order=1,datafile=fsdat_simul,nobs=192,loglinear,mh_replic=2000,mh_nblocks=2,mh_jscale=0.8,moments_varendo,consider_only_observed);
+estimation(order=1,datafile=fsdat_simul,nobs=192,silent_optimizer,loglinear,mh_replic=2000,mh_nblocks=2,mh_jscale=0.8,moments_varendo,consider_only_observed);
diff --git a/tests/estimation/heteroskedastic_shocks/fs2000_het.mod b/tests/estimation/heteroskedastic_shocks/fs2000_het.mod
index a0974c92c..32728313c 100644
--- a/tests/estimation/heteroskedastic_shocks/fs2000_het.mod
+++ b/tests/estimation/heteroskedastic_shocks/fs2000_het.mod
@@ -27,7 +27,7 @@ heteroskedastic_shocks;
   scales 0;
 end;
 
-estimation(order=1,datafile='../fsdat_simul',nobs=192,mode_compute=5,loglinear,mh_replic=0,smoother,filtered_vars,forecast=8,filter_step_ahead=[1:8],consider_all_endogenous,heteroskedastic_filter);
+estimation(order=1,datafile='../fsdat_simul',nobs=192,silent_optimizer,mode_compute=5,loglinear,mh_replic=0,smoother,filtered_vars,forecast=8,filter_step_ahead=[1:8],consider_all_endogenous,heteroskedastic_filter);
 
 @#define mode_file_name="'fs2000_het/Output/fs2000_het_mode'"
 @#include "fs2000_het_check.inc"
diff --git a/tests/estimation/heteroskedastic_shocks/fs2000_het_corr.mod b/tests/estimation/heteroskedastic_shocks/fs2000_het_corr.mod
index dae222e46..cbbe6b85b 100644
--- a/tests/estimation/heteroskedastic_shocks/fs2000_het_corr.mod
+++ b/tests/estimation/heteroskedastic_shocks/fs2000_het_corr.mod
@@ -31,7 +31,7 @@ heteroskedastic_shocks;
   scales 0;
 end;
 
-estimation(order=1,datafile='../fsdat_simul',nobs=192,mode_compute=5,loglinear,mh_replic=0,smoother,filtered_vars,forecast=8,filter_step_ahead=[1:8],consider_all_endogenous,heteroskedastic_filter);
+estimation(order=1,datafile='../fsdat_simul',nobs=192,mode_compute=5,silent_optimizer,loglinear,mh_replic=0,smoother,filtered_vars,forecast=8,filter_step_ahead=[1:8],consider_all_endogenous,heteroskedastic_filter);
 
 @#define mode_file_name="'fs2000_het_corr/Output/fs2000_het_corr_mode'"
 @#include "fs2000_het_check.inc" 
diff --git a/tests/estimation/heteroskedastic_shocks/fs2000_het_sample_restriction.mod b/tests/estimation/heteroskedastic_shocks/fs2000_het_sample_restriction.mod
index d0c6509b3..47ec2de2e 100644
--- a/tests/estimation/heteroskedastic_shocks/fs2000_het_sample_restriction.mod
+++ b/tests/estimation/heteroskedastic_shocks/fs2000_het_sample_restriction.mod
@@ -27,7 +27,7 @@ heteroskedastic_shocks;
   scales 0;
 end;
 
-estimation(order=1,datafile='../fsdat_simul',first_obs=10,nobs=182,mode_compute=5,loglinear,mh_replic=0,smoother,filtered_vars,forecast=8,filter_step_ahead=[1:8],consider_all_endogenous,heteroskedastic_filter);
+estimation(order=1,datafile='../fsdat_simul',first_obs=10,nobs=182,silent_optimizer,mode_compute=5,loglinear,mh_replic=0,smoother,filtered_vars,forecast=8,filter_step_ahead=[1:8],consider_all_endogenous,heteroskedastic_filter);
 
 if M_.heteroskedastic_shocks.Qscale(strmatch('e_a',M_.exo_names,'exact'),91)~=0 && M_.heteroskedastic_shocks.Qscale(strmatch('e_b',M_.exo_names,'exact'),91)~=0.01
     error('first_obs is incorrectly handled.')
diff --git a/tests/estimation/independent_mh/fs2000_independent_mh.mod b/tests/estimation/independent_mh/fs2000_independent_mh.mod
index 2f5d03425..0848ea77b 100644
--- a/tests/estimation/independent_mh/fs2000_independent_mh.mod
+++ b/tests/estimation/independent_mh/fs2000_independent_mh.mod
@@ -82,5 +82,5 @@ varobs gp_obs gy_obs;
 
 options_.solve_tolf = 1e-12;
 
-estimation(order=1,datafile='../fsdat_simul',nobs=192,loglinear,mh_replic=3000,
+estimation(order=1,datafile='../fsdat_simul',silent_optimizer,nobs=192,loglinear,mh_replic=3000,
         mh_nblocks=1,posterior_sampling_method='independent_metropolis_hastings',mh_jscale=0.8) y m;
diff --git a/tests/estimation/ls2003_endog_prior_restrict_estimation.mod b/tests/estimation/ls2003_endog_prior_restrict_estimation.mod
index 901ac60d4..34b04f2b0 100644
--- a/tests/estimation/ls2003_endog_prior_restrict_estimation.mod
+++ b/tests/estimation/ls2003_endog_prior_restrict_estimation.mod
@@ -81,5 +81,5 @@ y_obs,pie_obs(@{ilag}), -; //[ccf]
 @#endfor
 end;
 
-estimation(datafile='../gsa/data_ca1.m',mode_check,first_obs=8,nobs=79,mh_nblocks=1,
+estimation(datafile='../gsa/data_ca1.m',silent_optimizer,mode_check,first_obs=8,nobs=79,mh_nblocks=1,
   prefilter=1,mh_jscale=0.0005,mh_replic=5000, mode_compute=4, mh_drop=0.6, bayesian_irf,mcmc_jumping_covariance='identity_matrix') R_obs y;
diff --git a/tests/estimation/method_of_moments/AFVRR/AFVRR_M0.mod b/tests/estimation/method_of_moments/AFVRR/AFVRR_M0.mod
index 93e175da7..88bb95a00 100644
--- a/tests/estimation/method_of_moments/AFVRR/AFVRR_M0.mod
+++ b/tests/estimation/method_of_moments/AFVRR/AFVRR_M0.mod
@@ -295,7 +295,7 @@ method_of_moments(
                    ,'UseParallel' , 1
                    %,'Jacobian' , 'on'
                   )    % a list of NAME and VALUE pairs to set options for the optimization routines. Available options depend on mode_compute
-        %, silent_optimizer                  % run minimization of moments distance silently without displaying results or saving files in between
+        , silent_optimizer                  % run minimization of moments distance silently without displaying results or saving files in between
         %, analytic_standard_errors
         , se_tolx=1e-10
 );
diff --git a/tests/estimation/method_of_moments/AFVRR/AFVRR_MFB.mod b/tests/estimation/method_of_moments/AFVRR/AFVRR_MFB.mod
index 1de461adb..0faacd04a 100644
--- a/tests/estimation/method_of_moments/AFVRR/AFVRR_MFB.mod
+++ b/tests/estimation/method_of_moments/AFVRR/AFVRR_MFB.mod
@@ -296,7 +296,7 @@ method_of_moments(
                    ,'UseParallel' , 1
                    %,'Jacobian' , 'on'
                   )    % a list of NAME and VALUE pairs to set options for the optimization routines. Available options depend on mode_compute
-        %, silent_optimizer                  % run minimization of moments distance silently without displaying results or saving files in between
+        , silent_optimizer                  % run minimization of moments distance silently without displaying results or saving files in between
         %, analytic_standard_errors
         , se_tolx=1e-10
 );
diff --git a/tests/estimation/method_of_moments/AFVRR/AFVRR_MFB_RRA.mod b/tests/estimation/method_of_moments/AFVRR/AFVRR_MFB_RRA.mod
index c04cf9712..e8d0a97a4 100644
--- a/tests/estimation/method_of_moments/AFVRR/AFVRR_MFB_RRA.mod
+++ b/tests/estimation/method_of_moments/AFVRR/AFVRR_MFB_RRA.mod
@@ -295,7 +295,7 @@ method_of_moments(
                    ,'UseParallel' , 1
                    %,'Jacobian' , 'on'
                   )    % a list of NAME and VALUE pairs to set options for the optimization routines. Available options depend on mode_compute
-        %, silent_optimizer                  % run minimization of moments distance silently without displaying results or saving files in between
+        , silent_optimizer                  % run minimization of moments distance silently without displaying results or saving files in between
         %, analytic_standard_errors
         , se_tolx=1e-10
 );
diff --git a/tests/estimation/method_of_moments/AnScho/AnScho_MoM_common.inc b/tests/estimation/method_of_moments/AnScho/AnScho_MoM_common.inc
index dc2eb4971..cd0d1f06a 100644
--- a/tests/estimation/method_of_moments/AnScho/AnScho_MoM_common.inc
+++ b/tests/estimation/method_of_moments/AnScho/AnScho_MoM_common.inc
@@ -256,7 +256,7 @@ method_of_moments(
     %           ,'UseParallel' , 1        % when true (and supported by optimizer) solver estimates gradients in parallel (using Matlab/Octave's parallel toolbox)
     %           ,'Jacobian'    , 'off'    % when 'off' gradient-based solvers approximate Jacobian using finite differences; for GMM we can also pass the analytical Jacobian to gradient-based solvers by setting this 'on'
               )
-    %, silent_optimizer                    % run minimization of moments distance silently without displaying results or saving files in between
+    , silent_optimizer                    % run minimization of moments distance silently without displaying results or saving files in between
 
 % Numerical algorithms options
     % , aim_solver                             % Use AIM algorithm to compute perturbation approximation
diff --git a/tests/estimation/method_of_moments/RBC/RBC_MoM_Andreasen.mod b/tests/estimation/method_of_moments/RBC/RBC_MoM_Andreasen.mod
index e8af3f66a..7441e12f0 100644
--- a/tests/estimation/method_of_moments/RBC/RBC_MoM_Andreasen.mod
+++ b/tests/estimation/method_of_moments/RBC/RBC_MoM_Andreasen.mod
@@ -205,7 +205,7 @@ method_of_moments(
         %           ,'UseParallel' , 1        % when true (and supported by optimizer) solver estimates gradients in parallel (using Matlab/Octave's parallel toolbox)
         %           ,'Jacobian'    , 'off'    % when 'off' gradient-based solvers approximate Jacobian using finite differences; for GMM we can also pass the analytical Jacobian to gradient-based solvers by setting this 'on'
                   )                         
-        % , silent_optimizer                  % run minimization of moments distance silently without displaying results or saving files in between
+        , silent_optimizer                  % run minimization of moments distance silently without displaying results or saving files in between
 
     % Numerical algorithms options
         % , aim_solver                             % Use AIM algorithm to compute perturbation approximation
diff --git a/tests/estimation/method_of_moments/RBC/RBC_MoM_SMM_ME.mod b/tests/estimation/method_of_moments/RBC/RBC_MoM_SMM_ME.mod
index d8e6077de..df46d56fe 100644
--- a/tests/estimation/method_of_moments/RBC/RBC_MoM_SMM_ME.mod
+++ b/tests/estimation/method_of_moments/RBC/RBC_MoM_SMM_ME.mod
@@ -192,7 +192,7 @@ end
         %           ,'UseParallel' , 1        % when true (and supported by optimizer) solver estimates gradients in parallel (using Matlab/Octave's parallel toolbox)
         %           ,'Jacobian'    , 'off'    % when 'off' gradient-based solvers approximate Jacobian using finite differences; for GMM we can also pass the analytical Jacobian to gradient-based solvers by setting this 'on'
         %           )                         
-        % , silent_optimizer                  % run minimization of moments distance silently without displaying results or saving files in between
+        , silent_optimizer                  % run minimization of moments distance silently without displaying results or saving files in between
 
     % Numerical algorithms options
         % , aim_solver                             % Use AIM algorithm to compute perturbation approximation
diff --git a/tests/estimation/method_of_moments/RBC/RBC_MoM_optimizer.mod b/tests/estimation/method_of_moments/RBC/RBC_MoM_optimizer.mod
index 85f5ec095..db0a3ff17 100644
--- a/tests/estimation/method_of_moments/RBC/RBC_MoM_optimizer.mod
+++ b/tests/estimation/method_of_moments/RBC/RBC_MoM_optimizer.mod
@@ -142,7 +142,7 @@ options_.solveopt.TolXConstraint=1e-3;
                   ,'MaxFunEvals' , 1D3        % maximum number of function evaluations allowed, a positive integer
                   )
         @#endif
-        %, silent_optimizer                  % run minimization of moments distance silently without displaying results or saving files in between
+        , silent_optimizer                  % run minimization of moments distance silently without displaying results or saving files in between
     );
     
         @#if estimParams == 2 && optimizer == 13
diff --git a/tests/estimation/method_of_moments/RBC/RBC_MoM_prefilter.mod b/tests/estimation/method_of_moments/RBC/RBC_MoM_prefilter.mod
index 6bc36f3d4..7b1fc4758 100644
--- a/tests/estimation/method_of_moments/RBC/RBC_MoM_prefilter.mod
+++ b/tests/estimation/method_of_moments/RBC/RBC_MoM_prefilter.mod
@@ -164,7 +164,7 @@ save('test_matrix.mat','weighting_matrix')
         %           ,'UseParallel' , 1        % when true (and supported by optimizer) solver estimates gradients in parallel (using Matlab/Octave's parallel toolbox)
         %           ,'Jacobian'    , 'off'    % when 'off' gradient-based solvers approximate Jacobian using finite differences; for GMM we can also pass the analytical Jacobian to gradient-based solvers by setting this 'on'
         %           )                         
-        % , silent_optimizer                  % run minimization of moments distance silently without displaying results or saving files in between
+        , silent_optimizer                  % run minimization of moments distance silently without displaying results or saving files in between
 
     % Numerical algorithms options
         % , aim_solver                             % Use AIM algorithm to compute perturbation approximation
diff --git a/tests/estimation/no_init_estimation_check_first_obs/fs2000_init_check.mod b/tests/estimation/no_init_estimation_check_first_obs/fs2000_init_check.mod
index a95f006fe..95503aabc 100644
--- a/tests/estimation/no_init_estimation_check_first_obs/fs2000_init_check.mod
+++ b/tests/estimation/no_init_estimation_check_first_obs/fs2000_init_check.mod
@@ -71,4 +71,4 @@ end;
 varobs gp_obs gy_obs k;
 
 options_.solve_tolf = 1e-12;
-estimation(order=1,datafile=fsdat_mat,nobs=192,loglinear,mh_replic=0,use_univariate_filters_if_singularity_is_detected=0, smoother, consider_all_endogenous, no_init_estimation_check_first_obs);
+estimation(order=1,datafile=fsdat_mat,nobs=192,silent_optimizer,loglinear,mh_replic=0,use_univariate_filters_if_singularity_is_detected=0, smoother, consider_all_endogenous, no_init_estimation_check_first_obs);
diff --git a/tests/estimation/slice/fs2000_slice.mod b/tests/estimation/slice/fs2000_slice.mod
index db47758e4..f50a1ec4e 100644
--- a/tests/estimation/slice/fs2000_slice.mod
+++ b/tests/estimation/slice/fs2000_slice.mod
@@ -80,11 +80,11 @@ end;
 varobs gp_obs gy_obs;
 
 //options_.posterior_sampling_method = 'slice';
-estimation(order=1,datafile='../fsdat_simul',nobs=192,loglinear,mh_replic=50,mh_nblocks=2,mh_drop=0.2, //mode_compute=0,cova_compute=0,
+estimation(order=1,datafile='../fsdat_simul',nobs=192,silent_optimizer,loglinear,mh_replic=50,mh_nblocks=2,mh_drop=0.2, //mode_compute=0,cova_compute=0,
 posterior_sampling_method='slice'
 );
 // continue with rotated slice
-estimation(order=1,datafile='../fsdat_simul',nobs=192,loglinear,mh_replic=100,mh_nblocks=2,mh_drop=0.5,load_mh_file,//mode_compute=0,
+estimation(order=1,datafile='../fsdat_simul',silent_optimizer,nobs=192,loglinear,mh_replic=100,mh_nblocks=2,mh_drop=0.5,load_mh_file,//mode_compute=0,
 posterior_sampling_method='slice',
 posterior_sampler_options=('rotated',1,'use_mh_covariance_matrix',1)
 );
diff --git a/tests/estimation/system_prior_restriction/Gali_2015.mod b/tests/estimation/system_prior_restriction/Gali_2015.mod
index 007a4db24..acbcb2286 100644
--- a/tests/estimation/system_prior_restriction/Gali_2015.mod
+++ b/tests/estimation/system_prior_restriction/Gali_2015.mod
@@ -160,7 +160,7 @@ title('Prior')
 
 % Run estimation with 1 observation to show effect of _prior_restriction .m
 % on independent prior
-estimation(datafile='sim_data',mode_compute=5,mh_replic=2001,mh_nblocks=1,diffuse_filter,nobs=1,mh_jscale=0.8);
+estimation(datafile='sim_data',silent_optimizer,mode_compute=5,mh_replic=2001,mh_nblocks=1,diffuse_filter,nobs=1,mh_jscale=0.8);
 posterior_function(function='Gali_2015_PC_slope');
 PC_slope_vec=cell2mat(oo_.posterior_function_results(:,1));
 optimal_bandwidth = mh_optimal_bandwidth(PC_slope_vec,length(PC_slope_vec),0,'gaussian');
@@ -172,7 +172,7 @@ title('Updated Prior')
 
 
 % Run estimation with full observations
-estimation(datafile='sim_data',mode_compute=5,mh_replic=2001,mh_nblocks=1,diffuse_filter,nobs=100,mh_jscale=0.8);
+estimation(datafile='sim_data',silent_optimizer,mode_compute=5,mh_replic=2001,mh_nblocks=1,diffuse_filter,nobs=100,mh_jscale=0.8);
 
 posterior_function(function='Gali_2015_PC_slope');
 PC_slope_vec=cell2mat(oo_.posterior_function_results(:,1));
diff --git a/tests/estimation/t_proposal/fs2000_student.mod b/tests/estimation/t_proposal/fs2000_student.mod
index dec351f84..c3a7fb30a 100644
--- a/tests/estimation/t_proposal/fs2000_student.mod
+++ b/tests/estimation/t_proposal/fs2000_student.mod
@@ -114,9 +114,9 @@ end;
 
 varobs gp_obs gy_obs;
 
-estimation(order=1, datafile='../fsdat_simul',nobs=192, loglinear, mh_replic=2002, mh_nblocks=2, mh_jscale=0.8,mode_compute=4,
+estimation(order=1, datafile='../fsdat_simul',nobs=192, silent_optimizer,loglinear, mh_replic=2002, mh_nblocks=2, mh_jscale=0.8,mode_compute=4,
 posterior_sampler_options=('proposal_distribution','rand_multivariate_student','student_degrees_of_freedom',5,'save_tmp_file',0));
 
-estimation(order=1, datafile='../fsdat_simul',nobs=192, loglinear, mh_replic=30, mh_nblocks=1, mh_jscale=0.8,mode_compute=4,
+estimation(order=1, datafile='../fsdat_simul',nobs=192, silent_optimizer,loglinear, mh_replic=30, mh_nblocks=1, mh_jscale=0.8,mode_compute=4,
 posterior_sampling_method='tailored_random_block_metropolis_hastings',
 posterior_sampler_options=('proposal_distribution','rand_multivariate_student','student_degrees_of_freedom',5,'save_tmp_file',0));
diff --git a/tests/estimation/tune_mh_jscale/fs2000.mod b/tests/estimation/tune_mh_jscale/fs2000.mod
index 9dacfed62..1c13930f3 100644
--- a/tests/estimation/tune_mh_jscale/fs2000.mod
+++ b/tests/estimation/tune_mh_jscale/fs2000.mod
@@ -19,7 +19,7 @@
 
 @#include "fs2000.inc"
 
-estimation(order=1, datafile='../fsdat_simul', nobs=192, loglinear, mh_replic=10000, mh_nblocks=1, mh_tune_jscale=0.33,mh_tune_guess=0.7,plot_priors=0);
+estimation(order=1, datafile='../fsdat_simul', nobs=192,silent_optimizer, loglinear, mh_replic=10000, mh_nblocks=1, mh_tune_jscale=0.33,mh_tune_guess=0.7,plot_priors=0);
 
 mhdata = load('fs2000/metropolis/fs2000_mh_history_0.mat');
 
diff --git a/tests/filter_step_ahead/fs2000_filter_step_ahead_ML.mod b/tests/filter_step_ahead/fs2000_filter_step_ahead_ML.mod
index 270a0a150..5b1971013 100644
--- a/tests/filter_step_ahead/fs2000_filter_step_ahead_ML.mod
+++ b/tests/filter_step_ahead/fs2000_filter_step_ahead_ML.mod
@@ -108,7 +108,7 @@ end;
 
 varobs gp_obs gy_obs;
 
-estimation(order=1, datafile='../fs2000/fsdat_simul', nobs=192, loglinear, filter_step_ahead = [1 4 8 12], forecast=20,smoother,filtered_vars) m P c;
+estimation(order=1, datafile='../fs2000/fsdat_simul', nobs=192, silent_optimizer, loglinear, filter_step_ahead = [1 4 8 12], forecast=20,smoother,filtered_vars) m P c;
 
 
 /*
diff --git a/tests/filter_step_ahead/fs2000_filter_step_ahead_bayesian.mod b/tests/filter_step_ahead/fs2000_filter_step_ahead_bayesian.mod
index 687bb22a6..f022f4b5b 100644
--- a/tests/filter_step_ahead/fs2000_filter_step_ahead_bayesian.mod
+++ b/tests/filter_step_ahead/fs2000_filter_step_ahead_bayesian.mod
@@ -114,7 +114,7 @@ end;
 
 varobs gp_obs gy_obs;
 
-estimation(order=1, datafile='../fs2000/fsdat_simul', nobs=192, loglinear, mh_replic=2000, mh_nblocks=1, mh_jscale=0.8,filter_step_ahead = [1 4 8 12], forecast=20,smoother,filtered_vars) m P c;
+estimation(order=1, datafile='../fs2000/fsdat_simul', silent_optimizer,nobs=192, loglinear, mh_replic=2000, mh_nblocks=1, mh_jscale=0.8,filter_step_ahead = [1 4 8 12], forecast=20,smoother,filtered_vars) m P c;
 
 
 /*
diff --git a/tests/filter_step_ahead/trend_cycle_decomposition.mod b/tests/filter_step_ahead/trend_cycle_decomposition.mod
index 178dd0ed5..478f03231 100644
--- a/tests/filter_step_ahead/trend_cycle_decomposition.mod
+++ b/tests/filter_step_ahead/trend_cycle_decomposition.mod
@@ -31,4 +31,4 @@ end;
 
 varobs y; 
 
-estimation(datafile=trend_cycle_decomposition_data,nobs=82, mh_replic=2000, mode_compute=4, mh_nblocks=1, mh_jscale=0.3, filtered_vars, smoother, diffuse_filter) yp z; 
+estimation(datafile=trend_cycle_decomposition_data,nobs=82, silent_optimizer,mh_replic=2000, mode_compute=4, mh_nblocks=1, mh_jscale=0.3, filtered_vars, smoother, diffuse_filter) yp z; 
diff --git a/tests/fs2000/fs2000.mod b/tests/fs2000/fs2000.mod
index 469f12f05..7b910faeb 100644
--- a/tests/fs2000/fs2000.mod
+++ b/tests/fs2000/fs2000.mod
@@ -72,5 +72,5 @@ varobs gp_obs gy_obs;
 
 options_.solve_tolf = 1e-12;
 
-estimation(order=1,datafile=fsdat_simul,nobs=192,loglinear,mh_replic=2000,mh_nblocks=2,mh_jscale=0.8,moments_varendo,consider_only_observed);
+estimation(order=1,datafile=fsdat_simul,nobs=192,silent_optimizer,loglinear,mh_replic=2000,mh_nblocks=2,mh_jscale=0.8,moments_varendo,consider_only_observed);
 calib_smoother(parameter_set=posterior_mean) y;
\ No newline at end of file
diff --git a/tests/fs2000/fs2000_data.mod b/tests/fs2000/fs2000_data.mod
index 7560b042b..470471aa3 100644
--- a/tests/fs2000/fs2000_data.mod
+++ b/tests/fs2000/fs2000_data.mod
@@ -86,4 +86,4 @@ set_time(1970Q3); // Interpreted as the first date available in the sample loade
 
 data(file='fsdat_simul.m',first_obs=1971Q1, nobs=40);
 
-estimation(order=1,nobs=192,loglinear,mh_replic=2000,mh_nblocks=2,mh_jscale=0.8);
+estimation(order=1,silent_optimizer,nobs=192,loglinear,mh_replic=2000,mh_nblocks=2,mh_jscale=0.8);
diff --git a/tests/fs2000/fs2000_dseries_a.mod b/tests/fs2000/fs2000_dseries_a.mod
index 95a0a819c..3f771fa75 100644
--- a/tests/fs2000/fs2000_dseries_a.mod
+++ b/tests/fs2000/fs2000_dseries_a.mod
@@ -84,4 +84,4 @@ options_.solve_tolf = 1e-12;
 
 data(file=fsdat_simul_dseries,first_obs=1950Q3, nobs=192);
 
-estimation(order=1,loglinear,mh_replic=2000,mh_nblocks=2,mh_jscale=0.8);
+estimation(order=1,silent_optimizer,loglinear,mh_replic=2000,mh_nblocks=2,mh_jscale=0.8);
diff --git a/tests/fs2000/fs2000_dseries_b.mod b/tests/fs2000/fs2000_dseries_b.mod
index 632dee8f0..80fe8ff95 100644
--- a/tests/fs2000/fs2000_dseries_b.mod
+++ b/tests/fs2000/fs2000_dseries_b.mod
@@ -87,4 +87,4 @@ fsdataset = fsdataset(1950Q3:1950Q3+191);
 
 data(series=fsdataset);
 
-estimation(order=1,loglinear,mh_replic=2000,mh_nblocks=2,mh_jscale=0.8);
+estimation(order=1,silent_optimizer,loglinear,mh_replic=2000,mh_nblocks=2,mh_jscale=0.8);
diff --git a/tests/fs2000/fs2000_missing_data.mod b/tests/fs2000/fs2000_missing_data.mod
index 9e2d7cb06..237267433 100644
--- a/tests/fs2000/fs2000_missing_data.mod
+++ b/tests/fs2000/fs2000_missing_data.mod
@@ -80,7 +80,7 @@ end;
 
 varobs gp_obs gy_obs;
 
-estimation(order=1, datafile=fsdat_simul_missing_obs, nobs=192, loglinear, mh_replic=2000, mh_nblocks=2, mh_jscale=0.8);
+estimation(order=1, datafile=fsdat_simul_missing_obs,silent_optimizer, nobs=192, loglinear, mh_replic=2000, mh_nblocks=2, mh_jscale=0.8);
 
 
 /*
diff --git a/tests/fs2000/fs2000_particle.mod b/tests/fs2000/fs2000_particle.mod
index c2a2bb4fd..fd1a17e43 100644
--- a/tests/fs2000/fs2000_particle.mod
+++ b/tests/fs2000/fs2000_particle.mod
@@ -83,4 +83,4 @@ options_.solve_tolf = 1e-12;
 
 /* Not computing the mode because it is very expensive, just running a small MH */
 
-estimation(order=2,mode_compute=7,datafile=fsdat_simul,nobs=192);
+estimation(order=2,mode_compute=7,silent_optimizer,datafile=fsdat_simul,nobs=192);
diff --git a/tests/fs2000/fs2000_sd.mod b/tests/fs2000/fs2000_sd.mod
index c6d79db70..81b83f2cc 100644
--- a/tests/fs2000/fs2000_sd.mod
+++ b/tests/fs2000/fs2000_sd.mod
@@ -81,6 +81,6 @@ varobs gp_obs gy_obs;
 
 options_.solve_tolf = 1e-12;
 
-estimation(order=1,datafile=fsdat_simul,nobs=192,loglinear,mh_replic=0);
+estimation(order=1,datafile=fsdat_simul,nobs=192,loglinear,mh_replic=0,silent_optimizer);
 
 shock_decomposition(parameter_set=posterior_mode) gp_obs, gy_obs;
\ No newline at end of file
diff --git a/tests/fs2000/fs2000a.mod b/tests/fs2000/fs2000a.mod
index 3d4f2006d..5c7f44367 100644
--- a/tests/fs2000/fs2000a.mod
+++ b/tests/fs2000/fs2000a.mod
@@ -89,7 +89,7 @@ Y_obs (gam);
 end;
 
 estimation(order=1,datafile=fsdat_simul,nobs=192,loglinear,mh_replic=2000,
-           mode_compute=4,mh_nblocks=2,mh_drop=0.45,mh_jscale=0.65,diffuse_filter);
+           mode_compute=4,silent_optimizer,mh_nblocks=2,mh_drop=0.45,mh_jscale=0.65,diffuse_filter);
 
 //stoch_simul(order=1, periods=200);
 //datatomfile('fsdat_simul2', {'gy_obs'; 'gp_obs'; 'Y_obs'; 'P_obs'});
diff --git a/tests/gradient/fs2000_numgrad_13.mod b/tests/gradient/fs2000_numgrad_13.mod
index 6e3d49007..1c60db4de 100644
--- a/tests/gradient/fs2000_numgrad_13.mod
+++ b/tests/gradient/fs2000_numgrad_13.mod
@@ -79,4 +79,4 @@ varobs gp_obs gy_obs;
 
 options_.solve_tolf = 1e-12;
 
-estimation(order=1,datafile='../fs2000/fsdat_simul',nobs=192,loglinear,mh_replic=0,optim=('NumgradAlgorithm',13));
+estimation(order=1,datafile='../fs2000/fsdat_simul',silent_optimizer,nobs=192,loglinear,mh_replic=0,optim=('NumgradAlgorithm',13));
diff --git a/tests/gradient/fs2000_numgrad_15.mod b/tests/gradient/fs2000_numgrad_15.mod
index 0d7dbb2f1..b11c7e45c 100644
--- a/tests/gradient/fs2000_numgrad_15.mod
+++ b/tests/gradient/fs2000_numgrad_15.mod
@@ -79,4 +79,4 @@ varobs gp_obs gy_obs;
 
 options_.solve_tolf = 1e-12;
 
-estimation(order=1,datafile='../fs2000/fsdat_simul',nobs=192,loglinear,mh_replic=0,optim=('NumgradAlgorithm',15));
+estimation(order=1,datafile='../fs2000/fsdat_simul',silent_optimizer,nobs=192,loglinear,mh_replic=0,optim=('NumgradAlgorithm',15));
diff --git a/tests/gradient/fs2000_numgrad_2.mod b/tests/gradient/fs2000_numgrad_2.mod
index 2021a9b9a..192ff28a5 100644
--- a/tests/gradient/fs2000_numgrad_2.mod
+++ b/tests/gradient/fs2000_numgrad_2.mod
@@ -79,4 +79,4 @@ varobs gp_obs gy_obs;
 
 options_.solve_tolf = 1e-12;
 
-estimation(order=1,datafile='../fs2000/fsdat_simul',nobs=192,loglinear,mh_replic=0,optim=('NumgradAlgorithm',2));
+estimation(order=1,datafile='../fs2000/fsdat_simul',silent_optimizer,nobs=192,loglinear,mh_replic=0,optim=('NumgradAlgorithm',2));
diff --git a/tests/gradient/fs2000_numgrad_3.mod b/tests/gradient/fs2000_numgrad_3.mod
index 30f72c31c..d4f5b68cc 100644
--- a/tests/gradient/fs2000_numgrad_3.mod
+++ b/tests/gradient/fs2000_numgrad_3.mod
@@ -79,4 +79,4 @@ varobs gp_obs gy_obs;
 
 options_.solve_tolf = 1e-12;
 
-estimation(order=1,datafile='../fs2000/fsdat_simul',nobs=192,loglinear,mh_replic=0,optim=('NumgradAlgorithm',3));
+estimation(order=1,datafile='../fs2000/fsdat_simul',silent_optimizer,nobs=192,loglinear,mh_replic=0,optim=('NumgradAlgorithm',3));
diff --git a/tests/gradient/fs2000_numgrad_5.mod b/tests/gradient/fs2000_numgrad_5.mod
index a78f41674..0ed45d09a 100644
--- a/tests/gradient/fs2000_numgrad_5.mod
+++ b/tests/gradient/fs2000_numgrad_5.mod
@@ -79,4 +79,4 @@ varobs gp_obs gy_obs;
 
 options_.solve_tolf = 1e-12;
 
-estimation(order=1,datafile='../fs2000/fsdat_simul',nobs=192,loglinear,mh_replic=0,optim=('NumgradAlgorithm',5));
+estimation(order=1,datafile='../fs2000/fsdat_simul',silent_optimizer,nobs=192,loglinear,mh_replic=0,optim=('NumgradAlgorithm',5));
diff --git a/tests/gsa/ls2003.mod b/tests/gsa/ls2003.mod
index d4a56b4d5..47b806e34 100644
--- a/tests/gsa/ls2003.mod
+++ b/tests/gsa/ls2003.mod
@@ -146,7 +146,7 @@ disp('Press ENTER to continue'); pause(5);
 
 // run this to generate posterior mode and Metropolis files if not yet done
 estimation(datafile='data_ca1.m',first_obs=8,nobs=79,mh_nblocks=1,
-   prefilter=1,mh_jscale=0.5,mh_replic=5000, mode_compute=4, mh_drop=0.6, nodisplay,
+   prefilter=1,mh_jscale=0.5,mh_replic=5000,silent_optimizer, mode_compute=4, mh_drop=0.6, nodisplay,
    bayesian_irf, filtered_vars, smoother) y_obs R_obs pie_obs dq de;
 
 
diff --git a/tests/kalman/block/fs2000.mod b/tests/kalman/block/fs2000.mod
index 8c20bd649..dc9de8005 100644
--- a/tests/kalman/block/fs2000.mod
+++ b/tests/kalman/block/fs2000.mod
@@ -81,4 +81,4 @@ varobs gp_obs gy_obs;
 
 options_.solve_tolf = 1e-12;
 
-estimation(order=1,datafile='../../fs2000/fsdat_simul',nobs=192,mh_replic=0,mh_nblocks=1,mh_jscale=0.8,consider_only_observed);
\ No newline at end of file
+estimation(order=1,datafile='../../fs2000/fsdat_simul',silent_optimizer,nobs=192,mh_replic=0,mh_nblocks=1,mh_jscale=0.8,consider_only_observed);
\ No newline at end of file
diff --git a/tests/kalman/block/fs2000_missing_data.mod b/tests/kalman/block/fs2000_missing_data.mod
index 993bc4591..5a1c8c97f 100644
--- a/tests/kalman/block/fs2000_missing_data.mod
+++ b/tests/kalman/block/fs2000_missing_data.mod
@@ -80,4 +80,4 @@ end;
 
 varobs gp_obs gy_obs;
 
-estimation(order=1, datafile='../../fs2000/fsdat_simul_missing_obs', nobs=192, mh_replic=0, mh_nblocks=1, mh_jscale=0.8);
\ No newline at end of file
+estimation(order=1, datafile='../../fs2000/fsdat_simul_missing_obs',silent_optimizer, nobs=192, mh_replic=0, mh_nblocks=1, mh_jscale=0.8);
\ No newline at end of file
diff --git a/tests/kalman/likelihood_from_dynare/fs2000_estimation_check.inc b/tests/kalman/likelihood_from_dynare/fs2000_estimation_check.inc
index 0cef5554b..9c38cf3f8 100644
--- a/tests/kalman/likelihood_from_dynare/fs2000_estimation_check.inc
+++ b/tests/kalman/likelihood_from_dynare/fs2000_estimation_check.inc
@@ -1,6 +1,6 @@
 %%default
 options_.lik_init=1;
-estimation(kalman_algo=0,mode_compute=4,order=1,datafile=@{data_file_name},smoother,filter_decomposition,forecast = 8,filtered_vars,filter_step_ahead=[1,3],irf=20) m P c e W R k d y gy_obs;
+estimation(kalman_algo=0,silent_optimizer,mode_compute=4,order=1,datafile=@{data_file_name},smoother,filter_decomposition,forecast = 8,filtered_vars,filter_step_ahead=[1,3],irf=20) m P c e W R k d y gy_obs;
 fval_algo_0=oo_.likelihood_at_initial_parameters;
 %%Multivariate Kalman Filter
 options_.lik_init=1;
diff --git a/tests/kalman/likelihood_from_dynare/fs2000ns_estimation_check.inc b/tests/kalman/likelihood_from_dynare/fs2000ns_estimation_check.inc
index c89016583..8044208dc 100644
--- a/tests/kalman/likelihood_from_dynare/fs2000ns_estimation_check.inc
+++ b/tests/kalman/likelihood_from_dynare/fs2000ns_estimation_check.inc
@@ -1,5 +1,5 @@
 %%get mode
-estimation(diffuse_filter,kalman_algo=3,mode_compute=4,order=1,datafile=@{data_file_name},smoother,filter_decomposition,forecast = 8,filtered_vars,filter_step_ahead=[1,3],irf=20) m P c e W R k d y gy_obs;
+estimation(diffuse_filter,kalman_algo=3,silent_optimizer,mode_compute=4,order=1,datafile=@{data_file_name},smoother,filter_decomposition,forecast = 8,filtered_vars,filter_step_ahead=[1,3],irf=20) m P c e W R k d y gy_obs;
 fval_algo_0=oo_.likelihood_at_initial_parameters;
 
 %%Diffuse Multivariate Kalman Filter
diff --git a/tests/kalman/lyapunov/fs2000_lyap.mod b/tests/kalman/lyapunov/fs2000_lyap.mod
index 9a70d534b..09a523ec2 100644
--- a/tests/kalman/lyapunov/fs2000_lyap.mod
+++ b/tests/kalman/lyapunov/fs2000_lyap.mod
@@ -120,17 +120,17 @@ options_.lyapunov_fp = 0;
 options_.lyapunov_db = 0;
 options_.lyapunov_srs = 0;
 
-estimation(lyapunov=doubling,order=1,datafile='../../fs2000/fsdat_simul', nobs=192, loglinear, mh_replic=0, mh_nblocks=1, mh_jscale=0.8,nograph);
+estimation(lyapunov=doubling,order=1,datafile='../../fs2000/fsdat_simul',silent_optimizer, nobs=192, loglinear, mh_replic=0, mh_nblocks=1, mh_jscale=0.8,nograph);
 
 
 if (isoctave && user_has_octave_forge_package('control')) || (~isoctave && user_has_matlab_license('control_toolbox'))
     options_.lyapunov_fp = 0;
     options_.lyapunov_db = 0;
     options_.lyapunov_srs = 0;
-    estimation(lyapunov=square_root_solver,order=1,datafile='../../fs2000/fsdat_simul', nobs=192, loglinear, mh_replic=0, mh_nblocks=1, mh_jscale=0.8,nograph);
+    estimation(lyapunov=square_root_solver,order=1,datafile='../../fs2000/fsdat_simul',silent_optimizer, nobs=192, loglinear, mh_replic=0, mh_nblocks=1, mh_jscale=0.8,nograph);
 end
 
 options_.lyapunov_fp = 0;
 options_.lyapunov_db = 0;
 options_.lyapunov_srs = 0;
-estimation(lyapunov=fixed_point,order=1,datafile='../../fs2000/fsdat_simul', nobs=192, loglinear, mh_replic=0, mh_nblocks=1, mh_jscale=0.8,nograph);
\ No newline at end of file
+estimation(lyapunov=fixed_point,order=1,datafile='../../fs2000/fsdat_simul',silent_optimizer, nobs=192, loglinear, mh_replic=0, mh_nblocks=1, mh_jscale=0.8,nograph);
\ No newline at end of file
diff --git a/tests/kalman_filter_smoother/algo1.mod b/tests/kalman_filter_smoother/algo1.mod
index 7cbaf4eb8..38528b9cf 100644
--- a/tests/kalman_filter_smoother/algo1.mod
+++ b/tests/kalman_filter_smoother/algo1.mod
@@ -32,7 +32,7 @@ end;
 
 varobs dw dx dy z;
 
-estimation(datafile=data_algo,first_obs=1000,nobs=200,mh_replic=0,filtered_vars,smoothed_state_uncertainty);
+estimation(datafile=data_algo,silent_optimizer,first_obs=1000,nobs=200,mh_replic=0,filtered_vars,smoothed_state_uncertainty);
 
 //checking smoother consistency
 X = oo_.SmoothedVariables;
diff --git a/tests/kalman_filter_smoother/algo3.mod b/tests/kalman_filter_smoother/algo3.mod
index 9aa866252..6df16724b 100644
--- a/tests/kalman_filter_smoother/algo3.mod
+++ b/tests/kalman_filter_smoother/algo3.mod
@@ -35,7 +35,7 @@ end;
 
 varobs w x y;
 
-estimation(datafile=data_algo,first_obs=1000,nobs=200,mh_replic=0,diffuse_filter,filtered_vars,smoothed_state_uncertainty);
+estimation(datafile=data_algo,first_obs=1000,silent_optimizer,nobs=200,mh_replic=0,diffuse_filter,filtered_vars,smoothed_state_uncertainty);
 
 //checking smoother consistency
 X = oo_.SmoothedVariables;
diff --git a/tests/kalman_filter_smoother/algo4a.mod b/tests/kalman_filter_smoother/algo4a.mod
index 0ee94e30f..606157dbf 100644
--- a/tests/kalman_filter_smoother/algo4a.mod
+++ b/tests/kalman_filter_smoother/algo4a.mod
@@ -33,7 +33,7 @@ end;
 
 varobs dw dx y z;
        
-estimation(datafile=data_algo,first_obs=1000,nobs=200,mh_replic=0,diffuse_filter);
+estimation(datafile=data_algo,silent_optimizer,first_obs=1000,nobs=200,mh_replic=0,diffuse_filter);
 //estimation(datafile=data_algo,first_obs=1000,nobs=200,mh_replic=0,mode_compute=0,mode_file='algo3/Output/algo3_mode',diffuse_filter);
 
 //checking smoother consistency
diff --git a/tests/kalman_filter_smoother/algo4b.mod b/tests/kalman_filter_smoother/algo4b.mod
index 568484afe..ea07bd92c 100644
--- a/tests/kalman_filter_smoother/algo4b.mod
+++ b/tests/kalman_filter_smoother/algo4b.mod
@@ -33,7 +33,7 @@ end;
 
 varobs dw dx y z;
        
-estimation(datafile=data_algo,first_obs=1000,nobs=200,mh_replic=0,diffuse_filter,smoothed_state_uncertainty);
+estimation(datafile=data_algo,first_obs=1000,silent_optimizer,nobs=200,mh_replic=0,diffuse_filter,smoothed_state_uncertainty);
 //estimation(datafile=data_algo,first_obs=1000,nobs=200,mh_replic=0,mode_compute=0,mode_file='algo3/Output/algo3_mode',diffuse_filter);
 
 //checking smoother consistency
diff --git a/tests/kalman_filter_smoother/algoH1.mod b/tests/kalman_filter_smoother/algoH1.mod
index 7a852b979..f239f1b33 100644
--- a/tests/kalman_filter_smoother/algoH1.mod
+++ b/tests/kalman_filter_smoother/algoH1.mod
@@ -34,7 +34,7 @@ end;
 
 varobs dw dx dy z;
        
-estimation(datafile=data_algo,first_obs=1000,nobs=200,mh_replic=0,filtered_vars,smoothed_state_uncertainty);
+estimation(datafile=data_algo,first_obs=1000,silent_optimizer,nobs=200,mh_replic=0,filtered_vars,smoothed_state_uncertainty);
 
 //checking smoother consistency
 X = oo_.SmoothedVariables;
diff --git a/tests/kalman_filter_smoother/algoH3.mod b/tests/kalman_filter_smoother/algoH3.mod
index b25dce072..424ad3e90 100644
--- a/tests/kalman_filter_smoother/algoH3.mod
+++ b/tests/kalman_filter_smoother/algoH3.mod
@@ -37,7 +37,7 @@ end;
 
 varobs w x y;
        
-estimation(datafile=data_algo,first_obs=1000,nobs=200,mh_replic=0,diffuse_filter,smoothed_state_uncertainty);
+estimation(datafile=data_algo,first_obs=1000,silent_optimizer,nobs=200,mh_replic=0,diffuse_filter,smoothed_state_uncertainty);
 
 stoch_simul(irf=0);
 
diff --git a/tests/kalman_filter_smoother/check_variable_dimensions/fs2000.mod b/tests/kalman_filter_smoother/check_variable_dimensions/fs2000.mod
index 760c4cc91..4c82eb6ca 100644
--- a/tests/kalman_filter_smoother/check_variable_dimensions/fs2000.mod
+++ b/tests/kalman_filter_smoother/check_variable_dimensions/fs2000.mod
@@ -115,7 +115,7 @@ end;
 
 varobs gp_obs gy_obs;
 
-estimation(order=1,datafile='../fsdat_simul', nobs=192, loglinear, mh_replic=2000, mh_nblocks=1, mh_jscale=0.8,forecast=8,smoother,filtered_vars,filter_step_ahead=[1:2],filter_decomposition)  m P c e W R k d y gy_obs;
+estimation(order=1,datafile='../fsdat_simul', silent_optimizer,nobs=192, loglinear, mh_replic=2000, mh_nblocks=1, mh_jscale=0.8,forecast=8,smoother,filtered_vars,filter_step_ahead=[1:2],filter_decomposition)  m P c e W R k d y gy_obs;
 
 if size(oo_.PointForecast.deciles.gy_obs,1)~=9
     error('Number of deciles must be 9')
diff --git a/tests/kalman_filter_smoother/check_variable_dimensions/fs2000_ML.mod b/tests/kalman_filter_smoother/check_variable_dimensions/fs2000_ML.mod
index f36bec7b0..64d636f29 100644
--- a/tests/kalman_filter_smoother/check_variable_dimensions/fs2000_ML.mod
+++ b/tests/kalman_filter_smoother/check_variable_dimensions/fs2000_ML.mod
@@ -116,7 +116,7 @@ corr e_m, e_a, 0;
 stderr gp_obs, 0.01;
 end;
 options_.prior_trunc=0;
-estimation(order=1,datafile='../fsdat_simul', nobs=192, loglinear, moments_varendo,conditional_variance_decomposition=[1,3],forecast=8,smoother,filter_covariance,filtered_vars,filter_step_ahead=[1,2,4],filter_decomposition,selected_variables_only)  m P c e W R k d y gy_obs gp_obs;
+estimation(order=1,datafile='../fsdat_simul', nobs=192, silent_optimizer,loglinear, moments_varendo,conditional_variance_decomposition=[1,3],forecast=8,smoother,filter_covariance,filtered_vars,filter_step_ahead=[1,2,4],filter_decomposition,selected_variables_only)  m P c e W R k d y gy_obs gp_obs;
 
 
 if size(oo_.FilteredVariablesKStepAhead,3)~=(options_.nobs+max(options_.filter_step_ahead)) || ...
diff --git a/tests/kalman_filter_smoother/compare_results_simulation/fs2000.mod b/tests/kalman_filter_smoother/compare_results_simulation/fs2000.mod
index ac9acc7e8..b4c2af6df 100644
--- a/tests/kalman_filter_smoother/compare_results_simulation/fs2000.mod
+++ b/tests/kalman_filter_smoother/compare_results_simulation/fs2000.mod
@@ -114,7 +114,7 @@ end;
 
 varobs gp_obs gy_obs;
 
-estimation(order=1,datafile=fsdat_simul_logged,consider_all_endogenous,nobs=192,mh_replic=2000, mh_nblocks=1,smoother, mh_jscale=0.8);
+estimation(order=1,datafile=fsdat_simul_logged, silent_optimizer,consider_all_endogenous,nobs=192,mh_replic=2000, mh_nblocks=1,smoother, mh_jscale=0.8);
 
 ex_=[];
 for shock_iter=1:M_.exo_nbr
diff --git a/tests/kalman_filter_smoother/compare_results_simulation/fs2000_ML.mod b/tests/kalman_filter_smoother/compare_results_simulation/fs2000_ML.mod
index 4f92baa83..9cdffa0e8 100644
--- a/tests/kalman_filter_smoother/compare_results_simulation/fs2000_ML.mod
+++ b/tests/kalman_filter_smoother/compare_results_simulation/fs2000_ML.mod
@@ -114,7 +114,7 @@ stderr e_a, 0.035449;
 stderr e_m, 0.008862;
 end;
 
-estimation(order=1,datafile='fsdat_simul_logged', nobs=192, forecast=8,smoother,filtered_vars,filter_step_ahead=[1,2,4],filter_decomposition,selected_variables_only)  m P c e W R k d y gy_obs;
+estimation(order=1,datafile='fsdat_simul_logged', nobs=192, forecast=8, silent_optimizer, smoother,filtered_vars,filter_step_ahead=[1,2,4],filter_decomposition,selected_variables_only)  m P c e W R k d y gy_obs;
 
 % write shock matrix
 ex_=[];
diff --git a/tests/kalman_filter_smoother/compare_results_simulation/fs2000_ML_loglinear.mod b/tests/kalman_filter_smoother/compare_results_simulation/fs2000_ML_loglinear.mod
index 53c3881fa..17e44c8a3 100644
--- a/tests/kalman_filter_smoother/compare_results_simulation/fs2000_ML_loglinear.mod
+++ b/tests/kalman_filter_smoother/compare_results_simulation/fs2000_ML_loglinear.mod
@@ -113,8 +113,8 @@ del,  0.02;
 stderr e_a, 0.035449;
 stderr e_m, 0.008862;
 end;
-
-estimation(order=1,datafile='../fsdat_simul',loglinear, nobs=192, forecast=8,smoother,filtered_vars,filter_step_ahead=[1,2,4],filter_decomposition,selected_variables_only)  m P c e W R k d y gy_obs;
+warning('off','MATLAB:nearlySingularMatrix')
+estimation(order=1,datafile='../fsdat_simul',silent_optimizer,loglinear, nobs=192, forecast=8,smoother,filtered_vars,filter_step_ahead=[1,2,4],filter_decomposition,selected_variables_only)  m P c e W R k d y gy_obs;
 
 % write shock matrix
 ex_=[];
diff --git a/tests/kalman_filter_smoother/compare_results_simulation/fs2000_loglinear.mod b/tests/kalman_filter_smoother/compare_results_simulation/fs2000_loglinear.mod
index f30d9d3fc..7e507835f 100644
--- a/tests/kalman_filter_smoother/compare_results_simulation/fs2000_loglinear.mod
+++ b/tests/kalman_filter_smoother/compare_results_simulation/fs2000_loglinear.mod
@@ -131,7 +131,7 @@ end;
 
 varobs gp_obs gy_obs;
 
-estimation(order=1, datafile='../fsdat_simul', nobs=192, loglinear, mh_replic=2000, mh_nblocks=1,smoother, mh_jscale=0.8,consider_all_endogenous);
+estimation(order=1, datafile='../fsdat_simul', nobs=192, silent_optimizer, loglinear, mh_replic=2000, mh_nblocks=1,smoother, mh_jscale=0.8,consider_all_endogenous);
 
 ex_=[];
 for shock_iter=1:M_.exo_nbr
diff --git a/tests/kalman_filter_smoother/fs2000.mod b/tests/kalman_filter_smoother/fs2000.mod
index 0d0837824..220ad7abd 100644
--- a/tests/kalman_filter_smoother/fs2000.mod
+++ b/tests/kalman_filter_smoother/fs2000.mod
@@ -79,5 +79,5 @@ end;
 
 varobs gp_obs gy_obs;
 
-//estimation(order=1,datafile=fsdat_simul,nobs=192,loglinear,mh_replic=2000,mh_nblocks=2,mh_jscale=0.8,mode_check);
+//estimation(order=1,datafile=fsdat_simul,nobs=192,silent_optimizer,loglinear,mh_replic=2000,mh_nblocks=2,mh_jscale=0.8,mode_check);
 estimation(order=1,datafile=fsdat_simul,nobs=192,loglinear,mh_replic=0,mode_compute=0);
diff --git a/tests/kalman_filter_smoother/fs2000a.mod b/tests/kalman_filter_smoother/fs2000a.mod
index 2c28ab028..8ea7a68a0 100644
--- a/tests/kalman_filter_smoother/fs2000a.mod
+++ b/tests/kalman_filter_smoother/fs2000a.mod
@@ -89,6 +89,6 @@ P_obs (log(mst)-gam);
 Y_obs (gam);
 end;
 
-estimation(order=1,datafile=fsdat_simul,nobs=192,loglinear,mh_replic=0,
+estimation(order=1,datafile=fsdat_simul,nobs=192,silent_optimizer,loglinear,mh_replic=0,
            mode_compute=4,mh_nblocks=2,mh_drop=0.45,mh_jscale=0.65,diffuse_filter,smoother,forecast=10) P_obs gp_obs gy_obs;
 
diff --git a/tests/kalman_initial_state/fs2000_kalman_initial.mod b/tests/kalman_initial_state/fs2000_kalman_initial.mod
index 65a153af2..07d79555e 100644
--- a/tests/kalman_initial_state/fs2000_kalman_initial.mod
+++ b/tests/kalman_initial_state/fs2000_kalman_initial.mod
@@ -22,4 +22,4 @@ P(0)=2.5258;
 m(0) = mst;
 end;
 
-estimation(order=1,datafile='../fs2000/fsdat_simul',nobs=192,loglinear,mh_replic=2001,mh_nblocks=1,mh_jscale=0.8,moments_varendo,consider_only_observed,smoother);
+estimation(order=1,datafile='../fs2000/fsdat_simul',silent_optimizer,nobs=192,loglinear,mh_replic=2001,mh_nblocks=1,mh_jscale=0.8,moments_varendo,consider_only_observed,smoother);
diff --git a/tests/kalman_initial_state/fs2000_kalman_initial_2_lag.mod b/tests/kalman_initial_state/fs2000_kalman_initial_2_lag.mod
index 622ec2651..0d32f4cd8 100644
--- a/tests/kalman_initial_state/fs2000_kalman_initial_2_lag.mod
+++ b/tests/kalman_initial_state/fs2000_kalman_initial_2_lag.mod
@@ -84,4 +84,4 @@ P(0)=2.5258;
 m(-1) = mst;
 end;
 
-estimation(order=1,datafile='../fs2000/fsdat_simul',nobs=192,loglinear,mh_replic=2001,mh_nblocks=1,mh_jscale=0.8,moments_varendo,consider_only_observed,smoother);
+estimation(order=1,datafile='../fs2000/fsdat_simul',silent_optimizer,nobs=192,loglinear,mh_replic=2001,mh_nblocks=1,mh_jscale=0.8,moments_varendo,consider_only_observed,smoother);
diff --git a/tests/measurement_errors/fs2000_corr_me_ml_mcmc/fs2000_corr_ME.mod b/tests/measurement_errors/fs2000_corr_me_ml_mcmc/fs2000_corr_ME.mod
index 67ec377da..1af4aa4eb 100644
--- a/tests/measurement_errors/fs2000_corr_me_ml_mcmc/fs2000_corr_ME.mod
+++ b/tests/measurement_errors/fs2000_corr_me_ml_mcmc/fs2000_corr_ME.mod
@@ -111,8 +111,9 @@ stderr gp_obs, 1;
 stderr gy_obs, 1;
 corr gp_obs, gy_obs,0;
 end;
+warning('off','MATLAB:nearlySingularMatrix')
 
-estimation(order=1,datafile=fsdat_simul,mode_check,smoother,filter_decomposition,forecast = 8,filtered_vars,filter_step_ahead=[1,3],irf=20,tex) m P c e W R k d y gy_obs;
+estimation(order=1,datafile=fsdat_simul,silent_optimizer,prior_trunc=0,mode_check,smoother,filter_decomposition,forecast = 8,filtered_vars,filter_step_ahead=[1,3],irf=20,tex) m P c e W R k d y gy_obs;
 
 
 
@@ -128,6 +129,6 @@ stderr gp_obs, inv_gamma_pdf, 0.001, inf;
 //corr gp_obs, gy_obs,normal_pdf, 0, 0.2;
 end;
 
-estimation(mode_compute=5,order=1,datafile=fsdat_simul,mode_check,smoother,filter_decomposition,mh_replic=2000, mh_nblocks=1, mh_jscale=0.8,forecast = 8,bayesian_irf,filtered_vars,filter_step_ahead=[1,3],irf=20) m P c e W R k d y;
+estimation(mode_compute=5,silent_optimizer,order=1,datafile=fsdat_simul,mode_check,smoother,filter_decomposition,mh_replic=2000, mh_nblocks=1, mh_jscale=0.8,forecast = 8,bayesian_irf,filtered_vars,filter_step_ahead=[1,3],irf=20) m P c e W R k d y;
 shock_decomposition y W R;
 //identification(advanced=1,max_dim_cova_group=3,prior_mc=250);
diff --git a/tests/minimal_state_space_system/sw_minimal.mod b/tests/minimal_state_space_system/sw_minimal.mod
index cd4eacfe3..585e851f3 100644
--- a/tests/minimal_state_space_system/sw_minimal.mod
+++ b/tests/minimal_state_space_system/sw_minimal.mod
@@ -422,8 +422,8 @@ Sigmay_full = SS.C*Sigmax_full*SS.C' + SS.D*M_.Sigma_e*SS.D';
 Sigmax_min = lyapunov_symm(minSS.A, minSS.B*M_.Sigma_e*minSS.B', options_.lyapunov_fixed_point_tol, options_.qz_criterium, options_.lyapunov_complex_threshold, 1, options_.debug);
 Sigmay_min = minSS.C*Sigmax_min*minSS.C' + minSS.D*M_.Sigma_e*minSS.D';
 
-([Sigmay_full(:) - Sigmay_min(:)]')
-sqrt(([diag(Sigmay_full), diag(Sigmay_min)]'))
+([Sigmay_full(:) - Sigmay_min(:)]');
+sqrt(([diag(Sigmay_full), diag(Sigmay_min)]'));
 dx = norm( Sigmay_full - Sigmay_min, Inf);
 if dx > 3e-8
     error(sprintf('something wrong with minimal state space computations, as numerical error is %d',dx))
diff --git a/tests/moments/fs2000_post_moments.mod b/tests/moments/fs2000_post_moments.mod
index c1947c641..561f4d61e 100644
--- a/tests/moments/fs2000_post_moments.mod
+++ b/tests/moments/fs2000_post_moments.mod
@@ -122,7 +122,7 @@ end;
 
 varobs gp_obs gy_obs;
 
-estimation(order=1,mode_compute=5, datafile='../fs2000/fsdat_simul.m', nobs=192, loglinear, mh_replic=20, mh_nblocks=1, mh_jscale=0.8,moments_varendo,
+estimation(order=1,mode_compute=5,silent_optimizer, datafile='../fs2000/fsdat_simul.m', nobs=192, loglinear, mh_replic=20, mh_nblocks=1, mh_jscale=0.8,moments_varendo,
 conditional_variance_decomposition=[2,2000],consider_all_endogenous,sub_draws=2);
 
 stoch_simul(order=1,conditional_variance_decomposition=[2,2000],noprint,nograph);
@@ -194,7 +194,7 @@ stderr e_m, inv_gamma_pdf, 0.008862, inf;
 stderr gp_obs, inv_gamma_pdf, 0.003, inf;
 end;
 
-estimation(order=1,mode_compute=5, datafile='../fs2000/fsdat_simul.m', nobs=192, loglinear, mh_replic=20, mh_nblocks=1, mh_jscale=0.8,moments_varendo,
+estimation(order=1,mode_compute=5,silent_optimizer, datafile='../fs2000/fsdat_simul.m', nobs=192, loglinear, mh_replic=20, mh_nblocks=1, mh_jscale=0.8,moments_varendo,
 conditional_variance_decomposition=[2,2000],consider_all_endogenous,sub_draws=2);
 
 stoch_simul(order=1,conditional_variance_decomposition=[2,2000],noprint,nograph);
diff --git a/tests/observation_trends_and_prefiltering/MCMC/Trend_loglin_no_prefilt_first_obs_MC.mod b/tests/observation_trends_and_prefiltering/MCMC/Trend_loglin_no_prefilt_first_obs_MC.mod
index 091dfc270..05f602b22 100644
--- a/tests/observation_trends_and_prefiltering/MCMC/Trend_loglin_no_prefilt_first_obs_MC.mod
+++ b/tests/observation_trends_and_prefiltering/MCMC/Trend_loglin_no_prefilt_first_obs_MC.mod
@@ -4,7 +4,7 @@ addpath('..');
 generate_trend_stationary_AR1(M_.fname);
 
 estimation(order=1,datafile='Trend_loglin_no_prefilt_first_obs_MC_Exp_AR1_trend_data_with_constant',mh_replic=400,
-    mode_compute=4,first_obs=1000,loglinear,smoother,forecast=100,prefilter=0,
+    mode_compute=4,silent_optimizer,first_obs=1000,loglinear,smoother,forecast=100,prefilter=0,
     mcmc_jumping_covariance='Trend_loglin_no_prefilt_first_obs_MC_MCMC_jump_covar',
     filtered_vars, filter_step_ahead = [1,2,4],
     mh_nblocks=1,mh_jscale=0.3,no_posterior_kernel_density) P_obs Y_obs junk2;
diff --git a/tests/observation_trends_and_prefiltering/MCMC/Trend_loglin_prefilt_first_obs_MC.mod b/tests/observation_trends_and_prefiltering/MCMC/Trend_loglin_prefilt_first_obs_MC.mod
index 775067c8e..c50534c9b 100644
--- a/tests/observation_trends_and_prefiltering/MCMC/Trend_loglin_prefilt_first_obs_MC.mod
+++ b/tests/observation_trends_and_prefiltering/MCMC/Trend_loglin_prefilt_first_obs_MC.mod
@@ -4,7 +4,7 @@ addpath('..');
 generate_trend_stationary_AR1(M_.fname);
 
 estimation(order=1,datafile='Trend_loglin_prefilt_first_obs_MC_Exp_AR1_trend_data_with_constant',mh_replic=400,
-    mode_compute=4,first_obs=1000,loglinear,smoother,forecast=100,prefilter=1,
+    mode_compute=4,silent_optimizer,first_obs=1000,loglinear,smoother,forecast=100,prefilter=1,
     mcmc_jumping_covariance='Trend_loglin_prefilt_first_obs_MC_MCMC_jump_covar_prefilter',
     filtered_vars, filter_step_ahead = [1,2,4],
     mh_nblocks=1,mh_jscale=1e-4,no_posterior_kernel_density) P_obs Y_obs junk2;
diff --git a/tests/observation_trends_and_prefiltering/MCMC/Trend_loglinear_no_prefilter_MC.mod b/tests/observation_trends_and_prefiltering/MCMC/Trend_loglinear_no_prefilter_MC.mod
index 9353109a5..03d99442f 100644
--- a/tests/observation_trends_and_prefiltering/MCMC/Trend_loglinear_no_prefilter_MC.mod
+++ b/tests/observation_trends_and_prefiltering/MCMC/Trend_loglinear_no_prefilter_MC.mod
@@ -4,7 +4,7 @@ addpath('..');
 generate_trend_stationary_AR1(M_.fname);
 
 estimation(order=1,datafile='Trend_loglinear_no_prefilter_MC_Exp_AR1_trend_data_with_constant',mh_replic=400,
-    mode_compute=4,first_obs=1,loglinear,diffuse_filter,smoother,forecast=100,prefilter=0,
+    mode_compute=4,silent_optimizer,first_obs=1,loglinear,diffuse_filter,smoother,forecast=100,prefilter=0,
     mcmc_jumping_covariance='Trend_loglinear_no_prefilter_MC_MCMC_jump_covar',
     filtered_vars, filter_step_ahead = [1,2,4],
     mh_nblocks=1,mh_jscale=0.3) P_obs Y_obs junk2;
diff --git a/tests/observation_trends_and_prefiltering/MCMC/Trend_loglinear_prefilter_MC.mod b/tests/observation_trends_and_prefiltering/MCMC/Trend_loglinear_prefilter_MC.mod
index 0ddcb3742..e74801bf0 100644
--- a/tests/observation_trends_and_prefiltering/MCMC/Trend_loglinear_prefilter_MC.mod
+++ b/tests/observation_trends_and_prefiltering/MCMC/Trend_loglinear_prefilter_MC.mod
@@ -4,7 +4,7 @@ addpath('..');
 generate_trend_stationary_AR1(M_.fname);
 
 estimation(order=1,datafile='Trend_loglinear_prefilter_MC_Exp_AR1_trend_data_with_constant',mh_replic=400,
-    mode_compute=4,first_obs=1,loglinear,smoother,forecast=100,prefilter=1,
+    mode_compute=4,silent_optimizer,first_obs=1,loglinear,smoother,forecast=100,prefilter=1,
     mcmc_jumping_covariance='Trend_loglinear_prefilter_MC_MCMC_jump_covar_prefilter',
     filtered_vars, filter_step_ahead = [1,2,4],
     mh_nblocks=1,mh_jscale=1e-4) P_obs Y_obs junk2;
diff --git a/tests/observation_trends_and_prefiltering/MCMC/Trend_no_prefilter_MC.mod b/tests/observation_trends_and_prefiltering/MCMC/Trend_no_prefilter_MC.mod
index 8cf321d72..9c89cf9e0 100644
--- a/tests/observation_trends_and_prefiltering/MCMC/Trend_no_prefilter_MC.mod
+++ b/tests/observation_trends_and_prefiltering/MCMC/Trend_no_prefilter_MC.mod
@@ -3,7 +3,7 @@
 addpath('..');
 generate_trend_stationary_AR1(M_.fname);
 
-estimation(order=1,datafile='Trend_no_prefilter_MC_AR1_trend_data_with_constant',mh_replic=400,
+estimation(order=1,datafile='Trend_no_prefilter_MC_AR1_trend_data_with_constant',mh_replic=400,silent_optimizer,
             mode_compute=4,first_obs=1,smoother,mh_nblocks=1,mh_jscale=0.3,
             filtered_vars, filter_step_ahead = [1,2,4],
             mcmc_jumping_covariance='Trend_no_prefilter_MC_MCMC_jump_covar',forecast=100,prefilter=0) P_obs Y_obs junk2;
diff --git a/tests/observation_trends_and_prefiltering/MCMC/Trend_no_prefilter_first_obs_MC.mod b/tests/observation_trends_and_prefiltering/MCMC/Trend_no_prefilter_first_obs_MC.mod
index 90a9a76cb..58fc82ad3 100644
--- a/tests/observation_trends_and_prefiltering/MCMC/Trend_no_prefilter_first_obs_MC.mod
+++ b/tests/observation_trends_and_prefiltering/MCMC/Trend_no_prefilter_first_obs_MC.mod
@@ -4,7 +4,7 @@ addpath('..');
 generate_trend_stationary_AR1(M_.fname);
 
 estimation(order=1,datafile='Trend_no_prefilter_first_obs_MC_AR1_trend_data_with_constant',
-        mh_replic=400,mode_compute=4,first_obs=1000,smoother,forecast=100,prefilter=0,
+        mh_replic=400,mode_compute=4,silent_optimizer,first_obs=1000,smoother,forecast=100,prefilter=0,
         mcmc_jumping_covariance='Trend_no_prefilter_first_obs_MC_MCMC_jump_covar',
         filtered_vars, filter_step_ahead = [1,2,4],
         mh_nblocks=1,mh_jscale=0.3,no_posterior_kernel_density) P_obs Y_obs junk2;
diff --git a/tests/observation_trends_and_prefiltering/MCMC/Trend_prefilter_MC.mod b/tests/observation_trends_and_prefiltering/MCMC/Trend_prefilter_MC.mod
index ba2f88b73..2153093ce 100644
--- a/tests/observation_trends_and_prefiltering/MCMC/Trend_prefilter_MC.mod
+++ b/tests/observation_trends_and_prefiltering/MCMC/Trend_prefilter_MC.mod
@@ -3,7 +3,7 @@
 addpath('..');
 generate_trend_stationary_AR1(M_.fname);
 
-estimation(order=1,datafile='Trend_prefilter_MC_AR1_trend_data_with_constant',mh_replic=400,mode_compute=4,
+estimation(order=1,datafile='Trend_prefilter_MC_AR1_trend_data_with_constant',mh_replic=400,mode_compute=4,silent_optimizer,
     first_obs=1,smoother,prefilter=1,
     mh_nblocks=1,mh_jscale=1e-4,
     filtered_vars, filter_step_ahead = [1,2,4],
diff --git a/tests/observation_trends_and_prefiltering/MCMC/Trend_prefilter_first_obs_MC.mod b/tests/observation_trends_and_prefiltering/MCMC/Trend_prefilter_first_obs_MC.mod
index 4cfef3cad..79668c576 100644
--- a/tests/observation_trends_and_prefiltering/MCMC/Trend_prefilter_first_obs_MC.mod
+++ b/tests/observation_trends_and_prefiltering/MCMC/Trend_prefilter_first_obs_MC.mod
@@ -3,7 +3,7 @@
 addpath('..');
 generate_trend_stationary_AR1(M_.fname);
 
-estimation(order=1,datafile='Trend_prefilter_first_obs_MC_AR1_trend_data_with_constant',mh_replic=400,mode_compute=4,
+estimation(order=1,datafile='Trend_prefilter_first_obs_MC_AR1_trend_data_with_constant',mh_replic=400,mode_compute=4,silent_optimizer,
         first_obs=1000,smoother,prefilter=1,
         mh_nblocks=1,mh_jscale=1e-4,
         filtered_vars, filter_step_ahead = [1,2,4],
diff --git a/tests/observation_trends_and_prefiltering/ML/Trend_loglinear_no_prefilter.mod b/tests/observation_trends_and_prefiltering/ML/Trend_loglinear_no_prefilter.mod
index b98e24e81..ebf562d46 100644
--- a/tests/observation_trends_and_prefiltering/ML/Trend_loglinear_no_prefilter.mod
+++ b/tests/observation_trends_and_prefiltering/ML/Trend_loglinear_no_prefilter.mod
@@ -3,7 +3,7 @@
 addpath('..');
 generate_trend_stationary_AR1(M_.fname);
 
-estimation(order=1,datafile='Trend_loglinear_no_prefilter_Exp_AR1_trend_data_with_constant',mh_replic=0,
+estimation(order=1,datafile='Trend_loglinear_no_prefilter_Exp_AR1_trend_data_with_constant',mh_replic=0,silent_optimizer,
     mode_compute=4,first_obs=1,
     filtered_vars, filter_step_ahead = [1,2,4],        
     loglinear,smoother,forecast=100,prefilter=0) P_obs Y_obs junk2;
diff --git a/tests/observation_trends_and_prefiltering/ML/Trend_loglinear_no_prefilter_first_obs.mod b/tests/observation_trends_and_prefiltering/ML/Trend_loglinear_no_prefilter_first_obs.mod
index 5451c7904..252ed1298 100644
--- a/tests/observation_trends_and_prefiltering/ML/Trend_loglinear_no_prefilter_first_obs.mod
+++ b/tests/observation_trends_and_prefiltering/ML/Trend_loglinear_no_prefilter_first_obs.mod
@@ -3,7 +3,7 @@
 addpath('..');
 generate_trend_stationary_AR1(M_.fname);
 
-estimation(order=1,datafile='Trend_loglinear_no_prefilter_first_obs_Exp_AR1_trend_data_with_constant',mh_replic=0,
+estimation(order=1,datafile='Trend_loglinear_no_prefilter_first_obs_Exp_AR1_trend_data_with_constant',mh_replic=0,silent_optimizer,
     mode_compute=4,first_obs=1000,
     filtered_vars, filter_step_ahead = [1,2,4],        
     loglinear,smoother,forecast=100,prefilter=0) P_obs Y_obs junk2;
diff --git a/tests/observation_trends_and_prefiltering/ML/Trend_loglinear_prefilter.mod b/tests/observation_trends_and_prefiltering/ML/Trend_loglinear_prefilter.mod
index 302c5eb32..18fee61eb 100644
--- a/tests/observation_trends_and_prefiltering/ML/Trend_loglinear_prefilter.mod
+++ b/tests/observation_trends_and_prefiltering/ML/Trend_loglinear_prefilter.mod
@@ -3,7 +3,7 @@
 addpath('..');
 generate_trend_stationary_AR1(M_.fname);
 
-estimation(order=1,datafile='Trend_loglinear_prefilter_Exp_AR1_trend_data_with_constant',mh_replic=0,mode_compute=4,
+estimation(order=1,datafile='Trend_loglinear_prefilter_Exp_AR1_trend_data_with_constant',mh_replic=0,mode_compute=4,silent_optimizer,
         first_obs=1,smoother,loglinear,
         filtered_vars, filter_step_ahead = [1,2,4],        
         forecast=100,prefilter=1) P_obs Y_obs junk2;
diff --git a/tests/observation_trends_and_prefiltering/ML/Trend_loglinear_prefilter_first_obs.mod b/tests/observation_trends_and_prefiltering/ML/Trend_loglinear_prefilter_first_obs.mod
index 9ae1f90bb..20a3a8340 100644
--- a/tests/observation_trends_and_prefiltering/ML/Trend_loglinear_prefilter_first_obs.mod
+++ b/tests/observation_trends_and_prefiltering/ML/Trend_loglinear_prefilter_first_obs.mod
@@ -3,7 +3,7 @@
 addpath('..');
 generate_trend_stationary_AR1(M_.fname);
 
-estimation(order=1,datafile='Trend_loglinear_prefilter_first_obs_Exp_AR1_trend_data_with_constant',mh_replic=0,mode_compute=4,
+estimation(order=1,datafile='Trend_loglinear_prefilter_first_obs_Exp_AR1_trend_data_with_constant',mh_replic=0,mode_compute=4,silent_optimizer,
         first_obs=1000,smoother,loglinear,
         filtered_vars, filter_step_ahead = [1,2,4],        
         forecast=100,prefilter=1) P_obs  Y_obs junk2;
diff --git a/tests/observation_trends_and_prefiltering/ML/Trend_no_prefilter.mod b/tests/observation_trends_and_prefiltering/ML/Trend_no_prefilter.mod
index 1e617af87..bfd9f14f4 100644
--- a/tests/observation_trends_and_prefiltering/ML/Trend_no_prefilter.mod
+++ b/tests/observation_trends_and_prefiltering/ML/Trend_no_prefilter.mod
@@ -3,7 +3,7 @@
 addpath('..');
 generate_trend_stationary_AR1(M_.fname);
 
-estimation(order=1,datafile='Trend_no_prefilter_AR1_trend_data_with_constant',mh_replic=0,
+estimation(order=1,datafile='Trend_no_prefilter_AR1_trend_data_with_constant',mh_replic=0,silent_optimizer,
         mode_compute=4,first_obs=1,
         filtered_vars, filter_step_ahead = [1,2,4],        
         diffuse_filter,smoother,forecast=100,prefilter=0) P_obs Y_obs junk2;
diff --git a/tests/observation_trends_and_prefiltering/ML/Trend_no_prefilter_first_obs.mod b/tests/observation_trends_and_prefiltering/ML/Trend_no_prefilter_first_obs.mod
index feab481a6..beeeab780 100644
--- a/tests/observation_trends_and_prefiltering/ML/Trend_no_prefilter_first_obs.mod
+++ b/tests/observation_trends_and_prefiltering/ML/Trend_no_prefilter_first_obs.mod
@@ -4,7 +4,7 @@ addpath('..');
 generate_trend_stationary_AR1(M_.fname);
 
 estimation(order=1,datafile='Trend_no_prefilter_first_obs_AR1_trend_data_with_constant',mh_replic=0,
-        mode_compute=4,first_obs=1000,
+        mode_compute=4,first_obs=1000,silent_optimizer,
         filtered_vars, filter_step_ahead = [1,2,4],        
         smoother,forecast=100,prefilter=0) P_obs Y_obs junk2;
 
diff --git a/tests/observation_trends_and_prefiltering/ML/Trend_no_prefilter_selected_var.mod b/tests/observation_trends_and_prefiltering/ML/Trend_no_prefilter_selected_var.mod
index 2a25030d0..1235df3b9 100644
--- a/tests/observation_trends_and_prefiltering/ML/Trend_no_prefilter_selected_var.mod
+++ b/tests/observation_trends_and_prefiltering/ML/Trend_no_prefilter_selected_var.mod
@@ -83,7 +83,7 @@ oo_.SmoothedShocks  = [];
 
 set_dynare_seed('default');
 estimation(order=1,datafile='Trend_no_prefilter_selected_var_AR1_trend_data_with_constant',mh_replic=0,
-        mode_compute=4,first_obs=1,nobs=1000,
+        mode_compute=4,first_obs=1,nobs=1000,silent_optimizer,
         filtered_vars, filter_step_ahead = [1,2,4],        
         diffuse_filter,smoother,forecast=0,filter_covariance,prefilter=0,filter_decomposition,selected_variables_only) P_obs Y_obs junk2;
 
diff --git a/tests/observation_trends_and_prefiltering/ML/Trend_prefilter.mod b/tests/observation_trends_and_prefiltering/ML/Trend_prefilter.mod
index e6a73210d..c9ee6f2f1 100644
--- a/tests/observation_trends_and_prefiltering/ML/Trend_prefilter.mod
+++ b/tests/observation_trends_and_prefiltering/ML/Trend_prefilter.mod
@@ -3,7 +3,7 @@
 addpath('..');
 generate_trend_stationary_AR1(M_.fname)
 
-estimation(order=1,datafile='Trend_prefilter_AR1_trend_data_with_constant',mh_replic=0,mode_compute=4,
+estimation(order=1,datafile='Trend_prefilter_AR1_trend_data_with_constant',mh_replic=0,mode_compute=4,silent_optimizer,
         first_obs=1,
         filtered_vars, filter_step_ahead = [1,2,4],        
         smoother,forecast=100,prefilter=1) P_obs Y_obs junk2;
diff --git a/tests/observation_trends_and_prefiltering/ML/Trend_prefilter_first_obs.mod b/tests/observation_trends_and_prefiltering/ML/Trend_prefilter_first_obs.mod
index f9fc52af2..14917cd04 100644
--- a/tests/observation_trends_and_prefiltering/ML/Trend_prefilter_first_obs.mod
+++ b/tests/observation_trends_and_prefiltering/ML/Trend_prefilter_first_obs.mod
@@ -4,7 +4,7 @@ addpath('..');
 generate_trend_stationary_AR1(M_.fname);
 
 estimation(order=1,datafile='Trend_prefilter_first_obs_AR1_trend_data_with_constant',
-    mh_replic=0,mode_compute=4,
+    mh_replic=0,mode_compute=4,silent_optimizer,
     filtered_vars, filter_step_ahead = [1,2,4],        
     first_obs=1000,diffuse_filter,smoother,forecast=100,prefilter=1) P_obs Y_obs junk2;
 
diff --git a/tests/optimal_policy/OSR/osr_example.mod b/tests/optimal_policy/OSR/osr_example.mod
index d0b3e61ea..26517502a 100644
--- a/tests/optimal_policy/OSR/osr_example.mod
+++ b/tests/optimal_policy/OSR/osr_example.mod
@@ -39,6 +39,6 @@ end;
 
 osr_params gammax0 gammac0 gamma_y_ gamma_inf_;
 
-osr;
-osr(analytic_derivation,opt_algo=4);
-osr(analytic_derivation,opt_algo=1,optim=('DerivativeCheck','on','FiniteDifferenceType','central'));
\ No newline at end of file
+osr(silent_optimizer);
+osr(analytic_derivation,opt_algo=4,silent_optimizer);
+osr(analytic_derivation,silent_optimizer,opt_algo=1,optim=('DerivativeCheck','on','FiniteDifferenceType','central'));
\ No newline at end of file
diff --git a/tests/optimal_policy/OSR/osr_example_obj_corr_non_stat_vars.mod b/tests/optimal_policy/OSR/osr_example_obj_corr_non_stat_vars.mod
index 4720a2566..adad843bb 100644
--- a/tests/optimal_policy/OSR/osr_example_obj_corr_non_stat_vars.mod
+++ b/tests/optimal_policy/OSR/osr_example_obj_corr_non_stat_vars.mod
@@ -583,7 +583,7 @@ ruleT_B_debt
 
 ;
 
-osr(irf=5,maxit=10000, nograph);
+osr(irf=5,maxit=10000, nograph, silent_optimizer,nofunctions);
 
 
 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
diff --git a/tests/optimal_policy/OSR/osr_example_objective_correctness.mod b/tests/optimal_policy/OSR/osr_example_objective_correctness.mod
index d35ca9fba..b6dc92cb3 100644
--- a/tests/optimal_policy/OSR/osr_example_objective_correctness.mod
+++ b/tests/optimal_policy/OSR/osr_example_objective_correctness.mod
@@ -77,7 +77,7 @@ dummy_var 1;
 y,inflation 1;
 end;
 
-osr;
+osr(silent_optimizer);
 %compute objective function manually
 objective=oo_.var(strmatch('y',M_.endo_names,'exact'),strmatch('y',M_.endo_names,'exact'))+oo_.var(strmatch('inflation',M_.endo_names,'exact'),strmatch('inflation',M_.endo_names,'exact'))+oo_.var(strmatch('dummy_var',M_.endo_names,'exact'),strmatch('dummy_var',M_.endo_names,'exact'))+1*oo_.var(strmatch('y',M_.endo_names,'exact'),strmatch('inflation',M_.endo_names,'exact'));
 if abs(oo_.osr.objective_function-objective)>1e-8
diff --git a/tests/optimal_policy/OSR/osr_example_param_bounds.mod b/tests/optimal_policy/OSR/osr_example_param_bounds.mod
index 8f1c595de..5d154a1a0 100644
--- a/tests/optimal_policy/OSR/osr_example_param_bounds.mod
+++ b/tests/optimal_policy/OSR/osr_example_param_bounds.mod
@@ -42,4 +42,4 @@ osr_params_bounds;
 gamma_inf_, 0, 2.5;
 end;
 
-osr(opt_algo=9);
+osr(opt_algo=9,silent_optimizer);
diff --git a/tests/optimal_policy/OSR/osr_obj_corr_algo_1.mod b/tests/optimal_policy/OSR/osr_obj_corr_algo_1.mod
index 2b8a30406..3e10b3914 100644
--- a/tests/optimal_policy/OSR/osr_obj_corr_algo_1.mod
+++ b/tests/optimal_policy/OSR/osr_obj_corr_algo_1.mod
@@ -41,7 +41,7 @@ gammac0 = 1.5;
 gamma_y_ = 8;
 gamma_inf_ = 3;
 
-osr(opt_algo=1);
+osr(opt_algo=1,silent_optimizer);
 %compute objective function manually
 objective=oo_.var(strmatch('y',M_.endo_names,'exact'),strmatch('y',M_.endo_names,'exact'))+oo_.var(strmatch('inflation',M_.endo_names,'exact'),strmatch('inflation',M_.endo_names,'exact'))+oo_.var(strmatch('dummy_var',M_.endo_names,'exact'),strmatch('dummy_var',M_.endo_names,'exact'));
         
@@ -57,7 +57,7 @@ dummy_var 1;
 y,inflation 0.5;
 end;
 
-osr;
+osr(silent_optimizer);
 %compute objective function manually
 objective=oo_.var(strmatch('y',M_.endo_names,'exact'),strmatch('y',M_.endo_names,'exact'))+oo_.var(strmatch('inflation',M_.endo_names,'exact'),strmatch('inflation',M_.endo_names,'exact'))+oo_.var(strmatch('dummy_var',M_.endo_names,'exact'),strmatch('dummy_var',M_.endo_names,'exact'))+0.5*oo_.var(strmatch('y',M_.endo_names,'exact'),strmatch('inflation',M_.endo_names,'exact'));
 if abs(oo_.osr.objective_function-objective)>1e-8
@@ -95,7 +95,7 @@ y,inflation 0.5;
 inflation,y 0.5;
 end;
 
-osr;
+osr(silent_optimizer);
 %compute objective function manually
 objective=oo_.var(strmatch('y',M_.endo_names,'exact'),strmatch('y',M_.endo_names,'exact'))+oo_.var(strmatch('inflation',M_.endo_names,'exact'),strmatch('inflation',M_.endo_names,'exact'))+oo_.var(strmatch('dummy_var',M_.endo_names,'exact'),strmatch('dummy_var',M_.endo_names,'exact'))+0.5*oo_.var(strmatch('y',M_.endo_names,'exact'),strmatch('inflation',M_.endo_names,'exact'))+0.5*oo_.var(strmatch('inflation',M_.endo_names,'exact'),strmatch('y',M_.endo_names,'exact'));
 if abs(oo_.osr.objective_function-objective)>1e-8
diff --git a/tests/optimal_policy/OSR/osr_obj_corr_algo_3.mod b/tests/optimal_policy/OSR/osr_obj_corr_algo_3.mod
index a54224fc8..47f142d8e 100644
--- a/tests/optimal_policy/OSR/osr_obj_corr_algo_3.mod
+++ b/tests/optimal_policy/OSR/osr_obj_corr_algo_3.mod
@@ -41,7 +41,7 @@ gammac0 = 1.5;
 gamma_y_ = 8;
 gamma_inf_ = 3;
 
-osr(opt_algo=3);
+osr(opt_algo=3,silent_optimizer);
 %compute objective function manually
 objective=oo_.var(strmatch('y',M_.endo_names,'exact'),strmatch('y',M_.endo_names,'exact'))+oo_.var(strmatch('inflation',M_.endo_names,'exact'),strmatch('inflation',M_.endo_names,'exact'))+oo_.var(strmatch('dummy_var',M_.endo_names,'exact'),strmatch('dummy_var',M_.endo_names,'exact'));
         
@@ -57,7 +57,7 @@ dummy_var 1;
 y,inflation 0.5;
 end;
 
-osr;
+osr(silent_optimizer);
 %compute objective function manually
 objective=oo_.var(strmatch('y',M_.endo_names,'exact'),strmatch('y',M_.endo_names,'exact'))+oo_.var(strmatch('inflation',M_.endo_names,'exact'),strmatch('inflation',M_.endo_names,'exact'))+oo_.var(strmatch('dummy_var',M_.endo_names,'exact'),strmatch('dummy_var',M_.endo_names,'exact'))+0.5*oo_.var(strmatch('y',M_.endo_names,'exact'),strmatch('inflation',M_.endo_names,'exact'));
 if abs(oo_.osr.objective_function-objective)>1e-8
@@ -77,7 +77,7 @@ dummy_var 1;
 y,inflation 1;
 end;
 
-osr;
+osr(silent_optimizer);
 %compute objective function manually
 objective=oo_.var(strmatch('y',M_.endo_names,'exact'),strmatch('y',M_.endo_names,'exact'))+oo_.var(strmatch('inflation',M_.endo_names,'exact'),strmatch('inflation',M_.endo_names,'exact'))+oo_.var(strmatch('dummy_var',M_.endo_names,'exact'),strmatch('dummy_var',M_.endo_names,'exact'))+1*oo_.var(strmatch('y',M_.endo_names,'exact'),strmatch('inflation',M_.endo_names,'exact'));
 if abs(oo_.osr.objective_function-objective)>1e-8
@@ -95,7 +95,7 @@ y,inflation 0.5;
 inflation,y 0.5;
 end;
 
-osr;
+osr(silent_optimizer);
 %compute objective function manually
 objective=oo_.var(strmatch('y',M_.endo_names,'exact'),strmatch('y',M_.endo_names,'exact'))+oo_.var(strmatch('inflation',M_.endo_names,'exact'),strmatch('inflation',M_.endo_names,'exact'))+oo_.var(strmatch('dummy_var',M_.endo_names,'exact'),strmatch('dummy_var',M_.endo_names,'exact'))+0.5*oo_.var(strmatch('y',M_.endo_names,'exact'),strmatch('inflation',M_.endo_names,'exact'))+0.5*oo_.var(strmatch('inflation',M_.endo_names,'exact'),strmatch('y',M_.endo_names,'exact'));
 if abs(oo_.osr.objective_function-objective)>1e-8
diff --git a/tests/optimal_policy/OSR/osr_obj_corr_algo_4.mod b/tests/optimal_policy/OSR/osr_obj_corr_algo_4.mod
index cbbabab6b..fd837ce44 100644
--- a/tests/optimal_policy/OSR/osr_obj_corr_algo_4.mod
+++ b/tests/optimal_policy/OSR/osr_obj_corr_algo_4.mod
@@ -42,7 +42,7 @@ gammac0 = 1.5;
 gamma_y_ = 8;
 gamma_inf_ = 3;
 
-osr(opt_algo=4);
+osr(opt_algo=4,silent_optimizer);
 %compute objective function manually
 objective=oo_.var(strmatch('y',M_.endo_names,'exact'),strmatch('y',M_.endo_names,'exact'))+oo_.var(strmatch('inflation',M_.endo_names,'exact'),strmatch('inflation',M_.endo_names,'exact'))+oo_.var(strmatch('dummy_var',M_.endo_names,'exact'),strmatch('dummy_var',M_.endo_names,'exact'));
         
@@ -58,7 +58,7 @@ dummy_var 1;
 y,inflation 0.5;
 end;
 
-osr;
+osr(silent_optimizer);
 %compute objective function manually
 objective=oo_.var(strmatch('y',M_.endo_names,'exact'),strmatch('y',M_.endo_names,'exact'))+oo_.var(strmatch('inflation',M_.endo_names,'exact'),strmatch('inflation',M_.endo_names,'exact'))+oo_.var(strmatch('dummy_var',M_.endo_names,'exact'),strmatch('dummy_var',M_.endo_names,'exact'))+0.5*oo_.var(strmatch('y',M_.endo_names,'exact'),strmatch('inflation',M_.endo_names,'exact'));
 if abs(oo_.osr.objective_function-objective)>1e-8
@@ -78,7 +78,7 @@ dummy_var 1;
 y,inflation 1;
 end;
 
-osr;
+osr(silent_optimizer);
 %compute objective function manually
 objective=oo_.var(strmatch('y',M_.endo_names,'exact'),strmatch('y',M_.endo_names,'exact'))+oo_.var(strmatch('inflation',M_.endo_names,'exact'),strmatch('inflation',M_.endo_names,'exact'))+oo_.var(strmatch('dummy_var',M_.endo_names,'exact'),strmatch('dummy_var',M_.endo_names,'exact'))+1*oo_.var(strmatch('y',M_.endo_names,'exact'),strmatch('inflation',M_.endo_names,'exact'));
 if abs(oo_.osr.objective_function-objective)>1e-8
diff --git a/tests/optimal_policy/OSR/osr_obj_corr_algo_7.mod b/tests/optimal_policy/OSR/osr_obj_corr_algo_7.mod
index d23466728..c1a8a6aa3 100644
--- a/tests/optimal_policy/OSR/osr_obj_corr_algo_7.mod
+++ b/tests/optimal_policy/OSR/osr_obj_corr_algo_7.mod
@@ -42,7 +42,7 @@ gamma_y_ = 8;
 gamma_inf_ = 3;
 
 if ~isoctave
-osr(opt_algo=7);
+osr(opt_algo=7,silent_optimizer);
 %compute objective function manually
 objective=oo_.var(strmatch('y',M_.endo_names,'exact'),strmatch('y',M_.endo_names,'exact'))+oo_.var(strmatch('inflation',M_.endo_names,'exact'),strmatch('inflation',M_.endo_names,'exact'))+oo_.var(strmatch('dummy_var',M_.endo_names,'exact'),strmatch('dummy_var',M_.endo_names,'exact'));
         
@@ -58,7 +58,7 @@ dummy_var 1;
 y,inflation 0.5;
 end;
 
-osr;
+osr(silent_optimizer);
 %compute objective function manually
 objective=oo_.var(strmatch('y',M_.endo_names,'exact'),strmatch('y',M_.endo_names,'exact'))+oo_.var(strmatch('inflation',M_.endo_names,'exact'),strmatch('inflation',M_.endo_names,'exact'))+oo_.var(strmatch('dummy_var',M_.endo_names,'exact'),strmatch('dummy_var',M_.endo_names,'exact'))+0.5*oo_.var(strmatch('y',M_.endo_names,'exact'),strmatch('inflation',M_.endo_names,'exact'));
 if abs(oo_.osr.objective_function-objective)>1e-8
@@ -78,7 +78,7 @@ dummy_var 1;
 y,inflation 1;
 end;
 
-osr;
+osr(silent_optimizer);
 %compute objective function manually
 objective=oo_.var(strmatch('y',M_.endo_names,'exact'),strmatch('y',M_.endo_names,'exact'))+oo_.var(strmatch('inflation',M_.endo_names,'exact'),strmatch('inflation',M_.endo_names,'exact'))+oo_.var(strmatch('dummy_var',M_.endo_names,'exact'),strmatch('dummy_var',M_.endo_names,'exact'))+1*oo_.var(strmatch('y',M_.endo_names,'exact'),strmatch('inflation',M_.endo_names,'exact'));
 if abs(oo_.osr.objective_function-objective)>1e-8
@@ -96,7 +96,7 @@ y,inflation 0.5;
 inflation,y 0.5;
 end;
 
-osr;
+osr(silent_optimizer);
 %compute objective function manually
 objective=oo_.var(strmatch('y',M_.endo_names,'exact'),strmatch('y',M_.endo_names,'exact'))+oo_.var(strmatch('inflation',M_.endo_names,'exact'),strmatch('inflation',M_.endo_names,'exact'))+oo_.var(strmatch('dummy_var',M_.endo_names,'exact'),strmatch('dummy_var',M_.endo_names,'exact'))+0.5*oo_.var(strmatch('y',M_.endo_names,'exact'),strmatch('inflation',M_.endo_names,'exact'))+0.5*oo_.var(strmatch('inflation',M_.endo_names,'exact'),strmatch('y',M_.endo_names,'exact'));
 if abs(oo_.osr.objective_function-objective)>1e-8
diff --git a/tests/optimal_policy/OSR/osr_obj_corr_algo_8.mod b/tests/optimal_policy/OSR/osr_obj_corr_algo_8.mod
index 77d014d2f..691bc5010 100644
--- a/tests/optimal_policy/OSR/osr_obj_corr_algo_8.mod
+++ b/tests/optimal_policy/OSR/osr_obj_corr_algo_8.mod
@@ -41,7 +41,7 @@ gammac0 = 1.5;
 gamma_y_ = 8;
 gamma_inf_ = 3;
 
-osr(opt_algo=8);
+osr(opt_algo=8,silent_optimizer);
 %compute objective function manually
 objective=oo_.var(strmatch('y',M_.endo_names,'exact'),strmatch('y',M_.endo_names,'exact'))+oo_.var(strmatch('inflation',M_.endo_names,'exact'),strmatch('inflation',M_.endo_names,'exact'))+oo_.var(strmatch('dummy_var',M_.endo_names,'exact'),strmatch('dummy_var',M_.endo_names,'exact'));
         
@@ -57,7 +57,7 @@ dummy_var 1;
 y,inflation 0.5;
 end;
 
-osr;
+osr(silent_optimizer);
 %compute objective function manually
 objective=oo_.var(strmatch('y',M_.endo_names,'exact'),strmatch('y',M_.endo_names,'exact'))+oo_.var(strmatch('inflation',M_.endo_names,'exact'),strmatch('inflation',M_.endo_names,'exact'))+oo_.var(strmatch('dummy_var',M_.endo_names,'exact'),strmatch('dummy_var',M_.endo_names,'exact'))+0.5*oo_.var(strmatch('y',M_.endo_names,'exact'),strmatch('inflation',M_.endo_names,'exact'));
 if abs(oo_.osr.objective_function-objective)>1e-8
@@ -77,7 +77,7 @@ dummy_var 1;
 y,inflation 1;
 end;
 
-osr;
+osr(silent_optimizer);
 %compute objective function manually
 objective=oo_.var(strmatch('y',M_.endo_names,'exact'),strmatch('y',M_.endo_names,'exact'))+oo_.var(strmatch('inflation',M_.endo_names,'exact'),strmatch('inflation',M_.endo_names,'exact'))+oo_.var(strmatch('dummy_var',M_.endo_names,'exact'),strmatch('dummy_var',M_.endo_names,'exact'))+1*oo_.var(strmatch('y',M_.endo_names,'exact'),strmatch('inflation',M_.endo_names,'exact'));
 if abs(oo_.osr.objective_function-objective)>1e-8
@@ -95,7 +95,7 @@ y,inflation 0.5;
 inflation,y 0.5;
 end;
 
-osr;
+osr(silent_optimizer);
 %compute objective function manually
 objective=oo_.var(strmatch('y',M_.endo_names,'exact'),strmatch('y',M_.endo_names,'exact'))+oo_.var(strmatch('inflation',M_.endo_names,'exact'),strmatch('inflation',M_.endo_names,'exact'))+oo_.var(strmatch('dummy_var',M_.endo_names,'exact'),strmatch('dummy_var',M_.endo_names,'exact'))+0.5*oo_.var(strmatch('y',M_.endo_names,'exact'),strmatch('inflation',M_.endo_names,'exact'))+0.5*oo_.var(strmatch('inflation',M_.endo_names,'exact'),strmatch('y',M_.endo_names,'exact'));
 if abs(oo_.osr.objective_function-objective)>1e-8
diff --git a/tests/optimal_policy/OSR/osr_obj_corr_algo_9.mod b/tests/optimal_policy/OSR/osr_obj_corr_algo_9.mod
index 59a2fa250..b2ca9c107 100644
--- a/tests/optimal_policy/OSR/osr_obj_corr_algo_9.mod
+++ b/tests/optimal_policy/OSR/osr_obj_corr_algo_9.mod
@@ -41,7 +41,7 @@ gammac0 = 1.5;
 gamma_y_ = 8;
 gamma_inf_ = 3;
 
-osr(opt_algo=9);
+osr(opt_algo=9,silent_optimizer);
 %compute objective function manually
 objective=oo_.var(strmatch('y',M_.endo_names,'exact'),strmatch('y',M_.endo_names,'exact'))+oo_.var(strmatch('inflation',M_.endo_names,'exact'),strmatch('inflation',M_.endo_names,'exact'))+oo_.var(strmatch('dummy_var',M_.endo_names,'exact'),strmatch('dummy_var',M_.endo_names,'exact'));
         
@@ -57,7 +57,7 @@ dummy_var 1;
 y,inflation 0.5;
 end;
 
-osr;
+osr(silent_optimizer);
 %compute objective function manually
 objective=oo_.var(strmatch('y',M_.endo_names,'exact'),strmatch('y',M_.endo_names,'exact'))+oo_.var(strmatch('inflation',M_.endo_names,'exact'),strmatch('inflation',M_.endo_names,'exact'))+oo_.var(strmatch('dummy_var',M_.endo_names,'exact'),strmatch('dummy_var',M_.endo_names,'exact'))+0.5*oo_.var(strmatch('y',M_.endo_names,'exact'),strmatch('inflation',M_.endo_names,'exact'));
 if abs(oo_.osr.objective_function-objective)>1e-8
@@ -77,7 +77,7 @@ dummy_var 1;
 y,inflation 1;
 end;
 
-osr;
+osr(silent_optimizer);
 %compute objective function manually
 objective=oo_.var(strmatch('y',M_.endo_names,'exact'),strmatch('y',M_.endo_names,'exact'))+oo_.var(strmatch('inflation',M_.endo_names,'exact'),strmatch('inflation',M_.endo_names,'exact'))+oo_.var(strmatch('dummy_var',M_.endo_names,'exact'),strmatch('dummy_var',M_.endo_names,'exact'))+1*oo_.var(strmatch('y',M_.endo_names,'exact'),strmatch('inflation',M_.endo_names,'exact'));
 if abs(oo_.osr.objective_function-objective)>1e-8
@@ -95,7 +95,7 @@ y,inflation 0.5;
 inflation,y 0.5;
 end;
 
-osr;
+osr(silent_optimizer);
 %compute objective function manually
 objective=oo_.var(strmatch('y',M_.endo_names,'exact'),strmatch('y',M_.endo_names,'exact'))+oo_.var(strmatch('inflation',M_.endo_names,'exact'),strmatch('inflation',M_.endo_names,'exact'))+oo_.var(strmatch('dummy_var',M_.endo_names,'exact'),strmatch('dummy_var',M_.endo_names,'exact'))+0.5*oo_.var(strmatch('y',M_.endo_names,'exact'),strmatch('inflation',M_.endo_names,'exact'))+0.5*oo_.var(strmatch('inflation',M_.endo_names,'exact'),strmatch('y',M_.endo_names,'exact'));
 if abs(oo_.osr.objective_function-objective)>1e-8
diff --git a/tests/optimal_policy/OSR/osr_objective_correctness_anal_deriv.mod b/tests/optimal_policy/OSR/osr_objective_correctness_anal_deriv.mod
index 1a9b35189..c9212db61 100644
--- a/tests/optimal_policy/OSR/osr_objective_correctness_anal_deriv.mod
+++ b/tests/optimal_policy/OSR/osr_objective_correctness_anal_deriv.mod
@@ -41,7 +41,7 @@ gammac0 = 1.5;
 gamma_y_ = 8;
 gamma_inf_ = 3;
 
-osr(analytic_derivation,optim=('TolFun',1e-20));
+osr(analytic_derivation,optim=('TolFun',1e-20),silent_optimizer);
 %compute objective function manually
 objective=oo_.var(strmatch('y',M_.endo_names,'exact'),strmatch('y',M_.endo_names,'exact'))+oo_.var(strmatch('inflation',M_.endo_names,'exact'),strmatch('inflation',M_.endo_names,'exact'))+oo_.var(strmatch('dummy_var',M_.endo_names,'exact'),strmatch('dummy_var',M_.endo_names,'exact'));
         
@@ -57,7 +57,7 @@ dummy_var 1;
 y,inflation 0.5;
 end;
 
-osr(analytic_derivation);
+osr(analytic_derivation,silent_optimizer);
 %compute objective function manually
 objective=oo_.var(strmatch('y',M_.endo_names,'exact'),strmatch('y',M_.endo_names,'exact'))+oo_.var(strmatch('inflation',M_.endo_names,'exact'),strmatch('inflation',M_.endo_names,'exact'))+oo_.var(strmatch('dummy_var',M_.endo_names,'exact'),strmatch('dummy_var',M_.endo_names,'exact'))+0.5*oo_.var(strmatch('y',M_.endo_names,'exact'),strmatch('inflation',M_.endo_names,'exact'));
 if abs(oo_.osr.objective_function-objective)>1e-8
@@ -77,7 +77,7 @@ dummy_var 1;
 y,inflation 1;
 end;
 
-osr(analytic_derivation);
+osr(analytic_derivation,silent_optimizer);
 %compute objective function manually
 objective=oo_.var(strmatch('y',M_.endo_names,'exact'),strmatch('y',M_.endo_names,'exact'))+oo_.var(strmatch('inflation',M_.endo_names,'exact'),strmatch('inflation',M_.endo_names,'exact'))+oo_.var(strmatch('dummy_var',M_.endo_names,'exact'),strmatch('dummy_var',M_.endo_names,'exact'))+1*oo_.var(strmatch('y',M_.endo_names,'exact'),strmatch('inflation',M_.endo_names,'exact'));
 if abs(oo_.osr.objective_function-objective)>1e-8
@@ -95,7 +95,7 @@ y,inflation 0.5;
 inflation,y 0.5;
 end;
 
-osr(analytic_derivation);
+osr(analytic_derivation,silent_optimizer);
 %compute objective function manually
 objective=oo_.var(strmatch('y',M_.endo_names,'exact'),strmatch('y',M_.endo_names,'exact'))+oo_.var(strmatch('inflation',M_.endo_names,'exact'),strmatch('inflation',M_.endo_names,'exact'))+oo_.var(strmatch('dummy_var',M_.endo_names,'exact'),strmatch('dummy_var',M_.endo_names,'exact'))+0.5*oo_.var(strmatch('y',M_.endo_names,'exact'),strmatch('inflation',M_.endo_names,'exact'))+0.5*oo_.var(strmatch('inflation',M_.endo_names,'exact'),strmatch('y',M_.endo_names,'exact'));
 if abs(oo_.osr.objective_function-objective)>1e-8
diff --git a/tests/optimizers/fs2000_1.mod b/tests/optimizers/fs2000_1.mod
index 65b261d42..b0b005377 100644
--- a/tests/optimizers/fs2000_1.mod
+++ b/tests/optimizers/fs2000_1.mod
@@ -1,5 +1,5 @@
 @#include "fs2000.common.inc"
 
 if (isoctave && user_has_octave_forge_package('optim', '1.6')) || (~isoctave && user_has_matlab_license('optimization_toolbox'))
-  estimation(mode_compute=1,order=1, datafile='../fs2000/fsdat_simul', nobs=192, mh_replic=0);
+  estimation(mode_compute=1,silent_optimizer,order=1, datafile='../fs2000/fsdat_simul', nobs=192, mh_replic=0);
 end
diff --git a/tests/optimizers/fs2000_10.mod b/tests/optimizers/fs2000_10.mod
index d46ef9d85..a2cc1c84e 100644
--- a/tests/optimizers/fs2000_10.mod
+++ b/tests/optimizers/fs2000_10.mod
@@ -1,3 +1,3 @@
 @#include "fs2000.common.inc"
 
-estimation(mode_compute=10,order=1, datafile='../fs2000/fsdat_simul', nobs=192, mh_replic=0);
+estimation(mode_compute=10,silent_optimizer,order=1, datafile='../fs2000/fsdat_simul', nobs=192, mh_replic=0);
diff --git a/tests/optimizers/fs2000_101.mod b/tests/optimizers/fs2000_101.mod
index d301ecd18..36557bb86 100644
--- a/tests/optimizers/fs2000_101.mod
+++ b/tests/optimizers/fs2000_101.mod
@@ -1,3 +1,3 @@
 @#include "fs2000.common.inc"
 
-estimation(mode_compute=101,order=1, datafile='../fs2000/fsdat_simul', nobs=192, mh_replic=0);
+estimation(mode_compute=101,silent_optimizer,order=1, datafile='../fs2000/fsdat_simul', nobs=192, mh_replic=0);
diff --git a/tests/optimizers/fs2000_102.mod b/tests/optimizers/fs2000_102.mod
index f23ae2d77..1da672d4e 100644
--- a/tests/optimizers/fs2000_102.mod
+++ b/tests/optimizers/fs2000_102.mod
@@ -1,5 +1,5 @@
 @#include "fs2000.common.inc"
 
 if ~isoctave() && exist('simulannealbnd','file')
-   estimation(mode_compute=102,mode_file='../estimation/fs2000/Output/fs2000_mode',order=1, datafile='../fs2000/fsdat_simul', nobs=192, mh_replic=0, mh_nblocks=2, mh_jscale=0.8);
+   estimation(mode_compute=102,silent_optimizer,mode_file='../estimation/fs2000/Output/fs2000_mode',order=1, datafile='../fs2000/fsdat_simul', nobs=192, mh_replic=0, mh_nblocks=2, mh_jscale=0.8);
 end
diff --git a/tests/optimizers/fs2000_12.mod b/tests/optimizers/fs2000_12.mod
index 306d2aa80..206650cb1 100644
--- a/tests/optimizers/fs2000_12.mod
+++ b/tests/optimizers/fs2000_12.mod
@@ -1,3 +1,3 @@
 @#include "fs2000.common.inc"
 
-estimation(mode_compute=12,order=1, datafile='../fs2000/fsdat_simul', nobs=192, mh_replic=0);
+estimation(mode_compute=12,silent_optimizer,order=1, datafile='../fs2000/fsdat_simul', nobs=192, mh_replic=0);
diff --git a/tests/optimizers/fs2000_2.mod b/tests/optimizers/fs2000_2.mod
index 847883989..85e5125cf 100644
--- a/tests/optimizers/fs2000_2.mod
+++ b/tests/optimizers/fs2000_2.mod
@@ -1,6 +1,6 @@
 @#include "fs2000.common.inc"
 
-estimation(mode_compute=2,order=1, datafile='../fs2000/fsdat_simul', nobs=192, mh_replic=0,
+estimation(mode_compute=2,silent_optimizer,order=1, datafile='../fs2000/fsdat_simul', nobs=192, mh_replic=0,
 optim=(
 'MaxIter',5000,
 'TolFun',1e-4,
diff --git a/tests/optimizers/fs2000_3.mod b/tests/optimizers/fs2000_3.mod
index 5efc98d2a..9866fb7d2 100644
--- a/tests/optimizers/fs2000_3.mod
+++ b/tests/optimizers/fs2000_3.mod
@@ -1,5 +1,5 @@
 @#include "fs2000.common.inc"
 
 if exist('fminunc','file')
-  estimation(mode_compute=3,order=1, datafile='../fs2000/fsdat_simul', nobs=192, mh_replic=0);
+  estimation(mode_compute=3,silent_optimizer,order=1, datafile='../fs2000/fsdat_simul', nobs=192, mh_replic=0);
 end
diff --git a/tests/optimizers/fs2000_4.mod b/tests/optimizers/fs2000_4.mod
index c500afa7f..10eef7d9c 100644
--- a/tests/optimizers/fs2000_4.mod
+++ b/tests/optimizers/fs2000_4.mod
@@ -1,3 +1,3 @@
 @#include "fs2000.common.inc"
 
-estimation(mode_compute=4,order=1, datafile='../fs2000/fsdat_simul', nobs=192, mh_replic=0);
+estimation(mode_compute=4,silent_optimizer,order=1, datafile='../fs2000/fsdat_simul', nobs=192, mh_replic=0);
diff --git a/tests/optimizers/fs2000_4_with_optim.mod b/tests/optimizers/fs2000_4_with_optim.mod
index ecb4254ed..4043e1135 100644
--- a/tests/optimizers/fs2000_4_with_optim.mod
+++ b/tests/optimizers/fs2000_4_with_optim.mod
@@ -1,3 +1,3 @@
 @#include "fs2000.common.inc"
 
-estimation(mode_compute=4,order=1, datafile='../fs2000/fsdat_simul', nobs=192, mh_replic=0,optim=('NumgradEpsilon',1e-6,'NumgradAlgorithm',3,'MaxIter',100,'InitialInverseHessian','eye(9)*.0001'));
\ No newline at end of file
+estimation(mode_compute=4,silent_optimizer,order=1, datafile='../fs2000/fsdat_simul', nobs=192, mh_replic=0,optim=('NumgradEpsilon',1e-6,'NumgradAlgorithm',3,'MaxIter',100,'InitialInverseHessian','eye(9)*.0001'));
\ No newline at end of file
diff --git a/tests/optimizers/fs2000_5.mod b/tests/optimizers/fs2000_5.mod
index 3dc7e9e1d..f7f9d22da 100644
--- a/tests/optimizers/fs2000_5.mod
+++ b/tests/optimizers/fs2000_5.mod
@@ -1,4 +1,4 @@
 @#include "fs2000.common.inc"
 
-estimation(mode_compute=5,order=1, datafile='../fs2000/fsdat_simul', nobs=192, mh_replic=0);
-estimation(mode_compute=5,order=1, datafile='../fs2000/fsdat_simul', nobs=192, mh_replic=0, optim=('Hessian',2));
+estimation(mode_compute=5,silent_optimizer,order=1, datafile='../fs2000/fsdat_simul', nobs=192, mh_replic=0);
+estimation(mode_compute=5,silent_optimizer,order=1, datafile='../fs2000/fsdat_simul', nobs=192, mh_replic=0, optim=('Hessian',2));
diff --git a/tests/optimizers/fs2000_6.mod b/tests/optimizers/fs2000_6.mod
index 000fa1932..7743e51f7 100644
--- a/tests/optimizers/fs2000_6.mod
+++ b/tests/optimizers/fs2000_6.mod
@@ -1,7 +1,7 @@
 @#include "fs2000.common.inc"
 
-estimation(mode_compute=6,order=1, datafile='../fs2000/fsdat_simul', nobs=192, mh_replic=0, optim=('nclimb-mh', 10, 'ncov-mh', 1000, 'nscale-mh', 5000));
+estimation(mode_compute=6,silent_optimizer,order=1, datafile='../fs2000/fsdat_simul', nobs=192, mh_replic=0, optim=('nclimb-mh', 10, 'ncov-mh', 1000, 'nscale-mh', 5000));
 
 // test the mode file generated with mode_compute=6
-estimation(order=1,datafile='../fs2000/fsdat_simul',nobs=192,loglinear,mode_compute=0,mode_file='fs2000_6/Output/fs2000_6_mode',mh_replic=10,
+estimation(order=1,silent_optimizer,datafile='../fs2000/fsdat_simul',nobs=192,loglinear,mode_compute=0,mode_file='fs2000_6/Output/fs2000_6_mode',mh_replic=10,
         posterior_sampler_options=('scale_file','fs2000_6/Output/fs2000_6_optimal_mh_scale_parameter'));
diff --git a/tests/optimizers/fs2000_7.mod b/tests/optimizers/fs2000_7.mod
index 3a58b5fa2..f977c1f12 100644
--- a/tests/optimizers/fs2000_7.mod
+++ b/tests/optimizers/fs2000_7.mod
@@ -1,5 +1,5 @@
 @#include "fs2000.common.inc"
 
 if exist('fminsearch','file')
-  estimation(mode_compute=7,order=1, datafile='../fs2000/fsdat_simul', nobs=192, mh_replic=0);
+  estimation(mode_compute=7,silent_optimizer,order=1, datafile='../fs2000/fsdat_simul', nobs=192, mh_replic=0);
 end
diff --git a/tests/optimizers/fs2000_8.mod b/tests/optimizers/fs2000_8.mod
index f7415df12..ae87e9206 100644
--- a/tests/optimizers/fs2000_8.mod
+++ b/tests/optimizers/fs2000_8.mod
@@ -1,3 +1,3 @@
 @#include "fs2000.common.inc"
 
-estimation(mode_compute=8,order=1, datafile='../fs2000/fsdat_simul', nobs=192, mh_replic=0);
+estimation(mode_compute=8,silent_optimizer,order=1, datafile='../fs2000/fsdat_simul', nobs=192, mh_replic=0);
diff --git a/tests/optimizers/fs2000_8_with_optim.mod b/tests/optimizers/fs2000_8_with_optim.mod
index c166d7047..5f6e79185 100644
--- a/tests/optimizers/fs2000_8_with_optim.mod
+++ b/tests/optimizers/fs2000_8_with_optim.mod
@@ -1,7 +1,7 @@
 @#include "fs2000.common.inc"
 
 options_.solve_tolf = 1e-12;
-estimation(mode_compute=8,order=1, datafile='../fs2000/fsdat_simul', nobs=192, mh_replic=0,optim=(
+estimation(mode_compute=8,silent_optimizer,order=1, datafile='../fs2000/fsdat_simul', nobs=192, mh_replic=0,optim=(
 'MaxIter',5000,
 'TolFun',1e-4,
 'TolX',1e-4,
diff --git a/tests/optimizers/fs2000_9.mod b/tests/optimizers/fs2000_9.mod
index 96d75bf96..fb22f8827 100644
--- a/tests/optimizers/fs2000_9.mod
+++ b/tests/optimizers/fs2000_9.mod
@@ -1,3 +1,3 @@
 @#include "fs2000.common.inc"
 
-estimation(mode_compute=9,order=1, datafile='../fs2000/fsdat_simul', nobs=192, mh_replic=0);
+estimation(mode_compute=9,silent_optimizer,order=1, datafile='../fs2000/fsdat_simul', nobs=192, mh_replic=0);
diff --git a/tests/optimizers/fs2000_w.mod b/tests/optimizers/fs2000_w.mod
index 73f6bdc62..50e01f87a 100644
--- a/tests/optimizers/fs2000_w.mod
+++ b/tests/optimizers/fs2000_w.mod
@@ -1,3 +1,3 @@
 @#include "fs2000.common.inc"
 
-estimation(mode_compute=optimizer_function_wrapper,order=1, datafile='../fs2000/fsdat_simul', nobs=192, mh_replic=0);
+estimation(mode_compute=optimizer_function_wrapper,silent_optimizer,order=1, datafile='../fs2000/fsdat_simul', nobs=192, mh_replic=0);
diff --git a/tests/parallel/ls2003.mod b/tests/parallel/ls2003.mod
index cf3d8d076..1b8a30374 100644
--- a/tests/parallel/ls2003.mod
+++ b/tests/parallel/ls2003.mod
@@ -65,7 +65,7 @@ stderr e_pies,inv_gamma_pdf,1.88,0.9827;
 end;
 
 
-estimation(datafile=data_ca1,first_obs=8,nobs=79,mh_replic=0,nodisplay);
+estimation(datafile=data_ca1,first_obs=8,nobs=79,silent_optimizer,mh_replic=0,nodisplay);
 estimation(datafile=data_ca1,first_obs=8,nobs=79,mode_compute=0,nodisplay, mode_file='ls2003/Output/ls2003_mode', mh_nblocks=4, prefilter=1, mh_jscale=0.5, mh_replic=2000);
 estimation(datafile=data_ca1,first_obs=8,nobs=79,mode_compute=0,nodisplay, mode_file='ls2003/Output/ls2003_mode', mh_nblocks=4,prefilter=1,mh_jscale=0.5,mh_replic=2000,bayesian_irf,load_mh_file,smoother,forecast=12, filtered_vars, filter_step_ahead=[1 2 3 4]) y y_s R pie dq pie_s de A y_obs pie_obs R_obs;
 
diff --git a/tests/particle/dsge_base2.mod b/tests/particle/dsge_base2.mod
index 10d1acec6..ecc845db4 100644
--- a/tests/particle/dsge_base2.mod
+++ b/tests/particle/dsge_base2.mod
@@ -153,63 +153,63 @@ options_.threads.local_state_space_iteration_2 = 4;
 
 
 @#if LINEAR_KALMAN
-  estimation(nograph,order=1,mode_compute=8,mh_replic=0,mode_check);
+  estimation(nograph,order=1,mode_compute=8,silent_optimizer,mh_replic=0,mode_check);
 @#endif
 
 @#if NON_LINEAR_KALMAN
-  estimation(nograph,order=2,filter_algorithm=nlkf,mode_compute=8,mh_replic=0);
+  estimation(nograph,order=2,filter_algorithm=nlkf,mode_compute=8,silent_optimizer,mh_replic=0);
 @#endif
 
 @#if ALGO_SIR
-  estimation(order=2,nograph,number_of_particles=1000,mh_replic=0,mode_compute=8);
+  estimation(order=2,nograph,number_of_particles=1000,mh_replic=0,silent_optimizer,mode_compute=8);
 @#endif
 
 @#if ALGO_SISmoothR
-  estimation(order=2,nograph,number_of_particles=1000,resampling_method=smooth,mode_compute=8,mh_replic=0);
-  estimation(order=2,nograph,number_of_particles=1000,resampling_method=smooth,mode_compute=8,mode_file=dsge_base2_mode,mh_replic=0);
-  estimation(order=2,nograph,number_of_particles=1000,resampling_method=smooth,mode_compute=4,mode_file=dsge_base2_mode,mh_replic=0,mode_check);
+  estimation(order=2,nograph,number_of_particles=1000,resampling_method=smooth,mode_compute=8,silent_optimizer,mh_replic=0);
+  estimation(order=2,nograph,number_of_particles=1000,resampling_method=smooth,mode_compute=8,silent_optimizer,mode_file=dsge_base2_mode,mh_replic=0);
+  estimation(order=2,nograph,number_of_particles=1000,resampling_method=smooth,mode_compute=4,silent_optimizer,mode_file=dsge_base2_mode,mh_replic=0,mode_check);
 @#endif
 
 @#if ALGO_APF
-  estimation(order=2,nograph,filter_algorithm=apf,number_of_particles=10000,resampling=none,mh_replic=0,mode_compute=8,mode_check);
+  estimation(order=2,nograph,filter_algorithm=apf,number_of_particles=10000,resampling=none,mh_replic=0,mode_compute=8,silent_optimizer,mode_check);
 @#endif
 
 @#if ALGO_CPF
-  estimation(order=2,nograph,filter_algorithm=cpf,number_of_particles=10000,resampling=none,mh_replic=0,mode_compute=8,mode_check);
+  estimation(order=2,nograph,filter_algorithm=cpf,number_of_particles=10000,resampling=none,mh_replic=0,mode_compute=8,silent_optimizer,mode_check);
 @#endif
 
 @#if ALGO_GPF
-  estimation(order=2,nograph,filter_algorithm=gf,distribution_approximation=montecarlo,number_of_particles=1000,mh_replic=0,mode_compute=8);
-  estimation(order=2,nograph,filter_algorithm=gf,distribution_approximation=montecarlo,number_of_particles=1000,mode_file=dsge_base2_mode,mh_replic=0,mode_compute=4,mode_check);
+  estimation(order=2,nograph,filter_algorithm=gf,distribution_approximation=montecarlo,number_of_particles=1000,mh_replic=0,mode_compute=8,silent_optimizer);
+  estimation(order=2,nograph,filter_algorithm=gf,distribution_approximation=montecarlo,number_of_particles=1000,mode_file=dsge_base2_mode,mh_replic=0,mode_compute=4,silent_optimizer,mode_check);
 @#endif
 
 @#if ALGO_GCF
-  estimation(order=2,nograph,filter_algorithm=gf,mh_replic=0,mode_compute=8);
-  estimation(order=2,nograph,filter_algorithm=gf,mh_replic=0,mode_compute=4,mode_file=dsge_base2_mode,mode_check);
+  estimation(order=2,nograph,filter_algorithm=gf,mh_replic=0,mode_compute=8,silent_optimizer);
+  estimation(order=2,nograph,filter_algorithm=gf,mh_replic=0,mode_compute=4,silent_optimizer,mode_file=dsge_base2_mode,mode_check);
 @#endif
 
 @#if ALGO_GUF
-  estimation(order=2,nograph,filter_algorithm=gf,proposal_approximation=unscented,distribution_approximation=unscented,mh_replic=0,mode_compute=8);
-  estimation(order=2,nograph,filter_algorithm=gf,proposal_approximation=unscented,distribution_approximation=unscented,mh_replic=0,mode_compute=8,mode_check);
+  estimation(order=2,nograph,filter_algorithm=gf,proposal_approximation=unscented,distribution_approximation=unscented,mh_replic=0,silent_optimizer,mode_compute=8);
+  estimation(order=2,nograph,filter_algorithm=gf,proposal_approximation=unscented,distribution_approximation=unscented,mh_replic=0,mode_compute=8,silent_optimizer,mode_check);
 @#endif
 
 @#if ALGO_GMPF
-  estimation(nograph,order=2,filter_algorithm=gmf,distribution_approximation=montecarlo,number_of_particles=1000,mh_replic=0,mode_compute=8);
+  estimation(nograph,order=2,filter_algorithm=gmf,distribution_approximation=montecarlo,number_of_particles=1000,mh_replic=0,mode_compute=8,silent_optimizer);
   estimation(nograph,order=2,filter_algorithm=gmf,distribution_approximation=montecarlo,number_of_particles=1000,mh_replic=0,mode_file=dsge_base2_mode,mode_compute=8);
   estimation(nograph,order=2,filter_algorithm=gmf,distribution_approximation=montecarlo,number_of_particles=1000,mh_replic=0,mode_file=dsge_base2_mode,mode_compute=4,mode_check);
 @#endif
 
 @#if ALGO_GMCF
-  estimation(nograph,order=2,filter_algorithm=gmf,mh_replic=0,mode_compute=8);
-  estimation(nograph,order=2,filter_algorithm=gmf,mh_replic=0,mode_compute=4,mode_file=dsge_base2_mode,mode_check);
+  estimation(nograph,order=2,filter_algorithm=gmf,mh_replic=0,mode_compute=8,silent_optimizer);
+  estimation(nograph,order=2,filter_algorithm=gmf,mh_replic=0,mode_compute=4,silent_optimizer,mode_file=dsge_base2_mode,mode_check);
 @#endif
 
 @#if ALGO_ONLINE_2
-  estimation(order=2,number_of_particles=1000,mode_compute=11,mh_replic=0,particle_filter_options=('liu_west_delta',0.9));
+  estimation(order=2,number_of_particles=1000,mode_compute=11,silent_optimizer,mh_replic=0,particle_filter_options=('liu_west_delta',0.9));
 @#endif
 
 @#if ALGO_ONLINE_1
-  estimation(order=1,number_of_particles=1000,mode_compute=11,mh_replic=0,particle_filter_options=('liu_west_delta',0.9));
+  estimation(order=1,number_of_particles=1000,mode_compute=11,silent_optimizer,mh_replic=0,particle_filter_options=('liu_west_delta',0.9));
 @#endif
 
 @#if MCMC
diff --git a/tests/particle/dummy_model.mod b/tests/particle/dummy_model.mod
index 845e0a4b6..eeb389822 100644
--- a/tests/particle/dummy_model.mod
+++ b/tests/particle/dummy_model.mod
@@ -57,4 +57,4 @@ d, 0.7912;
 g, 0.2448;
 end;
 
-estimation(datafile=mydata,order=2,first_obs=5001,nobs=100,mh_replic=0,mode_compute=8,filter_algorithm=sis);
+estimation(datafile=mydata,order=2,first_obs=5001,nobs=100,mh_replic=0,mode_compute=8,silent_optimizer,filter_algorithm=sis);
diff --git a/tests/pi2004/ireland.mod b/tests/pi2004/ireland.mod
index 4c6552bde..c99117474 100644
--- a/tests/pi2004/ireland.mod
+++ b/tests/pi2004/ireland.mod
@@ -87,4 +87,4 @@ oy (log(eta));
 oc (log(eta));
 end;
 
-estimation(datafile=idata,mode_compute=1,nograph,dirname='MYDIR/mysubdir');
\ No newline at end of file
+estimation(datafile=idata,mode_compute=1,silent_optimizer,nograph,dirname='MYDIR/mysubdir');
\ No newline at end of file
diff --git a/tests/prior_posterior_function/fs2000_prior_posterior_function.mod b/tests/prior_posterior_function/fs2000_prior_posterior_function.mod
index 71d50c67d..cf26f2bc3 100644
--- a/tests/prior_posterior_function/fs2000_prior_posterior_function.mod
+++ b/tests/prior_posterior_function/fs2000_prior_posterior_function.mod
@@ -114,7 +114,7 @@ end;
 
 varobs gp_obs gy_obs;
 
-estimation(order=1,datafile='../fs2000/fsdat_simul', nobs=192, loglinear, mh_replic=2000, mh_nblocks=2, mh_jscale=0.8);
+estimation(order=1,datafile='../fs2000/fsdat_simul',silent_optimizer, nobs=192, loglinear, mh_replic=2000, mh_nblocks=2, mh_jscale=0.8);
 
 posterior_function(function='posterior_function_demo', sampling_draws=500);
 
diff --git a/tests/recursive/ls2003.mod b/tests/recursive/ls2003.mod
index 361ae4ede..20a51b4b7 100644
--- a/tests/recursive/ls2003.mod
+++ b/tests/recursive/ls2003.mod
@@ -61,5 +61,5 @@ stderr e_ys,inv_gamma_pdf,1.2533,0.6551;
 stderr e_pies,inv_gamma_pdf,1.88,0.9827;
 end;
 
-estimation(datafile=data_ca1,first_obs=8,nobs=[76 79],mh_nblocks=10,prefilter=1,mh_jscale=0.5,mh_replic=0,forecast=8) y_obs R_obs pie_obs dq de;
+estimation(datafile=data_ca1,silent_optimizer,first_obs=8,nobs=[76 79],mh_nblocks=10,prefilter=1,mh_jscale=0.5,mh_replic=0,forecast=8) y_obs R_obs pie_obs dq de;
 
diff --git a/tests/recursive/ls2003_bayesian.mod b/tests/recursive/ls2003_bayesian.mod
index 27d4f7c57..76a3954a9 100644
--- a/tests/recursive/ls2003_bayesian.mod
+++ b/tests/recursive/ls2003_bayesian.mod
@@ -61,5 +61,5 @@ stderr e_ys,inv_gamma_pdf,1.2533,0.6551;
 stderr e_pies,inv_gamma_pdf,1.88,0.9827;
 end;
 
-estimation(datafile=data_ca1,first_obs=8,nobs=[76 79],mh_nblocks=1,prefilter=1,mh_jscale=0.5,mh_replic=2000,forecast=8) y_obs R_obs pie_obs dq de;
+estimation(datafile=data_ca1,silent_optimizer,first_obs=8,nobs=[76 79],mh_nblocks=1,prefilter=1,mh_jscale=0.5,mh_replic=2000,forecast=8) y_obs R_obs pie_obs dq de;
 
diff --git a/tests/recursive/ls2003_bayesian_csv.mod b/tests/recursive/ls2003_bayesian_csv.mod
index 2678db52f..3279c5931 100644
--- a/tests/recursive/ls2003_bayesian_csv.mod
+++ b/tests/recursive/ls2003_bayesian_csv.mod
@@ -61,4 +61,4 @@ stderr e_ys,inv_gamma_pdf,1.2533,0.6551;
 stderr e_pies,inv_gamma_pdf,1.88,0.9827;
 end;
 
-estimation(datafile=data_ca1_csv,first_obs=8,nobs=[76 79],mh_nblocks=1,prefilter=1,mh_jscale=0.5,mh_replic=2000,forecast=8) y_obs R_obs pie_obs dq de;
+estimation(datafile=data_ca1_csv,silent_optimizer,first_obs=8,nobs=[76 79],mh_nblocks=1,prefilter=1,mh_jscale=0.5,mh_replic=2000,forecast=8) y_obs R_obs pie_obs dq de;
diff --git a/tests/recursive/ls2003_bayesian_xls.mod b/tests/recursive/ls2003_bayesian_xls.mod
index c2795e475..f91ec362c 100644
--- a/tests/recursive/ls2003_bayesian_xls.mod
+++ b/tests/recursive/ls2003_bayesian_xls.mod
@@ -61,4 +61,4 @@ stderr e_ys,inv_gamma_pdf,1.2533,0.6551;
 stderr e_pies,inv_gamma_pdf,1.88,0.9827;
 end;
 
-estimation(datafile='data_ca1_xls.xlsx',first_obs=8,nobs=[76 79],mh_nblocks=1,prefilter=1,mh_jscale=0.5,mh_replic=2000,forecast=8) y_obs R_obs pie_obs dq de;
+estimation(datafile='data_ca1_xls.xlsx',silent_optimizer,first_obs=8,nobs=[76 79],mh_nblocks=1,prefilter=1,mh_jscale=0.5,mh_replic=2000,forecast=8) y_obs R_obs pie_obs dq de;
diff --git a/tests/shock_decomposition/fs2000_est.mod b/tests/shock_decomposition/fs2000_est.mod
index 0f67bcf8e..6d8545c19 100644
--- a/tests/shock_decomposition/fs2000_est.mod
+++ b/tests/shock_decomposition/fs2000_est.mod
@@ -79,6 +79,6 @@ end;
 varobs gp_obs gy_obs;
 
 // Metropolis replications are too few, this is only for testing purpose
-estimation(order=1,datafile=fsdat_simul,nobs=192,loglinear,mh_replic=0);
+estimation(order=1,datafile=fsdat_simul,silent_optimizer,nobs=192,loglinear,mh_replic=0);
 
 shock_decomposition;
diff --git a/tests/shock_decomposition/fs2000_est_varlist.mod b/tests/shock_decomposition/fs2000_est_varlist.mod
index 3bf62bc47..fcef79532 100644
--- a/tests/shock_decomposition/fs2000_est_varlist.mod
+++ b/tests/shock_decomposition/fs2000_est_varlist.mod
@@ -78,6 +78,6 @@ end;
 
 varobs gp_obs gy_obs;
 
-estimation(order=1,datafile=fsdat_simul,nobs=192,loglinear,mh_replic=0) y W R;
+estimation(order=1,datafile=fsdat_simul,silent_optimizer,nobs=192,loglinear,mh_replic=0) y W R;
 
 shock_decomposition y W R;
diff --git a/tests/shock_decomposition/ls2003_plot.mod b/tests/shock_decomposition/ls2003_plot.mod
index db9179b63..2d15d0183 100644
--- a/tests/shock_decomposition/ls2003_plot.mod
+++ b/tests/shock_decomposition/ls2003_plot.mod
@@ -68,7 +68,7 @@ stderr e_ys,inv_gamma_pdf,1.2533,0.6551;
 stderr e_pies,inv_gamma_pdf,1.88,0.9827;
 end;
 
-estimation(datafile='../ls2003/data_ca1',first_obs=8,nobs=79,mh_nblocks=10,prefilter=1,mh_jscale=0.5,mh_replic=0,tex);
+estimation(datafile='../ls2003/data_ca1',silent_optimizer,first_obs=8,nobs=79,mh_nblocks=10,prefilter=1,mh_jscale=0.5,mh_replic=0,tex);
 close all
 
 shock_groups(name=trade);
diff --git a/tests/smoother2histval/fs2000_smooth.mod b/tests/smoother2histval/fs2000_smooth.mod
index 8a964b2d0..99cc95aed 100644
--- a/tests/smoother2histval/fs2000_smooth.mod
+++ b/tests/smoother2histval/fs2000_smooth.mod
@@ -82,6 +82,6 @@ varobs gp_obs gy_obs;
 
 options_.solve_tolf = 1e-12;
 
-estimation(order=1,datafile=fsdat_simul,mh_replic=1500,mh_nblocks=1,mh_jscale=0.8,smoother,consider_all_endogenous_and_auxiliary);
+estimation(order=1,datafile=fsdat_simul,silent_optimizer,mh_replic=1500,mh_nblocks=1,mh_jscale=0.8,smoother,consider_all_endogenous_and_auxiliary);
 
 smoother2histval(period = 5, outfile = 'fs2000_histval.mat');
diff --git a/tests/smoother2histval/fs2000_smooth_ML.mod b/tests/smoother2histval/fs2000_smooth_ML.mod
index 0cf14873f..83aba0a90 100644
--- a/tests/smoother2histval/fs2000_smooth_ML.mod
+++ b/tests/smoother2histval/fs2000_smooth_ML.mod
@@ -82,7 +82,7 @@ varobs gp_obs gy_obs;
 
 options_.solve_tolf = 1e-12;
 
-estimation(order=1,datafile=fsdat_simul,mh_replic=0,mh_nblocks=1,mh_jscale=0.8,smoother,consider_all_endogenous,forecast=5);
+estimation(order=1,datafile=fsdat_simul,silent_optimizer,mh_replic=0,mh_nblocks=1,mh_jscale=0.8,smoother,consider_all_endogenous,forecast=5);
 
 forecast_estimation=oo_.forecast;
 smoother2histval;
diff --git a/tests/smoother2histval/fs2000_smooth_stoch_simul.mod b/tests/smoother2histval/fs2000_smooth_stoch_simul.mod
index dbe0d15ba..587c789d8 100644
--- a/tests/smoother2histval/fs2000_smooth_stoch_simul.mod
+++ b/tests/smoother2histval/fs2000_smooth_stoch_simul.mod
@@ -82,7 +82,7 @@ varobs gp_obs gy_obs;
 
 options_.solve_tolf = 1e-12;
 
-estimation(order=1,loglinear,datafile=fsdat_simul,nobs=192,mh_replic=2,mh_nblocks=1,mh_jscale=0.8,smoother,consider_all_endogenous_and_auxiliary);
+estimation(order=1,loglinear,silent_optimizer,datafile=fsdat_simul,nobs=192,mh_replic=2,mh_nblocks=1,mh_jscale=0.8,smoother,consider_all_endogenous_and_auxiliary);
 steady;
 smoother2histval(period = 5);