diff --git a/tests/TeX/fs2000_corr_ME.mod b/tests/TeX/fs2000_corr_ME.mod
index b4a17fc7cf97c1df9a2eca8b59a51a993a70d1ab..b0ebe70fd2a809e303104d08088e93cdd654450a 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 a5e6eeec1e51b4835415ca654bff2aef29c7bd01..02ce409558c70573d78144fd8a826494dfc1d755 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 9020522def827d1d2cd16f32df62249670891071..44462f15aca9a807aa8a023cc17ffe4d6eef777b 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 ba439aa0b089501fb75f2168cfae2db033477530..23ec97eec71420f137c195f2b6a174caed971800 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 527015edd1d765b393daa31f9682ae76e3063311..3cc3a6d19b6614b75816bfafcce726a95f9cccbd 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 18eaa2b522b383611d434f2665fd0d8e573b37a2..cae45f66795c7b232b79bdaf2ae73bcff8d8918a 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 432e851d1febfecffe1e6dbb65860568dd6a1d4a..049d436f90e01cc29e59e9e9447337625de052b9 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 132a3887b8360e5aa57809d0fbf6f7cc8cfe0bc4..d5bf89b4f37dd87abb5541f08dfd02adab246443 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 c5e26af321ec5d21803cc46804b86843b33a1ec5..930c6d0d7ff262a978f698e54a767f00963c03d3 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 ce069da7be35ca2cb4c0a64ad8b3461a401cb62c..e2d79f4d78f53491f6ea618d335ed1bc312d783d 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 a2f0ff9512d98b37e9b105b9854f12602b2e27aa..b738f20ea2466e98782dec836bf53a587879d77d 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 929b1b4894a94e60d44cada39621a9aa321ba7b9..5cc64115e57d6d89d63160cd017f8d79046a2e01 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 e65a2d926ac6bb89369f36688ea177af0f10e80b..3bea2a0e0440dfc068d435e664f6b85f5691ba6f 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 ea05d899e8a5b6fe084e7bb1f9732ec0e875b2d4..6f7264e07a10594bc3473ce343359568617fa4cb 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 abebf5d6f77514e0d0556c9e1b5d28f080df4074..7e04cec2d9edebc168b4a561ef52ec1ad75ee252 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 9fd000d4345c690d92bc3e622e332bed4381c86c..ac901a06fb376d4f16ec7ae57c3e3981acbd492e 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 5b551e8d2e36b6790c3fdf708787e63d1196a436..36c1251a0b26f39a651c473d1c6dc63c42ddebf8 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 cb70cd1c9d0bfecf02e19098eda57ee4ea18be29..7c6575cabf255ec7ed1054332a67df362802459f 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 ecf0592d4796bc60b1eb738f26fcf248c98a1f84..58eae4f1bff6acf3309b21a0001d2e437f759673 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 ea4cb4520005d96330e34da4cffd5ec6555fe6f1..5acc4254a63c2100c61968b2942d7135b49eea4e 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 5118a37e0c9493d85c17baf752503154df8406ea..6ed7ce9913b4a12a8faa20d60f5a3b39ff7ce095 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 38c6411000c8555a79248ffc75cf237f83e5ea15..2e11b00c63d4697efb5b730a63aadfb1a8985c09 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 13f686415ba3b864c115b74591f068d8c4729dbd..071d047b65d62e005d54b14b0d31b28de54e2f8e 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 f8f8ac0a17fb10f1ad09c49140f2a13924a0766c..774411c9df4201414682fcbd164caeca02cd577b 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 a2acc3387567c23ed748063b5981b9afe5bb7b2c..f8cf47edb7fd30c48d95cfb6dad152d6bf633a57 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 a65ddccc92960746d2063d5882d1f741840dad38..4d9cb18a70e20b344cfac3e4c7c43686f2f1bfac 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 37c7f4dde5f17465beca381b79a81ecbc292e5ee..fededc5b4d6208f974a40fd18b695ee9db6d1c06 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 643c4866db726cb887fa1032c17486df5338f219..c9cc453718169e80766a53e79b83de2a0dee2584 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 372604a1f7f9364048f09800f1d4206c421dd704..26de297049fc131bb553740c85bb93269ded8d07 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 4ccce121285f5d184c511aad24919124d48dde56..e8a8ed1328ddac776b7eae89b9ce0a0cd46472ff 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 a0974c92c8d83b525f0aced13713a22c128ba725..32728313c43d8e7f1702a354a120c7bc4971f82e 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 dae222e46aaa4d49bafabdab2b30f8f59bdfae04..cbbe6b85b29dad8924e61d19c0bbe9adaafe5083 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 d0c6509b3050a6a06b4cbb347192e5dfdef4568f..47ec2de2eb820a438f1af153077631a5bc2ad483 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 2f5d03425380d097fd08bb6406c6b14214a9b5e5..0848ea77b1987ed6fadc6b98b8350df336eeac0c 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 901ac60d430e26401222ab175dec22a7a191102e..34b04f2b06c2837e5b2e13bb9394e662a7c8b063 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 93e175da70eb57872f0ba66f3df4a85bbe08bd26..88bb95a00661159c8af72aabac60db710c222f1a 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 1de461adbe77a3928bbe3db818fb8bcbb8d1811a..0faacd04a43f153059f69e83ccb88a83c597db3a 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 c04cf97127d26843da0251bd649577a99313a509..e8d0a97a4731cb7aecdebaa94cfb879c213b2fd8 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 dc2eb49718ca293c63ad52ef93b2418193b5a5e6..cd0d1f06a4f07d638f2792bcc834a8429ef8113d 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 e8af3f66ae384ed7a0eded4c179dba430d31ab29..7441e12f03baa9b75a76c29122a086d83b19aa50 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 d8e6077deb89cb63fda0a7f4cd65e29bc03b898a..df46d56fe85aed7e369786c36754e6815bb485ef 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 85f5ec095d883d021ea6d374734b630c2e70fcce..db0a3ff173f2faf0a37d078f3d2520572b0c9196 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 6bc36f3d41ed6e2251dccfaba22792559701447c..7b1fc4758cc87ab31ae165159c7d88dfd7d0266e 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 a95f006feb88df861e1c209790ba4c9c865444f6..95503aabc8571d3cfe0640ed67025699e052db6e 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 db47758e487dda4ebdf9c8cee8fc060fc5a8cdec..f50a1ec4e08bbbb06550da2980e55e15e44dcfc2 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 007a4db24a08828d858bcdec4d39a1346f63945f..acbcb22869e9b5fa426e221bf03708bd217de00b 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 dec351f848c099f2eb2f1e99c9db708aecf20074..c3a7fb30a762cdb00239c4ea94eb703396ccf08a 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 9dacfed62333c444aabed9b046c68a0ac8d28146..1c13930f3167938a579ac420866ec66d42694a0b 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 270a0a150c32a8dbb64f73b586e0baf1b5091a38..5b1971013a1722757ebdd4d7ce8bb3a09a196275 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 687bb22a6e59fa9de313c1a6ee4d6a134d941f63..f022f4b5b03bee94fade8a947afbbe309bb79a16 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 178dd0ed53df0b5e52528245dee80c866bc38b62..478f03231945db32f38449956a6876ecf8e8f03d 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 469f12f05a364d6e094df436849b312719b23adf..7b910faeb7ac5c9ed9d59587c2f3ff45de6282ab 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 7560b042b7039595f995007ed10fd251fff93d2b..470471aa389d6590831be10c0d8f3a75cf648dca 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 95a0a819cf15bc0ccebdc3fa076caaab05bc192b..3f771fa7580a4e632e1b1c07a89f97c2f1f29d69 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 632dee8f04112359d9c17063ea77d5ca0c44e23c..80fe8ff95e6cdafef5aa3c36138e39b793d0b4d5 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 9e2d7cb0661fd58f517110e2c7279e75062c26b2..2372674337e40f07618a925d5fdc30f344304cc3 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 c2a2bb4fd600e2343dc64c1f9cc9fbe4f54f9fe6..fd1a17e43c633d797f6d1e0f88ea411bd5fba770 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 c6d79db7079f0a14daacb373050eb30e9f1f6a71..81b83f2cc93afad5bff868a4079ba819d8998a39 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 3d4f2006d6f99a60cf830fec07c53dfda16de1bb..5c7f44367e6275d47df2dc99c093f1760c675fce 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 6e3d490075afe73d1cbb1374b78840687738b072..1c60db4de4f87d3ae1fdb862bd3a4d0ee7d253d1 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 0d7dbb2f1dd5575613f9ffc41fe97ed2a696ef2b..b11c7e45caab815045ece5e7f3aaa8c454d07e66 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 2021a9b9a1118aef85022dd0940edbb1490ce03c..192ff28a571c3bdf541ce8093a810bf830cdcb46 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 30f72c31cc689e2e0d5389e806bd43e1f6c31f21..d4f5b68cc64150d6b31b30bff110e6aef1b49b2b 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 a78f41674f2b6765c06a633a96e65c96bad9f9e9..0ed45d09a6ced54f01a6a63f90394ba7a4795a97 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 d4a56b4d5ebee864e0349dc9ae5343e35cbfbc02..47b806e34f41505a279a52c2e57aa36923061413 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 8c20bd6494db34ed2127b57b5d1f477dc116f145..dc9de80058bd7a5e5829264f49b93b40ceec553a 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 993bc4591cf9805a53ad1fef95dbf45e79cf0786..5a1c8c97f623e5300c203eaa9a4e3cc1b760618b 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 0cef5554bbed891cf1dcf671da6efcd9d53aaa09..9c38cf3f8feb88a455a7b7bcf751f6f43ad2f9d0 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 c890165834d91d92583a9932d999465bfab6920f..8044208dcea457cbaed4d586cc3c3990db5a7135 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 9a70d534b5ad03cfcbbe18b1290411b580f05010..09a523ec2b0256e9a238463a4ebf8f1b101d40a0 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 7cbaf4eb89ed55ffae04a9b31f6754d310af84f2..38528b9cfca269f1f77a48bda427e53f9bc66c91 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 9aa866252e46fb9d6558f7d2ae08603ba73e5970..6df16724bf10a1e724119d68175e6d59952102f2 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 0ee94e30f633929d0d64487f08ac6c8205175fd0..606157dbfd8b9037019d5bd8c23f50a51fc8af26 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 568484afe0dcd29581a532337cfebe861c1f344d..ea07bd92cf1211aeaedbc1e57a9b10b2f22f1527 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 7a852b97917553c7d41ce620862104e788e595a2..f239f1b335e88995e6cfb520f3c23d232aef56ec 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 b25dce072d66abc34f7ba80d8f4a5973a829861e..424ad3e90d1155342d83ef92d8a76d5895821039 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 760c4cc91db80a2e334661f424472fed0ff39caf..4c82eb6caac4eeba6d156ed6cbf7c205e9676f64 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 f36bec7b0e97cbc49414b99efcb74fd8d23373f0..64d636f29edbee865085f144d40ede1049521de6 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 ac9acc7e8c24813296e88484edfc5d6a343b121f..b4c2af6dfc81736f49e30ed8d8b659705c8cf23f 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 4f92baa837fbaff56880d66c9f9886f1d8628b4d..9cdffa0e87c7d9358d61f756b338d77b092a1282 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 53c3881fa6e708f57d877186e4493ed1e43bcdba..17e44c8a396ff7251a2d21a04e9ab741db23a5ef 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 f30d9d3fc9841e3fb801c5f00b0098eff161f63b..7e507835fcd3d854b7eff633deeb860b15d0ee9e 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 0d0837824f82fcab80978f6dae0f2dd4dc72ea8b..220ad7abdeb43f44e8ed08350156e0bc4378ddbb 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 2c28ab0281d67a38b07fc641bd6d6fc3d0f91268..8ea7a68a04101d568a203a65f125cf46fb72a6a0 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 65a153af29df2aefbc0cec575e7ca359fe3ed4e2..07d79555e9c7c86e572fa7f847a3d6ac6ddc6821 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 622ec2651a106d29be3b712aebc5b3571de0fce1..0d32f4cd8e3f864cc5469ab382e424d1ba42ccd0 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 67ec377dad34024a82e99ff5d81e8243d26d90fc..1af4aa4eb72b2f6c13b07d6d0ddb37f52a8882ab 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 cd4eacfe3f94b2203bbf0af45875a61291676db1..585e851f30c00f562e9e10c534cfad4d4df61e8a 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 c1947c64106c42ed25d19f2644b71050d11b3b56..561f4d61efeb810a8e617eb9691412239424be22 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 091dfc2709ccbb8e32395abccb88fff28d564fef..05f602b22c3d48c83cd68eb5dc0957b55acd30bc 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 775067c8ec75b02d43d346c47a022b7604828d78..c50534c9b4e27dfde3091ae5b1e61a16c2abaea7 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 9353109a5ccf05e0fdd7a04133ef9b6d07994aef..03d99442ff86f93993b05016ab6ab7f3cdfe1499 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 0ddcb37426bb5c8b3c9c6323bbf95b93e46fd29c..e74801bf0e2b79cd9e3b7443645411676338d83f 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 8cf321d725acb02595dffb4e00be86f7f49854ad..9c89cf9e035022b79f9fdf3185aa7b4e9aa2ff9b 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 90a9a76cb702ebd7101619352e5341fd687c4e8a..58fc82ad3757d9eb41a6326e976679717ea876de 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 ba2f88b731264ba63ecd6fb0f3004027ff4001ee..2153093ce25163e1371f166c9311353435c7af6b 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 4cfef3cadad5e6629a878f49bcbc55d021b598b7..79668c5764396350a261c14bd9b11823aa74b71f 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 b98e24e815cfef472cf0536b4e0aa72dd7397911..ebf562d46761d85f8e70860afa6661cda776e1ab 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 5451c790420560def55a6114cacd2715d19e0e9d..252ed12981be14ac5e9a03280579d2542052a759 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 302c5eb321c685a033cee26a6cdc8d356dc4a44f..18fee61eb0317f1a60c32bf45d79494dea52bd61 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 9ae1f90bb4300baed6f554319f320e675a94fc37..20a3a8340197efe37816de74af9c0d4f83ad6b09 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 1e617af876bec52c8b5d1d77ed82a19bc821175b..bfd9f14f46da7fdf9593150bdaf2e1c1348f2c6f 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 feab481a6d121ae4457db107b769b9cb4e91a6e8..beeeab7806aa2cca5d939402182b15dd5d07c2af 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 2a25030d0444926afd7eaa7735f4c258cf64426a..1235df3b93964226e1c1c6514cd836c4a3be99ee 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 e6a73210d78e52d792b2beb8ca5e72a67b9e4e33..c9ee6f2f12aa5c6d8870f0df2e1b008f260bba0f 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 f9fc52af24d09260623b95075bbb5a4b96293858..14917cd04c2b33ea6776f9f4d375840e1c1bf7a3 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 d0b3e61ead69f5600348384f10b8795b224a8d31..26517502a79a14f20d5e66e2c7d2336bc8a31fbd 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 4720a2566f7c49c7418b379acb59cb6fb2db49f8..adad843bb174be72d25922b1a1e0cc7fccf8df27 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 d35ca9fbad085c4e58276d5067abdce1b9ffb664..b6dc92cb314a311c60c7413a7c77d8547c723ac9 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 8f1c595def9ff4e4ac5978f55e46380ca7089b7b..5d154a1a040ede36db31f64186c240050ef2ff96 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 2b8a30406a3baeec9061ff3c2727fa11ed0eed17..3e10b3914ce6021b4e77c30adc543108be47a28a 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 a54224fc82b68e164886cf358565199a2aff6d14..47f142d8ec2909df28c7b6b0a364b8782c929531 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 cbbabab6b1d37eae2a4bedc840a9701b19a1929c..fd837ce44d516d7266f143027f66e422e48fef9c 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 d23466728f4c9e7b1c1660a795a386d6f6f151fe..c1a8a6aa3fd0967bef32062a3407fa48ecb34215 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 77d014d2f1e85f8eef3d55f4857b27b3808df1ff..691bc50102378adfac84207a18b441e6a779f48c 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 59a2fa250f62137bbd77a12b7920b3dd81c0d3c8..b2ca9c1077b369ae6b9f50cbe7bd0d8b37e0b6cf 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 1a9b351891a8e7f36752d14557b0cf3fa0ad2924..c9212db61729007f3208582b5634d0270a5dc196 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 65b261d42d2b4a968baf24bb38c8b37759f5ef5c..b0b0053778f4f062f268d7c1171ed37e90569fc0 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 d46ef9d85f9631fa94fd03a51252849a75a112f4..a2cc1c84eaf6f20c98334a42413936eb57cd353f 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 d301ecd186165a81dba729760d0e664e2ab7ca04..36557bb86ab20fe64311143d8df2128d4c968fc8 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 f23ae2d774c8fb4256105ce343921e0c7066bbd9..1da672d4e4e3f484a075b016198bd09151cf0e27 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 306d2aa8011ee3f01c92ab40a0886bae54a23b75..206650cb114f6f39f9f2f18bd8fd5bb8835bcb30 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 8478839894c8e609fdece903ca1f5366bf2e7573..85e5125cf8cafc0fb53a86e669c1d685c9b9c28d 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 5efc98d2a4e87b089c3a0ab7b46a1256733d7111..9866fb7d201c7dd44805fda70482b1bb4bfa015d 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 c500afa7fbc7e003c0574900f6fc5abe8628856d..10eef7d9cb6df1ca267d901c01090f98d5ebfdb7 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 ecb4254ed8d0cf5636af76cd51ba4d7ca497379c..4043e11354e8fe51eb7b89a52ead6e602d5eec69 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 3dc7e9e1dd67a63d2390ceed66e5e8dcff01470e..f7f9d22daabca4be8a8b3ffcd51d154474571680 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 000fa1932c2e113a479467cf71e8492c78782075..7743e51f7aa7b0b753fefd4efe427a3d0d45a7e4 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 3a58b5fa2f210f7055dbe774d514810c2f55c9d4..f977c1f1242634e71c83cb2dcfba728506e69798 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 f7415df12cb43d33f7b21165464d8883d1b2611f..ae87e92061ce02ffac69911ea55dd80b04065f4c 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 c166d7047ab56793ddad8a7c25feea785986c68d..5f6e79185bb02a23cd49d7d083dcb01a2db07008 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 96d75bf96f54df7b099d617e24e74ea3af30fae4..fb22f88278d575c28a27df5b61fc8cea8bc91674 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 73f6bdc62a2dcfb33e744cb97035071b6310cc7d..50e01f87a1dc2f1a71a14ca407c205250d2d9b72 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 cf3d8d0769a5e5ec449a33dc46bd202749af7782..1b8a3037448634bf4f1d11db791152ad285d9802 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 10d1acec6e35420629e1ef818b29abd00f8f5352..ecc845db4b935a88aacb90b5cc541f09537b1433 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 845e0a4b6ac415565c8476d0cf7f3aa5e168d8c9..eeb3898229ec67570b54342321b4098d678b7209 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 4c6552bdecedd88b916dd13cb9efca22043e1293..c991174740cc482708348f7c4f16b46be81fc74a 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 71d50c67dc5dfab1fe5bcb89baae09806929185e..cf26f2bc33a9212050c817ee0d95298059007ca1 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 361ae4ede5a1231aa8946290e472b69f0c268550..20a51b4b78fcc08575c5d034b49954102194c9f4 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 27d4f7c576d9b9307f3234c98da1713e633d7465..76a3954a9c7914b03c13b3f018f6581ac1288668 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 2678db52f8c8378742eb7461f8a0ad68d923082c..3279c5931822bf5632e9316dd885bf9c7a206d2f 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 c2795e475e561421f5c5509788ef106f212b8c5c..f91ec362c41e6444d86ef9e85132e749c15da7f5 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 0f67bcf8e394ae96f994e59a851adbcd38cf1533..6d8545c1967e6f3853d900fe7569bbf151d45b74 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 3bf62bc47faae01cda32e9ddc3193b6b40dd3243..fcef79532336b74f7d0e6ae880446f4fda6c78f6 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 db9179b6352c7ea608cd72389ce6f0710b7941a2..2d15d018375f3938e7f2d48646c36db000edc4bc 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 8a964b2d00378fa9af2984d87cee0eb0bac70778..99cc95aedb8fe10a4836e1536552b98cca5341ef 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 0cf14873f45ce3af0f2587397620fabb7c018e2b..83aba0a9044af62dab310f2dcbb15436f9b07eb2 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 dbe0d15ba56a36e1d0aba26bde96c9283e424774..587c789d82d66bcea6c4474fa979e01c454c4c05 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);