From 776c247b9b4207d1bd3ae8b59b9efa180740f64d Mon Sep 17 00:00:00 2001
From: Johannes Pfeifer <jpfeifer@gmx.de>
Date: Thu, 28 Sep 2023 11:25:48 +0200
Subject: [PATCH] testsuite: use silent_optimizer option to not clutter meson
log-file
---
tests/TeX/fs2000_corr_ME.mod | 4 +-
.../fs2000_analytic_derivation.mod | 20 +++++-----
tests/arima/mod1a.mod | 2 +-
tests/arima/mod1b.mod | 2 +-
tests/arima/mod1c.mod | 2 +-
tests/arima/mod2a.mod | 2 +-
tests/arima/mod2b.mod | 2 +-
tests/arima/mod2c.mod | 2 +-
tests/bgp/solow-1/solow.mod | 12 +++---
tests/conditional_forecasts/2/fs2000_est.mod | 2 +-
tests/data/mod1a.mod | 2 +-
tests/dates/dseries_interact.mod | 4 +-
tests/dates/fs2000.mod | 2 +-
tests/discretionary_policy/dennis_1_estim.mod | 2 +-
.../dsgevar_forward_calibrated_lambda.mod | 2 +-
.../dsgevar_forward_estimated_lambda.mod | 2 +-
.../estimation/MH_recover/fs2000_recover.mod | 2 +-
.../MH_recover/fs2000_recover_2.mod | 2 +-
.../MH_recover/fs2000_recover_3.mod | 2 +-
.../MH_recover/fs2000_recover_tarb.mod | 2 +-
.../1/fs2000_estimation_conditional.mod | 2 +-
.../1/fs2000_estimation_exact.mod | 2 +-
tests/estimation/fs2000.mod | 2 +-
.../fs2000_MCMC_jumping_covariance.mod | 8 ++--
.../fs2000_calibrated_covariance.mod | 2 +-
.../fs2000_estimated_params_remove.mod | 2 +-
tests/estimation/fs2000_fast.mod | 2 +-
.../fs2000_initialize_from_calib.mod | 2 +-
tests/estimation/fs2000_model_comparison.mod | 2 +-
.../estimation/fs2000_with_weibull_prior.mod | 2 +-
.../heteroskedastic_shocks/fs2000_het.mod | 2 +-
.../fs2000_het_corr.mod | 2 +-
.../fs2000_het_sample_restriction.mod | 2 +-
.../independent_mh/fs2000_independent_mh.mod | 2 +-
...ls2003_endog_prior_restrict_estimation.mod | 2 +-
.../method_of_moments/AFVRR/AFVRR_M0.mod | 2 +-
.../method_of_moments/AFVRR/AFVRR_MFB.mod | 2 +-
.../method_of_moments/AFVRR/AFVRR_MFB_RRA.mod | 2 +-
.../AnScho/AnScho_MoM_common.inc | 2 +-
.../RBC/RBC_MoM_Andreasen.mod | 2 +-
.../method_of_moments/RBC/RBC_MoM_SMM_ME.mod | 2 +-
.../RBC/RBC_MoM_optimizer.mod | 2 +-
.../RBC/RBC_MoM_prefilter.mod | 2 +-
.../fs2000_init_check.mod | 2 +-
tests/estimation/slice/fs2000_slice.mod | 4 +-
.../system_prior_restriction/Gali_2015.mod | 4 +-
.../estimation/t_proposal/fs2000_student.mod | 4 +-
tests/estimation/tune_mh_jscale/fs2000.mod | 2 +-
.../fs2000_filter_step_ahead_ML.mod | 2 +-
.../fs2000_filter_step_ahead_bayesian.mod | 2 +-
.../trend_cycle_decomposition.mod | 2 +-
tests/fs2000/fs2000.mod | 2 +-
tests/fs2000/fs2000_data.mod | 2 +-
tests/fs2000/fs2000_dseries_a.mod | 2 +-
tests/fs2000/fs2000_dseries_b.mod | 2 +-
tests/fs2000/fs2000_missing_data.mod | 2 +-
tests/fs2000/fs2000_particle.mod | 2 +-
tests/fs2000/fs2000_sd.mod | 2 +-
tests/fs2000/fs2000a.mod | 2 +-
tests/gradient/fs2000_numgrad_13.mod | 2 +-
tests/gradient/fs2000_numgrad_15.mod | 2 +-
tests/gradient/fs2000_numgrad_2.mod | 2 +-
tests/gradient/fs2000_numgrad_3.mod | 2 +-
tests/gradient/fs2000_numgrad_5.mod | 2 +-
tests/gsa/ls2003.mod | 2 +-
tests/kalman/block/fs2000.mod | 2 +-
tests/kalman/block/fs2000_missing_data.mod | 2 +-
.../fs2000_estimation_check.inc | 2 +-
.../fs2000ns_estimation_check.inc | 2 +-
tests/kalman/lyapunov/fs2000_lyap.mod | 6 +--
tests/kalman_filter_smoother/algo1.mod | 2 +-
tests/kalman_filter_smoother/algo3.mod | 2 +-
tests/kalman_filter_smoother/algo4a.mod | 2 +-
tests/kalman_filter_smoother/algo4b.mod | 2 +-
tests/kalman_filter_smoother/algoH1.mod | 2 +-
tests/kalman_filter_smoother/algoH3.mod | 2 +-
.../check_variable_dimensions/fs2000.mod | 2 +-
.../check_variable_dimensions/fs2000_ML.mod | 2 +-
.../compare_results_simulation/fs2000.mod | 2 +-
.../compare_results_simulation/fs2000_ML.mod | 2 +-
.../fs2000_ML_loglinear.mod | 4 +-
.../fs2000_loglinear.mod | 2 +-
tests/kalman_filter_smoother/fs2000.mod | 2 +-
tests/kalman_filter_smoother/fs2000a.mod | 2 +-
.../fs2000_kalman_initial.mod | 2 +-
.../fs2000_kalman_initial_2_lag.mod | 2 +-
.../fs2000_corr_me_ml_mcmc/fs2000_corr_ME.mod | 5 ++-
.../minimal_state_space_system/sw_minimal.mod | 4 +-
tests/moments/fs2000_post_moments.mod | 4 +-
.../Trend_loglin_no_prefilt_first_obs_MC.mod | 2 +-
.../Trend_loglin_prefilt_first_obs_MC.mod | 2 +-
.../MCMC/Trend_loglinear_no_prefilter_MC.mod | 2 +-
.../MCMC/Trend_loglinear_prefilter_MC.mod | 2 +-
.../MCMC/Trend_no_prefilter_MC.mod | 2 +-
.../MCMC/Trend_no_prefilter_first_obs_MC.mod | 2 +-
.../MCMC/Trend_prefilter_MC.mod | 2 +-
.../MCMC/Trend_prefilter_first_obs_MC.mod | 2 +-
.../ML/Trend_loglinear_no_prefilter.mod | 2 +-
...Trend_loglinear_no_prefilter_first_obs.mod | 2 +-
.../ML/Trend_loglinear_prefilter.mod | 2 +-
.../Trend_loglinear_prefilter_first_obs.mod | 2 +-
.../ML/Trend_no_prefilter.mod | 2 +-
.../ML/Trend_no_prefilter_first_obs.mod | 2 +-
.../ML/Trend_no_prefilter_selected_var.mod | 2 +-
.../ML/Trend_prefilter.mod | 2 +-
.../ML/Trend_prefilter_first_obs.mod | 2 +-
tests/optimal_policy/OSR/osr_example.mod | 6 +--
.../osr_example_obj_corr_non_stat_vars.mod | 2 +-
.../OSR/osr_example_objective_correctness.mod | 2 +-
.../OSR/osr_example_param_bounds.mod | 2 +-
.../OSR/osr_obj_corr_algo_1.mod | 6 +--
.../OSR/osr_obj_corr_algo_3.mod | 8 ++--
.../OSR/osr_obj_corr_algo_4.mod | 6 +--
.../OSR/osr_obj_corr_algo_7.mod | 8 ++--
.../OSR/osr_obj_corr_algo_8.mod | 8 ++--
.../OSR/osr_obj_corr_algo_9.mod | 8 ++--
.../osr_objective_correctness_anal_deriv.mod | 8 ++--
tests/optimizers/fs2000_1.mod | 2 +-
tests/optimizers/fs2000_10.mod | 2 +-
tests/optimizers/fs2000_101.mod | 2 +-
tests/optimizers/fs2000_102.mod | 2 +-
tests/optimizers/fs2000_12.mod | 2 +-
tests/optimizers/fs2000_2.mod | 2 +-
tests/optimizers/fs2000_3.mod | 2 +-
tests/optimizers/fs2000_4.mod | 2 +-
tests/optimizers/fs2000_4_with_optim.mod | 2 +-
tests/optimizers/fs2000_5.mod | 4 +-
tests/optimizers/fs2000_6.mod | 4 +-
tests/optimizers/fs2000_7.mod | 2 +-
tests/optimizers/fs2000_8.mod | 2 +-
tests/optimizers/fs2000_8_with_optim.mod | 2 +-
tests/optimizers/fs2000_9.mod | 2 +-
tests/optimizers/fs2000_w.mod | 2 +-
tests/parallel/ls2003.mod | 2 +-
tests/particle/dsge_base2.mod | 38 +++++++++----------
tests/particle/dummy_model.mod | 2 +-
tests/pi2004/ireland.mod | 2 +-
.../fs2000_prior_posterior_function.mod | 2 +-
tests/recursive/ls2003.mod | 2 +-
tests/recursive/ls2003_bayesian.mod | 2 +-
tests/recursive/ls2003_bayesian_csv.mod | 2 +-
tests/recursive/ls2003_bayesian_xls.mod | 2 +-
tests/shock_decomposition/fs2000_est.mod | 2 +-
.../fs2000_est_varlist.mod | 2 +-
tests/shock_decomposition/ls2003_plot.mod | 2 +-
tests/smoother2histval/fs2000_smooth.mod | 2 +-
tests/smoother2histval/fs2000_smooth_ML.mod | 2 +-
.../fs2000_smooth_stoch_simul.mod | 2 +-
148 files changed, 219 insertions(+), 216 deletions(-)
diff --git a/tests/TeX/fs2000_corr_ME.mod b/tests/TeX/fs2000_corr_ME.mod
index b4a17fc7cf..b0ebe70fd2 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 a5e6eeec1e..02ce409558 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 9020522def..44462f15ac 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 ba439aa0b0..23ec97eec7 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 527015edd1..3cc3a6d19b 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 18eaa2b522..cae45f6679 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 432e851d1f..049d436f90 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 132a3887b8..d5bf89b4f3 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 c5e26af321..930c6d0d7f 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 ce069da7be..e2d79f4d78 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 a2f0ff9512..b738f20ea2 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 929b1b4894..5cc64115e5 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 e65a2d926a..3bea2a0e04 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 ea05d899e8..6f7264e07a 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 abebf5d6f7..7e04cec2d9 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 9fd000d434..ac901a06fb 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 5b551e8d2e..36c1251a0b 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 cb70cd1c9d..7c6575cabf 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 ecf0592d47..58eae4f1bf 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 ea4cb45200..5acc4254a6 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 5118a37e0c..6ed7ce9913 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 38c6411000..2e11b00c63 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 13f686415b..071d047b65 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 f8f8ac0a17..774411c9df 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 a2acc33875..f8cf47edb7 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 a65ddccc92..4d9cb18a70 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 37c7f4dde5..fededc5b4d 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 643c4866db..c9cc453718 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 372604a1f7..26de297049 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 4ccce12128..e8a8ed1328 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 a0974c92c8..32728313c4 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 dae222e46a..cbbe6b85b2 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 d0c6509b30..47ec2de2eb 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 2f5d034253..0848ea77b1 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 901ac60d43..34b04f2b06 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 93e175da70..88bb95a006 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 1de461adbe..0faacd04a4 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 c04cf97127..e8d0a97a47 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 dc2eb49718..cd0d1f06a4 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 e8af3f66ae..7441e12f03 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 d8e6077deb..df46d56fe8 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 85f5ec095d..db0a3ff173 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 6bc36f3d41..7b1fc4758c 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 a95f006feb..95503aabc8 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 db47758e48..f50a1ec4e0 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 007a4db24a..acbcb22869 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 dec351f848..c3a7fb30a7 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 9dacfed623..1c13930f31 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 270a0a150c..5b1971013a 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 687bb22a6e..f022f4b5b0 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 178dd0ed53..478f032319 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 469f12f05a..7b910faeb7 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 7560b042b7..470471aa38 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 95a0a819cf..3f771fa758 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 632dee8f04..80fe8ff95e 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 9e2d7cb066..2372674337 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 c2a2bb4fd6..fd1a17e43c 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 c6d79db707..81b83f2cc9 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 3d4f2006d6..5c7f44367e 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 6e3d490075..1c60db4de4 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 0d7dbb2f1d..b11c7e45ca 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 2021a9b9a1..192ff28a57 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 30f72c31cc..d4f5b68cc6 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 a78f41674f..0ed45d09a6 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 d4a56b4d5e..47b806e34f 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 8c20bd6494..dc9de80058 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 993bc4591c..5a1c8c97f6 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 0cef5554bb..9c38cf3f8f 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 c890165834..8044208dce 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 9a70d534b5..09a523ec2b 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 7cbaf4eb89..38528b9cfc 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 9aa866252e..6df16724bf 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 0ee94e30f6..606157dbfd 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 568484afe0..ea07bd92cf 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 7a852b9791..f239f1b335 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 b25dce072d..424ad3e90d 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 760c4cc91d..4c82eb6caa 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 f36bec7b0e..64d636f29e 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 ac9acc7e8c..b4c2af6dfc 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 4f92baa837..9cdffa0e87 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 53c3881fa6..17e44c8a39 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 f30d9d3fc9..7e507835fc 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 0d0837824f..220ad7abde 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 2c28ab0281..8ea7a68a04 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 65a153af29..07d79555e9 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 622ec2651a..0d32f4cd8e 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 67ec377dad..1af4aa4eb7 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 cd4eacfe3f..585e851f30 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 c1947c6410..561f4d61ef 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 091dfc2709..05f602b22c 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 775067c8ec..c50534c9b4 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 9353109a5c..03d99442ff 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 0ddcb37426..e74801bf0e 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 8cf321d725..9c89cf9e03 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 90a9a76cb7..58fc82ad37 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 ba2f88b731..2153093ce2 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 4cfef3cada..79668c5764 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 b98e24e815..ebf562d467 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 5451c79042..252ed12981 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 302c5eb321..18fee61eb0 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 9ae1f90bb4..20a3a83401 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 1e617af876..bfd9f14f46 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 feab481a6d..beeeab7806 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 2a25030d04..1235df3b93 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 e6a73210d7..c9ee6f2f12 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 f9fc52af24..14917cd04c 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 d0b3e61ead..26517502a7 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 4720a2566f..adad843bb1 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 d35ca9fbad..b6dc92cb31 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 8f1c595def..5d154a1a04 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 2b8a30406a..3e10b3914c 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 a54224fc82..47f142d8ec 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 cbbabab6b1..fd837ce44d 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 d23466728f..c1a8a6aa3f 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 77d014d2f1..691bc50102 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 59a2fa250f..b2ca9c1077 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 1a9b351891..c9212db617 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 65b261d42d..b0b0053778 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 d46ef9d85f..a2cc1c84ea 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 d301ecd186..36557bb86a 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 f23ae2d774..1da672d4e4 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 306d2aa801..206650cb11 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 8478839894..85e5125cf8 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 5efc98d2a4..9866fb7d20 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 c500afa7fb..10eef7d9cb 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 ecb4254ed8..4043e11354 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 3dc7e9e1dd..f7f9d22daa 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 000fa1932c..7743e51f7a 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 3a58b5fa2f..f977c1f124 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 f7415df12c..ae87e92061 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 c166d7047a..5f6e79185b 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 96d75bf96f..fb22f88278 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 73f6bdc62a..50e01f87a1 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 cf3d8d0769..1b8a303744 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 10d1acec6e..ecc845db4b 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 845e0a4b6a..eeb3898229 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 4c6552bdec..c991174740 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 71d50c67dc..cf26f2bc33 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 361ae4ede5..20a51b4b78 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 27d4f7c576..76a3954a9c 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 2678db52f8..3279c59318 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 c2795e475e..f91ec362c4 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 0f67bcf8e3..6d8545c196 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 3bf62bc47f..fcef795323 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 db9179b635..2d15d01837 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 8a964b2d00..99cc95aedb 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 0cf14873f4..83aba0a904 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 dbe0d15ba5..587c789d82 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);
--
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