stepan
/
dynare
1
0
Fork 0
Code Issues Pull Requests Packages Projects Releases Wiki Activity

method_of_moments: remove to do list and maintaining authors

covariance-quadratic-approximation
Willi Mutschler 2023-12-13 12:59:32 +01:00
parent c59daa6139
commit 378e38c8c2
No known key found for this signature in database
GPG Key ID: 91E724BF17A73F6D
1 changed files with 0 additions and 46 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

46
matlab/+mom/run.m
View File

@ -96,11 +96,6 @@ function [oo_, options_mom_, M_] = run(bayestopt_, options_, oo_, estim_params_,
% o test_for_deep_parameters_calibration
% o transform_prior_to_laplace_prior
% o warning_config
% -------------------------------------------------------------------------
% Maintaining Author(s):
% o Willi Mutschler (willi@mutschler.eu)
% o Johannes Pfeifer (johannes.pfeifer@unibw.de)
% -------------------------------------------------------------------------
% Copyright © 2020-2023 Dynare Team
%
@ -119,47 +114,6 @@ function [oo_, options_mom_, M_] = run(bayestopt_, options_, oo_, estim_params_,
% You should have received a copy of the GNU General Public License
% along with Dynare. If not, see <https://www.gnu.org/licenses/>.
% -------------------------------------------------------------------------
% TO DO LISTS AND IDEAS
% -------------------------------------------------------------------------
% GENERAL
% - PREPROCESSOR CHANGE CALL TO FUNCTION (SEE ABOVE)
% - document all options in manual
% - document analytic_jacobian better
% - do endogenous_prior_restrictions work?, create test for prior restrictions file
% - implement penalty objective function for optimization
% - test optimizers (what about analytic Jacobians? Also check if mode compute is a string and additional optimizers also a string)
% - factorize mode_compute codes
% - analytic_jacobian with mode_compute 5
% - decide on default mode_compute
% - use same names for variables (e.g. for weighting matrix)
% - mom.objective_function: check the info values and make use of meaningful penalties (which numbers do we use??)
% - add Approximate Bayesian Computation (ABC) option
% - merge mode_compute functions for GMM/SMM and IRF_MATCHING
% GMM/SMM
% - do true Bayesian MCMC sampling and not just penalized
% - speed up pruned_state_space_system (by using doubling with old initial values, hardcoding zeros, other "tricks" used in e.g. nlma)
% - add option to use autocorrelations (we have useautocorr in identification toolbox already)
% - deal with measurement errors (once @wmutschl has implemented this in identification toolbox)
% - display scaled moments
% - enable to use first moments even if prefilter option is set
% IRF_MATCHING/SMM
% - add option to do simulations with extended path
% - add option to do simulations with perfect_foresight and perfect_foresight_with_expectation_errors
% - add option to do simulations with occbin
% - factorize stoch_simul irf codes that are the same as in mom.objective_function
% IRF_MATCHING
% - add analytic_standard_errors and analytic_jacobian (at least for order=1)
% - What about iterating over mode_compute and updating the weighting matrix? Is that also useful for IRF_MATCHING?
% Can we also use optimal_weighting_matrix for IRF_MATCHING or is this done outside of our codes?
% - check all mode compute options (and also optim options)
% - use_penalized_objective_for_hessian
% - do we need bayesian_irf? If not remove as option
% - check order > 1
% - print more info to console
fprintf('\n==== Method of Moments Estimation (%s) ====\n\n',options_mom_.mom.mom_method);