function DynareResults = initial_estimation_checks(xparam1,DynareDataset,Model,EstimatedParameters,DynareOptions,BayesInfo,DynareResults) % function initial_estimation_checks(xparam1,gend,data,data_index,number_of_observations,no_more_missing_observations) % Checks data (complex values, ML evaluation, initial values, BK conditions,..) % % INPUTS % xparam1: vector of parameters to be estimated % gend: scalar specifying the number of observations % data: matrix of data % % OUTPUTS % none % % SPECIAL REQUIREMENTS % none % Copyright (C) 2003-2011 Dynare Team % % This file is part of Dynare. % % Dynare is free software: you can redistribute it and/or modify % it under the terms of the GNU General Public License as published by % the Free Software Foundation, either version 3 of the License, or % (at your option) any later version. % % Dynare is distributed in the hope that it will be useful, % but WITHOUT ANY WARRANTY; without even the implied warranty of % MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the % GNU General Public License for more details. % % You should have received a copy of the GNU General Public License % along with Dynare. If not, see . if DynareDataset.info.nvobs>Model.exo_nbr+EstimatedParameters.nvn error(['initial_estimation_checks:: Estimation can''t take place because there are less shocks than observed variables!']) end if DynareOptions.dsge_var [fval,cost_flag,info] = DsgeVarLikelihood(xparam1,DynareDataset,DynareOptions,Model,EstimatedParameters,BayesInfo,DynareResults); else [fval,cost_flag,ys,trend_coeff,info] = DsgeLikelihood(xparam1,DynareDataset,DynareOptions,Model,EstimatedParameters,BayesInfo,DynareResults); end % when their is an analytical steadystate, check that the values % returned by *_steadystate match with the static model if DynareOptions.steadystate_flag [ys,check] = feval([Model.fname '_steadystate'],... DynareResults.steady_state,... [DynareResults.exo_steady_state; ... DynareResults.exo_det_steady_state]); if size(ys,1) < Model.endo_nbr if length(Model.aux_vars) > 0 ys = add_auxiliary_variables_to_steadystate(ys,Model.aux_vars,... Model.fname,... DynareResults.exo_steady_state,... DynareResults.exo_det_steady_state,... Model.params,... DynareOptions.bytecode); else error([Model.fname '_steadystate.m doesn''t match the model']); end end DynareResults.steady_state = ys; % Check if the steady state obtained from the _steadystate file is a % steady state. check1 = 0; if isfield(DynareOptions,'unit_root_vars') && DynareOptions.diffuse_filter == 0 if isempty(DynareOptions.unit_root_vars) if ~DynareOptions.bytecode check1 = max(abs(feval([Model.fname '_static'],... DynareResults.steady_state,... [DynareResults.exo_steady_state; ... DynareResults.exo_det_steady_state], Model.params))) > DynareOptions.dynatol ; else [info, res] = bytecode('static','evaluate',DynareResults.steady_state,... [DynareResults.exo_steady_state; ... DynareResults.exo_det_steady_state], Model.params); check1 = max(abs(res)) > DynareOptions.dynatol; end if check1 error(['The seadystate values returned by ' Model.fname ... '_steadystate.m don''t solve the static model!' ]) end end end end if info(1) > 0 disp('Error in computing likelihood for initial parameter values') print_info(info, DynareOptions.noprint) end if any(abs(DynareResults.steady_state(BayesInfo.mfys))>1e-9) && (DynareOptions.prefilter==1) disp(['You are trying to estimate a model with a non zero steady state for the observed endogenous']) disp(['variables using demeaned data!']) error('You should change something in your mod file...') end disp(['Initial value of the log posterior (or likelihood): ' num2str(-fval)]);