79 lines
3.2 KiB
Matlab
79 lines
3.2 KiB
Matlab
function DynareResults = initial_estimation_checks(objective_function,xparam1,DynareDataset,Model,EstimatedParameters,DynareOptions,BayesInfo,DynareResults)
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% function initial_estimation_checks(xparam1,gend,data,data_index,number_of_observations,no_more_missing_observations)
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% Checks data (complex values, ML evaluation, initial values, BK conditions,..)
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%
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% INPUTS
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% xparam1: vector of parameters to be estimated
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% gend: scalar specifying the number of observations
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% data: matrix of data
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%
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% OUTPUTS
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% DynareResults structure of temporary results
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%
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% SPECIAL REQUIREMENTS
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% none
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% Copyright (C) 2003-2012 Dynare Team
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%
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% This file is part of Dynare.
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%
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% Dynare is free software: you can redistribute it and/or modify
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% it under the terms of the GNU General Public License as published by
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% the Free Software Foundation, either version 3 of the License, or
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% (at your option) any later version.
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%
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% Dynare is distributed in the hope that it will be useful,
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% but WITHOUT ANY WARRANTY; without even the implied warranty of
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% MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
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% GNU General Public License for more details.
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%
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% You should have received a copy of the GNU General Public License
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% along with Dynare. If not, see <http://www.gnu.org/licenses/>.
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if DynareDataset.info.nvobs>Model.exo_nbr+EstimatedParameters.nvn
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error(['initial_estimation_checks:: Estimation can''t take place because there are less declared shocks than observed variables!'])
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end
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if DynareDataset.info.nvobs>find(diag(Model.Sigma_e))+EstimatedParameters.nvn
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error(['initial_estimation_checks:: Estimation can''t take place because too many shocks have been calibrated with a zero variance!'])
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end
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% check if steady state solves static model (except if diffuse_filter == 1)
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[DynareResults.steady_state] = evaluate_steady_state(DynareResults.steady_state,Model,DynareOptions,DynareResults,DynareOptions.diffuse_filter==0);
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% Evaluate the likelihood.
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ana_deriv = DynareOptions.analytic_derivation;
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DynareOptions.analytic_derivation=0;
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[fval,junk1,junk2,a,b,c,d] = feval(objective_function,xparam1,DynareDataset,DynareOptions,Model,EstimatedParameters,BayesInfo,DynareResults);
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DynareOptions.analytic_derivation=ana_deriv;
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if DynareOptions.dsge_var || strcmp(func2str(objective_function),'non_linear_dsge_likelihood')
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info = b;
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else
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info = d;
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end
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% if DynareOptions.mode_compute==5
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% if ~strcmp(func2str(objective_function),'dsge_likelihood')
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% error('Options mode_compute=5 is not compatible with non linear filters or Dsge-VAR models!')
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% end
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% end
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if isnan(fval)
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error('The initial value of the likelihood is NaN')
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elseif imag(fval)
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error('The initial value of the likelihood is complex')
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end
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if info(1) > 0
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disp('Error in computing likelihood for initial parameter values')
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print_info(info, DynareOptions.noprint)
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end
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if any(abs(DynareResults.steady_state(BayesInfo.mfys))>1e-9) && (DynareOptions.prefilter==1)
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disp(['You are trying to estimate a model with a non zero steady state for the observed endogenous'])
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disp(['variables using demeaned data!'])
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error('You should change something in your mod file...')
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end
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disp(['Initial value of the log posterior (or likelihood): ' num2str(-fval)]);
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