55 lines
1.7 KiB
Matlab
55 lines
1.7 KiB
Matlab
function err = linear_approximation_accuracy(options_, M_, oo_)
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% Evaluates the accuracy of the linear approximation when solving perfect foresight models, by
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% reporting the max absolute value of the dynamic residuals.
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%
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% INPUTS
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% - options_ [struct] contains various options.
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% - M_ [struct] contains a description of the model.
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% - oo_ [struct] contains results.
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%
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% OUTPUTS
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% - err [double] n*1 vector, evaluation of the accuracy (n is the number of equations).
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% Copyright © 2015-2017 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 <https://www.gnu.org/licenses/>.
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lead_lag_incidence = M_.lead_lag_incidence;
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ny = M_.endo_nbr;
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maximum_lag = M_.maximum_lag;
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periods = options_.periods;
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steady_state = oo_.steady_state;
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params = M_.params;
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endo_simul = oo_.endo_simul;
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exo_simul = oo_.exo_simul;
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model_dynamic = str2func([M_.fname,'.dynamic']);
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residuals = zeros(ny,periods);
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Y = endo_simul(:);
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i_cols = find(lead_lag_incidence')+(maximum_lag-1)*ny;
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for it = (maximum_lag+1):(maximum_lag+periods)
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residuals(:,it-1) = model_dynamic(Y(i_cols), exo_simul, params, steady_state,it);
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i_cols = i_cols + ny;
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end
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err = transpose(max(abs(transpose(residuals)))); |