Drop unused function

matlab/perfect-foresight-models/linear_approximation_accuracy.m

-function err = linear_approximation_accuracy(options_, M_, oo_)
-% Evaluates the accuracy of the linear approximation when solving perfect foresight models, by
-% reporting the max absolute value of the dynamic residuals.
-%
-% INPUTS
-% - options_ [struct] contains various options.
-% - M_       [struct] contains a description of the model.
-% - oo_      [struct] contains results.
-%
-% OUTPUTS
-% - err      [double] n*1 vector, evaluation of the accuracy (n is the number of equations).
-
-% Copyright © 2015-2017 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 <https://www.gnu.org/licenses/>.
-
-lead_lag_incidence = M_.lead_lag_incidence;
-
-ny = M_.endo_nbr;
-
-maximum_lag = M_.maximum_lag;
-
-periods = options_.periods;
-steady_state = oo_.steady_state;
-params = M_.params;
-endo_simul = oo_.endo_simul;
-exo_simul = oo_.exo_simul;
-
-model_dynamic = str2func([M_.fname,'.dynamic']);
-
-residuals = zeros(ny,periods);
-
-Y = endo_simul(:);
-
-i_cols = find(lead_lag_incidence')+(maximum_lag-1)*ny;
-
-for it = (maximum_lag+1):(maximum_lag+periods)
-    residuals(:,it-1) = model_dynamic(Y(i_cols), exo_simul, params, steady_state,it);
-    i_cols = i_cols + ny;
-end
-
-err = transpose(max(abs(transpose(residuals))));
\ No newline at end of file