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function [y, info_convergence, endogenousvariablespaths] = extended_path_core(periods,endo_nbr,exo_nbr,positive_var_indx, ...
exo_simul,init,initial_conditions,...
steady_state, ...
debug,order,M_,pfm,algo,solve_algo,stack_solve_algo,...
olmmcp,options_,oo_,initialguess)
% Copyright © 2016-2023 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/>.
ep = options_.ep;
if init% Compute first order solution (Perturbation)...
endo_simul = simult_(M_,options_,initial_conditions,oo_.dr,exo_simul(2:end,:),1);
else
if nargin==19 && ~isempty(initialguess)
% Note that the first column of initialguess should be equal to initial_conditions.
endo_simul = initialguess;
else
endo_simul = [initial_conditions repmat(steady_state,1,periods+1)];
end
end
oo_.endo_simul = endo_simul;
if debug
save ep_test_1.mat endo_simul exo_simul
end
if options_.bytecode && order > 0
error('Option order > 0 of extended_path command is not compatible with bytecode option.')
end
if options_.block && order > 0
error('Option order > 0 of extended_path command is not compatible with block option.')
end
if order == 0
options_.periods = periods;
options_.block = pfm.block;
oo_.endo_simul = endo_simul;
oo_.exo_simul = exo_simul;
oo_.steady_state = steady_state;
options_.lmmcp = olmmcp;
options_.solve_algo = solve_algo;
options_.stack_solve_algo = stack_solve_algo;
[endogenousvariablespaths, info_convergence] = perfect_foresight_solver_core(oo_.endo_simul, oo_.exo_simul, oo_.steady_state, oo_.exo_steady_state, M_, options_);
else
switch(algo)
case 0
[flag, endogenousvariablespaths] = ...
solve_stochastic_perfect_foresight_model(endo_simul, exo_simul, pfm, ep.stochastic.quadrature.nodes, ep.stochastic.order);
case 1
[flag, endogenousvariablespaths] = ...
solve_stochastic_perfect_foresight_model_1(endo_simul, exo_simul, options_, pfm, ep.stochastic.order);
end
info_convergence = ~flag;
end
if ~info_convergence && ~options_.no_homotopy
[info_convergence, endogenousvariablespaths] = extended_path_homotopy(endo_simul, exo_simul, M_, options_, oo_, pfm, ep, order, algo, 2, debug);
end
if info_convergence
y = endogenousvariablespaths(:,2);
else
y = NaN(size(endo_nbr,1));
end
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