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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,bytecode_flag,order,M,pfm,algo,solve_algo,stack_solve_algo,...
olmmcp,options,oo,initialguess)
% Copyright (C) 2016-2019 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 <http://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==20 && ~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 bytecode_flag && 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.bytecode = bytecode_flag;
options.lmmcp = olmmcp;
options.solve_algo = solve_algo;
options.stack_solve_algo = stack_solve_algo;
tmp = perfect_foresight_solver_core(M, options, oo);
if ~tmp.deterministic_simulation.status
info_convergence = false;
else
info_convergence = true;
end
else
switch(algo)
case 0
[flag, tmp.endo_simul] = ...
solve_stochastic_perfect_foresight_model(endo_simul, exo_simul, pfm, ep.stochastic.quadrature.nodes, ep.stochastic.order);
case 1
[flag, tmp.endo_simul] = ...
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, tmp.endo_simul] = extended_path_homotopy(endo_simul, exo_simul, M, options, oo, pfm, ep, order, algo, 2, debug);
end
if info_convergence
y = tmp.endo_simul(:,2);
else
y = NaN(size(endo_nbr,1));
end
endogenousvariablespaths = tmp.endo_simul;
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