function simulations = simul_backward_nonlinear_model(initialconditions, samplesize, DynareOptions, DynareModel, DynareOutput, innovations)

% Simulates a stochastic non linear backward looking model with arbitrary precision (a deterministic solver is used).
%
% INPUTS
% - initial_conditions  [dseries]     initial conditions for the endogenous variables.
% - sample_size         [integer]     scalar, number of periods for the simulation.
% - DynareOptions       [struct]      Dynare's options_ global structure.
% - DynareModel         [struct]      Dynare's M_ global structure.
% - DynareOutput        [struct]      Dynare's oo_ global structure.
% - innovations         [double]      T*q matrix, innovations to be used for the simulation.
%
% OUTPUTS
% - DynareOutput        [struct]      Dynare's oo_ global structure.
%
% REMARKS
% [1] The innovations used for the simulation are saved in DynareOutput.exo_simul, and the resulting paths for the endogenous
%     variables are saved in DynareOutput.endo_simul.
% [2] The last input argument is not mandatory. If absent we use random draws and rescale them with the informations provided
%     through the shocks block.
% [3] If the first input argument is empty, the endogenous variables are initialized with 0, or if available with the informations
%     provided thrtough the histval block.

% Copyright (©) 2012-2022 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/>.

if DynareModel.maximum_lead
    error('Model defined in %s.mod is not backward.', DynareModel.fname)
end

if ~DynareModel.maximum_lag
    error('Model defined in %s.mod is not backward.', DynareModel.fname)
end

if nargin<6
    innovations = [];
end

[initialconditions, samplesize, innovations, DynareOptions, DynareModel, DynareOutput, endonames, exonames, ~, ~, iy1, ~, model_dynamic] = ...
    simul_backward_model_init(initialconditions, samplesize, DynareOptions, DynareModel, DynareOutput, innovations);

[ysim, xsim] = simul_backward_nonlinear_model_(initialconditions, samplesize, DynareOptions, DynareModel, DynareOutput, innovations, iy1, model_dynamic);

simulations = [dseries(ysim', initialconditions.init, endonames(1:DynareModel.orig_endo_nbr)), dseries(xsim, initialconditions.init, exonames)];