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function yf=forcst2(y0,horizon,dr,n)
% function yf=forcst2(y0,horizon,dr,n)
%
% computes forecasts based on first order model solution, given shocks
% drawn from the shock distribution, but not including measurement error
% Inputs:
% - y0 [endo_nbr by maximum_endo_lag] matrix of starting values
% - dr [structure] structure with Dynare decision rules
% - e [horizon by exo_nbr] matrix with shocks
% - n [scalar] number of repetitions
%
% Outputs:
% - yf [horizon+ykmin_ by endo_nbr by n] array of forecasts
%
% Copyright (C) 2008-2017 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/>.
global M_ options_
Sigma_e_ = M_.Sigma_e;
endo_nbr = M_.endo_nbr;
exo_nbr = M_.exo_nbr;
ykmin_ = M_.maximum_endo_lag;
k1 = [ykmin_:-1:1];
k2 = dr.kstate(find(dr.kstate(:,2) <= ykmin_+1),[1 2]);
k2 = k2(:,1)+(ykmin_+1-k2(:,2))*endo_nbr;
% eliminate shocks with 0 variance
i_exo_var = setdiff([1:exo_nbr],find(diag(Sigma_e_) == 0));
nxs = length(i_exo_var);
chol_S = chol(Sigma_e_(i_exo_var,i_exo_var));
if ~isempty(Sigma_e_)
e = randn(nxs,n,horizon);
end
B1 = dr.ghu(:,i_exo_var)*chol_S';
yf = zeros(endo_nbr,horizon+ykmin_,n);
yf(:,1:ykmin_,:,:) = repmat(y0,[1,1,n]);
j = ykmin_*endo_nbr;
for i=ykmin_+(1:horizon)
tempx1 = reshape(yf(:,k1,:),[j,n]);
tempx = tempx1(k2,:);
yf(:,i,:) = dr.ghx*tempx+B1*squeeze(e(:,:,i-ykmin_));
k1 = k1+1;
end
yf(dr.order_var,:,:) = yf;
yf=permute(yf,[2 1 3]);
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