% function [fval,llik,cost_flag,ys,trend_coeff,info] = DsgeLikelihood_hh(xparam1,DynareDataset,DynareOptions,Model,EstimatedParameters,BayesInfo,DynareResults)
% Evaluates the posterior kernel of a dsge model.
%
% INPUTS
% xparam1 [double] vector of model parameters.
% gend [integer] scalar specifying the number of observations.
% data [double] matrix of data
% data_index [cell] cell of column vectors
% number_of_observations [integer]
% no_more_missing_observations [integer]
% OUTPUTS
% fval : value of the posterior kernel at xparam1.
% llik : probabilities at each time point
% cost_flag : zero if the function returns a penalty, one otherwise.
% ys : steady state of original endogenous variables
% trend_coeff :
% info : vector of informations about the penalty:
% 41: one (many) parameter(s) do(es) not satisfied the lower bound
% 42: one (many) parameter(s) do(es) not satisfied the upper bound
%
% SPECIAL REQUIREMENTS
%
% Copyright (C) 2004-2011 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/>.
% Declaration of the penalty as a persistent variable.
% Persistent variable 'penalty' is used to compute an endogenous penalty to
% the value 'fval' when various conditions are encountered. These conditions
% set also 'exit_flag' equal to 0 instead of 1. It is only when
% dsge_likelihood_hh() is called by an newrat() called by
% dynare_estimation_1() that 'exit_flag' is ignored and penalized 'fval' is
% actually used.
% In that case, 'penalty' is properly initialized, at the very end of the
% present function, by a call to dsge_likelihood_hh() made in
% initial_estimation_checks(). If a condition triggers exit_flag ==
% 0, initial_estimation_checks() triggers an error.
% In summary, an initial call to the present function, without triggering
% any condition, guarantees that 'penalty' is properly initialized when needed.
persistentpenalty
% Initialization of the returned variables and others...
fval=[];
ys=[];
trend_coeff=[];
cost_flag=1;
llik=NaN;
info=0;
singularity_flag=0;
ifDynareOptions.block==1
error('DsgeLikelihood_hh:: This routine (called if mode_compute==5) is not compatible with the block option!')
% Try to compute the cholesky decomposition of Q (possible iff Q is positive definite)
[CholQ,testQ]=chol(Q);
iftestQ
% The variance-covariance matrix of the structural innovations is not definite positive. We have to compute the eigenvalues of this matrix in order to build the endogenous penalty.
a=diag(eig(Q));
k=find(a<0);
ifk>0
fval=penalty+sum(-a(k));
exit_flag=0;
info=43;
return
end
end
offset=offset+EstimatedParameters.ncx;
end
% Get the off-diagonal elements of the covariance matrix for the measurement errors. Test if H is positive definite.
% Try to compute the cholesky decomposition of H (possible iff H is positive definite)
[CholH,testH]=chol(H);
iftestH
% The variance-covariance matrix of the measurement errors is not definite positive. We have to compute the eigenvalues of this matrix in order to build the endogenous penalty.
a=diag(eig(H));
k=find(a<0);
ifk>0
fval=penalty+sum(-a(k));
exit_flag=0;
info=44;
return
end
end
offset=offset+EstimatedParameters.ncn;
end
% Update estimated structural parameters in Mode.params.
