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Make sure that no variable is named hessian.

time-shift
Johannes Pfeifer 2015-05-09 15:34:37 +02:00
parent 450520e946
commit e76f81740f
4 changed files with 17 additions and 17 deletions
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16
matlab/dyn_second_order_solver.m
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@ -1,7 +1,7 @@
function dr = dyn_second_order_solver(jacobia,hessian,dr,M_,threads_ABC,threads_BC)
function dr = dyn_second_order_solver(jacobia,hessian_mat,dr,M_,threads_ABC,threads_BC)
%@info:
%! @deftypefn {Function File} {@var{dr} =} dyn_second_order_solver (@var{jacobia},@var{hessian},@var{dr},@var{M_},@var{threads_ABC},@var{threads_BC})
%! @deftypefn {Function File} {@var{dr} =} dyn_second_order_solver (@var{jacobia},@var{hessian_mat},@var{dr},@var{M_},@var{threads_ABC},@var{threads_BC})
%! @anchor{dyn_second_order_solver}
%! @sp 1
%! Computes the second order reduced form of the DSGE model
@ -11,7 +11,7 @@ function dr = dyn_second_order_solver(jacobia,hessian,dr,M_,threads_ABC,threads_
%! @table @ @var
%! @item jacobia
%! Matrix containing the Jacobian of the model
%! @item hessian
%! @item hessian_mat
%! Matrix containing the second order derivatives of the model
%! @item dr
%! Matlab's structure describing the reduced form solution of the model.
@ -73,7 +73,7 @@ function dr = dyn_second_order_solver(jacobia,hessian,dr,M_,threads_ABC,threads_
kk1 = reshape([1:nk^2],nk,nk);
kk1 = kk1(kk,kk);
% reordering second order derivatives
hessian = hessian(:,kk1(:));
hessian_mat = hessian_mat(:,kk1(:));
zx = zeros(np,np);
zu=zeros(np,M_.exo_nbr);
@ -91,7 +91,7 @@ function dr = dyn_second_order_solver(jacobia,hessian,dr,M_,threads_ABC,threads_
zu=[zu; eye(M_.exo_nbr);zeros(M_.exo_det_nbr,M_.exo_nbr)];
[nrzx,nczx] = size(zx);
[rhs, err] = sparse_hessian_times_B_kronecker_C(hessian,zx,threads_BC);
[rhs, err] = sparse_hessian_times_B_kronecker_C(hessian_mat,zx,threads_BC);
mexErrCheck('sparse_hessian_times_B_kronecker_C', err);
rhs = -rhs;
@ -118,7 +118,7 @@ function dr = dyn_second_order_solver(jacobia,hessian,dr,M_,threads_ABC,threads_
%ghxu
%rhs
hu = dr.ghu(nstatic+1:nstatic+nspred,:);
[rhs, err] = sparse_hessian_times_B_kronecker_C(hessian,zx,zu,threads_BC);
[rhs, err] = sparse_hessian_times_B_kronecker_C(hessian_mat,zx,zu,threads_BC);
mexErrCheck('sparse_hessian_times_B_kronecker_C', err);
hu1 = [hu;zeros(np-nspred,M_.exo_nbr)];
@ -136,7 +136,7 @@ function dr = dyn_second_order_solver(jacobia,hessian,dr,M_,threads_ABC,threads_
%ghuu
%rhs
[rhs, err] = sparse_hessian_times_B_kronecker_C(hessian,zu,threads_BC);
[rhs, err] = sparse_hessian_times_B_kronecker_C(hessian_mat,zu,threads_BC);
mexErrCheck('sparse_hessian_times_B_kronecker_C', err);
[B1, err] = A_times_B_kronecker_C(B*dr.ghxx,hu1,threads_ABC);
@ -164,7 +164,7 @@ function dr = dyn_second_order_solver(jacobia,hessian,dr,M_,threads_ABC,threads_
hxx = dr.ghxx(nstatic+[1:nspred],:);
[junk,k2a,k2] = find(M_.lead_lag_incidence(M_.maximum_endo_lag+2,order_var));
k3 = nnz(M_.lead_lag_incidence(1:M_.maximum_endo_lag+1,:))+(1:M_.nsfwrd)';
[B1, err] = sparse_hessian_times_B_kronecker_C(hessian(:,kh(k3,k3)),gu(k2a,:),threads_BC);
[B1, err] = sparse_hessian_times_B_kronecker_C(hessian_mat(:,kh(k3,k3)),gu(k2a,:),threads_BC);
mexErrCheck('sparse_hessian_times_B_kronecker_C', err);
RHS = RHS + jacobia(:,k2)*guu(k2a,:)+B1;

6
matlab/maximize_prior_density.m
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@ -1,4 +1,4 @@
function [xparams,lpd,hessian] = ...
function [xparams,lpd,hessian_mat] = ...
maximize_prior_density(iparams, prior_shape, prior_hyperparameter_1, prior_hyperparameter_2, prior_inf_bound, prior_sup_bound,DynareOptions,DynareModel,BayesInfo,EstimatedParams,DynareResults)
% Maximizes the logged prior density using Chris Sims' optimization routine.
%
@ -13,7 +13,7 @@ function [xparams,lpd,hessian] = ...
% OUTPUTS
% xparams [double] vector, prior mode.
% lpd [double] scalar, value of the logged prior density at the mode.
% hessian [double] matrix, Hessian matrix at the prior mode.
% hessian_mat [double] matrix, Hessian matrix at the prior mode.
% Copyright (C) 2009-2015 Dynare Team
%
@ -32,7 +32,7 @@ function [xparams,lpd,hessian] = ...
% You should have received a copy of the GNU General Public License
% along with Dynare. If not, see <http://www.gnu.org/licenses/>.
[xparams, lpd, exitflag, hessian]=dynare_minimize_objective('minus_logged_prior_density', ...
[xparams, lpd, exitflag, hessian_mat]=dynare_minimize_objective('minus_logged_prior_density', ...
iparams, DynareOptions.mode_compute, DynareOptions, [prior_inf_bound, prior_sup_bound], ...
BayesInfo.name, BayesInfo, [], ...
prior_shape, prior_hyperparameter_1, prior_hyperparameter_2, prior_inf_bound, prior_sup_bound, ...

10
matlab/mode_check.m
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@ -1,8 +1,8 @@
function mode_check(fun,x,hessian,DynareDataset,DatasetInfo,DynareOptions,Model,EstimatedParameters,BayesInfo,BoundsInfo,DynareResults)
function mode_check(fun,x,hessian_mat,DynareDataset,DatasetInfo,DynareOptions,Model,EstimatedParameters,BayesInfo,BoundsInfo,DynareResults)
% Checks the estimated ML mode or Posterior mode.
%@info:
%! @deftypefn {Function File} mode_check (@var{fun}, @var{x}, @var{hessian}, @var{DynareDataset}, @var{DynareOptions}, @var{Model}, @var{EstimatedParameters}, @var{BayesInfo}, @var{DynareResults})
%! @deftypefn {Function File} mode_check (@var{fun}, @var{x}, @var{hessian_mat}, @var{DynareDataset}, @var{DynareOptions}, @var{Model}, @var{EstimatedParameters}, @var{BayesInfo}, @var{DynareResults})
%! @anchor{mode_check}
%! @sp 1
%! Checks the estimated ML mode or Posterior mode by plotting sections of the likelihood/posterior kernel.
@ -58,13 +58,13 @@ function mode_check(fun,x,hessian,DynareDataset,DatasetInfo,DynareOptions,Model,
% along with Dynare. If not, see <http://www.gnu.org/licenses/>.
TeX = DynareOptions.TeX;
if ~isempty(hessian);
[ s_min, k ] = min(diag(hessian));
if ~isempty(hessian_mat);
[ s_min, k ] = min(diag(hessian_mat));
end
fval = feval(fun,x,DynareDataset,DatasetInfo,DynareOptions,Model,EstimatedParameters,BayesInfo,BoundsInfo,DynareResults);
if ~isempty(hessian);
if ~isempty(hessian_mat);
skipline()
disp('MODE CHECK')
skipline()

2
matlab/optimize_prior.m
View File

@ -51,7 +51,7 @@ objective_function_penalty_base = minus_logged_prior_density(xinit, BayesInfo.ps
BayesInfo.p4,DynareOptions,ModelInfo,EstimationInfo,DynareResults);
% Maximization of the prior density
[xparams, lpd, hessian] = ...
[xparams, lpd, hessian_mat] = ...
maximize_prior_density(xinit, BayesInfo.pshape, ...
BayesInfo.p6, ...
BayesInfo.p7, ...