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- Fixed bugs around analytic derivation. 

- Fixed test routine, eliminating diffuse filter.
- Trapped incompatibility of diffuse filter with analytic derivation.
time-shift
Marco Ratto 2015-04-01 09:00:51 +02:00
parent 4f1725455a
commit 214dc74723
4 changed files with 9 additions and 7 deletions
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2
matlab/dsge_likelihood.m
View File

@ -631,7 +631,7 @@ if analytic_derivation,
analytic_deriv_info={analytic_derivation,DT,DYss,DOm,DH,DP,asy_Hess};
else
analytic_deriv_info={analytic_derivation,DT,DYss,DOm,DH,DP,D2T,D2Yss,D2Om,D2H,D2P};
clear DT DYss DOm DH DP D2T D2Yss D2Om D2H D2P,
clear DT DYss DOm DP D2T D2Yss D2Om D2H D2P,
end
else
analytic_deriv_info={0};

3
matlab/dynare_estimation_init.m
View File

@ -442,6 +442,9 @@ else
end;
if options_.analytic_derivation,
if options_.lik_init == 3,
error('analytic derivation is incompatible with diffuse filter')
end
options_.analytic_derivation = 1;
if ~(exist('sylvester3','file')==2),
dynareroot = strrep(which('dynare'),'dynare.m','');

3
matlab/optimization/dynare_minimize_objective.m
View File

@ -178,9 +178,6 @@ switch minimizer_algorithm
end
[opt_par_values,hessian_mat,gg,fval,invhess] = newrat(objective_function,start_par_value,analytic_grad,crit,nit,0,varargin{:});
%hessian_mat is the plain outer product gradient Hessian
if options_.analytic_derivation %Hessian is already analytic one, reset option
options_.analytic_derivation = ana_deriv;
end
case 6
[opt_par_values, hessian_mat, Scale, fval] = gmhmaxlik(objective_function, start_par_value, ...
Initial_Hessian, options_.mh_jscale, bounds, prior_information.p2, options_.gmhmaxlik, options_.optim_opt, varargin{:});

8
tests/analytic_derivatives/fs2000_analytic_derivation.mod
View File

@ -61,7 +61,7 @@ alp, beta_pdf, 0.356, 0.02;
bet, beta_pdf, 0.993, 0.002;
gam, normal_pdf, 0.0085, 0.003;
mst, normal_pdf, 1.0002, 0.007;
rho, beta_pdf, 0.129, 0.223;
rho, beta_pdf, 0.129, 0.1;
psi, beta_pdf, 0.65, 0.05;
del, beta_pdf, 0.01, 0.005;
stderr e_a, inv_gamma_pdf, 0.035449, inf;
@ -74,5 +74,7 @@ options_.solve_tolf = 1e-12;
estimation(order=1,mode_compute=5,analytic_derivation,kalman_algo=1,datafile=fsdat_simul,nobs=192,mh_replic=0,mh_nblocks=2,mh_jscale=0.8);
estimation(order=1,mode_compute=5,analytic_derivation,kalman_algo=2,datafile=fsdat_simul,nobs=192,mh_replic=0,mh_nblocks=2,mh_jscale=0.8);
estimation(order=1,mode_compute=5,analytic_derivation,kalman_algo=3,datafile=fsdat_simul,nobs=192,mh_replic=0,mh_nblocks=2,mh_jscale=0.8);
estimation(order=1,mode_compute=5,analytic_derivation,kalman_algo=4,datafile=fsdat_simul,nobs=192,mh_replic=0,mh_nblocks=2,mh_jscale=0.8);
estimation(order=1,mode_compute=4,analytic_derivation,kalman_algo=1,datafile=fsdat_simul,nobs=192,mh_replic=0,mh_nblocks=2,mh_jscale=0.8);
estimation(order=1,mode_compute=4,analytic_derivation,kalman_algo=2,datafile=fsdat_simul,nobs=192,mh_replic=0,mh_nblocks=2,mh_jscale=0.8);
//estimation(order=1,mode_compute=5,analytic_derivation,kalman_algo=3,datafile=fsdat_simul,nobs=192,mh_replic=0,mh_nblocks=2,mh_jscale=0.8);
//estimation(order=1,mode_compute=5,analytic_derivation,kalman_algo=4,datafile=fsdat_simul,nobs=192,mh_replic=0,mh_nblocks=2,mh_jscale=0.8);