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Dynare
particles
Commits
21f97c8a
Commit
21f97c8a
authored
Dec 12, 2014
by
Stéphane Adjemian
Browse files
Fixed headers.
parent
f82afdf8
Changes
2
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src/auxiliary_particle_filter.m
View file @
21f97c8a
function
[
LIK
,
lik
]
=
auxiliary_particle_filter
(
ReducedForm
,
Y
,
start
,
DynareOptions
)
% Evaluates the likelihood of a nonlinear model with a particle filter allowing eventually resampling.
%
% INPUTS
% ReducedForm [structure] Matlab's structure describing the reduced form model.
% ReducedForm.measurement.H [double] (pp x pp) variance matrix of measurement errors.
% ReducedForm.state.Q [double] (qq x qq) variance matrix of state errors.
% ReducedForm.state.dr [structure] output of resol.m.
% Y [double] pp*smpl matrix of (detrended) data, where pp is the maximum number of observed variables.
% start [integer] scalar, likelihood evaluation starts at 'start'.
% mf [integer] pp*1 vector of indices.
% number_of_particles [integer] scalar.
%
% OUTPUTS
% LIK [double] scalar, likelihood
% lik [double] vector, density of observations in each period.
%
% REFERENCES
%
% NOTES
% The vector "lik" is used to evaluate the jacobian of the likelihood.
% Copyright (C) 2011-201
3
Dynare Team
% Copyright (C) 2011-201
4
Dynare Team
%
% This file is part of Dynare.
% This file is part of Dynare
(particles module)
.
%
% 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,
% Dynare
particles module
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/>.
persistent
init_flag
mf0
mf1
number_of_particles
persistent
sample_size
number_of_state_variables
number_of_observed_variables
number_of_structural_innovations
...
...
src/sequential_importance_particle_filter.m
View file @
21f97c8a
...
...
@@ -2,7 +2,7 @@ function [LIK,lik] = sequential_importance_particle_filter(ReducedForm,Y,start,P
% Evaluates the likelihood of a nonlinear model with a particle filter (optionally with resampling).
% Copyright (C) 2011-201
3
Dynare Team
% Copyright (C) 2011-201
4
Dynare Team
%
% This file is part of Dynare (particles module).
%
...
...
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