From 21f97c8a98a610382d0ff4d4680ef7db38af894f Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?St=C3=A9phane=20Adjemian=20=28Charybdis=29?= <stephane.adjemian@univ-lemans.fr> Date: Fri, 12 Dec 2014 18:09:04 +0100 Subject: [PATCH] Fixed headers. --- src/auxiliary_particle_filter.m | 27 ++++----------------- src/sequential_importance_particle_filter.m | 2 +- 2 files changed, 6 insertions(+), 23 deletions(-) diff --git a/src/auxiliary_particle_filter.m b/src/auxiliary_particle_filter.m index e869484..7fb7dce 100644 --- a/src/auxiliary_particle_filter.m +++ b/src/auxiliary_particle_filter.m @@ -1,41 +1,24 @@ 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) 2011-2013 Dynare Team +% Copyright (C) 2011-2014 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 diff --git a/src/sequential_importance_particle_filter.m b/src/sequential_importance_particle_filter.m index 1924138..24b0798 100644 --- a/src/sequential_importance_particle_filter.m +++ b/src/sequential_importance_particle_filter.m @@ -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) 2011-2013 Dynare Team +% Copyright (C) 2011-2014 Dynare Team % % This file is part of Dynare (particles module). % -- GitLab