73 lines
2.4 KiB
Matlab
73 lines
2.4 KiB
Matlab
function new_particles = multivariate_smooth_resampling(particles,weights)
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% Smooth Resampling of the particles.
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%@info:
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%! @deftypefn {Function File} {@var{new_particles} =} multivariate_smooth_resampling (@var{weights}, @var{particles}, @var{number_of_new_particles}, @var{number_of_partitions})
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%! @anchor{particle/multivariate_smooth_resampling}
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%! @sp 1
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%! Smooth Resampling of the particles (multivariate version).
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%! @sp 2
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%! @strong{Inputs}
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%! @sp 1
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%! @table @ @var
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%! @item weights
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%! n*1 vector of doubles, particles' weights.
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%! @item particles
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%! n*1 vector of doubles, particles.
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%! @item number_of_new_particles
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%! Integer scalar.
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%! @item number_of_partitions
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%! Integer scalar.
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%! @end table
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%! @sp 2
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%! @strong{Outputs}
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%! @sp 1
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%! @table @ @var
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%! @item indx
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%! number_of_new_particles*1 vector of doubles, new particles.
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%! @end table
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%! @sp 2
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%! @strong{This function is called by:}
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%! @sp 1
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%! @ref{particle/sequantial_importance_particle_filter}
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%! @sp 2
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%! @strong{This function calls:}
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%! @sp 1
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%! @ref{particle/univariate_smooth_resampling}
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%! @sp 2
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%! @end deftypefn
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%@eod:
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% Copyright © 2012-2017 Dynare Team
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%
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% This file is part of Dynare.
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%
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% Dynare is free software: you can redistribute it and/or modify
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% it under the terms of the GNU General Public License as published by
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% the Free Software Foundation, either version 3 of the License, or
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% (at your option) any later version.
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%
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% Dynare is distributed in the hope that it will be useful,
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% but WITHOUT ANY WARRANTY; without even the implied warranty of
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% MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
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% GNU General Public License for more details.
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%
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% You should have received a copy of the GNU General Public License
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% along with Dynare. If not, see <https://www.gnu.org/licenses/>.
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% AUTHOR(S) frederic DOT karame AT univ DASH lemans DOT fr
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% stephane DOT adjemian AT univ DASH lemans DOT fr
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number_of_particles = length(weights);
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number_of_states = size(particles,2);
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[P,D] = eig(particles'*(bsxfun(@times,1/number_of_particles,particles))) ;
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D = diag(D) ;
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vectors = bsxfun(@times,P,sqrt(D)') ;
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orthogonalized_particles = bsxfun(@rdivide,particles*vectors,D') ;
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new_particles = zeros(number_of_particles,number_of_states) ;
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for j=1:number_of_states
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tout = sortrows( [orthogonalized_particles(:,j) weights],1) ;
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new_particles(:,j) = univariate_smooth_resampling(tout(:,2),tout(:,1),number_of_particles) ;
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end
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new_particles = new_particles*(vectors') ;
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