Fixed copyright notices.

parent 4921000f
......@@ -2,7 +2,7 @@ function initial_distribution = auxiliary_initialization(ReducedForm,Y,start,Par
% Evaluates the likelihood of a nonlinear model with a particle filter allowing eventually resampling.
% Copyright (C) 2011-2014 Dynare Team
% Copyright (C) 2011-2017 Dynare Team
%
% This file is part of Dynare (particles module).
%
......
......@@ -3,7 +3,7 @@ function [LIK,lik] = auxiliary_particle_filter(ReducedForm,Y,start,ParticleOptio
% Evaluates the likelihood of a nonlinear model with the auxiliary particle filter
% allowing eventually resampling.
%
% Copyright (C) 2011-2015 Dynare Team
% Copyright (C) 2011-2017 Dynare Team
%
% This file is part of Dynare (particles module).
%
......
......@@ -18,7 +18,7 @@ function [ProposalStateVector,Weights] = conditional_filter_proposal(ReducedForm
%
% NOTES
% The vector "lik" is used to evaluate the jacobian of the likelihood.
% Copyright (C) 2012-2013 Dynare Team
% Copyright (C) 2012-2017 Dynare Team
%
% This file is part of Dynare.
%
......
......@@ -37,7 +37,7 @@ function [LIK,lik] = conditional_particle_filter(ReducedForm,Y,start,ParticleOpt
%
% NOTES
% The vector "lik" is used to evaluate the jacobian of the likelihood.
% Copyright (C) 2009-2010 Dynare Team
% Copyright (C) 2009-2017 Dynare Team
%
% This file is part of Dynare.
%
......
function [StateMu,StateSqrtP,StateWeights] = fit_gaussian_mixture(X,X_weights,StateMu,StateSqrtP,StateWeights,crit,niters,check)
% Copyright (C) 2013 Dynare Team
% Copyright (C) 2013-2017 Dynare Team
%
% This file is part of Dynare.
%
......
......@@ -19,7 +19,7 @@ function IncrementalWeights = gaussian_densities(obs,mut_t,sqr_Pss_t_t,st_t_1,sq
%
% NOTES
% The vector "lik" is used to evaluate the jacobian of the likelihood.
% Copyright (C) 2009-2010 Dynare Team
% Copyright (C) 2009-2017 Dynare Team
%
% This file is part of Dynare.
%
......
......@@ -30,7 +30,7 @@ function [LIK,lik] = gaussian_filter(ReducedForm, Y, start, ParticleOptions, Thr
%
% NOTES
% The vector "lik" is used to evaluate the jacobian of the likelihood.
% Copyright (C) 2009-2015 Dynare Team
% Copyright (C) 2009-2017 Dynare Team
%
% This file is part of Dynare.
%
......
......@@ -19,7 +19,7 @@ function [PredictedStateMean,PredictedStateVarianceSquareRoot,StateVectorMean,St
%
% NOTES
% The vector "lik" is used to evaluate the jacobian of the likelihood.
% Copyright (C) 2009-2012 Dynare Team
% Copyright (C) 2009-2017 Dynare Team
%
% This file is part of Dynare.
%
......
......@@ -21,7 +21,7 @@ function IncrementalWeights = gaussian_mixture_densities(obs,StateMuPrior,State
%
% NOTES
% The vector "lik" is used to evaluate the jacobian of the likelihood.
% Copyright (C) 2009-2012 Dynare Team
% Copyright (C) 2009-2017 Dynare Team
%
% This file is part of Dynare.
%
......
......@@ -35,7 +35,7 @@ function [LIK,lik] = gaussian_mixture_filter(ReducedForm,Y,start,ParticleOptions
%
% NOTES
% The vector "lik" is used to evaluate the jacobian of the likelihood.
% Copyright (C) 2009-2013 Dynare Team
% Copyright (C) 2009-2017 Dynare Team
%
% This file is part of Dynare.
%
......
......@@ -23,7 +23,7 @@ function [StateMuPrior,StateSqrtPPrior,StateWeightsPrior,StateMuPost,StateSqrtPP
%
% NOTES
% The vector "lik" is used to evaluate the jacobian of the likelihood.
% Copyright (C) 2009-2012 Dynare Team
% Copyright (C) 2009-2017 Dynare Team
%
% This file is part of Dynare.
%
......
function State_Particles = importance_sampling(StateMuPost,StateSqrtPPost,StateWeightsPost,numP)
% Copyright (C) 2013 Dynare Team
% Copyright (C) 2013-2017 Dynare Team
%
% This file is part of Dynare.
%
......
function measure = measurement_equations(StateVectors,ReducedForm,ThreadsOptions)
% Copyright (C) 2013 Dynare Team
% Copyright (C) 2013-2017 Dynare Team
%
% This file is part of Dynare.
%
......
......@@ -38,7 +38,7 @@ function new_particles = multivariate_smooth_resampling(particles,weights)
%! @end deftypefn
%@eod:
% Copyright (C) 2012-2013 Dynare Team
% Copyright (C) 2012-2017 Dynare Team
%
% This file is part of Dynare.
%
......
function [c,SqrtVariance,Weights] = mykmeans(x,g,init,cod)
% Copyright (C) 2013 Dynare Team
% Copyright (C) 2013-2017 Dynare Team
%
% This file is part of Dynare.
%
......
function n = neff(w)
% Evaluates the criterion for resampling
% Copyright (C) 2013 Dynare Team
% Copyright (C) 2013-2014 Dynare Team
%
% This file is part of Dynare.
%
......
......@@ -30,7 +30,7 @@ function [LIK,lik] = nonlinear_kalman_filter(ReducedForm, Y, start, ParticleOpti
%
% NOTES
% The vector "lik" is used to evaluate the jacobian of the likelihood.
% Copyright (C) 2009-2015 Dynare Team
% Copyright (C) 2009-2017 Dynare Team
%
% This file is part of Dynare.
%
......
function [prior,likelihood,C,posterior] = probability(mu,sqrtP,prior,X)
% Copyright (C) 2013 Dynare Team
% Copyright (C) 2013-2017 Dynare Team
%
% This file is part of Dynare.
%
......
......@@ -14,7 +14,7 @@ function [density] = probability2(mu,S,X)
%
% NOTES
%
% Copyright (C) 2009-2012 Dynare Team
% Copyright (C) 2009-2017 Dynare Team
%
% This file is part of Dynare.
%
......
function [prior,likelihood,C,posterior] = probability3(mu,sqrtP,prior,X,X_weights)
% Copyright (C) 2013 Dynare Team
% Copyright (C) 2013-2017 Dynare Team
%
% This file is part of Dynare.
%
......
......@@ -36,7 +36,7 @@ function resampled_output = resample(particles,weights,ParticleOptions)
%! @end deftypefn
%@eod:
% Copyright (C) 2011-2013 Dynare Team
% Copyright (C) 2011-2014 Dynare Team
%
% This file is part of Dynare.
%
......
......@@ -30,7 +30,7 @@ function return_resample = residual_resampling(particles,weights,noise)
%! @end deftypefn
%@eod:
% Copyright (C) 2011-2013 Dynare Team
% Copyright (C) 2011-2017 Dynare Team
%
% This file is part of Dynare.
%
......
......@@ -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) 2011-2014 Dynare Team
% Copyright (C) 2011-2015 Dynare Team
%
% This file is part of Dynare (particles module).
%
......
......@@ -101,7 +101,7 @@ function [ys,trend_coeff,exit_flag,info,Model,DynareOptions,BayesInfo,DynareResu
%! @end deftypefn
%@eod:
% Copyright (C) 2013 Dynare Team
% Copyright (C) 2013-2017 Dynare Team
%
% This file is part of Dynare.
%
......
......@@ -15,7 +15,7 @@ function [nodes,weights] = spherical_radial_sigma_points(n)
%
% NOTES
%
% Copyright (C) 2009-2012 Dynare Team
% Copyright (C) 2009-2017 Dynare Team
%
% This file is part of Dynare.
%
......
......@@ -33,7 +33,7 @@ function return_resample = traditional_resampling(particles,weights,noise)
%! @end deftypefn
%@eod:
% Copyright (C) 2011-2013 Dynare Team
% Copyright (C) 2011-2017 Dynare Team
%
% This file is part of Dynare.
%
......
......@@ -34,7 +34,7 @@ function new_particles = univariate_smooth_resampling(weights,particles,number_o
%! @end deftypefn
%@eod:
% Copyright (C) 2012 Dynare Team
% Copyright (C) 2012-2017 Dynare Team
%
% This file is part of Dynare.
%
......
......@@ -14,7 +14,7 @@ function [nodes,W_m,W_c] = unscented_sigma_points(n,ParticleOptions)
%
% NOTES
%
% Copyright (C) 2009-2012 Dynare Team
% Copyright (C) 2009-2017 Dynare Team
%
% This file is part of Dynare.
%
......
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