Commit 80af764e authored by Stéphane Adjemian's avatar Stéphane Adjemian
Browse files

Replaced DynareOptions by ParticleOptions and ThreadsOptions.

parent f4a1f065
function initial_distribution = auxiliary_initialization(ReducedForm,Y,start,DynareOptions)
function initial_distribution = auxiliary_initialization(ReducedForm,Y,start,ParticleOptions,ThreadsOptions)
% Evaluates the likelihood of a nonlinear model with a particle filter allowing eventually resampling.
%
% INPUTS
......@@ -45,7 +45,7 @@ if isempty(start)
end
% Set flag for prunning
%pruning = DynareOptions.particle.pruning;
%pruning = ParticleOptions.pruning;
% Get steady state and mean.
%steadystate = ReducedForm.steadystate;
......@@ -58,7 +58,7 @@ if isempty(init_flag)
mf1 = ReducedForm.mf1;
number_of_observed_variables = length(mf1);
number_of_structural_innovations = length(ReducedForm.Q);
number_of_particles = DynareOptions.particle.number_of_particles;
number_of_particles = ParticleOptions.number_of_particles;
init_flag = 1;
end
......@@ -102,9 +102,9 @@ StateVectors = bsxfun(@plus,StateVectorVarianceSquareRoot*randn(state_variance_r
yhat = bsxfun(@minus,StateVectors,state_variables_steady_state);
%if pruning
% yhat_ = bsxfun(@minus,StateVectors_,state_variables_steady_state);
% [tmp, tmp_] = local_state_space_iteration_2(yhat,zeros(number_of_structural_innovations,number_of_particles),ghx,ghu,constant,ghxx,ghuu,ghxu,yhat_,steadystate,DynareOptions.threads.local_state_space_iteration_2);
% [tmp, tmp_] = local_state_space_iteration_2(yhat,zeros(number_of_structural_innovations,number_of_particles),ghx,ghu,constant,ghxx,ghuu,ghxu,yhat_,steadystate,ThreadsOptions.local_state_space_iteration_2);
%else
tmp = local_state_space_iteration_2(yhat,zeros(number_of_structural_innovations,number_of_particles),ghx,ghu,constant,ghxx,ghuu,ghxu,DynareOptions.threads.local_state_space_iteration_2);
tmp = local_state_space_iteration_2(yhat,zeros(number_of_structural_innovations,number_of_particles),ghx,ghu,constant,ghxx,ghuu,ghxu,ThreadsOptions.local_state_space_iteration_2);
%end
PredictedObservedMean = weights*(tmp(mf1,:)');
PredictionError = bsxfun(@minus,Y(:,t),tmp(mf1,:));
......@@ -113,4 +113,4 @@ PredictedObservedVariance = bsxfun(@times,weights,dPredictedObservedMean)*dPredi
wtilde = exp(-.5*(const_lik+log(det(PredictedObservedVariance))+sum(PredictionError.*(PredictedObservedVariance\PredictionError),1))) ;
tau_tilde = weights.*wtilde ;
tau_tilde = tau_tilde/sum(tau_tilde);
initial_distribution = resample(StateVectors',tau_tilde',DynareOptions)' ;
\ No newline at end of file
initial_distribution = resample(StateVectors',tau_tilde',ParticleOptions)' ;
\ No newline at end of file
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