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evaluate_smoother.m: pass updated M_.params and oo_ back to base workspace 

Closes #1373
time-shift
Johannes Pfeifer 2017-01-09 18:10:15 +01:00 committed by Stéphane Adjemian (Charybdis)
parent b6a8887da3
commit 5d8d5e90d8
4 changed files with 18 additions and 14 deletions
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5
doc/dynare.texi
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@ -7058,7 +7058,10 @@ Specify the parameter set to use for running the smoother. The
@var{PARAMETER_SET} can take one of the following seven values:
@code{calibration}, @code{prior_mode}, @code{prior_mean},
@code{posterior_mode}, @code{posterior_mean},
@code{posterior_median}, @code{mle_mode}. Default value: @code{posterior_mean} if
@code{posterior_median}, @code{mle_mode}. Note that the parameter
set used in subsequent commands like @code{stoch_simul} will be set to
the specified @code{parameter_set}.
Default value: @code{posterior_mean} if
Metropolis has been run, @code{mle_mode} if MLE has been run.
@item datafile = @var{FILENAME}

7
matlab/evaluate_smoother.m
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@ -1,4 +1,4 @@
function [oo_,options_,bayestopt_,Smoothed_variables_declaration_order_deviation_form]=evaluate_smoother(parameters,var_list,M_,oo_,options_,bayestopt_,estim_params_)
function [oo_,M_,options_,bayestopt_,Smoothed_variables_declaration_order_deviation_form]=evaluate_smoother(parameters,var_list,M_,oo_,options_,bayestopt_,estim_params_)
% Evaluate the smoother at parameters.
%
% INPUTS
@ -21,13 +21,14 @@ function [oo_,options_,bayestopt_,Smoothed_variables_declaration_order_deviation
% - SmoothedMeasurementErrors
% - FilteredVariablesKStepAhead
% - FilteredVariablesKStepAheadVariances
% o M_ [structure] Definition of the model
% o options_ [structure] Options; returns options_.first_obs
% o bayestopt_ [structure] describing the priors; returns fields like bayestopt_.smoother_var_list from the smoother
% o Smoothed_variables_declaration_order_deviation_form
% Smoothed variables from the Kalman smoother in
% order of declaration of variables (M_.endo_names)
% in deviations from their respective mean, i.e.
% without trend and constant part (used for shock_decomposition)
% o options_ [structure] Options; returns options_.first_obs
% o bayestopt_ [structure] describing the priors; returns fields like bayestopt_.smoother_var_list from the smoother
%
% SPECIAL REQUIREMENTS
% None

16
matlab/shock_decomposition.m
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@ -1,4 +1,4 @@
function oo_ = shock_decomposition(M_,oo_,options_,varlist,bayestopt_,estim_params_)
function [oo_,M_] = shock_decomposition(M_,oo_,options_,varlist,bayestopt_,estim_params_)
% function z = shock_decomposition(M_,oo_,options_,varlist)
% Computes shocks contribution to a simulated trajectory. The field set is
% oo_.shock_decomposition. It is a n_var by nshock+2 by nperiods array. The
@ -17,6 +17,8 @@ function oo_ = shock_decomposition(M_,oo_,options_,varlist,bayestopt_,estim_para
%
% OUTPUTS
% oo_: [structure] Storage of results
% M_: [structure] Definition of the model; makes sure that
% M_.params is correctly updated
%
% SPECIAL REQUIREMENTS
% none
@ -69,10 +71,10 @@ end
options_.selected_variables_only = 0; %make sure all variables are stored
options_.plot_priors=0;
[oo,junk1,junk2,Smoothed_Variables_deviation_from_mean] = evaluate_smoother(parameter_set,varlist,M_,oo_,options_,bayestopt_,estim_params_);
[oo_, M_, junk1, junk2, Smoothed_Variables_deviation_from_mean] = evaluate_smoother(parameter_set, varlist, M_, oo_, options_, bayestopt_, estim_params_);
% reduced form
dr = oo.dr;
dr = oo_.dr;
% data reordering
order_var = dr.order_var;
@ -84,10 +86,10 @@ A = dr.ghx;
B = dr.ghu;
% initialization
gend = size(oo.SmoothedShocks.(deblank(M_.exo_names(1,:))),1);
gend = size(oo_.SmoothedShocks.(deblank(M_.exo_names(1,:))),1);
epsilon=NaN(nshocks,gend);
for i=1:nshocks
epsilon(i,:) = oo.SmoothedShocks.(deblank(M_.exo_names(i,:)));
epsilon(i,:) = oo_.SmoothedShocks.(deblank(M_.exo_names(i,:)));
end
z = zeros(endo_nbr,nshocks+2,gend);
@ -95,7 +97,6 @@ z = zeros(endo_nbr,nshocks+2,gend);
z(:,end,:) = Smoothed_Variables_deviation_from_mean;
maximum_lag = M_.maximum_lag;
lead_lag_incidence = M_.lead_lag_incidence;
k2 = dr.kstate(find(dr.kstate(:,2) <= maximum_lag+1),[1 2]);
i_state = order_var(k2(:,1))+(min(i,maximum_lag)+1-k2(:,2))*M_.endo_nbr;
@ -118,9 +119,8 @@ for i=1:gend
z(:,nshocks+1,i) = z(:,nshocks+2,i) - sum(z(:,1:nshocks,i),2);
end
oo_.shock_decomposition = z;
if ~options_.no_graph.shock_decomposition
plot_shock_decomposition(M_,oo_,options_,varlist);
end

4
preprocessor/ComputingTasks.cc
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@ -1662,7 +1662,7 @@ ShockDecompositionStatement::writeOutput(ostream &output, const string &basename
{
options_list.writeOutput(output);
symbol_list.writeOutput("var_list_", output);
output << "oo_ = shock_decomposition(M_,oo_,options_,var_list_,bayestopt_,estim_params_);" << endl;
output << "[oo_,M_]= shock_decomposition(M_,oo_,options_,var_list_,bayestopt_,estim_params_);" << endl;
}
ConditionalForecastStatement::ConditionalForecastStatement(const OptionsList &options_list_arg) :
@ -3191,7 +3191,7 @@ CalibSmootherStatement::writeOutput(ostream &output, const string &basename, boo
symbol_list.writeOutput("var_list_", output);
output << "options_.smoother = 1;" << endl;
output << "options_.order = 1;" << endl;
output << "[oo_,options_,bayestopt_]=evaluate_smoother('calibration',var_list_,M_,oo_,options_,bayestopt_,estim_params_);" << endl;
output << "[oo_,M_,options_,bayestopt_]=evaluate_smoother('calibration',var_list_,M_,oo_,options_,bayestopt_,estim_params_);" << endl;
}
ExtendedPathStatement::ExtendedPathStatement(const OptionsList &options_list_arg)