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ep: fixed return of solve_stochastic_perfect_foresight() and solve_stochastic_perfect_foresight_2()

time-shift
Michel Juillard 2015-07-28 17:16:12 +02:00
parent 448bece904
commit 1bd2a1b1c2
1 changed files with 23 additions and 26 deletions
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49
matlab/ep/extended_path.m
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@ -207,12 +207,12 @@ while (t <= sample_size)
exo_simul(2,:) = exo_simul_(M_.maximum_lag+t,:) + ...
shocks((t-2)*replic_nbr+k,:);
initial_conditions = results{k}(:,t-1);
results{k}(:,t) = extended_path_core(ep.periods,endo_nbr,exo_nbr,positive_var_indx, ...
exo_simul,ep.init,initial_conditions,...
maximum_lag,maximum_lead,steady_state, ...
ep.verbosity,bytecode_flag,ep.stochastic.order,...
M_.params,pfm,ep.stochastic.algo,ep.solve_algo,ep.stack_solve_algo,...
options_.lmmcp,options_,oo_);
[results{k}(:,t), info_convergence] = extended_path_core(ep.periods,endo_nbr,exo_nbr,positive_var_indx, ...
exo_simul,ep.init,initial_conditions,...
maximum_lag,maximum_lead,steady_state, ...
ep.verbosity,bytecode_flag,ep.stochastic.order,...
M_.params,pfm,ep.stochastic.algo,ep.solve_algo,ep.stack_solve_algo,...
options_.lmmcp,options_,oo_);
end
else
for k = 1:replic_nbr
@ -223,16 +223,21 @@ while (t <= sample_size)
exo_simul(maximum_lag+1,:) = ...
exo_simul_(maximum_lag+t,:) + shocks((t-2)*replic_nbr+k,:);
initial_conditions = results{k}(:,t-1);
results{k}(:,t) = extended_path_core(ep.periods,endo_nbr,exo_nbr,positive_var_indx, ...
exo_simul,ep.init,initial_conditions,...
maximum_lag,maximum_lead,steady_state, ...
ep.verbosity,bytecode_flag,ep.stochastic.order,...
M_,pfm,ep.stochastic.algo,ep.solve_algo,ep.stack_solve_algo,...
options_.lmmcp,options_,oo_);
[results{k}(:,t), info_convergence] = extended_path_core(ep.periods,endo_nbr,exo_nbr,positive_var_indx, ...
exo_simul,ep.init,initial_conditions,...
maximum_lag,maximum_lead,steady_state, ...
ep.verbosity,bytecode_flag,ep.stochastic.order,...
M_,pfm,ep.stochastic.algo,ep.solve_algo,ep.stack_solve_algo,...
options_.lmmcp,options_,oo_);
end
end
if verbosity
if info_convergence
disp(['Time: ' int2str(t) '. Convergence of the perfect foresight model solver!'])
else
disp(['Time: ' int2str(t) '. No convergence of the perfect foresight model solver!'])
end
end
end% (while) loop over t
dyn_waitbar_close(hh);
@ -263,13 +268,12 @@ end
assignin('base', 'Simulated_time_series', ts);
function y = extended_path_core(periods,endo_nbr,exo_nbr,positive_var_indx, ...
function [y, info_convergence] = extended_path_core(periods,endo_nbr,exo_nbr,positive_var_indx, ...
exo_simul,init,initial_conditions,...
maximum_lag,maximum_lead,steady_state, ...
verbosity,bytecode_flag,order,M,pfm,algo,solve_algo,stack_solve_algo,...
olmmcp,options,oo)
ep = options.ep;
if init% Compute first order solution (Perturbation)...
endo_simul = simult_(initial_conditions,oo.dr,exo_simul(2:end,:),1);
@ -321,23 +325,16 @@ if flag
else
switch(algo)
case 0
[flag,tmp] = ...
[flag,endo_simul] = ...
solve_stochastic_perfect_foresight_model(endo_simul,exo_simul,pfm,ep.stochastic.quadrature.nodes,ep.stochastic.order);
case 1
[flag,tmp] = ...
[flag,endo_simul] = ...
solve_stochastic_perfect_foresight_model_1(endo_simul,exo_simul,options_,pfm,ep.stochastic.order);
end
endo_simul = tmp;
tmp.endo_simul = endo_simul;
info_convergence = ~flag;
end
end
if verbosity
if info_convergence
disp(['Time: ' int2str(t) '. Convergence of the perfect foresight model solver!'])
else
disp(['Time: ' int2str(t) '. No convergence of the perfect foresight model solver!'])
end
end
if info_convergence
y = tmp.endo_simul(:,2);
else