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Cosmetic change + Added scramble mode (possibility to add noise in the future).

time-shift
Stéphane Adjemian (Charybdis) 2012-01-20 16:39:12 +01:00
parent 58a03937ec
commit 58f4feb6ad
2 changed files with 26 additions and 9 deletions
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33
matlab/ep/extended_path.m
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@ -85,8 +85,9 @@ time_series = zeros(M_.endo_nbr,sample_size);
% Set the covariance matrix of the structural innovations.
variances = diag(M_.Sigma_e);
positive_var_indx = find(variances>0);
covariance_matrix = M_.Sigma_e(positive_var_indx,positive_var_indx);
number_of_structural_innovations = length(covariance_matrix);
effective_number_of_shocks = length(positive_var_indx);
stdd = sqrt(variances(positive_var_indx));
covariance_matrix = M_.Sigma_e(positive_var_indx,positive_var_indx);
covariance_matrix_upper_cholesky = chol(covariance_matrix);
% Set seed.
@ -97,7 +98,7 @@ end
% Simulate shocks.
switch options_.ep.innovation_distribution
case 'gaussian'
oo_.ep.shocks = randn(sample_size,number_of_structural_innovations)*covariance_matrix_upper_cholesky;
oo_.ep.shocks = randn(sample_size,effective_number_of_shocks)*covariance_matrix_upper_cholesky;
otherwise
error(['extended_path:: ' options_.ep.innovation_distribution ' distribution for the structural innovations is not (yet) implemented!'])
end
@ -106,11 +107,16 @@ end
if options_.ep.stochastic.status
switch options_.ep.stochastic.method
case 'tensor'
[r,w] = gauss_hermite_weights_and_nodes(options_.ep.stochastic.nodes);
switch options_.ep.stochastic.ortpol
case 'hermite'
[r,w] = gauss_hermite_weights_and_nodes(options_.ep.stochastic.nodes);
otherwise
error('extended_path:: Unknown orthogonal polynomial option!')
end
if options_.ep.stochastic.order*M_.exo_nbr>1
for i=1:options_.ep.stochastic.order*M_.exo_nbr
rr(i) = {r};
ww(i) = {w};
rr(k) = {r};
ww(k) = {w};
end
rrr = cartesian_product_of_sets(rr{:});
www = cartesian_product_of_sets(ww{:});
@ -140,7 +146,7 @@ if options_.ep.stochastic.status
error('extended_path:: Unknown stochastic_method option!')
end
else
rrr = zeros(1,number_of_structural_innovations);
rrr = zeros(1,effective_number_of_shocks);
www = 1;
nnn = 1;
end
@ -163,8 +169,17 @@ while (t<sample_size)
% Put it in oo_.exo_simul (second line).
oo_.exo_simul(2,positive_var_indx) = shocks;
for s = 1:nnn
for u=1:options_.ep.stochastic.order
oo_.exo_simul(2+u,positive_var_indx) = rrr(s,(((u-1)*M_.exo_nbr)+1):(u*M_.exo_nbr))*covariance_matrix_upper_cholesky;
switch options_.ep.stochastic.ortpol
case 'hermite'
for u=1:options_.ep.stochastic.order
oo_.exo_simul(2+u,positive_var_indx) = rrr(s,(((u-1)*effective_number_of_shocks)+1):(u*effective_number_of_shocks))*covariance_matrix_upper_cholesky;
end
otherwise
error('extended_path:: Unknown orthogonal polynomial option!')
end
if options_.ep.stochastic.order && options_.ep.stochastic.scramble
oo_.exo_simul(2+options_.ep.stochastic.order+1:2+options_.ep.stochastic.order+options_.ep.stochastic.scramble,positive_var_indx) = ...
randn(options_.ep.stochastic.scramble,effective_number_of_shocks)*covariance_matrix_upper_cholesky;
end
if options_.ep.init% Compute first order solution...
initial_path = simult_(initial_conditions,oo_.dr,oo_.exo_simul(2:end,:),1);

2
matlab/global_initialization.m
View File

@ -135,6 +135,8 @@ ep.stack_solve_algo = 4;
% Stochastic extended path related options.
ep.stochastic.status = 0;
ep.stochastic.method = 'tensor';
ep.stochastic.ortpol = 'hermite';
ep.stochastic.scramble = 0;
ep.stochastic.order = 1;
ep.stochastic.nodes = 5;
ep.stochastic.pruned.status = 0;