stepan
/
dynare
1
0
Fork 0
Code Issues Pull Requests Packages Projects Releases Wiki Activity

Efficiency improvements in first order stochastic simulations (Simulate data in deviation to the steady state and then, 

after the loop, add the steady state using bsxfun routine, which is parallelized in recent version of matlab). Removed
use of M_.maximum_lag.
time-shift
Stéphane Adjemian (Charybdis) 2010-11-18 14:55:07 +01:00
parent 382ab96cde
commit ccf778e63a
1 changed files with 19 additions and 16 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

35
matlab/simult_.m
View File

@ -36,10 +36,15 @@ global M_ options_
iter = size(ex_,1);
y_ = zeros(size(y0,1),iter+M_.maximum_lag);
y_ = zeros(size(y0,1),iter+1);
y_(:,1) = y0;
if ~options_.k_order_solver
if iorder==1
y_(:,1) = y_(:,1) - dr.ys;
end
end
if options_.k_order_solver% Call dynare++ routines.
options_.seed = 77;
ex_ = [zeros(1,M_.exo_nbr); ex_];
@ -62,53 +67,51 @@ if options_.k_order_solver% Call dynare++ routines.
mexErrCheck('dynare_simul_', err);
y_(dr.order_var,:) = y_;
else
k2 = dr.kstate(find(dr.kstate(:,2) <= M_.maximum_lag+1),[1 2]);
k2 = k2(:,1)+(M_.maximum_lag+1-k2(:,2))*M_.endo_nbr;
k2 = dr.kstate(find(dr.kstate(:,2) <= 1+1),[1 2]);
k2 = k2(:,1)+(1+1-k2(:,2))*M_.endo_nbr;
switch iorder
case 1
if isempty(dr.ghu)
for i = 2:iter+M_.maximum_lag
yhat = y_(dr.order_var(k2),i-1)-dr.ys(dr.order_var(k2));
y_(dr.order_var,i) = dr.ys(dr.order_var)+dr.ghx*yhat;
for i = 2:iter+1
yhat = y_(dr.order_var(k2),i-1);
y_(dr.order_var,i) = dr.ghx*yhat;
end
else
for i = 2:iter+M_.maximum_lag
yhat = y_(dr.order_var(k2),i-1)-dr.ys(dr.order_var(k2));
y_(dr.order_var,i) = dr.ys(dr.order_var) + dr.ghx*yhat + dr.ghu*ex_(i-1,:)';
epsilon = dr.ghu*transpose(ex_); clear('ex_');
for i = 2:iter+1
yhat = y_(dr.order_var(k2),i-1);
y_(dr.order_var,i) = dr.ghx*yhat + epsilon(:,i-1);
end
end
y_ = bsxfun(@plus,y_,dr.ys);
case 2
constant = dr.ys(dr.order_var)+.5*dr.ghs2;
if options_.pruning
y__ = y0;
for i = 2:iter+M_.maximum_lag
for i = 2:iter+1
yhat1 = y__(dr.order_var(k2))-dr.ys(dr.order_var(k2));
yhat2 = y_(dr.order_var(k2),i-1)-dr.ys(dr.order_var(k2));
epsilon = ex_(i-1,:)';
[err, abcOut1] = A_times_B_kronecker_C(.5*dr.ghxx,yhat1,options_.threads.kronecker.A_times_B_kronecker_C);
mexErrCheck('A_times_B_kronecker_C', err);
[err, abcOut2] = A_times_B_kronecker_C(.5*dr.ghuu,epsilon,options_.threads.kronecker.A_times_B_kronecker_C);
mexErrCheck('A_times_B_kronecker_C', err);
[err, abcOut3] = A_times_B_kronecker_C(dr.ghxu,yhat1,epsilon,options_.threads.kronecker.A_times_B_kronecker_C);
mexErrCheck('A_times_B_kronecker_C', err);
y_(dr.order_var,i) = constant + dr.ghx*yhat2 + dr.ghu*epsilon ...
+ abcOut1 + abcOut2 + abcOut3;
y__(dr.order_var) = dr.ys(dr.order_var) + dr.ghx*yhat1 + dr.ghu*epsilon;
end
else
for i = 2:iter+M_.maximum_lag
for i = 2:iter+1
yhat = y_(dr.order_var(k2),i-1)-dr.ys(dr.order_var(k2));
epsilon = ex_(i-1,:)';
[err, abcOut1] = A_times_B_kronecker_C(.5*dr.ghxx,yhat,options_.threads.kronecker.A_times_B_kronecker_C);
mexErrCheck('A_times_B_kronecker_C', err);
[err, abcOut2] = A_times_B_kronecker_C(.5*dr.ghuu,epsilon,options_.threads.kronecker.A_times_B_kronecker_C);
mexErrCheck('A_times_B_kronecker_C', err);
[err, abcOut3] = A_times_B_kronecker_C(dr.ghxu,yhat,epsilon,options_.threads.kronecker.A_times_B_kronecker_C);
mexErrCheck('A_times_B_kronecker_C', err);
y_(dr.order_var,i) = constant + dr.ghx*yhat + dr.ghu*epsilon ...
+ abcOut1 + abcOut2 + abcOut3;
end