diff --git a/matlab/Q6_plication.m b/matlab/+pruned_SS/Q6_plication.m
similarity index 100%
rename from matlab/Q6_plication.m
rename to matlab/+pruned_SS/Q6_plication.m
diff --git a/matlab/allVL1.m b/matlab/+pruned_SS/allVL1.m
similarity index 100%
rename from matlab/allVL1.m
rename to matlab/+pruned_SS/allVL1.m
diff --git a/matlab/bivmom.m b/matlab/+pruned_SS/bivmom.m
similarity index 100%
rename from matlab/bivmom.m
rename to matlab/+pruned_SS/bivmom.m
diff --git a/matlab/prodmom.m b/matlab/+pruned_SS/prodmom.m
similarity index 97%
rename from matlab/prodmom.m
rename to matlab/+pruned_SS/prodmom.m
index f54e541d68dde8b5170046baad526e40986493de..ef42f6fe0b674ddb133cefc64965b38062dcdcc4 100644
--- a/matlab/prodmom.m
+++ b/matlab/+pruned_SS/prodmom.m
@@ -73,7 +73,7 @@ if m==2
return
end
rho = V(1,2)/sqrt(V(1,1)*V(2,2));
- y = V(1,1)^(nu(1)/2)*V(2,2)^(nu(2)/2)*bivmom(nu,rho);
+ y = V(1,1)^(nu(1)/2)*V(2,2)^(nu(2)/2)*pruned_SS.bivmom(nu,rho);
return
end
%
diff --git a/matlab/prodmom_deriv.m b/matlab/+pruned_SS/prodmom_deriv.m
similarity index 98%
rename from matlab/prodmom_deriv.m
rename to matlab/+pruned_SS/prodmom_deriv.m
index 2a2271c02b8f8041d9141e63f7a87a04d176f82e..7c7cd69706445790652d02a40b43322f6e48fd87 100644
--- a/matlab/prodmom_deriv.m
+++ b/matlab/+pruned_SS/prodmom_deriv.m
@@ -103,13 +103,13 @@ if m==2
rho = V(1,2)/sqrt(V(1,1)*V(2,2));
if nargout > 1
drho = dC(ii(1),ii(2),:);
- [tmp,dtmp] = bivmom(nu,rho);
+ [tmp,dtmp] = pruned_SS.bivmom(nu,rho);
dy = (nu(1)/2)*V(1,1)^(nu(1)/2-1)*dV(1,1,:) * V(2,2)^(nu(2)/2) * tmp...
+ V(1,1)^(nu(1)/2) * (nu(2)/2)*V(2,2)^(nu(2)/2-1)*dV(2,2,:) * tmp...
+ V(1,1)^(nu(1)/2) * V(2,2)^(nu(2)/2) * dtmp * drho;
dy = reshape(dy,1,size(dV,3));
else
- tmp = bivmom(nu,rho);
+ tmp = pruned_SS.bivmom(nu,rho);
end
y = V(1,1)^(nu(1)/2)*V(2,2)^(nu(2)/2)*tmp;
return
diff --git a/matlab/quadruplication.m b/matlab/+pruned_SS/quadruplication.m
similarity index 100%
rename from matlab/quadruplication.m
rename to matlab/+pruned_SS/quadruplication.m
diff --git a/matlab/pruned_state_space_system.m b/matlab/pruned_state_space_system.m
index bb408bf3f4808d1b83de9d85b4da8a6f1c292fb5..6d71597917c6b11a924752a50858cfb176fab611 100644
--- a/matlab/pruned_state_space_system.m
+++ b/matlab/pruned_state_space_system.m
@@ -424,8 +424,8 @@ if order > 1
%Compute unique fourth order product moments of u, i.e. unique(E[kron(kron(kron(u,u),u),u)],'stable')
u_nbr4 = u_nbr*(u_nbr+1)/2*(u_nbr+2)/3*(u_nbr+3)/4;
if isempty(QPu)
- QPu = quadruplication(u_nbr);
- COMBOS4 = flipud(allVL1(u_nbr, 4)); %all possible (unique) combinations of powers that sum up to four
+ QPu = pruned_SS.quadruplication(u_nbr);
+ COMBOS4 = flipud(pruned_SS.allVL1(u_nbr, 4)); %all possible (unique) combinations of powers that sum up to four
end
E_u_u_u_u = zeros(u_nbr4,1); %only unique entries
if compute_derivs && (stderrparam_nbr+corrparam_nbr>0)
@@ -433,9 +433,9 @@ if order > 1
end
for j4 = 1:size(COMBOS4,1)
if compute_derivs && (stderrparam_nbr+corrparam_nbr>0)
- [E_u_u_u_u(j4), dE_u_u_u_u(j4,:)] = prodmom_deriv(E_uu, 1:u_nbr, COMBOS4(j4,:), dE_uu(:,:,1:(stderrparam_nbr+corrparam_nbr)), dr.derivs.dCorrelation_matrix(:,:,1:(stderrparam_nbr+corrparam_nbr)));
+ [E_u_u_u_u(j4), dE_u_u_u_u(j4,:)] = pruned_SS.prodmom_deriv(E_uu, 1:u_nbr, COMBOS4(j4,:), dE_uu(:,:,1:(stderrparam_nbr+corrparam_nbr)), dr.derivs.dCorrelation_matrix(:,:,1:(stderrparam_nbr+corrparam_nbr)));
else
- E_u_u_u_u(j4) = prodmom(E_uu, 1:u_nbr, COMBOS4(j4,:));
+ E_u_u_u_u(j4) = pruned_SS.prodmom(E_uu, 1:u_nbr, COMBOS4(j4,:));
end
end
E_xfxf_uu = kron(E_xfxf,E_uu');
@@ -670,8 +670,8 @@ if order > 1
% Compute unique sixth-order product moments of u, i.e. unique(E[kron(kron(kron(kron(kron(u,u),u),u),u),u)],'stable')
u_nbr6 = u_nbr*(u_nbr+1)/2*(u_nbr+2)/3*(u_nbr+3)/4*(u_nbr+4)/5*(u_nbr+5)/6;
if isempty(Q6Pu)
- Q6Pu = Q6_plication(u_nbr);
- COMBOS6 = flipud(allVL1(u_nbr, 6)); %all possible (unique) combinations of powers that sum up to six
+ Q6Pu = pruned_SS.Q6_plication(u_nbr);
+ COMBOS6 = flipud(pruned_SS.allVL1(u_nbr, 6)); %all possible (unique) combinations of powers that sum up to six
end
E_u_u_u_u_u_u = zeros(u_nbr6,1); %only unique entries
if compute_derivs && (stderrparam_nbr+corrparam_nbr>0)
@@ -679,9 +679,9 @@ if order > 1
end
for j6 = 1:size(COMBOS6,1)
if compute_derivs && (stderrparam_nbr+corrparam_nbr>0)
- [E_u_u_u_u_u_u(j6), dE_u_u_u_u_u_u(j6,:)] = prodmom_deriv(E_uu, 1:u_nbr, COMBOS6(j6,:), dE_uu(:,:,1:(stderrparam_nbr+corrparam_nbr)), dr.derivs.dCorrelation_matrix(:,:,1:(stderrparam_nbr+corrparam_nbr)));
+ [E_u_u_u_u_u_u(j6), dE_u_u_u_u_u_u(j6,:)] = pruned_SS.prodmom_deriv(E_uu, 1:u_nbr, COMBOS6(j6,:), dE_uu(:,:,1:(stderrparam_nbr+corrparam_nbr)), dr.derivs.dCorrelation_matrix(:,:,1:(stderrparam_nbr+corrparam_nbr)));
else
- E_u_u_u_u_u_u(j6) = prodmom(E_uu, 1:u_nbr, COMBOS6(j6,:));
+ E_u_u_u_u_u_u(j6) = pruned_SS.prodmom(E_uu, 1:u_nbr, COMBOS6(j6,:));
end
end
diff --git a/matlab/resol.m b/matlab/resol.m
index 0726b309d4cfa874122b40bf8284a1de08002ce8..a99d94a26ac570c54f6e79e193d49b4f56560938 100644
--- a/matlab/resol.m
+++ b/matlab/resol.m
@@ -1,18 +1,18 @@
-function [dr, info, M, oo] = resol(check_flag, M, options, oo)
-
+function [dr, info, M_, oo_] = resol(check_flag, M_, options_, oo_)
+%[dr, info, M_, oo_] = resol(check_flag, M_, options_, oo_)
% Computes the perturbation based decision rules of the DSGE model (orders 1 to 3)
%
% INPUTS
% - check_flag [integer] scalar, equal to 0 if all the approximation is required, equal to 1 if only the eigenvalues are to be computed.
-% - M [structure] Matlab's structure describing the model (M_).
-% - options [structure] Matlab's structure describing the current options (options_).
-% - oo [structure] Matlab's structure containing the results (oo_).
+% - M_ [structure] Matlab's structure describing the model
+% - options_ [structure] Matlab's structure describing the current options
+% - oo_ [structure] Matlab's structure containing the results
%
% OUTPUTS
% - dr [structure] Reduced form model.
% - info [integer] scalar or vector, error code.
-% - M [structure] Matlab's structure describing the model (M_).
-% - oo [structure] Matlab's structure containing the results (oo_).
+% - M_ [structure] Matlab's structure describing the model
+% - oo_ [structure] Matlab's structure containing the results
%
% REMARKS
% Possible values for the error codes are:
@@ -49,46 +49,46 @@ function [dr, info, M, oo] = resol(check_flag, M, options, oo)
% You should have received a copy of the GNU General Public License
% along with Dynare. If not, see <https://www.gnu.org/licenses/>.
-if isfield(oo,'dr')
- if isfield(oo.dr,'kstate')
- dr.kstate = oo.dr.kstate;
+if isfield(oo_,'dr')
+ if isfield(oo_.dr,'kstate')
+ dr.kstate = oo_.dr.kstate;
end
- if isfield(oo.dr,'inv_order_var')
- dr.inv_order_var = oo.dr.inv_order_var;
+ if isfield(oo_.dr,'inv_order_var')
+ dr.inv_order_var = oo_.dr.inv_order_var;
end
- if isfield(oo.dr,'order_var')
- dr.order_var = oo.dr.order_var;
+ if isfield(oo_.dr,'order_var')
+ dr.order_var = oo_.dr.order_var;
end
- if isfield(oo.dr,'restrict_var_list')
- dr.restrict_var_list = oo.dr.restrict_var_list;
+ if isfield(oo_.dr,'restrict_var_list')
+ dr.restrict_var_list = oo_.dr.restrict_var_list;
end
- if isfield(oo.dr,'restrict_columns')
- dr.restrict_columns = oo.dr.restrict_columns;
+ if isfield(oo_.dr,'restrict_columns')
+ dr.restrict_columns = oo_.dr.restrict_columns;
end
- if isfield(oo.dr,'obs_var')
- dr.obs_var = oo.dr.obs_var;
+ if isfield(oo_.dr,'obs_var')
+ dr.obs_var = oo_.dr.obs_var;
end
end
-if M.exo_nbr == 0
- oo.exo_steady_state = [] ;
+if M_.exo_nbr == 0
+ oo_.exo_steady_state = [] ;
end
-[dr.ys,M.params,info] = evaluate_steady_state(oo.steady_state,[oo.exo_steady_state; oo.exo_det_steady_state],M,options,~options.steadystate.nocheck);
+[dr.ys,M_.params,info] = evaluate_steady_state(oo_.steady_state,[oo_.exo_steady_state; oo_.exo_det_steady_state],M_,options_,~options_.steadystate.nocheck);
if info(1)
- oo.dr = dr;
+ oo_.dr = dr;
return
end
-if options.loglinear
+if options_.loglinear
threshold = 1e-16;
% Find variables with non positive steady state. Skip auxiliary
% variables for lagges/leaded exogenous variables
- idx = find(dr.ys(get_all_variables_but_lagged_leaded_exogenous(M))<threshold);
+ idx = find(dr.ys(get_all_variables_but_lagged_leaded_exogenous(M_))<threshold);
if ~isempty(idx)
- if options.debug
- variables_with_non_positive_steady_state = M.endo_names{idx};
+ if options_.debug
+ variables_with_non_positive_steady_state = M_.endo_names{idx};
skipline()
fprintf('You are attempting to simulate/estimate a loglinear approximation of a model, but\n')
fprintf('the steady state level of the following variables is not strictly positive:\n')
@@ -111,5 +111,5 @@ if options.loglinear
end
end
-[dr, info] = stochastic_solvers(dr, check_flag, M, options, oo);
-oo.dr = dr;
+[dr, info] = stochastic_solvers(dr, check_flag, M_, options_, oo_);
+oo_.dr = dr;
diff --git a/matlab/stoch_simul.m b/matlab/stoch_simul.m
index 742b19f7ed5bdcd2108bd85049f0223e6a53fc91..864c0bd789d0e595b7cf3f3923eb263377be39e2 100644
--- a/matlab/stoch_simul.m
+++ b/matlab/stoch_simul.m
@@ -1,6 +1,20 @@
function [info, oo_, options_, M_] = stoch_simul(M_, options_, oo_, var_list)
+%[info, oo_, options_, M_] = stoch_simul(M_, options_, oo_, var_list)
+% Computes the stochastic simulations
+%
+% INPUTS
+% - M_ [structure] Matlab's structure describing the model
+% - options_ [structure] Matlab's structure describing the current options
+% - oo_ [structure] Matlab's structure containing the results
+% - var_list [character array] list of endogenous variables specified
+%
+% OUTPUTS
+% - info [integer] scalar or vector, error code.
+% - oo [structure] Matlab's structure containing the results (oo_).
+% - options_ [structure] Matlab's structure describing the current options
+% - M [structure] Matlab's structure describing the model (M_).
-% Copyright © 2001-2021 Dynare Team
+% Copyright © 2001-2023 Dynare Team
%
% This file is part of Dynare.
%