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Merge branch 'pr#1354'

time-shift
Stéphane Adjemian (Lupi) 2017-01-04 15:12:32 +01:00
parent b946d3c082 2c5b1fed2d
commit c893c0620c
12 changed files with 223 additions and 200 deletions
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20
matlab/DsgeSmoother.m
View File

@ -156,15 +156,7 @@ if options_.lik_init == 1 % Kalman filter
if kalman_algo ~= 2
kalman_algo = 1;
end
if options_.lyapunov_fp == 1
Pstar = lyapunov_symm(T,R*Q*R',options_.lyapunov_fixed_point_tol,options_.qz_criterium,options_.lyapunov_complex_threshold, 3, [], options_.debug);
elseif options_.lyapunov_db == 1
Pstar = disclyap_fast(T,R*Q*R',options_.lyapunov_doubling_tol);
elseif options_.lyapunov_srs == 1
Pstar = lyapunov_symm(T,Q,options_.lyapunov_fixed_point_tol,options_.qz_criterium,options_.lyapunov_complex_threshold, 4, R, options_.debug);
else
Pstar = lyapunov_symm(T,R*Q*R',options_.lyapunov_fixed_point_tol,options_.qz_criterium,options_.lyapunov_complex_threshold, [], [], options_.debug);
end;
Pstar=lyapunov_solver(T,R,Q,options_);
Pinf = [];
elseif options_.lik_init == 2 % Old Diffuse Kalman filter
if kalman_algo ~= 2
@ -210,15 +202,7 @@ elseif options_.lik_init == 5 % Old diffuse Kalman filter only for th
end
R_tmp = R(stable, :);
T_tmp = T(stable,stable);
if options_.lyapunov_fp == 1
Pstar_tmp = lyapunov_symm(T_tmp,R_tmp*Q*R_tmp',options_.lyapunov_fixed_point_tol,options_.qz_criterium,options_.lyapunov_complex_threshold, 3, [], options_.debug);
elseif options_.lyapunov_db == 1
Pstar_tmp = disclyap_fast(T_tmp,R_tmp*Q*R_tmp',options_.lyapunov_doubling_tol);
elseif options_.lyapunov_srs == 1
Pstar_tmp = lyapunov_symm(T_tmp,Q,options_.lyapunov_fixed_point_tol,options_.qz_criterium,options_.lyapunov_complex_threshold, 4, R_tmp, options_.debug);
else
Pstar_tmp = lyapunov_symm(T_tmp,R_tmp*Q*R_tmp',options_.lyapunov_fixed_point_tol,options_.qz_criterium,options_.lyapunov_complex_threshold, [], [], options_.debug);
end
Pstar_tmp=lyapunov_solver(T_tmp,R_tmp,Q,DynareOptions);
Pstar(stable, stable) = Pstar_tmp;
Pinf = [];
end

2
matlab/UnivariateSpectralDensity.m
View File

@ -95,7 +95,7 @@ for i=M_.maximum_lag:-1:2
end
[A,B] = kalman_transition_matrix(oo_.dr,ikx',1:nx,M_.exo_nbr);
[vx, u] = lyapunov_symm(A,B*M_.Sigma_e*B',options_.lyapunov_fixed_point_tol,options_.qz_criterium,options_.lyapunov_complex_threshold,[],[],options_.debug);
[vx, u] = lyapunov_symm(A,B*M_.Sigma_e*B',options_.lyapunov_fixed_point_tol,options_.qz_criterium,options_.lyapunov_complex_threshold,[],options_.debug);
iky = iv(ivar);
if ~isempty(u)
iky = iky(find(any(abs(ghx(iky,:)*u) < options_.Schur_vec_tol,2)));

32
matlab/dsge_likelihood.m
View File

@ -111,7 +111,7 @@ function [fval,info,exit_flag,DLIK,Hess,SteadyState,trend_coeff,Model,DynareOpti
%! @sp 2
%! @strong{This function calls:}
%! @sp 1
%! @ref{dynare_resolve}, @ref{lyapunov_symm}, @ref{compute_Pinf_Pstar}, @ref{kalman_filter_d}, @ref{missing_observations_kalman_filter_d}, @ref{univariate_kalman_filter_d}, @ref{kalman_steady_state}, @ref{getH}, @ref{kalman_filter}, @ref{score}, @ref{AHessian}, @ref{missing_observations_kalman_filter}, @ref{univariate_kalman_filter}, @ref{priordens}
%! @ref{dynare_resolve}, @ref{lyapunov_symm}, @ref{lyapunov_solver}, @ref{compute_Pinf_Pstar}, @ref{kalman_filter_d}, @ref{missing_observations_kalman_filter_d}, @ref{univariate_kalman_filter_d}, @ref{kalman_steady_state}, @ref{getH}, @ref{kalman_filter}, @ref{score}, @ref{AHessian}, @ref{missing_observations_kalman_filter}, @ref{univariate_kalman_filter}, @ref{priordens}
%! @end deftypefn
%@eod:
@ -351,15 +351,7 @@ switch DynareOptions.lik_init
% Use standard kalman filter except if the univariate filter is explicitely choosen.
kalman_algo = 1;
end
if DynareOptions.lyapunov_fp == 1
Pstar = lyapunov_symm(T,R*Q'*R',DynareOptions.lyapunov_fixed_point_tol,DynareOptions.qz_criterium,DynareOptions.lyapunov_complex_threshold, 3, [], DynareOptions.debug);
elseif DynareOptions.lyapunov_db == 1
Pstar = disclyap_fast(T,R*Q*R',DynareOptions.lyapunov_doubling_tol);
elseif DynareOptions.lyapunov_srs == 1
Pstar = lyapunov_symm(T,Q,DynareOptions.lyapunov_fixed_point_tol,DynareOptions.qz_criterium,DynareOptions.lyapunov_complex_threshold, 4, R, DynareOptions.debug);
else
Pstar = lyapunov_symm(T,R*Q*R',DynareOptions.lyapunov_fixed_point_tol,DynareOptions.qz_criterium,DynareOptions.lyapunov_complex_threshold, [], [], DynareOptions.debug);
end;
Pstar=lyapunov_solver(T,R,Q,DynareOptions);
Pinf = [];
a = zeros(mm,1);
Zflag = 0;
@ -471,7 +463,7 @@ switch DynareOptions.lik_init
if err
disp(['dsge_likelihood:: I am not able to solve the Riccati equation, so I switch to lik_init=1!']);
DynareOptions.lik_init = 1;
Pstar = lyapunov_symm(T,R*Q*R',DynareOptions.lyapunov_fixed_point_tol,DynareOptions.qz_criterium,DynareOptions.lyapunov_complex_threshold, [], [], DynareOptions.debug);
Pstar=lyapunov_solver(T,R,Q,DynareOptions);
end
Pinf = [];
a = zeros(mm,1);
@ -491,15 +483,7 @@ switch DynareOptions.lik_init
end
R_tmp = R(stable, :);
T_tmp = T(stable,stable);
if DynareOptions.lyapunov_fp == 1
Pstar_tmp = lyapunov_symm(T_tmp,R_tmp*Q*R_tmp',DynareOptions.lyapunov_fixed_point_tol,DynareOptions.qz_criterium,DynareOptions.lyapunov_complex_threshold, 3, [], DynareOptions.debug);
elseif DynareOptions.lyapunov_db == 1
Pstar_tmp = disclyap_fast(T_tmp,R_tmp*Q*R_tmp',DynareOptions.lyapunov_doubling_tol);
elseif DynareOptions.lyapunov_srs == 1
Pstar_tmp = lyapunov_symm(T_tmp,Q,DynareOptions.lyapunov_fixed_point_tol,DynareOptions.qz_criterium,DynareOptions.lyapunov_complex_threshold, 4, R_tmp, DynareOptions.debug);
else
Pstar_tmp = lyapunov_symm(T_tmp,R_tmp*Q*R_tmp',DynareOptions.qz_criterium,DynareOptions.qz_criterium,DynareOptions.lyapunov_complex_threshold, [], [], DynareOptions.debug);
end
Pstar_tmp=lyapunov_solver(T_tmp,R_tmp,Q,DynareOptions);
Pstar(stable, stable) = Pstar_tmp;
Pinf = [];
a = zeros(mm,1);
@ -580,14 +564,14 @@ if analytic_derivation,
for i=1:EstimatedParameters.nvx
k =EstimatedParameters.var_exo(i,1);
DQ(k,k,i) = 2*sqrt(Q(k,k));
dum = lyapunov_symm(T,DOm(:,:,i),DynareOptions.lyapunov_fixed_point_tol,DynareOptions.qz_criterium,DynareOptions.lyapunov_complex_threshold,[],[],DynareOptions.debug);
dum = lyapunov_symm(T,DOm(:,:,i),DynareOptions.lyapunov_fixed_point_tol,DynareOptions.qz_criterium,DynareOptions.lyapunov_complex_threshold,[],DynareOptions.debug);
% kk = find(abs(dum) < 1e-12);
% dum(kk) = 0;
DP(:,:,i)=dum;
if full_Hess
for j=1:i,
jcount=jcount+1;
dum = lyapunov_symm(T,dyn_unvech(D2Om(:,jcount)),DynareOptions.lyapunov_fixed_point_tol,DynareOptions.qz_criterium,DynareOptions.lyapunov_complex_threshold,[],[],DynareOptions.debug);
dum = lyapunov_symm(T,dyn_unvech(D2Om(:,jcount)),DynareOptions.lyapunov_fixed_point_tol,DynareOptions.qz_criterium,DynareOptions.lyapunov_complex_threshold,[],DynareOptions.debug);
% kk = (abs(dum) < 1e-12);
% dum(kk) = 0;
D2P(:,jcount)=dyn_vech(dum);
@ -607,7 +591,7 @@ if analytic_derivation,
offset = offset + EstimatedParameters.nvn;
if DynareOptions.lik_init==1,
for j=1:EstimatedParameters.np
dum = lyapunov_symm(T,DT(:,:,j+offset)*Pstar*T'+T*Pstar*DT(:,:,j+offset)'+DOm(:,:,j+offset),DynareOptions.lyapunov_fixed_point_tol,DynareOptions.qz_criterium,DynareOptions.lyapunov_complex_threshold,[],[],DynareOptions.debug);
dum = lyapunov_symm(T,DT(:,:,j+offset)*Pstar*T'+T*Pstar*DT(:,:,j+offset)'+DOm(:,:,j+offset),DynareOptions.lyapunov_fixed_point_tol,DynareOptions.qz_criterium,DynareOptions.lyapunov_complex_threshold,[],DynareOptions.debug);
% kk = find(abs(dum) < 1e-12);
% dum(kk) = 0;
DP(:,:,j+offset)=dum;
@ -621,7 +605,7 @@ if analytic_derivation,
D2Tij = reshape(D2T(:,jcount),size(T));
D2Omij = dyn_unvech(D2Om(:,jcount));
tmp = D2Tij*Pstar*T' + T*Pstar*D2Tij' + DTi*DPj*T' + DTj*DPi*T' + T*DPj*DTi' + T*DPi*DTj' + DTi*Pstar*DTj' + DTj*Pstar*DTi' + D2Omij;
dum = lyapunov_symm(T,tmp,DynareOptions.lyapunov_fixed_point_tol,DynareOptions.qz_criterium,DynareOptions.lyapunov_complex_threshold,[],[],DynareOptions.debug);
dum = lyapunov_symm(T,tmp,DynareOptions.lyapunov_fixed_point_tol,DynareOptions.qz_criterium,DynareOptions.lyapunov_complex_threshold,[],DynareOptions.debug);
% dum(abs(dum)<1.e-12) = 0;
D2P(:,jcount) = dyn_vech(dum);
% D2P(:,:,j+offset,i) = dum;

2
matlab/dsge_var_likelihood.m
View File

@ -187,7 +187,7 @@ end
%------------------------------------------------------------------------------
% Compute the theoretical second order moments
tmp0 = lyapunov_symm(T,R*Q*R',DynareOptions.lyapunov_fixed_point_tol,DynareOptions.qz_criterium,DynareOptions.lyapunov_complex_threshold, [], [], DynareOptions.debug);
tmp0 = lyapunov_symm(T,R*Q*R',DynareOptions.lyapunov_fixed_point_tol,DynareOptions.qz_criterium,DynareOptions.lyapunov_complex_threshold, [], DynareOptions.debug);
mf = BayesInfo.mf1;
% Get the non centered second order moments

6
matlab/getJJ.m
View File

@ -102,7 +102,7 @@ else
% return
% end
m = length(A);
GAM = lyapunov_symm(A,B*M_.Sigma_e*B',options_.lyapunov_fixed_point_tol,options_.qz_criterium,options_.lyapunov_complex_threshold,1,[],options_.debug);
GAM = lyapunov_symm(A,B*M_.Sigma_e*B',options_.lyapunov_fixed_point_tol,options_.qz_criterium,options_.lyapunov_complex_threshold,1,options_.debug);
k = find(abs(GAM) < 1e-12);
GAM(k) = 0;
% if useautocorr,
@ -116,7 +116,7 @@ else
% end
% XX = lyapunov_symm_mr(A,BB,options_.qz_criterium,options_.lyapunov_complex_threshold,0);
for j=1:length(indexo),
dum = lyapunov_symm(A,dOm(:,:,j),options_.lyapunov_fixed_point_tol,options_.qz_criterium,options_.lyapunov_complex_threshold,2,[],options_.debug);
dum = lyapunov_symm(A,dOm(:,:,j),options_.lyapunov_fixed_point_tol,options_.qz_criterium,options_.lyapunov_complex_threshold,2,options_.debug);
% dum = XX(:,:,j);
k = find(abs(dum) < 1e-12);
dum(k) = 0;
@ -141,7 +141,7 @@ else
end
nexo = length(indexo);
for j=1:length(indx),
dum = lyapunov_symm(A,dA(:,:,j+nexo)*GAM*A'+A*GAM*dA(:,:,j+nexo)'+dOm(:,:,j+nexo),options_.lyapunov_fixed_point_tol,options_.qz_criterium,options_.lyapunov_complex_threshold,2,[],options_.debug);
dum = lyapunov_symm(A,dA(:,:,j+nexo)*GAM*A'+A*GAM*dA(:,:,j+nexo)'+dOm(:,:,j+nexo),options_.lyapunov_fixed_point_tol,options_.qz_criterium,options_.lyapunov_complex_threshold,2,options_.debug);
% dum = XX(:,:,j);
k = find(abs(dum) < 1e-12);
dum(k) = 0;

2
matlab/get_variance_of_endogenous_variables.m
View File

@ -45,7 +45,7 @@ n = length(i_var);
[A,B] = kalman_transition_matrix(dr,nstatic+(1:nspred),1:nc,M_.exo_nbr);
[vx,u] = lyapunov_symm(A,B*Sigma_e*B',options_.lyapunov_fixed_point_tol,options_.qz_criterium,options_.lyapunov_complex_threshold, [], [], options_.debug);
[vx,u] = lyapunov_symm(A,B*Sigma_e*B',options_.lyapunov_fixed_point_tol,options_.qz_criterium,options_.lyapunov_complex_threshold, [], options_.debug);
if size(u,2) > 0
i_stat = find(any(abs(ghx*u) < options_.Schur_vec_tol,2)); %only set those variances of objective function for which variance is finite

186
matlab/lyapunov_solver.m Normal file
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@ -0,0 +1,186 @@
function P=lyapunov_solver(T,R,Q,DynareOptions) % --*-- Unitary tests --*--
% function P=lyapunov_solver(T,R,Q,DynareOptions)
% Solves the Lyapunov equation P-T*P*T' = R*Q*R' arising in a state-space
% system, where P is the variance of the states
%
% Inputs
% T [double] n*n matrix.
% R [double] n*m matrix.
% Q [double] m*m matrix.
% DynareOptions [structure] Dynare options
%
% Outputs
% P [double] n*n matrix.
%
% Algorithms
% Default, if none of the other algorithms is selected:
% Reordered Schur decomposition (Bartels-Stewart algorithm)
% DynareOptions.lyapunov_fp == 1
% iteration-based fixed point algorithm
% DynareOptions.lyapunov_db == 1
% doubling algorithm
% DynareOptions.lyapunov_srs == 1
% Square-root solver for discrete-time Lyapunov equations (requires Matlab System Control toolbox
% or Octave control package)
% Copyright (C) 2016 Dynare Team
%
% This file is part of Dynare.
%
% Dynare is free software: you can redistribute it and/or modify
% it under the terms of the GNU General Public License as published by
% the Free Software Foundation, either version 3 of the License, or
% (at your option) any later version.
%
% Dynare is distributed in the hope that it will be useful,
% but WITHOUT ANY WARRANTY; without even the implied warranty of
% MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
% GNU General Public License for more details.
%
% You should have received a copy of the GNU General Public License
% along with Dynare. If not, see <http://www.gnu.org/licenses/>.
if DynareOptions.lyapunov_fp == 1
P = lyapunov_symm(T,R*Q'*R',DynareOptions.lyapunov_fixed_point_tol,DynareOptions.qz_criterium,DynareOptions.lyapunov_complex_threshold, 3, DynareOptions.debug);
elseif DynareOptions.lyapunov_db == 1
[P, errorflag] = disclyap_fast(T,R*Q*R',DynareOptions.lyapunov_doubling_tol);
if errorflag %use Schur-based method
P = lyapunov_symm(T,R*Q*R',DynareOptions.lyapunov_fixed_point_tol,DynareOptions.qz_criterium,DynareOptions.lyapunov_complex_threshold, [], DynareOptions.debug);
end
elseif DynareOptions.lyapunov_srs == 1
% works only with Matlab System Control toolbox or Octave control package,
if isoctave
if ~user_has_octave_forge_package('control')
error('lyapunov=square_root_solver not available; you must install the control package from Octave Forge')
end
else
if ~user_has_matlab_license('control_toolbox')
error('lyapunov=square_root_solver not available; you must install the control system toolbox')
end
end
chol_Q = R*chol(Q,'lower');
R_P = dlyapchol(T,chol_Q);
P = R_P' * R_P;
else
P = lyapunov_symm(T,R*Q*R',DynareOptions.lyapunov_fixed_point_tol,DynareOptions.qz_criterium,DynareOptions.lyapunov_complex_threshold, [], DynareOptions.debug);
end;
%@test:1
%$ t = NaN(10,1);
%$ options_.lyapunov_complex_threshold = 1e-15;
%$ options_.qz_zero_threshold = 1e-6;
%$ options_.qz_criterium=1-options_.qz_zero_threshold;
%$ options_.lyapunov_fixed_point_tol = 1e-10;
%$ options_.lyapunov_doubling_tol = 1e-16;
%$ options_.debug=0;
%$
%$ n_small=8;
%$ m_small=10;
%$ T_small=randn(n_small,n_small);
%$ T_small=0.99*T_small/max(abs(eigs(T_small)));
%$ tmp2=randn(m_small,m_small);
%$ Q_small=tmp2*tmp2';
%$ R_small=randn(n_small,m_small);
%$
%$ n_large=9;
%$ m_large=11;
%$ T_large=randn(n_large,n_large);
%$ T_large=0.99*T_large/max(abs(eigs(T_large)));
%$ tmp2=randn(m_large,m_large);
%$ Q_large=tmp2*tmp2';
%$ R_large=randn(n_large,m_large);
%$
%$ % DynareOptions.lyapunov_fp == 1
%$ options_.lyapunov_fp = 1;
%$ try
%$ Pstar1_small = lyapunov_solver(T_small,R_small,Q_small,options_);
%$ Pstar1_large = lyapunov_solver(T_large,R_large,Q_large,options_);
%$ t(1) = 1;
%$ catch
%$ t(1) = 0;
%$ end
%$
%$ % Dynareoptions.lyapunov_db == 1
%$ options_.lyapunov_fp = 0;
%$ options_.lyapunov_db = 1;
%$ try
%$ Pstar2_small = lyapunov_solver(T_small,R_small,Q_small,options_);
%$ Pstar2_large = lyapunov_solver(T_large,R_large,Q_large,options_);
%$ t(2) = 1;
%$ catch
%$ t(2) = 0;
%$ end
%$
%$ % Dynareoptions.lyapunov_srs == 1
%$ if (isoctave && user_has_octave_forge_package('control')) || (~isoctave && user_has_matlab_license('control_toolbox'))
%$ options_.lyapunov_db = 0;
%$ options_.lyapunov_srs = 1;
%$ try
%$ Pstar3_small = lyapunov_solver(T_small,R_small,Q_small,options_);
%$ Pstar3_large = lyapunov_solver(T_large,R_large,Q_large,options_);
%$ t(3) = 1;
%$ catch
%$ t(3) = 0;
%$ end
%$ else
%$ t(3) = 1;
%$ end
%$
%$ % Standard
%$ options_.lyapunov_srs = 0;
%$ try
%$ Pstar4_small = lyapunov_solver(T_small,R_small,Q_small,options_);
%$ Pstar4_large = lyapunov_solver(T_large,R_large,Q_large,options_);
%$ t(4) = 1;
%$ catch
%$ t(4) = 0;
%$ end
%$
%$ % Test the results.
%$
%$ if max(max(abs(Pstar1_small-Pstar2_small)))>1e-8
%$ t(5) = 0;
%$ else
%$ t(5) = 1;
%$ end
%$
%$ if (isoctave && user_has_octave_forge_package('control')) || (~isoctave && user_has_matlab_license('control_toolbox'))
%$ if max(max(abs(Pstar1_small-Pstar3_small)))>1e-8
%$ t(6) = 0;
%$ else
%$ t(6) = 1;
%$ end
%$ else
%$ t(6) = 1;
%$ end
%$
%$ if max(max(abs(Pstar1_small-Pstar4_small)))>1e-8
%$ t(7) = 0;
%$ else
%$ t(7) = 1;
%$ end
%$
%$ if max(max(abs(Pstar1_large-Pstar2_large)))>1e-8
%$ t(8) = 0;
%$ else
%$ t(8) = 1;
%$ end
%$
%$ if (isoctave && user_has_octave_forge_package('control')) || (~isoctave && user_has_matlab_license('control_toolbox'))
%$ if max(max(abs(Pstar1_large-Pstar3_large)))>1e-8
%$ t(9) = 0;
%$ else
%$ t(9) = 1;
%$ end
%$ else
%$ t(9) = 1;
%$ end
%$
%$ if max(max(abs(Pstar1_large-Pstar4_large)))>1e-8
%$ t(10) = 0;
%$ else
%$ t(10) = 1;
%$ end
%$
%$ T = all(t);
%@eof:1

140
matlab/lyapunov_symm.m
View File

@ -1,4 +1,4 @@
function [x,u] = lyapunov_symm(a,b,lyapunov_fixed_point_tol,qz_criterium,lyapunov_complex_threshold,method, R, debug) % --*-- Unitary tests --*--
function [x,u] = lyapunov_symm(a,b,lyapunov_fixed_point_tol,qz_criterium,lyapunov_complex_threshold,method,debug) % --*-- Unitary tests --*--
% Solves the Lyapunov equation x-a*x*a' = b, for b and x symmetric matrices.
% If a has some unit roots, the function computes only the solution of the stable subsystem.
%
@ -20,12 +20,12 @@ function [x,u] = lyapunov_symm(a,b,lyapunov_fixed_point_tol,qz_criterium,lyapuno
%
% ALGORITHM
% Uses reordered Schur decomposition (Bartels-Stewart algorithm)
% [method<3] or a fixed point algorithm (method==4)
% [method<3] or a fixed point algorithm (method==3)
%
% SPECIAL REQUIREMENTS
% None
% Copyright (C) 2006-2014 Dynare Team
% Copyright (C) 2006-2016 Dynare Team
%
% This file is part of Dynare.
%
@ -46,7 +46,7 @@ if nargin<6 || isempty(method)
method = 0;
end
if nargin<8
if nargin<7
debug = 0;
end
@ -90,22 +90,7 @@ if method == 3
return;
end;
end;
elseif method == 4
% works only with Matlab System Control toolbox or octave the control package,
if isoctave
if ~user_has_octave_forge_package('control')
error('lyapunov=square_root_solver not available; you must install the control package from Octave Forge')
end
else
if ~user_has_matlab_license('control_toolbox')
error('lyapunov=square_root_solver not available; you must install the control system toolbox')
end
end
chol_b = R*chol(b,'lower');
Rx = dlyapchol(a,chol_b);
x = Rx' * Rx;
return;
end;
end
if method
persistent U T k n
@ -178,117 +163,4 @@ if i == 1
x(1,1) = (B(1,1)+c)/(1-T(1,1)*T(1,1));
end
x = U(:,k+1:end)*x*U(:,k+1:end)';
u = U(:,1:k);
%@test:1
%$ t = NaN(10,1);
%$ lyapunov_complex_threshold = 1e-15;
%$ qz_zero_threshold = 1e-6;
%$ qz_criterium=1-qz_zero_threshold;
%$ lyapunov_fixed_point_tol = 1e-10;
%$ lyapunov_doubling_tol = 1e-16;
%$
%$ n_small=8;
%$ m_small=10;
%$ T_small=randn(n_small,n_small);
%$ T_small=0.99*T_small/max(abs(eigs(T_small)));
%$ tmp2=randn(m_small,m_small);
%$ Q_small=tmp2*tmp2';
%$ R_small=randn(n_small,m_small);
%$
%$ n_large=9;
%$ m_large=11;
%$ T_large=randn(n_large,n_large);
%$ T_large=0.99*T_large/max(abs(eigs(T_large)));
%$ tmp2=randn(m_large,m_large);
%$ Q_large=tmp2*tmp2';
%$ R_large=randn(n_large,m_large);
%$
%$ % DynareOptions.lyapunov_fp == 1
%$ try
%$ Pstar1_small = lyapunov_symm(T_small,R_small*Q_small*R_small',lyapunov_fixed_point_tol,qz_criterium,lyapunov_complex_threshold,3, [], 0);
%$ Pstar1_large = lyapunov_symm(T_large,R_large*Q_large*R_large',lyapunov_fixed_point_tol,qz_criterium,lyapunov_complex_threshold,3, [], 0);
%$ t(1) = 1;
%$ catch
%$ t(1) = 0;
%$ end
%$
%$ % Dynareoptions.lyapunov_db == 1
%$ try
%$ Pstar2_small = disclyap_fast(T_small,R_small*Q_small*R_small',lyapunov_doubling_tol);
%$ Pstar2_large = disclyap_fast(T_large,R_large*Q_large*R_large',lyapunov_doubling_tol);
%$ t(2) = 1;
%$ catch
%$ t(2) = 0;
%$ end
%$
%$ % Dynareoptions.lyapunov_srs == 1
%$ if (isoctave && user_has_octave_forge_package('control')) || (~isoctave && user_has_matlab_license('control_toolbox'))
%$ try
%$ Pstar3_small = lyapunov_symm(T_small,Q_small,lyapunov_fixed_point_tol,qz_criterium,lyapunov_complex_threshold,4,R_small,0);
%$ Pstar3_large = lyapunov_symm(T_large,Q_large,lyapunov_fixed_point_tol,qz_criterium,lyapunov_complex_threshold,4,R_large,0);
%$ t(3) = 1;
%$ catch
%$ t(3) = 0;
%$ end
%$ else
%$ t(3) = 1;
%$ end
%$
%$ % Standard
%$ try
%$ Pstar4_small = lyapunov_symm(T_small,R_small*Q_small*R_small',lyapunov_fixed_point_tol,qz_criterium, lyapunov_complex_threshold, [], [], 0);
%$ Pstar4_large = lyapunov_symm(T_large,R_large*Q_large*R_large',lyapunov_fixed_point_tol,qz_criterium, lyapunov_complex_threshold, [], [], 0);
%$ t(4) = 1;
%$ catch
%$ t(4) = 0;
%$ end
%$
%$ % Test the results.
%$
%$ if max(max(abs(Pstar1_small-Pstar2_small)))>1e-8
%$ t(5) = 0;
%$ else
%$ t(5) = 1;
%$ end
%$
%$ if (isoctave && user_has_octave_forge_package('control')) || (~isoctave && user_has_matlab_license('control_toolbox'))
%$ if max(max(abs(Pstar1_small-Pstar3_small)))>1e-8
%$ t(6) = 0;
%$ else
%$ t(6) = 1;
%$ end
%$ else
%$ t(6) = 1;
%$ end
%$
%$ if max(max(abs(Pstar1_small-Pstar4_small)))>1e-8
%$ t(7) = 0;
%$ else
%$ t(7) = 1;
%$ end
%$
%$ if max(max(abs(Pstar1_large-Pstar2_large)))>1e-8
%$ t(8) = 0;
%$ else
%$ t(8) = 1;
%$ end
%$
%$ if (isoctave && user_has_octave_forge_package('control')) || (~isoctave && user_has_matlab_license('control_toolbox'))
%$ if max(max(abs(Pstar1_large-Pstar3_large)))>1e-8
%$ t(9) = 0;
%$ else
%$ t(9) = 1;
%$ end
%$ else
%$ t(9) = 1;
%$ end
%$
%$ if max(max(abs(Pstar1_large-Pstar4_large)))>1e-8
%$ t(10) = 0;
%$ else
%$ t(10) = 1;
%$ end
%$
%$ T = all(t);
%@eof:1
u = U(:,1:k);

2
matlab/non_linear_dsge_likelihood.m
View File

@ -306,7 +306,7 @@ ReducedForm.mf1 = mf1;
switch DynareOptions.particle.initialization
case 1% Initial state vector covariance is the ergodic variance associated to the first order Taylor-approximation of the model.
StateVectorMean = ReducedForm.constant(mf0);
StateVectorVariance = lyapunov_symm(ReducedForm.ghx(mf0,:),ReducedForm.ghu(mf0,:)*ReducedForm.Q*ReducedForm.ghu(mf0,:)',DynareOptions.lyapunov_fixed_point_tol,DynareOptions.qz_criterium,DynareOptions.lyapunov_complex_threshold,[],[],DynareOptions.debug);
StateVectorVariance = lyapunov_symm(ReducedForm.ghx(mf0,:),ReducedForm.ghu(mf0,:)*ReducedForm.Q*ReducedForm.ghu(mf0,:)',DynareOptions.lyapunov_fixed_point_tol,DynareOptions.qz_criterium,DynareOptions.lyapunov_complex_threshold,[],DynareOptions.debug);
case 2% Initial state vector covariance is a monte-carlo based estimate of the ergodic variance (consistent with a k-order Taylor-approximation of the model).
StateVectorMean = ReducedForm.constant(mf0);
old_DynareOptionsperiods = DynareOptions.periods;

23
matlab/partial_information/disclyap_fast.m
View File

@ -1,25 +1,25 @@
function [X,exitflag]=disclyap_fast(G,V,tol,ch)
function [X,exitflag]=disclyap_fast(G,V,tol,check_flag)
% function X=disclyap_fast(G,V,ch)
% Inputs:
% - G [double] first input matrix
% - V [double] second input matrix
% - tol [scalar] tolerance criterion
% - ch empty of non-empty if non-empty: check positive-definiteness
% - G [double] first input matrix
% - V [double] second input matrix
% - tol [scalar] tolerance criterion
% - check_flag empty of non-empty if non-empty: check positive-definiteness
% Outputs:
% - X [double] solution matrix
% - exitflag [scalar] 0 if solution is found, 1 otherwise
% - X [double] solution matrix
% - exitflag [scalar] 0 if solution is found, 1 otherwise
%
% Solve the discrete Lyapunov Equation
% X=G*X*G'+V
% Using the Doubling Algorithm
%
% If ch is defined then the code will check if the resulting X
% If check_flag is defined then the code will check if the resulting X
% is positive definite and generate an error message if it is not
%
% Joe Pearlman and Alejandro Justiniano
% 3/5/2005
% Copyright (C) 2010-2015 Dynare Team
% Copyright (C) 2010-2016 Dynare Team
%
% This file is part of Dynare.
%
@ -36,16 +36,13 @@ function [X,exitflag]=disclyap_fast(G,V,tol,ch)
% You should have received a copy of the GNU General Public License
% along with Dynare. If not, see <http://www.gnu.org/licenses/>.
if nargin <= 3 || isempty( ch ) == 1
if nargin <= 3 || isempty( check_flag ) == 1
flag_ch = 0;
else
flag_ch = 1;
end
s=size(G,1);
exitflag=0;
%tol = 1e-16;
P0=V;
A0=G;

6
matlab/th_autocovariances.m
View File

@ -129,7 +129,7 @@ end;
% and compute 2nd order mean correction on stationary variables (in case of
% HP filtering, this mean correction is computed *before* filtering)
if options_.order == 2 || options_.hp_filter == 0
[vx, u] = lyapunov_symm(A,B*M_.Sigma_e*B',options_.lyapunov_fixed_point_tol,options_.qz_criterium,options_.lyapunov_complex_threshold,[],[],options_.debug);
[vx, u] = lyapunov_symm(A,B*M_.Sigma_e*B',options_.lyapunov_fixed_point_tol,options_.qz_criterium,options_.lyapunov_complex_threshold,[],options_.debug);
if options_.block == 0
iky = inv_order_var(ivar);
else
@ -188,11 +188,11 @@ if options_.hp_filter == 0 && ~options_.bandpass.indicator
b1 = b1*cs;
b2(:,exo_names_orig_ord) = ghu(iky,:);
b2 = b2*cs;
vx = lyapunov_symm(A,b1*b1',options_.lyapunov_fixed_point_tol,options_.qz_criterium,options_.lyapunov_complex_threshold,1,[],options_.debug);
vx = lyapunov_symm(A,b1*b1',options_.lyapunov_fixed_point_tol,options_.qz_criterium,options_.lyapunov_complex_threshold,1,options_.debug);
vv = diag(aa*vx*aa'+b2*b2');
vv2 = 0;
for i=1:M_.exo_nbr
vx1 = lyapunov_symm(A,b1(:,i)*b1(:,i)',options_.lyapunov_fixed_point_tol,options_.qz_criterium,options_.lyapunov_complex_threshold,2,[],options_.debug);
vx1 = lyapunov_symm(A,b1(:,i)*b1(:,i)',options_.lyapunov_fixed_point_tol,options_.qz_criterium,options_.lyapunov_complex_threshold,2,options_.debug);
vx2 = abs(diag(aa*vx1*aa'+b2(:,i)*b2(:,i)'));
Gamma_y{nar+2}(stationary_vars,i) = vx2;
vv2 = vv2 +vx2;

2
matlab/thet2tau.m
View File

@ -55,7 +55,7 @@ elseif flagmoments==-1
tau=[oo_.dr.ys(oo_.dr.order_var); g1(:)];
else
GAM = lyapunov_symm(A,B*M_.Sigma_e*B',options_.lyapunov_fixed_point_tol,options_.qz_criterium,options_.lyapunov_complex_threshold,[],[],options_.debug);
GAM = lyapunov_symm(A,B*M_.Sigma_e*B',options_.lyapunov_fixed_point_tol,options_.qz_criterium,options_.lyapunov_complex_threshold,[],options_.debug);
k = find(abs(GAM) < 1e-12);
GAM(k) = 0;
if useautocorr,