function [Pstar,Pinf] = compute_Pinf_Pstar(mf,T,R,Q,qz_criterium, restrict_columns)
% function [Z,ST,QT,R1,Pstar,Pinf] = schur_statespace_transformation(mf,T,R,Q,qz_criterium, restrict_columns)
% Kitagawa transformation of state space system with a quasi-triangular
% transition matrix with unit roots at the top, but excluding zero columns of the transition matrix.
% Computation of Pstar and Pinf for Durbin and Koopman Diffuse filter
%
% The transformed state space is
%     y = [ss; z; x];
%     s = static variables (zero columns of T)
%     z = unit roots
%     x = stable roots
%     ss = s - z = stationarized static variables
%
% INPUTS
%   mf           [integer]    vector of indices of observed variables in
%                             state vector
%   T            [double]     matrix of transition
%   R            [double]     matrix of structural shock effects
%   Q            [double]     matrix of covariance of structural shocks
%   qz_criterium [double]     numerical criterium for unit roots
%
% OUTPUTS
%   Pstar        [double]     matrix of covariance of stationary part
%   Pinf         [double]     matrix of covariance initialization for
%                             nonstationary part
%
% ALGORITHM
%   Real Schur transformation of transition equation
%
% SPECIAL REQUIREMENTS
%   None

% Copyright (C) 2006-2017 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/>.

np = size(T,1);

% perform Kitagawa transformation
[QT,ST] = schur(T);
e1 = abs(ordeig(ST)) > 2-qz_criterium;
[QT,ST] = ordschur(QT,ST,e1);
k = find(abs(ordeig(ST)) > 2-qz_criterium);
nk = length(k);
nk1 = nk+1;
Pstar = zeros(np,np);
R1 = QT'*R;
B = R1*Q*R1';
% computes variance of stationary block (lower right)
i = np;
while i >= nk+2
    if ST(i,i-1) == 0
        if i == np
            c = zeros(np-nk,1);
        else
            c = ST(nk1:i,:)*(Pstar(:,i+1:end)*ST(i,i+1:end)')+...
                ST(i,i)*ST(nk1:i,i+1:end)*Pstar(i+1:end,i);
        end
        q = eye(i-nk)-ST(nk1:i,nk1:i)*ST(i,i);
        Pstar(nk1:i,i) = q\(B(nk1:i,i)+c);
        Pstar(i,nk1:i-1) = Pstar(nk1:i-1,i)';
        i = i - 1;
    else
        if i == np
            c = zeros(np-nk,1);
            c1 = zeros(np-nk,1);
        else
            c = ST(nk1:i,:)*(Pstar(:,i+1:end)*ST(i,i+1:end)')+...
                ST(i,i)*ST(nk1:i,i+1:end)*Pstar(i+1:end,i)+...
                ST(i,i-1)*ST(nk1:i,i+1:end)*Pstar(i+1:end,i-1);
            c1 = ST(nk1:i,:)*(Pstar(:,i+1:end)*ST(i-1,i+1:end)')+...
                 ST(i-1,i-1)*ST(nk1:i,i+1:end)*Pstar(i+1:end,i-1)+...
                 ST(i-1,i)*ST(nk1:i,i+1:end)*Pstar(i+1:end,i);
        end
        q = [eye(i-nk)-ST(nk1:i,nk1:i)*ST(i,i) -ST(nk1:i,nk1:i)*ST(i,i-1);...
             -ST(nk1:i,nk1:i)*ST(i-1,i) eye(i-nk)-ST(nk1:i,nk1:i)*ST(i-1,i-1)];
        z =  q\[B(nk1:i,i)+c;B(nk1:i,i-1)+c1];
        Pstar(nk1:i,i) = z(1:(i-nk));
        Pstar(nk1:i,i-1) = z(i-nk+1:end);
        Pstar(i,nk1:i-1) = Pstar(nk1:i-1,i)';
        Pstar(i-1,nk1:i-2) = Pstar(nk1:i-2,i-1)';
        i = i - 2;
    end
end
if i == nk+1
    c = ST(nk+1,:)*(Pstar(:,nk+2:end)*ST(nk1,nk+2:end)')+ST(nk1,nk1)*ST(nk1,nk+2:end)*Pstar(nk+2:end,nk1);
    Pstar(nk1,nk1)=(B(nk1,nk1)+c)/(1-ST(nk1,nk1)*ST(nk1,nk1));
end

% stochastic trends with no influence on observed variables are
% arbitrarily initialized to zero
Pinf = zeros(np,np);
Pinf(1:nk,1:nk) = eye(nk);
for k = 1:nk
    if norm(QT(mf,:)*ST(:,k)) < 1e-8
        Pinf(k,k) = 0;
    end
end

Pinf = QT*Pinf*QT';
Pstar = QT*Pstar*QT';