function [Z,ST,R1,QT,Pstar,Pinf] = schur_statespace_transformation(mf,T,R,Q,qz_criterium) % function [Z,ST,QT,R1,Pstar,Pinf] = schur_statespace(mf,T,R,Q,qz_criterium) % Kitagawa transformation of state space system with a quasi-triangular % transition matrix with unit roots at the top. Computation of Pstar and % Pinf for Durbin and Koopman Diffuse filter % % 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 % Z [double] transformed matrix of measurement equation % ST [double] tranformed matrix of transition % R1 [double] tranformed matrix of structural shock effects % QT [double] matrix of Schur vectors % 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) 2006-2011 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 . np = size(T,1); [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); B = QT'*R*Q*R'*QT; 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 Z = QT(mf,:); R1 = QT'*R; % stochastic trends with no influence on observed variables are % arbitrarily initialized to zero Pinf = zeros(np,np); Pinf(1:nk,1:nk) = eye(nk); [QQ,RR,EE] = qr(Z*ST(:,1:nk),0); k = find(abs(diag([RR; zeros(nk-size(Z,1),size(RR,2))])) < 1e-8); if length(k) > 0 k1 = EE(:,k); dd =ones(nk,1); dd(k1) = zeros(length(k1),1); Pinf(1:nk,1:nk) = diag(dd); end