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Highlights from
Solution to Linear Rational Expectations Models

from Solution to Linear Rational Expectations Models by Pawel Kowal
Solves linear rational expectation models, delivers derivatives of solutions

gschur(A,B,COND);
function [U,V,TA,TB,AR,AI,BETA] = gschur(A,B,COND);
%  PURPOSE: returns ordered generalized Schur decomposition of a matrix pair (A,B)
%           
% ---------------------------------------------------
%  USAGE: [U,V,TA,TB,AR,AI,BETA] = gschur(A,B,COND);
%  where: 
%         A,B               nxn matrices 
%         COND              7x1 matrix determining an ordering rule
%                           or 0 if no ordering
%
%         U,V,TA,TB         generalized real  schur decomposition
%
%                               A = U' TA V
%                               B = U' TB V
%
%         AR,AI,BETA        real vectors describing eigenvalues
%
%                               lambda[k] = (AR[k]+i AI[k])./BETA[k]
%
%                           additionally BETA[k]>=0
%                           left-upper block contains eigenvalues satisfying 
%
%                               COND(1)*AR^2+COND(2)*AI^2+COND(3)*BETA^2 + 
%                               COND(4)*AR  +COND(5)*AI  +COND(6)*BETA   +
%                               COND(7) > 0
%
%                           This allows to consider the most standar
%                           orderings: 1) real(lambda)>m, 2) real(lambda)<m,
%                           3) abs(lambda)>m, 4) abs(lambda)<m
%
%   COMMENTS:
%       mex file, gschur.dll is required
%       based on Lapack dgges routine
%
% Copyright  (c) Pawel Kowal (2006)
% All rights reserved
% LREM_SOLVE toolbox is available free for noncommercial academic use only.
% pkowal3@sgh.waw.pl

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